Overtaking maneuvers on two-lane highways under the microscope: Exploration of a multidimensional framework for the analysis of safety, comfort and efficiency using simulator data.

An unreasonable overtaking attempt on two-lane highways could cause drivers to suffer in terms of driving safety, comfort, and efficiency. Several external factors related to the traffic environment (e.g., speed and car type of surrounding vehicles), were found to be the significant factors in drivers' overtaking performance in the previous studies. However, the microscopic decision-making (e.g., the moments of the occupation of the opposite lane) mechanisms during overtaking, by means of which drivers react to changes in the external traffic environment and adjust their overtaking trajectories, are still need to be explored. Hence, this study had three goals: (i) To explore the spatial characteristics of micro-decisions (MDs) (such as the start and end point) in overtaking trajectories; (ii) To measure three types of performance indicators (i.e., safety, comfort, and efficiency) for the execution of overtaking maneuvers; (iii) To quantitatively explain the microscopic decision-making mechanism in overtaking. Data for overtaking trajectories were collected from driving a simulation experiment where 52 Chinese student drivers completed a series of overtaking maneuvers on a typical two-lane highway under different traffic conditions. Two analyses were conducted: firstly, the distributions of the relative distance between the ego and surrounding vehicles at four key points (i.e., the start, entry, back, and end) in the overtaking trajectory were investigated and clustered to uncover the spatial characteristics of the MDs. Secondly, the safety, comfort, and efficiency of the overtaking were measured by the aggregations of multi-targets collision risks, triaxial acceleration variances, and spatial consumptions respectively based on the Data Envelopment Analysis (DEA), which were further applied in a two-stage SEM model to reveal the quantitative interrelationships among the external factors, microscope decisions and performances in overtaking. We confirmed that the MDs could be considered as the mediating variables between the external factors and overtaking performances. In the presence of the more hazardous traffic environment (e.g., faster traffic flow and impeded by a truck), the safety, comfort and efficiency of overtaking would be deteriorated inevitably. But drivers would execute the overtaking under the longer passing sight distance, migrate their trajectories forward, and shorten the spatial duration to significantly improve the overtaking performances. Based on this mechanism, a overtaking trajectory optimization strategy for the advanced or automatic driving system, was confirmed and concluded that 1) the passing gap should be firstly planned according to the sight distance acceptance of different drivers, which directly determine the upper limit of the safety performance in the overtaking; 2) the trajectory forward migration and shortening the whole duration in overtaking could be effective to enhance the overtaking performances of the overtaking on the two-lane highway; 3) the guidance of the stable control of the steering wheel and gas/brake pedals is essential in the overtaking.

Towards better road safety management: Lessons learned from inter-national benchmarking.

Inter-national benchmarking of road safety, with the purpose of achieving continuous improvement by learning lessons from existing best practices, has currently been widely encouraged by most countries as an emerging management tool to improve the level of road safety. However, performing a successful road safety benchmarking practice is by no means easy. Challenges exist from ascertaining the benchmarking framework at the very beginning to making final policy decisions. In this study, based on the identification of leading road safety risk factors, a comprehensive set of hierarchically structured safety performance indicators was developed, some necessary data processing procedures were conducted, and the use of data envelopment analysis (DEA) for composite indicator (CI) construction was elaborated. An interval multiple layer DEA-based CI model was proposed to take both the hierarchical structure of the indicators and the data uncertainty into account, and was used to benchmark road safety performance for a set of European countries. Based on the model output, best-performing and underperforming countries were distinguished and all the countries were further ranked by computing their cross-index score. Moreover, by taking the characteristics of each country in the data set into account, country-specific benchmarks for those underperforming countries were identified, and useful insight in the areas of underperformance in each country was gained. Meanwhile, by summarizing the risk aspects that need urgent policy action for all these countries, some specific road safety enhancing recommendations for this region as a whole were formulated.

Identifying the most significant indicators of the total road safety performance index.

