Estimation of social value of statistical life using willingness-to-pay method in Nanjing,China

Rational decision making regarding the safety related investment programs greatly depends on the economic valuation of traffic crashes. The primary objective of this study was to estimate the social value of statistical life in the city of Nanjing in China. A stated preference survey was conducted to investigate travelers’ willingness to pay for traffic risk reduction. Face-to-face interviews were conducted at stations, shopping centers, schools, and parks in different districts in the urban area of Nanjing. The respondents were categorized into two groups, including motorists and non-motorists. Both the binary logit model and mixed logit model were developed for the two groups of people. The results revealed that the mixed logit model is superior to the fixed coefficient binary logit model. The factors that significantly affect people’s willingness to pay for risk reduction include income, education, gender, age, drive age (for motorists), occupation, whether the charged fees were used to improve private vehicle equipment (for motorists), reduction in fatality rate, and change in travel cost. The Monte Carlo simulation method was used to generate the distribution of value of statistical life (VSL). Based on the mixed logit model, the VSL had a mean value of 3,729,493 RMB ($586,610) with a standard deviation of 2,181,592 RMB ($343,142) for motorists; and a mean of 3,281,283 RMB ($505,318) with a standard deviation of 2,376,975 RMB ($366,054) for non-motorists. Using the tax system to illustrate the contribution of different income groups to social funds, the social value of statistical life was estimated. The average social value of statistical life was found to be 7,184,406 RMB ($1,130,032).     

International comparison of costs of a fatal casualty of road accidents in 1990 and 1999

The purpose of this study is to assemble information of costs per fatal casualty in traffic accidents, adopted by authorities in different countries. analyse and compare these figures as well as the methods used for estimating these values. A questionnaire was sent to 19 countries from which 11 gave information on cost per fatality and methods of valuation. The costs per fatality, usually defined as direct and indirect costs plus a value of safety per se, are compared both between countries and over time, 1990 and 1999, for each country. The average cost per fatality has increased between 1990 and 1999 (fixed prices) due to both changes in the methodology and changes of valuations. Great Britain, New Zealand, Sweden and the US conduct own willingness-to-pay (WTP) surveys, while the Netherlands and Norway make reviews of these studies. In Finland, the cost per fatality is a combination of the value of lost productivity and the cost of care for an institutionalised disabled person. In Australia, Austria, Germany and Switzerland, the cost per fatality is estimated as a value of lost productivity and an addition of a human cost based on compensation payments or insurance payments. Estimates from recently conducted WTP surveys or meta-analyses are considered in Austria, Finland and Sweden, however, not yet adopted as official values for use in road traffic planning.     

Social costs of road crashes: An international analysis

This paper provides an international overview of the most recent estimates of the social costs of road crashes: total costs, value per casualty and breakdown in cost components. The analysis is based on publications about the national costs of road crashes of 17 countries, of which ten high income countries (HICs) and seven low and middle income countries (LMICs). Costs are expressed as a proportion of the gross domestic product (GDP). Differences between countries are described and explained. These are partly a consequence of differences in the road safety level, but there are also methodological explanations. Countries may or may not correct for underreporting of road crashes, they may or may not use the internationally recommended willingness to pay (WTP)-method for estimating human costs, and there are methodological differences regarding the calculation of some other cost components.The analysis shows that the social costs of road crashes in HICs range from 0.5% to 6.0% of the GDP with an average of 2.7%. Excluding countries that do not use a WTP- method for estimating human costs and countries that do not correct for underreporting, results in average costs of 3.3% of GDP. For LMICs that do correct for underreporting the share in GDP ranges from 1.1% to 2.9%. However, none of the LMICs included has performed a WTP study of the human costs.A major part of the costs is related to injuries: an average share of 50% for both HICs and LMICs. The average share of fatalities in the costs is 23% and 30% respectively. Prevention of injuries is thus important to bring down the socio-economic burden of road crashes.The paper shows that there are methodological differences between countries regarding cost components that are taken into account and regarding the methods used to estimate specific cost components. In order to be able to make sound comparisons of the costs of road crashes across countries, (further) harmonization of cost studies is recommended. This can be achieved by updating and improving international guidelines and applying them in future cost studies. The information regarding some cost components, particularly human costs and property damage, is poor and more research into these cost components is recommended.     

