The rapid growth of innovations in all fields of science has made our lives easier, but the increase in traffic accidents on roads over the years has cost many lives. Local governments are unable to control the global economic growth that is accompanied by an increase in the number of automobiles on the road. Controlling traffic has been a problem for more than a decade and will continue to be a major concern in the near future. Despite the fact that numerous researchers presented their research findings, the problem remains unresolved. This work focuses on a novel approach to automated real-time traffic control based on artificial intelligence concepts. The videos were shot at a four-lane traffic signal in Dehradun and are being tested for various models capable of detecting and counting all types of vehicles. This research focuses on the development of a model that can automatically control traffic based on the YOLO model and DMM to control the traffic light. The YOLO model is integrated in such a way that traffic-related obstacles are minimized. The videos are taken with a 13mega pixel Camera in three places: morning, afternoon and evening. The gray-scale image subtraction system is used. The highest accuracy of the vehicle count is at a mean visibility of 96.15% in the morning, while the lowest accuracy of the fog/low visibility in the night is 66.66% It is also used to control traffic light automatically with the intelligence transportation system.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Artificial Intelligence based Framework for Effective Performance of Traffic Light Control System


    Beteiligte:


    Erscheinungsdatum :

    2021-09-24


    Format / Umfang :

    4973174 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Intelligent Traffic Control System Based on Artificial Intelligence

    Europäisches Patentamt | 2021

    Freier Zugriff

    Traffic lamp control system based on artificial intelligence

    QIN HONGJIA | Europäisches Patentamt | 2015

    Freier Zugriff

    Intelligent Traffic Control System Based on Artificial Intelligence

    GO YOUNG NAM | Europäisches Patentamt | 2021

    Freier Zugriff

    Density-Based Traffic Control System Using Artificial Intelligence

    Sabeenian, R. S. / Ramapriya, R. / Swetha, S. | Springer Verlag | 2022


    Artificial intelligence Internet of Things traffic light system

    HAI KEHONG / WANG YINGSHU | Europäisches Patentamt | 2020

    Freier Zugriff