The paper presents an adaptive traffic signal control method that is invariant to its configuration. The proposed method uses a single neural network model to control traffic lights of different configurations, i.e. having a different set of phases and number of controlled lanes. Experimental studies on the effectiveness of the proposed method were carried out in a specialized traffic flow modeling environment, SUMO (Simulation of Urban MObility). The results obtained confirmed the operability and efficiency of the proposed method.


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    Title :

    Reinforcement learning based adaptive traffic signal control method invariant to the configuration of the traffic lights


    Contributors:


    Publication date :

    2024-05-20


    Size :

    754305 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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