Typical pedestrian accident scenarios for the development of autonomous emergency braking test protocols

An increasing proportion of new vehicles are being fitted with autonomous emergency braking systems. It is difficult for consumers to judge the effectiveness of these safety systems for individual models unless their performance is evaluated through track testing under controlled conditions. This paper aimed to contribute to the development of relevant test conditions by describing typical circumstances of pedestrian accidents. Cluster analysis was applied to two large British databases and both highlighted an urban scenario in daylight and fine weather where a small pedestrian walks across the road, especially from the near kerb, in clear view of a driver who is travelling straight ahead. For each dataset a main test configuration was defined to represent the conditions of the most common accident scenario along with test variations to reflect the characteristics of less common accident scenarios. Some of the variations pertaining to less common accident circumstances or to a minority of casualties in these scenarios were proposed as optional or supplementary test elements for an outstanding performance rating. Many considerations are incorporated into the final design and implementation of an actual testing regime, such as cost and the state of development of technology; only the representation of accident data lay within the scope of this paper. It would be desirable to ascertain the wider representativeness of the results by analysing accident data from other countries in a similar manner.     

Willingness-to-pay for reducing fatal accident risk in urban areas: an Internet-based Web page stated preference survey

Contemporary transport project evaluation requires the ability to value reductions in the number of estimated fatal and non-fatal accidents after project implementation. In this quest, we designed a stated preference (SP) experiment to estimate willingness-to-pay (WTP) for reducing fatal accident risk in urban areas. The survey was implemented in a Web page allowing rapid turnover and a complete customisation of the interview. The sample was presented with a series of route choice situations based on travel time, cost and number of car fatal accidents per year. With this data we estimated Multinomial Logit (MNL) and Mixed Logit (ML) models based on a consistent microeconomic framework; the former with linear and non-linear utility specifications and allowing for various stratifications of the data. The more flexible ML models also allow to treat the repeated observations problem common to SP data and, as expected, gave a better fit to the data in all cases. Based on these models, we estimated subjective values of time, that were consistent with previous values obtained in the country, and also sensible values for the WTP for reductions in fatal accident risk. Thus, the Internet appears as a potentially very interesting medium to carry out complex stated choice surveys.     

Health-health analysis-an alternative method for economic appraisal of health policy and safety regulation. Some empirical Swedish estimates

Health-health analysis (HHA) focuses on statistical lives themselves as a numeraire. The underlying principle is that the expected gains in health and safety of reduced risks in one area may result in increasing risks somewhere else in society. By reducing one risk other risks may increase due to changed individual behaviour.In addition to this direct effect, another indirect effect will also be present. Expenditure on a particular health policy or safety regulation must be financed in one way or another, which will result in an opportunity cost or income effect leaving less resources for other health and safety promoting activities in society. Thus, we will have an effect that reduces safety and health benefits induced by that income loss. Whether the total net health effect from a specific safety regulation or health policy is positive or negative must be empirically analysed. One way of estimating the income loss that induces one death, which we call the value of an induced death (VOID), is to estimate it as a multiple of the traditional value to avert a statistical death, also named the value of a statistical life (VOSL).A contingent valuation (CV) study eliciting the willingness-to-pay (WTP) for reducing the overall risk of dying was performed as a postal questionnaire in Sweden in 1998. By use of data from this study, it was possible to estimate the VOID and the VOSL in Sweden amounting to SEK116 and SEK20.8 million respectively, indicating that the net health result confined to mortality effects, will be negative (more lives will be lost than saved) if a health policy or safety regulation will cost more than SEK116 million per life saved.     

Accidents in the construction industry in the Netherlands: An analysis of accident reports using Storybuilder

As part of an ongoing effort by the Ministry of Social Affairs and Employment of the Netherlands, a research project is being undertaken to construct a causal model for occupational risk. This model should provide quantitative insight into the causes and consequences of occupational accidents. One of the components of the model is a tool to systematically classify and analyse reports of past accidents. This tool ‘Storybuilder’ was described in earlier papers. In this paper, Storybuilder is used to analyse the causes of accidents reported in the database of the Dutch Labour Inspectorate involving people working in the construction industry. Conclusions are drawn on measures to reduce the accident probability. Some of these conclusions are contrary to common beliefs in the industry.     

