This paper proposes a framework of signalized corridor management with vehicle platooning and trajectory control (SCoPTO) using connected automated vehicle (CAV) technologies. In this framework, the major road platoons can request green time extensions when arriving at the downstream intersections to reduce unnecessary stops. The vehicular trajectories of CAVs can also be optimized to maximize the utilization of the green time and reduce the start-up lost time. CAV platooning operation is implemented such that CAVs can pass the intersection efficiently to potentially increase green time utilization and improve traffic stability. Simulations are performed in a realistic signalized corridor with three intersections, and the results show that the proposed SCoPTO framework can significantly improve the throughput and reduce the average delay across different CAV penetration rates. This study provides insights for traffic management centers to use SCoPTO for future urban signalized corridor management.

本文提出了一个使用联网自动驾驶汽车 (CAV) 技术的车辆排队和轨迹控制 (SCoPTO) 的信号化走廊管理框架。在这个框架下，主要道路排在到达下游交叉路口时可以要求延长绿灯时间，以减少不必要的停车。还可以优化 CAV 的车辆轨迹，以最大限度地利用绿灯时间并减少启动损失时间。实施 CAV 队列操作，使 CAV 可以有效地通过交叉路口，从而潜在地提高绿灯利用率并提高交通稳定性。模拟是在具有三个十字路口的现实信号走廊中进行的，结果表明，所提出的 SCoPTO 框架可以显着提高吞吐量并减少不同 CAV 穿透率的平均延迟。本研究为交通管理中心使用 SCoPTO 进行未来城市信号化走廊管理提供了见解。