“Low carbon” is a trend of today’s transportation. Improving road traffic efficiency and reducing energy consumption are our primary goals. In urban traffic, unreasonable signal control scheme will cause traffic congestion and increase fuel consumption of gasoline powered vehicles. Therefore, a low fuel consumption traffic signal optimization algorithm based on Q learning is proposed, which can dynamically adjust the timing scheme according to the real-time traffic state to achieve the goal of minimum fuel consumption. At the same time, each phase control is independent, and has the same state and action set. Starting from the optimal control of single phase, it is extended to multi-phase control to effectively improve the iteration speed and convergence effect of the algorithm. Considering the high experience risk in the actual traffic environment, a simulation platform is developed to model the actual traffic flow, which can verify the rationality of the traffic control algorithm.


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    Title :

    Traffic Signal Optimization Method for Urban Intersections with Low Fuel Consumption


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Qian, Zhihong (editor) / Jabbar, M.A. (editor) / Cheung, Simon K. S. (editor) / Li, Xiaolong (editor) / Tao, Wusi (author) / Chen, Feng (author)

    Conference:

    INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND APPLICATIONS ; 2022 ; Wuhan, China December 16, 2022 - December 18, 2022



    Publication date :

    2023-07-27


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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