Counterexample-Guided Safety Contracts for Autonomous Driving
Author(s)
DeCastro, Jonathan; Liebenwein, Lucas; Vasile, Cristian-Ioan; Tedrake, Russell L; Karaman, Sertac; Rus, Daniela L; ... Show more Show less
DownloadMain article (1.181Mb)
Open Access Policy
Open Access Policy
Creative Commons Attribution-Noncommercial-Share Alike
Terms of use
Metadata
Show full item recordAbstract
Ensuring the safety of autonomous vehicles is paramount for their successful deployment. However, formally verifying autonomous driving decisions systems is difficult. In this paper, we propose a frame-work for constructing a set of safety contracts that serve as design requirements for controller synthesis for a given scenario. The contracts guarantee that the controlled system will remain safe with respect to probabilistic models of traffic behavior, and, furthermore, that it will fol-low rules of the road. We create contracts using an iterative approach that alternates between falsification and reachable set computation. Counterexamples to collision-free behavior are found by solving a gradient-based trajectory optimization problem. We treat these counter examplesas obstacles in a reach-avoid problem that quantifies the set of behaviors an ego vehicle can make while avoiding the counterexample. Contracts are then derived directly from the reachable set. We demonstrate that the resulting design requirements are able to separate safe from unsafe behaviors in an interacting multi-car traffic scenario, and further illustrate their utility in analyzing the safety impact of relaxing traffic rules. Keyword: Logic and Verification; Collision Avoidance; Falsification; Rules of the Road
Date issued
2018-12Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Department of Aeronautics and AstronauticsJournal
Proceedings of the 13th Workshop on the Algorithmic Foundations of Robotics
Citation
De Castro, Jonathan et al. "Counterexample-Guided Safety Contracts for Autonomous Driving." The 13th International Workshop on the Algorithmic Foundations of Robotics, December 2018, Merida, Mexico.
Version: Author's final manuscript
Collections
The following license files are associated with this item: