基于车速与信号协同优化的区域绿波协调控制模型

针对车路协同环境下的区域绿波协调控制问题，根据自动驾驶车辆车速可控的特点，提出利用绿波车速与信号配时的协同优化方法，建立一种区域绿波协调控制模型。模型在信号配时与相位相序优化的基础上，增加对路段绿波车速的优化，为车路协同环境下的自动驾驶车辆提供路段车速引导方案；通过扩大优化模型的可行解空间，以解决区域协调中相位差的设计问题；选取绿波带宽折减率与通行速度折减率的加权量作为模型评价指标，使得设计方案能够实现绿波带宽与通行速度的综合最优。算例结果分析表明：模型可以根据不同的绿波带宽权重系数，求解相应的绿波带宽与通行速度综合最优协调控制方案，其中绿波带宽最优方案的路网绿波带宽占比均值能够达到95%，明显优于TRANSYT模型的绿波协调优化效果。VISSIM仿真结果显示，与TRANSYT优化方案相比，所提模型方案能够减少干道平均停车次数39%，缩短交叉口平均延误时间10%，使区域交叉口的通行效率得到进一步提升。

Regional Green Wave Coordinated Control Model Based on Cooperative Optimization of Vehicle Speed and Traffic Signal

To solve the regional green wave coordinated control problem in a vehicle infrastructure cooperative environment, this paper proposes a cooperative optimization method for the green wave speed and signal timing according to the controllable characteristics of autonomous vehicle speed. A regional green wave coordinated control model was established. Based on the optimization of the signal timing and phase sequence, this model incorporates the optimization of the green wave speed, thus providing speed guidance strategies for autonomous vehicles traveling in vehicle infrastructure cooperative environment. Simultaneously, it also expands the feasible solution space and solves the problem of the offset design in regional coordinated control. The reduction rate of the green wave bandwidth and that of the green wave speed are used as model evaluation indicators, such that the design scheme can achieve a comprehensive optimization of the green wave bandwidth and speed. The experimental results indicate that this model can derive the corresponding optimal scheme by considering the comprehensive optimization of vehicle speed and bandwidth under different green wave bandwidth weights. The average proportion of the green wave bandwidth of the scheme optimized via this model can reach 95%, which is clearly better than the green wave coordination optimization effect of the TRANSYT model. Furthermore, VISSIM simulation results indicate that, compared with the TRANSYT model, this model reduces the average number of stops on the artery by 39%, shortens the average delay time at the intersection by 10%, and further improves the traffic efficiency of the regional intersection.