Evaluation of Traffic and Fire Accidents in Road ...

International Journal of Civil Engineering Research. ISSN 2278-3652 Volume 3, Number 3 (2012), pp. 201-222 © Research India Publications http://www.ripublication.com/ijcer.htm

Evaluation of Traffic and Fire Accidents in Road Tunnels, and a Cost-Benefit Analysis Ciro Caliendoa,*, Maria Luisa De Guglielmoa a

Department of Civil Engineering, University of Salerno, 84084 Fisciano (SA), Italy. (*) Corresponding Author. Tel. : +39+89+964140; fax: +39+89+964045 E-mail Address: [email protected] (C. Caliendo)

Abstract This paper presents the results of a study carried out in order to estimate accident rates and associated social-cost rates in motorway tunnels. A comparison between the results obtained in the investigated tunnels and those of the corresponding motorways containing these structures was also made. For this aim a 4-year monitoring period was considered in the analysis. The data-base used consisted of 195 unidirectional tunnels, in which 762 severe accidents were attributable to traffic with 774 injuries and 18 deaths. The results showed that severe accident rates and accident cost rates in tunnels were higher than those on the corresponding motorways. Accidents due to fire in tunnels were also investigated during the aforementioned monitoring period. The total number of these fire accidents occurring in 45 of the tunnels investigated were computed to be 53, 3 of which with 3 injuries and with zero deaths. Fortunately no major fire accident had occurred as a result of a catastrophic event or an explosion. Fire accident rates in tunnels were found to be lower than accident rates due to traffic only. A cost-benefit analysis, which is thought of as an aid in the choice of the priority of assigning public money in order to improve tunnels safety in compliance with the 2004/54/EC Directive, was also developed. This analysis was made assuming as a benefit the 50% potential reduction estimated for 2020 when compared to that of 2010 in social-costs of the consequences due to both traffic and fire accidents in tunnels. State funds that had been required by the Tunnels Management Agencies were assumed as the costs of measures that have to be implemented in the existing tunnels for improving safety. Costbenefit analysis might represent, at a preliminary level, an alternative approach to help decision-makers regarding the assignation of public funds when specific risk analyses of each tunnel are not available.

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Ciro Caliendo et al Keywords: Tunnel safety, Traffic accidents, Fire accidents, Cost-benefit analysis

Introduction

Traffic accidents in road tunnels differ from those occurring on open roads because are more especially attributable to the driver’s behaviour. Driving within the tunnel may generate anxiety as these structures are dark, narrow, and monotonous when compared to open roads. In addition drivers generally modify their lateral position in order to avoid the disturbing effect due to the tunnel wall being too close to the traffic lane. Geometric and traffic characteristics may also have a negative effect on tunnel safety. When a tunnel is narrow and/or an emergency lane is not present, the aforementioned effects on lateral position is expected to be greater; also longer tunnels and/or tunnels with small horizontal curves are often considered to be more dangerous. In addition high traffic volumes and the percentage of trucks may significantly influence accidents in tunnels. In the light of these considerations, it is worthwhile making an investigation into accidents caused by traffic in tunnels and comparing the results to those of open sections. Fire accidents in tunnels, which in contrast with the aforementioned traffic accidents are prevalently caused by electrical and/or mechanical defects of vehicles, generally attract more attention since catastrophic consequences and/or explosions might occur. However, also small-size fires may prove particularly critical for human life. Fires in tunnels produce heat, smoke, and toxic products, which can cause loss of life both for the tunnel users directly involved in accidents and for other people during their evacuation process from the tunnel. A fire also inevitably causes traffic congestion owing to the closure of the tunnel after the fire has started, which brings about extra transport time. The closure time of a tunnel may take minutes, hours or days depending on the fire size and its consequences. High temperatures produced by fire may also cause damage to structures (e.g. concrete spalling, ceiling collapsing, pavement burning) and/or to installations (e.g. ventilation, lighting, road signs, and monitoring systems). Finally, it is to be said that due to the confined space of a tunnel, when a fire occurs much more dangerous conditions than those outside the tunnel are found within this structure. The negative consequences of accidents, more especially in terms of deaths and injuries, have also a substantial economic cost. With reference to tunnels this economic cost may be higher than that relating to open roads since in the event of a fire traffic congestion is inevitability expected, as well as damage to structures and installations may also be found. Therefore, an economic evaluation of these costs in road tunnels is certainly also of interest. The high toll of human lives in Europe over the last few years due to large-scale fires (Mont Blanc tunnel in 1999 with 39 deaths, Tauern tunnel in 1999 with 12 deaths, Saint Gotthard tunnel in 2001 with 11 deaths), as well as the costs for repairing these structures and the indirect cost associated with the temporary closure of the roads containing these tunnels, have been the main reasons for the development of actions for reinforcing safety in road tunnels. In this respect, in 2004 the European

