A method of modifying or controlling a highway traffic system may include training a machine learning model using historical traffic data corresponding to a roadway traffic system in which the historical traffic data is indicative of traffic patterns over a historical time interval. The method may include obtaining, by the machine learning model, traffic data corresponding to the roadway traffic system and determining a probability of traffic congestion occurrence based on the obtained traffic data corresponding to the roadway traffic system. The method may include comparing the probability of traffic congestion occurrence to a traffic control probability threshold, and responsive to the probability of traffic congestion exceeding the traffic control probability threshold, adjusting operations associated with one or more traffic controls that correspond to the roadway traffic system. The machine learning model may be retrained after a time interval using the obtained traffic data corresponding to the roadway traffic system.


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    Titel :

    MACHINE-LEARNING BASED CONTROL OF TRAFFIC OPERATION


    Beteiligte:
    PITTMAN MARK ERIC (Autor:in) / SACHARNY DAVID (Autor:in) / CANTWELL JENNIFER (Autor:in) / PROBST GERALD (Autor:in)

    Erscheinungsdatum :

    24.11.2022


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



    Machine-learning based control of traffic operation

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