Connected and automated vehicles (CAVs) trajectories not only provide more real-time information by vehicles to infrastructure but also can be controlled and optimized, to further save travel time and gasoline consumption. This paper proposes a two-level model for traffic signal timing and trajectories planning of multiple connected automated vehicles considering the random arrival of vehicles. The proposed method contains two levels, i.e., CAVs’ arrival time and traffic signals optimization, and multiple CAVs trajectories planning. The former optimizes CAVs’ arrival time and traffic signals in a random environment, to minimize the average vehicle’s delay. The latter designs multiple CAVs trajectories considering average gasoline consumption. The dynamic programming (DP) and the General Pseudospectral Optimal Control Software (GPOPS) are applied to solve the two-level optimization problem. Numerical simulation is conducted to compare the proposed method with a fixed-time traffic signal. Results show that the proposed method reduces both average vehicle’s delay and gasoline consumption under different traffic demand significantly. The average reduction of vehicle’s delay and gasoline consumption are 26.91% and 10.38%, respectively, for a two-phase signalized intersection. In addition, sensitivity analysis indicates that the minimum green time and free-flow speed have a noticeable effect on the average vehicle’s delay and gasoline consumption.

中文翻译：

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随机环境中多个CAV的交通信号正时和轨迹规划的两级模型

联网和自动驾驶（CAV）轨迹不仅可以通过车辆向基础设施提供更多的实时信息，而且可以进行控制和优化，以进一步节省出行时间和汽油消耗。考虑车辆的随机到达，本文提出了一种用于多连接自动车辆的交通信号定时和轨迹规划的两级模型。所提出的方法包含两个层次，即CAV的到达时间和交通信号优化，以及多个CAV的轨迹规划。前者在随机环境中优化了CAV的到达时间和交通信号，以最大程度地减少平均车辆的延误。后者根据平均汽油消耗量设计了多个CAV轨迹。应用动态规划（DP）和通用伪谱最优控制软件（GPOPS）来解决两级优化问题。进行了数值模拟，以比较该方法与固定时间的交通信号。结果表明，该方法在不同交通需求下均能显着降低平均车辆延误和汽油消耗。对于两相信号交叉口，车辆延误和汽油消耗的平均减少分别为26.91％和10.38％。此外，敏感性分析表明，最短的绿色行驶时间和自由流动速度对平均车辆的延迟和汽油消耗有显着影响。结果表明，该方法在不同交通需求下均能显着降低平均车辆延误和汽油消耗。对于两相信号交叉口，车辆延误和汽油消耗的平均减少分别为26.91％和10.38％。此外，敏感性分析表明，最短的绿色行驶时间和自由流动速度对平均车辆的延迟和汽油消耗有显着影响。结果表明，该方法在不同交通需求下均能显着降低平均车辆延误和汽油消耗。对于两相信号交叉口，车辆延误和汽油消耗的平均减少分别为26.91％和10.38％。此外，敏感性分析表明，最短的绿色行驶时间和自由流动速度对平均车辆的延迟和汽油消耗有显着影响。