关键词: 网联交通, 交通分流, 车辆轨迹与信号配时联合优化, 交通事件

Abstract:

The existing signal control methods for traffic incidents do not consider the impact of traffic flow redistribution caused by the adjustment of the current intersection control scheme on adjacent intersections, and the essence is only to transfer the traffic problem, which is not conducive to the evacuation of congestion. In view of this, based on the textability of connected traffic, the controllability of connected automated vehicles, and the inducibility of connected human-driven vehicles, aiming to solve the congestion problems caused by traffic incidents, a signal control method for adaptive traffic events - SCM-ATE (Signal control method of adaptive traffic events) is proposed. Based on identifying lanes and traffic volume blocked by traffic incidents, as well as surplus capacity at adjacent intersections, SCM-ATE employs the shortest-path algorithm to plan detour routes for obstructed traffic flows. Aiming to minimize the average vehicle delay at all intersections along these detour routes, the system adopts dynamic programming to jointly optimize traffic signal timings and the trajectories of connected vehicles. This coordinated approach mitigates the adverse impacts of traffic incidents. The simulation results show that the average delay per vehicle of SCM-ATE under low, medium, and high traffic loads decreased by 14.4%, 25.5%, and 5.6%, respectively, compared to traditional signal control method; and the average delay was reduced by 15.3%,11.6% and 1.27%, respectively, compared to a single-layer approach for joint optimization of traffic signals and cooperative vehicle trajectories at isolated intersections,(JOTS-CVT), confirming the effectiveness of SCM-ATE. Further research shows that intersection traffic load and the penetration rate of connected and automated vehicle have a significant impact on the optimization effect of SCM-ATE. SCM-ATE is demonstrated that the optimal performance in traffic environments where the penetration rate of connected and automated vehicle is more than 0.3 and the intersection volume-to-capacity ratio is less than 0.7.

Key words: connected traffic, traffic diversion, joint optimization of vehicle trajectory and signal timing, traffic incident