Self-driving Car Safety through Accurate Sensor Simulation and Scenario-Based Validation at Scale
The primary engineering challenge in developing ADAS and Autonomous Vehicles is ensuring that they will operate safely under all situations. Since vehicles are likely to encounter millions of different driving situations throughout their operational life, engineering of ADAS and AVs must comprehensively address the design and validation of their software and hardware components to cover the entire spectrum of driving scenarios. A Model-based systems engineering is a methodology that focuses on creating, maintaining, and exploiting models as the primary means of systems analysis and engineering collaboration between different disciplines. This presentation demonstrates Ansys commitment to safety as we apply these principles to the triumvirate of a) safety by design b) safety by verification & validation and c) the delivery of incremental safety cases by combining simulation with analysis and scenario at scale for L3 autonomous functions. We will also introduce customer use cases which illustrate proven applications of our approach to help bring safe and reliable L3 functions to market.
In this talk, you will learn how to:
Reduce field operation testing by using physics-based sensor simulation from early design stages up to V&V activities at xIL validation of ADAS/AD Systems.
Generate synthetic sensor data for Machine Learning as well as for testing.
Connect safety by design and safety by V&V to drive the incremental safety case.