DELIVERABLE D9 Compact Low Emission Vehicle ...

DELIVERABLE D9 Benefits for urban traffic Status: final

Compact Low Emission Vehicle for Urban Transport Contract No G3RD-CT-2002-00815

PROJECT START DATE:

01.12.2002

DURATION:

36 MONTHS

DATE OF ISSUE OF THIS REPORT:

30.09.2005

Project funded by the European Commission under the ‘Competitive and Sustainable Growth’ Programme of the Fifth Framework Programme

CLEVER Compact Low Emission Vehicle for Urban Transport Deliverable D9 Benefits for urban traffic

CLEVER CONSORTIUM PROJECT CO-ORDINATORS: Administrative Co-ordinator: Technical University of Berlin, Institut fuer Land- und Seeverkehr (TUB), Berlin (D) Scientific Co-ordinator: BMW Bayerische Motoren Werke AG (BMW), Munich (D) PROJECT PARTNERS: Technical University of Berlin, Institut fuer Land- und Seeverkehr (TUB), Berlin (D) BMW Bayerische Motoren Werke AG (BMW), Munich (D) Cooper Avon Tyres (UK) ARC Leichtmetall Kompetenzzentrum Ranshofen GmbH (LKR), Ranshofen (A) Institut Français du Pétrole (IFP), Vernaison (F) Takata-Petri AG (TP), Berlin (D) University of Bath, Department of Mechanical Engineering (UBAH.MECH), Bath (UK) University for Bodenkultur Vienna, Institute for Transport Studies (BOKU-ITS), Vienna (A) WEH GmbH (WEH), Illertissen (D)

DOCUMENT PRODUCED BY: BOKU-ITS (A) – S. Hanzl, A. Neumann, J. Stark, G. Sammer

In Co-operation with: TUB (D) – H. Johannsen, L. Lasek, V. Schindler BMW (D) – P. Krams TRIAS S.A. (GR) – M. Peleka, P. Papaioannou

QUALITY CONTROL: UBAH.MECH (UK)

The Commission of the European Commission has financed 66 % of this research work within the Fifth Framework Programme.

Benefits for urban traffic – D9: October 2005

CLEVER

TABLE OF CONTENTS 1

INTRODUCTION ............................................................................... 5

1.1

Background .................................................................................................. 5

1.1.1

The Problem .................................................................................................. 5

1.1.2

Objectives and Aims of CLEVER ................................................................... 5

1.2

Project Methodology ................................................................................... 6

1.3

Objective of D9 ............................................................................................. 9

1.4

Structure of D9 ............................................................................................. 9

2

THE CLEVER CONCEPT ............................................................... 10

3

METHODOLOGY ............................................................................ 13

3.1

Research Flow............................................................................................ 13

3.2

Selection of the Case Study Cities ........................................................... 14

3.3

Survey Method ........................................................................................... 14

3.3.1

Revealed Preference Survey ....................................................................... 15

3.3.2

Stated Preference Survey ............................................................................ 15

3.4

Sampling, Gross and Net Sample............................................................. 16

3.4.1

Revealed Preference Survey ....................................................................... 16

3.4.2

Stated Preference Survey ............................................................................ 17

3.5

Data Checks, Quality Control and Weighting .......................................... 18

3.5.1

Data Checks and Quality Control ................................................................. 18

3.5.2

Weighting and Grossing Up ......................................................................... 19

3.6

General Data Analysis ............................................................................... 21

3.7

Evaluation of Effects and Impacts............................................................ 21

4

CASE STUDY CITIES..................................................................... 22

4.1

Graz / Austria ............................................................................................. 22

4.1.1

General Characteristics ............................................................................... 22

4.1.2

Transport Infrastructure and Organisation ................................................... 22

4.2

Greater Thessaloniki Area/ Greece .......................................................... 24

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4.2.1

General Characteristics ............................................................................... 24

4.2.2

Transport Infrastructure and Organisation ................................................... 25

5

MEASURES AND SCENARIOS ..................................................... 27

5.1

Possible Measures to Support CLEVER .................................................. 27

5.1.1

Infrastructure & Organisational Measures .................................................... 27

5.1.2

Information & Awareness Measures ............................................................ 28

5.1.3

Accompanying Measures ............................................................................. 29

5.1.4

Restrictions and Impacts for “Non-CLEVER” Vehicles ................................. 29

5.2

Scenarios for the SP Survey ..................................................................... 30

5.2.1

SCENARIO A ............................................................................................... 30

5.2.2

SCENARIO B ............................................................................................... 31

5.2.3

SCENARIO C............................................................................................... 32

6

CONFIDENCE INTERVALS AND RANDOM ERROR ................... 34

7

TRAVEL BEHAVIOUR AND USER REQUIREMENTS .................. 37

7.1

CLEVER Assessment and User Requirements ....................................... 37

7.2

Mode Choice in the Scenarios .................................................................. 40

7.2.1

Mode Shift – Relative Values ....................................................................... 41

7.2.2

Mode Shift – Absolute Values ...................................................................... 46

7.2.3

Reasons for the Mode Choice...................................................................... 49

7.2.4

Influencing Factors on the Mode Choice ...................................................... 51

7.3

Market Potential of CLEVER ..................................................................... 63

7.4

Comparison Graz – Thessaloniki ............................................................. 66

8

BENEFITS FOR URBAN TRAFFIC ................................................ 68

8.1

Hazardous Air Pollutants and CO2-Emissions ........................................ 69

8.1.1

Basics for the Calculation ............................................................................ 69

8.1.2

Results ......................................................................................................... 74

8.1.3

Costs............................................................................................................ 77

8.2

Fuel consumption and running costs ...................................................... 79

8.2.1


8.2.2

Results ......................................................................................................... 80 Page - 2 -


CLEVER

8.2.3

Costs............................................................................................................ 84

8.3

Noise ........................................................................................................... 90

8.3.1


8.3.2

Results ......................................................................................................... 91

8.3.3

Costs............................................................................................................ 92

8.4

Road accidents .......................................................................................... 93

8.4.1


8.4.2

Results ......................................................................................................... 97

8.4.3

Costs.......................................................................................................... 101

8.5

Journey time............................................................................................. 103

8.5.1

Basics for the Calculation .......................................................................... 103

8.5.2

Results ....................................................................................................... 103

8.5.3

Costs.......................................................................................................... 108

8.6

Parking infrastructure ............................................................................. 109

8.6.1

Basics for the Calculation .......................................................................... 109

8.6.2

Results ....................................................................................................... 111

8.6.3

Costs.......................................................................................................... 113

8.7

Welfare Losses......................................................................................... 114

8.8

Summary of the Cost Benefit Analysis .................................................. 115

9

POLICY MAKERS’ ATTITUDE TOWARDS CLEVER.................. 121

9.1

Methodical Approach .............................................................................. 121

9.1.1

Sample Selection and Interview Procedure ............................................... 121

9.1.2

Questionnaire............................................................................................. 122

9.2

Sample ...................................................................................................... 123

9.2.1

Overall Figures........................................................................................... 123

9.2.2

Specification of the Persons (Functions and Authorities) ........................... 124

9.3

Results ...................................................................................................... 125

9.3.1

Transport and Environmental Problems and Politics ................................. 125

9.3.2

Presentation of the CLEVER-Vehicle and Assessment ............................. 126

9.3.3

Presentation of the Results of the Household Survey ................................ 128

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9.3.4

Feasibility of Measures Favouring the Use of CLEVER ............................. 128

9.4

Summary of Interviews with Policy Makers ........................................... 130

10 CONCLUSIONS ............................................................................ 133 11 GLOSSARY AND ABBREVIATIONS ........................................... 135 12 LIST OF FIGURES ....................................................................... 136 13 LIST OF TABLES ......................................................................... 140 14 BIBLIOGRAPHY AND REFERENCES ........................................ 146 15 ANNEX 1 – QUESTIONNAIR OF THE DAILY MOBILITY SURVEY ....................................................................................... 150 16 ANNEX 2 – INTERVIEW GUIDELINES OF THE IN-DEPTH SURVEY ....................................................................................... 153 17 ANNEX 3 – INFO SHEETS OF THE IN-DEPTH SURVEY ........... 185

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1

CLEVER

INTRODUCTION

1.1 Background 1.1.1 The Problem With the constantly increasing need for mobility, in particular in urban areas, various problems arise. In this context the consumption of urban space and energy, and exhaust and noise emissions have to be mentioned. In order to be able to satisfy the mobility needs in the future, solutions are required that are able to solve these problems. One possibility is to develop new concepts for individual urban transport to close the gap between conventional individual transport and public transport. Due to the increasing readiness of customers for the acquisition of second or third vehicles, there might be a market for new innovative vehicles for urban transport. 1.1.2 Objectives and Aims of CLEVER The objective of the project “Compact Low Emission Vehicle for Urban Transport” (CLEVER) is the development of a small vehicle for clean urban transport with minimal requirements on urban space, both in traffic and parking, as well as low energy consumption and low exhaust and noise emissions. To improve the usage of alternative energies for the propulsion of vehicles, the development of a new storage and refuelling technology is to be developed. The safety of the new vehicle must be comparable with high-end micro cars. The project aims at improving urban transport and the negative environmental impacts from increased mobility. Technical and scientific objectives and innovative aspects of the new vehicle:

Room for two seats and luggage (or 1 + 1 and luggage), full-lining for occupant protection and protection against rain, appropriate heating and air-conditioning, low requirements with respect to road and parking space (w < 0,8 m, l < 2,5 m).

CO2 emissions < 50 g/km, super-low emission propulsion (10 % Euro IV), possibility for refuelling at home, possibility of using different propulsion systems with different energy supplies within the same package (e.g. hydrogen).

High level of pedestrian protection, high level of compatibility, high level of occupant protection.

Protection against tilting at low velocities, easy manoeuvring, stable driveability at high velocities, low sensitivity against side winds, car like handling at low speed.

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CLEVER

The main project output will be represented by

the technical specification for the vehicle (Deliverable 2),

the refuelling technology with exchangeable gas bottles (Deliverable 5),

the safety concept for small vehicles (Deliverable 3),

the prototype of the vehicle (Deliverable 10) and

a proposal for the adoption of European legal framework concerning technical and traffic organisational aspects (Deliverable 11).

The results of the research project will have impacts on the European standardisation (e.g. vehicle concept and refuelling technology). Solving urban transport problems by decreasing energy consumption and emissions will help to support sustainable transport growth.

1.2 Project Methodology The improvement of individual urban transport in Europe through the development of a new vehicle concept requires co-operation between technical and transport organisational science to obtain the required wide acceptance for the vehicle. In order to guarantee the achievement of project objectives for the target groups (vehicle manufacturers and their suppliers, vehicle users, European citizens), a thorough analysis considering all relevant fields of influence (e.g. safety for occupants and partners, high comfort, agility, legal framework concerning technical as well as transport organisational topics, anticipated future technologies for vehicle concept and vehicle components like body panel and low weight windscreens) was conducted at the project’s commencement. The result of the analysis phase is a technical product guideline, which comprises the entire range of demands from all fields of scientific knowledge. This serves as system specifications required for the design and development phase that follows. From the very beginning, the development of the vehicle is supported by digital models and numerical simulation. This leads to an early prediction of the feasibility of the concept (and the different solutions for the components) combined with minimal development costs and prototype testing. The development of the vehicle is divided into task packages: styling, safety concept, frame, body panel, propulsion system, transmission, chassis as well as construction of prototypes and vehicle testing. Due to interactions between styling, package and passive safety, these parts are combined into one work package. Frame and body panel is combined into one work package; also propulsion, transmission and chassis. This ensures an optimised and co-ordinated project approach.

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CLEVER

The final result of the technical work is to build one vehicle with full function, and additional prototypes for testing of different vehicle functions (e.g. passive safety). The technical project approach is accompanied by investigating impacts the new vehicle concept might have on urban transport. Predicted impacts are based on a survey of potential vehicle users in two cities from different countries in Europe. Based on the technical and traffic organisational results of the project, proposals for the adoption of legal framework are envisaged. Scientific and Technical Work Plan In the sense of a logical and manageable structure, the project is divided into six work packages (Figure 1-1). Work package 1 (“Definition of CLEVER”) covers all analysis and specification steps required for developing a small, environmentally friendly vehicle, which is based on the state of the art as well as legal and user requirements. The main target of WP1 is the preparation of a technical product guideline that will be the specification input for the styling and package, the safety concept, the propulsion and chassis as well as testing. The aim of work package 2 (“Benefits for urban traffic”) is to develop infrastructure and organisational measures that are able to favour the new vehicle in urban areas, as well as the investigation of the policy makers’ willingness to support the new vehicle. Based on the user requirements from the previous work package the market potential in two European cities is calculated. This will lead to an analysis of the benefits for urban traffic (e.g. improvements of the capacity of road space in urban areas) and environmental impacts. In work package 3 (“Package concept, styling and passive safety”) the vehicle styling and package is defined. As both are strongly interrelated with pedestrian and occupant safety, safety are investigated concurrently. The definition of the safety concept results from the investigation of the accident situation of comparable vehicles (e.g. micro cars and scooters). Work package 4 (“Vehicle and cabin”) is focused on the design and construction of the vehicle frame and body panels. Due to the requirements for energy consumption, lightweight materials is used, following lightweight design rules. As a result the vehicle has an aluminium frame and plastic body panels. The results from the state of the art review and the styling, package and safety concept are considered. The study, definition and implementation of the power train, rear chassis, tilt mechanism and suspension takes place in work package 5 (“Propulsion, chassis and tilt mechanism”). This includes the definition of the propulsion system with the engine, energy storage, and refuelling technology.

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CLEVER

The objective of work package 6 (“Integration and evaluation”) is the assembly of prototypes and the evaluation of vehicle characteristics. Definition of recommendations for adaptation of the legal framework to support the project results is also part of this work package. After proof of the required attributes of the vehicle and its components, assembly and test of prototypes takes place.

Project Structure Plan CLEVER WP 1

WP 2

Definition of CLEVER

Benefits for urban traffic

1.1

2.1

State of the art

1.2

Infrastructure and/or organisational measures

Propulsion, chassis and tilt mechanism

WP 6 Integration and validation

3.1

4.1

5.1

6.1

Styling

Scenarios for case studies

1.3

2.3

User requirements

1.4

Conception and conducting of the stated preferences survey

2.4

Technical product guidelines

3.3

3.4

Evaluation, market potential and requirements

4.2

Accident investigation and definition of safety concept

Restraint system development

3.5

Attitude survey of policy makers

4.3

Design of vehicle and cabin

Compatibility

Definition of propulsion system

Numerical simulation

5.2

Fuel storage and refuelling technology

6.2

5.3

Development and design of propulsion system

6.3

Body panels

5.4

6.4

Powertrain design

5.5

Concept development of complete chassis including steering

5.6

Design and manufacture of chassis

Pedestrian protection

3.6

2.6

Vehicle frame

Package

Data analysis

2.5

Figure 1-1:

WP 4 Vehicle and cabin

3.2

2.2

Legal conditions

WP 5

WP 3 Package, styling and passive safety

6.5

Test of components

Assembly of prototypes

Test of prototypes

Required legal frameworks and realization strategies

CLEVER Project Structure Plan

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CLEVER

1.3 Objective of D9 The objective of D9 is to summarise the results of WP2, which encompasses the development of scenarios, based on a bundle of measures favouring CLEVER in urban areas, the preparation and conduction of a two-stage mobility survey investigating the mobility behaviour and the potential of CLEVER in two European case study cities, an analysis of the benefits for urban traffic and the environment and an investigation of policy makers’ willingness to support CLEVER. The main focus is on the investigation of the market potential of the CLEVER vehicle and on the effects of its use for the urban traffic and the environment. Interaction with other work packages The benefits for urban traffic (D9) are based on the user requirements of WP1 and on the vehicle concept developed in WP3, which is necessary for the development of measures and scenarios.

1.4 Structure of D9 The general introduction presents the background of the CLEVER project and the project methodology, whereas in chapter 2 ‘Methodology’ the approach of WP2, the process of the investigation and analysis is addressed. Chapter 3 to chapter 5 comprise all relevant information, necessary for the CLEVER survey. The CLEVER concept is outlined and the two European case study cities are described. Measures supporting CLEVER in urban areas are reflected and combined to scenarios, which provide the basis for the mode choice in the in-depth survey. The chapters ‘Traveller behaviour and user requirements’ (chapter 6) and the ‘Benefits for urban traffic’ (Chapter 7) build up the main parts of D9. Chapter 6 deals with the change in mobility behaviour, resulting in the mode shift, regards influencing factors (socioeconomic as well as trip related ones) on the mode choice and includes an assessment of CLEVER and its market potential. Chapter 7 comprises the results of the Cost Benefit Analysis of both case study cities, detecting the benefits for urban traffic by the use of CLEVER. The results of interviews with policy makers, investigating their willingness to support the new vehicle, are presented in chapter 8. The ‘Conclusions’ identify the main findings of the investigation, emphasising the market potential of the new vehicle and its benefits for urban traffic and especially for the environment.

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CLEVER

2 THE CLEVER CONCEPT The tilting three-wheeled CLEVER offers room for two occupants sitting in a tandem arrangement (Figure 2-2). The external dimensions are 3 m length, 1 m width and 1,4 m height. The aluminium space frame cabin together with the full lining protects the occupants against weather conditions and offers a suitable passenger compartment stiff enough to withstand normal accident conditions (Figure 2-1).

Figure 2-1:

Front side of the three-wheeled CLEVER

Figure 2-2:

Interior of CLEVER – offering room for two occupants

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CLEVER

Due to the compressed natural gas (CNG) engine the energy consumption is less than 2,4 l gasoline equivalent per 100 km. A special refuelling system allows to use CLEVER in areas with insufficient natural gas infrastructure. CLEVER CNG Engine The designated 213 cc one cylinder CNG engine, accelerates the CLEVER vehicle to 60 km/h in less than 7 s. Due to a special light-off catalyst, stoichiometric air-fuel mixture over the entire load and speed range and low row emissions very low emissions are expected. The CO2 emissions will be less than 60 g/km. A maximum speed of 100 km/h can be reached, which guarantees the permission to be used on motorways. The driving range is approximately 160 km with the full gas cylinders. CLEVER Refuelling System CLEVER is equipped with two removable gas cylinders with a capacity of 2 x 6 l CNG (Figure 2-3). To facilitate the use of CLEVER in regions with poor CNG infrastructure they can be external refilled after removal from CLEVER. It is possible to exchange the cylinders e.g. at normal gas stations. However the central conventional refuelling of both cylinders at natural gas filling stations without removal is possible too.

Figure 2-3:

CLEVER CNG engine and refuelling system at the back of the vehicle

CLEVER Tilting Mechanism Due to the narrow track of the CLEVER vehicle, a tilting chassis is necessary to maintain stability in corners (Figure 2-4). An efficient hydraulic system is employed to tilt the vehicle towards the centre of the corner. This is automatically controlled based

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CLEVER

on the driver’s input by an active direct tilt control system. This system also allows for car-like controls and has the advantage of keeping the vehicle upright while stationary.

Figure 2-4:

CLEVER tilting mechanism

CLEVER Safety The main aim is at least a 3 star rating in an EuroNCAP equivalent test procedure. The designated energy absorbing structure keeps the maximum cabin acceleration below 55 g. CLEVER has a two-chamber driver air bag and a belt system with pretensioner and a dual stage load limiter. Due to the stiff side structure of the cabin and the low vehicle weight, the intrusion can be limited with an expected intrusion velocity to be less than 8 m/s at a maximum crush of 125 mm. CLEVER Use and Costs CLEVER is designed to be primarily used in urban areas for relatively short trips with the option to be used on motorways as well. Due to its small size advantages in parking can be gained. Its low emissions are a reasonable argument for promoting the vehicle and supporting measures. The purchase costs are about € 9.000,–. The running costs are due to the low fuel consumption and CNG costs estimated to be half of a conventional car. The driver of a CLEVER has to hold a driving licence B. The overall aim of CLEVER is the substitution of car trips by CLEVER trips to achieve a reduction of CO2 emissions and emissions of hazardous air pollutants satisfying at the same time individual mobility needs.

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CLEVER

3 METHODOLOGY 3.1 Research Flow

Scenarios

Preparation and conduction of the RP survey (postal household survey)

Preparation and conduction of the SP survey (in-depth interactive interviews)

Coding, plausibility checks, weighting Mode shift to CLEVER according to scenarios Assessment of CLEVER, reasons for choice

CLEVER market potential Cost Benefit Analysis

Figure 3-1:

Survey

Case study cities

Data Analysis

Measures suppoting CLEVER

Results

CLEVER concept

Framework

The evaluation of the market potential of CLEVER and its benefits for urban traffic and for the environment is carried out in a stepwise approach (Figure 3-1). The frame is set by the CLEVER concept, according to which measures that could support the use of CLEVER in urban areas are identified. Out of these measures scenarios are developed, which are applicable in the selected case study cities. A two stage mobility survey made up of a revealed preference survey (RP) and a stated preference survey (SP) is carried out in the case study cities to collect necessary data concerning the behaviour and mode choice related to the use of CLEVER. Data are coded, checked for their plausibility and weighted before they are analysed in view of a mode shift towards CLEVER according to the scenarios and the reasons for the choice/non-choice of CLEVER.

CLEVER research flow

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CLEVER

Based on the mode shift the potential use of CLEVER is estimated as well as the effects and impacts on urban traffic and the environment, which is done by means of a cost benefit analysis (CBA). Referring to those results policy makers of the case study cities and some other European cities were interviewed concerning their willingness to support measures favouring the new vehicle in urban areas to look at the feasibility of the CLEVER concept in urban traffic.

3.2 Selection of the Case Study Cities The specification for the selection of the case study cities for the investigation of the potential of the CLEVER vehicle are relatively widely set: two European cities covering different cultural regions and different climate zones (such as continental or maritime) have to be selected. The intention to have two cities from different parts of Europe is to get to know if the market for the CLEVER vehicle is different e.g. in a city in the south from one in the middle of Europe. Cultural habits and customs, differences in mobility behaviour and socio-economic factors may have an influence on the choice and use of CLEVER. Furthermore different requirements on the vehicle may appear due to climatic diversities. The feasibility of measures favouring CLEVER in urban areas is related to the administrative and political conditions in the respective city or country and may arise in different attitudes of policy makers and their willingness to support CLEVER. The selected cities should be medium sized (around 300.000 inhabitants) and suffer from more or less traffic respectively environmental problems, which are assumed to be relieved by the use of CLEVER. A relatively high share of car driver trips in the cities’ modal split may be favourable as particularly the mode shift from car traffic towards CLEVER is wished. A more practical argument is that socio-economic as well as transport and environmental related data have to be available. The use of CNG (compressed natural gas) in transport is not a precondition for the selection of a city. Finally the city of Graz in Austria has been chosen as a representative of the middle of Europe and Thessaloniki respectively the Greater Thessaloniki Area in Greece for the south (chapter 4).

3.3 Survey Method A two-stage mobility survey was conducted in both case study cities to gain information and data for the estimation of the market potential of CLEVER and the assessment of the benefits of its use. At first a revealed preference survey (RP) was carried out by means of a postal household survey to collect basic mobility behaviour data of a normal working day as well as mobility behaviour influencing key factors of potential CLEVER users. In a second step a stated preference survey (SP) is conducted. The hypothetical use of CLEVER was tested in in-depth interactive

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CLEVER

interviews on the basis of the defined scenarios. The objective is to investigate potential changes in mobility behaviour. 3.3.1 Revealed Preference Survey The aim of a revealed preference survey is to examine the real behaviour of persons examined on the basis of a past situation. In this case the actual mobility behaviour on a reporting day considering mode choice, trip destination, trip purpose etc. was surveyed. In a postal household survey questionnaires (household/person and individual trip questionnaires) were sent to randomly selected households. A reminder procedure (postal and by phone) guaranteed a satisfactory response rate. 3.3.2 Stated Preference Survey In a stated preference survey the hypothetical behaviour of the interviewees is asked on the basis of given modified conditions. The objective is to test for example the potential of a new product or to examine the willingness to pay for a non-market good. In the CLEVER project the market potential of CLEVER is assessed not only by personal ratings of the respondents but by means of their mode choice under scenario conditions. Based on the trips done and reported in the RP survey, the mode choice in the three scenarios is resumed, whereas different advantages concerning travel time and costs arise depending on the scenario and on the mode (car driver, car passenger, public transport, moped/motorcycle, bicycle) from which the shift towards CLEVER appears (compare chapter 5.2). As the survey is done by means of face-to-face interviews in the households of the interviewees the role of the interviewer is a very important one. Before the start of the SP survey the interviewers are trained to get familiar with the procedure of the interview and with the several questionnaires and information sheets and to be sufficiently ready for any kind of questions of the interviewees. The interviewer has to prepare the questionnaires for the interviews, filling in existing trip information from the RP survey as a reminder in each trip questionnaire and precoding the trip characteristics (travel time and costs with the originally chosen mode and with CLEVER) in the scenario questionnaires due to a defined estimation. During the interview the interviewer has a neutral position concerning the CLEVER vehicle. His/her task is to ensure a smooth run of the interview and to give support to the interviewees in case of ambiguities and to explore specific reasons and changed behaviour if it is realistic. The interview was conducted in several steps (Figure 3-2), at which all the household members aged 16 or older and having done a trip on the reporting day should be present. At first the availability of vehicles in the household and of modes of transport is discussed among the participating household members. Then each participant fills

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CLEVER

in the trip questionnaires resuming the reported trips of the RP survey and answering more detailed questions about reasons for the mode choice, experiences with other modes etc. Following the interviewer presents the CLEVER vehicle (pictures and characteristics) to the respondents, who get the task to assess and form their opinion about the vehicle and its use. After that the different scenarios are presented by the interviewer. According to them the interviewees have to reconsider their travel behaviour and mode choice. The interview ends with some general questions concerning CLEVER (availability, replacement of vehicles in the household etc.). Availability of vehicles/modes of transport

Activities on the reporting day

(Individual questionnaires of the RP survey)

Reasons for the mode choice Experiences with other modes of transport

Presentation of the CLEVER-vehicle Assessment of the CLEVER-vehicle

Presentation of Scenarios A, B, C Reactions on Scenarios (Mode choice)

CLEVER related and general questions

Figure 3-2:

Steps of in-depth interview

3.4 Sampling, Gross and Net Sample 3.4.1 Revealed Preference Survey The sample of the RP survey was drawn at random out of an official register for both case study cities. The required usable net sample size was pre-defined with •

500 persons (> 6 years) per city and

•

should guarantee that the sub-sample of 150 persons for the SP survey drawn out of the RP sample could be reached.

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CLEVER

As due to the specific selection criteria of the second stage (compare chapter 3.4) this second target was not reached, the survey in Graz was extended a priori, while in Greater Thessaloniki Area (GTA) the RP survey had to be restarted in parallel to the SP survey. Therefore the time period of the RP survey in GTA lasted from January 2004 to November 2004, in Graz the survey was completed between November 2003 and January 2004 with an extension to April 2004. The final net sample for both case study cities is shown in Table 3-1. The response rate in Graz was 61%, whereas in GTA it was 30%. Table 3-1:

Net sample of the household survey in GRAZ and in GREATER THESSALONIKI AREA, 2003/2004

Net sample of the household survey (RP) Number of …

GRAZ

GTA

511

283

Persons (> 6 years)

1.262

797

Trips

3.969

2.306

Households

The spatial scope of the survey is defined for the Greek case study city to comprise the municipalities of Greater Thessaloniki Area. In Graz the inhabitants of Graz are included in the survey. 3.4.2 Stated Preference Survey The usable net-sample for the in-depth interactive interviews is drawn out of the sample of the household survey (RP) and includes about 150 persons, aged 16 years or older. It is a non-random sample as the interviewed households are selected. The following criteria for the selection of the persons respectively of the households are defined: –

In the selected households at least one person should have had at least one car trip (as car driver). Altogether at least 100 persons with car trips (as car driver) have to be interviewed in the sample.

–

All other mobile persons, who are aged 16 years or older and who attend the interview, are valid for the net-sample as well. All household members aged 16 years or older should preferably had trips on the reporting day.

–

All household members aged 16 years or older should attend the interview.

–

Households, which had no car trip at all on the reporting day, have to be excluded a priori.

–

All modes (car driver, car passenger, public transport, bicycle) should be represented in the net sample.

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CLEVER

The net sample size of the in-depth interactive interviews according to the units households, persons and trips for both case study cities are shown in Table 3-2. Table 3-2:

Net sample of the in-depth interviews in GRAZ and in GREATER THESSALONIKI AREA, 2004

Net sample of the in-depth interactive interviews Number of …

GRAZ

GTA

Households

73

87

(Mobile) Persons (> 16 years)

151

134

Trips

557

474

In Graz in 49% of the pre-selected households interviews were carried out, 40% refused to participate in the survey and 11% were not reached. The in-depth interviews were conducted in the period from April 2004 to June 2004, in GTA during May 2004 and November 2004.

3.5 Data Checks, Quality Control and Weighting 3.5.1 Data Checks and Quality Control General data and plausibility checks are done to eliminate coding errors and implausibilities due to unreliable or implausible answers of the respondents. Special attention is paid to the plausibility of the answers concerning the choice of CLEVER in the scenarios. As the CLEVER choice is hypothetical it has to be checked in detail, how realistic is it that the person, pretending in the interview to use CLEVER for a trip, would use and buy it in reality. Due to this consideration the CLEVER choice in the scenarios is stepwise revised regarding the following constraints: –

The potential CLEVER user needs to own a driving licence for a passenger car (category B).

–

Negative assessments of CLEVER (negative comments on purchase costs, aesthetic design etc.) lead to the assumption that one would not use and buy a CLEVER in fact.

–

If the question “Could you imagine to use the CLEVER?” (posed before the new mode choice according to the scenarios) is answered with “no” or “possibly” (plus comments suggesting that CLEVER would not be used), the choice of CLEVER is not reliable.

–

The question about the kind of availability of CLEVER (purchase, rental, car sharing) should be clearly answered with “purchase”, all the other possibilities Page - 18 -


CLEVER

(considering also the comments) may suggest that the use of CLEVER is not a permanent one. –

The status of CLEVER (CLEVER as a single, second, third etc. vehicle) is examined in connection with the question about the replacement of other vehicles and the total number of cars in a household. Inconsistencies may again suggest that the use of CLEVER is not binding.

If only one of these constraints is applicable (each trip respectively CLEVER choice is regarded separately), the choice is reset to the originally chosen mode. 3.5.2 Weighting and Grossing Up The goal of the weighting procedure is to avoid any bias of the target characteristics of the survey. Whenever bias is found, known or presumed to exist in the raw data set of a survey, weighting is necessary. This is necessary for instance if the response rate is less than 100%. Generally, assessment of bias is done by comparing certain key variables of the sample with recent data of the population and other possible benchmarking sources [Neumann A., 2003]. Weighting was done on person level using national data of the population separately for each case study city. In this step the data are weighted using the socio-demographic characteristics •

household size (5 classes),

•

the cross distribution of age and gender (10 classes) and

•

the employment status (4 classes).

The weighting was done simultaneously. The aim of a simultaneous weighting procedure is to produce consistent weights in several mathematically coordinated iteration steps. These weights have to satisfy all known distributions of characteristic variables of the population (census data). The weights are iteratively adapted from the initial values to those values, that fulfil the conditions represented by the distribution of the weighting characteristics in the population as a whole. After each weighting step on person level the total number of units (persons) were standardised to the original sample size. In Figure 3-3 and Figure 3-4 the distribution of the weights are shown for Graz and Thessaloniki. In Graz the minimum value is 0,17, the maximum value is 4,45. In Thessaloniki the minimum value is 0,30 the maximum value is 5,00.

Page - 19 -


CLEVER

25%

share [%]

20% 15% 10%

2,35 - 2,85

> 2,85

2,35 - 2,85

> 2,85

1,95 - 2,35

1,61 - 1,95

1,33 - 1,61

1,10 - 1,33

0,91 - 1,10

0,75 - 0,91

0,62 - 0,75

0,51 - 0,62

0,42 - 0,51

0,35 - 0,42

0%

< 0,35

5%

classes of weights

Figure 3-3:

Share of classes of weights, Graz, n=971 persons

18% 16% 14% share [%]

12% 10% 8% 6% 4%

1,95 - 2,35

1,61 - 1,95

1,33 - 1,61

1,10 - 1,33

0,91 - 1,10

0,75 - 0,91

0,62 - 0,75

0,51 - 0,62

0,42 - 0,51

0,35 - 0,42

0%

< 0,35

2%

classes of weights

Figure 3-4:

Share of classes of weights, Thessaloniki, n=797 persons

In order to get indicators of the travel behaviour for the total population the results of the weighting and grossing up procedure are multiplied according to the given figures of the population per case study city.

Page - 20 -


CLEVER

3.6 General Data Analysis The analysis of the valid data set is carried out in order to investigate the potential changes in mobility behaviour and of the market potential of the new vehicle. The potential mode shift for all types of modes (car driver, car passenger, public transport, bicycle, moped/motorcycle) is estimated considering the following questions: –

From which modes does the mode shift towards CLEVER appear?

–

How many trips can be substituted by CLEVER and how do the kilometres travelled by the different modes change?

–

Which kind of trips (related to trip purpose and trip lengths) are covered by CLEVER?

–

Who are the potential CLEVER users? Who is the target group?

–

What are the objective as well as subjective reasons for respectively the constraints and obstacles against the use of CLEVER?

The analysis is carried out using SPSS 11.0 and Microsoft Excel 2000.

3.7 Evaluation of Effects and Impacts Based on the data of the in-depth survey and concretely on the (revised) mode shift towards CLEVER in the scenarios the market potential of CLEVER is estimated and the most important effects of the use of CLEVER on the urban traffic and the environment according to the scenarios are quantified and estimated by means of a cost benefit analysis (CBA). Those effects are identified using indicators related to the actual state. The reference data of the actual state are either calculated on the basis of the projected data of the revealed preference survey – guaranteeing the validity for the whole viewed city – or taken from literature (e.g. emission loads, number of road accidents). The quantities in the scenarios are calculated considering the percentage change of the modal split and the change in kilometres travelled by the defined modes. The following indicators are used in the CBA: –

CO2 emissions and emissions of hazardous air pollutants;

–

Running costs (including fuel consumption);

–

Noise and road accidents;

–

Journey time;

–

Required parking infrastructure and costs of measures.

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CLEVER

4 CASE STUDY CITIES 4.1 Graz / Austria 4.1.1 General Characteristics The city of Graz is the second largest town in Austria with a population of about 226.000 permanent residents. Another 110.000 inhabitants, who commute to a large extent to Graz daily, live in the surrounding region. More than 150.000 jobs are available in Graz. Graz has 3 universities with about 40.000 students, whereof the majority are not permanents residents and are therefore not included in the figures above. Transport policy in Graz has been characterised by the slogan “gentle mobility” for more than a decade. This policy has been unique in Austria comprising the promotion of walking, cycling and public transport while restricting motorised private transport especially commuter traffic. However, a change in transport policy has been observed in the past years giving car traffic more priority. 4.1.2 Transport Infrastructure and Organisation The present supply of transport infrastructure is characterised by the environmentally friendly transport policy of the past [STADT GRAZ 2005]: •

pedestrian zones are arranged in the inner city with a network length of 4,5 km;

•

the cycle path network currently comprises approximately 106 kilometres. In total 84 km are planned additionally to establish a complete network (190km) throughout the city;

•

public transport comprises six tram lines (with a total network length of 32 km) and 45 urban bus lines;

•

the road network is characterised by a speed limit of 30 kilometres per hour on all streets except for priority streets; and

•

nearly 24.000 parking spaces are part of the inner city parking management scheme (Figure 4-1).

Transport organisation in Graz is based on a zonal traffic concept characterised by a single-centred town structure [SAMMER et al. 1994]. Five zones are arranged concentrically with differences in access for the transport modes: Zone 1 comprises the heart of the city centre – a pedestrian zone with assured passage for public transport and bicycles. Motorised traffic is restricted to loading activities within time limits.

