Since January 2011, it is possible to link data of the Road Traffic Accident Register (VU) with other registers of the Swiss Federal Roads Office (FEDRO) and with data from various other sources. This newly created pool of data allows detailed analysis of various factors on accident rates. The according research package “road safety gains resulting from datapooling and structured data analysis" (VeSPA) comprises six sub-projects (TP). The scientific sub-projects examine in two phases impacts of persons/society, situation/infrastructure, vehicle, weather, and medical consequences. The objective of this research project in the research package VeSPA is to combine the factors on an aggregated level of the road network that affect accident events and to detect interactions among those effects in order to identify countermeasures for road administrations. Sub-project TP1-M will focus on influence factors or rather countermeasures regarding road infrastructure at network level. Accident prediction models will be validated, adjusted and newly developed aimed at describing measures for safety improvement. In cooperation with the works in the sub-project TP1-M influence factors regarding road users, vehicles and weather are also considered. Countermeasures are derived based on the results from the models. Countermeasure effects are estimated as well. Relevant results will be prepared for practical applications, advices are given for design standards and there will be an outlook on future applications regarding the models and the countermeasures for improving road safety.
The main objective of this research project is the specification of accident prediction models with focus on identifying and assessing countermeasures. An explanatory model is set up first that contains factors on road infrastructure and connects them to other influences like individuals, vehicles and weather. Secondly empirical models are built and validated as a base for a multilevel model that combines the different influence dimensions. Final objective is the identification of countermeasures as well as the evaluation of their effectiveness.