Road Safety Performance Indicators: Theory. Deliverable D3.6 of the EU FP6 project SafetyNet.

This document provides details about the theory behind the development of Safety Performance Indicators (SPIs) in seven major areas which are central to the fields of activity in road safety in Europe. The fields of activity were selected as a result of reviews of national road safety plans in many of the EU countries and around the world and are considered the central themes of activity in road safety, necessary to bring about a significant improvement in road safety in the EU countries. Within each field SPIs were developed which are directly related to that field of activity, can be quantitatively measured, can provide the basis for the assessment of the level of road safety in each country and can serve as an indicator to describe the level of activity in that field and country and can provide a yardstick for comparison. Comparisons can be before and after certain actions are taken or can be comparisons between countries. As stated above, this document deals with the theory behind the development of each of the seven SPIs. It provides the rationale behind their development, the proofs for their relevance in the specific fields and the existing limitations that led to the adoption of the specific SPIs. The document provides also some recommendations for the possible improvements required to obtain better SPIs. Two companion documents are also being prepared. One is a manual which provides details on the procedures necessary to collects the required data for the development of each SPI in each country. The second document provides results on the data collected so far for each of the 25 EU countries and the SPIs developed so far, based on the data submitted by each of the countries. It can be seen that a lot of work still has to be done, both in collecting the necessary data and in improving the SPIs, once better and more detailed data becomes available

The Comparison between IHSDM and NSM to Assess the Safety Performance of Two-Lane Rural Roads

The objectives of this research were to explore ways to assess the safety performance of two-lane rural roads in NRW (North Rein Westphalia, Germany), and in particular to identify road factors affecting accidents on rural roads. Following a wide-ranging literature review, the Interactive Highway Safety Design Model (IHSDM) was identified as worthy of further investigation for its adaptation to use. Initial investigations showed that IHSDM is a promising tool for safety and operational assessment of two-lane rural roads in Germany. Incorporating crash history data generally improves IHSDM's accuracy in crash numbers, and appears to provide a better level of "local calibration". A number of tasks were identified and undertaken to adapt IHSDM for general use here, including calibrating the Crash Prediction Module (CPM), developing a Design Policy file based on local agency standards for use within the program, and developing an importing routine for the highway geometry and accident data. This research aims to present and illustrate a comprehensive road safety method: Network Safety Management (NSM). NSM, based on the German Guidelines for Safety Analysis of Road Networks ESN, describes a methodology for analyzing road networks from the traffic safety point of view. It also helps the road administrations in detecting those sections within the network with the highest safety potential, i.e. where an improvement of the infrastructure is expected to be highly cost efficient. Suitable measures can then be derived from a comprehensive analysis of the accidents. The safety potential and the calculated cost of the measure together form the basis for an economic assessment, which is usually conducted as a cost–benefit analysis. A systematic algorithm to assess traffic accident risk in the study area was developed in this study. The algorithm helps to identify factors that have significant influence on accidents, and to identify the road sections that have high risk of accidents. This algorithm provides both geographical and statistical analysis on accident events, i.e. mapping "Safety Analysis of Road Networks ESN" and statistical techniques "cluster analysis".Diese Forschungsarbeit hat als Ziel, die Sicherheitseffizienz zweispuriger Landstraßen in Deutschland (NRW) zu berechnen und insbesondere die Unfallfaktoren auf diesen Straßen zu ermitteln. Nach intensiver Literaturrecherche wurde festgestellt, dass das in den USA entwickelte Interactive Highway Safety Design Model (IHSDM) für weitere Untersuchungen genutzt werden kann. Die anfänglichen Untersuchungen haben ergeben, dass IHSDM ein vielversprechendes Sicherheits- und Bewertungsinstrument für zweispurige Landstraßen in Deutschland ist. Unfalldaten aus den Jahren zuvor zeigen, dass das IHSDM Informationen bereitstellt, die es erlauben, Maßnahmen zu benennen, um die Unfallzahlen zu verringern. Zudem bietet es vom Ansatz her eine gute Basis für die „Kalibrierung vor Ort“. Die Untersuchungen haben ergeben, dass das IHSDM für den allgemeinen Gebrauch in Deutschland angepasst werden muss. Vor allem müssen das Crash Prediction Module (CPM) kalibriert werden, eine Design-Policy-Datei basierend auf den lokalen Richtlinien entwickelt werden und eine Import-Routine für die Straßengeometrie und die Unfalldaten entwickelt werden. Das Ziel dieser Forschungsarbeit ist, einen Vergleich der IHSDM -Methode mit der Methode„Network Safety Management NSM“herzustellen. NSM ist eine Methode, die auf den deutschen Richtlinien für Sicherheitsanalysen von Straßennetzen ESN basiert. Sie analysiert Straßennetze, wobei die Verkehrssicherheit im Blickpunkt steht, und hilft dem Straßenverkehrsamt die Abschnitte mit dem höchsten Sicherheitspotenzial innerhalb des Netzes zu erfassen, beispielsweise wenn zu erwarten ist, dass eine Verbesserung der Infrastruktur in hohem Maße kosteneffizient ist. Allerdings liefert NSM nur indirekt Ansatzpunkte für eignete Maßnahmen, die aus den umfassenden Analysen der Unfälle abgeleitet werden müssen. Somit bietet es sich an, ein an deutsche Verhältnisse angepasstes IHSDM für die Untersuchung von Unfällen und die Entwicklung von Reduktionsstrategien einzusetzen. In der vorliegenden Studie wurden beide Methoden ein systematischer Algorithmus zur Feststellung des Unfallrisikos im Untersuchungsgebiet entwickelt. Der Algorithmus hilft, ausschlaggebende Unfallfaktoren und Streckenabschnitte, die eine hohe Unfallgefahr besitzen, zu identifizieren. Er bietet sowohl geographische als auch statistische Analysen zu Unfallereignissen, wie zum Beispiel einer Kartierung der "Sicherheitsanalyse von Straßennetzen ESN" sowie statistischer Methoden wie der "Clusteranalyse"

