Thierry Hermitte

The European road safety decision support system on risks and measures

The European Road Safety Decision Support System (roadsafety-dss.eu) is an innovative system providing the available evidence on a broad range of road risks and possible countermeasures. This paper describes the scientific basis of the DSS. The structure underlying the DSS consists of (1) a taxonomy identifying risk factors and measures and linking them to each other, (2) a repository of studies, and (3) synopses summarizing the effects estimated in the literature for each risk factor and measure, and (4) an economic efficiency evaluation instrument (E3-calculator). The DSS is implemented in a modern web-based tool with a highly ergonomic interface, allowing users to get a quick overview or go deeper into the results of single studies according to their own needs.

Analyzing the Maximum Abbreviated Injury Scale in Vehicle Crashes by Using a Logistic Normal Model

This paper presents a model centered on the estimation of the maximum abbreviated injury scale–based injury predicting models by using a logistic normal model with random effects. The study identified energy equivalent speed, collision type, crash year, location, drivers age, and gender for the analysis of the gravity in vehicle crashes. The study showed that the collision type variable was modeled better by random effects than by fixed effects and that energy equivalent speed, crash year, location, drivers age, and gender were contributing factors with fixed effects to the injury severity. Therefore, the authors took advantage of the mixed logit models ability to account for unobserved effects that are difficult to quantify and may affect the model estimation. Crashes from the database of detailed studies of personal accidents occurring from 1991 to 2010 in France were used. The estimation of the parameters (fixed and random effects) was performed by several approximation methods. Energy equivalent speed was found to be, by far, the most significant variable. If drivers age 75 and older were considered as a reference, drivers in the 25-to-34 age bracket were significant contributors and were followed by those in the 35-to-44 age bracket and then by those in the 55-to-65 age bracket. In addition, vehicles that crashed between 1995 and 1999 were more significant contributors than were those in the reference period, 1991 to 1994. For assessment of the performance of the model proposed, a binary logit model was compared with the mixed logit by means of cross validation. The obtained results revealed that the logistic normal mixed model is preferred because it detects more vehicle crashes with serious injuries than does the classic logistic regression model.

New Challenges in Road Safety Evaluation: Towards the Development of an Evolutionary Framework

As road safety issues become increasingly complex and involve various stakeholders, designing of safety actions as on-board vehicle safety systems or public policy measures needs knowledge that describes the performance level to fulfil the objectives. Performance is assessed by evaluating designed actions as regards their functional specifications. By its ability to create new knowledge, evaluation is also used to improve existing actions or to specify road safety strategies. However, given the complexity of the evaluation activity and its context, experts consider that the existing knowledge is insufficient. One considers that this situation reflects the lack of a theoretical framework. In particular, there is no way to identify emerging assessment issues due to the insertion of new safety systems and the emergence of new users’ behaviours. In this paper, we introduce a framework that describes the design of the evaluation methods in the field of road safety. It is used as a guide to build new evaluation models for specific stakeholders and viewpoints. This framework is based on the identification of the objectives to be achieved and the use of the evaluators’ expertise.Copyright