High Throughput Vehicle Coordination Strategies at Road Intersections
Changhao Liu, Yixiao Zhang, Tingting Zhang, Xuanli Wu, Lin Gao, Qinyu Zhang
Abstract
In modern transportation systems, the road intersections where multiple roads merge usually become the traffic bottleneck. Existing coordination solutions such as the traffic signs tend to be ineffective. In order to exploit the full potential of the road infrastructure, we try to address the optimal vehicle coordination problem, by which the traffic throughput can be maximized. We first formulate it as a general centralized collision-free traffic scheduling framework. The involved vehicles could cooperate via instructions from the coordination center, by solving the essential non-convex coordination problem. Aiming at the dynamic arrival of vehicles, a corresponding coordination strategy is thus proposed to achieve better quality of service (QoS), including the traffic throughput, and delay. The queue stability on each road can be guaranteed according to the Rate Stability Theorem, and Lyapunov Theorem. We then try to extend the proposed intelligent coordination framework to the multi-collision-set one, by which the traffic throughput can be significantly improved. A spatial domain based solution is given to solve the multi-collision-set coordination problem. Due to the essential non-convex formulation, high accuracy linearization approximate algorithms are also provided. In the numerical results, we show the vehicle maneuvers, and statistical coordination time as the performance evaluation. They validate our analysis, and show the performance advantages achieved by the proposed framework.