Simulations are of considerable importance for the quantitative testing and validation of future automated driving functions. However, to reliably replace real test drives in public transport, a well-founded virtual representation of real traffic, and in particular its risk factors, is required.
The AVEAS project developed scalable and sustainable methods for the dedicated acquisition of critical situations in public traffic, and converting them into models for scenario generation and simulation. In order to draw founded conclusions about the safety of future driving functions in mixed traffic consisting of automated and human road users from data that can be collected today, AVEAS focuses on three situational risk aspects:













