The review of the national and international literature dealing with the assessment of the road safety level has shown great efforts of the authors who tried to define the methodology for calculating the composite road safety index on a territory (region, state, etc.). The procedure for obtaining a road safety composite index of an area has been largely harmonized. The question that has not been fully resolved yet concerns the selection of indicators. There is a wide range of road safety indicators used to show a road safety situation on a territory. Road safety performance index (RSPI) obtained on the basis of a larger number of safety performance indicators (SPIs) enable decision makers to more precisely define the earlier goal- oriented actions. However, recording a broader comprehensive set of SPIs helps identify the strengths and weaknesses of a country's road safety system. Providing high quality national and international databases that would include comparable SPIs seems to be difficult since a larger number of countries dispose of a small number of identical indicators available for use. Therefore, there is a need for calculating a road safety performance index with a limited number of indicators (RSPIlnn) which will provide a comparison of a sufficient quality, of as many countries as possible. The application of the Data Envelopment Analysis (DEA) method and correlative analysis has helped to check if the RSPIlnn is likely to be of sufficient quality. A strong correlation between the RSPIlnn and the RSPI has been identified using the proposed methodology. Based on this, the most contributing indicators and methodologies for gradual monitoring of SPIs, have been defined for each country analyzed. The indicator monitoring phases in the analyzed countries have been defined in the following way: Phase 1- the indicators relating to alcohol, speed and protective systems; Phase 2- the indicators relating to roads and Phase 3- the indicators relating to trauma management. This will help achieve the standardization of indicators including data collection procedures and selection of the key list of indicators that need to be monitored. Based on the results, it has been concluded that the use of the most contributing indicators will make it possible to assess the level of road safety on a territory, with an acceptable quality score by focusing on the low-ranked countries. A smaller set of significant indicators defined in this manner can serve for a fast and simple understanding of a road safety situation and assessment of effects of measures undertaken. Also, this universal index approach is applicable in cases when a broader comprehensive set of indicators is analyzed, which provides a more accurate identification of weaker points and rank the countries in a more meaningful way.

Traffic fatality indicators in Brazil: State diagnosis based on data envelopment analysis research.

The intense economic growth experienced by Brazil in recent decades and its consequent explosive motorization process have evidenced an undesirable impact: the increasing and unbroken trend in traffic fatality numbers. In order to contribute to road safety diagnosis on a national level, this study presents a research into two main indicators available in Brazil: mortality rate (represented by fatalities per capita) and fatality rate (represented by two sub-indicators, i.e., fatalities per vehicle and fatalities per vehicle kilometer traveled). These indicators were aggregated into a composite indicator or index through a multiple layer data envelopment analysis (DEA) composite indicator model, which looks for the optimum combination of indicators' weights for each decision-making unit, in this case 27 Brazilian states. The index score represents the road safety performance, based on which a ranking of states can be made. Since such a model has never been applied for road safety evaluation in Brazil, its parameters were calibrated based on the experience of more consolidated European Union research in ranking its member countries using DEA techniques. Secondly, cluster analysis was conducted aiming to provide more realistic performance comparisons and, finally, the sensitivity of the results was measured through a bootstrapping method application. It can be concluded that by combining fatality indicators, defining clusters and applying bootstrapping procedures a trustworthy ranking can be created, which is valuable for nationwide road safety planning.

Drivers' behavioral responses to combined speed and red light cameras.

BACKGROUND: Numerous signalized intersections worldwide have been equipped with enforcement cameras in order to tackle red light running and often also to enforce speed limits. However, various impact evaluation studies of red light cameras (RLCs) showed an increase of rear-end collisions (up to 44%). OBJECTIVE: The principal objective of this study is to provide a better insight in possible explaining factors for the increase in rear-end collisions that is caused by placing combined speed and red light cameras (SRLCs). METHOD: Real-world observations and driving simulator-based observations are combined. Video recordings at two signalized intersections where SRLCs were about to be installed are used to analyze rear-end conflicts, interactions and driver behavior in two conditions (i.e., with and without SRLC). Furthermore, one of these intersections was rebuilt in a driving simulator equipped with an eye tracking system. At this location, two test conditions (i.e., SRLC and SRLC with a warning sign) and one control condition (i.e., no SRLC) are examined. The data of 63 participants were used to estimate the risk of rear-end collisions by means of a Monte Carlo Simulation. RESULTS: The results of the on-site observation study reveal decreases in the number of red and yellow light violations, a shift (i.e., closer to the stop line) in the dilemma zone and a time headway reduction after the installation of the SRLC. Based on the driving simulator data, the odds of rear-end collisions (compared to the control condition) for the conditions with SRLC and SRLC+warning sign is 6.42 and 4.01, respectively. CONCLUSION: The real-world and driving simulator observations indicate that the risk of rear-end collisions increases when SRLCs are installed. However, this risk might decrease when a warning sign is placed upstream.

