Monitoring road safety constitutes, due to the social and economical consequences of the accidents, one of the fundamental goals of any traffic management policy. The achievement of such a goal depends on the availability of reliable data collection procedures. Good quality data will in fact allow the extraction of knowledge useful to evaluate the consequences and the potential side effects of any decision aimed at improving safety practices. The authors present here the first result of a project aimed at enhancing data quantity and quality, shortening collection time, minimizing traffic disruption, and increasing efficiency during crash data collection. An important milestone in such a project is the development of an adaptive Accident Reporting System (ARS), which relies on artificial intelligence technology, supplied through a Decision Support System component, and on a cognitively-grounded information design to provide a user-friendly and helpful data collection environment. The ARS approach to the improvement of road accident data collection is based on the joint adoption of linkage procedures and computer-mediated data collection strategies (via the ARS software).
Samenvatting