Maneuver-based Resimulation of Driving Scenarios based on Real Driving Data


Development and testing of automated driving functions is complex and costly. Experts accord that it is necessary to cover most of the process by simulation. While tools and standards are evolving to satisfy this need, it is still challenging to generate appropriate driving scenarios for the simulation. In this paper we present a method for processing real driving data in order to generate maneuver-based scenarios for resimulation. We propose an automatic extraction of sequential, parametrized maneuvers - expressed in a high level format such as OpenSCENARIO. This enables to intuitively vary maneuver parameters and automatically generate whole sets of new discrete test scenarios, providing a link between simulation and real driving tests. The application of the method shows promising results in respect to the creation of meaningful scenarios with little loss in precision at reproducing the original driving tests.

2021 IEEE Intelligent Vehicles Symposium (IV)