Automated Driving

Counterexample‑Guided Safety Contracts for Autonomous Driving

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TRI Authors: Jonathan DeCastro, Russ Tedrake

All Authors: J. DeCastro, L. Liebenwein, C.-I. Vasile, R. Tedrake, S. Karaman and D. Rus

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 framework 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 follow 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 gradientbased trajectory optimization problem. We treat these counterexamples as 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. Read More

Citation: DeCastro, Jonathan, Lucas Liebenwein, Cristian-Ioan Vasile, Russ Tedrake, Sertac Karaman, and Daniela Rus. "Counterexample-guided safety contracts for autonomous driving." In International Workshop on the Algorithmic Foundations of Robotics, 2018.

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