Due to human driving habits, traffic flow often has stop-and-go phenomena, resulting in reduced traffic efficiency, increased fuel consumption and emissions. This paper models the general heterogeneous mixed traffic flow and describes in detail the driving characteristics of human drivers in the traffic flow. Based on this model, an ecological driving strategy for autonomous vehicles is proposed. The optimization problem of autonomous vehicles is established based on the heterogeneous mixed traffic flow model. An improved proximal policy optimization (PPO) algorithm is designed to solve the optimal control input of the grid-connected autonomous vehicle (CAV). The effectiveness of the optimization algorithm is demonstrated through numerical simulation.


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    Titel :

    Eco-Driving and Suppression of Traffic Waves in Mixed Heterogeneous Traffic Streams Using Connected-Automated Vehicle


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Jia, Limin (Herausgeber:in) / Zhang, Qiang (Herausgeber:in) / Xie, Zhengyu (Herausgeber:in) / Li, Haibin (Herausgeber:in) / Yong, Kenan (Herausgeber:in) / Wang, Li (Herausgeber:in) / Gu, Yunyang (Autor:in) / Xu, Yueru (Autor:in)

    Kongress:

    International Conference on Artificial Intelligence and Autonomous Transportation ; 2024 ; Beijing, China December 06, 2024 - December 08, 2024



    Erscheinungsdatum :

    19.04.2025


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch







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