Relative fatality risk curve to describe the effect of change in the impact speed on fatality risk of pedestrians struck by a motor vehicle

Models describing the relation between impact speed and fatality risk for pedestrians struck by a motor vehicle have frequently been used by practitioners and scientists in applying an S curve to visualize the importance of speed for the chance of survival. Recent studies have suggested that these risk curves are biased and do not give representative risk values. These studies present new fatality risk curves that show much lower risks of fatality than before, which has caused confusion and misconceptions about how these new curves should be interpreted, and how this should affect speed management policy.     

Storybuilder—A tool for the analysis of accident reports

As part of an ongoing effort by the ministry of Social Affairs and Employment of The Netherlands a research project is being undertaken to construct a causal model for the most commonly occurring scenarios related to occupational risk. This model should provide quantitative insight in the causes and consequences of occupational accidents. The results should be used to help selecting optimal strategies to reduce these risks taking the costs of accidents and of measures into account. The research is undertaken by an international consortium under the name of Workgroup Occupational Risk Model. One of the components of the model is a tool to systematically classify and analyse past accidents. This tool: “Storybuilder” and its place in the Occupational Risk Model (ORM) are described in the paper.The paper gives some illustrations of the application of the Storybuilder, drawn from the study of ladder accidents, which forms one of the biggest single accident categories in the Dutch data.     

The fatality and injury risk of light truck impacts with pedestrians in the United States

In the United States, passenger vehicles are shifting from a fleet populated primarily by cars to a fleet dominated by light trucks and vans (LTVs). Because light trucks are heavier, stiffer, and geometrically more blunt than passenger cars, they pose a dramatically different type of threat to pedestrians. This paper investigates the effect of striking vehicle type on pedestrian fatalities and injuries. The analysis incorporates three major sources of data, the Fatality Analysis Reporting System (FARS), the General Estimates System (GES), and the Pedestrian Crash Data Study (PCDS). The paper presents and compares pedestrian impact risk factors for sport utility vehicles, pickup trucks, vans, and cars as developed from analyses of US accident statistics. Pedestrians are found to have a two to three times greater likelihood of dying when struck by an LTV than when struck by a car. Examination of pedestrian injury distributions reveals that, given an impact speed, the probability of serious head and thoracic injury is substantially greater when the striking vehicle is an LTV rather than a car.     

Scenario analysis of freight vehicle accident risks in Taiwan

This study develops a quantitative risk model by utilizing Generalized Linear Interactive Model (GLIM) to analyze the major freight vehicle accidents in Taiwan. Eight scenarios are established by interacting three categorical variables of driver ages, vehicle types and road types, each of which contains two levels. The database that consists of 2043 major accidents occurring between 1994 and 1998 in Taiwan is utilized to fit and calibrate the model parameters. The empirical results indicate that accident rates of freight vehicles in Taiwan were high in the scenarios involving trucks and non-freeway systems, while; accident consequences were severe in the scenarios involving mature drivers or non-freeway systems. Empirical evidences also show that there is no significant relationship between accident rates and accident consequences. This is to stress that safety studies that describe risk merely as accident rates rather than the combination of accident rates and consequences by definition might lead to biased risk perceptions. Finally, the study recommends using number of vehicle as an alternative of traffic exposure in commercial vehicle risk analysis. The merits of this would be that it is simple and thus reliable; meanwhile, the resulted risk that is termed as fatalities per vehicle could provide clear and direct policy implications for insurance practices and safety regulations.     

