A distributed machine learning based traffic prediction method is provided for predicting traffic of roads. In this case, the distributed machine learning based traffic prediction method includes distributing global multi-task traffic models by a learning server to learning agents to locally train the traffic models, uploading locally trained traffic models by learning agents to the learning server, updating global multi-task traffic models by the learning server using locally trained traffic model parameters acquired from learning agents, generating a time-dependent global traffic map by the learning server using the well trained global multi-task traffic models, distributing the time-dependent global traffic map to vehicles traveling on the roads, and computing an optimal travel route with the least travel time by a vehicle using the time-dependent global traffic map based on a driving plan.


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    Titel :

    DISTRIBUTED MULTI-TASK MACHINE LEARNING FOR TRAFFIC PREDICTION


    Weitere Titelangaben:

    VERTEILTES MASCHINENLERNEN MIT MEHREREN AUFGABEN ZUR VERKEHRSVORHERSAGE
    APPRENTISSAGE MACHINE MULTITÂCHE DISTRIBUÉ POUR LA PRÉDICTION DE TRAFIC


    Beteiligte:
    GUO JIANLIN (Autor:in) / ZENG TENGCHAN (Autor:in) / KIM KYEONG JIN (Autor:in) / PARSONS KIERAN (Autor:in) / ORLIK PHILIP (Autor:in) / DI CAIRANO STEFANO (Autor:in)

    Erscheinungsdatum :

    04.10.2023


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

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



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