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Interaction-aware eco-driving control under complex traffic environment: A comprehensive review

Author

Listed:
  • Wang, Yue
  • Li, Weiliang
  • Wu, Jingda
  • Gao, Bolin
  • Zhong, Wei
  • He, Lei
  • Lv, Chen
  • He, Hongwen
  • Li, Keqiang

Abstract

The rapid development of eco-driving technologies is conducive to improving the energy economy of connected and automated vehicles (CAV). However, most eco-driving control methods have ineffective practical application in complex traffic environments because existing methods cannot sufficiently consider the complex interaction behaviors and factors. To reveal the limitations and improvement direction of current researches, this paper delivers a comprehensive review of interaction-aware eco-driving control under a complex traffic environment. The features and modeling process of the interaction-aware eco-driving control problem are first elaborated in detail. Influencing factors of eco-driving control in the interaction scenario are then innovatively summarized from the people-vehicle-road interactive environment. Furthermore, interactive scenario-oriented eco-driving studies in complex traffic environments are generalized and divided into five typical types: car-following interaction scenarios, lane-changing interaction scenarios, intersection interaction scenarios, ramp merging interaction scenarios, and multi-vehicle platoon interaction scenarios. Finally, according to the above-stated overview, technical challenges and future research trends for interaction-aware eco-driving are suggested from five aspects: scenario cognition, personalization, decision-making, algorithm self-evolution, and control robustness.

Suggested Citation

  • Wang, Yue & Li, Weiliang & Wu, Jingda & Gao, Bolin & Zhong, Wei & He, Lei & Lv, Chen & He, Hongwen & Li, Keqiang, 2025. "Interaction-aware eco-driving control under complex traffic environment: A comprehensive review," Applied Energy, Elsevier, vol. 401(PB).
    • Handle: RePEc:eee:appene:v:401:y:2025:i:pb:s0306261925014382
    DOI: 10.1016/j.apenergy.2025.126708
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    References listed on IDEAS