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Parliament and Council adopted the European Directive 2004/54/CE. The main objective of this Directive is to reduce the high toll of human lives in road tunnels in the future. This Directive has been adopted by each of the Member States, including Italy. In this respect, in 2010 several Italian Motorway Agencies that manage in Italy most of the tunnels of the Trans-European Road Network to which the aforementioned document is applicable, have required State funds for improving safety level of these structures in compliance with the Directive. Among many possible actions, the proposed safety measures more especially regard the reinforcing and/or the implementation of installations in the existing tunnels. It is generally believed that these measures can make a substantial contribution to meeting the objective of reducing fatalities in tunnels. However, when a tunnel has special characteristics the Directive recommends that a specific risk analysis should be carried out to establish whether additional safety measures and/or supplementary equipment are necessary to ensure a higher level of tunnel safety. Unfortunately, as far as the authors of this paper are aware, the aforementioned requests for economic contributions are generally not supported by any specific risk analysis of each tunnel. Therefore, the leading question is how to evaluate the effectiveness of the proposed safety measures. Among several alternative methods, this might be brought about by means of a cost-benefit analysis from a social perspective viewpoint. A cost-benefit analysis involving the social costs of accidents might be a support in the decision process aimed at the assignation of public funds when specific risk analyses of each tunnel are not available. Although the cost-benefit ratio has often been used for showing the cost effectiveness of countermeasures in road safety with reference to open roads, this ratio has hitherto been used to a lesser degree for tunnels. Using this ratio might be useful for setting, at a preliminary decision-making level, the priorities among different tunnels compatibly with available economic resources. In the light of the previous considerations, there are at least four main reasons for justifying this paper. The first is motivated by the need to quantify traffic accident rates in motorway tunnels and compare the results obtained to those of the corresponding motorways containing these structures. In fact there is an a priori reason for believing that traffic accidents in tunnels are higher than those on the corresponding open sections. The second is to make an evaluation of the social costs due to traffic accidents in tunnels. Such knowledge may be helpful for showing the economic relevance of these accidents particularly when compared to that of the corresponding motorways. The third reason is for investigating the number of accidents due to fire in tunnels and their consequences. In fact, if it is true that fire accidents in tunnels are generally less frequent than traffic accidents, these accidents are able to cause much more serious consequences in particular in the event of a large-scale fire. Finally, given that risk analyses for each tunnel might not be available for the evaluation of the effectiveness of measures aimed to improve safety level in tunnels in compliance with the 2004/54/EC Directive, alternative approaches should be implemented such as, for example, a cost-benefit analysis. This paper sets out to study both traffic accidents and fire accidents occurring in Italian motorway tunnels. The objective of the work is to estimate the frequency of these accidents using the vehicle-kilometres travelled in each tunnel as a measure of

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exposure, as well as to develop a cost-benefit analysis for an evaluation of the effectiveness of safety measures in tunnels. The cost-benefit analysis, however, will not take the place of the risk analysis, but may represent a useful tool for showing the early results that can support the decision process in assigning public funds for tunnels safety. For these purposes a 4-year monitoring period (2006-2009) was considered in the analysis. The present paper is organized as follows: the next section contains a review of the literature concerning both traffic and fire accidents in road tunnels, as well as economic evaluations of social costs of accidents, the subsequent section deals with the data set used and the process of preparing it for analysis, then the results are presented and discussed. Finally, conclusions and addresses for further studies are made.

Literature Review Traffic Accidents As far as the authors are aware the first studies on traffic accidents in road tunnels were devised by the PIARC Committee (1995) on Tunnel Safety. This Committee reported that: tunnels are safer than open roads except in the case of horizontal and/or vertical alignment defects; bidirectional tunnels cause more accidents than unidirectional tunnels; the average accident rate with injuries is 8 and 10 accident/108 veh.km for unidirectional and bidirectional tunnels, respectively. In studying driving behaviour in road tunnels, Törnoros (1998) found that the lateral distance to the nearest tunnel wall was greater when this wall was located to the left side of the drivers than to the right side. Amundsen and Ranes (2000) showed that traffic accident rates, which are higher in the entrance zone of tunnels, diminish as one proceeds inside the tunnel. These accident rates were also negatively associated with: tunnel length, AADT (annual average daily traffic), and tunnel width. Lemke (2000) found that: accident rates in unidirectional tunnels are fewer than those of the open roads (reduced by half); accident rates were associated positively with the tunnel length and negatively with the presence of shoulder; accident cost rates, which were estimated by the “human capital” approach, were in tunnels between one-third and one-half of those of open sections. SAFESTAR (2002), having found that the injury accident rates in unidirectional tunnels were both higher and lower than those of the corresponding open sections, argues that one cannot generally conclude that safety in tunnels is better or worse than on open roads. Salvisberg et al. (2004) claims that the risk of an accident occurring in a tunnel is lower in longer tunnels than in shorter tunnels, and that this risk increases with the AADT and/or trucks. Manser and Hancock (2007) found that the drivers’ perception of speed and their subsequent behaviour are influenced by the visual pattern and the texture applied to the tunnel wall. Nussbaumer (2007) supported Salvisberg’s aforementioned study and adds that the risk of accidents is higher in tunnels with bidirectional traffic than in tunnels with unidirectional traffic. Vashitz and al. (2008) showed that by means of improved communications in real time between drivers and tunnel through Intelligent Transport System (ITS) fewer accidents are expected. SWOV (2009) found that motorway


