Passing method at unsignalized intersections for intelligent vehicle

Traffic congestion and accidents are prone to occurring at multi-lane unsignalized intersections during high traffic flow, and it is a challenge to automated vehicle also. To improve safety and passage efficiency, a passing method for connected automated vehicle (CAV) at unsignalized intersections is proposed. The solution can be divided to two stages, passing sequence decision and token-based resource reservation. Firstly, a decision method based on the optimal model of multi-lane queue is proposed. CAVs are stored in queue models, and the cost function is established based on three indicators, traffic efficiency, vehicle waiting time and static right-of-way priority, to evaluate each queue. Then the passing sequences of vehicles at the intersection are optimized by selecting the best queue continuously. Finally, the conflict areas are associated with tokens, and the token is preempted by the head vehicle of best queue by resource reservation in advance to lead the queue to pass through the intersection. The simulation results show that the scheme can effectively improve the traffic efficiency at intersections and reduce vehicle waiting time and queue length at medium or high traffic flows. In addition, the proposed method is also applicable to non-autonomous vehicles by providing assisted decision-making information to drivers to pass the unsignalized intersections.