Page - 22 -


CLEVER

Zone 2 surrounds the first zone and is freely open to public transport and bicycles. Car traffic is permitted permanently to residents only and to local business people and handicapped persons. A speed limit of 30 kilometres per hour is prescribed throughout the whole zone. In zone 3 passage is assured for motorised traffic for the whole day. All parking areas are paid parking, limited to 1,5 to 3 hours. General parking for longer periods is only possible in public garages. Apart from priority streets, all other streets are subject to the 30 km/h speed limit. Through the provision of bus lanes and tramway tracks, public transport can pass without constraint and receives priority at traffic lights. Zone 4 comprises the suburbs and newly-built areas. This zone is very much identical to zone 3 in terms of traffic organisation. The only difference is that onstreet parking is for free due to parking management is not applied. Zone 5 is defined as the surrounding countryside. Current plans are to provide attractive public transport routes, as well as park-and-ride and bike-and-ride facilities. Figure 4-1 shows the city map of Graz with two measures favouring the CLEVER in the scenarios – exception from parking management and allowed on bus lanes.

Page - 23 -


Figure 4-1:

CLEVER

City map of Graz with districts with parking management marked

4.2 Greater Thessaloniki Area/ Greece 4.2.1 General Characteristics The Greater Area of Thessaloniki in Greece includes 15 municipalities with approximately 800.000 inhabitants in total (Figure 4-2). It is divided in 6 sectors, whereas sector 1 & 2 comprise the city of Thessaloniki with about 364.000

Page - 24 -


CLEVER

inhabitants and a population density of 295 inhabitants/ha. A number of municipalities around Thessaloniki function as satellite cities since large number of their inhabitants are employed or do everyday business within Greater Thessaloniki Area limits. Thessaloniki lies at the north part of Greece expanded along the coastal line (gulf of Thermaikos) and it is the second largest city in Greece after the capital Athens. Its geographic site makes it very important in terms of commercial, cultural and political interest. In education alone, Thessaloniki accommodates some 70.000 students who study in two Universities and one Technological Institute. The city’s main transport infrastructure also comprises an international airport and an international port, which experience increasing volumes of passengers and goods. Particularly, the port of Thessaloniki is the second largest in Greece after Piraeus. The area is closely situated to the summer recreation area of Chalkidiki and Pieria (Mount Olympus) and welcomes every year a large number of foreign and Greek tourists.

Figure 4-2:

Map of Greater Thessaloniki Area

4.2.2 Transport Infrastructure and Organisation The central part of the Greater Thessaloniki Area (GTA) is the City of Thessaloniki, which is built on the ruins of the old city and is a rather narrow strip between the coastal line (south) and the nearby mountains (north). The whole city is very densely

Page - 25 -


CLEVER

populated with high-rised buildings (especially in the centre) and inadequate road infrastructure. The road network in the city centre has a grid pattern which extends to the east and the west. However as the city widens at its two edges the networks becomes radial. Thus, all the main roads which are parallel to the sea coast and have an east – west direction need to come through the centre or the use of the ring road. More specifically the centre, the most important part of the city in terms of traffic, is crossed by 6 main parallel roads that run along the coast. Only one of them is a two-way street, while the others are one-way streets. The ring road, constructed at the northeast area of the city, was fully opened 10 years ago in order to absorb a part of through traffic as well as to serve the heavy traffic. Today, the ring road operates at its capacity especially during the peak hours and major improvements are under construction. These improvements include the construction of at-level intersections to replace the level ones which are controlled with traffic signals. GTA, especially city centre, suffers from heavy traffic. City centre is congested during almost all day (not only in peak-hours). While the update of traffic signal system, the traffic enforcement for illegal on-street parking and the bus lane implementation have improved the situation in horizontal axis, the situation in the vertical axis has been deteriorated and the (legal and illegal) on-street parking is believed to contribute significantly in this situation. Generally speaking, there is a significant lack of parking spaces both for long term and short-term parking. This situation applies not only to the city centre but also to most of the municipalities. As a result vehicles park illegally reducing road capacity and increasing congestion both in duration and severity. Public transport is provided only through a surface bus network operated by Thessaloniki Transport Operator (OASTH), which is a private co-operative organisation subsidised by the Central Government and supervised by the Committee of Thessaloniki Public Transport (SASTH) that co-ordinates the provision of public transport services in the whole Prefecture of Thessaloniki. Up to 2001, the level of service provided by OASTH was deteriorating year by year. However, during the last two years some major actions have been taken to enhance service quality. These actions include the rationalisation of bus lines, change in ticketing system, the relocation of transfer stations, the replenishment of rolling stock, the upgrading of airport line and the gradual implementation of bus lanes along five main arteries of Thessaloniki that has contributed significantly in the enhancement of public transport service. OASTH offers service with 69 bus lines, whereas the total passenger load for 2002 averaged at 152,85 million passengers. A cycling network does not exist in Thessaloniki. There are only two bicycle lanes in the city centre, both of them along the coast and exclusively used for leisure activities. Pedestrian zones do exist to some extent in several parts of the city, but primarily in the city centre.

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CLEVER

5 MEASURES AND SCENARIOS 5.1 Possible Measures to Support CLEVER The use of CLEVER is amongst others dependent on measures favouring and promoting the new vehicle in urban areas. “Legal and regulatory measures can change the demand pattern in favour of sustainable modes like public transport, cycling and walking, and as such can reduce urban traffic problems and their negative impacts [LEDA 1999].” This also applies to the CLEVER project: the demand for CLEVER is aimed to be raised pursuing the goal to gain above all a reduction of negative impacts on the environment especially a reduction of CO2 emissions, emissions of hazardous air pollutants and fuel consumption. The strategy to achieve this goal is to address potential CLEVER users by means of incentives. Measures have to create advantages for the individual whether financial or time benefits or others to result in a shift from the originally used mode to CLEVER. However one should be aware that only a substitution of trips made by individual motorised modes (car driver, moped/motorcycle) by CLEVER causes the wanted effects. A shift from environmentally friendly modes (car passenger, public transport, bicycle, walking) to CLEVER results in an increase of kilometres travelled on the roads and consequently an increase of emissions, noise, accidents etc. is expected. “Measures are most effective when they are embedded in a total transport planning policy [LEDA 1999],” and when there are not only single but a bundle of measures aiming at the same goal. The categorisation of transport policy measures can be done in different ways. The one chosen for the proposed measures favouring the use of CLEVER uses a first general categorisation and then tries to allocate the type of measure more specifically (Table 5-1 to Table 5-4): 5.1.1 Infrastructure & Organisational Measures For example to build a bus lane or a CLEVER lane is clearly an infrastructure measure, but dividing the available space on a street by assigning a bus lane (and thus reducing the space for cars) is primarily a regulatory respectively an organisational measure. (The main component of legal and regulatory measures lies in a new (or amended) law or regulation) [LEDA 1999]. It is imaginable to allow the use of CLEVER on priority lanes like bus lanes, HOV (high occupancy vehicle) and HOT (high occupancy toll) lanes and to exempt CLEVER from existing access restrictions. Concerning parking exemptions from parking fees or reduced tariffs as well as designated parking places for CLEVER are possible.

Page - 27 -


Table 5-1:

CLEVER

Infrastructure and organisational measures supporting CLEVER Type of measures

Parking

Traffic

Infrastructure & Organisational Measures

legal & financial infraregulator structure y

X

organisational

information

X

x

Separate lanes for CLEVER

X

Use of bus lanes

X

X

x

Use of HOV lanes

X

X

x

Use of HOT lanes

X

X

x

Exemption from access restrictions (environmental zones, limited access to the city centre etc.)

X

X

x

Exemption from access pricing (e.g. congestion pricing)

X

X

x

Exemption from road pricing on urban motorways

X

X

x

Designated parking spaces on the street (in the city centre)

X

X

x

Designated parking spaces in public garages (in the city centre, at the station – Park & Ride)

X

X

x

Exemption from parking fees resp. reduced tariffs in on-street parking zones

X

X

X

x

Exemption from parking fees resp. reduced tariffs in public garages

X

X

X

x

No time limits for CLEVER in short-term parking zones

X

X

x

others

5.1.2 Information & Awareness Measures Information & awareness measures (Table 5-2): Information is absolutely necessary to make people aware of the existence respectively of the advantages of the new vehicle. Table 5-2:

Information and awareness measures supporting CLEVER Type of measures

Information & Awareness Measures


organisational

information

Marketing & promotion of CLEVER

X

Information campaigns, individual marketing

X

others

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CLEVER

5.1.3 Accompanying Measures Accompanying measures and others (Table 5-3): An area wide supply of gas stations providing CNG for private cars is a precondition for the launch of CLEVER. Financial incentives like subsidies for buying or leasing a CLEVER or tax relieves may support the selling of CLEVER. Providing the possibility of CLEVER sharing or rental may convince those who would like to test CLEVER before owning it. Table 5-3:

Accompanying measures and others supporting CLEVER Type of measures

Accompanying measures and others

information

others

x

X

Subsidies for buying or leasing a CLEVER, benefits on vehicle assurance

x

X

Benefits on vehicle tax or on impact fees

x

X

“Rent a CLEVER”

X

X

Offering CLEVER-Sharing

X

X

Gas stations providing CNG for private cars (area wide)


X

organisational

5.1.4 Restrictions and Impacts for “Non-CLEVER” Vehicles Restrictions and impacts for “Non-CLEVER” vehicles (Table 5-4): Restrictions and constraints for car drivers should encourage them to rethink their mode choice and change to CLEVER respectively to PT, cycling or walking. Access restrictions like access pricing aim at reducing car/vehicle traffic in the city by making road users pay. In environmental zones entry is restricted to vehicles which do not meet certain environmental standards. The aim is to protect particularly sensitive areas in the central part of the city, which are affected by pollution and noise from traffic. Congestion charging is a way of ensuring that those using valuable and congested road space make a financial contribution. It encourages the use of other modes of transport and is also intended to ensure that, for those who have to use the roads, journey times are quicker and more reliable [LONDON 2005]. The raise of fuel prices has to exceed a relatively high threshold to convince car drivers to shift to another mode, on the other hand it may be easier to change to a comparable equal individual mode like CLEVER for which the fuel (CNG) prices are much lower.

Page - 29 -


Table 5-4:

CLEVER

Restrictions and impacts for “Non-CLEVER” vehicles


Type of measures legal & financial infraregulator structure y

organisational

information

X

x

X

x

General access respective time limited restrictions to the city centre (environmental zones)

X

Congestion charging in the city centre

X

Introduction of HOV lanes

X

x

X

x

Introduction of HOT lanes

X

x

X

x

Increase of fuel prices (for petrol and diesel)

X

X

X

others

x

5.2 Scenarios for the SP Survey Out of the proposed measures supporting the use of CLEVER, three scenarios were developed, which were used in the SP survey. They were presented to the respondents as a basis for their new mode choice. The measures were selected due to their applicability in the two scenarios. 5.2.1 SCENARIO A In Scenario A the CLEVER vehicle is launched at the market. An area wide supply of gas stations offering CNG is a precondition for the use of CLEVER. Sales, distribution and service supply is guaranteed. Beside the option to buy a CLEVER, CLEVER sharing and rental is offered. There are neither infrastructure nor any organisational measures planned. LAUNCH of a new motorised private vehicle (CLEVER)

Area wide supply of gas stations for vehicles run by compressed natural gas (CNG) like the CLEVER

Sales and distribution of the CLEVER in the whole country

Good service supply (garages etc.) for the CLEVER

Supply of “CLEVER rental” und “CLEVER sharing

Page - 30 -


CLEVER

The advantages respectively disadvantages of the use of CLEVER in comparison to the originally chosen modes in Scenario A regarding the trip characteristics “travel time” and “travel costs” are depicted in Table 5-5. While there are no time advantages for CLEVER compared to car driver, car passenger and moped/ motorcycle, one may be faster using CLEVER instead of public transport or bicycle. Cost advantages for CLEVER appear compared to car driver, due to the lower fuel prices (CNG) for CLEVER, and to some extent to public transport. Table 5-5:

Advantages/disadvantages of the use of CLEVER regarding travel time and costs in Scenario A in comparison to originally used modes

SCENARIO A Mode shift from … to CLEVER as driver

Travel time

Travel costs

Car driver

o

+

Car passenger

o

–

Moped/motorcycle driver

o

o

Public Transport user

+

+/–

Bicycle user

+

–

+ … advantage for CLEVER

o … no difference

– … disadvantage for CLEVER

5.2.2 SCENARIO B This scenario includes only “pull”-measures (= measures favouring the new vehicle) that could be implemented with low financial effort as nearly no infrastructure has to be built, only slight adaptations have to be done. While the use of bus lanes and designated parking spaces for CLEVER in the city centre implicate time advantages for the CLEVER user, an exemption from road pricing and reduced parking fees guarantee additional financial benefits (Table 5-6).

Page - 31 -


CLEVER

Policies to promote the CLEVER in the city/area

No parking fees and no time limitations in on-street parking zones for the CLEVER;

Reduced parking fees (– 50%) in garages for the CLEVER

Priority parking sites for the CLEVER in the city centre and at P&R locations (in garages and on-street)

Use of bus lanes with the CLEVER in the city

Exemption from road pricing

Table 5-6:

Advantages/disadvantages of the use of CLEVER regarding travel time and costs in Scenario B in comparison to originally used modes

SCENARIO B Mode shift from … to CLEVER as driver

Travel time

Travel costs

Car driver

+

+

Car passenger

+

–

Moped/motorcycle driver

o

o

Public Transport user

+

+/–

Bicycle user

+

–


o … no difference


5.2.3 SCENARIO C Scenario C includes all measures of Scenario B and the promotion activities of Scenario A. In addition to Scenario B “push”-measures (= restrictions and constraints for car drivers aiming at triggering a mode shift towards environmentally friendly modes) are considered, which are limited to the raise of fuel prices by 75% and 150%. As a consequence the difference in travel costs between car and CLEVER increases (Table 5-7). The sub sample of the in-depth interactive survey was divided in two classes, were the trip costs in the first class were calculated with fuel prices plus 75%, in the second class with fuel prices plus 150%. These two different levels of fuel prices in the scenarios were chosen to find out the elasticity of the reaction to Page - 32 -


CLEVER

this measure. Analysis have shown, that there is no significant difference in the reaction of the respondents related to these two classes. Therefore the calculation of the modal shift and the Cost Benefit Analysis are based on fuel prices plus 112,5% this is the mean value of these two classes. Policies to promote the CLEVER in the city/area according to Scenario B and at the same time increase of the fuel prices of 112,5% throughout the country. AUSTRIA: Petrol 2,13€/l; diesel 1,60€/l GREECE: Petrol 1,73€/l; diesel 1,47€/l Table 5-7:

Advantages/disadvantages of the use of CLEVER regarding travel time and costs in Scenario C in comparison to originally used modes

SCENARIO C Mode shift from … to CLEVER as driver

Travel time

Travel costs

Car driver

+

+

Car passenger

+

–

Moped/motorcycle

o

o

Public Transport

+

+/–

Bicycle

+

–


o … no difference


Page - 33 -


6

CLEVER

CONFIDENCE INTERVALS AND RANDOM ERROR

The confidence intervals / random error of the results of the survey as percentage values of the share of an attribute are shown in Figure 6-1 and Figure 6-2, both for Graz and Thessaloniki on person and trip level based on the values shown in Table 6-1. The values are calculated by

P = p ± Δp with

⎛1− p ⎞ ⎛ N − n ⎞ Δp = t ⋅ p ⋅ ⎜ ⎟⋅⎜ ⎟ ⎝ n ⎠ ⎝ N ⎠

where: P

[ ]

estimated value of the share of an attribute

Δp

[ ]

random error of the value of the share of an attribute

p

[ ]

share of an attribute

n

[ ]

sample size

N

[ ]

population

t

[ ]

1,96 for a statistical reliability of 95%

Page - 34 -


Table 6-1:

CLEVER

Confidence intervals / random error related to percentage values of the share of an attribute for Graz and Thessaloniki, person and trip level Person Level

Trip Level

n

N

n

N

Graz

151

226241

557

692683

Thessaloniki

134

1057825

474

492127

share of an attribute

Graz

Thessaloniki

Graz

Thessaloniki

5%

3,5%

3,7%

1,8%

2,0%

10%

4,8%

5,1%

2,5%

2,7%

15%

5,7%

6,0%

3,0%

3,2%

20%

6,4%

6,8%

3,3%

3,6%

25%

6,9%

7,3%

3,6%

3,9%

30%

7,3%

7,8%

3,8%

4,1%

35%

7,6%

8,1%

4,0%

4,3%

40%

7,8%

8,3%

4,1%

4,4%

45%

7,9%

8,4%

4,1%

4,5%

50%

8,0%

8,5%

4,2%

4,5%

55%

7,9%

8,4%

4,1%

4,5%

60%

7,8%

8,3%

4,1%

4,4%

65%

7,6%

8,1%

4,0%

4,3%

70%

7,3%

7,8%

3,8%

4,1%

75%

6,9%

7,3%

3,6%

3,9%

80%

6,4%

6,8%

3,3%

3,6%

85%

5,7%

6,0%

3,0%

3,2%

90%

4,8%

5,1%

2,5%

2,7%

95%

3,5%

3,7%

1,8%

2,0%

Person Level

Trip Level

Page - 35 -

CLEVER

9,0% 8,0% 7,0% 6,0% 5,0% 4,0% 3,0% 2,0% 1,0% 0,0%

Thessaloniki

95%

85%

75%

65%

55%

45%

35%

25%

15%

Graz

5%

Random Error [%]


percentage value of the share of the attribute, person level

Confidence intervals / random error related to percentage values of the share of an attribute for Graz and Thessaloniki, person level

5,0% 4,5% 4,0% 3,5% 3,0% 2,5% 2,0% 1,5% 1,0% 0,5% 0,0%

Thessaloniki

95%

85%

75%

65%

55%

45%

35%

25%

15%

Graz

5%

Random Error [%]

Figure 6-1:

percentage value of the share of the attribute, trip level

Figure 6-2:

Confidence intervals / random error related to percentage values of the share of an attribute for Graz and Thessaloniki, trip level

Page - 36 -


7

CLEVER

TRAVEL BEHAVIOUR AND USER REQUIREMENTS

The household, person and trip information collected in the RP survey and the mode choice and CLEVER assessment investigated in the SP survey provide the data for the analysis of the travel behaviour and requirements of potential CLEVER users. The influencing factors of the mode choice, the mode shift towards CLEVER and the reasons for the potential use of CLEVER are analysed. Out of the mode choice under scenario conditions and the assessment of CLEVER the market potential of the new vehicle in the two case study cities is estimated.

7.1 CLEVER Assessment and User Requirements In the SP survey in both case study cities the characteristics of CLEVER were assessed by all respondents (CLEVER users and Non-CLEVER users). As a result the CLEVER idea and the low running costs are assessed mainly positively, whereas the capacity of CLEVER to transport baggage or persons as well as the purchase costs (EUR 9.000,-- “too expensive”) are rated rather negatively (Figure 7-1). The view on the aesthetic design is quite divided. While some of the respondents found it “innovative” and “awesome”, the others disliked the aesthetic design arguing that it is “too modern” or “too unusual”. The technical features of CLEVER are mostly positively assessed in Graz as well as in Greater Thessaloniki Area, whereby the low emissions of CLEVER are especially favoured (Figure 7-2). Generally the positive assessment of CLEVER is higher in Thessaloniki than in Graz.

Page - 37 -


CLEVER GRAZ n=134

100% 16%

10%

20%

1% 12% 5%

44% 57%

20%

39%

60%

39% 22%

29%

45%

35%

-2

31% 34%

19%

CLEVER design

11% 2%

GTA

GRAZ

GTA

GRAZ

GTA

7%

24% 16%

20%

Transport persons

2%

Transport baggage

24%

6%

Purchase costs

GTA

22%

48%

GRAZ

20%

+2 21%

34%

29%

43% 25%

32%

34%

+1

35%

GRAZ

37%

GTA

40%

GTA

44%

20%

-1

55%

CLEVER idea

Running costs

CLEVER assessment according to its practical characteristics by all the respondents (CLEVER users and Non-CLEVER users) in GRAZ and in GREATER THESSALONIKI AREA, 2003, [+2 … very positive, -2… very negative]

GRAZ n=134 100%

7% 19%

13%

80%

5% 15%

8%

1% 17% 9%

7% 16%

16%

15%

Percentage of CLEVER assessment

9%

14% 25%

0%

Figure 7-1:

19%

33%

GRAZ

80%

GRAZ

Percentage of CLEVER assessment

7%

23%

GTA n=155

19%

21%

16%

17%

15%

GTA n=155 12% 4%

2% 2% 27%

11%

17%

33%

48%

60%

-2 46% 43%

-1

55% 53%

45% 54%

40%

55%

+1

62%

53%

+2 69% 51%

42%

20%

32% 24%

18%

25%

24% 14%

20%

14%

11%

Speed

Figure 7-2:

Acceleration

Driving range

Consumption

Tilting

GTA

GRAZ

GTA

GRAZ

GTA

GRAZ

GTA

GRAZ

GTA

GRAZ

GTA

GRAZ

0%

Emissions

CLEVER assessment according to its technical characteristics by all the respondents (CLEVER users and Non-CLEVER users) in GRAZ and in GREATER THESSALONIKI AREA, 2003, [+2 … very positive, 2… very negative]

Page - 38 -


CLEVER

Imaging the hypothetical use of CLEVER 17% of the respondents in Graz and 21% of the interviewees in Greater Thessaloniki Area said they would probably use it. Their arguments in Graz were that they are interested and curious to drive it, it is cheaper to use the CLEVER than a car for a trip and there would be no parking problems (Figure 7-3). Many of the respondents would find it useful to substitute short car trips by CLEVER. In Greater Thessaloniki Area the (running) cost argument, environmental considerations and eased parking conditions made the interviewees think to use the CLEVER. 35%

GRAZ n = 33

28%

GREATER THESSALONIKI AREA n = 39

28%

25%

18%

18%

18%

15% 13%

12% 8%

for shopping trips

3%

0% for short trips

no parking problems

cost advantages

interest, fun

0%

3%

time advantages

3%

Figure 7-3:

6%

6%

3%

for leisure trips

5%

environmental considerations

Percentage of reasons for the use of CLEVER

33%

Reasons and arguments for the use of CLEVER by all respondents (CLEVER users and Non-CLEVER users) in GRAZ and in GTA, 2003

The majority of the respondents (59% in Graz and 43% in Greater Thessaloniki Area – the rest was indifferent) can not imagine to use the CLEVER. In Graz the (small) size of CLEVER was the main argument against CLEVER, followed by that other modes are favoured and that the aesthetic design is disliked (Figure 7-4). In Greater Thessaloniki Area the high purchase costs were criticized as well as the aesthetic design.

Page - 39 -


CLEVER

35%

GREATER THESSALONIKI AREA n = 122 25%

21%

21%

18% 15% 14%

9% 8%

7% 7%

Figure 7-4:

3%

no interest

too expensive

too small

unfunctional

0%

design disliked

1% 1%

have no driving licence

3%

2% 1%

4% 2% 2% other modes favoured

6%

not suitable for long distances

5%

unsafe

9%

unrealisable, no market

10%

9%

13%

13%

problematic for elderly people

15%

no comfort

Percentage of reasons for the use of CLEVER

GRAZ n = 139

Reasons and arguments against the use of CLEVER by all respondents (CLEVER users and Non-CLEVER users) in GRAZ and in GTA, 2003

7.2 Mode Choice in the Scenarios Some of the analysis in this chapter are on a very disaggregated level – especially in chapter 0 and 7.2.4. The possible level of disaggregation is always dependent on the sample size per class. The smaller the sample size gets, the larger gets the random error and the confidence intervals (see chapter 6). All figures, charts and interpretations of the analysis given have to have these circumstances in mind. The alternatives for mode choice in the three scenarios are dependent on the originally chosen mode and on the scenarios themselves. In Scenario A and Scenario B two alternatives are available – the originally chosen mode and CLEVER (Table 7-1). The choice of any other alternative would not be rational explainable. In Scenario C there are some more alternatives for car driver, car passenger and moped/motorcycle beside CLEVER, as in Scenario C the cost argument appears due to rising fuel prices (compare chapter 5.2). For public transport and bicycle also in Scenario C the CLEVER is the only alternative as any other alternative would not be rational explainable, too.

Page - 40 -


Table 7-1:

CLEVER

Possible alternatives for mode choice in the three scenarios according to the originally chosen mode

Possible mode alternatives for choice in the three scenarios Originally chosen mode

Scenario A

Scenario B

Scenario C Car driver

Car driver

Car passenger

Car driver CLEVER

Car passenger CLEVER

Car driver CLEVER

Car passenger CLEVER

CLEVER Car passenger Public Transport Bicycle On foot Trip skipped Car passenger CLEVER Car driver Public Transport Bicycle On foot Trip skipped Moped/motorcycle

Moped/motorcycle

Moped/motorcycle

CLEVER

CLEVER

CLEVER Car passenger Public Transport Bicycle On foot Trip skipped

Public Transport users

Public Transport CLEVER



Bicycle user

Bicycle CLEVER

Bicycle CLEVER

Bicycle CLEVER

Moped/motorcycle rider

The following results are related to the average travel behaviour on a weekday of the inhabitants of Graz respectively of the inhabitants of Greater Thessaloniki Area. 7.2.1 Mode Shift – Relative Values 7.2.1.1 GRAZ The launch of the CLEVER in Scenario A without any supporting or restrictive measures brings a modal shift towards CLEVER of about 1,4% of all trips in Graz, whereby the trips are mainly shifted from car driver trips induced by the cost Page - 41 -


CLEVER

advantage, while a small share comes from car passenger trips (Figure 7-5). User of public transport, moped/motorcycle or bicycle find no need respectively argument to use the CLEVER.

Car passenger 8,4% 8,7% 0,3%

37,3% 36,1%

19,6%

1,2%

Public Transport 1,4% CLEVER

Car driver

12,8% Bicycle 20,8% Figure 7-5:

0,9% Moped/motorcycle

On foot

Modal shift in Scenario A in GRAZ, 2003

The measures favouring the use of CLEVER in Scenario B cause a slight rise of the shift from car driver trips towards CLEVER compared to Scenario A (+ 0,2%) and bring a small share of public transport passengers (0,8%) to use the new vehicle, which results in a CLEVER share of 2,4% of all trips in Graz (Figure 7-6). Cost as well as time advantages compared to the originally chosen mode make travellers use CLEVER in this scenario.


37,3%

0,8%

35,9%

1,4%

Car driver

19,6% 18,7% Public Transport

2,4% CLEVER 12,8% Bicycle

20,8% Figure 7-6:

On foot

0,9% Moped/motorcycle

Modal shift in Scenario B in GRAZ, 2003

Page - 42 -


CLEVER

As in Scenario C users of private motorised vehicles (car driver and passenger, moped/motorcycle) have more than two alternatives for choice – due to the argument of rising fuel prices – the mode shift is more complex (Figure 7-7).


37,3% 35,8% Car driver

0,1%

0,8%

1,3% 0,1%

2,3% CLEVER 0,1%

20,8% Figure 7-7:

On foot

19,6% 18,9% Public Transport

12,8% 13,0% Bicycle

0,9% 0,8% Moped/motorcycle

Modal shift in Scenario C in GRAZ, 2003

Car driver trips are not only substituted by CLEVER trips, but by trips made by public transport or by bicycle. The share of CLEVER trips shifted from public transport trips stay constant compared to Scenario B, which argues for that the time advantage is the main reason for the use of CLEVER. The share of CLEVER trips of all trips in Graz in Scenario C is 2,3%. Figure 7-8 gives an overview of the modal split in Graz in the actual state and in the three scenarios. Worth mentioning is the relatively high share of bicycle trips resulting from the fact that Graz is a bicycle friendly city. As a maximum a share of CLEVER trips of 2,4% can be expected in Scenario B, whereby mainly car driver trips can be substituted by CLEVER trips.

Page - 43 -


CLEVER

On Foot

20.8%

20.8%

20.8%

20.8%

Bicycle Motorcycle

12.8% 0.9%

12.8% 0.9%

12.8% 0.9%

13.0% 0.8%

Public Transport

19.6%

19.6%

18.7% 2.4%

18.9% 2.3%

8.4%

8.4%

35.8%

8.7%

1.4% 8.4%

37.3%

36.1%

35.9%

Actual state

Scenario A

Scenario B

CLEVER Car passenger

Car driver

Figure 7-8:

Scenario C

Modal split in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips

7.2.1.2 GREATER THESSALONIKI AREA In the Greater Thessaloniki Area the results of the SP survey show a higher share of CLEVER trips compared to the case study city Graz. In Scenario A 6,3% of the car driver trips, 4,4% of the trips made by public transport and 0,4% of car passenger trips are shifted to CLEVER, which results in a CLEVER share of 11,1% of all trips in the Greater Thessaloniki Area (Figure 7-9). Bicycle and motorcycle trips are not affected. In Scenario B the share of CLEVER trips slightly increases to 11,6%, whereby the rise exclusively comes from the shift from car driver trips (Figure 7-10).

Car passenger 14,2%

13,8%

0,4%

37,3% 39,1%

4,4%

36,1% 32,8%

6,3%

Car driver

19,6%

11,1% CLEVER

19,5%

15,1%

Public Transport

0,2% Bicycle 2,6%

24,4%

Figure 7-9:

On foot

Moped/motorcycle

Modal shift in Scenario A in GREATER THESSALONIKI AREA, 2003

Page - 44 -


CLEVER

Car passenger 14,2%

13,8%

0,4%

37,3% 39,1%

19,6%

4,4% 6,8%

36,1% 32,3% Car driver

11,6% CLEVER

19,5%

15,1%

Public Transport

0,2% Bicycle 2,6%

24,4%

Moped/motorcycle

On foot

Figure 7-10: Modal shift in Scenario B in GREATER THESSALONIKI AREA, 2003

The rising fuel prices in Scenario C cause a more complex mode shift also in Greater Thessaloniki Area (Figure 7-11). The cost argument is a strong one for car drivers to use modes which are more affordable. 7,3% of car driver trips are shifted to CLEVER, 2,6% to public transport, 1,4% to trips on foot, 0,1% to bicycle and 0,7% of the car driver trips are even skipped. Car passengers also seek for alternatives and shift to CLEVER, to public transport or make their trips on foot.

Car passenger

Trip skipped 0,7%

14,2%

10,8%

1,7%

1,3% 0,4%

19,5%

2,6%

37,3% 39,1% 36,1% 27,0% Car driver

7,3%

12,5% CLEVER 0,1%

27,0%

Public Transport

4,8%

1,4%

24,4%

19,0%

0,2%

0,3% Bicycle

2,6% On foot

Moped/motorcycle

Figure 7-11: Modal shift in Scenario C in GREATER THESSALONIKI AREA, 2003 Page - 45 -


CLEVER

The modal split in Greater Thessaloniki Area in the actual state and in the three scenarios shown in Figure 7-12, present the highest share of CLEVER trips in Scenario C with 12,5%, which is quite remarkable as it in fact exceeds expectations. As in Graz the most potential trips to be shifted to CLEVER are car driver trips. 0.7%

Trip skipped On Foot Bicycle Motorcycle Public Transport

24.4%

24.4%

24.4%

2.6% 0.2%

2.6% 0.2%

2.6% 0.2%

19.5%

15.1%

15.1%


CLEVER 11.1% 14.2%

13.8%

27.0% 2.6%

0.3%

19.0%

CLEVER 11.6% 13.8%

CLEVER 12.5% 10.8%

Car driver

39.1%

Actual state

32.8%

Scenario A

32.3%

Scenario B

27.0%

Scenario C

Figure 7-12: Modal split in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n= 474 trips In Table 7-2 and Table 7-3 the person mileage [km/day] per mode in the actual state compared to the Scenarios A, B and C are shown for Graz and Thessaloniki. The differences between the modal shift and the figures in Table 7-2 and Table 7-3 are caused by the fact, that the modal shift is calculated for trips and not for the mileage. The calculation of the cost benefit analysis is always based on the mileage. 7.2.2 Mode Shift – Absolute Values In Graz the total number of trips and mileage does not change between the actual state and the scenarios. The total mileage of car driver and passenger, moped and CLEVER (individual motorized vehicles) is slightly increasing in Scenario B and C. This effect could also be seen in Thessaloniki for the Scenarios A and B. In Scenario C the mileage of Public Transport increases a lot due to very long trips with a mode shift to Public Transport.

Page - 46 -


Table 7-2:

CLEVER

Person mileage per mode [km/day] in the actual state compared to the Scenarios A, B and C for Graz Actual state 2003

Scenario A

Scenario B

Scenario C

4.022.164

3.961.624

3.944.929

3.943.620

899.773

844.184

844.184

844.184

46.608

46.608

46.608

39.492

Cyclist

332.059

332.059

332.059

340.245

Pedestrian

200.895

200.895

200.895

200.895

1.631.319

1.631.319

1.600.987

1.605.677

Car driver using CLEVER instead

–

60.540

77.235

72.785

Car passenger using CLEVER instead

–

55.589

55.589

55.589

PT passenger using CLEVER instead

–

–

30.332

30.332

CLEVER (sum)

–

116.129

163.156

158.706

Total sum

7.132.818

7.132.818

7.132.818

7.132.818

Total sum motorized

4.968.545

4.968.545

4.998.877

4.986.002

Total sum non-motorized

2.164.273

2.164.273

2.133.941

2.146.817

–

0,0%

0,6%

0,4%

–

0,0%

-1,4%

-0,8%

GRAZ Car driver Car passenger Moped/motorcycle

Public Transport

Δ Actual State – Scenario for car driver and passenger, moped and CLEVER

Δ Actual State – Scenario for cyclists, pedestrians and Public Transport

Page - 47 -


Table 7-3:

CLEVER

Person mileage per mode [km/day] in the actual state compared to the Scenarios A, B and C for Thessaloniki Actual state 2003

Scenario A

Scenario B

Scenario C

Car driver

7.368.663

6.773.488

6.683.200

4.489.405

Car passenger

1.974.392

1.929.743

1.929.743

1.712.234

203.890

203.890

203.890

203.890

37.088

37.088

37.088

44.821

419.450

419.450

419.450

503.932

Public Transport

2.750.840

2.241.509

2.241.509

4.258.217

Car driver using CLEVER instead

–

595.175

685.463

930.272

Car passenger using CLEVER instead

–

44.649

44.649

44.649

PT passenger using CLEVER instead

–

509.332

509.332

531.972

CLEVER (sum)

–

1.149.156

1.239.444

1.506.893

12.754.323

12.754.323

12.754.323

12.719.392

Total sum motorized

9.546.945

10.056.277

10.056.277

7.912.422

Total sum nonmotorized

3.207.378

2.698.046

2.698.046

4.806.970

–

5,3%

5,3%

-17,1%

–

-15,9%

-15,9%

49,9%

GTA

Moped/motorcycle Cyclist Pedestrian

Total sum

Δ Actual State – Scenario for car driver and passenger, moped and CLEVER

Δ Actual State – Scenario for cyclists, pedestrians and Public Transport

In Table 7-2 and Table 7-3 the total sum of mileage is shown for Graz and Thessaloniki. Only in Scenario C in GTA the total mileage decreases slightly due to 3 trips surveys, that would be skipped due to increasing fuel prices (see chapter 8.7). These tables show, that there are no induced trips and mileage as no one of the respondent will change the destination of a trip.

Page - 48 -


CLEVER

7.2.3 Reasons for the Mode Choice To explore the possibilities how to induce travellers and especially car drivers to shift to another – environmentally friendly – mode, the reasons and motives for the mode choice are asked in the SP survey. Exemplary the arguments for car and CLEVER choice under the conditions of Scenario C are presented in the following figures for the two case study cities. Two categories of arguments can be distinguished: arguments for using the chosen modes, which can be objective or subjective ones, and supportive reasons against other alternatives. In case of the car drivers in Graz the most often mentioned arguments are “subjective advantages”, which include “functionality”, “comfort” and “flexibility”, “transport of persons or goods” and “cost advantages” against public transport (Figure 7-13). In Greater Thessaloniki Area the cost argument for the CLEVER is the strongest one, despite the fact that in Scenario C costs for car trips increase. “Subjective advantages” as well as “time advantage” are additional reasons. To justify their choice of the car, the car drivers specified their reasons why they would not choose the CLEVER instead. In Graz most of the respondents argue that the CLEVER is too small and that it provides no comfort and in general no advantages. In Greater Thessaloniki Area the arguments against CLEVER are more balanced, whereby the size, the aesthetic design and the purchase costs of CLEVER are mainly criticized.

