Hope for the Best, Prepare for the Worst: Occlusion-Aware Contingency Planning for Autonomous Vehicles

arXiv:2607.03155v1 Announce Type: new Abstract: The deployment of autonomous vehicles in urban environments introduces significant safety challenges, particularly in scenarios with occlusions, where critical traffic participants may be hidden from view. Recent accidents involving driverless vehicles highlight the importance of motion planners that explicitly addresses the risks posed by occlusions. In this work, we propose a formal, occlusion-aware trajectory planning framework that guarantees c...