One important objective of urban traffic signal control is to reduce individual delay and improve safety for travelers in both private car and public bus transit. To achieve signal control optimization from the perspective of all users, this paper proposes a platoon-based adaptive signal control (PASC) strategy to provide multimodal signal control based on the online connected vehicle (CV) information. By introducing unified phase precedence constraints, PASC strategy is not restricted by fixed cycle length and offsets. A mixed-integer linear programming (MILP) model is proposed to optimize signal timings in a real-time manner, with platoon arrival and discharge dynamics at stop line modeled as constraints. Based on the individual passenger occupancy, the objective function aims at minimizing total personal delay for both buses and automobiles. With the communication between signals, PASC achieves to provide implicit coordination for the signalized arterials. Simulation results by VISSIM microsimulation indicate that PASC model successfully reduces around 40% bus passenger delay and 10% automobile delay, respectively, compared with signal timings optimized by SYNCHRO. Results from sensitivity analysis demonstrate that the model performance is not sensitive to the number fluctuation of bus passengers, and the requested CV penetration rate range is around 20% for the implementation.

中文翻译：

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车联网技术的基于排的自适应信号控制方法。

城市交通信号灯控制的一个重要目标是减少个人延迟，并改善私家车和公共公交系统中旅客的安全性。为了从所有用户的角度实现信号控制优化，本文提出了一种基于排的自适应信号控制（PASC）策略，以基于在线连接车辆（CV）信息提供多模式信号控制。通过引入统一的相位优先约束，PASC策略不受固定周期长度和偏移量的限制。提出了一种混合整数线性规划（MILP）模型，以实时方式优化信号时序，并以停车线的排到达和排出动力学为约束条件。根据个人乘客的占用情况，目标函数旨在最大程度地减少公交车和汽车的总个人延误。通过信号之间的通信，PASC可以为信号动脉提供隐式协调。VISSIM微观仿真的仿真结果表明，与SYNCHRO优化的信号时序相比，PASC模型分别成功地减少了约40％的公交车乘客延迟和10％的汽车延迟。敏感性分析的结果表明，模型的性能对公交车乘客的数量波动不敏感，实施时要求的CV渗透率范围约为20％。与SYNCHRO优化的信号时序相比。敏感性分析的结果表明，模型的性能对公交车乘客的数量波动不敏感，实施时要求的CV渗透率范围约为20％。与SYNCHRO优化的信号时序相比。敏感性分析的结果表明，模型的性能对公交车乘客的数量波动不敏感，实施时要求的CV渗透率范围约为20％。