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tunnels have more injury accidents per vehicle/kilometre than open road sections in contrast with other international studies. Kircher and Ahlstrom (2012) showed how driver’s behaviour in tunnels is influenced by the illumination level and brightness of the tunnel walls. Caliendo et al. (2012b) developed a prediction model for predicting traffic accidents in Italian motorway tunnels. The results showed that traffic accidents are positively associated with: tunnel length (L), annual average daily traffic per lane (AADT), percentage of trucks (%Tr), and number of lanes (NL). The presence of shoulder did not appear to be statistically significant at the 5%level. The aforementioned studies show that traffic accident rates can be found to be both higher and lower than those of the corresponding open sections. This paper sets out to make a contribution to the state-of-the-art by helping to understand more about this leading question. Fire Accidents With reference to fire accidents, if one excludes the catastrophic events occurring in Europe during the last 15 years as a result of a fire, the most serious fire accidents in the world from 1949 to 2002 according to PIARC (2006) are 32, 27 of which brought about serious consequences to people, structures, and installations. Beard and Cope (2007) by means of an analysis of the world-wide accidents occurring in the period from 1987 to 2006 found that the number of significant road tunnel fires was 49 (including 43 in Europe) 13 of which with fatalities. Since too few fire accidents are recorded in general as in the past, these data are often insufficient to form a basis for a rigorous statistical analysis. However, it is to be said that the effect of a fire accident becomes much more dangerous when vehicles carry dangerous goods. In this respect, the passage of vehicles carrying dangerous goods through road tunnels is actually limited by specific restriction that are contained in the European Agreement concerning International Carriage of Dangerous Goods by Road (ADR). This agreement, which was made in 1957 under the auspices of the United Nations Economic Commission for Europe, has been recently upgraded by taking new amendments (United Nations, 2010) into account. With reference to the carriage of dangerous goods, Bubbico et al. (2009) by investigating the risk associated with the road transportation of hazardous material in tunnels found a higher risk in tunnels when compared to open roads. Their results suggested that the circulation through road tunnels of some types of dangerous goods should be allowed or forbidden on the basis of a specific risk analysis. Tunnel fires, however, are very complex phenomena because of the mutual interactions between physical and chemical processes (turbulence, combustion, radiation, etc.) which control fire and smoke development in a confined space. Among approaches for studying and analysing tunnel fires, computer simulations have nowadays become an ever more common practice for showing fire behaviour and for quantifying consequences. In this respect a vast literature exists (see Caliendo et al. (2012a) for greater in-depth knowledge). However, all these studies suffer from the lack of a more accurate evaluation of the frequency of fire accidents in tunnels. This paper makes this additional contribution possible by taking into account the exposure of fire accidents expressed in terms of vehicle-kilometres travelled in each tunnel.

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Economic Evaluation of Accidents Many studies concerning estimates of road accident costs are reported in the literature. In general they are based on two different methods, namely the so-called “human capital” approach and the “willingness to pay” approach. The former is based on the value of the economic production that is lost on account of the accident, while the latter is based on the estimation of the amounts that road users are willing to pay for a reduced accident risk. Discussions concerning potentiality, applicability and controversies of the economic evaluations of road accidents can be found more especially in: Elvik, 1995; Elvik, 2001; Trawén et al., 2002; Elvik, 2003; ICF, 2003. Elvik (1995) describes economic evaluations (costs) of a traffic accident fatality in 20 motorized countries. In a subsequent paper Elvik (2001) discusses, in contrast, the applicability of cost-benefit analysis as an aid to policy making for road safety measures. Trawén et al. (2002) collate information regarding costs for fatal casualty in traffic, which are adopted by different countries, and discuss the methods used for estimating these costs. Elvik (2003) analyses how to set priorities for road safety according to cost-benefit analysis. ICF (2003), finally, in accordance with the European Commission’s prior objective to reduce fatalities and injuries due to road accidents by 50% between 2001 and 2010, documents the benefits and costs of implementing some road safety measures. The proposed initiatives, which are based prevalently on the enforcement of existing road safety laws, gave helpful information to decision makers in the European Parliament and Council. However, these international studies based on an economic evaluation of accidents refer to open road sections only. In addition the costs per unit of persons killed or injured in a road accident which are adopted in foreign countries could be different from those in Italy. Therefore, this paper makes a contribution to our knowledge also through an economic evaluation of accidents occurring in Italian motorway tunnels and by comparing the results obtained to those of the corresponding motorways containing these structures. A cost-benefit analysis is also developed for showing the effectiveness of safety measures in the potential reduction in the consequences due to both traffic and fire accidents in tunnels. The next section describes the data set used and the procedure of preparing it for accident analysis in Italian motorway tunnels.

Data Description Traffic Accidents in Tunnels A 4-year monitoring period extending from 2006 to 2009 was considered for Italian motorway tunnels (unidirectional traffic only). The data base consisted of 195 unidirectional tunnels, 172 of which were two-lane tunnels while the remaining 23 were three-lane tunnels. Some 762 severe accidents (i.e. including injury and fatal accidents) were considered in the present paper, 668 of which occurred in two-lane tunnels and 94 in three-lane tunnels. The total number of injuries and deaths was 774 and 18 respectively; 681 injuries with 17 deaths occurring in two-lane tunnels and 93 injuries with 1 death in three lane-tunnels. Table 1 gives severe accident count data observed for each year, with the numbers of injuries and deaths being given in

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Evaluation of Traffic and Fire Accidents in Road Tunnels brackets.