Doctor of Philosophy

dissertationObservational studies are a frequently used "tool" in the field of road safety research because random assignments of safety treatments are not feasible or ethical. Data and modeling issues and challenges often plague observational road safety studies, and impact study results. The objective of this research was to explore a selected number of current data and modeling limitations in observational road safety studies and identify possible solutions. Three limitations were addressed in this research: (1) a majority of statistical road safety models use average annual daily traffic (AADT) to represent traffic volume and do not explicitly capture differences in traffic volume patterns throughout the day, even though crash risk is known to change by time of day, (2) statistical road safety models that use AADT on the "right-hand side" of the model equation do not explicitly account for the fact that these values for AADT are estimates with estimation errors, leading to potential bias in model estimation results, and (3) the current state-of-the-practice in road safety research often involves "starting over" with each study, choosing a model functional form based on the data fit, and letting the estimation results drive interpretations, without fully utilizing previous study results. These limitations were addressed by: (1) estimating the daily traffic patterns (by time of day) using geo-spatial interpolation methods, (2) accounting for measurement error in AADT estimates using measurement error models of expected crash frequency, and (3) incorporating prior knowledge on the safety effects of explanatory variables into regression models of expected crash frequency through informative priors in a Bayesian methodological framework. These alternative approaches to address the selected observational road safety study limitations were evaluated using data from rural, two-lane highways in the states of Utah and Washington. The datasets consisted of horizontal curve segments, for which crash data, roadway geometric features, operational characteristics, roadside features, and weather data were obtained. The results show that the methodological approaches developed in this research will allow road safety researchers and practitioners to accurately evaluate the expected road safety effects. These methods can further be used to increase the accuracy and repeatability of study results, and ultimately expand the current practice of evaluating regression models of expected crash frequency in observational road safety studies

Accident causation and pre-accidental driving situations: Part 1. Overview and general statistics

WP2 of the European Project TRACE is concerned with “Types of Situations” to analyse the causation of road traffic accidents from the pre-accidental driving situation point of view. Four complementary situations were defined: stabilized situations, intersection, specific manoeuvre and degradation scenario. To reach this objective, the analysis is based on a common methodology composed on 3 steps: the “descriptive analysis” which from general statistics will allow to identify among the studied situations those them relevant and to give their characteristics, the “in-depth analysis” allowing to obtain accident causes from the generic description of the problems identified in the previous step and the risk analysis identifying the risk of being involved in an accident taking into account the results obtained from the ‘in–depth’ level. This report is dedicated to the descriptive analysis with the identification of the most relevant scenario regarding the situation in which the driver is involved just prior the accident. The results are based on the literature review, general statistics and the analysis of the national databases available in TRACE via WP8. Because the information level differ from databases to another, the available scenario presented here for the 4 predefined types of situations are generics and some specific situations could not have be distinguished. For each situation some key indicators are given, such as prevalence, severity, KSI (killed x severely injured), etc. When it is possible, these indicators are estimated at the EU27 level

Intelligent Transportation Related Complex Systems and Sensors

Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITS) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include: road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas. The efficient operation of these complex systems requires: i) efficient solutions to the issues of sensors/actuators used to capture and control the physical parameters of these systems, as well as the quality of data collected from these systems; ii) tackling complexities using simulations and analytical modelling techniques; and iii) applying optimization techniques to improve the performance of these systems. It includes twenty-four papers, which cover scientific concepts, frameworks, architectures and various other ideas on analytics, trends and applications of transportation-related data

