Nowadays, the vehicles in the world are increasing along with the human’s population and one of the issues that causes because of this increasing use of vehicles in traffic. Due to this, it is also getting a hectic task to keep track of vehicles, and one of the best methodologies is by using video recordings of vehicles go by which does not disturb the traffic flow and can be easily installed. There are some techniques for detecting, counting, and tracking the vehicles for traffic flow controlling like point detection which did not reach up to the mark, and our project will present a video-based solution with background subtractor in OpenCV development, and with this, we can detect, count, and track the moving vehicles accurately, and thus, countermeasures can be taken to avoid traffic congestions.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Deep Learning Approach to Analyze Traffic Congestions for Effective Traffic Management


    Additional title:

    Algorithms for Intelligent Systems


    Contributors:


    Publication date :

    2022-09-16


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Automated Traffic Management Handling Traffic Congestions

    Roy, Reema Anne / Patil, Sunita R | IEEE | 2022


    Airports facing air traffic congestions

    Valin, Jean-Yves | SLUB | 1989


    Spatio-Temporal Evolution of Traffic Congestions on Urban Freeways

    Chen, X. / Li, R. / Lu, H. et al. | British Library Conference Proceedings | 2009


    Analysis of traffic congestions for automated driving with cooperative approach

    Urhahne,J.A. / Steiger,R. / Van der Voort,M. et al. | Automotive engineering | 2014


    A Developed Traffic Light Approach to Control Road Congestions in VANETs

    Kadhim, Randa Mahdi / Talib Hasson, Saad | IEEE | 2023