Table 1. Severe accident count data observed during the 4-year monitoring period, with the number of injuries and deaths given in brackets. Year

Number of severe accidents (no. of injuries and deaths) Year’s total Two-lane tunnels Three-lane tunnels 2006 246 (251* + 6**) 33 (33* + 1**) 279 (284* + 7**) 2007 180 (184* + 5**) 33 (32* + 0**) 213 (216* + 5**) 2008 122 (124* + 3**) 15 (15* + 0**) 137 (139* + 3**) 2009 120 (122* +3**) 13 (13* + 0**) 133 (135* + 3**) Total 668 (681*+17**) 94 (93* + 1**) 762 (774* + 18**) (*) Number of injuries; (**) Number of deaths AADT values per each travel direction ranging from 4,500 to 40,761 vehicles per day were found for the two-lane tunnels and between 11,439 and 32,260 vehicles per day were evaluated for the three-lane tunnels. The percentage of trucks was 14÷31% and 17÷24% for two and three-lane tunnels, respectively. Summary statistics of the characteristics of the investigated tunnels are given in Table 2. However a more detailed description of accidents and characteristics of the investigated tunnels can be found in Caliendo and De Guglielmo (2012). Table 2. Summary statistics of characteristics of tunnels studied Characteristics Length (km) AADT per direction in tunnels (veh./day) Percentage of trucks (%)

Type of tunnel Two lanes Three lanes Two lanes Three lanes Two lanes Three lanes

Mean

Mode

1.16 0.18 17,273 23,416 21 22

0.53 0.89 6,126 25,533 16 23

Standard deviation 0.54 0.14 8,449 4,857 4 2

Minimum

Maximum

0.49 0.52 4,500 11,439 14 17

3.25 0.98 40,761 32,260 31 24

Traffic Accidents on Corresponding Motorways Severe accidents occurring in the aforementioned period (2006-2009) on the motorways containing the tunnels investigated were obtained from the accident data available on the official site of the Italian Association of Motorways and Tunnels (AISCAT, 2011). These accident data refer to both travel directions, and the AADT also refers to both directions. The number of motorways containing the tunnels investigated was found to be 17. The number of severe accidents occurring on these motorways in the 4-year period of monitoring was equal to a total of 19,028 for both travel directions; 11,654 of which occurred on two-lane motorways and 7,374 on three-lane motorways. The total number of injuries and deaths was 37,614 and 1,096 respectively. Table 3 gives severe accident count data for both travel directions with an associated number of injuries and deaths observed on two- and three-lane

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motorways, respectively. Table 3. Accident count recorded (both travel directions) on motorways containing the tunnels investigated. Year

Two-lane motorways Severe accidents

Injuries

Deaths

3,344

6,252

178

2007

3,032

5,766

2008

2,656

2009 Total

2006

Three-lane motorways Severe accidents

Injuries

Deaths

2,064

3,904

118

154

1,858

3,568

108

5,594

234

1,694

3,498

146

2,622

5,546

94

1,758

3,486

64

11,654

23,158

660

7,374

14,456

436

(*) Number of injuries; (**) Number of deaths

Two- and threelane motorways Year’s total

5,408 (10,156*+296**) 4,890 (9,334*+262**) 4,350 (9,092*+380**) 4,380 (9,032*+158**) 19,028 (37,614*+1,096**)

Table 4 gives summary statistics for two- and three-lane motorways at the same time with reference to the length of motorways, AADT for both travel directions, and percentage of trucks. Table 4. Summary statistics of characteristics of motorways containing the tunnels investigated. Characteristics

Mean

Mode

Standard deviation 220

Length 178 131 (km) AADT(***) 33,121 32,268 14,194 (veh./day) Percentage of trucks 22 22 4 (%) (***) AADT for both travel directions on motorways.

Minimum Maximum 24

804

8,786

59,090

14

31

Traffic Accident Costs Information about traffic accident costs was obtained from a study of the Italian Ministry of Infrastructure and Transport (MIT, 2010). In this regard the cost of a fatal accident is obtained as the sum of the costs of lost productive capacity, moral suffering, and medical care. Lost productive cost is the value of production lost due to a fatal accident. Moral cost refers to the pain, grief and suffering components that follow from a death. Medical cost is related to health care costs (including costs of


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first aid, ambulance transport, ambulatory care, and in-patient treatment) for a fatal injury in a road accident. In addition to the costs of lost production, moral suffering, and medical care, one has also to consider the general cost of a traffic accident. General cost represents costs of property damage on vehicles and roads, police and court, administration for insurance companies, etc. According to the MIT study this leads to the following total costs, which refer to the year 2010, for a person killed in a road accident: 940,291 € (lost production) + 561,734 € (moral suffering) + 1,965 € (medical care) = 1,503,990 €. With regard to a person injured in a road accident, according to MIT the corresponding total cost (i.e. including lost production, moral suffering, and medical care) is 42,219 €. The general cost of a traffic accident is, instead, assumed to be 10,986 €. Taking into account the average annual inflation rate of costs, in the present paper the costs per unit person dead or injured have been estimated, as well as the general cost per traffic accident, in the years from 2006 to 2009 (time period in which severe accidents were observed) as reported in Table 5. Table 5. Costs per unit of person dead or injured in a traffic accident on roads, and general cost of an accident. Year 2006 2007 2008 2009

