Pushing ROS towards the Dark Side: A ROS-based Co-Simulation Architecture for Mixed-Reality Test Systems for Autonomous Vehicles

Abstract

Validation and verification of autonomous vehicles is still an unsolved problem. Although virtual approaches promise a cost efficient and reproducible solution, a most comprehensive and realistic representation of the real world traffic domain is required in order to make valuable statements about the performance of a highly automated driving (HAD) function. Models from different domain experts offer a repository of such representations. However, these models must be linked together for an extensive and uniform mapping of real world traffic domain for HAD performance assessment.Hereby, we propose the concept of a co-simulation architecture built upon the Robot Operating System (ROS) for both coupling and for integration of different domain expert models, immersion and stimulation of real pedestrians as well as AD systems into a common test system. This enables a unified way of generating ground truth for the performance assessment of multi-sensorial AD systems. We demonstrate the applicability of the ROS powered co-simulation by coupling behavior models in our mixed reality environment.