Control Parameter Optimization for Autonomous Vehicle Software Using Virtual Prototyping

Reliability and safety are important properties in the development of complex cyber-physical systems such as autonomous vehicles. Achieving a reliable autonomous vehicle is a challenging problem, as the unpredictability of the environment demands a reliable design methodology. Additionally, current testing procedures for ADAS features on vehicles are exhausting and time-consuming, so that a better way to do testing is required. In order to address these challenges, we propose a co-simulation tool-chain which integrates multiple simulation environments, optimizes the control parameters of autonomous vehicle software based on metrics, and visualizes the vehicle behavior using a video game engine.