Costs for unit of person dead (cf) € 1,383,944.23 € 1,425,536.11 € 1,409,356.67 € 1,491,973.21

Costs per unit of person injured (ci) € 38,851.25 € 40,018.85 € 39,564.65 € 41,883.93

General costs of a traffic accident (cg) € 9,984.51 € 10,284.58 € 10,167.85 € 10,763.89

In this paper traffic accident social costs for each tunnel were evaluated by considering the aforementioned unit costs and applied the following equation: Cs = cf (Nf) + ci(Ni) + cg(Nt,a)

(1)

where: Cs= social cost per year due to traffic accidents occurring in each tunnel; cf = unit cost per individual fatality, and Nf = number of fatalities per year due to traffic accidents in each tunnel; ci = unit cost per individual injury, and Ni = number of injuries per year due to traffic accidents in each tunnel; cg = general cost per each traffic accident, and Nt,a = number of traffic accidents occurring per year in each tunnel. Likewise, traffic accident social costs on the corresponding motorways containing the tunnels investigated were evaluated.

Analysis of Results Traffic Accident Rates The traffic accident indicator used in this analysis is the number of severe traffic

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accidents per 100 million vehicle-kilometres per one travel direction. These severe accident rates were computed for each tunnel and year. Likewise, this was made for each of the motorway containing the corresponding investigated tunnels. Table 6 reports severe accident rates due to traffic in the tunnels investigated and on the motorways containing these tunnels. Table 6. Severe accident rates due to traffic in the tunnels investigated and on the corresponding motorways.

Motorway Number of tunnels for motorway 1 1 2 7 3 34 4 2 5 6 6 30 7 16 8 27 9 7 10 12 11 1 12 17 13 13 14 4 15 14 16 1 17 3

Severe accident rates due to traffic Severe accident rates due to traffic on the motorways containing the in the tunnels investigated tunnels investigated (severe accidents/108 veh.km) (severe accidents/108 veh.km) Year Year 2006 2007 2008 2009 13.40 7.66 11.06 6.73 17.10 18.57 22.73 8.25 12.28 12.65 7.12 10.84 8.95 0.95 5.22 4.34 4.45

15.79 6.15 8.56 6.88 12.37 13.32 23.13 6.84 10.68 11.40 6.78 8.89 9.57 4.83 5.60 6.24 5.46

9.83 8.89 8.26 5.43 10.40 15.22 15.84 5.52 10.94 10.44 9.75 7.88 8.51 2.85 6.24 5.98 4.56

10.87 8.09 9.47 4.50 8.53 13.03 18.09 6.31 12.68 10.52 10.20 8.15 7.82 0.00 6.84 8.04 5.29

Average Average 2006 2007 2008 2009 values values 12.47 7.70 9.34 5.88 12.10 15.04 19.95 6.73 11.64 11.25 8.46 8.94 8.71 2.16 5.97 6.15 4.94

42.24 15.67 32.71 0.00 22.33 20.03 26.68 21.54 20.12 30.97 19.74 22.14 19.77 16.45 15.67 0.00 21.50

0.00 6.50 18.40 0.00 10.96 17.31 24.70 18.78 19.37 26.99 18.99 19.17 13.28 27.43 3.73 0.00 47.80

0.00 0.00 10.63 14.31 0.00 11.68 8.97 11.72 4.30 25.15 0.00 10.70 9.52 4.89 14.06 29.36 0.00

44.48 10.40 13.67 37.16 0.00 9.92 11.33 8.78 2.42 18.39 0.00 10.40 6.56 0.00 10.54 0.00 34.31

21.68 8.14 18.85 12.87 8.32 14.74 17.92 15.21 11.55 25.38 9.68 15.60 12.28 12.19 11.00 7.34 25.90

One can note that severe accident rates in the investigated tunnels are in general higher than those of the corresponding motorways. More especially we found that this occurred in about two-thirds of the tunnels studied, and that in the remaining one-third accident rates are instead lower. These results prove that severe accident rates due to traffic increase in tunnels in most of the cases investigated when compared to those of the corresponding motorways. However, in general it cannot be concluded that safety in tunnels is always lower than that of motorways. Apart from driver behaviour and visibility, tunnel safety is affected also by the geometric and traffic characteristics of the specific tunnel. Therefore different combinations of these variables might cause safety conditions that are either better or worse than those of the corresponding motorways.

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Tables 7 synthesises the average severe accident rates due to traffic in the aforementioned tunnels calculated by summing the accident rates of each tunnel per year and dividing the total by the number of the investigated tunnels (195) (in brackets are the average severe accident rates on the corresponding 17 motorways containing these tunnels). This table shows that the average severe accident rates are between 9.13 and 20.45 accidents/108veh.km for tunnels and between 8.62 and 10.14 accidents/108veh.km for motorways. This indicates that the average severe accident rates in tunnels are higher than those of the corresponding motorways. Table 7. Average severe accident rates due to traffic in the unidirectional tunnels investigated (severe accident rates of motorways (one direction) containing these tunnels). Tunnels Average severe accident rates (accident/108veh.km)

2006 20.45 (10.14)

2007 16.08 (9.56)

2008 9.13 (8.62)

2009 12.84 (8.73)

