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

2026-07-03

AI Summary

This work addresses the collision risks posed by occluded traffic participants in urban autonomous driving. The authors propose a formal occlusion-aware trajectory planning framework that, for the first time, unifies reachability reasoning under both future observability and complete non-observability within a single model. Integrated with a tree-based motion planner, the approach reduces the excessive conservatism of traditional methods while preserving formal safety guarantees. By explicitly modeling occlusion states and the evolution of observability, the framework enables proactive and efficient trajectory planning. Experimental results demonstrate that the method effectively avoids collisions and significantly improves traffic throughput in challenging simulated occlusion scenarios.

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 collision avoidance even when there are possible hidden traffic participants. Building on our previous methods that apply reachability analysis to sequentially determine the possible states of hidden traffic participants, we integrate a tree-based motion planner capable of reasoning over future observations and the absence thereof. This approach reduces conservativeness while maintaining safety guarantees. We demonstrate the effectiveness of our framework in a challenging simulated occluded scenario, showing that it pro-actively and efficiently guarantees collision-avoidance.

Problem

• occlusion
• autonomous vehicles
• safety
• motion planning
• collision avoidance

Innovation

• occlusion-aware planning
• reachability analysis
• contingency planning
• autonomous vehicles
• tree-based motion planner