TY - JOUR
T1 - Interaction-aware eco-driving control under complex traffic environment
T2 - A comprehensive review
AU - Wang, Yue
AU - Li, Weiliang
AU - Wu, Jingda
AU - Gao, Bolin
AU - Zhong, Wei
AU - He, Lei
AU - Lv, Chen
AU - He, Hongwen
AU - Li, Keqiang
N1 - Publisher Copyright:
© 2025
PY - 2025/12/15
Y1 - 2025/12/15
N2 - 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.
AB - 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.
KW - Complex interaction scenario
KW - Connected and automated vehicles
KW - Eco-driving
KW - Interaction-aware
UR - https://www.scopus.com/pages/publications/105015381024
U2 - 10.1016/j.apenergy.2025.126708
DO - 10.1016/j.apenergy.2025.126708
M3 - Article
AN - SCOPUS:105015381024
SN - 0306-2619
VL - 401
JO - Applied Energy
JF - Applied Energy
M1 - 126708
ER -