新型混合交通交叉口信号与车辆轨迹协同控制方法

新型混合交通环境下的交叉口交通控制可通过信号灯控制与自动驾驶车辆的轨迹控制协同实现，能够极大地优化道路通行资源利用效率。已有研究中，信号配时与车辆轨迹集中优化的控制策略难以应用于车辆自组织控制的现实场景，且往往计算复杂度较高。本文提出一种无中心框架下基于逻辑的交叉口信号与车辆轨迹协同控制方法。基于协同理论中的快慢变量主动伺服控制原理，设计一种交叉口信号配时慢变量与车辆轨迹策略快变量协同框架，并分别提出基于逻辑的信号配时优化和网联自动驾驶车辆轨迹协同控制方法。协同控制方法可以在车辆自主控制的条件下，一方面，实现交叉口信号配时动态适应交通需求；另一方面，实现网联自动驾驶车辆主动优化驾驶速度，高效通过交叉口。而且网联自动驾驶车辆在进口道可引导混合车队高效通过交叉口，降低绿灯启动损失，提高交叉口通行效率。仿真实验表明，本文的协同控制方法相较于传统控制方法可显著降低交叉口车辆平均延误，同时，基于逻辑的决策模型可实现快速求解。通过对网联自动驾驶车辆控制策略关键参数的敏感性分析，进一步讨论新型混合交通流交叉口通行公平性，并比较在不同网联自动驾驶车辆渗透率下的控制效果。

Coordination of Signal and Vehicle Trajectory atIntersections for Mixed Traffic Flow

The intersection traffic control under the mixed traffic environment can be realized by the coordination of thesignal control and the trajectory control of automated vehicles, which can greatly improve the utilization efficiency ofroad traffic resources. The centralized control strategies in previous studies with the integrated optimization of signaltiming and vehicle trajectory are difficult to be applied to the real operations with self-organized vehicles, and oftenhave high computational complexity. In this paper, a logic-based coordinated control of the signal and vehicle trajectoryis proposed within a decentralized framework. Based on the active servo control principle of fast and slow variables inthe coordination theory, a coordination framework of the slow variables of intersection signal timing and the fastvariables of vehicle trajectory strategy is designed. A logic-based signal timing optimization method and a speedcontrol method are proposed for the connected and automated vehicles (CAV). The signal timing at the intersection canadapt to traffic demand dynamically, and the CAVs can optimize their speed strategy based on the prediction of thetraffic states to pass the intersection efficiently and smoothly. Based on the reasonable speed control of the leadingvehicle in the approach lanes during the green signal, the "leading effect" of the CAV can be utilized to avoid start-uploss and make the platoon pass the intersection efficiently. The simulation results show that the proposed cooperatedcontrol method can significantly reduce the average vehicle delay at intersections compared with the traditional controlmethods, and the logic-based decision making model can be solved efficiently. Based on the sensitivity analysis of thekey parameters of the control strategy for the CAV, the fairness of the mixed traffic flow at intersection is further discussed, and the effectiveness of the control methods are compared for the mixed traffic with different penetrationrates of CAVs.