Modelling and evaluating collaborative urban freight ...

How electric vehicles can affect current urban freight distribution organizations?

Jesus Gonzalez-Feliu Laboratoire d'Economie des Transports 14 Avenue Berthelot, Lyon, France

Agenda

     

Introduction Urban goods movement categories The proposed framework Scenarios Results Conclusion

Seminario CREI, Roma Tre, 19 ottobre 2011

Introduction

 Electric mobility is a popular subject that seems to have direct applications on people trip chains  In freight transport, only the urban zones (and not for all types of transport) appear to be possible application areas  Some works deal with technical aspects of electric engines or on distance and time constraints, but there are few works dealing with the organizational changes that electric vehicles imply on urban goods transport  This communication deal with organizational impacts of using electric vehicles for urban deliveries


Urban goods movement categories

Collaboration levels (Gonzalez-Feliu et al., 2012):  Inter-establishment trips: several types can be made by electric vehicles, mainly when few restrictive time constraints are imposed  End-consumer’s trips: shopping trips can be made by electric vehicles, under some conditions, as well as store-picking home deliveries  Urban management trips: Non applicable In this paper we focus on inter-establishment trips


Logistics pooling and logistics sharing

In analogy to car pooling (De la Morsaglière et al., 1980), logistics pooling can be defined as:  Vehicle sharing among two or more transporters that visit common or nearby customers  Collaborative platform and land resource sharing among loaders and/or transporters Logistics sharing can be defined as (Gonzalez-Feliu and Morana, 2011):  Joint use of common resources for logistics management  Separate use of common vehicles for deliveries  Division of common logistics spaces in slots used by two or more loaders and/or transporters


Urban goods movement route categories, collaboration and use of electric vehicles Characteristics of routes able to be considered in the proposed work (Author’s elaboration from French Surveys) ID code

Package

Org. mode

Nr. of stops

Unitary load (per delivery)

G1

Pallet/Box

Third party

3-10

80-500

G2

Pallet/Box

Third party

11-20

50-250

G3

Pallet/Box

Third party

21-30

40-150

EC

Box

Third party

31 and more

1-30

O1

Pallet/Box

Own 3-20 account (E)

5-500

O2

Box

Own account (D)

5-150

French Surveys are presented in Ambrosini et al. (2010) Seminario CREI, Roma Tre, 19 ottobre 2011

The scenario assessment procedure Input data: Geographical, demographical, socio-economic data (SIRENE files)

Estimation of number of deliveries (Freturb model, Gonzalez-Feliu et al., 2012a)

Estimation of delivery loads (adapted from Gonzalez-Feliu et al., 2012b)

Route construction procedure (GonzalezFeliu et al., 2010; Gonzalez-Feliu, 2012) Road occupancy, economic costs and environmental impacts (Gonzalez-Feliu, 2011) Seminario CREI, Roma Tre, 19 ottobre 2011

Route assessment: Clustering phase

• Sweep algorithm (adapted from Gonzalez-Feliu, 2012) Vehicle 2

Vehicle 2

Vehicle 1

Vehicle 1

Vehicle 3

Vehicle 3

Iteration – customer insertion on a cluster

Initialization phase

Vehicle 2

Vehicle 2

Vehicle 1

Vehicle 1

Vehicle 3

Vehicle 3

Cluster definition

Cluster assignment to a satellite

Depot

Customer

Satellite

Cluster’s centroid


Route assessment: Route construction phase

• Nearest-neighbor algorithm (adapted from Gonzalez-Feliu et al., 2010)

C a n d i d a t e l i s t

V e h i c l e 2 C a n d i d a t e l i s t

V e h i c l e 1

V e h i c l e 2

I n i t i a l i z a t i o n p h a s e

V e h i c l e 2 I t e r a t i o n – c u s t o m e r i n s e r t i o n o n a r o u t e

I t e r a t i o n – r o u t e f i n i t i o n f o r o n e s a t e l l i t e


Estimation of transportation costs, traffic issues and GHG emissions  Transportation costs: only fuel and employees costs (author’s elaboration from raw data presented in Russo, 2002 and Generalitat de Catalunya, 2011)  Road occupancy factors (Gonzalez-Feli, 2011)