Page - 49 -


CLEVER

45%

38%

41%

Arguments against CLEVER choice

34%

35%

GRAZ

1% 1%

Too far to use another mode

8%

9%

8% 1% 6%

No parking problems

14%

16%

19% 14%

12% 1%

Company car, business trip

5%

10%

15%

20%

18%

22%

22%

21%

20%

25%

16% 20%

GREATER THESSALONIKI AREA

8%

Percentage of reasons for the car choice and against the choice of CLEVER

Arguments for the CLEVER choice

CLEVER no advantages

CLEVER too unsafe

CLEVER too expensive

CLEVER design disliked

CLEVER no comfort

CLEVER too small

Transport of goods, persons

Subjective advantages

Cost advantage

Time advantage

0%

Figure 7-13: Reasons of car drivers for the choice of the car and arguments against the choice of CLEVER in Scenario C in GRAZ and in GREATER THESSALONIKI AREA, 2003 Graz: n=253 positive mentions, 202 negative mentions GTA: n=217 positive mentions, 128 negative mentions Those persons who choose the CLEVER in Scenario C in Graz emphasize its environmentally friendliness, the cost advantages against the use of a car and the advantage of having no parking problems (Figure 7-14). In Greater Thessaloniki Area the cost as well as the time advantages are the most often mentioned arguments for using the CLEVER.

Page - 50 -


CLEVER

60%

Percentage of reasons for the choice of CLEVER

GRAZ 52%

50%

GREATER THESSALONIKI AREA 40%

42%

30%

31%

20%

21%

21%

10%

3%

0%

1%

CLEVER design disliked

4%

CLEVER ideal for short trips

No parking problems

Environmental awareness

Cost advantage

4%

8%

Flexibility, independency

0%

Time advantage

0%

8%

6%

Figure 7-14: Reasons of CLEVER users for the choice of CLEVER in Scenario C in GRAZ and in GREATER THESSALONIKI AREA, 2003 Graz: n=24 mentions GTA: n=113 mentions 7.2.4 Influencing Factors on the Mode Choice The mode shift is not only dependent on the different conditions in the scenarios, but on person as well as on trip related factors. The question which people use which kind of mode for which kind of trips is reflected in the following considering the dependencies of mode choice and –

gender

–

age

–

trip purpose and

–

trip length.

Page - 51 -


CLEVER

7.2.4.1 Mode Choice and Gender The modal shift related to gender in the actual state in Graz shows that nearly half of all trips made by men are car (driver) trips, whereas the mode choice of women is more balanced; they make their trips quite equally on foot, by car and by public transport (Figure 7-15 and Table 7-4). A look at the mode shift towards CLEVER in the three scenarios presents that in Scenario A men and women choose CLEVER to an equal share. However, men only substitute car driver trips by CLEVER trips, while women shift from car driver as well as from car passenger trips. In Scenario B men act the same way as in Scenario A, which is indicated by the identical modal split in both scenarios. Women make use of their chance to save time using CLEVER and substitute public transport as well as additional car (driver) trips by CLEVER, which results in a higher share of CLEVER trips made by women (3,5%) than by men (1,4%). In Scenario C CLEVER trips made by men are reduced to 1,2% due to the rising fuel prices, which also affects the costs of CNG and induce some men to return to the originally used car, which explains the increase of male car driver trips compared to Scenario B. Men also substitute car driver as well as motorcycle trips by bicycle in this scenario. The share of CLEVER trips made by women stays constant while the car driver trips further decrease for the benefit of public transport and bicycle trips. On foot

17.1%

Bicycle

14.5%

Motorcycle

1.2%

Public Transport

15.1%

CLEVER

5.0%

Car passenger

24.5%

17.1%

14.5% 11.2% 0.5% 23.9%

1.2% 15.1% 1.4% 5.0%

12.3% 47.0%

male

female

Actual state

17.1%

23.9%

1.2% 15.1% 1.4% 5.0%

17.1%

24.5%

14.6% 11.2% 0.5% 22.3%

1.1% 15.1% 1.2% 5.0%

11.4% 0.5% 22.5%

1.4%

3.5%

3.5%

11.8%

11.8%

11.8% 45.9%

45.6% 26.7%

male

24.5%

14.5% 11.2% 0.5%

45.6% 27.6%

Car driver

24.5%

female

Scenario A

26.3%

male

female

Scenario B

25.8%

male

female

Scenario C

Figure 7-15: Modal split related to gender in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips

Page - 52 -


Table 7-4:

Modal split related to gender in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips Public Transport

Moped/ motorcycle

Bicycle

On Foot

Sum

N (trips)

Actual state

CLEVER

male

47,0%

5,0%

0,0%

15,1%

1,2%

14,5%

17,2%

100%

464.100

female

27,7%

12,3%

0,0%

23,9%

0,5%

11,2%

24,5%

100%

467.600

Scenari oA

Car passenger

male

45,6%

5,0%

1,4%

15,1%

1,2%

14,5%

17,2%

100%

464.100

female

26,7%

11,8%

1,4%

23,9%

0,5%

11,2%

24,5%

100%

467.600

Scenari oB

Car driver

male

45,6%

5,0%

1,4%

15,1%

1,2%

14,5%

17,2%

100%

464.100

female

26,3%

11,8%

3,5%

22,3%

0,5%

11,2%

24,5%

100%

467.600

Scenari oC

Modal Split in %

CLEVER

male

45,9%

5,0%

1,2%

15,1%

1,1%

14,6%

17,2%

100%

464.100

female

25,8%

11,8%

3,5%

22,5%

0,5%

11,4%

24,5%

100%

467.600

In Greater Thessaloniki Area the discrepancy between male and female car drivers is quite obvious in the actual state as well as in the three scenarios (Figure 7-16 and Table 7-5). While for two third of all trips made by men the car is used, women mainly walk or use public transport. Under this background it is interesting to see that in Scenario A and B men not only shift from car to CLEVER but to a great extent from public transport, which leads to the assumption that men in Greece are not very keen on using public transport preferring the advantages of using an own vehicle. Women substitute mainly car driver trips by CLEVER and to a far smaller extent public transport trips.

Page - 53 -


Trip skipped On foot Bicycle Motorcycle Public Transport


CLEVER

1.4% 14.4%

14.4%

14.4%

0.4% 4.3%

0.4% 4.3% 4.0%

0.4% 4.3% 4.0%

34.6%

12.0% 9.7%

0.9%

16.7%

34.6%

17.4%

0.9%

16.7% 34.6%

9.2% 26.5%

26.5% 9.2%

27.3% 5.4% 18.8%

51.0%

18.5%

Car driver male

female

Actual state

0.9% 30.1%

5.7% 50.2%

18.4%

14.3%

male

37.5%

8.2% 0.9% 18.4%

9.2%

59.3%

0.6% 4.3%

6.5% 18.4%

41.1%

14.0%

female

male

Scenario A

female

Scenario B

12.4% 12.6%

male

female

Scenario C

Figure 7-16: Modal split related to gender in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n=474 trips In Scenario C the highest share of CLEVER trips among men and women can be realised. The share of (male and female) car trips is reduced significantly and the share of public transport trips made by women increases a lot. Anyhow it can be seen that in the Greek case study city the major part of the CLEVER users are men. Table 7-5:

Modal split related to gender in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n=474 trips

Modal split against gender in GRETER THESSALONIKI AREA Moped/ Bicycle motorcycle

On Foot

Trip skipped

Sum

N (trips)

Actual state

Public Transport

male

59,3%

9,7%

0,0%

12,0%

4,3%

0,4%

14,4%

0,0%

100%

1.069.300

female

18,5%

18,8%

0,0%

27,3%

0,9%

0,0%

34,6%

0,0%

100%

1.046.900

Scenari oA

Car CLEVER passenger

male

51,0%

9,2%

16,7%

4,1%

4,3%

0,4%

14,4%

0,0%

100%

1.069.300

female

14,3%

18,4%

5,4%

26,5%

0,9%

0,0%

34,6%

0,0%

100%

1.046.900

Scenari oB

Car driver

male

50,2%

9,2%

17,4%

4,1%

4,3%

0,4%

14,4%

0,0%

100%

1.069.300

female

14,0%

18,4%

5,7%

26,5%

0,9%

0,0%

34,6%

0,0%

100%

1.046.900

Scenari oC

Modal Split in %

male

41,1%

9,2%

18,4%

8,2%

4,3%

0,6%

16,7%

1,4%

100%

1.069.300

female

12,6%

12,4%

6,5%

30,1%

0,9%

0,0%

37,6%

0,0%

100%

1.046.900

Page - 54 -


CLEVER

7.2.4.2 Mode Choice and Age The comparison of mode choice and age shows that the target group for CLEVER users in Graz has to be assumed to include persons aged 46 and older (Table 7-6). Figure 7-17 presents exemplary the modal shift against age in Graz in Scenario C.

On foot

17.3%

24.5%

20.3%

15.8%

Bicycle Motorcycle

10.0% 0.2%

0.2%

14.0%

0.9% 4.7%

Public Transport

8.1%

13.9%

13.8%

3.0%

28.4%

4.9%

27.3%

7.7%

30.7%

5.7%

CLEVER

0.0%

Car passenger

15.4%

Car driver

12.5%

16 – 25 years

47.2%

10.2%

43.0%

20.3%

26 - 45 years

46 – 65 years

> 65 years

Figure 7-17: Modal split related to age in GRAZ in Scenario C, 2003, n=557 trips Table 7-6:

Modal split related to age in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips

Modal split against age in GRAZ

Scenario C

Scenario B

Scenario A

Actual state

Modal Split in % 16 – 25 years 26 – 45 years 46 – 65 years > 65 years 16 – 25 years 26 – 45 years 46 – 65 years > 65 years 16 – 25 years 26 – 45 years 46 – 65 years > 65 years 16 – 25 years 26 – 45 years 46 – 65 years > 65 years

Car driver

Car passenger

12,5%

15,4%

0,0%

30,7%

3,0%

14,0%

47,5%

5,3%

0,0%

13,8%

0,3%

45,4%

7,7%

0,0%

16,4%

27,2%

10,2%

0,0%

12,5%

15,4%

47,2%

CLEVER

Public Transport

Moped/ motorcycle

Bicycle

On Foot

Sum

N (trips)

24,5%

100%

201.900

15,7%

17,3%

100%

373.900

0,2%

10,0%

20,3%

100%

262.200

27,3%

0,0%

7,0%

28,4%

100%

93.600

0,0%

30,7%

3,0%

14,0%

24,5%

100%

201.900

4,7%

0,9%

13,8%

0,3%

15,7%

17,3%

100%

373.900

43,8%

7,7%

1,6%

16,4%

0,2%

10,0%

20,3%

100%

262.200

21,5%

10,2%

5,7%

27,3%

0,0%

7,0%

28,4%

100%

93.600

12,5%

15,4%

0,0%

30,7%

3,0%

14,0%

24,5%

100%

201.900

47,2%

4,7%

0,9%

13,8%

0,3%

15,7%

17,3%

100%

373.900

43,2%

7,7%

5,1%

13,5%

0,2%

10,0%

20,3%

100%

262.200

21,0%

10,2%

6,2%

27,3%

0,0%

7,0%

28,4%

100%

93.600

12,5%

15,4%

0,0%

30,7%

3,0%

14,0%

24,5%

100%

201.900

47,2%

4,7%

0,9%

13,8%

0,2%

15,8%

17,3%

100%

373.900

43,0%

7,7%

4,9%

13,9%

0,2%

10,0%

20,3%

100%

262.200

20,4%

10,2%

5,7%

27,3%

0,0%

8,1%

28,4%

100%

93.600

Page - 55 -


CLEVER

In Greater Thessaloniki Area the majority of the CLEVER users are between 46 and 65 years old (Table 7-7 and exemplary for Scenario C Figure 7-18), followed by persons aged 26 to 45 years. It is assumed that the main argument for this distribution are the relatively high purchase costs – older people can afford the CLEVER more easily than younger ones. Trip skipped

0.3%

On foot

19.8% 32.2%

Bicycle Motorcycle Public Transport

1.6%

0.4% 1.4% 24.9%

0.1% 5.2% 14.2%

27.2% 0.5% 0.5%

45.0%

14.5%

7.9% 9.1%

CLEVER

35.0%

4.3%

Car passenger

20.3%

Car driver

16.1%

42.1%

36.0%

0.5%

1.7%

21.8%

9.4% 7.9%

16 – 25 years

26 – 45 years

46 – 65 years

> 65 years

Figure 7-18: Modal split related to age in GREATER THESSALONIKI AREA in Scenario C, 2003, n=474 trips

Page - 56 -


Table 7-7:

CLEVER

Modal split related to age in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n=474 trips

Modal split against age in GREATER THESSALONIKI AREA

Scenario C

Scenario B

Scenario A

Actual state

Modal Split in % Car driver 16 – 25 years 26 – 45 years 46 – 65 years > 65 years 16 – 25 years 26 – 45 years 46 – 65 years > 65 years 16 – 25 years 26 – 45 years 46 – 65 years > 65 years 16 – 25 years 26 – 45 years 46 – 65 years > 65 years

Car passenger

CLEVER

Public Transport

Moped/ motorcycle

Bicycle

On Foot

Trip skipped

Sum

N (trips)

19,6%

20,3%

0,0%

26,0%

1,5%

0,4%

32,2%

0,0%

100%

691.900

50,7%

10,2%

0,0%

16,2%

5,2%

0,1%

17,6%

0,0%

100%

819.900

52,4%

13,5%

0,0%

14,3%

0,5%

0,0%

19,3%

0,0%

100%

479.600

20,2%

9,4%

0,0%

25,4%

0,0%

0,0%

45,0%

0,0%

100%

124.800

18,9%

20,3%

2,9%

23,8%

1,5%

0,4%

32,2%

0,0%

100%

691.900

45,0%

9,1%

8,6%

14,3%

5,2%

0,1%

17,6%

0,0%

100%

819.900

35,8%

13,5%

29,5%

1,3%

0,5%

0,0%

19,3%

0,0%

100%

479.600

18,5%

9,4%

1,8%

25,4%

0,0%

0,0%

45,0%

0,0%

100%

124.800

18,3%

20,3%

3,5%

23,8%

1,5%

0,4%

32,2%

0,0%

100%

691.900

44,7%

9,1%

9,0%

14,3%

5,2%

0,1%

17,6%

0,0%

100%

819.900

35,1%

13,5%

30,2%

1,3%

0,5%

0,0%

19,3%

0,0%

100%

479.600

18,4%

9,4%

1,8%

25,4%

0,0%

0,0%

45,0%

0,0%

100%

124.800

16,1%

20,3%

4,3%

24,9%

1,5%

0,4%

32,2%

0,3%

100%

691.900

42,1%

9,1%

7,9%

14,2%

5,2%

0,1%

19,8%

1,7%

100%

819.900

21,9%

0,5%

35,0%

14,5%

0,5%

0,5%

27,2%

0,0%

100%

479.600

7,9%

9,4%

1,7%

36,0%

0,0%

0,0%

45,0%

0,0%

100%

124.800

7.2.4.3 Mode Choice and Trip Purpose The distribution of mode choice and trip purpose shows that in the actual state in Graz business and service trips bringing and picking up family members are mainly made by car (driver), commuter trips by car (driver) and by public transport, education trips mostly by public transport, by bicycle and on foot and shopping as well as leisure trips by car, by public transport and on foot (Table 7-8).

Page - 57 -


Table 7-8:

CLEVER

Modal split related to trip purpose in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips

Modal split against trip purpose in GRAZ Car driver

Car passenger

Business

66,0%

5,6%

0,0%

9,8%

0,2%

9,4%

8,9%

100%

69.800

Commuter

49,2%

3,9%

0,0%

19,5%

0,8%

13,3%

13,4%

100%

215.000

Education

7,1%

10,7%

0,0%

35,2%

2,3%

21,3%

23,4%

100%

134.200

Shopping & errands

31,7%

8,8%

0,0%

19,7%

0,4%

10,8%

28,7%

100%

244.600

Leisure

35,7%

14,4%

0,0%

15,1%

0,8%

12,1%

21,9%

100%

226.900

Bringing & picking up

66,9%

0,0%

0,0%

9,1%

0,0%

5,0%

19,0%

100%

41.100

Business

66,0%

2,5%

3,2%

9,8%

0,2%

9,4%

8,9%

100%

69.800

Commuter

49,2%

3,9%

0,0%

19,5%

0,8%

13,3%

13,4%

100%

215.000

Education

6,3%

10,7%

0,8%

35,2%

2,3%

21,3%

23,4%

100%

134.200

Shopping & errands

29,5%

8,8%

2,2%

19,7%

0,4%

10,8%

28,7%

100%

244.600

Leisure

33,8%

14,4%

1,9%

15,1%

0,8%

12,1%

21,9%

100%

226.900


66,9%

0,0%

0,0%

9,1%

0,0%

5,0%

19,0%

100%

41.100

Business

66,0%

2,5%

3,2%

9,8%

0,2%

9,4%

8,9%

100%

69.800

Commuter

48,2%

3,9%

4,5%

16,0%

0,8%

13,3%

13,4%

100%

215.000

Education

6,3%

10,7%

0,8%

35,2%

2,3%

21,3%

23,4%

100%

134.200

Shopping & errands

29,5%

8,8%

2,2%

19,7%

0,4%

10,8%

28,7%

100%

244.600

Leisure

33,8%

14,4%

1,9%

15,1%

0,8%

12,1%

21,9%

100%

226.900


66,9%

0,0%

0,0%

9,1%

0,0%

5,0%

19,0%

100%

41.100

Business

66,0%

2,5%

3,2%

9,8%

0,2%

9,4%

8,9%

100%

69.800

Commuter

48,3%

3,9%

4,4%

16,0%

0,6%

13,5%

13,4%

100%

215.000

Education

6,4%

10,7%

0,7%

35,2%

2,3%

21,3%

23,4%

100%

134.200

Shopping & errands

29,2%

8,8%

2,0%

20,1%

0,4%

10,8%

28,7%

100%

244.600

Leisure

33,5%

14,4%

1,7%

15,1%

0,8%

12,6%

21,9%

100%

226.900


66,9%

0,0%

0,0%

9,1%

0,0%

5,0%

19,0%

100%

41.100

Scenario C

Scenario B

Scenario A

Actual state

Modal Split in %

CLEVER

Public Transport

Moped/ motorcycle

Bicycle

On Foot

Sum

N (trips)

The mode shift towards CLEVER referring to the trip purpose comes in Scenario A from business trips made as car passengers and from education, shopping and leisure trips made by car (drivers). In Scenario B commuter trips made by car (drivers) and by public transport are added to the CLEVER share of Scenario A. In Scenario C the relatively highest share of CLEVER trips is made for commuter (4,4%) and for business trips (3,2%) (Figure 7-19), whereby the shift of the CLEVER business trips comes again from car passengers, while commuter trips made by CLEVER originally were made by car drivers respectively by public transport. In addition to that commuter trips made by car (drivers) are not only substituted by CLEVER but by public transport and by bicycle trips. Leisure/car driver trips are also shifted to CLEVER as well as to bicycle.

Page - 58 -

Benefits for urban traffic – D9: October 2005 On foot

8.9%

Bicycle Motorcycle

9.4%

Public Transport

CLEVER

0.2% 9.8% 3.2% 2.5%

Car passenger

CLEVER

13.4% 23.4% 13.5%

28.7%

12.6%

0.6% 16.0%

21.3%

4.4% 3.9%

2.3%

10.8% 0.4% 20.1% 2.0%

35.2%

66.0%

21.9%

19.0% 5.0% 9.1%

0.8% 15.1% 1.7% 14.4%

8.8%

66.9%

48.3% 0.7% 10.7%

Car driver

29.2%

33.5%

6.4%

Buisness

Commuter

Education

Shopping & errands

Leisure


Figure 7-19: Modal split related to trip purpose in GRAZ in Scenario C, 2003, n=557 trips In Greater Thessaloniki Area the majority of the business and bringing and picking up trips is made – as in Graz – in the actual state by car (drivers). Education trips are mostly made by public transport respectively on foot and shopping as well as leisure trips by car, by public transport and on foot (Table 7-9). Trip skipped On foot Bicycle Motorcycle Public Transport

10.1% 4.1% 1.8%

CLEVER

12.3%

Car passenger

15.1%

19.7% 0.4% 4.4%

23.0% 34.1% 42.6%

1.7% 0.8% 1.2%

16.9% 2.6% 18.0% 2.9%

9.3%

29.6%

Car driver

2.6% 7.3%

14.6%

1.1% 37.7%

14.4%

15.1% 31.6% 17.1%

56.6%

17.2%

58.6% 13.2%

13.1% 22.5%

17.9%

9.1%

Buisness

Commuter

Education

Shopping & errands

Leisure


Figure 7-20: Modal split related to trip purpose in GREATER THESSALONIKI AREA in Scenario C, 2003, n=474 trips In Scenario A and B CLEVER is mainly used for commuter, shopping and leisure trips. Commuter and shopping trips are shifted from car (drivers) and from public transport towards CLEVER, leisure trips additionally from car passengers. All the Page - 59 -


CLEVER

other purposes are shifted from car driver trips towards CLEVER. In Scenario C the main purposes to use CLEVER are the same as in the scenarios before – commuter, shopping and leisure trips. However, commuter trips are not only shifted from car drivers to CLEVER, but to public transport, cycling and walking, and from car passengers to public transport and to walking. Shopping trips made by car (divers) are substituted by CLEVER trips and by walking, while leisure/car driver trips are substituted by CLEVER, public transport and walking. In addition service trips originally made by car (drivers) are skipped in Scenario C. Table 7-9:

Scenario C

Scenario B

Scenario A

Actual state

Modal Split in %

Modal split related to trip purpose in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n=474 trips Car driver

Car CLEVER passenger

Public Transport

Moped/ Bicycle motorcycle

On Foot

Trip skipped

Sum

N (trips) 152.000

Business

63,8%

15,1%

0,0%

7,0%

4,1%

0,0%

10,1%

0,0%

100%

Commuter

57,9%

10,8%

0,0%

14,1%

4,4%

0,0%

12,8%

0,0%

100%

569.700

Education Shopping & errands Leisure Bringing & picking up

11,8%

13,1%

0,0%

30,0%

2,6%

0,0%

42,6%

0,0%

100%

409.700

24,4%

17,1%

0,0%

22,9%

1,2%

0,8%

33,6%

0,0%

100%

458.000

37,5%

19,3%

0,0%

21,7%

1,7%

0,0%

19,7%

0,0%

100%

436.800

85,6%

0,0%

0,0%

0,0%

0,0%

0,0%

14,4%

0,0%

100%

89.900

Business

56,7%

15,1%

7,1%

7,0%

4,1%

0,0%

10,1%

0,0%

100%

152.000

Commuter

46,5%

10,8%

14,2%

11,4%

4,4%

0,0%

12,8%

0,0%

100%

569.700


9,2%

13,1%

2,7%

30,0%

2,6%

0,0%

42,6%

0,0%

100%

409.700

23,9%

17,1%

14,0%

9,4%

1,2%

0,8%

33,6%

0,0%

100%

458.000

28,5%

17,3%

14,5%

18,2%

1,7%

0,0%

19,7%

0,0%

100%

436.800

80,8%

0,0%

4,8%

0,0%

0,0%

0,0%

14,4%

0,0%

100%

89.900

Business

56,5%

15,1%

7,3%

7,0%

4,1%

0,0%

10,1%

0,0%

100%

152.000

Commuter

44,3%

10,8%

16,3%

11,4%

4,4%

0,0%

12,8%

0,0%

100%

569.700


11,3%

13,1%

0,5%

30,0%

2,6%

0,0%

42,6%

0,0%

100%

409.700

23,9%

17,1%

14,0%

9,4%

1,2%

0,8%

33,6%

0,0%

100%

458.000

26,9%

17,3%

16,2%

18,2%

1,7%

0,0%

19,7%

0,0%

100%

436.800

80,7%

0,0%

4,9%

0,0%

0,0%

0,0%

14,4%

0,0%

100%

89.900

Business

56,6%

15,1%

12,3%

1,8%

4,1%

0,0%

10,1%

0,0%

100%

152.000

Commuter

37,7%

2,9%

18,0%

16,9%

4,4%

0,4%

19,7%

0,0%

100%

569.700


9,1%

13,1%

1,1%

31,6%

2,6%

0,0%

42,6%

0,0%

100%

409.700

22,5%

17,1%

15,1%

9,3%

1,2%

0,8%

34,1%

0,0%

100%

458.000

17,9%

13,2%

14,6%

29,6%

1,7%

0,0%

23,0%

0,0%

100%

436.800

58,6%

0,0%

7,3%

2,6%

0,0%

0,0%

14,4%

17,2%

100%

89.900

7.2.4.4 Mode Choice and Trip Length The distribution of trip length according to the mode choice shows for Graz that with rising trip length the share of car (driver) trips increases (Table 7-10 and exemplary for Scenario C Figure 7-21). The highest share of walking trips can naturally be found at a trip length less than 1 km. The optimum trip length for bicycle trips seems to be up to 3 km. The optimum scope of use of the CLEVER required by the users is

Page - 60 -


CLEVER

assumed to be up to 15 km for one trip – the highest share of CLEVER trips is indicated from 3 to 5 km; the driving range of CLEVER is about 160 km. Table 7-10: Modal split related to trip length in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips Modal split against trip length in GRAZ

Scenario C

Scenario B

Scenario A

Actual state

Modal Split in %

Car driver

Car passenger

CLEVER

Public Transport

Moped/ motorcycle

Bicycle

On Foot

Sum

N (trips)

< 1 km

11,1%

2,8%

0,0%

4,8%

0,2%

14,1%

67,0%

100%

216.300

1,1 – 2 km

28,5%

7,5%

0,0%

16,3%

1,0%

25,7%

21,1%

100%

141.200

2,1 – 3 km

37,4%

7,5%

0,0%

25,7%

1,5%

19,6%

8,3%

100%

122.900

3,1 – 5 km

42,0%

10,3%

0,0%

33,4%

1,0%

10,3%

3,3%

100%

172.200

5,1 – 10 km

52,9%

13,2%

0,0%

25,7%

1,1%

5,0%

2,2%

100%

164.700

10,1 – 15 km

64,5%

12,8%

0,0%

17,6%

1,1%

4,1%

0,0%

100%

36.100

15,1 – 20 km

67,1%

9,6%

0,0%

16,4%

0,6%

6,4%

0,0%

100%

17.100

> 20 km

70,9%

15,1%

0,0%

13,4%

0,3%

6,4%

0,0%

100%

61.000

< 1 km

10,6%

2,8%

0,5%

4,8%

0,2%

14,1%

67,0%

100%

216.300

1,1 – 2 km

28,5%

7,5%

0,0%

16,3%

1,0%

25,7%

21,1%

100%

141.200

2,1 – 3 km

35,7%

7,5%

1,7%

25,7%

1,5%

19,6%

8,3%

100%

122.900

3,1 – 5 km

40,1%

10,3%

1,9%

33,4%

1,0%

10,3%

3,1%

100%

172.200

5,1 – 10 km

50,9%

13,2%

2,0%

25,7%

1,1%

5,0%

2,2%

100%

164.700

10,1 – 15 km

61,5%

12,8%

3,0%

17,6%

1,1%

4,1%

0,0%

100%

36.100

15,1 – 20 km

67,1%

9,6%

0,0%

16,4%

0,6%

6,4%

0,0%

100%

17.100

> 20 km

70,9%

11,4%

3,6%

13,4%

0,3%

0,2%

0,0%

100%

61.000

< 1 km

10,5%

2,8%

0,5%

4,8%

0,2%

14,1%

67,0%

100%

216.300

1,1 – 2 km

28,5%

7,5%

0,0%

16,3%

1,0%

25,7%

21,1%

100%

141.200

2,1 – 3 km

35,5%

7,5%

1,9%

25,7%

1,5%

19,6%

8,3%

100%

122.900

3,1 – 5 km

39,9%

10,3%

6,4%

29,0%

1,0%

10,3%

3,1%

100%

172.200

5,1 – 10 km

50,0%

13,2%

2,8%

25,7%

1,1%

5,0%

2,2%

100%

164.700

10,1 – 15 km

61,2%

12,8%

3,2%

17,6%

1,1%

4,1%

0,0%

100%

36.100

15,1 – 20 km

67,1%

9,6%

0,0%

16,4%

0,6%

6,4%

0,0%

100%

17.100

> 20 km

70,9%

11,4%

3,6%

13,4%

0,3%

0,2%

0,0%

100%

61.000

< 1 km

10,1%

2,8%

0,5%

4,8%

0,2%

14,6%

67,0%

100%

216.300

1,1 – 2 km

27,7%

7,5%

0,0%

17,0%

1,0%

25,7%

21,1%

100%

141.200

2,1 – 3 km

35,7%

7,5%

1,7%

25,7%

1,5%

19,6%

8,3%

100%

122.900

3,1 – 5 km

40,1%

10,3%

6,3%

29,0%

1,0%

10,3%

3,1%

100%

172.200

5,1 – 10 km

50,3%

13,2%

2,6%

25,7%

0,8%

5,3%

2,2%

100%

164.700

10,1 – 15 km

61,5%

12,8%

3,0%

17,6%

1,1%

4,1%

0,0%

100%

36.100

15,1 – 20 km

67,1%

9,6%

0,0%

16,4%

0,6%

6,4%

0,0%

100%

17.100

> 20 km

70,9%

11,4%

3,6%

13,4%

0,3%

0,2%

0,0%

100%

61.000

Page - 61 -


CLEVER

8.3%

10.3%

21.1%

On foot

3.1%

1.4% 67.0%

Motorcycle

17.0%


Car driver

29.0% 2.6%

25.7% 6.3%

14.6%

1.7% 7.5%

0.2% 4.1% 1.1% 17.6%

25.7%

25.7%

1.0%

Public Transport

5.3% 0.8%

1.0% 19.6%

Bicycle

2.2%

3.0%

6.4% 0.6% 16.4%

0.3% 13.4% 3.6% 11.4%

9.6%

12.8%

13.2%

10.3%

7.5%

61.5%

67.1%

70.9%

50.3% 0.2% 4.8% 0.5% 2.8%

35.7%

40.1%

27.7%

10.1%

< 1 km

1.1 – 2 km

2.1 – 3 km

3.1 – 5 km

5.1 – 10 km

10.1 – 15 km

15.1 – 20 km

> 20 km

Figure 7-21: Modal split related to trip length in GRAZ in Scenario C, 2003, n=557 trips

In Greater Thessaloniki Area the distribution of the trip length according to the mode is similar to Graz in the actual state (rising share of car driver trips with increasing trip length, highest share of walking trips at less than 1 km, approximately equally distributed public transport trips over trip length) (Table 7-11) and obviously differs especially in Scenario C (Figure 7-22). Trip skipped

4.5%

7.1% 6.7%

On foot

3.1% 0.5% 3.9%

0.5% 1.2% 2.2%

2.1%

16.7%

17.5%

31.7%

Motorcycle

80.0%

Public Transport

40.0% 25.8%

0.3% 2.6% 19.1%

Car passenger

1.6% 2.5% 0.8% 5.4%

Car driver

9.8%

< 1 km

15.5%

6.3%

10.2% 9.1%

15.0%

42.0%

23.2% 15.7%

CLEVER

18.5%

3.1% 23.5%

Bicycle

4.4%

18.6%

4.8%

62.3%

18.5%

22.5%

20.9%

1.1 – 2 km

2.1 – 3 km

17.9%

32.0%

35.0%

3.1 – 5 km

5.1 – 10 km

61.6%

33.8%

10.1 – 15 km

15.1 – 20 km

> 20 km

Figure 7-22: Modal split related to trip length in GREATER THESSALONIKI AREA in Scenario C, 2003, n=474 trips

Page - 62 -


CLEVER

Remarkable in Scenario C is that the highest share of public transport trips can be found on the one hand at 3 to 5 km and on the other hand at trip lengths more than 20 km. The highest share of CLEVER trips is indicated at 5 to 10 km, which corresponds to projected aim that CLEVER is mainly used in urban areas at low trip lengths. Table 7-11: Modal split related to trip length in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n=474 trips Modal split against trip length in GREATER THESSALONIKI AREA

Scenario C

Scenario B

Scenario A

Actual state

Modal Split in %

Car driver

Car passenge r

CLEVER

Public Moped/ Bicycle Transport motorcycle

On Foot

Trip skipped

Sum

N (trips) 555.100

< 1 km

11,3%

5,4%

0,0%

2,5%

1,6%

0,0%

79,3%

0,0%

100%

1,1 – 2 km

42,5%

18,0%

0,0%

22,0%

2,6%

0,3%

14,7%

0,0%

100%

301.700

2,1 – 3 km

44,3%

18,5%

0,0%

23,3%

6,8%

0,0%

7,1%

0,0%

100%

207.800

3,1 – 5 km

48,8%

15,9%

0,0%

28,3%

3,9%

0,0%

3,1%

0,0%

100%

403.800

5,1 – 10 km

43,9%

18,6%

0,0%

34,1%

2,2%

0,0%

1,2%

0,0%

100%

390.600

10,1 – 15 km

65,4%

15,1%

0,0%

17,5%

0,0%

2,1%

0,0%

0,0%

100%

141.000

15,1 – 20 km

80,1%

15,5%

0,0%

4,4%

0,0%

0,0%

0,0%

0,0%

100%

47.000

> 20 km

66,7%

17,9%

0,0%

15,4%

0,0%

0,0%

0,0%

0,0%

100%

69.100

< 1 km

10,5%

5,4%

0,8%

2,5%

1,6%

0,0%

79,3%

0,0%

100%

555.100

1,1 – 2 km

31,5%

18,0%

13,5%

19,4%

2,6%

0,3%

14,7%

0,0%

100%

301.700

2,1 – 3 km

30,5%

18,5%

21,3%

15,8%

6,8%

0,0%

7,1%

0,0%

100%

207.800

3,1 – 5 km

39,0%

13,7%

12,1%

28,3%

3,9%

0,0%

3,1%

0,0%

100%

403.800

5,1 – 10 km

39,4%

18,6%

22,4%

16,2%

2,2%

0,0%

1,2%

0,0%

100%

390.600

10,1 – 15 km

62,2%

15,1%

3,1%

17,5%

0,0%

2,1%

0,0%

0,0%

100%

141.000

15,1 – 20 km

70,7%

15,5%

9,4%

4,4%

0,0%

0,0%

0,0%

0,0%

100%

47.000

> 20 km

66,7%

17,9%

0,0%

15,4%

0,0%

0,0%

0,0%

0,0%

100%

69.100

< 1 km

10,5%

5,4%

0,8%

2,5%

1,6%

0,0%

79,3%

0,0%

100%

555.100

1,1 – 2 km

34,3%

18,0%

10,7%

19,4%

2,6%

0,3%

14,7%

0,0%

100%

301.700

2,1 – 3 km

30,3%

18,5%

21,5%

15,8%

6,8%

0,0%

7,1%

0,0%

100%

207.800

3,1 – 5 km

35,5%

13,7%

15,5%

28,3%

3,9%

0,0%

3,1%

0,0%

100%

403.800

5,1 – 10 km

38,2%

18,6%

23,6%

16,2%

2,2%

0,0%

1,2%

0,0%

100%

390.600

10,1 – 15 km

62,2%

15,1%

3,2%

17,5%

0,0%

2,1%

0,0%

0,0%

100%

141.000

15,1 – 20 km

70,5%

15,5%

9,5%

4,4%

0,0%

0,0%

0,0%

0,0%

100%

47.000

> 20 km

66,7%

17,9%

0,0%

15,4%

0,0%

0,0%

0,0%

0,0%

100%

69.100 555.100

< 1 km

9,8%

5,4%

0,8%

2,5%

1,6%

0,0%

80,0%

0,0%

100%

1,1 – 2 km

22,5%

9,1%

10,2%

19,1%

2,6%

0,3%

31,7%

4,5%

100%

301.700

2,1 – 3 km

20,9%

18,5%

23,2%

23,5%

6,8%

0,0%

7,1%

0,0%

100%

207.800

3,1 – 5 km

32,0%

4,8%

15,7%

40,0%

3,9%

0,6%

3,1%

0,0%

100%

403.800

5,1 – 10 km

35,0%

18,6%

25,8%

16,7%

2,2%

0,0%

1,2%

0,5%

100%

390.600

10,1 – 15 km

62,3%

15,1%

3,1%

17,5%

0,0%

2,1%

0,0%

0,0%

100%

141.000

15,1 – 20 km

61,6%

15,5%

18,5%

4,4%

0,0%

0,0%

0,0%

0,0%

100%

47.000

> 20 km

33,8%

17,9%

6,3%

42,0%

0,0%

0,0%

0,0%

0,0%

100%

69.100

7.3 Market Potential of CLEVER A comparison of the hypothetical use (“Can you imagine to use the CLEVER”) and the actual use (use in one of the three scenarios related to the concrete trips made by the respondents) of CLEVER shows that in fact only 3,7% of the inhabitants of

Page - 63 -


CLEVER

Percentage of hypothetical and actual use of CLEVER

Graz and surprisingly 20,6% of the inhabitants of Greater Thessaloniki Area would use the CLEVER (Figure 7-23). Although the high purchase costs are criticized especially in Greater Thessaloniki Area, in both case study cities most of the persons who would use the CLEVER would buy it (Figure 7-24). However, it is noticeable that in Graz purchase is only one type of considered availability in addition to rental or sharing. Those who answered they would like CLEVER to be given as a gift are not considered to be potential CLEVER users. Due to its small and compact size CLEVER is aimed to be used as a second or third vehicle in a household, which is seen the same way by most of the respondents (Figure 7-24). Nevertheless especially in Greater Thessaloniki Area a high share of the respondents answered that CLEVER would be the single motor vehicle in the household as a car substitute.

