Current literature on joint optimization of intersection signal timing and connected automated vehicle (CAV) trajectory mostly focuses on vehicular movements paying no or little attention to pedestrians. This paper presents a methodology to safely incorporate pedestrians into signalized intersections with CAVs and connected human‐driven vehicles (CHVs). The movements of vehicles are controlled using both traffic lights and mobile CAV controllers during our newly introduced “white phase.” CAVs navigate platoons of CHVs through the intersection when the white phases are active. In addition to optimizing CAV trajectories, the model optimally selects the status of the traffic light signal among white and green indications for vehicular and walk and do‐not‐walk intervals for pedestrian movements. A receding horizon‐based methodology is used to capture the stochastic nature of the problem and to reduce computational complexity. The case study results show the successful operation of fleets consisting of pedestrians, CAVs, and CHVs with various demand levels through isolated intersections. The results also show that increasing the CAV market penetration rate (MPR) can decrease average intersection delay by up to 27%. Moreover, the average pedestrian, CHV, and CAV delays decrease as the CAV MPR increases and reach their minimum values with a fully CAV fleet. In addition, the presence of the white phase can decrease the intersection average delay by up to 14.7%.

中文翻译：

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推进白阶段移动交通控制范式以考虑行人

目前关于交叉口信号配时和联网自动车辆（CAV）轨迹联合优化的文献主要关注车辆运动，而没有或很少关注行人。本文提出了一种通过 CAV 和联网人力驾驶车辆 (CHV) 安全地将行人纳入信号交叉口的方法。在我们新引入的“白色阶段”中，车辆的移动由交通信号灯和移动 CAV 控制器控制。当白色阶段激活时，CAV 引导 CHV 排通过交叉路口。除了优化 CAV 轨迹外，该模型还可以在车辆的白色和绿色指示以及行人运动的步行和不步行间隔之间选择交通灯信号的状态。基于后退视野的方法用于捕获问题的随机性质并降低计算复杂性。案例研究结果表明，由行人、CAV 和 CHV 组成的车队在不同需求水平下通过孤立的十字路口成功运营。结果还表明，提高 CAV 市场渗透率 (MPR) 可以将平均交叉路口延误减少高达 27%。此外，随着 CAV MPR 的增加，行人、CHV 和 CAV 的平均延误会减少，并在完全 CAV 车队的情况下达到最小值。此外，白相的存在可以将路口平均延迟减少高达 14.7%。