For comparing the mean of the traffic accident rates in tunnels with that of the corresponding motorways a T-test was also used. For this aim, the annual average traffic accident rate of each tunnel and that of the corresponding motorway were computed, and two independent data samples with size n1 = 195 and n2 = 17 were considered for tunnels and motorways, respectively. The obtained data were converted to logarithms and using Normal Test Plots was verified that both data exhibited the normal distribution. Then the one-tailed T-test was carried out, and the calculated T-statistic was found to be equal 2.36 against the tabulated critical value of 1.65 at the 95% confidence level for 210 degrees of freedom. Hence the null hypothesis (Ho), which stated that the means of two samples were equal, was rejected and obviously the alternative hypothesis (H1) stating that the mean of traffic accident rates in tunnels were higher than that of the motorways was accepted. The aforementioned table shows also a systematic reduction in severe crashes over time both for tunnels and motorways (with a slight exception for the year 2009). This reduction might be attributable to an increasing installation of electronic speed control systems (Tutor) carried out on Italian motorways during the aforementioned monitoring period (Autostrade, 2012), as well as to the positive effects of the introduction of the driving licence, introduced in Italy in 2003, with the demerit point system in the event of Highway Code infringement. Finally, a reduction in accidents also may be due to the training of drivers based on information campaigns to control speed and to encourage respect of the speed limits. Besides, it is to be said that severe crashes in tunnels decrease over time at a slightly greater rate than on the corresponding open roads, which might be due to the implementation and/or reinforcement of some facilities in tunnels after October 2006, the date of the coming into force in Italy of the European Directive 2004/54/EC. Traffic Accident Cost Rates Traffic accident costs were evaluated in this paper by using the aforementioned

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human capital approach and assuming the unit costs of the cited Table 5 as a reference. By multiplying the number of deaths and injuries of each tunnel respectively by the corresponding unit costs, the social costs of deaths and injuries as well as the general costs of traffic accidents were evaluated. The resulting cost was obtained as the sum of the above-mentioned three costs. Dividing the resulting cost by the number of the monitored years, AADT, and the length of each tunnel, the annual average severe accident cost rates were estimated. These were expressed in terms of euro per 103 veh.km per one travel direction in each tunnel. A similar procedure was followed for computing the annual average severe accident cost rates of the corresponding motorways. Table 8 contains the results obtained both for the tunnels and the corresponding motorways. Table 8. Severe accident cost rates both of the investigated tunnels and corresponding motorways. Motorway Number of tunnels for motorway

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

1 7 34 2 6 30 16 27 7 12 1 17 13 4 14 1 3

Severe accident cost rates [€/103 veh.km] (average values in 4-year period) Motorway Tunnels 42.59 36.67 19.86 60.77 13.02 54.99 4.08 60.81 17.29 13.98 33.57 37.04 332.43 44.08 12.41 51.48 71.24 54.94 3.46 43.24 17.88 284.72 1.10 39.79 3.79 137.03 216.64 20.74 1.81 36.67 66.40 60.77 104.76 54.99

This table shows that the severe accident cost rates of the road tunnels are higher than those of the corresponding motorways in about four-fifths of the investigated tunnels, whereas in the remaining one-fifth are lower. These findings indicate not only that severe accident rates in most of the tunnels are higher than those of the corresponding motorways, but also that the severity of accidents in tunnels involves more injuries and deaths, and as a consequence higher social cost rates.

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Fire Accidents in Tunnels Fire Accident Rates During the period monitored, fire accidents occurred in 45 of the investigated tunnels (35 of which were two-lane tunnels while the remaining 10 were three-lane tunnels). The total number of these fire accidents were computed to be 53, 3 of which with 3 injuries and 0 deaths. Fortunately no major fire accident had occurred as a result of a catastrophic event or an explosion. Table 9 gives fire accident count data in each year for two and three lane tunnels, respectively. Summary statistics of characteristics of the tunnels in which these fire accidents occurred are given in Table 10. Table 9. Fire accident count data recorded in the 45 of the investigated tunnels during the monitoring period. Year

Number of fire accidents Year’s total Two-lane tunnels Three-lane tunnels 2006 7 3 10 2007 10 6 16 2008 11 3 14 2009 10 3 13 Total 38 15 53 Table 10. Summary statistics of characteristics of the tunnels in which fire accidents occurred. Characteristics Length (km) AADT per direction in tunnels (veh./day) Percentage of trucks (%)

Type of tunnel Two lanes Three lanes Two lanes Three lanes Two lanes Three lanes

Mean

Mode

1.32 0.83 16,931 24,247 23 23

1.30 0.90 6,126 25,533 16 23

Standard deviation 0.50 0.32 8,336 6,408 5 2

Minimum

Maximum

0.54 0.52 4,500 11,439 15 17

2.79 0.98 32,258 32,260 31 23

Also with reference to fire accidents, since three-lane tunnels are much smaller in number than two-lane tunnels, no distinction was subsequently made between twoand three-lane tunnels, and only a comparison between fire accident rates and traffic accident rates for all tunnels was made in this paper. Table 11 shows that the fire accident rates in tunnels are between 4.33 and 6.19 fire accidents/108 veh.km. Compared to those of Table 7 these results indicate that fire accident rates in tunnels are much lower than traffic accident rates. More especially fire accident rate is found to be between one-half and one-fourth of that due to traffic. This confirms that fire accidents are less frequent than traffic accidents, even if they might cause catastrophic consequences.

