The traffic monitoring system has become an important part of a smart city. With the increase in traffic, conventional systems are not capable of managing traffic in densely populated areas. Also, there is no way of determining speed of vehicles using these conventional systems. Various challenges like increase in transportation cost and number of accidents due to traffic jams are also encountered. This system intends to monitor and manage traffic flow without any human interference. In conventional traffic management system traffic police uses timer-based traffic lights to manage traffic. But in such systems, it becomes hard for traffic authorities to manage traffic congestion in different areas with limited manpower. The Intelligent Traffic Management System is much needed for monitoring and analysis of traffic. Designing an Intelligent Traffic Management System is also inevitable for the urban cities. This research work will propose an In this paper, we propose an Intelligent Traffic Management System that will help to maintain the traffic congestion without any human interference. The You Only Look Once (YOLO) algorithm is used to detect vehicles from a given video feed. The total number of vehicles detected are also counted in the video provided. The proposed system will detect and count the number of vehicles, which will provide effective solution for traffic monitoring system. This system will also perform classification of vehicles in different categories i.e., Car, Motorbike, Bus, Truck etc. Depending on the count it will determine the traffic density, which will be used for setting the time of the traffic signals.


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    Titel :

    Computer Vision based Intelligent Traffic Management System


    Beteiligte:
    Darwhekar, Kshitij (Autor:in) / Patil, Amey (Autor:in) / Ghodke, Sankalp (Autor:in) / Bawkar, Rushikesh (Autor:in) / Rudrawar, Shilpa (Autor:in)


    Erscheinungsdatum :

    2022-12-01


    Format / Umfang :

    829124 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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