IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v325y2025ics036054422501816x.html
   My bibliography  Save this article

Hierarchical cooperative eco-driving optimization for multidimensional mixed vehicles at signalized intersections

Author

Listed:
  • Cai, Jianjun
  • Liu, Yonggang
  • Zhang, Yuanjian
  • Shen, Shiquan
  • Lei, Zhenzhen
  • Chen, Zheng

Abstract

Electric vehicles (EVs) and connected and automated vehicles (CAVs) are increasingly developed, while traditional fuel vehicles (FVs) and human-driven vehicles (HDVs) still dominate the market. Therefore, future road traffic will consist mainly of multidimensional mixed vehicles, including EVs-FVs and CAVs-HDVs. To improve their overall energy efficiency at signalized intersections, this paper proposes a hierarchical cooperative eco-driving optimization method based on the control of “1+n” mixed vehicle platoon, which consists of one leading CAV and n following HDVs and includes both EVs and FVs. Firstly, based on the energy consumption characteristics of EVs and FVs, a speed planning algorithm considering traffic uncertainties is designed in the upper layer to efficiently determine the reference speed trajectory for the leading CAV. Furthermore, in the lower layer, a model predictive control-based eco-driving strategy is proposed to optimize the platoon's overall energy efficiency by controlling the leading CAV to follow the reference trajectory. Simulation and hardware-in-loop experiment results validate the effectiveness and feasibility of this approach, reducing average energy consumption by 3.48 % for EVs and 8.23 % for FVs compared to a non-optimized model. Additionally, the algorithm's sensitivity to varying vehicle penetration rates and its robustness to HDV lane-changing behavior are assessed.

Suggested Citation

  • Cai, Jianjun & Liu, Yonggang & Zhang, Yuanjian & Shen, Shiquan & Lei, Zhenzhen & Chen, Zheng, 2025. "Hierarchical cooperative eco-driving optimization for multidimensional mixed vehicles at signalized intersections," Energy, Elsevier, vol. 325(C).
    • Handle: RePEc:eee:energy:v:325:y:2025:i:c:s036054422501816x
    DOI: 10.1016/j.energy.2025.136174
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422501816X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2025.136174?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Bo & Sun, Chao & Wang, Bo & Liang, Weiqiang & Ren, Qiang & Li, Junqiu & Sun, Fengchun, 2022. "Bi-level convex optimization of eco-driving for connected Fuel Cell Hybrid Electric Vehicles through signalized intersections," Energy, Elsevier, vol. 252(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jia, Chunchun & He, Hongwen & Zhou, Jiaming & Li, Jianwei & Wei, Zhongbao & Li, Kunang, 2023. "A novel health-aware deep reinforcement learning energy management for fuel cell bus incorporating offline high-quality experience," Energy, Elsevier, vol. 282(C).
    2. Simin Hesami & Majid Vafaeipour & Cedric De Cauwer & Evy Rombaut & Lieselot Vanhaverbeke & Thierry Coosemans, 2023. "Dynamic Pro-Active Eco-Driving Control Framework for Energy-Efficient Autonomous Electric Mobility," Energies, MDPI, vol. 16(18), pages 1-19, September.
    3. Ding, Heng & Sun, Yuan & Wang, Liangwen & Zheng, Xiaoyan & Huang, Wenjuan & Lu, Xiaoshan, 2024. "Intersection eco-driving strategies under mixed traffic environment: An novel cooperation of traffic signal and vehicle trajectory planning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 655(C).
    4. Zhang, Chi & Zeng, Guohong & Wu, Jian & Wei, Shaoyuan & Zhang, Weige & Sun, Bingxiang, 2023. "Integrated optimization of driving strategy and energy management for hybrid diesel multiple units," Energy, Elsevier, vol. 281(C).
    5. Chen, Shuiwang & Hu, Lu & Yao, Zhihong & Zhu, Juanxiu & Zhao, Bin & Jiang, Yangsheng, 2022. "Efficient and environmentally friendly operation of intermittent dedicated lanes for connected autonomous vehicles in mixed traffic environments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P2).
    6. Wei, Xiaodong & Wang, Jiaqi & Sun, Chao & Liu, Bo & Huo, Weiwei & Sun, Fengchun, 2023. "Guided control for plug-in fuel cell hybrid electric vehicles via vehicle to traffic communication," Energy, Elsevier, vol. 267(C).
    7. Li, Menglin & Yin, Long & Yan, Mei & Wu, Jingda & He, Hongwe & Jia, Chunchun, 2024. "Hierarchical intelligent energy-saving control strategy for fuel cell hybrid electric buses based on traffic flow predictions," Energy, Elsevier, vol. 304(C).
    8. Huang, Ruchen & He, Hongwen & Su, Qicong & Härtl, Martin & Jaensch, Malte, 2025. "Type- and task-crossing energy management for fuel cell vehicles with longevity consideration: A heterogeneous deep transfer reinforcement learning framework," Applied Energy, Elsevier, vol. 377(PC).
    9. Zhang, Baodi & Chang, Liang & Teng, Teng & Chen, Qifang & Li, Qiangwei & Cao, Yaoguang & Yang, Shichun & Zhang, Xin, 2024. "Multi-objective optimization with Q-learning for cruise and power allocation control parameters of connected fuel cell hybrid vehicles," Applied Energy, Elsevier, vol. 373(C).
    10. Zhiming Zhang & Jun Zhang & Liang Shi & Tong Zhang, 2022. "A Study of Contact Pressure with Thermo-Mechanical Coupled Action for a Full-Dimensional PEMFC Stack," Sustainability, MDPI, vol. 14(14), pages 1-16, July.
    11. Zhang, Yahui & Wei, Zeyi & Wang, Zhong & Tian, Yang & Wang, Jizhe & Tian, Zhikun & Xu, Fuguo & Jiao, Xiaohong & Li, Liang & Wen, Guilin, 2024. "Hierarchical eco-driving control strategy for connected automated fuel cell hybrid vehicles and scenario-/hardware-in-the loop validation," Energy, Elsevier, vol. 292(C).
    12. Li, Jie & Fotouhi, Abbas & Liu, Yonggang & Zhang, Yuanjian & Chen, Zheng, 2024. "Review on eco-driving control for connected and automated vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    13. Wilberforce, Tabbi & Anser, Afaaq & Swamy, Jangam Aishwarya & Opoku, Richard, 2023. "An investigation into hybrid energy storage system control and power distribution for hybrid electric vehicles," Energy, Elsevier, vol. 279(C).
    14. Jia, Chunchun & Zhou, Jiaming & He, Hongwen & Li, Jianwei & Wei, Zhongbao & Li, Kunang & Shi, Man, 2023. "A novel energy management strategy for hybrid electric bus with fuel cell health and battery thermal- and health-constrained awareness," Energy, Elsevier, vol. 271(C).
    15. Ju, Fei & Murgovski, Nikolce & Zhuang, Weichao & Hu, Xiaosong & Song, Ziyou & Wang, Liangmo, 2023. "Predictive energy management with engine switching control for hybrid electric vehicle via ADMM," Energy, Elsevier, vol. 263(PE).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:325:y:2025:i:c:s036054422501816x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.