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Ciro Caliendo et al Table 11. Fire accident rates of the tunnels in which fire accidents occurred. Tunnels 2006 2007 2008 2009 8 Fire accident rates (fire accidents/10 veh.km) 5.10 6.19 5.07 4.33

Fire Accident Cost Rates Fire in a tunnels produces heat, smoke, and toxic products, which may cause the loss of life both for drivers and tunnel occupants during their evacuation process. A fire also certainly causes traffic delays as a result of a temporary closure of the tunnel. In addition, high temperatures produced by fire might also cause damage to structures and/or installations. Therefore the economic losses due to fire accidents in tunnels are related, unlike traffic accidents, also to traffic congestion and damaged tunnel. An economic evaluation of the loss of time due to the traffic congestion in the event of a fire in the tunnel is complicated for several reasons. In fact the closure time of a tunnel can take minutes, hours or days depending on the size of fire and its consequences. Moreover, the monetary value of the lost time depends on the types of driver and passenger, the motive for going from one place to another, as well as the types of goods that are carried by commercial vehicles. Unfortunately the data base available did not contain any information about the closure time for all the 45 tunnels. However, it is to be said that 40 of these tunnels were recorded to have been affected only by small size fires that did not cause either damage to structures or to installations. Therefore for these tunnels a reduced closure time was expected. In this respect given the uncertainty about the exact closure time, the latter was assumed to be equal to the minimum time strictly necessary for extinguishing a small-size fire and in a short time annulling the disturbance to traffic flow after the fire start. More especially in this paper a minimum closure time of 30 minutes was assumed to be reasonably plausible. Since the congestion cost per unit of time can vary in a wide range depending on user type and carried goods, an average value of the unit cost of the delay time (td) caused by a fire in the tunnel was assumed. The monetary value of the lost time was considered to be on average 20 €/h per person for passenger cars (weighted average of travel time values considering both personal and business reasons) and 35 €/h for all trucks (FHWA, 2012). On the basis of these hourly values, which are related to 2012, hourly delay time costs were estimated in the years from 2006 to 2009, as well as in 2010, taking into account the annual average inflation rate of costs. In the light of these assumptions, the social cost of the delay time Ct,d attributable to a fire accident in the tunnel was evaluated through the following equation: Ct,d =ct,d(Np)td

(2)

where: Ct,d = delay time cost attributable to a fire accident in the tunnel; ct,d = unit cost of the delay time per hour, (ct,d equal to 20 €/h per person for cars and 35 €/h per person for trucks, respectively); Np = number of persons that are in queued vehicles = (AADT/24)∙cp∙(% vehicles),


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where AADT is the annual average daily traffic, cp is the persons average number per vehicle (cp was assumed to be equal to1.6 and 1.0 for cars and trucks, respectively), % vehicles is the percentage of cars or trucks within the AADT, respectively; td = delay time expressed in hour (td was assumed to be equal to 1/2 hour in this paper for all vehicles). Obviously by multiplying the delay time cost attributable to a fire accident by the number of fires occurring in the year in each tunnel, the corresponding annual delay time cost for each tunnel was computed. Damages to structures and/or installations due to fire were recorded to have been in 4 tunnels. This also caused the closure of these tunnels for much more than the aforementioned 30 minutes. In addition the available data-base did not contain further information for quantifying the costs of damages to structures and/or installation (which are expected to be much higher than social costs of the loss of human life and/or delay time). Given that transport is crucial for economic and cultural exchanges of a country and/or between different countries, there is convergence of opinions in public authorities concerning the fact that the investment costs for repairing the motorway tunnels damaged by fire should be considered as the most urgent in a list of priorities for immediately ensuring the service level of these tunnels in safety conditions. Since the authors of this paper agree in giving priority to motorway tunnels damaged by fire, the aforementioned 4 tunnels were considered to be in the first list of priorities so that they were excluded by the subsequent economic evaluation of fire accidents. This one is based only on the social costs of fatalities, injuries, and delay time. In Table 12 are given the cost rates computed as mentioned above for the 41 tunnels in which small-size fire accidents had occurred. Table 12. Fire accident cost rates of the tunnels in which fires occurred. Tunnels 2006 2007 2008 2009 3 Fire accident cost rates (€/10 veh.km) 3.37 1.79 1.72 1.69 This table shows that fire accident cost rates are found to be lower than those related to traffic accidents when damages to structures and/or installation are not considered in the analysis.