Serious injuries: an additional indicator to fatalities for road safety benchmarking.

OBJECTIVES: Almost all of the current road safety benchmarking studies focus entirely on fatalities, which, however, represent only one measure of the magnitude of the road safety problem. The main objective of this article was to investigate the possibility of including the number of serious injuries in addition to the number of fatalities for road safety benchmarking and to further illuminate its impact on the countries' rankings. METHODS: We introduced the technique of data envelopment analysis (DEA) to the road safety domain and developed a DEA-based road safety model (DEA-RS) in this study. Moreover, we outlined different types of possible weight restrictions and adopted 2 of them to indicate the relationship between road fatalities and serious injuries for the sake of rational benchmarking. One was a relative weight restriction based on the information of their shadow price, and the other was a virtual weight restriction using a priori knowledge about the importance level of these 2 aspects. RESULTS: By computing the most optimal road safety risk scores of 10 European countries based on the different models, we found that United Kingdom was the only best-performing country no matter which model was utilized. However, countries such as The Netherlands, Sweden, and Switzerland were no longer best-performing when the serious injuries were integrated. On the contrary, Spain, which ranked almost at the bottom among all of the countries when only the number of road fatalities was considered, became a relatively well-performing country when integrating its number of serious injuries in the evaluation. In general, no matter whether the country's road safety ranking was improved or deteriorated, most of the countries achieved a higher risk score when the number of serious injuries was included, which implied that compared to the road fatalities, more policy attention has to be paid to improve the situation of serious injuries in most countries. CONCLUSIONS: Given the importance of considering the serious injuries in addition to the fatalities for international benchmarking of road safety, the proposed model (i.e., the DEA-RS model with weight restrictions) turned out to be effective in deriving reasonable results. We are thereby also inspired to apply this kind of model to a more complete road safety benchmarking practice in the future when the data on, for example, the number of slight injuries, the degree of property damage, and the number of crashes are ready (i.e., comparable) to use.

Automated section speed control on motorways: an evaluation of the effect on driving speed.

Automated section speed control is a fairly new traffic safety measure that is increasingly applied to enforce speed limits. The advantage of this enforcement system is the registration of the average speed at an entire section, which would lead to high speed limit compliances and subsequently to a reduction in the vehicle speed variability, increased headway, more homogenised traffic flow and increased traffic capacity. However, the number of studies that analysed these effects are limited. The present study evaluates the speed effect of two section speed control systems in Flanders, Belgium. Both sections are located in the opposite direction of a three-lane motorway with a posted speed limit of 120 km/h. Speed data were collected at different points: from 6 km before the entrance of the section to 6 km downstream from the section. The effect was analysed through a before- and after comparison of travel speeds. General time trends and fluctuations were controlled through the analysis of speeds at comparison locations. On the enforced sections considerable decreases were found of about 5.84 km/h in the average speed, 74% in the odds of drivers exceeding the speed limit and 86% in the odds of drivers exceeding the speed limit by more than 10%. At the locations up- and downstream from the section also favourable effects were found for the three outcomes. Furthermore a decrease in the speed variability could be observed at all these data points.

Behavioural effects of fixed speed cameras on motorways: overall improved speed compliance or kangaroo jumps?

The present study evaluates the speed effects of fixed speed cameras on motorways. Two locations with speed cameras were extensively examined in a quasi-experiment: (1) a two-lane motorway and (2) a three-lane motorway, each with a posted speed limit of 120 km/h and sited in Flanders, Belgium. The effect is analysed through a before-and-after comparison of travel speeds. General time trends and fluctuations were controlled through the analysis of the speeds at comparison locations. At each of the two roads, data were gathered at five measurement points from 3 km upstream to 3.8 km downstream of the camera. Three outcomes were analysed: (1) average speed, (2) the odds of drivers exceeding the speed limit and (3) the odds of drivers exceeding the speed limit by more than 10%. Speeds decreased on average by 6.4 km/h at the camera locations. Both the odds of drivers exceeding the speed limit (-80%) and the odds of drivers exceeding the speed limit by more than 10% (-86%) decreased considerably. However, before and beyond the cameras the speeds hardly, if at all, reduced. Moreover, the analyses of the speed profiles before and beyond the cameras show that drivers do slow down quite abruptly before the camera and speed up again after passing the camera. It is concluded that a V-profile is found in the spatial speed distribution for both locations.

