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汽车安全与节能学报

汽车安全与节能学报 ›› 2022, Vol. 13 ›› Issue (4): 676-685.DOI: 10.3969/j.issn.1674-8484.2022.04.009

• 智能驾驶与智慧交通 • 上一篇    下一篇

异构智能网联车辆编队的双阶段节能驾驶控制策略(英文)

杨金松1(), 赵德宗1,3,*(), 江菁晶2, 蓝江林1, 李亮3   

  1. 1.格拉斯哥大学 工程学院，格拉斯哥，G12 8QQ，英国
    2.拉夫堡大学 航空与汽车工程系，拉夫堡，LE11 3TU，英国
    3.清华大学，汽车安全与能源国家重点实验室，北京，100084，中国
  • 收稿日期:2021-07-19 修回日期:2022-07-27 出版日期:2022-12-31 发布日期:2023-01-01
  • 通讯作者: 赵德宗
  • 作者简介:*赵德宗，副教授。E-mail: dezong.zhao@glasgow.ac.uk。
    杨金松（1995—），男（汉），吉林，博士研究生。E-mail: 2618741y@student.gla.ac.uk。
  • 基金资助:
    汽车安全与节能国家重点实验室(清华大学，中国)(KF2009);EPSRC (Engineering and Physical Science Research Council, UK) Innovation Fellowship(EP/S001956/1)

Two-stage eco-driving control strategy for heterogeneous connected and automated vehicle platoons

YANG Jinsong1(), ZHAO Dezong1,3,*(), JIANG Jingjing2, LAN Jianglin1, LI Liang3   

  1. 1. School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK
    2. Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough LE11 3TU, UK
    3. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
  • Received:2021-07-19 Revised:2022-07-27 Online:2022-12-31 Published:2023-01-01
  • Contact: ZHAO Dezong
  • Supported by:
    State Key Laboratory of Automotive Safety and Energy (Tsinghua University, China)(KF2009);EPSRC (Engineering and Physical Science Research Council, UK) Innovation Fellowship(EP/S001956/1)

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摘要：

为了提高智能网联自动驾驶汽车 (CAV) 车队的燃油效率，提出了一种CAV异构车队的双阶段节能驾驶控制策略。在离线控制策略阶段，速度优化通过利用动态规划(DP)，为智能网联自动驾驶车队创建参考节能速度曲线。在在线控制阶段，采用双向控制与领队跟随(BDLF)策略，来保持车队的稳定性，并实时跟踪参考速度曲线。利用Matlab构建的双阶段节能驾驶策略，在Autonomie车辆系统仿真工具中进行了仿真。在多组道路环境下，基于美国加州交通局(Caltrans)性能测量系统(PeMS)提供的交通数据对该策略的性能进行了测试验证。结果表明：本双阶段节能驾驶策略将CAV车队的燃油效率提高了10.1%。因而，该方法可以保持CAV异构车队的稳定并为车队提供更加节能的控制方法。

关键词: 智能网联自动驾驶汽车(CAV), 节能驾驶, 车辆编队行驶, 驾驶控制策略, 速度优化

Abstract:

A two-stage eco-driving control strategy was proposed for the heterogeneous platoon consisting of different Connected and Automated Vehicles (CAVs) to improve the fuel efficiency of the platoons. The speed optimisation based on dynamic programming (DP) created an energy-efficient reference speed profile for the CAV platoon at the offline planning control strategy. A Bi-Directional Leader Following (BDLF) strategy was employed at real-time control strategy, to maintain the platoon string stability and to track the reference speed profile in real-time. The proposed two-stage eco-platoon control strategy was established in MATLAB. Its performances were validated by the Autonomie Vehicle System Simulation tool based on the traffic data provided by the California Department of Transportation (Caltrans) (USA) Performance Measurement System (PeMS). The results show that the proposed two-stage eco-driving strategy improves the fuel efficiency of the CAV platoon by 10.1% compared to benchmark strategies. Therefore, this method can maintain the string stability and provide a more energy-efficient solution for the heterogeneous CAV platoons.

Key words: connected and automated vehicles (CAV), eco-driving, vehicle platoons, driving control strategy, speed optimisation

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