5th International Probabilistic Workshop: 28-29 November 2007, Ghent, Belgium

These are the proceedings of the 5th International Probabilistic Workshop. Even though the 5th anniversary of a conference might not be of such importance, it is quite interesting to note the development of this probabilistic conference. Originally, the series started as the 1st and 2nd Dresdner Probabilistic Symposium, which were launched to present research and applications mainly dealt with at Dresden University of Technology. Since then, the conference has grown to an internationally recognised conference dealing with research on and applications of probabilistic techniques, mainly in the field of structural engineering. Other topics have also been dealt with such as ship safety and natural hazards. Whereas the first conferences in Dresden included about 12 presentations each, the conference in Ghent has attracted nearly 30 presentations. Moving from Dresden to Vienna (University of Natural Resources and Applied Life Sciences) to Berlin (Federal Institute for Material Research and Testing) and then finally to Ghent, the conference has constantly evolved towards a truly international level. This can be seen by the language used. The first two conferences were entirely in the German language. During the conference in Berlin however, the change from the German to English language was especially apparent as some presentations were conducted in German and others in English. Now in Ghent all papers will be presented in English. Participants now, not only come from Europe, but also from other continents. Although the conference will move back to Germany again next year (2008) in Darmstadt, the international concept will remain, since so much work in the field of probabilistic safety evaluations is carried out internationally. In two years (2009) the conference will move to Delft, The Netherlands and probably in 2010 the conference will be held in Szczecin, Poland. Coming back to the present: the editors wish all participants a successful conference in Ghent

Determination and measurement of factors which influence propensity to cycle to work

2.89% of the UK population cycled for the journey to work as measured by the census in 200I. This percentage is similar to the percentage from the 1991 census and indicates a levelling off in the decline that had been seen in the previous two decades in bicycle use for the journey to work, but does not demonstrate any increase in line with policy aspirations. Choice is a complex issue and related to a wide range of factors including socio-economic variables and the nature of transport infrastructure and the physical geography of an area. As well as the rational and measurable factors, there are many much more complex and subtle factors including the influences of culture and social norms. Changes to behaviour probably take an extended period of time and require a range Qf conditions to be appropriate before a positive choice can be made. Waldman (1977) undertook the last countrywide aggregate study of the variation in use of the bicycle for the journey to work, but a number of the variables he constructed were measured inappropriately, not the least of which was his measure for "danger", which he recommended for further study. It is widely considered that perception of risk from motor traffic is a reason why many people do not currently use the bicycle. This is only one measurable attribute and European bicycle planners consider network coherence, directness, attractiveness and comfort as other equally important issues when designing schemes to promote bicycle use. This research has used primary data collected on perceptions of risk. The particular contribution of the research is in the development of a methodology for the determination of perception of risk for a whole journey, including routes and junctions, and the extension of this methodology to create a measure for risk at an area wide level. Measures that have been found to be significant in relation to the use of the bicycle for the journey to work are car ownership, socio-economic classification, ethnicity, distance to work, condition of the highway pavement, highway network density and population density, hi lIiness, rainfall and mean temperature. In addition the length of bicycle lane, length of bus lane and length of traffic free route have also been found to be important in so far as it influences the perception of risk, which in turn influences the level of bicycle use. The length of route that is signed has also been found to be important. In a sample of four districts for which appropriate data is available, a seven fold increase in route length with cycle facilities, or signed route, would create conditions suitable for an increase in cycle use for the journey to work by a factor of the order of two. An elimination of highways with negative residual life would create conditions suitable for an increase of 10% in the number of bicycle trips for the journey to work

Investigating safety performance of the SAFESTAR system for route-based curve treatment

In order to improve curve safety, warning signs are used to alert drivers to unexpected changes in horizontal alignment and speed variations. While all countries have standards and guidelines for signs, markings and delineations to ensure a uniform system, they do not use them in the same way and choices and combinations may differ. SAFESTAR project promoted a method for establishing uniform curve signs on two lane rural roads to force drivers to adjust their speed to the actual risk. Although widely applied around the world and producing speed reduction benefits, as evidenced in the literature, the reliability in terms of statistical safety significance of the method has not been well established. The goal of this paper is to assess the safety fundamentals of SAFESTAR's risk ranking system and safety performance of the proposed signing schemes. Crash data and road characteristics from two Polish regions are used to carry out sound statistical analysis. Building on data from treated and untreated sites, the analysis first looks at relative changes in Crash Rates for different risk categories. Next, Crash Modification Factors are estimated. Results are interesting and suggest that system needs revision, both in terms of risk classification and on how treatments are implemented