100%

80%

60%

GRAZ n = 134

GTA n = 155

40% 24.7% 20%

20.6%

17.2% 3.7%

0%

hypothetical use

actual use in Scenarios

hypothetical use

Figure 7-23: Hypothetical and use of CLEVER in one of the Scenarios in GRAZ and in GREATER THESSALONIKI AREA, 2003

Page - 64 -


CLEVER

80%

GRAZ n = 31

Percentage of types of availability of CLEVER

79%

GREATER THESSALONIKI AREA n = 79

60%

40%

45%

20%

23%

19%

13% 9%

0%

6%

6%

0%

0% Purchase

Rental

Leasing

Gift

Car Sharing

Figure 7-24: Type of hypothetical CLEVER availability in GRAZ and in GREATER THESSALONIKI AREA, 2003

60% 59%

GRAZ n = 22

55%

Percentage of CLEVER Status

GREATER THESSALONIKI AREA n = 78 40%

27% 20% 21%

19% 14%

0%

1%

5% single motor vehicle

second vehicle

third vehicle

forth vehicle

Figure 7-25: Type of hypothetical CLEVER status in GRAZ and in GREATER THESSALONIKI AREA, 2003

Page - 65 -


CLEVER

As a result the target group for CLEVER are car drivers who substitute their trips by CLEVER trips. The potential CLEVER users are in Graz men and women equally, aged 46 years and older. In Greater Thessaloniki Area mainly men would use CLEVER and in general people between 46 – 65 years. The grossed up CLEVER potential in Graz is about 4.000 CLEVER vehicles, which means that 3,7% of the households in Graz would own a CLEVER (Table 7-12). However, in Greater Thessaloniki Area the potential is due to the optimistic results of the survey, about 60.000 vehicles, whereby the very high share of 21,6% of the households would own a CLEVER. Table 7-12: CLEVER potential under Scenario C in GRAZ and in GREATER THESSALONIKI AREA, 2003 GRAZ

GTA

110.000*

280.000o

3,7%

21,6%

116.000**

200.000

515

253oo

% of CLEVER related to number of cars

3,5%

30,4%

Number of CLEVER in total

4.000

60.000

Number of households % of households – CLEVER would be used Number of private cars Car ownership rate [Cars/1.000 inhabitants]

* [STATISTIK AUSTRIA (2005): Grosszählung 2001]; average household size in Graz: 2,03 persons ** [STATISTIK AUSTRIA (2005): Statistik der Kraftfahrzeuge] o

[General Secretariat of National Statistical Service of Greece 2001]; average household size: 2,70 persons [Transportation and Traffic Plan for Greater Thessaloniki Area 1998]

oo

7.4 Comparison Graz – Thessaloniki The idea of a small vehicle like the CLEVER with the advantage of low running costs, especially the low fuel costs, is seen positively in both cities – but more positive in Thessaloniki. All the other characteristics are seen quite equally but – overall – the result of the assessment of CLEVER is more positive in Thessaloniki than in Graz. This might be a reason for the differences in the use of the vehicle – analysed based on the results of the interactive in-depth survey. In all the surveyed scenarios the share of the CLEVER of the modal split in Thessaloniki is more than 4 times as high as in Graz. Another reason for the differences in the modal shift lies in the different mobility behaviour and traffic conditions in these two cities: The actual public transport supply in Graz is better than in Thessaloniki with the consequence of a higher share of the public transport within the modal split. Therefore especially in Scenario C there is a better alternative to the private car and also to the CLEVER. Another reason for the higher number of CLEVER trips in Thessaloniki is the parking situation: In Graz the load of the parking spaces is lower. Therefore the advantage of Page - 66 -


CLEVER

a small car – in Scenario B and C with exclusive designated parking spaces – is not seen as that important as in Thessaloniki. It has to be stated that also the cultural and climatic background might play a role for the differences between Graz and Thessaloniki as well. It seems that the Mediterranean countries have a greater potential for CLEVER as it can be observed also for motorbikes. Over all, the hypothetical use of the CLEVER in Thessalonioki can for sure be seen as far above the average of European cities. Another difference between Graz and Thessaloniki is the use of the CLEVER concerning gender. In Thessaloniki the share of male CLEVER users is higher than in Graz. Concerning age there is no difference between these two cities – in both cases the majority of CLEVER users is within the group of 46 – 65 years old people. Concerning the purpose and length of CLEVER trips there are no big differences between Graz and Thessaloniki.

Page - 67 -


8

CLEVER

BENEFITS FOR URBAN TRAFFIC

The benefits for urban traffic caused by the use of CLEVER are evaluated by means of a cost benefit analysis based (CBA) on the hypothetical change of the modal split in the surveyed scenarios. Excursus: Basic principles of a cost benefit analysis In general economic costs are defined as a monetary evaluation of the consumption of resources. Economic resources consumed in context with transport issues are for example the construction and maintenance of transport infrastructure, harm and damages to persons and nature caused by traffic, time consumption etc. Payment flows between groups of people and organisations (e.g. taxes paid by car drivers) are not considered. Depending on if economic resources are traded on a market or not different problems arise for particular cost components. For the evaluation of resources traded on a market the available market prices are used. Taxes and duties are not considered as they are transfer payments and not consumable resources. The consumption of natural resources, which are not traded on markets, cause an enormous economic loss. Those “negative external effects” of production and consumption activities are seldom borne by the originator, but cause costs for the community. Negative external effects comprise among others CO2 emissions and emissions of hazardous air pollutants, noise costs and to some extent accident costs. Evaluating non-market goods mainly the damage, which is caused, is estimated. Thereby damage caused to the environment is evaluated due to the dose-effect relationship by means of calculating the costs for the regeneration or loss of things or human health [PISCHINGER et al. 1998]. The calculation of the CBA in this project is based on the weighted and projected data of the survey in Graz and in Greater Thessaloniki Area. In both case study cities only the trips by the inhabitants of the respective city in and outside the city boarders are considered. Trips of residents living outside the city and travelling into the surveyed area are not regarded. We know that this amount of travel is nearly the same as the amount of travel of the inhabitants of Graz or Greater Thessaloniki leaving the city limits. Therefore we can talk about the travel in Graz or Greater Thessaloniki as well as of the amount of travel of the inhabitants of Graz or Greater Thessaloniki. The mode shift in the three scenarios and the resulting change in kilometres travelled by individual motorised modes (car driver, moped/motorcycle, CLEVER) cause a change of the regarded values considered for the evaluation of the benefits for urban traffic due to the use of CLEVER. Those values comprise CO2 emissions and Page - 68 -


CLEVER

emissions of hazardous air pollutants, fuel consumption and running costs, noise, road accidents, journey time and parking infrastructure (Figure 8-1).

Modal Shift in the 3 scenarios Traffic volume [vehicle-km]

Air pollutants & CO2-emission

Fuel consumption & running costs

Noise

Road accidents

Journey time

Infrastructure-Parking

Figure 8-1:

Costs

Values

Input

As the values in the actual state and in the scenarios are calculated per day, they are multiplied with the factor 230 (considering only weekdays from Monday to Friday minus holidays and days off) to achieve the values per year. Out of the estimated values the costs are calculated for the year 2003 (rate of inflation considered) and summed up to a general positive or negative evaluation.

Approach of the CBA

8.1 Hazardous Air Pollutants and CO2-Emissions 8.1.1 Basics for the Calculation Evaluating the pollutant emissions a distinction is made between the local effective hazardous air pollutants (CO, HC, NOx, SO2, particles) and the global effective CO2emissions. The emissions caused by car, moped/motorcycle and CLEVER trips are taken into account. Basis for the calculation of the emissions are the weighted and projected trips made by individual motorised modes like car (driver) or moped/motorcycle as result of the of the household survey. Since the velocities of the individual car and motorcycle trips, which are considered in the calculations, are estimations of the respondents, calculated from the information about trip length and trip duration, they were checked according to their plausibility and if necessary corrected. Car and Motorcycle Based on the emission curves for collectives of vehicles from the recommendations for economic feasibility studies for roads (EWS) [FGSV 1997] the emission factors for the different pollutants are calculated for petrol and diesel cars related to speed [km/h] using a regression model (Figure 8-2) according to the below given formula. Page - 69 -


EFVG , j (V ) = (c0 + c1 *V 2 +

CLEVER

c2 ) V

for V > 20 km/h

c ⎫ ⎧ for V ≤ 20 km/h EFVG , j (V ) = min ⎨cs , (c 0 +c1 *V 2 + 2 )⎬ V ⎭ ⎩ Emission factor of the pollutant j of the vehicle group VG EFVG , j (V ) against speed V

[g/(km*vehicle)]

V c0

Average speed per VG [km/h] Parameter [g/vehicle-km]

c1

Parameter

[g*h2/km3]

c2

Parameter

[g/h]

cs

Emission factor cs for congestion within built-up areas [g/vehicle-km] CO emissions against speed

HC emissions against speed

12,00

1,20

Car - Petrol

Car - Petrol 1,00

Car - Diesel Emissions in [g/car-km]

Emissions in [g/car-km]

10,00

8,00

6,00

4,00

Car - Diesel

0,80

0,60

0,40

0,20

2,00

0,00

0,00 0

10

20

30

40

50

60

70

0

80

10

20

30

40

50

60

70

80

Speed [km/h]

Speed [km/h]

SO2 emissions against speed

NOx emissions against speed 0,08

0,60 Car - Petrol 0,50

Car - Petrol

0,07

Car - Diesel

Car - Diesel



0,06 0,40

0,30

0,20

0,05 0,04 0,03 0,02

0,10

0,01 0,00

0,00 0

10

20

30

40

50

60

70

80

0

10

20

Speed [km/h]

30

40

50

60

70

80

Speed [km/h]

Particles against speed

CO2 emissions against speed

0,12 600

Car - Petrol

Car - Petrol

Car - Diesel

500

0,08



0,10

0,06

0,04

Car - Diesel

400

300

200

100

0,02

0

0,00 0

10

20

30

40

Speed [km/h]

Figure 8-2:

50

60

70

80

0

10

20

30

40

50

60

70

80

Speed [km/h]

Emissions related to speed according to petrol and diesel cars for a passenger car collective for 2002 [FGSV 1997]

Page - 70 -


CLEVER

Table 8-1 gives the parameters c0, c1 and c2 of the emission factors for petrol and diesel cars for each relevant pollutant j. At congestion within built-up areas (velocities less than 20 km/h) constant emission loads are assumed according to Table 8-2. Reduction factors (Table 8-3) consider the change of the composition of the collective of vehicles after the year 1990 and are taken for 2003. The allocation of the trips in the dataset according to petrol respectively diesel cars is done at random due to the ratio given in Table 8-4 for Austria and Greece. Table 8-1:

Parameters c0, c1 and c2 of the emission factors (related to speed) for petrol and diesel cars, 1990 [FSGV 1997] Car - petrol

Pollutant

c0

Car - diesel

c1

c2

c0 0,0574

CO

-2,0002

0,0008431

299,98

HC

0,275764

0,000019585

NOx

0,988995

SO2 Particles CO2

Table 8-2:

c1

c2

0,000017

24,24

32,9727

-0,044245 0,000002796

7,9606

0,00011532

8,2855

0,295481 0,000024449

11,92

0,006751

0,000000897

0,5555

0,058791 0,000006394

3,5314

-

-

-

0,00614 0,000010555

3,6378

55,9963

0,0074359

4.604,89

59,7388

0,0064969

3.588,39

Emission factor cs [g/vehicle-km] at congestion within built-up areas for petrol and diesel cars, 1990 [FSGV 1997] cs

Pollutant

Car - petrol

Car - diesel

CO

31,084

1,680

HC

5,049

0,365

NOx

1,234

1,378

SO2

0,066

0,319

-

0,375

343,994

323,978

Particles CO2

Page - 71 -


Table 8-3:

CLEVER

Reduction factor kf (Y) for pollutants (basic year 1990 = 1) for year 1995, 2000, 2005 and 2010 for petrol and diesel cars [FSGV 1997]

kf (Y)

Car - petrol

Car - diesel

Pollutant

1995

2000

2005

2010

1995

2000

2005

2010

CO

0,60

0,33

0,23

0,20

0,72

0,51

0,44

0,42

HC + NOx

0,57

0,26

0,15

0,10

0,85

0,67

0,55

0,50

SO2

0,96

0,91

0,87

0,83

0,95

0,26

0,25

0,25

-

-

-

-

0,76

0,51

0,35

0,25

Particles

Table 8-4:

Ratio of petrol and diesel passenger cars in Austria [STATISTIK AUSTRIA 2004] and Greece [NTZIACHRISTOS L., Z. SAMARAS 2000], 2003

Proportion of petrol and diesel

Car – petrol

Car – diesel

AUSTRIA

53,49%

46,51%

GREECE

86,42%

13,58%

The emission loads are calculated due to the approach described above for the actual state on the basis of the data of the household survey considering car (driver) and motorcycle trips using the actual speed of each surveyed trip. A comparison with the emission loads out of the emission register in Graz [Forschungsgesellschaft fuer Verbrennungskraftmaschinen und Thermodynamik mbH 2004] and GTA [SAMARAS Z. et al. 2002 and NTZIACHRISTOS L., Z. SAMARAS 2000] showed that the calculations are fitting very well. Due to the fact, that the values of the emission registers are calculated much more in detail, these values were taken as reference data for the actual state 2003. In the three scenarios the emissions caused by car/motorcycle trips are estimated considering the percentage change of those trips according to the shift to CLEVER related to the calculated emissions in the actual state. The emissions caused by CLEVER trips (calculation of the CLEVER emissions is described subsequently) are added and the percentage change of the total emissions compared to the (calculated) actual stated is viewed. This calculated percentage change of emissions is taken to estimate the emission loads in the three scenarios related to the reference data from the literature.

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CLEVER

CLEVER Natural gas vehicles emit far less pollutants than petrol or diesel-powered vehicles. It is a lead-free fuel that contains no SO2 and no particulates. Specific emission reductions depend on different factors (e.g. type and make of vehicle) but on the average, anticipated reductions of regulated emissions are as listed in Table 8-5 [European Natural Gas Association 2005]. Table 8-5:

Emissions of CNG vehicles compared to petrol [European Natural Gas Association 2005] and diesel cars (FGW 2005]

Emissions of CNG vehicles compared to petrol and diesel cars Pollutants

Petrol

Diesel

CO

– 76% to – 95%

– 50%

HC

– 85% to – 90%

– 90%

NOx

– 77%

– 90%

SO2

– 100%

– 100%

–

– 100%

– 25%

– 10%

Particles CO2

Estimating the emissions for CLEVER, which is run by a CNG-engine, some assumptions are followed. Relevant for the estimations are the reductions of a CNG engine compared to a petrol engine, as CNG vehicles have to cope with petrol legislation and the CLEVER engine is an original petrol engine converted to a CNG engine. CO, HC and NOx emissions for CLEVER trips are calculated according to the same formula as presented for petrol and diesel cars, considering an average speed lower than 20 km/h (as the CLEVER mainly is used in urban areas) and therefore taking the cs emission factor, which is in a next step reduced according to the reduction percentages for petrol in Table 8-5. The emission loads per day caused by CLEVER trips in the scenarios result from the multiplication of these estimated values with the kilometres travelled per day in the case study cities (Table 8-6). For the calculation of the CO2 emissions a mean value of 60 g CO2/km [VENTURI S. 2003] is applied and as well multiplied with the kilometres travelled per day by CLEVER which results in the CO2 emission loads per day in the scenarios.

Page - 73 -


Table 8-6:

CLEVER

Kilometres travelled per day by CLEVER [km/day] in GRAZ and in GREATER THESSALONIKI AREA in the three scenarios, 2003

Kilometres travelled per day by CLEVER in GRAZ and GTA [km/day] Scenario A GRAZ GTA

Scenario B

Scenario C

116.129 km

163.156 km

158.706 km

1.091.666 km

1.199.018 km

1.561.115 km

While the estimations above are mainly based on established assumptions the following excursus describes the more specific and detailed process of CO, HC and NOx emissions of a CNG engine during a MVEG cycle. 8.1.2 Results The emission loads decline continuously in both case study cities and in all three scenarios. That is caused on the one hand by the shift from car (drivers) to the lower emitting CLEVER in all scenarios and in Scenario C additionally by the shift from car (drivers) to environmentally friendly modes like PT and bicycle. The decrease ranges in Graz between –2,1% and – 3,7% (Table 8-7, Figure 8-3) and in Greater Thessaloniki Area between –11,3% and –17,0% (Table 8-8, Figure 8-4).

Page - 74 -


Table 8-7:

CLEVER

Results of the emission loads in GRAZ in [tons/year] in the actual state [Forschungsgesellschaft fuer Verbrennungskraftmaschinen und Thermodynamik mbH 2004] and in the three scenarios, 2003

Emission loads in GRAZ Actual state 2003

Scenario A

Scenario B

Scenario C

CO

1.380 t

1.339 t

1.332 t

1.325 t

HC

144 t

140 t

139 t

138 t

NOx

656 t

639 t

637 t

633 t

SO2

20 t

19 t

19 t

19 t

Particles

43 t

42 t

41 t

41 t

2.243 t

2.179 t

2.168 t

2.156 t

Absolute difference to the actual state

– 64 t

– 75 t

– 87 t

Relative difference to the actual state [%]

– 2,83%

– 3,35%

– 3,73%

226.471 t

225.890 t

224.760 t


– 4.959 t

– 5.540 t

– 6.670 t


– 2,14%

– 2,39%

– 2,88%

-2,9%

-2,1%

CO2 -2,4%

-4,1%

-3,0%

-3,6%

Particles -4,1%

-3,0%

-3,6%

SO2 -3,4%

NOx -2,6%

-2,9%

-3,5%

-2,9%

Percentage change of emission loads [%] compared to actual state

HC -4,0%

CO

0%

-3,0%

231.430 t

CO2

-3,9%

Sum

-3,5%

[tons/year]

-5%

-10%

-15% A - Launch of CLEVER B - Measures supporting CLEVER -20%

Figure 8-3:

C - Raise of fuel prices

Relative change of the emission loads in GRAZ compared to the actual state in the three scenarios, 2003

Page - 75 -


Table 8-8:

CLEVER

Results of the emission loads in GREATER THESSALONIKI AREA in [tons/year] in the actual state [SAMARAS Z. et al. 2002 and NTZIACHRISTOS L., Z. SAMARAS 2000] and in the three scenarios, 2003

Emission loads in GREATER THESSALONIKI AREA Actual state 2003

Scenario A

Scenario B

Scenario C

CO

47.000 t

40.000 t

39.500 t

38.900 t

HC

6.300 t

5.400 t

5.300 t

5.200 t

NOx

2.100 t

1.850 t

1.830 t

1.820 t

SO2

59 t

50 t

50 t

49 t

Particles

14 t

12 t

12 t

12 t

55.473 t

47.312 t

46.692 t

45.981 t


– 8.161 t

– 8.781 t

– 9.492 t


– 14,68%

– 15,90%

– 17,04%

642.400 t

636.000 t

635.900 t


– 81.800 t

– 88.200 t

– 88.300 t


– 11,29%

– 12,17%

– 12,19%

[tons/year]

Sum

724.200 t

CO2

CO

HC

NOx

SO2

Particles

CO2

-12,2%

-11,3%

-12,2%

-17,5%

-15,0%

-16,3%

-17,5%

-15,0%

-13,4%

A - Launch of CLEVER B - Measures supporting CLEVER

-16,3%

-17,0%

-14,7%

-15,9%

-17,2%

-14,8%

-15%

-20%

Figure 8-4:

-12,2%

-10%

-13,1%

-5%

-16,0%

Percentage change of emission loads [%] compared to actual state

0%


Relative change of the emission loads in GREATER THESSALONIKI AREA compared to the actual state in the three scenarios, 2003

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CLEVER

8.1.3 Costs The costs for hazardous air pollutants (direct emissions emerging directly at the vehicle) include effects on human health (e.g. costs for medical attendance), damage to premises or buildings and harm of vegetation and are calculated according to PISCHINGER et al. [1997] for Graz and ATTIKO METRO [2005] for Greater Thessaloniki Area. The costs for the global effective CO2 are set with 100,70 € per ton for Graz according to the recommendations for economic feasibility studies for roads [FGSV 1997] and with 97,18 € per ton for GTA (Table 8-9). Table 8-9:

Costs [€] per ton hazardous air pollutants [PISCHINGER R., G. SAMMER, F. SCHNEIDER et al. 1998] and per ton CO2 [FGSV 1997] in Austria and in Greece [ATTIKO METRO 2005], 2003

Costs in € per ton emissions CO

HC

NOx

SO2

Particles

CO2

AUSTRIA

23,93

11.962,52

2.392,71

5.287,86

2.487,93

100,70

GREECE

6,80

11.103,14*

3.673,47

4.907,98*

2.309,20*

97,18

* As the costs per ton emission of HC, SO2 and particles have not been not available for Greece, the missing values have been calculated according to the known emission costs in Greece proportional to them in Austria.

In both case study cities savings due to decreasing emission loads and costs can be gained in all three scenarios (Table 8-10, Table 8-11), whereas the emission cost savings in Greater Thessaloniki Area are a multiple of those in Graz due to the higher share of CLEVER trips in GTA.

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CLEVER

Table 8-10: Results of the emission costs in GRAZ in [M €/year] in the actual state and in the three scenarios, 2003 Emission costs in GRAZ [M €/year]

Actual state 2003

Scenario A

Scenario B

Scenario C

CO

0,03 M €

0,03 M €

0,03 M €

0,03 M €

HC

1,72 M €

1,67 M €

1,66 M €

1,66 M €

NOx

1,57 M €

1,53 M €

1,52 M €

1,52 M €

SO2

0,11 M €

0,10 M €

0,10 M €

0,10 M €

Particles

0,11 M €

0,10 M €

0,10 M €

0,10 M €

Sum

3,54 M €

3,43 M €

3,42 M €

3,41 M €


– 0,11 M €

– 0,12 M €

– 0,13 M €


– 2,76%

– 3,26%

– 3,73%

22,81 M €

22,75 M €

22,63 M €


– 0,50 M €

– 0,56 M €

– 0,68 M €


– 2,14%

– 2,39%

– 2,88%

CO2

23,31 M €

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CLEVER

Table 8-11: Results of the emission costs in GREATER THESSALONIKI AREA in [M €/year] in the actual state and in the three scenarios, 2003 Emission costs in GREATER THESSALONIKI AREA [M €/year]

Actual state 2003

Scenario A

Scenario B

Scenario C

CO

0,32 M €

0,27 M €

0,27 M €

0,26 M €

HC

70,18 M €

59,87 M €

59,02 M €

58,22 M €

NOx

7,73 M €

6,79 M €

6,72 M €

6,69 M €

SO2

0,29 M €

0,25 M €

0,24 M €

0,24 M €

Particles

0,03 M €

0,03 M €

0,03 M €

0,03 M €

78,55 M €

67,21 M €

66,27 M €

65,44 M €


– 11,34 M €

– 12,28 M €

– 13,11 M €


– 14,44%

– 15,63%

– 16,69%

62,43 M €

61,81 M €

61,79 M €


– 7,95 M €

– 8,57 M €

– 8,59 M €


– 11,29%

– 12,17%

– 12,19%

Sum

CO2

70,38 M €

8.2 Fuel consumption and running costs 8.2.1 Basics for the Calculation Fuel consumption is regarded for trips made by car drivers, moped/motorcycle riders and CLEVER drivers. For car and motorcycle (respectively petrol and diesel) trips fuel consumption is calculated equivalent to the emissions:

FCVG , f (V ) = (c0 + c1 *V 2 +

c2 ) V

c ⎫ ⎧ FCVG , f (V ) = min ⎨cs , (c 0 +c1 *V 2 + 2 )⎬ V ⎭ ⎩

FCVG , f (V )

for V > 20 km/h for V ≤ 20 km/h

Fuel consumption (petrol, diesel – f) of the vehicle group VG related to speed V

[g/(km*vehicle)]

Page - 79 -


CLEVER

Table 8-12 gives the parameters c0, c1, c2 and cs of the factors of fuel consumption for petrol and diesel cars. The reduction factors are listed in Table 8-13. Table 8-12: Parameters c0, c1, c2 of the factors of fuel consumption (related to speed) and factor of fuel consumption cs [g/vehicle-km] for congestion within built-up areas for petrol and diesel cars, 1990 [FSGV 1997] Fuel

c0

c1

c2

cs

Car - petrol

17,7766

0,0023606

1.461,87

174,357

Car - diesel

18,9647

0,0020625

1.139,17

102,85

Table 8-13: Reduction factor kf (Y) for fuel consumption (basic year 1990 = 1) for year 1995, 2000, 2005 and 2010 for petrol and diesel cars [FSGV 1997] kf(Y)

1995

2000

2005

2010

Car - petrol

0,96

0,91

0,87

0,83

Car - diesel

0,95

0,91

0,86

0,85

Contrary to the calculation of the emissions for the calculation of fuel consumption no reference data from the literature are reverted to, but the calculated values in the actual state based on the data of the household survey are considered for estimating the changes and fuel consumption in the three scenarios. For the calculation of the CNG consumption by CLEVER 22 g CNG/km [VENTURI S. 2003] are applied and multiplied with the kilometres travelled per day by CLEVER in the scenarios (Table 8-6). For all calculations the actual speed per trip was used, calculated out of the relevant data surveyed. 8.2.2 Results Due to the mode shift from car (driver) to CLEVER in the scenarios (compare chapter 7.2.1) and the resulting decreasing kilometres travelled by car (Table 8-16 and Table 8-17) the fuel consumption of petrol and diesel declines in both case study cities (Table 8-14, Table 8-15 and Figure 8-5, Figure 8-6). Equivalent to that the CNG consumption increases, whereas in Graz the maximum CNG consumption is registered in Scenario B, while in Thessaloniki the most CNG is consumed in Scenario C (Figure 8-7). In the actual state (2003) CNG is not at all used in transport in Greece, in Austria the number of CNG vehicles added up to 250 vehicles [BGW 2003], whereas most of them are busses or taxis.

Page - 80 -


CLEVER

Table 8-14: Fuel consumption in [M l/year] for petrol and diesel and in [t/year] for CNG in GRAZ in the actual state and in the three scenarios, 2003 Fuel consumption (petrol, diesel, CNG) per year in GRAZ Actual state 2003

Fuel

Scenario A

Scenario B

Scenario C

Petrol [M l/year]

47,22 M l

45,80 M l

45,51 M l

45,30 M l

Diesel [M l/year]

20,42 M l

19,81 M l

19,68 M l

19,59 M l

Sum

67,64 M l

65,60 M l

65,19 M l

64,89 M l


– 2,04 M l

– 2,45 M l

– 2,75 M l


– 3,01%

– 3,61%

– 4,07%

587,60 t

825,60 t

803,10 t

CNG [t/year]

–

160,00

Fuel consumption in [M l / year]

0 - Actual state A - Launch of CLEVER

120,00

B - Measures supporting CLEVER C - Raise of fuel prices

80,00

40,00

47,22 45,80 45,51 45,30 20,42 19,81 19,68 19,59

0,00

Petrol

Figure 8-5:

Diesel

Fuel consumption in [M l/year] for petrol and diesel in GRAZ in the actual state and in the three scenarios, 2003

Page - 81 -


CLEVER

Table 8-15: Fuel consumption in [M l/year] for petrol and diesel and in [t/year] for CNG in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003 Fuel consumption (petrol, diesel, CNG) per year in GTA Actual state 2003

Fuel

Scenario A

Scenario B

Scenario C

Petrol [M l/year]

152,83 M l

129,90 M l

127,99 M l

126,08 M l

Diesel [M l/year]

10,74 M l

9,13 M l

9,00 M l

8,86 M l

163,57 M l

139,03 M l

136,99 M l

134,94 M l


– 24,54 M l

– 26,58 M l

– 28,63 M l


– 15,00%

– 16,25%

– 17,50%

5.523,80 t

6.067,00 t

7.899,20 t

Sum

–

CNG [t/year]

160,00

Fuel consumption in [M l / year]

152,83

120,00

0 - Actual state 129,90 127,99 126,08

A - Launch of CLEVER B - Measures supporting CLEVER C - Raise of fuel prices

80,00

40,00

10,74

0,00

Petrol

Figure 8-6:

9,13

8,99

8,86

Diesel

Fuel consumption in [M l/year] for petrol and diesel in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003

Page - 82 -


CLEVER

8.000 7.899

CNG consumption in [t / year]

A - Launch of CLEVER B - Measures supporting CLEVER

6.000


6.067 5.524

4.000

2.000

588

0

826

803

Graz

Figure 8-7:

Greater Thessaloniki Area

CNG consumption in [t/year] in GRAZ and in GTA in the three scenarios, 2003

Table 8-16: Kilometres travelled per day [km/day] (including car driver, motorcycle/moped and CLEVER trips) in GRAZ in the actual state and in the three scenarios, 2003 Kilometres travelled per day [km/day] in GRAZ Trips

Actual state 2003

Scenario A

Scenario B

Scenario C

Car driver, motorcycle/ moped [km/day]

4.068.800 km

4.008.200 km

3.991.500 km

3.983.100 km

116.100 km

163.200 km

158.700 km

4.124.300 km

4.154.700 km

4.141.800 km


+ 55.500 km

+ 85.900 km

+ 73.000 km


+ 1,37%

+ 2,11%

+ 1,80%

CLEVER [km/day] Sum

– 4.068.800 km

Page - 83 -


CLEVER

Table 8-17: Kilometres travelled per day [km/day] (including car driver, motorcycle/moped and CLEVER trips) in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003 Kilometres travelled per day [km/day] in GREATER THESSALONIKI AREA Trips

Actual state 2003

Scenario A

Scenario B

Car driver, motorcycle/ moped [km/day]

7.572.600 km

6.977.400 km

6.887.100 km

4.693.300 km

–

1.091.700 km

1.199.000 km

1.561.100 km

7.572.600 km

8.069.100 km

8.086.100 km

6.254.400 km


+ 496.500km

+ 513.500 km

– 1.318.200 km


+ 6,56%

+ 6,78%

– 17,41 %

CLEVER [km/day] Sum

Scenario C

8.2.3 Costs The running costs for passenger cars contain fuel costs and basic values for running costs. According to FGSV [1997] the basic values for running costs include amortisation of vehicles, maintenance and servicing, wear of tyres and oil consumption. They are given with 0,09 €/vehicle-km for Austria and 0,14 €/vehiclekm for Greece (Table 8-20) and are calculated by the kilometres travelled in the scenarios. The value for Greece seems to be quite high, but several checks have shown, that this value should be taken as basis for the calculation. The basic values for running costs for CLEVER are assumed to be the same as for passenger cars. For the calculation of the fuel costs the net prices (without any taxes) of the average fuel prices of the year 2003 for petrol, diesel and CNG in Austria and Greece are taken (Table 8-18, Table 8-19). Table 8-18: Average fuel prices for petrol and diesel [€/l] [OEAMTC 2005] and for CNG [€/kg] [FGW 2005)] in AUSTRIA in 2003 AUSTRIA Fuel

Gross price

Petroleum tax

Tax for natural gas

Purchase tax (20%)

Net price

Petrol [€/l]

0,850

0,41

-

0,15

0,290

Diesel [€/l]

0,740

0,28

-

0,14

0,320

CNG [€/kg]

0,700

-

0,084*

0,12

0,499

* The tax for natural gas is in Austria subject to act of tax for natural gas BGBl. Nr. 201/1996 last modified by BGBl. I Nr. 71/2003 0,066 €/m3 [Oesterreichisches Bundesrecht 2003]. The

Page - 84 -


CLEVER

conversion from m3 CNG into kg is done via the specific density of CNG, which is 0,784 kg [VEST Energie Marketing 2005].

Table 8-19: Avarage fuel prices for petrol and diesel [€/l] [Ministry of Development 2004] in GREECE in 2003 and for CNG [€/kg] according to assumptions GREECE Fuel

Gross price

Petroleum tax

Tax for natural gas

Purchase tax (20%)

Net price

Petrol [€/l]

0,7660

0,4180

-

0,1182

0,2298

Diesel [€/l]

0,6792

0,3538

-

0,0753

0,2500

N/A

N/A

N/A

N/A

0,3050*

CNG [€/kg]*

* CNG is used in Greece mainly for house heating and industrial purposes, but not in transport. The CNG net price in Greece is therefore an assumption, calculated according to the fuel prices in Greece proportional to them in Austria.

