Occlusion-Aware Motion Planning at Roundabouts

In this work, we present a motion planning framework for automated vehicles to drive safely through intersections despite occlusions and the uncertain behavior of the surrounding vehicles. A context representation based on probably-free gaps is proposed as a means to provide, in occluded scenes, richer information to the motion planner compared to representations only based on observed objects. Our solution builds upon the path-velocity decomposition approach. Path planning is performed with state-of-the-art techniques, while a novel trajectory abstraction is used to reason about speed profiles without explicitly generating sequences of accelerations. To efficiently identify the best safe speed profile for every path candidate, a reachability-based analysis is also formulated. The proposed planning workflow is evaluated in roundabout scenarios. Our simulation study shows that the proposed context representation facilitates the decision-making in occluded scenes and that the reachability-based planning strategy is robust, computationally efficient, and outperforms a simpler reactive strategy.