Share the Unseen: Sequential Reasoning About Occlusions Using Vehicle-to-Everything Technology

Abstract

Vehicle-to-everything (V2X) communication holds significant promise for augmenting autonomous driving capabilities. Particularly in dense traffic with occluded areas, V2X can be used to share information about the respective observed areas between traffic participants. In turn, reducing uncertainty about unseen areas can lead to less conservative behaviors while maintaining collision avoidance. This article aims to leverage V2X to improve situation awareness for trajectory planning. We particularly address two challenges. First, the ego vehicle may not always receive up-to-date information. Second, some areas may remain occluded despite receiving information from other participants. In this work, we fuse the received information about the detected free space. We use reachability analysis to compute areas that are guaranteed to be free despite being occluded. This way, we can maintain collision-avoidance guarantees. We demonstrate the benefits of our proposed method both in simulations and physical experiments.