Table 8-20: Basic value for running costs for passenger cars and for CLEVER in [€/vehicle-km] in AUSTRIA [FGSV 1997] and in GREECE [Ministry for the Environment, Physical Planning and Public Works 2001], 2003 Basis value for running costs for passenger cars without fuel costs Running cost value per vehicle-km [€/vehicle-km]

AUSTRIA

GREECE

0,09117

0,13850

The results of the running costs in the actual state and in the three scenarios with the rate of change are presented in Table 8-25 and Figure 8-8 for Graz and in Table 8-26 and Figure 8-9 for Greater Thessaloniki Area. The results of the components fuel costs (Table 8-21, Table 8-22) and basic values for running costs (Table 8-23, Table 8-24) are listed in the tables before. While the fuel costs decrease in both case study cities in all three scenarios (despite the additional trips by individual motorised modes, which result from the shift from PT and car passengers to CLEVER) since CNG is more economic – the energy consumption is less than 2,4 l gasoline equivalent, the basic values for running costs increase because of the fact that these values are the same for passenger cars and CLEVER and the shift to CLEVER not only comes from car drivers but also from the other modes (PT, car passenger), where these components were irrelevant before. As the basic values for running costs exceed the fuel costs the total running costs increase as a result. An exception is Scenario C in Greater Thessaloniki Area, where

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CLEVER

the basic values and the running costs decrease because of the decreasing kilometres travelled by individual motorised modes. Table 8-21: Fuel costs in [M €/year] for petrol, diesel and CNG in GRAZ in the actual state and in the three scenarios, 2003 Energy costs (petrol, diesel, CNG) in [M €/year] in GRAZ Fuel

Actual state 2003

Scenario A

Scenario B

Scenario C

Petrol [M €/year]

13,69 M €

13,28 M €

13,20 M €

13,14 M €

Diesel [M €/year]

6,53 M €

6,34 M €

6,30 M €

6,27 M €

–

0,29 M €

0,41 M €

0,40 M €

20,22 M €

19,91 M €

19,91 M €

19,81 M €


– 0,31 M €

– 0,31 M €

– 0,41 M €


– 1,56%

– 1,58%

– 2,09%

CNG [M €/year] Sum

Table 8-22: Fuel costs in [M €/year] for petrol, diesel and CNG in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003 Energy costs (petrol, diesel, CNG) in [M €/year] in GTA Fuel

Actual state 2003

Scenario A

Scenario B

Scenario C

Petrol [M €/year]

35,12 M €

29,85 M €

29,41 M €

28,97 M €

Diesel [M €/year]

0,27 M €

0,23 M €

0,23 M €

0,22 M €

–

1,15 M €

1,26 M €

1,65 M €

35,39 M €

31,23 M €

30,90 M €

30,84 M €


– 4,16 M €

– 4,49 M €

– 4,55 M €


– 11,75%

– 12,68%

–12,85%

CNG [M €/year] Sum

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CLEVER

Table 8-23: Basic values for running costs for passenger cars and for CLEVER in [M €/year] in GRAZ in the actual state and in the three scenarios, 2003 Basic values for running costs for passenger cars and for CLEVER in GRAZ Vehicles Passenger cars [M €/year]

Actual state 2003

Scenario A

Scenario B

Scenario C

85,32 M €

84,05 M €

83,70 M €

83,52 M €

–

2,44 M €

3,42 M €

3,33 M €

85,32 M €

86,49 M €

87,12 M €

86,85 M €

+ 1,17 M €

+ 1,80 M €

+ 1,53 M €

+ 1,37%

+ 2,11%

+ 1,80%

CLEVER [M €/year] Sum

Absolute difference to the actual state Relative difference to the actual state [%]

Table 8-24: Basic values for running costs for passenger cars and for CLEVER in [M €/year] in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003 Basic values for running costs for passenger cars and for CLEVER in GTA Vehicles Passenger cars [M €/year]

Actual state 2003

Scenario A

Scenario B

Scenario C

241,29 M €

222,32 M €

219,45 M €

149,54 M €

–

34,78 M €

38,20 M €

49,74 M €

241,29 M €

257,10 M €

257,65 M €

199,28 M €

+ 15,81 M €

+ 16,36 M €

– 42,01 M €

+ 6,56%

+ 6,78%

– 17,41%



Page - 87 -


CLEVER

Table 8-25: Running costs (sum of energy costs and basic values for running costs) for passenger cars and for CLEVER in [M €/year] in GRAZ in the actual state and in the three scenarios, 2003 Running costs (sum of energy costs and basic values for running costs) for passenger cars and for CLEVER in GRAZ Vehicles Passenger cars [M €/year]

Actual state 2003

Scenario A

Scenario B

Scenario C

105,55 M €

103,67 M €

103,20 M €

102,93 M €

–

2,73 M €

3,83 M €

3,73 M €

105,55 M €

106,40 M €

107,03 M €

106,66 M €

+ 0,85 M €

+ 1,48 M €

+ 1,11 M €

+ 0,81%

+ 1,41%

+ 1,05%



300,0

0 - Actual state A - Launch of CLEVER B - Measures supporting CLEVER C - Raise of fuel prices

200,0

Figure 8-8:

107,0

106,7

Running costs

Basic value costs

20,2 19,9 19,9 19,8

2,7 3,8 3,7

Running costs

CLEVER

Fuel costs

2,4 3,4 3,3

Basic value costs

0,3 0,4 0,4

Car

Running costs

Basic value costs

Fuel costs

0,0

CNG costs

50,0

85,3 84,0 83,7 83,5 105,5 103,7 103,2 102,9

100,0

85,3 86,5 87,1 86,9 105,5 106,4

150,0

20,2 19,6 19,5 19,4

Running costs in [M € / year]

250,0

Car & CLEVER

Running costs (sum of energy costs and basic values for running costs) for passenger cars and for CLEVER in [M €/year] in GRAZ in the actual state and in the three scenarios, 2003

Page - 88 -


CLEVER

Table 8-26: Running costs (sum of energy costs and basic values for running costs) for passenger cars and for CLEVER in [M €/year] in GTA in the actual state and in the three scenarios, 2003 Running costs (sum of energy costs and basic values for running costs) for passenger cars and for CLEVER in GREATER THESSALONIKI AREA Vehicles

Actual state 2003

Scenario A

Scenario B

Scenario C

276,68 M €

252,40 M €

249,08 M €

178,74 M €

–

35,94 M €

39,47 M €

51,39 M €

276,68 M €

288,34 M €

288,55 M €

230,13 M €

+ 11,66 M €

+ 11,87 M €

– 46,55 M €

+ 4,21%

+ 4,29%

– 16,82%

Passenger cars [M €/year] CLEVER [M €/year] Sum


300,0

149,5

150,0

276,7 288,3 288,6

B - Measures supporting CLEVER

199,3


230,1

241,3 257,1 257,6

A - Launch of CLEVER

178,7

241,3 222,3 219,4

200,0

Car

Figure 8-9.

Running costs

35,9 39,5 51,4

Running costs

Basic value costs

34,8 38,2 49,7

Basic value costs

CLEVER

Fuel costs

1,2 1,3 1,6

Running costs

Basic value costs

Fuel costs

0,0

CNG costs

50,0

35,4 31,2 30,9 30,8

100,0

35,4 30,1 29,6 29,2

Running costs in [M € / year]

250,0

276,7 252,4 249,1

0 - Actual state

Car & CLEVER

Running costs (sum of energy costs and basic values for running costs) for passenger cars and for CLEVER in [M €/year] in GTA in the actual state and in the three scenarios, 2003

Page - 89 -


CLEVER

8.3 Noise 8.3.1 Basics for the Calculation The assessment of the traffic noise within the boundaries of Graz is carried out considering the traffic noise emissions dependent on the kilometres travelled with passenger cars, motorcycles and CLEVER by the inhabitants of Graz and the persons and apartments who are affected by traffic noise. The following approach is used for an approximation [SAMMER G., F. WERNSPERGER 1994]:

Pa = 37,5 * (log10 ( pkms ) − log10 ( pkma ))

Pa …

Change of share of persons who feel disturbed by noise caused by traffic [%]

pkms … Car kilometres (including car, moped/motorcycle and CLEVER kilometres) in the scenario [km]

pkma … Car kilometres (including car and moped/motorcycle kilometres) in the actual state [km] There is no distinction made between the kilometres travelled by car and those travelled by CLEVER, which would have an influence on the noise emissions. Compared to a gasoline engine noise emission of a CNG engine is quite similar. The CNG engine has smoother combustion, but the higher compression ratio used to increase global engine efficiency (high equivalent octane number) slightly increases the noise level, so that in general there is no advantage of a CNG engine in terms of noise emissions in comparison to a gasoline engine [VENTURI S. 2005]. Table 8-27 shows the kilometres travelled per day in Graz and in the Greater Thessaloniki Area in the actual state and in the three scenarios as input parameters for the approximation presented above. Table 8-27: Kilometres travelled [km] per day (including car driver, motorcycle/ moped and CLEVER trips) in GRAZ and in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003 Kilometres travelled per day [km]

Actual state 2003

Scenario A

Scenario B

Scenario C

GRAZ

4.068.800

4.124.400

4.154.700

4.141.800

GTA

7.572.600

8.069.000

8.086.100

6.254.400

Page - 90 -


CLEVER

8.3.2 Results As a reference number of inhabitants of Graz who feel disturbed by traffic noise in the actual state the available quantity of 96.000 inhabitants (these are about 42%) is taken from a survey about the “Satisfaction of living regarding traffic noise” by SAMMER, WERNSPERGER [1992]. The approximation of the change of share and number of persons who feel disturbed by noise caused by traffic in Graz brought the results presented in Table 8-28. According to the increase of kilometres travelled with an individual motorised mode – car, motorcycle/moped or CLEVER – the noise emissions and the share and number of disturbed persons increase at a minimum in all the three scenarios. Table 8-28: Change of share and number of persons who feel disturbed by noise caused by traffic in GRAZ in the actual state and in the three scenarios, 2003 GRAZ Change of share of persons disturbed by traffic noise [%] Number of persons disturbed by traffic noise in Graz

Actual state 1992 (2003)

Scenario A

Scenario B

Scenario C

-

+ 0,22%

+ 0,34%

+ 0,29%

96.000

96.212

96.327

96.278

As for the Greater Thessaloniki Area no reference data of persons who feel disturbed by traffic noise are available, only the change of share of disturbed persons has been calculated (Table 8-29). After the share increases in the scenarios A and B, it declines due to the decreasing kilometres travelled in scenario C to minus 3,12%. The share of persons who feel disturbed by traffic noise is estimated as 42,5% - this is the value of Graz. The assumption is, that on the one hand the level of traffic noise is higher in Thessaloniki than in Graz but on the other hand the subjective level of disturbance is lower. This leads to the effect, that the share of persons who feel disturbed by traffic noise in Thessaloniki might be the same as in Graz. Therefore these are about 155.000 persons in the city of Thessaloniki.

Page - 91 -


CLEVER

Table 8-29: Change of share and number of persons who feel disturbed by noise caused by traffic in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003 GTA Change of share of persons disturbed by traffic noise [%] Number of persons disturbed by traffic noise in GTA

Actual state 2003

Scenario A

Scenario B

Scenario C

-

+ 1,03%

+ 1,07%

– 3,12%

not available

not available

not available

not available

[155.000]

[156.596]

[156.658]

[150.164]

8.3.3 Costs The costs caused by traffic noise in Graz are calculated according to PISCHINGER, SAMMER, SCHNEIDER et al. [1998], wherein the noise costs are identified to amount to 1,87% of the gross domestic product. This value includes obsolescence of accommodation, medical attendance, costs for pharmaceuticals as well as for cures and relocation. In the year 2002 the traffic noise costs in Austria add up to 3,7 billions Euro [Statistk Austria 2001]. 2,3 M Austrians (28,3%) felt disturbed by noise in their home as a result of a census (Micro census 1998). According to this the noise costs in Austria are determined to be € 1.644,10 (2003) per person who is disturbed by noise, whereas for Greece no noise costs are available (Table 8-30). The noise costs for Greece are estimated based on the costs in Austria and the Gross Domestic Product of these two countries. Therefore about 60% of the costs in Austria are taken for Greece. The results of the (traffic) noise costs in Graz and Thessaloniki are presented in the following table. Table 8-30: Noise costs per person who is disturbed by noise caused by traffic in [€] in AUSTRIA [PISCHINGER R., G. SAMMER, F. SCHNEIDER et al. 1998], 2003 Noise costs

AUSTRIA

Costs per person who is disturbed by noise caused by traffic [€]

1.644,10

GREECE not available [986,5]

Page - 92 -


CLEVER

Table 8-31: (Traffic) Noise costs in [Mio. €/year] in Graz in the actual state and in the three scenarios, 2003 Actual state 1992 (2003)

Scenario A

Scenario B

Scenario C

157,83 M €

158,18 M €

158,37 M €

158,29 M €


+ 0,35 M €

+ 0,54 M €

+ 0,46 M €


+ 0,22%

+ 0,34%

+ 0,29%

GRAZ (Traffic) Noise costs [M €/year]

Table 8-32: (Traffic) Noise costs in [Mio. €/year] in Thessaloniki in the actual state and in the three scenarios, 2003 Actual state 1992 (2003)

Scenario A

Scenario B

Scenario C

152,91 M €

154,48 M €

154,54 M €

148,14 M €


+ 1,57 M €

+ 1,64 M €

-4,77 M €


+ 1,03%

+ 1,07%

– 3,12%

THESSALONIKI (Traffic) Noise costs [M €/year]

8.4 Road accidents 8.4.1 Basics for the Calculation Basis for the calculations of the road accidents in the scenarios are the number of injured persons in the actual state. To minimise the random error due to low numbers of casualties, the average of the number of casualties of five years (1999 – 2003 for Graz; 1996 – 2001 for Greater Thessaloniki Area) is taken (Table 8-33 and Table 8-34).

Page - 93 -


CLEVER

Table 8-33: Number of casualties in road accidents according to modes and severity of injury in GRAZ, average of five years (1999 – 2003) [KfV 2000 to 2004] GRAZ Number of injured persons Road users involved Killed

Seriously injured

Slightly injured

Undefined injured

Car driver

3

25

1.236

1

Car passenger

0

13

358

0

Moped, motorcycle

2

41

278

0

Cyclist

2

42

325

0

Pedestrian

5

50

197

0

Public Transport

0

7

68

0

Truck

0

2

42

0

Others

0

4

34

0

12

184

2.539

1

Sum

Table 8-34: Number of casualties in road accidents according to modes and severity of injury in GREATER THESSALONIKI AREA, average of five years (1996 – 2001) [ROAD ACCIDENTS GTA 2001] GREATER THESSALONIKI AREA Number of injured persons Road users involved Killed

Seriously injured

Slightly injured

Undefined injured

Car driver

47

50

498

-

Car passenger

32

35

437

-

Moped, motorcycle

28

74

619

-

2

2

17

-

32

46

351

-

Public Transport

1

1

48

-

Others

3

1

13

-

145

209

1.983

-

Cyclist Pedestrian

Sum

Page - 94 -


CLEVER

As the number of casualties per mode is dependent on the kilometres travelled with the respective mode the following probability to be killed respectively to be injured is defined for the actual state:

CAm,k =

CAm Km

CAm,k

Probability to be killed respectively to be injured per mode and kilometres travelled per year [Casualties/km] (= Average number of casualties per mode and kilometres travelled per year)

CAm

Average number of casualties per mode and year [Casualties]

Km

Kilometres travelled per mode per year [km]

Table 8-35 and Table 8-36 show the results of the probabilities to be killed and to be injured for Graz and Greater Thessaloniki Area for the actual state dependent on the kilometres travelled. It can be seen in both case study cities that moped and motorcycle riders have the highest risk to be killed or injured in an accident, followed by pedestrians and cyclists. Table 8-35: Probability to be killed respectively to be injured (according to the severity of injury) per mode and kilometres travelled per year [Casualties / 100.000 km] for GRAZ in the actual state GRAZ

Road users involved

Average number of casualties per mode and per 100.000 kilometres travelled (= CAm,k) Killed

Seriously injured

Slightly injured

Undefined injured

Car driver

0,08

0,63

30,73

0,02

Car passenger

0,04

1,49

39,81

0,04

Moped, motorcycle

3,86

87,11

596,46

0,86

Cyclist

0,54

12,71

97,87

0,06

Pedestrian

2,39

24,79

97,86

0,00

Public Transport

0,00

0,43

4,18

0,00

Page - 95 -


CLEVER

Table 8-36: Probability to be killed respectively to be injured (according to the severity of injury) per mode and kilometres travelled per year [Casualties / 100.000 km] for GREATER THESSALONIKI AREA in the actual state GREATER THESSALONIKI AREA

Road users involved

Average number of casualties per mode and per 100.000 kilometres travelled (= CAm,k) Killed

Seriously injured

Slightly injured

Undefined injured

Car driver

0,64

0,68

6,75

0,00

Car passenger

1,62

1,78

22,11

0,00

13,82

36,46

303,68

0,00

Cyclist

4,50

5,85

46,73

0,00

Pedestrian

7,55

11,04

83,60

0,00

Public Transport

0,05

0,04

1,73

0,00

Moped, motorcycle

In the next step those probabilities are multiplied with the kilometres travelled per mode in the three scenarios which results in the predicted number of casualties:

C m, s = CAm, k * K m, s Cs

Number of casualties per mode in the scenarios per year

CAm, k

Probability to be killed respectively to be injured per mode and kilometres travelled per year [casualties/km] (= average number of casualties per mode and kilometres travelled per year)

K m, s

Kilometres travelled per mode in the scenarios per year [km]

Developing CLEVER a lot of effort has been put into the processing and testing of safety (compare CLEVER D3). Due to CLEVER’s minimal size and weight it is nearly impossible to make it safer than a car, but it has been achieved that it is as safe as a small car, which brings advantages for those who change mode from moped /motorcycle or bicycle – those modes that bear a high accident risk – to CLEVER. The number of casualties per CLEVER are therefore calculated with the probability of being killed or injured for a car driver in the actual state (compare first numerical row

Page - 96 -


CLEVER

in Table 8-35 and Table 8-36) and the kilometres travelled with CLEVER in the scenarios. The increase of kilometres travelled with individual motorized modes in the scenarios also has an influence on the accident risk for pedestrians, as serious pedestrian accidents primarily occur with car drivers. This factor is considered calculating the rising number of killed or injured pedestrians at constant pedestrian kilometres with the probability of being killed or injured depending on the car kilometres in the scenarios. 8.4.2 Results The number of casualties per mode is derived from the probability of getting killed or injured and the kilometres travelled per mode per year in the scenarios. Depending on the mode shift in the scenarios (compare chapter 7.2.1) the number of casualties per mode declines or remains constant, while the number of casualties in accidents with CLEVER or with pedestrians rises due to the increase of kilometres travelled with CLEVER respectively with individual motorized modes (Figure 8-10 for Graz and Figure 8-12 for Greater Thessaloniki Area). The total number and percentage change of casualties in Graz (Table 8-37 and Figure 8-11) is alternating in the three scenarios and is strongly depended on the risk respectively probability to get killed or injured, which clearly differs between the particular modes and the severity of injury, and on the kilometres travelled with the respective mode. While in Scenario A the number of casualties slightly decreases (decrease of killed/injured car drivers and car passengers, increase of killed/injured CLEVER drivers and pedestrians), it increases in Scenario B due to the instance that also PT passengers who have a minimal risk to get involved in an accident change to the comparable more risky CLEVER. The re-decrease in Scenario C can be explained with the decline of motorcycle/moped riders who bear the highest risk to get killed or injured in an accident.

Page - 97 -


1.400

0 - Actual state A - Launch of CLEVER B - Measures supporting CLEVER C - Raise of fuel prices

1.265 1.246 1.241 1.240

1.000 800 600

0 Car Car Motorcycle Cyclist driver passenger rider

0

37 51 50

83 83 83 83

369 369 369 378 251 255 257 256 75 75 74 74

200

321 321 321 272

400 372 349 349 349

Number of casualties / year

1.200

CLEVER

Pedestrian PT Others CLEVER passenger driver

Figure 8-10: Number of casualties per year in GRAZ according to the modes in the actual state and in the three scenarios, 2003

Table 8-37: Number of casualties per year in GRAZ according to the severity of injury in the actual state and in the three scenarios, 2003 Number of casualties in GRAZ according to the severity of injury Severity of injury

Actual state 2003

Scenario A

Scenario B

Scenario C

12,60

12,70

12,75

12,50

184,40

184,60

185,00

179,70

2.538,60

2.536,20

2.545,80

2.509,10

1,80

1,78

1,79

1,73

2.737,40

2.735,30

2.745,30

2.703,00


– 2,1

+ 7,9

– 34,4


– 0,1%

+ 0,3%%

– 1,3%

Killed persons Seriously injured persons Slightly injured persons Undefined injured persons Sum

Page - 98 -


Sum of casualties

-1,3%

-0,1%

-0,7% -3,8%

-4%

-0,9%

-1,2%

0,3%

0,3% -0,1%

-2,6%

-2%

Undefined injured

Slightly injured

0,4%

0,1%

1,2%

0% -0,8%

Percentage change of casualties [%] compared to the actual state

2%

Seriously injured

Killed 0,7%

4%

CLEVER

-6% A - Launch of CLEVER -8% -10%


Figure 8-11: Change of casualties according to the severity of injury in GRAZ in the three scenarios compared to the actual state, 2003

In Greater Thessaloniki Area the percentage change of the number of accidents respectively casualties is due the mode shift and the higher share of CLEVER clearly higher than in Graz (Table 8-38 and Figure 8-13). The identical increase of casualties in Scenario A and Scenario B in GTA comes off due to the situation that the share and kilometres travelled by car and PT passengers (shifting to CLEVER) stay the same in Scenario B while the share of car drivers decreases but shifts to CLEVER at the same rate as in Scenario A. The apparent decrease of casualties in Scenario C can be traced back to the fact that the kilometres travelled by car (driver) strongly drop due to the shift of trips with long trip lengths to Public Transport.

Page - 99 -


1.400


1.200


1.000

0

Car Car Motorcycle Cyclist driver passenger rider

0

93 100 122

21 21 21 26

50 41 41 78

200

17 17 17 17

429 460 460 422

362

400

504 492 492 437

600

722 722 722 722

800

595 546 539

Number of casualties / year

CLEVER

Pedestrian PT Others CLEVER passenger driver

Figure 8-12: Number of casualties per year in GREATER THESSALONIKI AREA according to the modes in the actual state and in the three scenarios, 2003

Table 8-38: Number of casualties per year in GREATER THESSALONIKI AREA according to the severity of injury in the actual state and in the three scenarios, 2003 Number of casualties in Greater Thessaloniki Area according to the severity of injury Severity of injury

Actual state 2003

Scenario A

Scenario B

Scenario C

Killed persons

144,30

149,20

149,20

131,90

Seriously injured persons

210,70

216,80

216,80

197,00

1.981,80

2.026,20

2.026,20

1.855,20

0

0

0

0

2.336,80

2.392,20

2.392,20

2.184,10


+ 55,40

+ 55,40

– 152,70


+ 2,37%

+ 2,37%

– 6,54%

Slightly injured persons Undefined injured persons Sum

Page - 100 -


CLEVER

Seriously injured

Slightly injured

Undefined injured

2,4%

2,4%

0,0%

0,0%

2,2%

2,2%

2,9%

2,9%

3,4%

Killed

0,0%

0%

3,4%

2%

Sum of casualties

-2%

-10%

-6,5%

-6,5%

-6% -8%

-6,4%

-4%

-8,6%

Percentage change of casualties [%] compared to the actual state

4%


Figure 8-13: Change of casualties according to the severity of injury in GREATER THESSALONIKI AREA in the three scenarios compared to the actual state, 2003 8.4.3 Costs Road accidents cause costs due to damage to property as well as to persons, which partly have to be borne by the general public. Those costs include in addition to the salvage expenses and medical costs, loss of production, compensation for pain and suffering, costs for administration, law and police as well as costs for losses of time. The assessment of the road accident costs is done for Austria due to the approach of METELKA [1997] and for Greece due to ATTIKO METRO [2005] according to the severity of injury (Table 8-39). Table 8-39: Road accident costs in [€] according to the severity of injury for Austria [METELKA 1997] and Greece [ATTIKO METRO 2005], 2003 Costs for persons killed or injured in road accidents [€] Severity of injury Costs for a killed person Costs for a seriously injured person Costs for a slightly injured person Costs for a person who is injured undefined

AUSTRIA

GREECE

963.961,–

1.000.000,–

52.107,–

135.000,–

4.416,–

15.000,–

47.338,–

N/A

Page - 101 -


CLEVER

The accident costs are calculated due to the number of casualties according to the severity of injury in the scenarios and the accident costs for Austria and Greece and are presented for Graz and Greater Thessaloniki Area in the following tables (Table 8-40 and Table 8-41). In both case study cities accident costs rise in the scenarios A and B, while they decrease in Scenario C. Table 8-40: Accident costs in [M €/year] in GRAZ according to the severity of injury in the actual state and in the three scenarios, 2003 Accident costs [M €/year] in GRAZ according to the severity of injury Severity of injury

Actual state 2003

Scenario A

Scenario B

Scenario C

12,15 M €

12,23 M €

12,29 M €

12,04 M €

9,61 M €

9,62 M €

9,64 M €

9,31 M €

Slightly injured persons

11,21 M €

11,20 M €

11,24 M €

11,08 M €

Undefined injured persons

0,09 M €

0,07 M €

0,08 M €

0,08 M €

33,05 M €

33,12 M €

33,25 M €

32,52 M €


+ 0,07 M €

+ 0,20 M €

– 0,53 M €


+ 0,2%

+ 0,6%

– 1,6%

Killed persons Seriously injured persons

Sum

Page - 102 -


CLEVER

Table 8-41: Accident costs in [M €/year] in GREATER THESSALONIKI AREA according to the severity of injury in the actual state and in the three scenarios, 2003 Accident costs [M €/year] in Greater Thessaloniki Area according to the severity of injury Severity of injury

Actual state 2003

Scenario A

Scenario B

Scenario C

144,34 M €

149,21 M €

149,21 M €

131,93 M €

Seriously injured persons

28,44 M €

29,27 M €

29,27 M €

26,59 M €

Slightly injured persons

29,73 M €

30,39 M €

30,39 M €

27,83 M €

0M€

0M€

0M€

0M€

202,51 M €

208,87 M €

208,87 M €

186,35 M €


+ 6,36 M €

+ 6,36 M €

– 16,16 M €


+ 3,14%

+ 3,14%

– 7,98%

Killed persons

Undefined injured persons Sum

8.5 Journey time 8.5.1 Basics for the Calculation The journey time for the particular modes has been calculated from the projected values of the survey (subjective specifications of the journey time by the respondents). The definition of the scenarios (compare chapter 5.2) determines time advantages for CLEVER compared to the car (driver and passenger) in Scenario B and Scenario C. Motorcycle/moped riders have no time advantages compared to CLEVER, but neither disadvantages – they are as fast as CLEVER drivers. Whereas PT passengers and cyclists gain time savings using CLEVER in all the three scenarios. 8.5.2 Results The reduction of the journey time according to the modes results in Scenario A from a mode shift from public transport or bicycle to CLEVER and in Scenario B from the shift from all modes towards CLEVER, while in Scenario C not only time savings are gained but time losses are accepted to some extent resulting from the shift from a faster mode (e.g. car) to a slower one (e.g. PT or bicycle).

Page - 103 -


CLEVER

As in Graz in Scenario A only car drivers and car passengers change to CLEVER and no time advantage is determined in Scenario A for the use of CLEVER, no time savings can be registered for this scenario. In Scenario B the defined time savings justified by various measures favouring the CLEVER vehicle in the city (compare chapter 5.2.2) lead to a journey time reduction of approximately 1%. In Scenario C the time savings are partly compensated due to the change from car or motorcycle to PT respectively bicycle. The results of the journey time and time savings in the scenarios in Graz are shown in Table 8-42, Table 8-43 and Figure 8-14. Table 8-42: Journey time in [h/day] in GRAZ according to the modes in the actual state and in the three scenarios, 2003 Journey time in [h/day] in GRAZ according to the modes Modes

Actual state 2003

Scenario A

Scenario B

Scenario C

10.314 h

10.111 h

10.005 h

9.975 h

Car passenger

1.669 h

1.620 h

1.620 h

1.620 h

Public Transport

2.936 h

2.936 h

2.898 h

2.925 h

Bicycle

846 h

846 h

846 h

1.032 h

Motorcycle

635 h

635 h

635 h

558 h

–

251 h

246 h

241 h

16.400 h

16.400 h

16.249 h

16.351 h


0h

– 151 h

– 49 h


0%

– 0,92%

– 0,30%

Car driver

CLEVER Sum

Page - 104 -


CLEVER

18.000


10.000

10.314 10.111 10.005 9.975

251 246 241

Bicycle

558

Public Transport

635 635 635

846 846 846 1.032

2.000

2.936 2.936 2.898 2.925

6.000 1.669 1.620 1.620 1.620

Journey time in [h / day]

14.000

16.400 16.400 16.249 16.351

0 - Actual state

0 Car driver

Car passenger

Moped/ Motorcycle

CLEVER

Sum

Figure 8-14: Journey time according to the modes in [h/day] in GRAZ in the actual state and in the three scenarios, 2003 Table 8-43: Saving of journey time according to the mode shift in [h/day] in GRAZ in the scenarios compared to the actual state, 2003 Saving of journey time according to the mode shift in [h/day] in GRAZ in the scenarios compared to the actual state Mode shift

Scenario A

Scenario B

Scenario C

CLEVER instead of car driver

0h

– 124 h

– 120 h

CLEVER instead of car passenger

0h

– 20 h

– 20 h

CLEVER instead of PT

0h

–8h

–8h

PT instead of car driver

–

–

+ 10 h

Bicycle instead of car driver

–

–

–5h

Bicycle instead of motorcycle

–

–

+ 104 h

Trip skipped

–

–

– 11 h

0h

– 151 h

– 49 h

Sum

In Greater Thessaloniki Area the time savings in Scenario A result from the shift from public transport to CLEVER. In Scenario B the determined time savings for CLEVER towards all modes lead to a journey time reduction of around 5% caused by a mode shift from car driver, car passenger and PT passenger to CLEVER. In Scenario C the more complex mode shift not only to CLEVER but also among other modes leads on the one hand to the expected time savings on the other hand to time losses due to Page - 105 -


CLEVER

the change from car driver and car passenger to public transport and to walking. The results of the journey time and time savings in the scenarios in Greater Thessaloniki Area are shown in Table 8-44, Table 8-45 and Figure 8-15. Table 8-44: Journey time in [h/day] in GREATER THESSALONIKI AREA according to the modes in the actual state and in the three scenarios, 2003 Journey time in [h/day] in GREATER THESSALONIKI AREA according to the modes Modes

Actual state 2003

Scenario A

Scenario B

Scenario C

151.448 h

128.451 h

126 742 h

111.430 h

Car passenger

18.631 h

18.262 h

18.262 h

16.754 h

Public Transport

29.820 h

25.392 h

25.392 h

36.230 h

256 h

256 h

256 h

467 h

1.983 h

1.983 h

1.983 h

1.983 h

CLEVER

–

26.358 h

19.044 h

20.258 h

On Foot

–

–

–

6.506 h

202.138 h

200.702 h

191.679 h

193.627 h


– 1.436 h

– 10.459 h

– 8,511 h


– 0,71%

– 5,17%

– 4,21%

Car driver

Bicycle Motorcycle

Sum

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CLEVER

220.000

A - Launch of CLEVER

180.000


0 Car driver

Car Public passenger Transport

Bicycle

Moped/ CLEVER Motorcycle

6.506

256 256 256 467

20.000

26.358 19.044 20.258

18.631 18.262 18.262 16.754

60.000

1.983 1.983 1.983 1.983

100.000

29.820 25.392 25.392 36.230

140.000

151.448 128.451 126.742 111.430

Journey time in [h / day]

202.138 200.702 191.679 193.627

0 - Actual state

On foot

Sum

Figure 8-15: Journey time according to the modes in [h/day] in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003 Table 8-45: Saving of journey time according to the mode shift in [h/day] in GTA in the scenarios compared to the actual state, 2003 Saving of journey time according to the mode shift in [h/day] in GREATER THESSALONIKI AREA in the scenarios compared to the actual state Mode shift

Scenario A

Scenario B

Scenario C

CLEVER instead of car driver

0h

– 8.538 h

– 9.000 h

CLEVER instead of car passenger

0h

– 25 h

– 25 h

CLEVER instead of PT

– 1.436 h

– 1.896 h

– 1.866 h

PT instead of car driver

–

–

+ 2.164 h

Bicycle instead of car driver

–

–

– 150 h

–

+ 56 h

On foot instead of car driver Trip skipped instead of car driver

–

–

– 1.261 h

PT instead of car passenger

–

–

+ 906 h

On foot instead of car passenger

–

–

+ 664 h

– 1.436 h

– 10.459 h

– 8.511 h

Sum

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8.5.3 Costs Time spent for travelling is a very important variable for mode choice. It is often used as an argument to travel by an individual motorised mode (car, moped/motorcycle or CLEVER) instead by public transport or another environmentally friendly mode. However, the monetary quantification of journey time is quite difficult, since the valuation of time varies depending on mode, trip purpose and time horizon according to different subjective and objective criteria. For the time costs in Austria the valuation approach of PISCHINGER et al. [1998] is used, for Greece the value of ATTIKO METRO [2005] is taken (Table 8-46). Table 8-46: Time costs in [€/hour] in AUSTRIA [PISCHINGER R., G. SAMMER, F. SCHNEIDER et al. 1998] and GREECE [ATTIKO METRO 2005], 2003 Time costs Average hourly rate in [€/hour]

AUSTRIA

GREECE

3,45 €

3,72 €

Based on the calculation of the journey time in the scenarios the economic valuation of the journey time has been carried out and is presented in the following tables for Graz and Greater Thessaloniki Area (Table 8-47 and Table 8-48). In both case study cities the use of CLEVER respectively the mode shift results in cost savings in all the three scenarios (except in Scenario A in Graz) due to time savings. Table 8-47: Journey time costs in [M €/year] in GRAZ according to the modes in the actual state and in the three scenarios, 2003 Journey time costs in [M €/year] in GRAZ according to the modes Modes

Actual state 2003

Scenario A

Scenario B

Scenario C

Car driver

8,19 M €

8,03 M €

7,94 M €

7,92 M €

Car passenger

1,33 M €

1,29 M €

1,29 M €

1,29 M €

Public Transport

2,33 M €

2,33 M €

2,30 M €

2,32 M €

Bicycle

0,67 M €

0,67 M €

0,67 M €

0,82 M €

Motorcycle

0,50 M €

0,50 M €

0,50 M €

0,44 M €

–

0,20 M €

0,20 M €

0,19 M €

13,02 M €

13,02 M €

12,90 M €

12,98 M €


0M€

– 0,12 M €

– 0,04 M €


0%

– 0,92%

– 0,30%

CLEVER Sum

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CLEVER

Table 8-48: Journey time costs in [M €/year] in GREATER THESSALONIKI AREA according to the modes in the actual state and in the three scenarios, 2003 Journey time costs in [M €/year] in GTA according to the modes Modes

Actual state 2003

Scenario A

Scenario B

Scenario C

129,58 M €

109,90 M €

108,44 M €

95,34 M €

Car passenger

15,94 M €

15,62 M €

15,62 M €

14,33 M €

Public Transport

25,51 M €

21,73 M €

21,73 M €

31,00 M €

Bicycle

0,22 M €

0,22 M €

0,22 M €

0,40 M €

Motorcycle

1,70 M €

1,70 M €

1,70 M €

1,70 M €

CLEVER

–

22,55 M €

16,29 M €

17,33 M €

On Foot

–

–

–

5,57 M €

172,95 M €

171,72 M €

164,00 M €

165,67 M €


– 1,23 M €

– 8,95 M €

– 7,28 M €


– 0,71%

– 5,17%

– 4,21%

Car driver

Sum

8.6 Parking infrastructure 8.6.1 Basics for the Calculation The estimation of the required parking infrastructure for CLEVER vehicles is based on reference data of parking infrastructure in both case study cities. In Graz only the inner districts (districts 1 – 6, parking management applied) are considered, in the other districts there is no need of designated CLEVER parking spaces due to the fact that there is enough parking space available. Table 8-49 gives the actual number of on-street and off-street parking spaces in the inner city of Graz. Table 8-49: Parking infrastructure in the inner city of GRAZ (districts 1 – 6) [GRAZ 2005] Number of parking spaces in the inner city of GRAZ Districts 1 – 6

On-street parking spaces 18.653

Off-street parking spaces

Total number of parking spaces

5.129

23.782

For the estimation of the required number of parking spaces for CLEVER the following data and considerations are taken into account for Graz: –

Actual number of parking spaces in the districts 1 – 6 in Graz Page - 109 -


CLEVER

–

Number of car (driver) trips per day to district 1 – 6 done by inhabitants and non-inhabitants of Graz in the actual state

–

Number of CLEVER trips per day shifted from car (driver) trips to the defined districts in the three scenarios

–

Number of CLEVER trips per day shifted from moped/motorcycle, PT, bicycle, car passenger trips to the defined districts in the three scenarios

In Greater Thessaloniki Area parking is a more serious problem than in Graz. There is a significant lack of parking spaces both for long term and for short-term parking. This situation applies not only to the city centre (Sector 1 & 2) but also to most of the municipalities (Sector 3 – 6). As a result vehicles park illegally reducing road capacity and increasing congestion. For the estimation of the required CLEVER parking spaces only the number of legal parking spaces in the actual state are considered (Table 8-50). Table 8-50: Parking infrastructure in GREATER THESSALONIKI AREA in the different transport sectors [Organisation of Thessaloniki for the Thessaloniki Master Plan Implementation and Environmental Protection 1998] Number of parking spaces in the sectors of GTA

On-street parking spaces

Off-street parking spaces

Total number of parking spaces

Sector 1 & 2

51.588

11.651

63.239

Sector 3

11.091

7.883

18.974

Sector 4

5.257

1.134

6.391

Sector 5

8.885

3.039

11.924

Sector 6

24.460

7.248

31.708

101.281

30.955

132.236

Sum

As for Graz beside the number of actual parking spaces, the number of car (driver) trips per day to transport sector 1 – 6 in the actual state, the number of CLEVER trips per day shifted from car (driver) trips and from the other modes to the defined districts in the three scenarios are considered in GTA. It is assumed that for all CLEVER trips to the relevant districts shifted from car (driver) trips an existing car parking space is replaced by a CLEVER parking space (based on the actual number of parking spaces). Trips shifted from other modes to CLEVER require an additional parking space, as they claimed no parking space before. The number of CLEVER parking spaces corresponds with the number of car parking spaces in a ratio of 2:3 considering the required space of 10 m² for a CLEVER and 15 m² for a car parking space.