Estimation of the social costs of home injury: a comparison with estimates for road injury

Home injury is thought to constitute a major health burden in most developed countries. However, efforts to address this burden have been hampered by reluctance from outside agencies to interfere with the home environment of individuals, even if it benefits the occupant's safety. This paper outlines cost–benefit evaluation methods established in the transport safety domain applied to home safety to estimate the social cost of unintentional home injury in New Zealand. Estimates of costs imposed on society by home injury can provide an important motivator for initiating research and programmes to reduce home injury risk. Data sources used included mortality data, hospitalisation data and data on minor injuries that required medical treatment, but not hospital admission. We estimated that unintentional home injuries in New Zealand impose an annual social cost of about $NZ 13 billion (about $US 9 billion), which is about 3.5 times the annual social cost of road injury. These estimates provide a rational evidence base for decisions on housing-focused safety regulation or interventions that always carry some cost, and therefore need to be weighed against the benefits of injuries potentially prevented.     

A new method for assessing the risk of accident associated with darkness

This paper presents a new method for assessing the risk of accidents associated with darkness. The method estimates the risk of accident associated with darkness in terms of an odds ratio, which is defined as follows: [(number of accidents in darkness in a given hour of the day)/(number of accidents in daylight in the same hour of the day)]/[(Number of accidents in a given comparison hour when the case hour is dark)/(Number of accidents in a given comparison hour when the case hour is in daylight)]. This estimate of the risk of accident associated with darkness does not require data on exposure, but relies on the count of accidents in the same pair of hours throughout the year. One of the hours is dark part of the year, but has daylight the rest of the year. The comparison hour, which has daylight the whole year, is used to control for seasonal variations. The aim of relying on the same pair of hours throughout the year is to minimise the influence of potentially confounding factors. Estimates of the risk of injury accidents associated with darkness are developed on the basis of accident data for Norway, Sweden and the Netherlands. It is found that the risk of an injury accident increases by nearly 30% in darkness in urban areas, by nearly 50% in rural areas, and by about 40% for urban and rural areas combined (adjusted estimate).     

Sensitivity analysis of an accident prediction model by the fractional factorial method

Sensitivity analysis of a model can help us determine relative effects of model parameters on model results. In this study, the sensitivity of the accident prediction model proposed by Zegeer et al. [Zegeer, C.V., Reinfurt, D., Hummer, J., Herf, L., Hunter, W., 1987. Safety Effect of Cross-section Design for Two-lane Roads, vols. 1-2. Report FHWA-RD-87/008 and 009 Federal Highway Administration, Department of Transportation, USA] to its parameters was investigated by the fractional factorial analysis method. The reason for selecting this particular model is that it incorporates both traffic and road geometry parameters besides terrain characteristics. The evaluation of sensitivity analysis indicated that average daily traffic (ADT), lane width (W), width of paved shoulder (PA), median (H) and their interactions (i.e., ADT-W, ADT-PA and ADT-H) have significant effects on number of accidents. Based on the absolute value of parameter effects at the three- and two-standard deviation thresholds ADT was found to be of primary importance, while the remaining identified parameters seemed to be of secondary importance. This agrees with the fact that ADT is among the most effective parameters to determine road geometry and therefore, it is directly related to number of accidents. Overall, the fractional factorial method was found to be an efficient tool to examine the relative importance of the selected accident prediction model parameters.     

The role of the built environment in explaining relationships between perceived and actual pedestrian and bicyclist safety

While the conventional approach to safety planning has emphasized crash analysis with police-reported crash information, transportation professionals increasingly recognize the importance of proactively identifying potential crash risk and considering environmental characteristics. In a proactive approach, individuals’ perception of crash risk provides important information in identifying potential crash risk. As built environment characteristics influence the levels of pedestrian and bicycle safety, this study examined how perceived and actual crash risk are related with each other and with respect to built environmental characteristics. Our results showed that residents who live in low density-single residential neighborhoods are more likely to perceive their neighborhood as dangerous relative to residents of compact, mixed-use neighborhoods even though the latter exhibited higher actual crash rates. The results of path analyses confirmed that a simultaneous but opposite relationship exists between perceived and actual crash risks. Our results indicate that higher actual crash risk increases perceived crash risk, while higher perceived crash risk is negatively associated to actual crash rates. Consequently, low density and non-mixed land uses increase individuals perception of crash risk, and increased perception of risk and unfriendly environment for pedestrian and bikers reduces actual crash rates as a result of behavioral changes. From a policy standpoint, more attention and proactive interventions are desirable in suburban areas beyond the areas with high crash rates, as some of these areas have high-perceived risks.     

