Set-based Scheduling for Highway Entry of Autonomous Vehicles

Abstract This paper proposes a framework for generation of collision-free reference trajectories in a cooperative multi-agent setting. The approach is hierarchical: a high-level controller schedules groups of cooperating agents, for which trajectories are then determined by a lower-level trajectory planner. Admissible behaviors of a cooperative group are encoded by so-called maneuvers, which are modeled by hybrid automata. This allows to plan trajectories by solving hybrid optimal control problems. Controllable sets characterize the solution sets of these problems and are used for quick assessment of feasibility prior to planning. This enables the high-level controller to quickly assess the feasibility of different maneuver options and cooperative groups. Special emphasis is put on safety and feasibility of the framework. The efficacy of the approach is demonstrated by simulation of a highway entry scenario for autonomous vehicles.