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CLEVER

8.6.2 Results Table 8-51 gives an overview of the number of required CLEVER parking spaces in the districts 1 – 6 in Graz in the three scenarios. The numbers in brackets refer to the corresponding number of car parking spaces due to the needed space. The CLEVER parking spaces make up between 1% and 2% of the sum of the car parking spaces in the three scenarios. Table 8-51: Required CLEVER parking spaces in the districts 1 – 6 in GRAZ in the three scenarios, 2003 Required CLEVER parking spaces in the districts 1 – 6 in GRAZ Number of CLEVER parking spaces

Scenario A

Scenario B

Scenario C

213 (142)

577 (385)

556 (371)

CLEVER off-street parking spaces - in garages (corresponding to number of car parking spaces)

58 (39)

159 (159)

153 (102)

Sum of needed CLEVER parking spaces (corresponding to number of car parking spaces)

271 (181)

736 (490)

709 (472)

0,76%

2,06%

1,99%

CLEVER on-street parking spaces (corresponding to number of car parking spaces)

Share of CLEVER parking spaces (corresponding to car parking spaces) in number of existing car parking spaces

Due to the shift from car (drivers) to CLEVER the demand of car parking spaces decreases in all three scenarios between 1,1% and 1,5% (Table 8-52). Summing up the number of required car parking spaces and the required CLEVER parking spaces (in the corresponding number of car parking spaces) and comparing it to the existing number of car parking spaces brings the result that in Scenario A less car parking spaces respectively less space is needed than in the actual state. That means that there are still space and vacant parking spaces available despite a designation of car parking in CLEVER parking spaces. Whereas in Scenario B and Scenario C additional parking spaces are needed. But as space on-street as well as off-street is limited and the situation for car parking should not be impaired it is worth to have a look at the degree of utilisation of the existing car parking spaces. That means that at an original degree of utilisation of 99,3% in Scenario B and of 99,5% in Scenario C, the required CLEVER parking spaces can be designated without any restraints for the car drivers. Page - 111 -


CLEVER

Table 8-52: Required car parking spaces in the districts 1 – 6 in GRAZ in the three scenarios, 2003 Required car parking spaces in the districts 1 – 6 in GRAZ Scenario A Number of required car parking spaces (without CLEVER) Relative difference to the actual state [%] Number of parking spaces-new (including car and CLEVER parking spaces – considering space) Absolute difference to the actual number of car parking spaces

Scenario B

Scenario C

23.511

23.457

23.429

– 1,14%

– 1,37%

– 1,48%

23.692

23.947

23.902

– 90

+ 165

+ 120

Due to the higher share of CLEVER and the originally higher number of parking spaces in Greater Thessaloniki Area the required CLEVER parking spaces exceed those of Graz a lot (Table 8-53).

Table 8-53: Required CLEVER parking spaces in the transport districts 1 – 6 in GEATER THESSALONIKI AREA in the three scenarios, 2003 Required CLEVER parking spaces in the transport sectors 1 – 6 in GTA Number of CLEVER parking spaces CLEVER on-street parking spaces (corresponding to number of car parking spaces)

Scenario A

Scenario B

Scenario C

32.111 (21.407)

33.864 (22.576)

32.857 (21.905)

CLEVER off-street parking spaces - in garages (corresponding to number of car parking spaces)

8.276 (5.517)

8.723 (5.815)

7.707 (5.138)

Sum of needed CLEVER parking spaces (corresponding to number of car parking spaces)

40.387 (26.925)

42.588 (28.392)

40.564 (27.043)

Share of CLEVER parking spaces (corresponding to car

20,36%

21,47%

20,45%

parking spaces) in number of

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CLEVER

existing car parking spaces

Although the number of required car parking spaces decreases in Scenario A and in Scenario B, the use of CLEVER can not solve the parking problems in Greater Thessaloniki Area (Table 8-54). Far from it additional parking spaces are needed. But facing the number of illegally parked vehicles there is no space available, so that the situation for car parking is expected to impair in case all the required CLEVER parking spaces are designated. Even Scenario C can not ease the situation. Although the need for car parking spaces decreases, the number of illegally parked vehicles exceeds that of the reduced demand. Table 8-54: Required car parking spaces in the sectors 1 – 6 in GTA in the three scenarios, 2003 Required car parking spaces in the sectors 1 – 6 in GTA Scenario A Number of required car parking spaces (without CLEVER)

Scenario B

Scenario C

111.645

109.445

99.146

– 15,57%

– 17,24%

– 25,02%

Number of parking spaces-new (including car and CLEVER parking spaces – considering space)

138.570

137.837

126.189

Absolute difference to the actual number of car parking spaces

+ 6.334

+ 5.601

– 6.047


8.6.3 Costs For the valuation of a CLEVER parking space only the costs for marking a parking space are taken per year. It is assumed that the marking has to be renewed yearly. As the required marking for a 10 m² sized CLEVER parking space is estimated to be 10,5 running meters, the sum of 73,50 € results for Austria and 68,20 € for Greece (Table 8-55).

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Table 8-55: Costs for marking a CLEVER parking space in AUSTRIA [Information by MA 46, Verkehrsorganisation und technische Angelegenheiten, Wien 2005] and in GREECE [estimation], 2003 Costs for marking a CLEVER parking space

AUSTRIA

GREECE

Costs per running meter marking [€/rm]

7,00 €

6,50 €

CLEVER parking space [€/parking space]

73,50 €

68,20 €

Based on the estimation of the number of required parking spaces for CLEVER in Graz and in Greater Thessaloniki Area in the three scenarios the costs for CLEVER parking infrastructure are listed in Table 8-56. Table 8-56: Costs for CLEVER parking infrastructure in [€/year] in GRAZ and in GREATER THESSALONIKI AREA in the three scenarios, 2003 Costs for CLEVER parking infrastructure [€/year] GRAZ GTA

Scenario A

Scenario B

Scenario C

19.934 €

54.075 €

52.081 €

2.754.735 €

2.904.817 €

2.766.804 €

8.7 Welfare Losses Welfare losses (or top down costs) are the reduction in welfare caused by reducing traffic volume as a consequence of increasing travel costs. This is in the CLEVER project only for scenario C relevant (increasing fuel prices). In Table 8-57 the numbers of trips in total and skipped trips are shown. In Graz no trip was skipped due to the increasing fuel prices. In Thessaloniki only 3 trips would not be made in Scenario C. All these three trips are trips of the category “bringing & picking up” as car drivers. With the assumption of 0,14€ per kilometre and the average trip length of 3,48 kilometres the welfare losses are 7.525€ per day. With about 200 “bringing & picking up” trips per year the total sum is 1,51 M € per year. Table 8-57: Number of trips skipped due to increasing travel costs in Scenario C in GRAZ and in GREATER THESSALONIKI AREA Number of trips total

Number of skipped trips

Percentage

GRAZ (sample, unweighted)

553

0

0%

GTA (sample, unweighted)

474

3

0,63%

Page - 114 -


GRAZ GTA

CLEVER

931.663

0

0%

2.116.205

15.446

0,73 %

8.8 Summary of the Cost Benefit Analysis A first glance at the summary of the CBA in Graz seems to demand on rethinking the headline of the chapter. In all three scenarios an increase of the total costs appears, whereas the highest rise is located in Scenario B (Table 8-58). This after all not surprising result is caused due to the fact that not only car drivers supplement their trips by CLEVER trips but that also user of environmentally friendly modes (e.g. public transport, bicycle) in the actual state decide to shift to CLEVER in the scenarios due to individual advantages of costs and time they gain. That leads to an increase of kilometres travelled by individual motorised modes and thus to a slightly increase of noise, road accidents and running costs. However looking at the details of the analysis (Table 8-59 and Figure 8-16) the advantages of the use of CLEVER appear. The most favourable result is that the loads and thus the costs of CO2 emissions and emissions of hazardous air pollutants can be reduced. Another positive component in terms of cost reduction and favourable to the environment are the fuel costs, which in fact are not apparent in this table as they are part of the running costs, which in total increase. Furthermore costs for journey time can be reduced in all three scenarios and accident costs at least in Scenario C.

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Table 8-58: Results of the Cost Benefit Analysis in GRAZ according to the indicators, costs in [M €/year] in the actual state and in the three scenarios, 2003 GRAZ – Results of the CBA [M €/year] Indicators

Actual state 2003

Scenario A

Scenario B

Scenario C

Hazardous air pollutants

3,54 M €

3,44 M €

3,42 M €

3,41 M €

CO2-emissions

23,31 M €

22,81 M €

22,75 M €

22,63 M €

Running costs

105,55 M €

106,40 M €

107,03 M €

106,66 M €

Noise

157,83 M €

158,18 M €

158,37 M €

158,29 M €

33,05 M €

33,12 M €

33,25 M €

32,52 M €

Parking infrastructure

0M€

0,02 M €

0,05 M €

0,05 M €

Journey time

13,02 M €

13,02 M €

12,90 M €

12,98 M €

-

-

-

-

336,29 M €

336,99 M €

337,78 M €

336,54 M €


+ 0,69 M €

+ 1,49 M €

+ 0,25 M €


+ 0,21%

+ 0,44%

+ 0,07%

Road accidents

Welfare losses Sum

Table 8-59: Cost difference in GRAZ in the three scenarios according to the indicators compared to the actual state 2003 in [M € / year] GRAZ – Cost difference compared to the actual state 2003 [M €/year] Indicators

Scenario A

Scenario B

Scenario C


– 0,10 M €

– 0,12 M €

– 0,13 M €

CO2-emissions

– 0,50 M €

– 0,56 M €

– 0,67 M €

Running costs

+ 0,85 M €

+ 1,48 M €

+ 1,11 M €

Noise

+ 0,35 M €

+ 0,54 M €

+ 0,46 M €

Road accidents

+ 0,07 M €

+ 0,20 M €

– 0,53 M €


+ 0,20 M €

+ 0,05 M €

+ 0,05 M €

0M€

– 0,12 M €

– 0,04 M €

+ 0,69 M €

+ 1,49 M €

+ 0,25 M €

+ 0,21%

+ 0,44%

+ 0,07%

Journey time Sum Relative difference [%]

Page - 116 -


10,00


8,00


6,00

0,69 1,49 0,25 -0,04

-0,12

0,0

0,20

0,05 0,05

0,07 0,20

0,46

0,35 0,54

-0,53

-2,00

-0,50 -0,56 -0,67

0,00

0,85

2,00

1,48 1,11

4,00

-0,10 -0,12 -0,13

Costs and savings in [M € / year]

CLEVER

-4,00

-6,00

Air pollutants

CO2- Running emissions costs

Noise

Parking Road Journey accidents infrastructure time

Sum

Figure 8-16: Results of the CBA in GRAZ – costs and savings in [M €/year] in the actual state and in the three scenarios, 2003 The results in the Greek case study are more varying than in Graz due to the higher share of CLEVER trips in the scenarios on the one hand and due to the shift to other modes and the resulting high reduction of kilometres travelled by individual motorised modes in Scenario C on the other hand. While in Scenario A the costs rise by 2% compared to the actual state, a decrease can be noticed in Scenario B and C (Table 8-60). The relatively high decrease of about 9,5% in Scenario C is a result of the comparable high reduction of car kilometres travelled caused by the shift of trips with high trip lengths of car drivers to public transport. The results of the single components of the CBA in Greater Thessaloniki Area show similar tendencies as in Graz (Table 8-61 and Figure 8-17). A reduction of (loads and) costs can be gained at CO2 emissions, emissions of hazardous air pollutants, fuel consumption and journey time. The exceeding running costs influencing the total sum in Scenario C are caused as mentioned above by the high reduction of car kilometres travelled.

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Table 8-60: Results of the Cost Benefit Analysis in GREATER THESSALONIKI AREA according to the indicators, costs in [M €/year] in the actual state and in the three scenarios, 2003 GREATER THESSALONIKI AREA – Results of the CBA [M €/year] Indicators

Actual state 2003

Scenario A

Scenario B

Scenario C


78,55 M €

67,21 M €

66,27 M €

65,44 M €

CO2-emissions

70,37 M €

62,43 M €

61,81 M €

61,79 M €

Running costs

276,68 M €

288,34 M €

288,55 M €

230,13 M €

Noise

179,54 M €

181,39 M €

181,46 M €

173,94 M €

Road accidents

202,51 M €

208,87 M €

208,87 M €

186,35 M €


0M€

2,75 M €

2,90 M €

2,77 M €

Journey time

172,95 M €

171,72 M €

164,00 M €

165,67 M €

-

-

-

1,51 M €

953,97 M €

955,81 M €

946,95 M €

861,80 M €


+ 1,84 M €

– 7,01 M €

– 92,17 M €


+ 0,19 %

– 0,74 %

– 9,66 %

Welfare losses Sum

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Table 8-61: Cost difference in GREATER THESSALONIKI AREA in the three scenarios according to the indicators compared to the actual state 2003 in [M €/year] GREATER THESSALONIKI AREA Cost difference compared to the actual state 2003 [M €/year] Indicators

Scenario A

Scenario B

Scenario C

– 11,34 M €

– 12,28 M €

– 13,11 M €

CO2-emissions

– 7,94 M €

– 8,57 M €

– 8,58 M €

Running costs

+ 11,66 M €

+ 11,88 M €

– 46,55 M €

Noise

+ 1,57 M €

+ 1,64 M €

-4,77 M €

Road accidents

+ 6,36 M €

+ 6,36 M €

– 16,16 M €


+ 2,75 M €

+ 2,90 M €

+ 2,77 M €

Journey time

– 1,23 M €

– 8,95 M €

– 7,28 M €

-

-

+ 1,51 M €

+ 1,84 M €

– 7,01 M €

– 92,17 M €

+ 0,19 %

– 0,74 %

– 9,66 %


Welfare losses Sum Relative difference [%]

-7,01

-1,23 -8,95 -7,28

1,84

2,75 2,90 2,77 -16,16

6,36

6,36

1,64

-46,55

-40,00

-60,00

-4,77

11,66 11,88 -8,57 -8,58

-20,00

-7,94

-12,28 -13,11

-11,34

0 - Actual state A - Launch of CLEVER B - Measures supporting CLEVER

-80,00

-100,00

C - Raise of fuel prices Air pollutants

CO2Running emissions costs

-92,17

Costs and savings in [M € / year]

0,00

1,57

20,00

Noise

Parking Road Journey accidents infrastructure time

Sum

Figure 8-17: Results of the CBA in GREATER THESSALONIKI AREA – costs and savings in [M €/year] in the actual state and in the three scenarios, 2003

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On the whole positive conclusions can be drawn in both case study cities as clear benefits can be gained for the environment – a reduction of CO2 emissions, emissions of hazardous air pollutants and fuel consumption.

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9 POLICY MAKERS’ ATTITUDE TOWARDS CLEVER In several European cities decision makers and experts were asked concerning existing traffic and transport problems and problems caused by traffic. The survey gives an impression about the potential and acceptance for innovative ideas, as for example for low emission vehicles for urban transport from the position of transport politics. As such an innovative concept for environmentally friendly urban mobility the CLEVER vehicle was presented.

9.1 Methodical Approach 9.1.1 Sample Selection and Interview Procedure

Selection of the target person

Announcement letter, contact by phone and making an appointment for the interview

Preparation

The involved partners - BOKU-ITS (Vienna), LKR (Ranshofen), TRIAS (Thessaloniki), TUB (Berlin), UBAH.MECH (Bath), WEH (Illertissen) - selected policy makers in the field of transportation with special competencies and influence (chapter 9.2.2). After the selection of the target persons announcement letters were sent out to communicate the aim of the survey to the decision makers and experts (Figure 9-1).

Welcome, introduction

Presentation of CLEVER Assessment by the target person

INTERVIEW

Questions about transport and environmental problems and transport politics of the city

Presentation and discussion of the results of the CLEVER-survey

Completing the answers in the document

Completed interview to BOKU-ITS

Finishing

Discussion of supporting measures and implementation

Figure 9-1: Approach of the interviews with policy makers

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The letter included a description of main topics of the interview’s contents like transport and traffic problems in the different cities and possible measures to solve them. The announcement letter gave also notice of an interviewer’s telephone call during the next days to make an appointment for a personal interview. The contacts/attempts and the refusals/non response were documented. The used method is a face-to-face interview technique. This type of interview is well approved in the field of transportation policy surveys, especially for interviews with experts with a small net sample. Within face-to-face interviews the interviewer is able to show pictures or to use visual scales to assist the interview. The interviewee’s emotions and reactions could be taken up exactly. Furthermore the presence of an interviewer makes the interview situation controllable and makes it possible to clarify both questions and answers. Extensions could be made for particularly interesting problems or comments. During the interview the interviewers were geared to a questionnaire (chapter 9.1.2) and had to take notes. The interviews took between 25 and 60 minutes. 9.1.2 Questionnaire The questionnaire included only open-ended questions and had four main parts: (1) transport and environmental problems and politics, (2) presentation of the CLEVER vehicle and assessment, (3) presentation of the results of the household survey and (4) feasibility of measures favouring the use of CLEVER. In the first part of the interview the interviewees had to name the most serious traffic and transport problems and problems caused by traffic in the particular city. The mentioned problems had to be ranked according to their importance. In the next step the most important measures to solve the mentioned problems had to be named and ranked. The target persons were asked whether (and if not, why not) these solutions are implemented in the particular city. In a next step the interviewee assessed 12 different measures according to their importance (from 5 - not important to 1 - very important). The second part of the questionnaire comprised the presentation of the CLEVER vehicle. The interviewees were informed about the characteristics, specifications and facts of CLEVER and CNG by means of pictures and digital animation. The first impressions of the vehicle respectively of the concept were collected. The policy makers were asked about their possible personal usage, the expected acceptance of the road users and the expected benefit of the vehicle.

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During the third part the policy makers were faced with the results of the travel survey (chapter 6) including the explanation of the applied different scenarios. The comments on the results of the modal split respectively modal shift were collected. Furthermore the estimated effects on the emissions based on the changed mode choice were presented and the comments referring to this were collected. In the fourth part of the interview the target persons were asked about their support of each of the following measures favouring the use of CLEVER: -

reserved parking spaces for CLEVER in the city centre,

-

no parking fees and no time limitations in on-street parking zones,

-

use of bus lanes and

-

exemption from road pricing.

The policy makers had to name problems from their point of view that would hamper the implementation of these measures. The last part of the interview related to the politicians’ support of a pilot project (implementation of these measures).

9.2 Sample 9.2.1 Overall Figures The sample included policy makers out of seven different cities from Austria, Germany, Greece and United Kingdom (Table 9-1). Table 9-1:

Gross and net sample size per city and per country (persons)

country

city

number of contacted persons gross sample

number of interviews per city net sample

Braunau am Inn

1

1

Graz

3

3

Vienna

6

3

Berlin

1

1

Ulm

1

1

Greece

Thessaloniki

7

3

3

United Kingdom

Bath

1

1

1

Austria

Germany

∑

20

number of interviews per country

7

2

13 (response rate 65 %)

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The gross sample included 20 persons. Overall 13 persons were interviewed. The response rate is 65 %. The target group includes policy makers like executives, administrators in leading positions, city councillors with authorities / responsibilities in traffic and transport planning. 9.2.2 Specification of the Persons (Functions and Authorities) The interviewed persons were experts from politics (for example mayors, city councillors, Spokesmen of the Board) or administration (for example government building officers, chairmen or representatives of Transport Planning Offices or Committees) with different functions and authorities (Table 9-2). The persons were divided into two groups: persons with “high” and persons with “low” authority. Target persons with high authority have direct decision-making authority and competencies. Target persons with low authority have indirect decision-making authority, but positions of esteem and are able to affect decisions with lobbying. Table 9-2:

Authorities of target persons

country

city

politics high authority

administration

low authority

high authority

e.g. mayors, e.g. Spokesmen e.g. government city councillors of the Board building officers, chairmen of Transport Planning Offices or Committees

low authority e.g. representatives of Transport Planning Offices or Committees

Braunau am Inn

1

-

Graz

1

1

1

-

Vienna

-

-

2

1

Berlin

-

-

1

-

Ulm

1

-

-

-

Greece

Thessaloniki

2

-

1

-

United Kingdom

Bath

1

-

-

-

6

1

5

1

Austria

Germany

∑

-

-

Age and Gender The average age of the target persons was 58 years. Ten out of the 13 interviewed persons were male.

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9.3 Results 9.3.1 Transport and Environmental Problems and Politics From the policy maker’s point of view main transport and environmental problems are caused by -

the increasing motorisation,

-

the high motorised individual traffic in the modal-split respectively and

-

the high amount of commuters by car.

During the interviews policy makers often named -

the lack of supply of public transport - especially in the border areas -,

-

the lack of supply of bicycle and foot paths,

-

pollutant and noise emissions caused by traffic,

-

parking problems like the lack of parking spaces - especially the low supply of park&ride-possibilities or

-

illegal parking (e.g. at the pavement as a big problem for pedestrians or disabled people) as very serious problems.

As reasonable measures to solve the transport, traffic and environmental problems target persons named themselves -

the extension of the public transport supply or priority for public transport,

-

measures favouring pedestrians and cyclists (e.g. extension of bicycle infrastructure),

-

parking management and an improvement of the park&ride supply and

-

awareness measures (e.g. information campaigns, car free days).

Six out of 13 interviewed persons stated that the particular named measures are implemented in their city to work against existing traffic and environmental problems. Six persons indicated a partial and one no implementation at present. Reasons for a failing implementation were for example conflicts of interests between municipality and economy or financing problems. Figure 9-2 shows the politicians’ average assessment of specified measures to solve transport and traffic problems according to their importance from 5 - not important to 1 - very important. An extension of the public transport supply and parking management seem to be the best methods of

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resolution to overcome urban traffic problems from the policy makers’ point of view. Innovative, environmentally friendly vehicles for urban transport got an average assessment from 2.2. Not important 5

Very important 4

3

2

Extension of the public transport supply, priority for public transport

1,0

Measures favouring pedestrians and cyclists (extension of bicycle infrastructure etc.)

1,9

Extension of the road network

3,3

Lanes reserved for certain vehicles (for car pools, low-emission vehicles etc.)

3,3 1,6

Parking management Reserved parking spaces for certain vehicles (for car pools, low-emission vehicles etc.) Congestion charging, city toll Traffic information systems (information on travel time and route selection etc.) Access restrictions to the city center for certain groups of vehicles

3,0 4,0 2,6 2,8

Mobility management

2,3

Awareness measures (information campaigns, car free day etc.)

2,3

Innovative, environmentally friendly vehicles for urban transport (electric or CNG cars etc.)

Figure 9-2:

1

2,2

Average assessment of measures to solve transport and traffic problems from 5 - not important to 1 - very important, n=12 persons

9.3.2 Presentation of the CLEVER-Vehicle and Assessment The first impressions of the CLEVER vehicle were positive for the most part 20 positive mentions, 12 negative mentions, 6 neutral mentions (Figure 9-3). According to their mostly positive impressions seven of the 13 interviewed policy makers appraised that the vehicle will be accepted and used by road users. Compared to the opinion of the respondents of the household survey on the vehicle’s aesthetic design (chapter 7.1) - their view is quite divided - the policy makers’ view Page - 126 -


CLEVER

was mainly positively: The vehicle’s aesthetic design was referred to as for example “funny, dynamic, smart, modern”. There were just two negative mentions concerning the vehicle’s shape. Like the assessment of the respondents of the household survey (chapter 7.1) policy makers looked upon the low emissions and the speed of CLEVER favourably. There were also negative impressions of the CLEVER vehicle: The target persons assessed the size of the vehicle’s internal space as too small, the sales price as too high and expressed objection to the vehicle’s safety. These impressions align with the results of the household survey, too.

number of mentions (multiple mentions possible)

The CLEVER vehicle reminded the policy makers of other cars, e.g. the Smart and they often said that it looks like a three-wheeled motor bike. Five of the 13 interviewed persons would personal use one, three are indecisive. The policy makers who would not use CLEVER named the same arguments as respondents of the household survey in Graz (chapter 7): The main argument was, that the vehicle is too small and therefore not useful for special activities like shopping or picking children up (from the policy makers’ point of view), followed by the favouring of other modes. 22 20 18

positive “Low overheads!” “Max. speed positive!” “High cruising range!”

1 1 1

“Smart concept!”

3

“Low emissions!”

3

16 14 12

negative

10 8 6

neutral “Shape-positive!”

“Objection to the safety!” “Sales price too high!” “Target group / purpose of use doubtful!”

1 1

“Shape negative!”

2

“Shortage of space!”

6

2

11

4

“Classification?”

2

“Comparison with other vehicles.”

3 3

0

Figure 9-3:

First impressions of CLEVER of the policy makers, multiple mentions possible, n=13 persons, 38 mentions

According to the properties of CLEVER most of the target persons thought the use of CLEVER could make at least a small contribution to solve transport and environmental problems in their cities.

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9.3.3 Presentation of the Results of the Household Survey The interviewers confronted the target persons with the results of the household survey for the scenarios “with supporting measures” and “without supporting measures” (chapter 5.2). The results of modal shift to the CLEVER vehicle come up to the politician’s expectations in 10 out of 13 cases. Most of them expected, that the results are very low; just two policy makers would have expected a greater shift to the CLEVER vehicle. Another comment on the modal-shift was that there are just little differences between both scenarios (two mentions). Two policy makers arrived to the conclusion that the public transport supply is not attractive enough. They found fault with the shift from the modes public transport and bike to CLEVER. In contrast to the comments on the modal-shift to the CLEVER vehicle most of the policy makers assessed the reduction of the emissions as remarkable (8 mentions) and categorised CLEVER as an “useful alternative mode”. 9.3.4 Feasibility of Measures Favouring the Use of CLEVER The interviewed persons stated their approach to measures which would have time and cost advantages for CLEVER users (compared to the use of a car) by declaring their support of the measures and by pointing out potential problems that would hamper the implementation of these measures. The sample in the following chapter includes 12 persons, because in one interview the part “support of measures favouring the use of CLEVER” was skipped by time reasons. Reserved Parking Spaces for CLEVER in the City Centre Most of the policy makers (8 out of 12 persons) would not support the arrangement of reserved parking spaces for CLEVER in the city centre (Figure 9-4). One named reason for their refusal was the low difference of modal shift between the scenarios “launch of CLEVER with supporting measures” and “without supporting measures” (2 mentions). In two cases the results of modal shift to CLEVER did not convince the politicians. Furthermore the target persons objected to privilege one product (3) and fear the people’s lack of acceptance (3). One named condition to support this measure was to keep the number of existing parking spaces up and create new ones for CLEVER.

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Support of measures ...

... reserved parking spaces

CLEVER

Yes

Yes, under certain conditions

3

1

... exemption from parking fees

... use of bus lanes

... exemption from road pricing

8

7

5

4

4

Missing, Not relevant

No

7

1

1

5

2

Number of mentions (n = 12 persons)

Figure 9-4:

Support of the measures “Reserved parking spaces for CLEVER in the city centre”, “Exemption from parking fees and no time limitations in onstreet parking zones for CLEVER”, “Use of designated bus lanes”, “Exemption from road pricing for CLEVER”, n=12 persons

Exemption from Parking Fees and No Time Limitations in On-Street Parking Zones for CLEVER Seven out of 12 persons would support to exclude the CLEVER-users from parking fees and time limitations in on-street parking zones (Figure 9-4). Refusals followed from very low modal shift to CLEVER (3) according to the results of the survey (“Results are not revolutionary!”) and because policy makers do not want to privilege one product (2). Policy makers also refused the support of this measure because they do not want to attract more traffic or parked vehicles in the inner city where required space exists (3). All of the interviewed persons from Thessaloniki, but no one from Vienna would support the exemption from parking fees and time-limitations for CLEVER-users. Use of Designated Bus Lanes by CLEVER In Braunau am Inn (Austria) the question was not relevant, because there are no designated bus lanes. Seven out of 12 policy makers objected to grant CLEVER vehicles the use of designated bus lanes (Figure 9-4). Main reason for their refusal was the risk of obstructions for busses or the risk to provoke accidents when

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CLEVER vehicles and busses share the lanes (4 mentions). The target persons also argued that the implementation of such measure is not warrantable, because in comparison with a bus a CLEVER vehicle transports a maximum of two persons (3). Another reason for no support of this measure was the low differences between the scenarios “with supporting measures” and “without supporting measures” (1). Exemption from Road Pricing for CLEVER Four out of 12 target persons generally would support an exemption from road pricing for CLEVER vehicles (Figure 9-4). In the case that road users will get any information about the benefits of CLEVER also another policy maker would support this measure. The most important reason for refusal was the use of revenues for road maintenance or for the support of public transport. The favourable characteristics of the CLEVER vehicle do not warrant an exemption from contributes to support public transport from the politicians’ point of view (4). Other reasons were the low modal shift to CLEVER (1) and the rejection to privilege one product (2). Nearly all of the target persons, who would support this measure derive from cities where no road pricing exists.

9.4 Summary of Interviews with Policy Makers In seven European cities overall 13 decision makers and experts from politics and administration were asked about existing traffic and transport problems, problems caused by traffic, possible solutions to solve those problems and their attitude towards the concept of CLEVER. Especially their assessment of the CLEVER vehicle as an usable alternative mode and their preparedness to support the concept with special measures favouring the use of CLEVER were collected. The supporting measures were -

reserved parking spaces for CLEVER in the city centre,

-

no parking fees and no time limitations in on-street parking zones,

-

use of bus lanes and

-

exemption from road pricing.

As important problems pollutant and noise emissions, the lack of supply of public transport and parking problems were named most frequently. Reasonable measures to solve those problems were for example the extension of the public transport supply, parking management and measures favouring pedestrians and cyclists from the policy makers’ point of view. The policy maker’s first impressions of the CLEVER vehicle were mostly positive (20 positive, 12 negative mentions) especially concerning the vehicle’s aesthetic Page - 130 -


CLEVER

design and its low emissions. The interviewed persons assessed the results of the behavioural analysis (modal shift to CLEVER) as low and pointed out that there are just small differences of the modal shift between both scenarios (“with supporting measures” and “without supporting measures”). The survey shows the policy makers’ sceptical attitude towards the implementation of supporting measures favouring the use of CLEVER. In principle they do not refuse the vehicle as an unusable alternative mode or as no smart concept, but policy makers -

expect difficulties arising from the implementation of supporting such momentous measures,

-

classify the vehicle’s positive effects as “not revolutionary” and/or

-

see no urgent need for their support because of the low differences between the scenarios.

Therefore the common consent to implement supporting measures exists but is very low. An exemption from parking fees and time limitations in on street parking zones to support the use of CLEVER vehicles is the most accepted measure according to the answers of the interviewed persons (Figure 9-4). Reserved parking spaces in the city centre for CLEVER and the use of designated bus lanes are the most refused ones. A high acceptance of the parking fee-exemption could be caused by an effortless feasibility, policy makers associate with. Tendencies in the general statements of the policy makers can be derived, that -

in Greece there’s the highest disposition to implement supporting measures - in opposition the lowest in Austria (Table 9-3),

-

rather experts from politics than experts from administration would support measures favouring the use of CLEVER and

-

rather policy makers with “high” than with “low” authority would support measures favouring the use of CLEVER.

Table 9-3:

Comparison (Austria and Greece) of mentions "rather yes" and "rather no" towards the support of measures favouring the use of CLEVER, percentage of total mentions

country

support of measures … … rather yes

… rather no

Austria

29 %

64 %

Greece

75 %

25 %

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The acceptance in Thessaloniki could be caused by the high volume of traffic with a simultaneous lack of parking spaces in the inner city. One possible explanation for the higher willingness to support CLEVER on the part of politicians and policy makers with “high authority” is that politicians might regard CLEVER as chance to make transport policy by supporting this environmental friendly type of vehicle.

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10 CONCLUSIONS The following findings can be drawn as a result of the Deliverable 6 “Benefits for Urban Traffic”: Market Potential The share of trips of residents which can be shifted to the CLEVER vehicle has a range between 2 and 13% indicated by the two case cities Graz and Thessaloniki, which indicates quite a respectable market potential. This modal shift comes mainly from car drivers but one third can be originated also from public transport. The size of this range is caused by different influencing factors. On the one hand very important are the existing traffic conditions as the parking and congestion problem. A high lack of parking spaces and a high load of traffic in central parts of the conurbations increases the potential of the CLEVER vehicle. On the other hand the quality and standard of the alternative modes relating to the car has a strong influence on the market potential of CLEVER: The availability of alternative modes on a high quality level reduces the potential share. That leads to the conclusion, that the CLEVER vehicle is an interesting alternative in cities with big car traffic problems. It has to be stated that also the cultural and climatic background plays a role. It seems that the Mediterranean countries have a greater potential for CLEVER as it can be observed also for motorbikes. The user costs of cars (e.g. fuel price and road pricing) and the purchase costs of the CLEVER vehicle are an additional influencing factor for the potential share of the modal split. Accompanying promoting measures have a less effect on the use of CLEVER than expected. The range of the potential differs between the scenario with and without accompanying promotion measures for CLEVER (e.g. allowance of use of bus lanes for CLEVER, designated parking spaces for CLEVER, exception of road pricing) only up to 2 %. The potential user group of CLEVER consists mainly of male persons in the age group between 45 and 65 years. Economic and Environmental Effects The main important benefits of the CLEVER vehicle are the reduction in exhaust gas emissions and fuel consumption. The reduction has a potential range up to 17 % dependent of the single components of pollutants and the realized mode shift to CLEVER. The implementation of the CLEVER vehicle lets expect a small decrease of the travelled journey time. The potential reduction for CO2-emissions and fuel consumption indicates a range up to 12 % for the analysed scenarios. There is no significant change in the indicators of traffic safety and the total economic costs, but there is a remarkable benefit from the side of public household: the implementation of the CLEVER vehicle doesn’t require huge public investments, it is mainly based on private investments.

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Attitudes of Policy Makers Towards CLEVER Policy makers and transport experts have a mostly positive attitude mainly based on the contribution to reduce air pollutants and CO2 emissions as well as the innovative vehicle aesthetic design. They welcome a new vehicle like CLEVER on the market, but they see no urgent need to give specific incentives and support for the implementation of the CLEVER vehicle, because the positive effect of these accompanying measures for the CLEVER is not respectable enough to argue such activities towards the public.

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11 GLOSSARY AND ABBREVIATIONS CBA

Cost Benefit Analysis

CNG

Compressed Natural Gas

GTA

Greater Thessaloniki Area

HOT lanes

High Occupancy Toll (HOT) lanes: high occupancy vehicles are allowed to use a HOT lane for free, drivers of vehicles without any passenger have to pay for using a HOT lane.

HOV lanes

High Occupancy Vehicle (HOV) lanes: only vehicles with more than (one) two passengers are allowed to be driven on those lanes

M

Million

Modal Split

Allocation of trips according to the used modes

Mode Shift

Change in mobility behaviour concerning the mode used for a trip

MVEG

Motor Vehicle Emissions Group

N/A

not applicable

PT

Public Transport

RP survey

Revealed preference survey – The real behaviour of the interviewees is examined on the basis of a past situation. In this project the real mobility behaviour (mode choice, trip destination, trip length, number of trips per day etc.) of a past day is resumed.

SP survey

Stated preference survey – The hypothetical behaviour of the interviewees (mode choice in this project) is asked on the basis of given modified (travel) conditions respectively different (trip/mode) characteristics.