Cost Effectiveness of Safety Measures in Road Tunnels Risk Analysis There are several methods for evaluating the safety level of a tunnel and the effectiveness of safety measures that can be implemented for reducing the consequences of accidents. However, in order to compare the safety level of different tunnels and for investigating the cost effectiveness of safety measures, the probabilistic risk analysis is generally considered to be the best tool. Probabilistic analysis is based on the so-called event tree which is made from all possible accident scenarios that can occur during the use of the tunnel. Besides the normal situation, this event tree also includes every disturbance in the tunnel and its consequences that are

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expressed in terms of fatalities and injuries, as well as damage (e.g. to vehicles, structures, installations, and traffic flows). When both the probability and the consequences are assigned to every branch of the event tree, one can estimate the risk level of a tunnel as the sum of probabilities multiplied by consequences. To judge the risk level that is acceptable different criteria exist in the literature. In this respect, however, the social acceptable risk level is often used. Societal risk is frequently represented graphically in the form of an FN-curve; where F is the cumulative probability that the number of fatalities is equal to or greater than a given number N. This curve is a straight line on a double logarithmic scale. If the risk indicator is below the aforementioned FN-curve, the risk level is considered acceptable, whereas if the risk level is above the FN-curve it should be reduced by safety measures, which obviously have some costs. In the light of these considerations, the cost effectiveness of safety measures should be related to reducing the level of risk in the tunnel. However, it is to be said that the finding of a clear relationship by means of a risk analysis, between the investment costs and their quantified effects on the level of safety in tunnels does not appear to be easy for various reasons. First of all, many studies reported in the literature on tunnels safety have been carried out from a deterministic point of view, so that the knowledge of the effects of safety measures based on a probabilistic approach still appears rather limited. In addition, little is known about the cumulative effects of various safety measures and their interdependence in risk analysis. Therefore, alternative approaches as, for example, cost-benefit analysis might be helpful when specific risk analyses for each tunnel are not available. Cost-Benefit Analysis Road safety has been greatly improved since the number of road accident fatalities was reduced by 50% in 2010 when compared to that of 2001. Nevertheless, there is still a large potential for further reducing fatalities on roads by using appropriate safety measures. In this respect, the objective reported in the recent Communication from European Commission to the European Parliament (COM, 2010) indicates a further 50% reduction of the number of deaths on roads estimated for 2020 when compared to that of 2010. Among different methods that are suitable for an economic evaluation of road accident prevention measures in accordance with the aforementioned objective, there is also the cost-benefit analysis (CBA) from a social perspective. The CBA is generally carried out by comparing the benefits of the implementation of safety measures, which are expressed in monetary terms of prevented social costs of causalities, with their costs. However, it is to be said that there are two considerations that are often made against the use of this approach. One concerns the fact that the putting of a monetary value on human life does not appear to be not ethically acceptable. Another argument is that some issues are not subject to an economic evaluation as, for example, damage to environment. In this respect it is to be said that fire in a tunnel might potentially represent a hazard to the environment for the toxicity of the smoke and substances in the drainage. Nevertheless, the costbenefit analysis has been successfully applied in road safety for many years, but it is


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not within the scope of this paper the discussing the eventual implications of the aforementioned criticisms. The focus of discussion in this paper are not potentialities and/or controversies of the cost-benefit analysis, but since the risk analyses of tunnels might not be available the CBA might represent an alternative for setting the priorities of investments at least at a preliminary decision level.

Procedure and Results from Cost-Benefit Analysis

One of the key steps in the cost-benefit analysis that has been carried out in this paper is in the assuming as a reference the aforementioned objective to reduce by 50% the number of deaths on roads estimated for 2020 when compared to that of 2010. However, this paper extends this objective to the reduction of more consequences in tunnels such as fatalities, injuries, and general damage when traffic accidents are considered. In addition also the delay time due to traffic congestion is considered in the event of fire accidents. These consequences are expressed in monetary terms of social costs both for traffic accidents and fire accidents that have occurred between 2006 and 2009 in the tunnels investigated. The computed annual average social cost for each tunnel was assumed as a reference in 2010. The situation in 2010 was taken as the baseline for estimating future social costs for 2020 without the implementation of safety measures in the tunnel, and taking into account the annual average inflation rate of costs. The economic benefits (B) were assumed to be in the 50% reduction in the aforementioned social costs predicted for 2020 when the proposed safety measures in the tunnel are assumed to be fully implemented in 2010. As regards investment costs (C), it is to be said that several Italian Motorway Agencies that in Italy manage most of the tunnels of the Trans-European Road Network required, in 2010, State funds for improving safety level of these structures in compliance with the European Directive 2004/54/CE. The proposed safety measures more especially regard the reinforcing and/or the implementation of installations in the existing tunnels. Unfortunately, as has already been said, the aforementioned requests for economic contributions were generally not supported by specific risk analysis for each of tunnels. Therefore, a cost-benefit analysis was carried out as a criterion that may help to decide what are the first tunnels that might be improved. The investment costs (C) were required for 177 of the tunnels investigated. Table 13 gives summary statistics of these investments for all these mentioned tunnels. Table 13. Summary statistics of investment costs (C) required in 2010 for all tunnels. Investment Mean Mode Standard Minimum Maximum Costs deviation € 2,996,317.39 6,317,075.00 4,398,986.22 150,091.00 18,406,550.00 Since the aforementioned 4 tunnels damaged by large-size fires have priority, these tunnels were not included in the subsequent cost-benefit analysis. Therefore the

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benefit-investment cost ratios (B/C), are restricted exclusively to 173 tunnels. Table 14 gives summary statistics of the benefit-cost ratios for all tunnels. Table 14. Summary statistics of the benefit-investment cost ratios (B/C) for 173 tunnels. Mean Mode Standard deviation Minimum Maximum 0.7 0.004 1.2 0.004 8.1 More especially a percentage of tunnels equal to 25% was found for having a B/C ratio higher than 1.0; a percentage of 15% was computed to have 1