Safety and Reliability: Validation for Automated Driving Functions through Scenario-Based Testing

This paper presents an infrastructure for defining scenarios and utilizing them to validate automated driving systems. It addresses various aspects of scenario-based testing, with a focus on lane keeping, lane changing, and traffic light scenarios. We define the scenarios using the OpenSCENARIO 2.0 format, as well as directly through Python scripts. These scenarios are integrated into two distinct simulators: an in-house simulator based on the Intelligent Driver Model (IDM), and the CARLA simulator. In these simulators, two agents are subjected to a range of challenging conditions, and the risk of failure is assessed. This evaluation provides insights into the agents' performance and their safety compliance, acting as a benchmark for safety assessment in the different scenarios.