To brake or to accelerate? Safety effects of combined speed and red light cameras.

INTRODUCTION: The present study evaluates the traffic safety effect of combined speed and red light cameras at 253 signalized intersections in Flanders, Belgium that were installed between 2002 and 2007. METHOD: The adopted approach is a before-and-after study with control for the trend. RESULTS: The analyses showed a non-significant increase of 5% in the number of injury crashes. An almost significant decrease of 14% was found for the more severe crashes. The number of rear-end crashes turned out to have increased significantly (+44%), whereas a non-significant decrease (-6%) was found in the number of side crashes. The decrease for the severe crashes was mainly attributable to the effect on side crashes, for which a significant decrease of 24% was found. PRACTICAL APPLICATIONS: It is concluded that combined speed and red light cameras have a favorable effect on traffic safety, in particular on severe crashes. However, future research should examine the circumstances of rear-end crashes and how this increase can be managed.

Latent risk and trend models for the evolution of annual fatality numbers in 30 European countries.

In this paper a unified methodology is presented for the modelling of the evolution of road safety in 30 European countries. For each country, annual data of the best available exposure indicator and of the number of fatalities were simultaneously analysed with the bivariate latent risk time series model. This model is based on the assumption that the amount of exposure and the number of fatalities are intrinsically related. It captures the dynamic evolution in the fatalities as the product of the dynamic evolution in two latent trends: the trend in the fatality risk and the trend in the exposure to that risk. Before applying the latent risk model to the different countries it was first investigated and tested whether the exposure indicator at hand and the fatalities in each country were in fact related at all. If they were, the latent risk model was applied to that country; if not, a univariate local linear trend model was applied to the fatalities series only, unless the latent risk time series model was found to yield better forecasts than the univariate local linear trend model. In either case, the temporal structure of the unobserved components of the optimal model was established, and structural breaks in the trends related to external events were identified and captured by adding intervention variables to the appropriate components of the model. As a final step, for each country the optimally modelled developments were projected into the future, thus yielding forecasts for the number of fatalities up to and including 2020.

Safety effects of an extensive black spot treatment programme in Flanders-Belgium.

Black spot management is a widely implemented measure to improve traffic safety. This study evaluates the safety effects of an extensive black spot programme that has been implemented in Flanders-Belgium. In total, around 800 black spots were selected, from which 134 locations, redesigned between 2004 and 2007, were included in this study. The adopted approach is an empirical Bayes before- and after study that accounts for effects of general trends and for the stochastic nature of crashes, including regression to the mean. Two different comparison groups were established. The analyses showed a decrease in the number of injury crashes of 24-27%, significant at the 1%-level. A separate analysis for crashes with serious or fatal injuries showed a decrease of 46-57%, also significant at the 1% level. The highest effects were found for the implementation of changes in the layout of priority controlled intersections and for the installation of traffic signals, which showed a decrease of respectively 42% and 35% in the number of injury crashes. Signalized intersections at which left-turn phasing was implemented resulted in a decrease of 22% in the number of injury crashes, changes in the layout leaded to a decrease of 11%. The conversion of intersections (both signalized and priority controlled) into roundabouts resulted in a decrease of 21% in injury crashes. The black spot programme generated a favourable effect on each of the road user categories (car occupants, moped riders, cyclists, motorcyclist, pedestrians and truck drivers).

Road safety development in Europe: a decade of changes (2001-2010).

