Due to the chaotic nature of day-to-day traffic density trends, the current traffic management system needs to be immediately improved. The timers in the system have a predetermined amount of time to switch the direction of traffic flow. Because of this, even though there is little traffic density, vehicles must wait longer. As a workaround, the signal timer can be programmed to vary based on the variation in traffic density. This has a great deal of other advantages and can greatly lessen traffic congestion. The suggested system intends to improve the current traffic management system and concentrates on four-way crossings with square traffic signals. The model uses machine learning and image processing to process and estimate actual traffic on the roads. The system will then figure out how long each road will take before turning on the signal. The system is an intelligent spoof of a conventional traffic officer who has successfully made wiser choices to guarantee the intersection's efficient flow of traffic.


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    Titel :

    Smart Traffic Lights


    Beteiligte:
    Joshi, Nikita (Autor:in) / Shah, Karan (Autor:in) / Heniya, Nidhi (Autor:in) / Zaveri, Jainam (Autor:in) / Nikam, Rushikesh (Autor:in) / Deherkar, Kadambari (Autor:in)


    Erscheinungsdatum :

    2023-07-29


    Format / Umfang :

    2212135 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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