Yearly Archives: 2022

In order to achieve scalability and robustness, verification and validation (V&V) of self-driving vehicle systems need to be largely performed virtually. This requires validated models on sensors, vehicles and environments where the systems are to operate. The aim of this pre-study is to identify state-of-the-art (SoA) and high-priority research questions within methods for validating models […]