Intelligent Co-Simulation Framework for Cooperative Driving Functions

Cooperative driving, a technology domain that allows for autonomous as well as manually driven vehicles to cooperatively coordinate their maneuvers with the aid of inter-vehicular communication, represents nowadays a highly active scientific topic for numerous research projects, notably such as German funded project IMAGinE. In the development process of the corresponding cooperative driving functions, a big challenge is posed by their extensive and complex testing as well as verification and validation procedures, which is reasoned by the vast amount of relevant scenarios needed to consider, even when using modern simulation-based methods. In the work at hand, we introduce our novel co-simulation framework, involving a coupling of traffic flow simulation with vehicle dynamics simulation, as well as an integrated machine learning classification module, which is able to detect, generate and evaluate test scenes and scenarios. As a result, with our approach, we achieve an intelligent way to test and to evaluate the cooperative driving functions practically solely on relevant test scenarios, organized in a systematical workflow with reasonable effort.