    as
    1. He, Hongwen & Wang, Yunlong & Han, Ruoyan & Han, Mo & Bai, Yunfei & Liu, Qingwu, 2021. "An improved MPC-based energy management strategy for hybrid vehicles using V2V and V2I communications," Energy, Elsevier, vol. 225(C).
    2. Ganesh, Akhil Hannegudda & Xu, Bin, 2022. "A review of reinforcement learning based energy management systems for electrified powertrains: Progress, challenge, and potential solution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    3. Nowakowski, Christopher & Shladover, Steven E & Lu, Xiao-Yun & Thompson, Deborah & Kailas, Aravind, 2015. "Cooperative Adaptive Cruise Control (CACC) for Truck Platooning: Operational Concept Alternatives," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7jf9n5wm, Institute of Transportation Studies, UC Berkeley.
    4. Xie, Shaobo & Lang, Kun & Qi, Shanwei, 2020. "Aerodynamic-aware coordinated control of following speed and power distribution for hybrid electric trucks," Energy, Elsevier, vol. 209(C).
    5. Zhuang, Weichao & Li, Jinhui & Ju, Fei & Li, Bingbing & Liu, Haoji & Yin, Guodong, 2024. "Dual-objective eco-routing strategy for vehicles with different powertrain types," Energy, Elsevier, vol. 293(C).
    6. Panagiotis Fafoutellis & Eleni G. Mantouka & Eleni I. Vlahogianni, 2020. "Eco-Driving and Its Impacts on Fuel Efficiency: An Overview of Technologies and Data-Driven Methods," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
    7. Nie, Zifei & Farzaneh, Hooman, 2023. "Energy-efficient lane-change motion planning for personalized autonomous driving," Applied Energy, Elsevier, vol. 338(C).
    8. Liu, Teng & Tan, Wenhao & Tang, Xiaolin & Zhang, Jinwei & Xing, Yang & Cao, Dongpu, 2021. "Driving conditions-driven energy management strategies for hybrid electric vehicles: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    9. Li, Jie & Wu, Xiaodong & Fan, Jiawei & Liu, Yonggang & Xu, Min, 2023. "Overcoming driving challenges in complex urban traffic: A multi-objective eco-driving strategy via safety model based reinforcement learning," Energy, Elsevier, vol. 284(C).
    10. Xie, Shaobo & Hu, Xiaosong & Liu, Teng & Qi, Shanwei & Lang, Kun & Li, Huiling, 2019. "Predictive vehicle-following power management for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 166(C), pages 701-714.
    11. Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(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. Zhang, Hanyu & Du, Lili, 2023. "Platoon-centered control for eco-driving at signalized intersection built upon hybrid MPC system, online learning and distributed optimization part II: Theoretical analysis," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 199-216.
    14. Li, Jie & Fotouhi, Abbas & Pan, Wenjun & Liu, Yonggang & Zhang, Yuanjian & Chen, Zheng, 2023. "Deep reinforcement learning-based eco-driving control for connected electric vehicles at signalized intersections considering traffic uncertainties," Energy, Elsevier, vol. 279(C).
    15. Zhang, Hanyu & Du, Lili, 2023. "Platoon-centered control for eco-driving at signalized intersection built upon hybrid MPC system, online learning and distributed optimization part I: Modeling and solution algorithm design," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 174-198.
    16. Mo, Xiaoyu & Xing, Yang & Lv, Chen, 2024. "Heterogeneous graph social pooling for interaction-aware vehicle trajectory prediction," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 191(C).
    17. Nègre, Julien & Delhomme, Patricia, 2017. "Drivers’ self-perceptions about being an eco-driver according to their concern for the environment, beliefs on eco-driving, and driving behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 95-105.
    18. Liu, Jinqiang & Wang, Chunyan & Zhao, Wanzhong, 2024. "An eco-driving strategy for autonomous electric vehicles crossing continuous speed-limit signalized intersections," Energy, Elsevier, vol. 294(C).
    19. 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).
    20. 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).
    21. Li, Yun & Zhang, Wenshan & Zhang, Shengrui & Pan, Yingjiu & Zhou, Bei & Jiao, Shuaiyang & Wang, Jianpo, 2024. "An improved eco-driving strategy for mixed platoons of autonomous and human-driven vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
    22. Wu, Fuliang & Bektaş, Tolga & Dong, Ming & Ye, Hongbo & Zhang, Dali, 2021. "Optimal driving for vehicle fuel economy under traffic speed uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 175-206.
    23. Zhang, Chuntao & Huang, Wenhui & Zhou, Xingyu & Lv, Chen & Sun, Chao, 2024. "Expert-demonstration-augmented reinforcement learning for lane-change-aware eco-driving traversing consecutive traffic lights," Energy, Elsevier, vol. 286(C).
    24. Zhou, Jiaxuan & Peng, Jiankun & Wu, Jingda & Wei, Zhongbao & Fan, Yi & Guo, Xin, 2024. "Multi-performance enhanced eco-driving strategy for connected fuel cell hybrid electric bus based on stein soft actor-3-critic," Energy, Elsevier, vol. 307(C).
    25. Wang, Zhong & Zhao, Yahui & Zhang, Yahui & Tian, Yang & Jiao, Xiaohong, 2024. "Safe off-policy reinforcement learning on eco-driving for a P2-P3 hybrid electric truck," Energy, Elsevier, vol. 313(C).
    26. Wu, Fuliang & Ye, Hongbo & Bektaş, Tolga & Dong, Ming, 2025. "New and tractable formulations for the eco-driving and the eco-routing-and-driving problems," European Journal of Operational Research, Elsevier, vol. 321(2), pages 445-461.
    27. Huang, Yuhan & Ng, Elvin C.Y. & Zhou, John L. & Surawski, Nic C. & Chan, Edward F.C. & Hong, Guang, 2018. "Eco-driving technology for sustainable road transport: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 596-609.
    28. Zhao, Shuaidong & Zhang, Kuilin, 2021. "Online predictive connected and automated eco-driving on signalized arterials considering traffic control devices and road geometry constraints under uncertain traffic conditions," Transportation Research Part B: Methodological, Elsevier, vol. 145(C), pages 80-117.
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