As societal demands on traffic control increase, traditional model-based traffic control methods are showing their limitations. This paper introduces a Distributed Adaptive Coordination Control (DACC) algorithm, which integrates data-driven control and multi-agent systems, aimed at optimizing traffic signal control across multiple intersections to effectively balance queuing times. Through joint simulation experiments with SUMO and Python, and comparison with the Proportional-Integral-Derivative Coordination Control (PIDCC) algorithm, the DACC algorithm has demonstrated advantages in reducing average queuing times and improving traffic flow efficiency. The results indicate that the DACC algorithm excels in managing traffic flow variations.


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    Titel :

    Distributed Adaptive Coordination Control for Autonomous Road Traffic at Multiple Intersections


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Liu, Jun (Herausgeber:in) / Wang, Yongcai (Herausgeber:in) / Wu, Bin (Herausgeber:in) / Jiang, Zehao (Herausgeber:in) / Xiao, Yao (Herausgeber:in) / Ji, Honghai (Autor:in) / Shi, Qirui (Autor:in) / Liu, Shida (Autor:in) / Fan, Lingling (Autor:in) / wang, Li (Autor:in)

    Kongress:

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



    Erscheinungsdatum :

    16.03.2025


    Format / Umfang :

    7 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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