Welcome to Journal of Automotive Safety and Energy,

Journal of Automotive Safety and Energy ›› 2022, Vol. 13 ›› Issue (4): 676-685.DOI: 10.3969/j.issn.1674-8484.2022.04.009

• Intelligent Driving and Intelligent Transportation • Previous Articles     Next Articles

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 E-mail:2618741y@student.gla.ac.uk;dezong.zhao@glasgow.ac.uk
  • 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)

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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