To evaluate the road safety development of a country over time, the percentage change in the number of road fatalities is traditionally the main indicator. However, simply considering the reduction in the road fatalities may not correctly reflect the real improvement in road safety because the transport circumstances of a country underlying the road fatalities also change every year. In this study, we present a new way for measuring the road safety performance change over time, which is to use the technique of data envelopment analysis (DEA) and the Malmquist productivity index. In doing so, we can not only focus on the evolution of road safety final outcomes within a given period, but also take the changes of different measures of exposure in the same period into account. In the application, the DEA-based Malmquist productivity index (DEA-MI) is used to measure the extent to which the EU countries have improved their road safety performance over the period 2001-2010. More objective and insightful results are obtained compared to the ones based on the traditional indicator. The results show considerable road safety progress in most of the Member States during these ten years, and the fatality risk rather than the fatality number on Europe's roads has actually been reduced by approximately half. However, the situation differed considerably from country to country. The decomposition of the DEA-MI into 'efficiency change' and 'technical change' further reveals that the bulk of the improvement during the last decade was attained through the adoption of productivity-enhancing new technologies throughout the road transport sector in Europe, rather than through the relatively underperforming countries catching up with those best-performing ones.

Road safety risk evaluation and target setting using data envelopment analysis and its extensions.

Currently, comparison between countries in terms of their road safety performance is widely conducted in order to better understand one's own safety situation and to learn from those best-performing countries by indicating practical targets and formulating action programmes. In this respect, crash data such as the number of road fatalities and casualties are mostly investigated. However, the absolute numbers are not directly comparable between countries. Therefore, the concept of risk, which is defined as the ratio of road safety outcomes and some measure of exposure (e.g., the population size, the number of registered vehicles, or distance travelled), is often used in the context of benchmarking. Nevertheless, these risk indicators are not consistent in most cases. In other words, countries may have different evaluation results or ranking positions using different exposure information. In this study, data envelopment analysis (DEA) as a performance measurement technique is investigated to provide an overall perspective on a country's road safety situation, and further assess whether the road safety outcomes registered in a country correspond to the numbers that can be expected based on the level of exposure. In doing so, three model extensions are considered, which are the DEA based road safety model (DEA-RS), the cross-efficiency method, and the categorical DEA model. Using the measures of exposure to risk as the model's input and the number of road fatalities as output, an overall road safety efficiency score is computed for the 27 European Union (EU) countries based on the DEA-RS model, and the ranking of countries in accordance with their cross-efficiency scores is evaluated. Furthermore, after applying clustering analysis to group countries with inherent similarity in their practices, the categorical DEA-RS model is adopted to identify best-performing and underperforming countries in each cluster, as well as the reference sets or benchmarks for those underperforming ones. More importantly, the extent to which each reference set could be learned from is specified, and practical yet challenging targets are given for each underperforming country, which enables policymakers to recognize the gap with those best-performing countries and further develop their own road safety policy.

Benchmarking road safety: lessons to learn from a data envelopment analysis.

Road safety performance indicators (SPI) have recently been proposed as a useful instrument in comparing countries on the performance of different risk aspects of their road safety system. In this respect, SPIs should be actionable, i.e. they should provide clear directions for policymakers about what action is needed and which priorities should be set in order to improve a country's road safety level in the most efficient way. This paper aims at contributing to this issue by proposing a computational model based on data envelopment analysis (DEA). Based on the model output, the good and bad aspects of road safety are identified for each country. Moreover, targets and priorities for policy actions can be set. As our data set contains 21 European countries for which a separate, best possible model is constructed, a number of country-specific policy actions can be recommended. Conclusions are drawn regarding the following performance indicators: alcohol and drugs, speed, protective systems, vehicle, infrastructure and trauma management. For each country that performs relatively poor, a particular country will be assigned as a useful benchmark.

Combining road safety information in a performance index.

In this paper we focus on an essential step in the construction process of a composite road safety performance indicator: the assignment of weights to the individual indicators. In the composite indicator literature, this subject has been discussed for a long time, and no agreement has been reached so far. The aim of this research is to provide insights in the most important weighting methods: factor analysis, analytic hierarchy process, budget allocation, data envelopment analysis and equal weighting. We will give the essential theoretical considerations, apply the methods on road safety data from various countries and discuss their advantages and disadvantages. This will facilitate the selection of a justifiable method. It is shown that the position of a country in the ranking is influenced by the method used. The weighting methods agree more for countries with a relatively bad road safety performance. Of the five techniques, the weights based on data envelopment analysis resulted in the highest correlation with the road safety ranking of 21 European countries based on the number of traffic fatalities per million inhabitants. This method is valuable for the development of a road safety index.