Dampen the Stop-and-Go Traffic with Connected and Automated Vehicles – A Deep Reinforcement Learning Approach*
Dampen the Stop-and-Go Traffic with Connected and Automated Vehicles – A Deep Reinforcement Learning Approach*
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DOI：
10.1109/mt-its49943.2021.9529289
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发表时间：
2020-05
期刊：
影响因子：
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通讯作者：
Liming Jiang;Yuanchang Xie;Danjue Chen;Tienan Li;Nicholas G. Evans
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文献类型：
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作者：
Liming Jiang;Yuanchang Xie;Danjue Chen;Tienan Li;Nicholas G. Evans
走走停停的交通对交通运行的效率和安全构成了重大挑战，其影响和工作机制备受关注。最近的研究表明，具有精心设计的纵向控制的互联和自动化车辆(CAV)具有基于模拟的车辆轨迹来抑制走走停停的波的潜力。在这项研究中，采用深度强化学习(DRL)来控制CAV的纵向行为，并利用真实的车辆轨迹数据来训练DRL控制器。它考虑一辆载人(HD)车辆，后面跟着一辆CAV，然后跟着一排HD车辆。这样的实验设计是为了测试CAV如何帮助抑制主高清车辆产生的走走停停的波，并有助于平滑后续高清车辆的速度分布。DRL控制使用真实世界的车辆轨迹进行训练，并最终使用相扑仿真进行评估。结果表明，DRL控制使CAV的速度振荡减小了54%，而对于HD车辆则减小了8%~28%。还观察到了显著的燃油消耗节约。此外，研究结果表明，如果骑士队选择稍微无私地行事，他们可能会起到交通稳定器的作用。
Stop-and-go traffic poses significant challenges to the efficiency and safety of traffic operations, and its impacts and working mechanism have attracted much attention. Recent studies have shown that Connected and Automated Vehicles (CAVs) with carefully designed longitudinal control have the potential to dampen the stop-and-go wave based on simulated vehicle trajectories. In this study, Deep Reinforcement Learning (DRL) is adopted to control the longitudinal behavior of CAVs and real-world vehicle trajectory data is utilized to train the DRL controller. It considers a Human-Driven (HD) vehicle tailed by a CAV, which are then followed by a platoon of HD vehicles. Such an experimental design is to test how the CAV can help to dampen the stop-and-go wave generated by the lead HD vehicle and contribute to smoothing the following HD vehicles’ speed profiles. The DRL control is trained using real-world vehicle trajectories, and eventually evaluated using SUMO simulation. The results show that the DRL control decreases the speed oscillation of the CAV by 54% and 8%-28% for those following HD vehicles. Significant fuel consumption savings are also observed. Additionally, the results suggest that CAVs may act as a traffic stabilizer if they choose to behave slightly altruistically.