Using online verification to prevent autonomous vehicles from causing accidents

Abstract

Ensuring that autonomous vehicles do not cause accidents remains a challenge. We present a formal verification technique for guaranteeing legal safety in arbitrary urban traffic situations. Legal safety means that autonomous vehicles never cause accidents although other traffic participants are allowed to perform any behaviour in accordance with traffic rules. Our technique serves as a safety layer for existing motion planning frameworks that provide intended trajectories for autonomous vehicles. We verify whether intended trajectories comply with legal safety and provide fallback solutions in safety-critical situations. The benefits of our verification technique are demonstrated in critical urban scenarios, which have been recorded in real traffic. The autonomous vehicle executed only safe trajectories, even when using an intended trajectory planner that was not aware of other traffic participants. Our results indicate that our online verification technique can drastically reduce the number of traffic accidents. Recent accidents with autonomous test vehicles have eroded trust in such self-driving cars. A shift in approach is required to ensure autonomous vehicles can never be the cause of accidents. An online verification technique is presented that guarantees provably safe motions, including fallback solutions in safety-critical situations, for any intended trajectory calculated by the underlying motion planner.