The present traffic light management system causes a lot of problems such as long delays and congestion. The existing traffic signal system is in such a way that the signal is given for a lane using a timer circuit irrespective of the density of traffic in that lane, due to this the waiting period of a lane with more number of vehicles will be increased. In order to increase the efficiency, we need to consider the traffic information at the junctions as an input to decide the signal. In this paper, we propose a model to improve efficiency of traffic management by taking real-time traffic information. The model takes the video input from each lane at the intersection and decides the signal considering the following three factors:

    number of vehicles

    type of vehicle

    emergency vehicle.

    The vehicles are classified using TensorFlow, and density across the lanes is calculated based on the count and weightage of the vehicles. Along with this, we are considering the emergency vehicles, and the waiting time is also set for the lanes which can be used for a lane with the least number of vehicles waiting for a longer time. Using these factors, signals are decided across the lanes.


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    Titel :

    Intelligent Traffic Light Management System


    Beteiligte:
    Kiran Mai, C. (Herausgeber:in) / Kiranmayee, B. V. (Herausgeber:in) / Favorskaya, Margarita N. (Herausgeber:in) / Chandra Satapathy, Suresh (Herausgeber:in) / Raju, K. Srujan (Herausgeber:in) / Jahnavi, Somavarapu (Autor:in) / Prasanth, G. (Autor:in) / Priyanka, D. (Autor:in) / Sneheth, A. (Autor:in) / Navya, M. (Autor:in)

    Erscheinungsdatum :

    01.01.2021


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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