This study develops a novel mixed-integer non-linear program to control the trajectory of mixed connected-automated vehicles (CAVs) and connected human-driven vehicles (CHVs) through signalized intersections. The trajectory of CAVs is continuously optimized via a central methodology, while a new “white” phase is introduced to enforce CHVs to follow their immediate front vehicle. The movement of CHVs is incorporated in the optimization framework utilizing a customized linear car-following model. During the white phase, CAVs lead groups of CHVs through an intersection. The proposed formulation determines the optimal signal indication for each lane-group in each time step. We have developed a receding horizon control framework to solve the problem. The case study results indicate that the proposed methodology successfully controls the mixed CAV-CHV traffic under various CAV market penetration rates and different demand levels. The results reveal that a higher CAV market penetration rate induces more frequent white phase indication compared to green-red signals. The proposed program reduces the total delay by 19.6%–96.2% compared to a fully-actuated signal control optimized by a state-of-practice traffic signal timing optimization software.

这项研究开发了一种新颖的混合整数非线性程序，通过信号交叉口来控制混合自动连接车辆（CAV）和人类驱动车辆（CHV）的轨迹。通过中央方法不断优化CAV的轨迹，同时引入新的“白色”阶段以强制CHV跟随其前排车辆行驶。CHV的运动利用定制的线性跟车模型被纳入优化框架。在白色阶段，CAV通过交叉路口引导CHV组。提出的公式确定了每个时间步长中每个车道组的最佳信号指示。我们已经开发了后退的水平控制框架来解决该问题。案例研究结果表明，该方法成功地控制了各种CAV市场渗透率和不同需求水平下的CAV-CHV混合流量。结果表明，与绿色红色信号相比，较高的CAV市场渗透率会引起更频繁的白相指示。与通过实际交通信号定时优化软件进行优化的全驱动信号控制相比，该程序可将总延迟降低19.6％–96.2％。