Towards Safe Autonomous Driving: Model Checking a Behavior Planner during Development

Abstract

AbstractAutomated driving functions are among the most critical software components to develop. Before deployment in series vehicles, it has to be shown that the functions drive safely and in compliance with traffic rules. Despite the coverage that can be reached with very large amounts of test drives, corner cases remain possible. Furthermore, the development is subject to time-to-delivery constraints due to the highly competitive market, and potential logical errors must be found as early as possible. We describe an approach to improve the development of an actual industrial behavior planner for the Automated Driving Alliance between Bosch and Cariad. The original process landscape for verification and validation is extended with model checking techniques. The idea is to integrate automated extraction mechanisms that, starting from the C++ code of the planner, generate a higher-level model of the underlying logic. This model, composed in closed loop with expressive environment descriptions, can be exhaustively analyzed with model checking. This results, in case of violations, in traces that can be re-executed in system simulators to guide the search for errors. The approach was exemplarily deployed in series development, and successfully found relevant issues in intermediate versions of the planner at development time.