Distributed Conflict Resolution for Connected Autonomous Vehicles

This paper proposes a novel communication-enabled distributed conflict resolution mechanism in order for a group of connected autonomous vehicles to navigate safely and efficiently in intersections without any traffic manager. The conflict resolution strategy for individual vehicle is decoupled temporally. In a decision maker, the vehicle computes the desired time slots to pass the conflict zones by solving a conflict graph locally based on the broadcasted information from other vehicles. In a motion planner, the vehicle computes the desired speed profile by solving a temporal optimization problem constrained in the desired time slot. The estimated time to occupy the conflict zones given the new speed profile is then broadcasted again. It is proved that the aggregation of these local decisions solves the conflicts globally. Theoretically, this method provides an efficient parallel mechanism to obtain local optimal solutions of a large-scale optimization problem (e.g., multivehicle navigation). Application-wise, as demonstrated by extensive simulation, this mechanism increases the efficiency of autonomous vehicles in terms of smaller delay time, as well as the efficiency of the traffic in terms of larger throughput when there is no traffic manager to mediate the conflicts.