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12 LIST OF FIGURES Figure 1-1:

CLEVER Project Structure Plan

Figure 2-1:

Front side of the three-wheeled CLEVER

10

Figure 2-2:

Interior of CLEVER – offering room for two occupants

10

Figure 2-3:

CLEVER CNG engine and refuelling system at the back of the vehicle

11

Figure 2-4:

CLEVER tilting mechanism

12

Figure 3-1:

CLEVER research flow

13

Figure 3-2:

Steps of in-depth interview

16

Figure 3-3:

Share of classes of weights, Graz, n=971 persons

20

Figure 3-4:

Share of classes of weights, Thessaloniki, n=797 persons

20

Figure 4-1:

City map of Graz with districts with parking management marked

24

Figure 4-2:

Map of Greater Thessaloniki Area

25

Figure 6-1:

Confidence intervals / random error related to percentage values of the share of an attribute for Graz and Thessaloniki, person level

36

Confidence intervals / random error related to percentage values of the share of an attribute for Graz and Thessaloniki, trip level

36

CLEVER assessment according to its practical characteristics by all the respondents (CLEVER users and Non-CLEVER users) in GRAZ and in GREATER THESSALONIKI AREA, 2003, [+2 … very positive, -2… very negative]

38

CLEVER assessment according to its technical characteristics by all the respondents (CLEVER users and Non-CLEVER users) in GRAZ and in GREATER THESSALONIKI AREA, 2003, [+2 … very positive, -2… very negative]

38

Reasons and arguments for the use of CLEVER by all respondents (CLEVER users and Non-CLEVER users) in GRAZ and in GTA, 2003

39

Reasons and arguments against the use of CLEVER by all respondents (CLEVER users and Non-CLEVER users) in GRAZ and in GTA, 2003

40

Figure 7-5:

Modal shift in Scenario A in GRAZ, 2003

42

Figure 7-6:

Modal shift in Scenario B in GRAZ, 2003

42

Figure 7-7:

Modal shift in Scenario C in GRAZ, 2003

43

Figure 7-8:

Modal split in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips

44

Figure 6-2:

Figure 7-1:

Figure 7-2:

Figure 7-3:

Figure 7-4:

8

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Figure 7-9:

CLEVER

Modal shift in Scenario A in GREATER THESSALONIKI AREA, 2003

44

Figure 7-10: Modal shift in Scenario B in GREATER THESSALONIKI AREA, 2003

45

Figure 7-11: Modal shift in Scenario C in GREATER THESSALONIKI AREA, 2003

45

Figure 7-12: Modal split in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n= 474 trips

46

Figure 7-13: Reasons of car drivers for the choice of the car and arguments against the choice of CLEVER in Scenario C in GRAZ and in GREATER THESSALONIKI AREA, 2003 Graz: n=253 positive mentions, 202 negative mentions GTA: n=217 positive mentions, 128 negative mentions

50

Figure 7-14: Reasons of CLEVER users for the choice of CLEVER in Scenario C in GRAZ and in GREATER THESSALONIKI AREA, 2003 Graz: n=24 mentions GTA: n=113 mentions

51

Figure 7-15: Modal split related to gender in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips

52

Figure 7-16: Modal split related to gender in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n=474 trips

54

Figure 7-17: Modal split related to age in GRAZ in Scenario C, 2003, n=557 trips

55

Figure 7-18: Modal split related to age in GREATER THESSALONIKI AREA in Scenario C, 2003, n=474 trips

56

Figure 7-19: Modal split related to trip purpose in GRAZ in Scenario C, 2003, n=557 trips

59

Figure 7-20: Modal split related to trip purpose in GREATER THESSALONIKI AREA in Scenario C, 2003, n=474 trips

59

Figure 7-21: Modal split related to trip length in GRAZ in Scenario C, 2003, n=557 trips

62

Figure 7-22: Modal split related to trip length in GREATER THESSALONIKI AREA in Scenario C, 2003, n=474 trips

62

Figure 7-23: Hypothetical and use of CLEVER in one of the Scenarios in GRAZ and in GREATER THESSALONIKI AREA, 2003

64

Figure 7-24: Type of hypothetical CLEVER availability in GRAZ and in GREATER THESSALONIKI AREA, 2003

65

Figure 7-25: Type of hypothetical CLEVER status in GRAZ and in GREATER THESSALONIKI AREA, 2003

65

Figure 8-1:

69

Approach of the CBA

Page - 137 -


Figure 8-2: Figure 8-3: Figure 8-4:

Figure 8-5: Figure 8-6:


Figure 8-9.

CLEVER

Emissions related to speed according to petrol and diesel cars for a passenger car collective for 2002 [FGSV 1997]

70

Relative change of the emission loads in GRAZ compared to the actual state in the three scenarios, 2003

75

Relative change of the emission loads in GREATER THESSALONIKI AREA compared to the actual state in the three scenarios, 2003

76

Fuel consumption in [M l/year] for petrol and diesel in GRAZ in the actual state and in the three scenarios, 2003

81

Fuel consumption in [M l/year] for petrol and diesel in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003

82

CNG consumption in [t/year] in GRAZ and in GTA in the three scenarios, 2003

83

Running costs (sum of energy costs and basic values for running costs) for passenger cars and for CLEVER in [M €/year] in GRAZ in the actual state and in the three scenarios, 2003

88

Running costs (sum of energy costs and basic values for running costs) for passenger cars and for CLEVER in [M €/year] in GTA in the actual state and in the three scenarios, 2003

89

Figure 8-10: Number of casualties per year in GRAZ according to the modes in the actual state and in the three scenarios, 2003

98

Figure 8-11: Change of casualties according to the severity of injury in GRAZ in the three scenarios compared to the actual state, 2003

99

Figure 8-12: Number of casualties per year in GREATER THESSALONIKI AREA according to the modes in the actual state and in the three scenarios, 2003

100

Figure 8-13: Change of casualties according to the severity of injury in GREATER THESSALONIKI AREA in the three scenarios compared to the actual state, 2003

101

Figure 8-14: Journey time according to the modes in [h/day] in GRAZ in the actual state and in the three scenarios, 2003

105

Figure 8-15: Journey time according to the modes in [h/day] in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003

107

Figure 8-16: Results of the CBA in GRAZ – costs and savings in [M €/year] in the actual state and in the three scenarios, 2003

117

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CLEVER

Figure 8-17: Results of the CBA in GREATER THESSALONIKI AREA – costs and savings in [M €/year] in the actual state and in the three scenarios, 2003

119

Figure 9-1: Approach of the interviews with policy makers

121

Figure 9-2:


Average assessment of measures to solve transport and traffic problems from 5 - not important to 1 - very important, n=12 persons

126

First impressions of CLEVER of the policy makers, multiple mentions possible, n=13 persons, 38 mentions

127

Support of the measures “Reserved parking spaces for CLEVER in the city centre”, “Exemption from parking fees and no time limitations in on-street parking zones for CLEVER”, “Use of designated bus lanes”, “Exemption from road pricing for CLEVER”, n=12 persons

129

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13 LIST OF TABLES Table 3-1:

Net sample of the household survey in GRAZ and in GREATER THESSALONIKI AREA, 2003/2004

17

Net sample of the in-depth interviews in GRAZ and in GREATER THESSALONIKI AREA, 2004

18

Table 5-1:

Infrastructure and organisational measures supporting CLEVER

28

Table 5-2:

Information and awareness measures supporting CLEVER

28

Table 5-3:

Accompanying measures and others supporting CLEVER

29

Table 5-4:


30

Table 5-5:

Advantages/disadvantages of the use of CLEVER regarding travel time and costs in Scenario A in comparison to originally used modes

31

Advantages/disadvantages of the use of CLEVER regarding travel time and costs in Scenario B in comparison to originally used modes

32

Advantages/disadvantages of the use of CLEVER regarding travel time and costs in Scenario C in comparison to originally used modes

33

Confidence intervals / random error related to percentage values of the share of an attribute for Graz and Thessaloniki, person and trip level

35

Possible alternatives for mode choice in the three scenarios according to the originally chosen mode

41

Person mileage per mode [km/day] in the actual state compared to the Scenarios A, B and C for Graz

47

Person mileage per mode [km/day] in the actual state compared to the Scenarios A, B and C for Thessaloniki

48

Modal split related to gender in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips

53

Modal split related to gender in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n=474 trips

54

Modal split related to age in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips

55

Modal split related to age in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n=474 trips

57

Modal split related to trip purpose in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips

58

Table 3-2:

Table 5-6:

Table 5-7:

Table 6-1:

Table 7-1: Table 7-2: Table 7-3: Table 7-4: Table 7-5:

Table 7-6: Table 7-7: Table 7-8:

Page - 140 -


Table 7-9:

CLEVER

Modal split related to trip purpose in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n=474 trips

60

Table 7-10: Modal split related to trip length in GRAZ in the actual state and in the three scenarios, 2003, n=557 trips

61

Table 7-11: Modal split related to trip length in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003, n=474 trips

63

Table 7-12: CLEVER potential under Scenario C in GRAZ and in GREATER THESSALONIKI AREA, 2003

66

Table 8-1: Table 8-2: Table 8-3:

Table 8-4:

Table 8-5: Table 8-6:

Table 8-7:

Table 8-8:

Table 8-9:

Parameters c0, c1 and c2 of the emission factors (related to speed) for petrol and diesel cars, 1990 [FSGV 1997]

71

Emission factor cs [g/vehicle-km] at congestion within built-up areas for petrol and diesel cars, 1990 [FSGV 1997]

71

Reduction factor kf (Y) for pollutants (basic year 1990 = 1) for year 1995, 2000, 2005 and 2010 for petrol and diesel cars [FSGV 1997]

72

Ratio of petrol and diesel passenger cars in Austria [STATISTIK AUSTRIA 2004] and Greece [NTZIACHRISTOS L., Z. SAMARAS 2000], 2003

72

Emissions of CNG vehicles compared to petrol [European Natural Gas Association 2005] and diesel cars (FGW 2005]

73

Kilometres travelled per day by CLEVER [km/day] in GRAZ and in GREATER THESSALONIKI AREA in the three scenarios, 2003

74

Results of the emission loads in GRAZ in [tons/year] in the actual state [Forschungsgesellschaft fuer Verbrennungskraftmaschinen und Thermodynamik mbH 2004] and in the three scenarios, 2003

75

Results of the emission loads in GREATER THESSALONIKI AREA in [tons/year] in the actual state [SAMARAS Z. et al. 2002 and NTZIACHRISTOS L., Z. SAMARAS 2000] and in the three scenarios, 2003

76

Costs [€] per ton hazardous air pollutants [PISCHINGER R., G. SAMMER, F. SCHNEIDER et al. 1998] and per ton CO2 [FGSV 1997] in Austria and in Greece [ATTIKO METRO 2005], 2003

77

Table 8-10: Results of the emission costs in GRAZ in [M €/year] in the actual state and in the three scenarios, 2003

78

Table 8-11: Results of the emission costs in GREATER THESSALONIKI AREA in [M €/year] in the actual state and in the three scenarios, 2003

79

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CLEVER

Table 8-12: Parameters c0, c1, c2 of the factors of fuel consumption (related to speed) and factor of fuel consumption cs [g/vehicle-km] for congestion within built-up areas for petrol and diesel cars, 1990 [FSGV 1997]

80

Table 8-13: Reduction factor kf (Y) for fuel consumption (basic year 1990 = 1) for year 1995, 2000, 2005 and 2010 for petrol and diesel cars [FSGV 1997]

80

Table 8-14: Fuel consumption in [M l/year] for petrol and diesel and in [t/year] for CNG in GRAZ in the actual state and in the three scenarios, 2003

81

Table 8-15: Fuel consumption in [M l/year] for petrol and diesel and in [t/year] for CNG in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003

82

Table 8-16: Kilometres travelled per day [km/day] (including car driver, motorcycle/moped and CLEVER trips) in GRAZ in the actual state and in the three scenarios, 2003

83

Table 8-17: Kilometres travelled per day [km/day] (including car driver, motorcycle/moped and CLEVER trips) in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003

84

Table 8-18: Average fuel prices for petrol and diesel [€/l] [OEAMTC 2005] and for CNG [€/kg] [FGW 2005)] in AUSTRIA in 2003

84

Table 8-19: Avarage fuel prices for petrol and diesel [€/l] [Ministry of Development 2004] in GREECE in 2003 and for CNG [€/kg] according to assumptions

85

Table 8-20: Basic value for running costs for passenger cars and for CLEVER in [€/vehicle-km] in AUSTRIA [FGSV 1997] and in GREECE [Ministry for the Environment, Physical Planning and Public Works 2001], 2003

85

Table 8-21: Fuel costs in [M €/year] for petrol, diesel and CNG in GRAZ in the actual state and in the three scenarios, 2003

86

Table 8-22: Fuel costs in [M €/year] for petrol, diesel and CNG in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003

86

Table 8-23: Basic values for running costs for passenger cars and for CLEVER in [M €/year] in GRAZ in the actual state and in the three scenarios, 2003

87

Table 8-24: Basic values for running costs for passenger cars and for CLEVER in [M €/year] in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003

87

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CLEVER

Table 8-25: Running costs (sum of energy costs and basic values for running costs) for passenger cars and for CLEVER in [M €/year] in GRAZ in the actual state and in the three scenarios, 2003

88

Table 8-26: Running costs (sum of energy costs and basic values for running costs) for passenger cars and for CLEVER in [M €/year] in GTA in the actual state and in the three scenarios, 2003

89

Table 8-27: Kilometres travelled [km] per day (including car driver, motorcycle/ moped and CLEVER trips) in GRAZ and in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003

90

Table 8-28: Change of share and number of persons who feel disturbed by noise caused by traffic in GRAZ in the actual state and in the three scenarios, 2003

91

Table 8-29: Change of share and number of persons who feel disturbed by noise caused by traffic in GREATER THESSALONIKI AREA in the actual state and in the three scenarios, 2003

92

Table 8-30: Noise costs per person who is disturbed by noise caused by traffic in [€] in AUSTRIA [PISCHINGER R., G. SAMMER, F. SCHNEIDER et al. 1998], 2003

92

Table 8-31: (Traffic) Noise costs in [Mio. €/year] in Graz in the actual state and in the three scenarios, 2003

93

Table 8-32: (Traffic) Noise costs in [Mio. €/year] in Thessaloniki in the actual state and in the three scenarios, 2003

93

Table 8-33: Number of casualties in road accidents according to modes and severity of injury in GRAZ, average of five years (1999 – 2003) [KfV 2000 to 2004]

94

Table 8-34: Number of casualties in road accidents according to modes and severity of injury in GREATER THESSALONIKI AREA, average of five years (1996 – 2001) [ROAD ACCIDENTS GTA 2001]

94

Table 8-35: Probability to be killed respectively to be injured (according to the severity of injury) per mode and kilometres travelled per year [Casualties / 100.000 km] for GRAZ in the actual state

95

Table 8-36: Probability to be killed respectively to be injured (according to the severity of injury) per mode and kilometres travelled per year [Casualties / 100.000 km] for GREATER THESSALONIKI AREA in the actual state

96

Table 8-37: Number of casualties per year in GRAZ according to the severity of injury in the actual state and in the three scenarios, 2003

98

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Table 8-38: Number of casualties per year in GREATER THESSALONIKI AREA according to the severity of injury in the actual state and in the three scenarios, 2003

100

Table 8-39: Road accident costs in [€] according to the severity of injury for Austria [METELKA 1997] and Greece [ATTIKO METRO 2005], 2003

101

Table 8-40: Accident costs in [M €/year] in GRAZ according to the severity of injury in the actual state and in the three scenarios, 2003

102

Table 8-41: Accident costs in [M €/year] in GREATER THESSALONIKI AREA according to the severity of injury in the actual state and in the three scenarios, 2003

103

Table 8-42: Journey time in [h/day] in GRAZ according to the modes in the actual state and in the three scenarios, 2003

104

Table 8-43: Saving of journey time according to the mode shift in [h/day] in GRAZ in the scenarios compared to the actual state, 2003

105

Table 8-44: Journey time in [h/day] in GREATER THESSALONIKI AREA according to the modes in the actual state and in the three scenarios, 2003

106

Table 8-45: Saving of journey time according to the mode shift in [h/day] in GTA in the scenarios compared to the actual state, 2003

107

Table 8-46: Time costs in [€/hour] in AUSTRIA [PISCHINGER R., G. SAMMER, F. SCHNEIDER et al. 1998] and GREECE [ATTIKO METRO 2005], 2003

108

Table 8-47: Journey time costs in [M €/year] in GRAZ according to the modes in the actual state and in the three scenarios, 2003

108

Table 8-48: Journey time costs in [M €/year] in GREATER THESSALONIKI AREA according to the modes in the actual state and in the three scenarios, 2003

109

Table 8-49: Parking infrastructure in the inner city of GRAZ (districts 1 – 6) [GRAZ 2005]

109

Table 8-50: Parking infrastructure in GREATER THESSALONIKI AREA in the different transport sectors [Organisation of Thessaloniki for the Thessaloniki Master Plan Implementation and Environmental Protection 1998]

110

Table 8-51: Required CLEVER parking spaces in the districts 1 – 6 in GRAZ in the three scenarios, 2003

111

Table 8-52: Required car parking spaces in the districts 1 – 6 in GRAZ in the three scenarios, 2003

112

Table 8-53: Required CLEVER parking spaces in the transport districts 1 – 6 in GEATER THESSALONIKI AREA in the three scenarios, 2003

112

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CLEVER

Table 8-54: Required car parking spaces in the sectors 1 – 6 in GTA in the three scenarios, 2003

113

Table 8-55: Costs for marking a CLEVER parking space in AUSTRIA [Information by MA 46, Verkehrsorganisation und technische Angelegenheiten, Wien 2005] and in GREECE [estimation], 2003

114

Table 8-56: Costs for CLEVER parking infrastructure in [€/year] in GRAZ and in GREATER THESSALONIKI AREA in the three scenarios, 2003

114

Table 8-57: Number of trips skipped due to increasing travel costs in Scenario C in GRAZ and in GREATER THESSALONIKI AREA

114

Table 8-58: Results of the Cost Benefit Analysis in GRAZ according to the indicators, costs in [M €/year] in the actual state and in the three scenarios, 2003

116

Table 8-59: Cost difference in GRAZ in the three scenarios according to the indicators compared to the actual state 2003 in [M € / year]

116

Table 8-60: Results of the Cost Benefit Analysis in GREATER THESSALONIKI AREA according to the indicators, costs in [M €/year] in the actual state and in the three scenarios, 2003

118

Table 8-61: Cost difference in GREATER THESSALONIKI AREA in the three scenarios according to the indicators compared to the actual state 2003 in [M €/year]

119

Table 9-1:

Gross and net sample size per city and per country (persons)

123

Table 9-2:

Authorities of target persons

124

Table 9-3:

Comparison (Austria and Greece) of mentions "rather yes" and "rather no" towards the support of measures favouring the use of CLEVER, percentage of total mentions

131

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14 BIBLIOGRAPHY AND REFERENCES ATTIKO METRO (2005): Economic Evaluation Study of Thessaloniki Metro System. Thessaloniki 2005 BGW Bundesverband der deutschen Gas- und Wasserwirtschaft e.V. (2003): http://www.erdgasfahrzeuge.de (01.10.03), Berlin 2003 European Natural Gas Vehicle Association (2005): http://www.engva.org, April 2005 FGW (2005): http://www.erdgasautos.at (Erdgasfahrzeuge in Oesterreich), Fachverband Gas Waerme, Wien 2005 Forschungsgesellschaft für Strassen- und Verkehrswesen (FGSV): Empfehlungen für Wirtschaftlichkeitsuntersuchungen an Straßen (EWS). Arbeitsgruppe Verkehrsplanung, Aktualisierung der RAS-W 86, Ausgabe 1997, Koeln 1997 Forschungsgesellschaft fuer Verbrennungskraftmaschinen und Thermodynamik mbH (2004): Emissionskataster Graz 2001. Teilbericht Verkehr – Bezugsjahr 2003. i.A. des Amtes der Steiermärkischen Landesregierung, Fachabteilung 17c, Graz 2004 General Secretariat of National Statistical Service of Greece (2001): Socioeconomic data. Greece 2001 GRAZ (2005): http://graz.at/parken/ (Parken in Graz), 29.03.2005 KfV (2004): Unfallstatistik 2003 – Steiermark. Hrsg. Kuratorium fuer Verkehrssicherheit, Institut fuer Unfallstatistik, Wien 2004 KfV (2003): Unfallstatistik 2002 – Steiermark. Hrsg. Kuratorium fuer Verkehrssicherheit, Institut fuer Unfallstatistik, Wien 2003 KfV (2002): Unfallstatistik 2001 – Steiermark. Hrsg. Kuratorium fuer Verkehrssicherheit, Institut fuer Unfallstatistik, Wien 2002 KfV (2001): Unfallstatistik 2000 – Steiermark. Hrsg. Kuratorium fuer Verkehrssicherheit, Institut fuer Unfallstatistik, Wien 2001 KfV (2000): Unfallstatistik 1999 – Steiermark. Hrsg. Kuratorium fuer Verkehrssicherheit, Institut fuer Unfallstatistik, Wien 2000

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LEDA – Legal and regulatory measures for sustainable transport in cities (1999): Funded by the European Commission, DGVII, under the Transport RTD Programme, www.leda.ils.nrw.de (14.07.2005), 1999 LONDON (2005): What is congestion charging? www.cclondon.com/whatis.shtml (14.07.2005), 2005 METELKA M. (1997) : Österreichische Unfallkosten- und Verkehrssicherheitsrechnung. Hrsg. Bundesministerium fuer Wissenschaften und Verkehr, Forschungsarbeiten aus dem Verkehr, Band 79, Wien 1997 Ministry for the Environment, Physical Planning and Public Works (2001): Study for the running cost calculation. Greece 2001 Ministry of Development (2004): The petroleum products market. Hellenic Petroleum S.A., Greece 2004 NEUMANN A. (2003): Korrekturverfahren für Stichproben von Verkehrsverhaltenserhebungen des Personenfernreiseverkehrs, Institut fuer Verkehrswesen, Universitaet fuer Bodenkultur Wien, Wien 2003 NTZIACHRISTOS L., Z. SAMARAS (2000): COPERT III – Computer programme to calculate emissions from road transport. Methodology and emission factors (Version 2.1), Technical report No 49, European Environmental Agency, Copenhagen 2000 OEAMTC (2005): http://www.oeamtc.at (Entwicklung der Treibstoffpreise) March 2005 OESTERREICHISCHES BUNDESRECHT (2003): http://www.ris.bka.gv.at (Erdgasabgabegesetz BGBl. I Nr. 71/2003) Wien 2003 Organisation of Thessaloniki for the Thessaloniki Master Plan Implementation and Environmental Protection (1998): General Transport and Traffic Study for Thessaloniki Agglomeration and Greater Thessaloniki Area. Thessaloniki 1998 PISCHINGER R., G. SAMMER, F. SCHNEIDER (1998): Volkswirtschaftliche KostenNutzenanalyse von Maßnahmen zur Reduktion der CO2-Emission des Verkehrs in Österreich. i.A. des BM für Umwelt, Jugend und Familie (Akademie fuer Umwelt und Energie), Graz-Linz-Wien 1998 ROAD ACCIDENTS GTA (2001): Greater Thessaloniki Area Road Accidents Statistics 1996 – 2001. Traffic Police Database for Traffic Accidents, GTA 2001

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SAMARAS Z. et al. (2002) : Development of a database system for the calculation of indicators of environmental pressure caused by transport. TRENDS Detailed Report 1: Road Transport Module, Greece 2002 SAMMER G., F. WERNSPERGER (1992): Die verkehrspolitische Einstellung der Grazerinnen und Grazer. Meinungen und Fakten im Zeitvergleich. im Auftrag des Magistrats Graz 1992 SAMMER G., G., ROESCHEL, V. SAURUGGER (1994): Gesamtverkehrskonzept 1994 der Landeshauptstadt Graz. Generelles Maßnahmenprogramm. Im Auftrag des Magistrats Graz, Stadtbaudirektion, Verkehrsreferat, Graz 1994 SAMMER G., WERNSPERGER F. (1994): Stadtverkehr der Zukunft, neues motorisiertes Zweirad. Verlag fuer die Technische Universitaet Graz, Heft Nr. 18, Garz 1994 SAMMER G., ROIDER O., KLEMENTSCHITZ R. (2004) : MS-Wien. Volkswirtschaftliche Auswirkung eines reduzierten OEV-Anteils des Modal Splits im Wiener Verkehr. Institut fuer Verkehrswesen, Universitaet fuer Bodenkultur Wien. i.A. der Wiener Linien & Co KG und der MA18 Stadtentwicklung und Stadtplanung, Wien 2004 STADT GRAZ (2005): www.graz.at (11.07.05), Graz 2005 STATISTIK AUSTRIA (2001): Statistisches Jahrbuch Oesterreichs. Ausgabe 2001, Wien 2001 STATISTIK AUSTRIA (2004): Statistik der Kraftfahrzeuge 2003. Wien 2004 STATISTIK AUSTRIA (2003): Volkszählung 2001. Hauptergebnisse I – Steiermark. Wien 2003 STATISTIK AUSTRIA (2005): Großzählung 2001. Ausgewählte Maßzahlen nach Gemeinden. Wien 2005 STATISTIK AUSTRIA (2005): Statistik der Kraftfahrzeuge. Bestand am 31.12.2004. Wien 2005 THALLER O. (1999): Impact analysis of urban road-use pricing on travel behaviour, the environment and the economy. Doctoral thesis on the Universitaet fuer Boenkultur Vienna, Institute for Transport Studies, Vienna 1999 Transportation and Traffic Plan for Greater Thessaloniki Area (1998): Car Ownersip Index. Greece 1998 Page - 148 -


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VENTURI S. (2005): Emissions’ comparison according to fuel type. CLEVER Working paper, IFP, Lyon 2005 VEST Energie Marketing (2005): http://www.gas24.de (Erdgasfahrzeuge), Osnabrueck 2005 VENTURI S. (2003): Average consumption on European driving cycle MVEG. CLEVER Working paper, IFP, Lyon 2003

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15 ANNEX 1 – QUESTIONNAIR OF THE DAILY MOBILITY SURVEY

EXPLANATORY NOTES FOR FILLING IN THE INDIVIDUAL QUESTIONNAIRES

There is one INDIVIDUAL QUESTIONNAIRE for each member of your household aged 6 or older. Please help children and elderly persons with the questionnaire. Please fill in the first name of all members of your household and the number assigned to them in the INDIVIDUAL QUESTIONNAIRE! Please tick off all the modes of transport used for each trip! Please enter all the trips made throughout the reporting day. Please don’t forget any trips! Even walks, short trips and return trips are important! A „trip“ is defined as the move from a starting point to a certain destination which you made for a certain purpose (e.g. shopping, going to work or home). You might have used several modes of transport. If you need more INDIVIDUAL QUESTIONNAIRES because there are more than 5 persons aged 6 or older in your household, please dial the number listed below and request additional questionnaires. A person can use an additional INDIVIDUAL QUESTIONNAIRE if s/he made more than 7 trips on the reporting day. In this case the number assigned to this person in the HOUSEHOLD QUESTIONNAIRE has to be used also for the additional INDIVIDUAL QUESTIONNAIRE. If you need additional questionnaires ring the number listed below and request them. Please return the completed questionnaires even if you did not leave the house on the reporting day. Please complete the INDIVIDUAL QUESTIONNAIRE for the following reporting day: Please return the completed HOUSEHOLD QUESTIONNAIRE and all the INDIVIDUAL QUESTIONNAIRES on the day after the reporting day. By doing that you save us a lot of work and further inquires. For your convenience please find a return envelope enclosed. If you have any further questions, please contact: Name of the contact person Name of the organisation in charge of the survey Telephone number, Monday till Friday x:00 to y:00 ALL INFORMATION IS CONSIDERED STRICTLY CONFIDENTIAL AND THE EVALUATION WILL BE CARRIED OUT ANONYMOUSLY. Participation in this survey is voluntary. The validity of the results, however, is highly dependent on a vast majority of all the households contacted returning these questionnaires. Thank you very much for filling in these questionnaires and for contributing to the success of this study, which is being carried out also for your sake!

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TRAVEL SURVEY THESSALONIKI Please note

Please complete the HOUSEHOLD QUESTIONNAIRE before filling in the INDIVIDUAL QUESTIONNAIRES! Please answer the questions on this page first. Then fill in the answers on the other side of the household questionnaire for all members aged 6 or older! Please read the explanatory notes on the accompanying sheet before filling in the individual questionnaires!

HOUSEHOLD QUESTIONNAIRE Members of your household are all persons (including yourself) who are living with you. A household can also consist of a single person (one-person-household). Residents of senior citizens’ homes, students’ hostels etc. are also regarded as one-person households. How many persons are living in your household including yourself? Number of persons:

Children younger than 3 years old:

Children 3 to 5 years old:

How far from your home is the nearest public transport stop (bus stop or railway station)? Do you have a telephone or mobile phone in your household?

Yes

No

Do you have a private Internet access in your household?

Yes

No

m

Please answer now the questions on the back side of this questionnaire for all members of your household aged 6 or older!

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PLEASE ANSWER NOW THE FOLLOWING QUESTIONS FOR ALL MEMBERS OF YOUR HOUSEHOLD AGED 6 OR OLDER Persons in your household aged 6 or older

Oldest person

Second eldest person

Third eldest person

Forth eldest person

Fifth eldest person

1

2

3

4

5

First name

First name

First name

First name

First name

Year of birth

Year of birth

Year of birth

Number assigned to the person DEMOGRAPHIC DATA

Year of birth

Gender

male

female

Year of birth

male

female

male

female

male

female

male

female

LEVEL OF EDUCATION COMPLETED Primary and secondary school Primary, secondary and vocational school A-levels (university entrance exam) University degree OCCUPATION / EMPLOYMENT Full-time employed (more than 30 hours a week) Part time employed (up to 30 hours a week) Not employed Home duties (full time) Retired On maternity leave Military service At present unemployed / looking for work Student (school or university) Apprentice WORKING HOURS Do you have flexible working time?

Yes

How many hours (including overtime) did you work last week?

No

Yes

Hours

No

Yes

Hours

No

Yes

Hours

No

Yes

No

Hours

Hours

CAR PARKING Do you have a place to park your car at work owned by your company?

Yes

No

Yes

No

Yes

No

Yes

No

Yes

No

Do you have a private car parking place (hired or owned) at your home?

Yes

No

Yes

No

Yes

No

Yes

No

Yes

No

Do you have a driving licence for cars?

Yes

No

Yes

No

Yes

No

Yes

No

Yes

No

Do you have a driving licence for mopeds/motorcycles?

Yes

No

Yes

No

Yes

No

Yes

No

Yes

No

DRIVING LICENCE

OWNERSHIP OF VEHICLES

Number

Number

Number

Number

Number

Car (personal property) Car (owned by your company but for private use) Van Moped, motorcycle Bicycle Others, please specify: OWNERSHIP OF A PUBLIC TRANSPORT PASS OR A RAILWAY DISCOUNT CARD None Weekly ticket Monthly ticket Annual ticket (Free) student pass Others, please specify:

Please note: On the back side of this questionnaire you will find important information for further proceedings!

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16 ANNEX 2 – INTERVIEW GUIDELINES OF THE IN-DEPTH SURVEY

The interview is confidential and must not be made accessible to any third party in any way whatsoever.

Implementation and contacts: TRIAS SA Consulting 39 G.Seferi Str, GR 54250 Thessaloniki Contact person:

Maria Peleka Tel. e-mail: [email protected] Panos Papaioannou Tel. e-mail: [email protected]

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CLEVER

1. Choice of the households and target persons

3. Agreement of an appointment for the in-depth interview

4. Preparation and precoding of the interview (at TRIAS)

TRIAS

/

To the extent possible, all household members who made a trip on the reporting date should attend, all chosen target persons (passenger car drivers) must attend the interview (appointment in the evening or at the weekend). Presumable duration of the interview (depending on the size of the household and number of trips): 60 - 120 minutes

INTERVIEWER

2. Establishment of telephone contact

5. Conducting of the interview

6. Checking and delivery at TRIAS

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CLEVER

ALLOCATION OF INTERVIEW GROUPS All households shall be assigned to one of 4 possible interview groups. The groups differ in terms of the boundary conditions (duration/time and costs of the trips) in scenarios B and C.

Interview group 1

Interview group 2

I C / IT

IC / IIT

IIC / IIT

IIC / IT

Interview group 4

Interview group 3

Index C ... Costs Index T … Time

IC ...

Fuel price increase in scenario C by 75%

IIC ... Fuel price increase in scenario C by 150% IT ...

Time saved with the CLEVER in scenarios B and C

IIT ... Additional time saved with the CLEVER in scenarios B and C

In total, each of the 4 groups should account for 25% of the surveyed households. Method: Household 1:

I C / IT

(Interview group 1)

Household 2:

IC / IIT (Interview group 2)

Household 3:

IIC / IT (Interview group 3)

Household 4:

IIC / IIT (Interview group 4)

Household 5:

I C / IT

(Interview group 1)

....

The interview group allocation will be done by TRIAS and must be entered in IEP 0a (see chapter 0). The interview group must be considered for the purposes of precoding; they concern calculation patterns 1, 1a, 4 and 4a (see chapter 0).

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PREPARATION, PRECODING AND CONDUCTING OF THE INTERVIEW The interviewer will get the Address Record with address and telephone number of the target persons at TRIAS and will made an appointment for the interview with the household by telephone. After having fixed the date, the coder will precode the relevant interview using the household and personal questionnaires of the household (available at TRIAS). The interviewer will get the pre-coded documentation for the interview. 9 Note the agreed appointment in the Address Record. After having conducted the interview, add the missing information (duration of the interview, number of household members involved in the interview, comments etc.) in the Address Record. Fill in the questionnaire „Interview – Method“. 9 Carefully read the interview instructions and familiarize yourself with the interview sequence and with the survey documentation. Forms, questionnaires and information sheets for each interview step

Page - 156 -


IEP 0a

Participants in the interview, Interviewer explanation

IEP 0b

A1 IEP 2a

CLEVER

IEP 1

Game

IEP 2b

Q 1a

Q 1b

IS 1

IS 2a

Routine of the day - key date, PT

Q 1c IS 2b

Q 1d IS 2c

IEP 3

Q2

CLEVER introduction, assessment

Routine of the day - key date

IS 3a

IS 3b

IS 3c

Q 3a

Q 3b

Q 3c

Q4

Q5

A3

“Trips” questionnaires

Description of scenarios

Q 3d

“Scenarios” questionnaires Use of CLEVER, Income

A4

... Formats

Forms, questionnaires and information leaflets for each interview step (0) Opening of the interview

– IEP 0a: “Interview participants“ + Address Record

(1) Introductory game

– A 1: “Mobility options: Availability and use of vehicles and means of transport“ – IEP 1: “Mobility options: Reasons and explanations concerning the availability of transport means“

(2) Routine of the day - key date

– IEP 2a: “Routine of the day – key date“ – IEP 2b: “PT alternatives for the trips(car driver, car passenger, bicycle) on the key date“ – Q 1a – Q 1d: Questionnaires for the routine of the day on the key date differentiated by the means of transport

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– IS 1 “Features of the CLEVER“

(3) CLEVER

– IS 2a, 2b and 2c: Pictures of the CLEVER – Q 2 “CLEVER – Assessment” (4) Scenarios A, B and C

– IS 3a: “Scenario A” – IS 3b: “Scenario B” – IS 3c: “Scenario C” – Q 3a – Q 3d: Questionnaires for scenarios A, B and C differentiated by the means of transport – IEP 3: “Routine of the day – key date” – Q 4 “CLEVER – Use” – Q 5: “Household income”

(5) Other

– IEP 0b: “Interviewer explanation“ Abbreviations used in the documentation: Q IS IEP PT IIN MT

Questionnaire for interviewees (to be filled in by the interviewees) Information sheet (Information for the interviewees) Interviewer entry pattern (to be filled in by the interviewer) Public transport Individual identification number Means of transport

Entry pattern: White boxes on a white White boxes on a grey background must be filled in by background must be filled in the interviewer by the interviewee Interviewer

Interviewee

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CLEVER

Structure of the interview including precoding Control of the household and personal questionnaires 9

Check if the household and personal questionnaires are completely filled in and all questions were answered. The coder has to identify and mark missing data on the relevant form. The interviewer has to check missing information with the interviewees.

9

In case that the pre-coding of Q 3 can not be completed due to missing data (duration of a trip, trip length) in the personal questionnaires, the coder has to make a note for the interviewer. The interviewer has to pre-code the missing data (duration of a trip resp. trip length) before handing out the Q 3.

Start of precoding [Enter preliminary information in the forms/questionnaires.] Form

Information to be filled in

IEP 0a

Interview participants

• •

A1

Game: Availability of means of transport

• •

IEP 1

Game: Availability of means of transport

• •

IEP 2a

Routine of the day – key date

• • • •

Interview number, Interview group allocation First names, year of birth Interview number First names Interview number First names Key date (day of the week and date) Interview number, IIN, first name Starting address For all trips: starting time, destination address, purpose, MT, trip duration

Source Household questionnaire Household questionnaire Household questionnaire

Personal questionnaire

9 Check in IEP 2a if the duration of the forward and back trips (e.g. trip forward = trip to a destination: home → work; trip back: work → home) are the same or similar, which should be the normal case. In case the difference is more than 50%, make an X in the last column of IEP 2a. The interviewer has to check this inconsistency with the interviewee. Example: Trip to a destination 15 min., trip back 25 min resp. trip back 15 min., trip to a destination 25 min. 15 min. + 50% = 22,5 min.