Total on-load weight Less than 3.5 t 3.5-7 t 7-16 t More than 12 t

Weight factor 1 1.5 2 2.5

 GHG emissions: IMPACT ADEME sofware (French Agency of the Environment, 2003) Seminario CREI, Roma Tre, 19 ottobre 2011

Scenarios

We simulate a total of 5 scenarios, described below:  1: Only thermic vehicles (big)  2: Only electric vehicles (small)  3: Big vehicles in periphery, small in the central areas (electric) without collaboration  4: Collaborative solution


The case study

 Data simulation from Lyon (France)  Potential demand of 5 small supermarket groups in the central area of Lyon  From survey data (Ambrosini et al., 2010) we defined five transportation companies  We calculate the following indicators: -

Total travelled distance (in km) Total travelled time (in hours) Road occupancy rates (in km.PCU) Collective GHG emissions (in CO2-equivalent units)


Results By transport operator

Scenario Distances (km) Times (h)

CO2

Op. cost Part of electric

1

73 185

15 486

11 260

590 017

0%

2

108 982

10 539

Negligible

633 059

100%

3

103 534

10 387

6 797

614 110

65%

4

100 417

9 187

5 071

626 516

50%

Overall


Conclusion

 The proposed method combines several modules and targets planners and practitionners.  From the simulation, we observe that electric vehicles are efficient if used in a suitable way  This approach leads to the most environmental-friendly results.  Next steps: adapt the method to simulate the entire area’s flows


References Ambrosini, C., Patier, D., & Routhier, J. L. (2010). Urban freight establishment and tour based surveys for policy oriented modelling. Procedia-Social and Behavioral Sciences, vol. 2, n. 3, pp. 6013-6026. De La Morsanglière, H., Diaz Olvera, L., Ambrosini, C. (1982), La voiture en commun. Quelques données quantitatives sur l'agglomération lyonnaise, Transport environnement circulation, Vol. 55, pp. 7-12. French Agency of the Environment (2003). Logiciel IMPACT-ADEME v2.0 - Livret de présentation. ADEME, Paris. Generalitat de Catalunya (2011), Observatori de costos del transport de mercaderies per carretera a Catalunya, Butlletí de transports Número 58 – Març 2011, Direcció General de Transports i Mobilitat, Generalitat de Catalunya, Barcelone, Spain. Gonzalez-Feliu, J. (2011), Costs and benefits of logistics sharing for urban freight distribution: scenario simulation and assessment for strategic decision support. Seminario CREI, Università Roma 3, Rome, Italy, 19 October. Gonzalez-Feliu, J. (2012), Freight distribution systems with cross-docking: a multidisciplinary analysis, Journal of the Transportation Research Forum, vol. 51, n. 1, pp. 93-109. Gonzalez-Feliu, J., Ambrosini, C., Pluvinet, P., Toilier, F., Routhier, J.L. (2012a), A simulation framework for evaluating the impacts of urban goods transport in terms of road occupancy, Journal of Computational Science, vol. 6, n. 4, pp. 206-215. Gonzalez-Feliu, J., Ambrosini, C., Routhier, J.L. (2012b), New trends on urban goods movement: modelling and simulation of e-commerce distribution, European Transport/Trasporti Europei, vol. 50, Paper n. 6, pp. 1-23.

Gonzalez-Feliu, J., Morana, J. (2011), Collaborative transport sharing: from theory to practice via a case study from France. In: Yearwood, J., Stranieri, A. (eds.), Technologies for Supporting Reasoning Communities and Collaborative Decision Making: Cooperative Approaches. IGI Global, Hershey, pp. 237-251. Gonzalez-Feliu, J., Peris-Pla, C., Rakotonarivo, D. (2010), Simulation and optimization methods for logistics pooling approaches in the outbound supply chain. In Romano, C.A. (ed.), Towards a Sustainable Development and Corporate Social Responsibility Strategies in the 21st Century Global Market. Proceedings of the 3rd International Conference on Value Chain Sustainability, UPV, Valencia, Spain, pp. 394-401. Russo, F. (2002), Modelli per l’analisi dei sistemi di trasporto merci a scala nazionale, Franco Angelli, Milano.
