Safety performance assessment of assisted and automated driving in traffic: Simulation as knowledge synthesis

Abstract

Advanced driver assistance and automated driving can influence traffic safety in a variety of ways. The development and implementation of safety-relevant functions require prospective, quantitative assessment of their traffic safety impacts. Both benefits and risks can be quantified using simulation-based virtual experimental techniques. To this end, traffic phenomena are modeled taking into account key safety-relevant processes; “stochastic�? simulation is performed on large, representative virtual samples. The virtual representations of traffic phenomena are based on detailed, stochastic models of drivers, vehicles, traffic flow, and the road environment, together with their interactions. The models incorporate knowledge from field operational test (FOT), naturalistic driving studies (NDS), laboratory and driving simulator experiments, and other sources. Simulation serves to synthesize this knowledge. Large-scale, comprehensive simulations could help in identifying and evaluating the relevant situations in which automated driving impacts traffic safety. One key objective is a standardized harmonized methodology, agreed upon by all stakeholders, for comprehensive assessment of the impact of new driver assistance or automated driving functions on traffic safety.