Paper builds a next-day traffic forecasting system using machine learning. By the use of historical information, it can correctly predict what will happen in the case of traffic conditions. It also provides dynamic routing options that help to alleviate congestion and improve travel time. With this proactive approach, road network efficiency is enhanced which in turn reduces congestion and improves travel experience. Integrating Real-time Data with Machine Learning: This promotes smoother traffic flows as well as reduced carbon footprints.


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    Titel :

    Traffic Awareness for Travelers One Day before Travel Using Machine Learning


    Beteiligte:
    Rindhe, Amol (Autor:in) / Rahate, Jagruti (Autor:in) / Bhange, Vaibhavi (Autor:in) / Yadav, Ashwini (Autor:in)


    Erscheinungsdatum :

    16.12.2024


    Format / Umfang :

    582911 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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