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基于 MPC 系统的 CAV 在分岔区的动态换道驾驶策略。

A Dynamic Lane-Changing Driving Strategy for CAV in Diverging Areas Based on MPC System.

机构信息

Research Institute of Highway Ministry of Transport, Beijing 100088, China.

Department of Automation, Tsinghua University, Beijing 100083, China.

出版信息

Sensors (Basel). 2023 Jan 4;23(2):559. doi: 10.3390/s23020559.

Abstract

Freeway-diverging areas are prone to low traffic efficiency, congestion, and frequent accidents. Because of the fluctuation of the surrounding traffic flow distribution, the individual decision-making of vehicles in diverging areas is typically unable to plan a departure trajectory that balances safety and efficiency well. Consequently, it is critical that vehicles in freeway-diverging regions develop a lane-changing driving strategy that strives to improve both the safety and efficiency of divergence areas. For CAV leaving the diverging area, this study suggested a full-time horizon optimum solution. Since it is a dynamic strategy, an MPC system based on rolling time horizon optimization was constructed as the primary algorithm of the strategy. A simulation experiment was created to verify the viability of the proposed methodology based on a mixed-flow environment. The results show that, in comparison with the feasible strategies exiting to off-ramp, the proposed strategy can take over 60% reduction in lost time traveling through a diverging area under the premise of safety and comfort without playing a negative impact on the surrounding traffic flow. Thus, the MPC system designed for the subject vehicle is capable of performing an optimal driving strategy in diverging areas within the full-time and space horizon.

摘要

匝道分岔区存在交通效率低、拥堵和频繁事故等问题。由于周围交通流分布的波动,分岔区车辆的个体决策通常无法规划出安全与效率平衡的驶出轨迹。因此,匝道分岔区车辆需要制定一种换道驾驶策略,以提高分岔区的安全性和效率。对于离开分岔区的 CAV,本研究提出了一个全时 horizon 最优解。由于这是一种动态策略,因此构建了基于滚动时间 horizon 优化的 MPC 系统作为该策略的主要算法。基于混合流环境创建了一个仿真实验来验证所提出方法的可行性。结果表明,与驶出匝道的可行策略相比,在安全舒适的前提下,所提出的策略可以减少超过 60%的通过分岔区的旅行时间损失,而对周围交通流没有负面影响。因此,为主体车辆设计的 MPC 系统能够在全时和空间 horizon 内执行最优的分岔区驾驶策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2b1/9864889/a5a4f423be06/sensors-23-00559-g001.jpg

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