Quantifying human and organizational factors in accident management using decision trees: the HORAAM method

In the framework of the level 2 Probabilistic Safety Study (PSA 2) project, the Institute for Nuclear Safety and Protection (IPSN) has developed a method for taking into account Human and Organizational Reliability Aspects during accident management. Actions are taken during very degraded installation operations by teams of experts in the French framework of Crisis Organization (ONC). After describing the background of the framework of the Level 2 PSA, the French specific Crisis Organization and the characteristics of human actions in the Accident Progression Event Tree, this paper describes the method developed to introduce in PSA the Human and Organizational Reliability Analysis in Accident Management (HORAAM). This method is based on the Decision Tree method and has gone through a number of steps in its development. The first one was the observation of crisis center exercises, in order to identify the main influence factors (IFs) which affect human and organizational reliability. These IFs were used as headings in the Decision Tree method. Expert judgment was used in order to verify the IFs, to rank them, and to estimate the value of the aggregated factors to simplify the quantification of the tree. A tool based on Mathematica was developed to increase the flexibility and the efficiency of the study.     

Stated preference in the valuation of interurban road safety

In Chile, as in most less-developed nations, if life savings are valued at all the human capital approach is used in a rather non-consistent fashion. As part of a 5-year research project on the value of transport externalities, a stated preference (SP) experiment was carried out in order to assess the value of a statistical life for Chilean interurban motorways. Interviewees had to choose among different routes for a hypothetical trip, based on the following attributes: travel time, toll charge and level of risk. The results of our experiment show that people were sensitive to the risk variable, thus "stating" a preference for safer routes. Several models were estimated with linear and non-linear utility specifications, and also incorporating the effects of socio-economic variables in a novel and interesting fashion. We were able to estimate subjective values of time consistent with previous values obtained in the country and reasonably looking values (in comparison to Chilean prices and foreign experience) of a statistical life. The paper discusses the experimental design, data collection and analysis, with emphasis on the role of lexicographic individuals that are a feature of SP studies that has not been carefully explored in the literature. We also present our modelling results and compare our derived values (of time and of a statistical life) with values found previously and/or elsewhere.     

The value of statistical life in road safety: a meta-analysis

Costs of accidents make up an important part of the total external cost of traffic. A substantial proportion of accident costs is related to fatal accidents. In the evaluation of fatal accident costs the availability of an estimate of the economic value of a statistical life is pivotal. We present an overview of the empirical literature on the value of statistical life in road safety (VOSL), and use meta-analysis to determine variables that explain the variation in VOSL estimates reported in the literature. We show that the magnitude of VOSL estimates depends on the value assessment approach (particularly, stated versus revealed preference), and for contingent valuation studies also on the type of payment vehicle and elicitation format. We explain that VOSL estimates cannot simply be averaged over studies. The magnitude of VOSL is intrinsically linked to the initial level of the risk of being caught up in a fatal traffic accident and to the risk decline implied by the research set-up.     

Diagnostic analysis of the logistic model for pedestrian injury severity in traffic crashes

This study attempts to evaluate the injury risk of pedestrian casualties in traffic crashes and to explore the factors that contribute to mortality and severe injury, using the comprehensive historical crash record that is maintained by the Hong Kong Transport Department. The injury, demographic, crash, environmental, geometric, and traffic characteristics of 73,746 pedestrian casualties that were involved in traffic crashes from 1991 to 2004 are considered. Binary logistic regression is used to determine the associations between the probability of fatality and severe injury and all contributory factors. A consideration of the influence of implicit attributes on the trend of pedestrian injury risk, temporal confounding, and interaction effects is progressively incorporated into the predictive model. To verify the goodness-of-fit of the proposed model, the Hosmer–Lemeshow test and logistic regression diagnostics are conducted. It is revealed that there is a decreasing trend in pedestrian injury risk, controlling for the influences of demographic, road environment, and other risk factors. In addition, the influences of pedestrian behavior, traffic congestion, and junction type on pedestrian injury risk are subject to temporal variation.