A system and method of multi-agent reinforcement learning for integrated and networked adaptive traffic controllers (MARLIN-ATC). Agents linked to traffic signals generate control actions for an optimal control policy based on traffic conditions at the intersection and one or more other intersections. The agent provides a control action considering the control policy for the intersection and one or more neighboring intersections. Due to the cascading effect of the system, each agent implicitly considers the whole traffic environment, which results in an overall optimized control policy.


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    Title :

    Multi-agent reinforcement learning for integrated and networked adaptive traffic signal control


    Contributors:

    Publication date :

    2017-11-14


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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