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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    Titel :

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


    Beteiligte:


    Erscheinungsdatum :

    20.05.2024


    Format / Umfang :

    754305 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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