A Process for Scenario Prioritization and Selection in Simulation-Based Safety Testing of Automated Driving Systems

Simulation-based safety testing of Automated Driving Systems (ADS) is a cost-effective and safe alternative to field tests. However, it is practically impossible to test every scenario using a simulator. We propose a process for prioritizing and selecting scenarios from an existing list of scenarios. The aim is to refine the scope of tested scenarios and focus on the most representative and critical ones for evaluating ADS safety. As a proof-of-concept, we apply our process to two pre-existing scenario catalogs provided by the Land Transport Authority of Singapore and the Department of Transportation. After applying our process, we prioritized and selected six scenario groups containing 51 scenarios for testing ADS in the CARLA simulator.