Use Cases and Methods of Virtual ADAS/ADS Calibration in Simulation

Integration, testing, and release of complex Advanced Driver Assistance Systems (ADAS) Automated Driving (ADS) is one the main challenges in field automated driving. In order for systems to be accepted by customers compete market, they have feature functional, comfortable, safe, efficient, natural driving behavior. The calibration process acquires increasing importance achievement this objective. Complex ADAS/ADS require optimization interacting parameters a large number different scenarios—a task that can hardly performed with feasible effort cost using conventional methods. Virtual simulation enables reproducible testing data sets various scenarios. These capabilities facilitate use cases extend through virtual testing. This paper discusses methods achieve desired objectives. A special focus on multi-scenario-level method used iteratively calibrate optimal behavior variety scenarios, resulting more system still test cases. presented are implemented an Adaptive Cruise Control model evaluation.