Driving risk assessment with belief functions

Abstract

This paper describes a new strategy to assess a priori driving risk. The originality lies in the simultaneous consideration of the information related to the Vehicle, the Driver and the Environment (VDE). The heterogeneity and the imperfections of the information are taken into account thanks to the belief functions. A first fusion level determines the local risks related to the VDE entities, while their combination allows to determine the global a priori risk of the current driving situation. Both fusion levels are processed considering three combination rules to manage the eventual conflict. Comparative simulation results help to show the validity and the coherency of this multi-level risk assessment.