The increasing complexity of autonomous driving from basic cruise control to full autonomous driving calls for an efficient testing framework. It is challenging to validate a complex ADAS system considering the diversity of traffic conditions such as road types, complex traffic, weather conditions. Recently, the ADAS industry has relied on scenario-based approach with a V&V-cycle for testing. This process however poses several challenges: 1: simulate realistic scenarios virtually that are beneficial for physical testing; 2: when transferring from virtual to physical scenario-based testing we still need do a great number of real tests. 

Today, The Simcenter Autonomy team presents an efficient ADAS scenario-based testing process, with focus on how to reconstruct and adapt virtual test cases via exploiting real logged vehicle sensors data (camera, lidar, GPS) over a sensor fused perception layer that helps to make the scenario more realistic and close the gap between virtual and real test cases.