25 min. > 22,5 min → check!

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CLEVER

Continuation precoding Form

IEP 2b

PT – Alternatives

Information to be filled in • • •

• • • •

IEP 3

Routine of the day – key date (entire household)

Interview number, IIN, first name, trip number Starting point (address), start of the trip (time) Stop at origin, lines, stop at destination, arrival at the destination (time), trip duration, trip length, destination (address) Costs PT Key date (day of the week and date) Interview number, number of available vehicles All trips for all members of the household (trip, purpose and means of transport) – see example:

Source Personal questionnaire Map of PT lines, internet


Compile a set of Q 1 for every interviewee: There is a separate form for every trip on the key date (see also personal questionnaires within the scope of the written household survey and IEP 2a) depending on the means of transport: – Q 1a Car driver – Q 1b Car passenger – Q 1c PT – Q 1d Bicycle In case that more than one mode is used for a trip the form/mode is chosen due to the following hierarchy (applies also for EB 3): (1) PT (2) Car driver (3) Car passenger (4) Bicycle (5) On foot

→ the number of forms for each interviewee corresponds to the number of trips of that person on the key date. For trips by moped or motorbike, please use Q 1a – with a note in the header.

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CLEVER

Continuation precoding Form Q 1a

Car driver

Q 1b

Car passenger

Q 1c

PT

Q 1d

Bicycle

Q2

CLEVER – assessment


• •

Source

• •

Interview number, IIN, first name, trip number Start of the trip (time), arrival at the destination (time) Duration and length of the trip Purpose of the trip


•

Interview number, IIN, first name

Household questionnaire

Compile a set of Q 3 for every interviewee: There is a separate form for every trip on the key date depending on the means of transport: – – – –

Q 3a Q 3b Q 3c Q 3d

Car driver: Scenarios A, B, C Car passenger: Scenarios A, B, C PT: Scenarios A, B, C Bicycle: Scenarios A, B, C

→ the number of forms for each interviewee corresponds to the number of trips of that person on the key date. For trips by moped or motorbike, please use Q 3a – with a note in the header.

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Continuation precoding Form


Source

Scenario A: • Total costs of the trip:

-

Car

-

CLEVER

• Fuel costs of the trip:

-

Car

-

CLEVER

• Duration of the trip:

-

Car

-

CLEVER

• Total costs of the trip:

-

Car

-

CLEVER

• Fuel costs of the trip:

-

Car

-

CLEVER


-

Car

Pers. questionnaire

-

CLEVER

Pattern 4

-

Car

Pattern 1

-

CLEVER

-

PT

Pattern 3

-

Bicycle

Pattern 2

Fuel costs of the trip:

-

Car

-

CLEVER

Duration of the trip:

-

Car

Pers. questionnaire

-

CLEVER

Pattern 4

-

PT

IEP 2b

-

Bicycle

-

On foot

Pattern 1

Pattern 1a

Pers. questionnaire Car trip

Scenario B:

Q 3a

Car driver (resp. moped/ motorcycle)

• • • • • •

Interview number IIN, first name Trip number Start time Trip length Purpose of the trip

Pattern 1

Pattern 1a

Scenario C: •

Interview group

•

•

•

Total costs of the trip:

Pattern 1a

Pattern 5

Page - 162 -


Form

CLEVER


Source

Scenario A: • Total costs of the trip:


-

Car passenger

in the interview Q 1b

-

CLEVER

Pattern 1

-

Car passenger

Pers. questionnaire Car passenger trip

-

CLEVER

-

Car passenger

in the Interview Q 1b

-

CLEVER

Pattern 1

-

Car passenger

Pers. questionnaire

-

CLEVER

Pattern 4

-

Car passenger

in the interview Q 1b

-

CLEVER

Pattern 1

-

PT

Pattern 3

-

Bicycle

Pattern 2

-

Car passenger

Pers. questionnaire

-

CLEVER

Pattern 4

-

PT

IEP 2b

-

Bicycle

-

On foot

Scenario B: • Total costs of the trip:

Q 3b

Car passenger

• • • • • •



Scenario C: •

Interview group

• Total costs of the trip:


Pattern 5

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Form

CLEVER


Source

Scenario A: •

•

Q 3c

PT

• • • • • •


Interview group

•

PT

Pattern 3

-

CLEVER

Pattern 1


-

PT

Pers. questionnaire

-

CLEVER

Pattern 4a


-

PT

Pattern 3

-

CLEVER

Pattern 1


-

PT

Pers. questionnaire

-

CLEVER

Pattern 4a


-

PT

Pattern 3

-

CLEVER

Pattern 1


-

PT

Pers. Questionnaire

-

CLEVER

Pattern 4a

Scenario C: •

•

Form

-

Scenario B:

• •



Source

Scenario A: •

•

Q 3d

Bicycle

• • • • • •


Interview group

-

Bicycle

Pattern 2

-

CLEVER

Pattern 1


-

Bicycle

Pers. questionnaire

-

CLEVER

Pattern 4a


-

Bicycle

Pattern 2

-

CLEVER

Pattern 1


-

Bicycle

Pers. questionnaire

-

CLEVER

Pattern 4a


-

Bicycle

Pattern 2

-

CLEVER

Pattern 1


-

Bicycle

Pers. questionnaire

-

CLEVER

Pattern 4a

Scenario B: •

• •


Scenario C: •

•

Page - 164 -


Form

Q4

CLEVER

Information to be filled in •

Interview number, IIN, first name


•

Use in scenarios A,B, C

in the interview

•

Interview number


CLEVER – Use

Q5

Household income

Source

Start of the interview

•

Opening of the interview (IEP 0a) – if necessary check of missing information with the interviewees and introductory game (IEP 1) – (A1)

•

Routine of the day – key date (IEP 2a, IEP 2b) – (Q 1a to Q 1d): if necessary check of missing information and check of possible inconsitencies concerning the duration of the trips

•

Introduction of the CLEVER (information sheets and pictures: IS 1, IS 2a, IS 2b, IS 2c) and CLEVER Mobil assessment (Q 2)

Coding of the missing information for scenario enquiry A, B and C in Q 3b Costs of the trip for car passengers Form Car passenger: Scenarios A, B, C

Q 3b

Information to be filled in •

Costs of the trip in A, B and C for Car passengers

Source from Q 1b, question 2

Continuation of the interview

•

Introduction of scenarios (IS 3a, IS 3b, IS 3c)

•

Scenario enquiry A, B and C – (Q 3a to Q 3d and IEP 3)

Precoding Q 4 Form Q4

CLEVER – use

•

•


Source

Use in scenario A, B, C (at least one entry per scenario in Q 3)

Q3

CLEVER – Use (Q 4) and Household income (Q 5)

Interviewer declaration (IEP 0b) End of the interview

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Calculation patterns

PATTERN 1 – “Total costs of the trip in A, B and C for cars, mopeds/motorcycles and CLEVER“ for Q 3a (Car driver resp. moped/motorcycle), Q Q 3b (Car passenger), Q Q 3c (PT), Q Q 3d (Bicycle) Calculation depends on the interview group (see chapter 0): Means of transport Scenario A IC

CAR

IIC CLEVER Moped/ motorcycle 1)

km:

IC IIC

1)

km x 0,35 €

1)

km x 0,18 €

Scenario B IC IIC IC IIC

1)

km x 0,35 €

1)

km x 0,16 €

Scenario C IC

km1) x 0,40 €

IIC

km1) x 0,46 €

IC

km1) x 0,18 €

IIC

km1) x 0,20 €

Length of the trip – Information from the personal questionnaire of the written household survey

PATTERN 1a – “Fuel costs of the trip in A, B und C for cars, mopeds/motorcycles and CLEVER“ for Q 3a (Car driver resp. moped/motorcycle) Calculation depends on the interview group (see chapter 0): Means of transport Scenario A IC

CAR

IIC CLEVER Moped/motorcycle 1)

km:

IC IIC

1)

km x 0,06 €

km1) x 0,03 €

Scenario B IC IIC IC IIC

1)

km x 0,06 €

km1) x 0,03 €

Scenario C IC

km1) x 0,11 €

IIC

km1) x 0,15 €

IC

km1) x 0,05 €

IIC

km1) x 0,08 €


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CLEVER

PATTERN 2 –“Costs of the trip in A, B and C for bicycle“ for Q 3a (car Car driver resp. moped/motorcycle), Q 3b (Car passenger), Q 3d (Bicycle) Means of transport

Scenario A

Scenario B km1) x 0,05 €

BICYCLE 1)

km:

Scenario C


PATTERN 3 –“Costs of the trip in A, B and C for PT“ for Q 3a (Car driver resp. moped/motorcycle), Q 3b (Car passenger), Q 3c (PT) Means of transport

Scenario A

Scenario B

Scenario C

Depending on whether or which PT pass the interviewee owns (see household questionnaire): PT

-

For pupils, students and members of large families: 0,20 €

-

PT monthly, 6-monthly or annual ticket in Thessaloniki: 0,75 33 €

-

Ordinary ticket: 0,45 €

Consider the different PT-zones!

PATTERN 4 – “Duration of the trip in A, B and C for CLEVER“ for Q 3a (Car driver), Q 3b (Car passenger) Attention! Different for moped/motorcycle-trips! Calculation depends on the interview group (see chapter 0): Means of transport Scenario A CLEVER (for car driver and car passenger)

CLEVER

Trip duration as given in the personal questionnaire

Scenario B IT IIT

Scenario C

d2) [minutes] – 10%3) (rounded to the nearest whole minute)

d2) [minutes] – 40%3) (rounded to the nearest whole minute)

Trip duration as given in the personal questionnaire

(for moped/motorcycle) 2) 3)

d = Trip duration as given in the personal questionnaire 10% or 40% time saving due to the use of bus lanes, reduced time spent for looking for a parking space etc.

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CLEVER

PATTERN 4a – “Duration of the trip in A, B and C for CLEVER“ for Q 3c (PT), Q 3d (Bicycle) Means of transport

Calculation depends on the interview group (see chapter 0): Scenario A

CLEVER

(km1) x 2) + 5 min. [Assumption: vCLEVER = 30km/h; 1km = 2 minutes]

1) 3)

Scenario B

Scenario C

((km1) x 2) + 5 min.) – 10%3)

IZ

(rounded to the nearest whole minute)

((km1) x 2) + 5 min.) – 40%3)

IIZ

(rounded to the nearest whole minute)

km: Length of the trip – Information from the personal questionnaire of the written household survey 10% or 40% time saving due to the use of bus lanes, reduced time spent for looking for a parking space etc.

PATTERN 5 –“Duration of the trip in A, B and C for bicycle and by foot“ for Q 3a (Car driver resp. moped/motorcycle), Q 3b (Car passenger) Means of transport BICYCLE

BY FOOT 1)

km:

Scenario A

Scenario B

Scenario C

km1) x 5 min. [Assumption: bicycle speed = 15 km/h]

km1) x 15 min. [Assumption: walking speed (pedestrian) = 4 km/h]


The following must be taken to the interview: 9 Address Record 9 Interview instructions 9 Survey documentation (forms, questionnaires, information sheets) 9 Red pen, pencil 9 Pocket calculator 9 Notepad 9 Map of public transport lines, list of public transport rates

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CLEVER

Interview (0) Opening of the interview Introduction and initiation 9 Introduction of the interviewer 9 Reference to agreed appointments 9 Establishment of a connection with the written household survey about mobility and the use of different modes of transport (December 2003) 9 Explanation that the interviews –

serve the purpose of extending the knowledge already gained on the basis of randomly selected individuals/households certain issues require oral clarification.

–

are an important contribution to the solution of transport and mobility-related issues.

because

9 Stressing compliance with the Protection of Data Act! Evaluation of the data is based on anonymity! Registration of the interview participants 9 Introduction of the household members. 9 In the IEP 0a, enter the date of the interview, the attendance of the participants and the reasons for any absence, if applicable. Add possibly missing data.

(1) “Introductory game” – vehicles, their availability and use in the household Forms:

– A 1: “Mobility options: Availability and use of vehicles and means of transport“ → 1 form per household – IEP 1: “Mobility options: Reasons and explanations concerning the availability of transport means” → Interviewer entry pattern to the documentation by the interviewer

Page - 169 -


Instruction

CLEVER

Explanation/question

9

Present form A 1.

9

Keep availability symbols ready.

At the beginning of this interview, I would like to discuss the vehicles that you as a household dispose of.

Question 1: Vehicles 9 Hand out the corresponding number of passenger car cards and instruct persons to lay them out one below the other in the MT column of A 1.

How many passenger cars do you have in your household?

9 Passenger car: categories:

Please specify the type of the car(s) and state its/their year of manufacture.

-

Limousine Compact (small) car Estate car Sports car/coupé Convertible Minivan SUV – sporty utility vehicle

Who is the owner /are the owners?

Please allocate each passenger car to one of these categories!

9 Place corresponding card symbols on How many mopeds/motorcycles and A 1 – irrespective of their number, bicycles do you have in your household? place only one card per Which type? moped/motorcycle and bicycle.

9 Moped/motorcycle: number and type (moped, motorcycle).

Who is the owner/who are the owners?

9 Bicycle: number and type (city bike, trekking bike, mountain bike, racing bike, etc.).

Enter all information about the vehicles in the corresponding fields of IEP 1. Tick the owner “O“ in the corresponding IIN/MT field – even if he/she does not attend the interview. Document other vehicles or if the household disposes of more than 3 passenger cars on the back of IEP 1 according to the same entry pattern.

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CLEVER

Question 2a: Availability of the vehicles

9 Hand out cards with “+“,”–“,”0“. Explain the symbols. 9 Assign to every interviewee, according to his/her IIN, the column where he/she should place the symbols. 9 Make sure that every interviewee places a symbol next to every vehicle or MT.

9 A discussion of the HH members about the degree of availability of shared MT (i.e. vehicles used by several household members) for certain members is permissible and desirable.

Now I would like to find out from each one of you to which extent he/she is free to dispose of the vehicles you have mentioned. “+“ means that you (are free to) use the relevant vehicle at any time. PT: You use PT regularly, you may own a PT pass Car passenger: you get a lift in a passenger car on a regular basis. “–“ means that you never use the relevant vehicle or that you never use public transport or that you are never a passenger in a passenger car. “0“ means vehicles which you can use occasionally (restricted use) or vehicles which are available only if certain conditions are satisfied. PT and Car passengers – they use these possibilities occasionally

I request each of you to indicate on this sheet for each MT (including “on foot “, “Car as passenger“ and “PT “), by means of the corresponding symbol, to which extent you are able to dispose of that MT for your normal activities during working days. Transfer the result to IEP 1. Tick the corresponding symbol in the appropriate IIN/MT field. Except in cases of a disability, “on foot“ always gets a “+“.

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CLEVER

Question 2b: Availability of the vehicles – explanations 9 Ask questions about the meaning of the “+“, “–“, “0“ symbols.

Please give me a more detailed explanation of the symbols you have used. “+“ For which activities/trips do you use the vehicle/MT? How many times per week? “–“ What are the reasons why you may not dispose of a vehicle/MT or why it may not be available for use or why it is not used? “0“ Under which circumstances is the vehicle/MT available/can it be used? Under which circumstances is it not available/can it not be used?

Write down the results in IEP 1 in the corresponding IIN/MT field. If there is not enough space for your comments, please continue the comments on the back of the IEP 1, stating the IIN and MT. Collect form A 1 and the symbol cards.

(2) Routine of the day on the key date Forms:

– IEP 2a: “Routine of the day – key date” → previously completed by the interviewer – IEP 2b: “PT alternatives for the trips on the key date“ → previously completed by the interviewer; serves to check the statements about PT alternatives. – Q 1a – Q 1d: Questionnaire for interviewees to describe the routine of the day on the key date, differentiated by MT → boxes on a white background have been filled in by interviewer; white boxes on a grey background must be filled in by the interviewee.

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Instruction

9 Show each interviewee his/her routine of the day (IEP 2a). 9 Hand out the routine of the day and his/her set of QI 1 to each interviewee, sorted according to the sequence of trips.

CLEVER

Explanation/Question Now I would like to continue with an indepth discussion of the trips stated by each of you on the given key date of our written household survey. Based on this routine of the day, a separate form has been prepared for each trip, depending on the means of transport you have used.

Check any missing data or inconsitencies with the interviewees (marked on IEP 2a). Inconsistencies concerning trip duration of trips forward (trip to a destination) and back trips (note in the last column of IEP 2a with an X) have to be clarified by/with the interviewees. Note explanations (e.g. congestion) on the back of the questionnaire with a red pen stating the trip number. If necessary correct the trip duration. Be aware that a modified trip duration may in some cases also affect the precoded trip duration in EB 3 – check this issue! Explanation about Q 1 9 Ask the interviewees to fill in Q 1 independently.

The used MT is shown in the header, below it you see all the information about the trip 9 Do not help them to fill in the form, as given by you in writing within the scope only address problems and questions of the household survey. concerning the method of completion according to the explanations given further down.

9 Ensure that the questions are answered completely. 9 It is important that back trips, which often seem to be equal with the trip forward (trip to a destination), are answered as well, especially the questions concerning car passengers, baggage (question 2) and parking space (Q 1a/question 3)! The questions concerning reasons (question 1), costs (2), PT-alternatives (3 resp. 4) and reasons for not using alternative modes (4 resp. 5) may be left out on the back trip forms with a reference to the trip forward. Page - 173 -


CLEVER

Q 1 – Question about the reasons (Question 1) 9 If the interviewee does not remember Please state for which personal reasons the trip, ask him/her for his/her you used the relevant MT. Please indicate reasons from today’s point of view. the priority of these reasons. 9 If the same reasons as for the previous trip apply, this question may be left out (tick the box!).

Q 1 – Question regarding passengers (Question 2 – Q 1a) 9 Allocation to groups of persons only. 9 This question even has to be answered if the back trip seems to be equal to the trip forward.

Please enter the number of your passengers. Who did you take on this trip?

Q 1 – Question regarding baggage (Question 2) 9 Rough allocation, for instance

Which type of baggage did you take?

handbag or briefcase, rucksack, shopping bags, crate of bottles, TV set, pram, etc.

9 This question even has to be answered if the back trip seems to be equal to the trip forward.

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CLEVER

Q 1 – Question regarding costs (Question 2) 9 Passenger car: The interviewees

Please estimate your total trip costs.

should estimate the costs per kilometre without any additional information from the interviewer! The point is to obtain a personal estimation of the trip costs.

9 Car passenger: Indication of a contribution to costs, if any. 9 PT: Costs depending on the ticket type – if not known exactly, estimated trip costs. 9 In case the back trip corresponds to the trip forward (trip to a destination), this question may be left out (on the form for the back trip).

Q 1a – Car driver: Question 3 about the parking space 9 “Non-chargeable parking space on public land“ shall mean a parking space on the side of the road.

Where did you park your car? Please tick the type of parking space.

9 The question concerning parking

Are you charged for parking your car? If so, please tick “Parking fees” in the corresponding line and state the amount of the fees.

fees relates to short-term parking areas, public garage or private parking space. If no fees are payable for the garage or the private parking space, please state the reasons next to the answer.

9 The distance from the parking space to the destination has to be estimated (in m or in minutes).

9 Even if the back trip seems to be equal to the trip forward, this question has to be answered (different destinations and therefore different parking spaces!).

Q 1 – Question about PT alternative (question 3/Q 1b, 1d and question 4/Q 1a) Page - 175 -


9 With this question, we intend to find out whether the relevant interviewee is aware of the PT alternative. Therefore, to answer this question, you must not provide any assistance in terms of substance, nor may the interview participants assist each other! It is also prohibited to look up maps and public transport timetables.

CLEVER

At this point, we wish to find out more about the PT alternative to the means of transport you have chosen. Please describe how this trip would look like if you went by public transport ...

9 If an interviewee does not know how that trip can be covered by public transport or if there is no PT alternative for this trip in his or her opinion, he/she may tick the appropriate box and continue with the next question. The times given for the duration of the PT trips are based on subjective estimates.

9 In case the back trip corresponds to the trip forward (trip to a destination), this question may be left out (on the form for the back trip).

Q 1 – Alternative means of transport (question 4/Q 1b, 1c, 1d or question 5/Q 1a) 9 Motivate the interviewees to explain their answers in greater detail. They should give as a minimum one resaon per mode (more would be better) against their choice.

9 Ensure that the interviewees explain their answers: in case of “yes” or “no” they should give reasons for resp. against a possible use; in case of “possibly” the conditions/ circumstances under which they can imagine a use should be stated.

For what reasons didn’t you use any of the given modes for this trip on the reporting day? Please explain the reasons against your choice of the given modes. Is it for you in principle imaginable to use these modes for this trip? Please explain the resaons respectively circumstances.

9 In case the back trip corresponds to the trip forward (trip to a destination), this question may be left out (on the form for the back trip).

After completion, collect all Q 1. Sort them by interviewee in the sequence of trip numbers. Go through the completed Q 1 item by item with the relevant Page - 176 -


CLEVER

interviewee. As you go through the Q 1, also try to elicit answers to questions that may have remained unanswered. Then enter these answers, if appropriate, with a red pen next to the relevant question: 9 Reasons for using the chosen means of transport: Ask for the given explanations as detailed as possible! Ask until you are certain that you do really know the reason why the relevant MT has been chosen. 9 Questions conecerning the alternatives: Ask for the reasons for not-using one of the alternatives on the reporting day. Ask for the reasons for resp. against a possible use of the alternatives. Write the results of your in-depth enquiry, if possible next the appropriate question. (3) CLEVER Information sheets: – IS 1 “Features of the CLEVER“ → for inspection by the interviewees – IS 2a – IS 2c: Pictures of the CLEVER → for inspection by the interviewees – “Natural gas as an alternative fuel“ → as background information for the interviewer (in the Annex) Form: – Q 2 “CLEVER – Assessment“ CLEVER 9 Present the vehicle using Information Sheets IS 1 and IS 2a – IS 2c. Point out the advantages of natural gas powered vehicles. 9 Hand each interviewee Q 2 with the previously completed header. 9 Ensure that the list is completed fully and that the reasons for negative opinions are stated, if applicable!

9 Leave the information sheets on the table while the questionnaire is filled in and answer possible questions about the vehicle or the natural gas powered engine (Information Sheet for Interviewer: “Natural Gas as an Alternative Fuel“ in the Annex).

As you will be aware, there are ongoing efforts to develop new concepts and ideas in order to solve transport & mobility problems and control the negative environmental impact of traffic. Thus, an environmentally friendly city car is in development (and has reached the project stage). The aim of the project is to get car drivers to abandon the car in favour of this vehicle ...

This is a first draft of the CLEVER ... What is your opinion about the CLEVER and its features after this brief introduction? Could you imagine using the CLEVER? In answering the questions, please follow the arrows… After completion, collect all Q 2. Sort them by interviewee. Go through the completed Q 2 item by item with the relevant interviewee. Also try to elicit answers to Page - 177 -


CLEVER

questions that may have remained unanswered. Then enter these answers, if appropriate, with a red pen next to the relevant question. 9 Assessment of the CLEVER: Ensure that the assessment list is fully completed and that the reasons are stated if the assessment is negative! If there are any doubts, ask for an explanation! Even neutral comments (“I don’t care”, “Is quite ok”, “Does not affect me” etc.) have to be ranked. 9 Use of the CLEVER: Get as much background information as possible about the reasons stated in favour of or against the use of the CLEVER! 9 Write down the results of your in-depth enquiry, if possible next to the appropriate question. Do not forget to collect the Information Sheets (features of the CLEVER and pictures of the CLEVER)! By no means leave them behind in the household! The designs have not been approved for publication yet!

(4) Scenarios A, B and C Information Sheets:

Forms:

– IS 3a: Scenario A – IS 3b: Scenario B – IS 3c: Scenario C

– Q 3a – Q 3d: Questionnaire for scenarios A, B and C differentiated by means of transport → boxes on a white background have been filled in by the interviewer; white boxes on a grey background must be filled in by the interviewee – IEP 3 “Routine of the day – key date (entire household)“ → previously filled in by the interviewer to help the interviewees answer the question how the trips of the household members would be influenced if the CLEVER is chosen – Q 4 „CLEVER – Use“

Before you hand the prepared set of Q 3 to the members of the household, transfer the passenger costs stated by the interviewee in Q 1b to Q 3b (Car passengers).

In the following part of the survey, I would like to confront you with three scenarios in which the CLEVER plays a central role. In these scenarios, concrete advantages

Page - 178 -


CLEVER

of the vehicle in terms of trip duration and trip costs compared to all other means of transport will be revealed. When you answer the questions, please assume that you have a CLEVER at your disposal.

Scenario A

(Q 3a – Q 3d)

9 Hand each interviewee his or her set of Q 3. 9 Introduce Scenario A using Information Sheet IS 3a.

9 Each interviewee now fills in Scenario A of the questionnaire for all trips.

Now I would like to go through your trips on the key date of the household survey, but with a view to the introduction of the CLEVER. Taking your routine of the key date as the basis, a separate form has been prepared depending on the means of transport you have used. In Scenario A ... With the following questions, we wish to find out whether and how your choice of the means of transport is influenced by the launch of the CLEVER. This trip costs you €... with the CLEVER, €... with the ... This trip takes ... minutes with the CLEVER, ... minutes with the ... Please decide whether you will continue to use the means of transport originally chosen by you, or whether you wish to use the CLEVER. In answering the question, please follow the arrows.

9 When all interviewees have finished completing the questionnaire, go through Scenario A with each interviewee for each separate trip. Pay special attention to possible changes of their mobility behaviour. 9 Pay attention to the plausibility of the chain of trips – if a chain of trips started with the car, it cannot (in most cases) be continued with the CLEVER.

As a result of your change of the choice of the modes, your routine of the day or your trips could change as follows: -

You may decide to attend to your business at another destination if this were possible (for instance shopping in the city centre rather than remote urban zones etc.)

-

Other trips could be added (for instance giving others a lift, shopping

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9 Remember that certain trips are impossible with the CLEVER, for instance if it is necessary to transport large items and baggage or if more than one passenger is to be given a lift. 9 To answer the question how the trips of the other household members will be influenced, please offer IEP 3 to the interviewees for assistance. 9 In any case positive reasons for the mode choice have to be given (for what reasons has a mode been chosen?). Additionally negative reasons can be stated (why have the other modes not been chosen?).

CLEVER

on the way etc.). -

The starting time of your trip could change – for instance, you could leave later because the new mode presumably takes you to your destination more quickly.

Your changed mobility behaviour (different mode, different destination, different starting time of your trip etc.) could also influence the trips of other members of the household (for instance: the previously unavailable car could get available for another household member).

9 Ensure that all questions are answered and that the interviewees enter the answers on Q 3. 9 Please enter additions and amendments prompted by your questions and your explanations next to the appropriate question in red.

Scenario B

(Q 3a – Q 3d)

9 Introduce Scenario B using Information Sheet IS 3b.

9 Each interviewee now fills in Scenario B of the questionnaire for all trips.

In Scenario B, the traffic boundary conditions change in favour of the CLEVER ... This trip costs you €... with the CLEVER, €... with the ... This trip takes ... minutes with the CLEVER, ... minutes with the ... Please decide whether you will continue to use the means of transport originally chosen by you, or whether you wish to use the CLEVER. In answering the question, please follow the arrows.

9 When all interviewees have finished completing the questionnaire, go through Scenario B with each

As a result of your change of the choice of modes, your routine o the day or your trips Page - 180 -


interviewee for each separate trip. Pay special attention to possible changes of their mobility behaviour. 9 Pay attention to the plausibility of the chain of trips– if a chain of trips started with the car, it cannot (in most cases) be continued with the CLEVER. 9 Remember that certain trips are impossible with the CLEVER, for instance if it is necessary to transport large items and baggage or if more than one passenger is to be given a lift. 9 To answer the question how the trips of the other household members will be influenced, please offer IEP 3 to the interviewees for assistance. 9 In any case positive reasons for the mode choice have to be given (for what reasons has a mode been chosen?). Additionally negative reasons can be stated (why have the other modes not been chosen?).

CLEVER

could change as follows: -


-

Other trips could be added (for instance giving others a lift, shopping on the way etc.).

-


Your changed mobility behaviour (different mode, different destination, different starting time of your trip etc.) could also influence the trips of other members of the household (for instance: the previously unavailable car could get available for another household member).


Scenario C

(Q 3a – Q 3d)

9 Introduce Scenario C using Information Sheet IS 3c (depending on the interview group – see Chapter 0): IC ... Fuel prices x 1,75 IIC ... Fuel prices x 2,5 9 Each interviewee now fills in Scenario C of the questionnaire for

In Scenario C, the traffic boundary conditions change in favour of the CLEVER (Scenario B), and the fuel prices increase.

This trip costs you €... with the CLEVER, €... with the ... This trip takes ... minutes with the CLEVER, ... minutes with the ...

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all trips.

CLEVER

Please decide whether you will continue to use the means of transport originally chosen by you, or whether you wish to use the CLEVER or another mode. In answering the question, please follow the arrows.

9 When all interviewees have finished completing the questionnaire, go through Scenario C with each interviewee for each separate trip. Pay special attention to possible changes of their mobility behaviour. 9 Pay attention to the plausibility of the chain of trips– if a chain of trips started with the car, it cannot (in most cases) be continued with the CLEVER. 9 Remember that certain trips are impossible with the CLEVER, for instance if it is necessary to transport large items and baggage or if more than one passenger is to be given a lift. 9 To answer the question how the trips of the other household members will be influenced, please offer IEP 3 to the interviewees for assistance. 9 In any case positive reasons for the mode choice have to be given (for what reasons has a mode been chosen?). Additionally negative reasons can be stated (why have the other modes not been chosen?).

As a result of your change of the choice of the means of transport, your routine of the day or your trips could change as follows: -


-

Other trips could be added (for instance giving others a lift, shopping on the way etc.).

-


Your changed mobility behaviour (different mode, different destination, different starting time of your journey etc.) could also influence the trips of other members of the household (for instance: the previously unavailable car could get available for another household member).


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CLEVER

After completion, collect all Q 3. Sort them by interviewee and trip. Look for the Q 3 where the interviewee has stated that he/she would use the CLEVER instead of the original MT. Prepare Q 4 for these interviewees – now tick the box with the scenario(s) for which the CLEVER would be used. Q 4 CLEVER – Use 9 Distribute Q 4 to all interviewees who have ticked that they would use the CLEVER in Q 3 and ask them to complete it. 9 If required, explain what the term “Car Sharing“ (Table 1) means.

9 “Other“ can mean (for instance): leasing or one member of the household owns the CLEVER, but it is used by somebody else.

Now I would like to ask those who could imagine using the CLEVER to explain their reason(s) for their decision. Please also answer the following questions about the availability/ownership of the CLEVER and its ranking vis-à-vis other vehicles in the household.

Table 1: Definition Car Sharing Car Sharing is the joint or shared use of one or several cars by several users. Currently, the main organizers of Car Sharing pools are co-operatives or limited liability companies. The differences between car hire and Car Sharing are -

that car sharing usually requires membership,

-

that the car can also be hired for a short period of time (by the hour),

-

that there are usually many locations in a region where the car can be picked up and turned in,

-

that access to the vehicles is easy (e.g. with key card), and

-

that Car Sharing pools are often run by non-profit organizations.

After completion, collect all Q 4. Sort them by interviewee. Look through the completed questionnaires and make sure they are fully completed. If certain answers remain unanswered or if the answer is unclear, please ask again and, if required, enter the answers with a red pen next to the relevant question.

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CLEVER

(5) Miscellaneous Forms:

– Q 5 Household income – IEP 0b Interviewer declaration

Q 5 Household income 9 Present Q 5. 9 If the members of the household are not prepared to answer this question, please note this on the questionnaire.

To conclude the interview, please provide very rough information about your net household income – just like all other data, this information will be treated confidentially and evaluated without reference to yourself.

This takes us to the end of the interview. Thank you very much for your kind participation and co-operation! When you have concluded the interview, please enter the duration of the interview, the household category and comments about the interview in IEP 0b. Complete the questionnaires for interviewers „Interview – Method“. If possible give reasons for your assessment.

CHECKS 9 At home or in the office, please check whether the interview documentation is complete. 9 Sort the completed forms and questionnaires by interview characteristics, by person and by trip. 9 Check the information about PT alternatives in Q 1a, Q 1b and Q 1d with the aid of IEP 2b. If the information does not coincide, take this into account for the coding procedure (see coding pattern). 9 Complete the address record. 9 Confirm that the interview has been conducted and checked properly by signing IEP 0b. 9 Deliver all interview documentation at TRIAS.

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CLEVER

17 ANNEX 3 – INFO SHEETS OF THE IN-DEPTH SURVEY

IS 1 CHARACTERISTICS of CLEVER CHARACTERISTICS:

Closed vehicle with 3 wheels (1 front wheel, 2 rear wheels)

DIMENSIONS:

Length: 3,0 m, width: 1,0 m, height: 1,4 m

WEIGHT:

about 300 kg

TRANSPORT-CAPACITY:

2 persons (1 driver in the front, 1 passenger in the back) + small luggage

DRIVING LICENCE:

Driving licence for cars (B)

PROPULSION:

Combustion engine run by compressed natural gas 176 ccm; 21 PS

PERFORMANCE:

Maximum speed: 110 km/h → motorways can be used Acceleration: 0 – 60 km/h in 9 s Tilting mechanism (front wheel and cabin)

DRIVING RANGE:

max. 160 km with the full gas cylinders

CONSUMPTIONS:

7,5 l CNG/100km → 4,8 l diesel/100 km resp. 4,1 l petrol/100 km

REFUELLING:

At conventional natural gas filling stations without removing the cylinders or by exchange of the gas cylinders (2 removable gas bottles containing 2 x 6l)

EMISSIONS:

Exhaust gas emissions: about 80% less than a conventional car (diesel or petrol) Noise: reduced noise of the engine compared to vehicles run by petrol or diesel

OPERATION and EQUIPEMENT:

Full automatic transmission, pedals, steering wheel; 1 door on the leftside, side window can be opened; no heating

SAFETY CONCEPT:

Crash safety and safety concept meet those of a modern compact car.

COSTS:

Purchase costs: about € 9.000,-Running costs: about € 0,18/km (Car about € 0,35/km)

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CLEVER

CNG as alternative fuel International studies prove that vehicles run by CNG are a forward-looking alternative to vehicles run by petrol or diesel. With emissions far below the requirements of European standards, they are well suited for urban traffic. What is CNG (compressed natural gas)?

Fossil fuels; CNG consists of up to 99% methane, a small amount of hydrocarbons and traces of other gases.

CHARACTERISTICS:

nontoxic, odourless, lighter than air

Don’t mix it up with liquefied petroleum gas (LPG)! LPG is a product of the distillation of crude oil in refineries. It is heavier than air, volatilises slower and is more inflammable!

energy is better usable than energy of liquid fuel inflammable at a temperature of approximately 600°C (petrol: 360°C) EMISSIONS:

COSTS:

Advantages of CNG compared with petrol and diesel: CO2

CO

NOx

NMHC

Carbon black

SO2

Petrol

- 30%

- 90%

- 85%

- 70%

–

–

Diesel

- 10%

- 50%

- 90%

- 90%

- 98%

- 100%

CNG is much cheaper than petrol or diesel. 1 kg CNG costs roughly 0,70 € (€ 0,44/l): CLEVER: 7,5 l CNG/100km → 3,30 €/100 km (€ 0,44/l) Comparison: 9l Petrol/100km → 7,29 €/100 km (€ 0,81/l) 7l Diesel/100 km → 4,83 €/100 km (€ 0,69/l)

SAFETY:

Crash-tests prove that the high-strength tanks and other properties guarantee highest safety in case of accidents. Fire hazard does not exceed that of vehicles run by petrol or diesel.

UNDERGROUND PARKING:

CNG is lighter than air, with 600°C it has a comparable high ignition temperature and it volatilises very easily. In Vienna (and also in Germany) CNG run vehicles are allowed to be parked in underground garages.

CNG in Greece:

CNG is used by PT busses only in Athens (295 vehicles) and by some taxis. In comparison Austria has presently 250 (mostly taxis or busses) CNG vehicles, Italy has 434.000 CNG vehicles.

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