The Traffic Analysis System utilizes machine learning for real-time traffic insights at a junction. It provides instant stats like vehicle count, density, and FPS, while summarizing average vehicle crossings, densities, stop times, and identifying peak minutes. Machine learning techniques include object detection, tracking, and lane segmentation. The system offers a user-friendly interface with graphical representations, aiding traffic management decisions. It not only ensures efficient traffic control but also allows for predictive analytics and potential integration with traffic light systems for adaptive signal adjustments. Continuous model training and future enhancements promise improved accuracy and adaptability to evolving traffic scenarios.


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    Titel :

    YOLOv4-Powered Traffic Intelligence: From Detection to Optimization


    Beteiligte:
    Sanjiv, Sinha (Autor:in) / E, Tharunn (Autor:in) / Baskar, M. (Autor:in)


    Erscheinungsdatum :

    28.06.2024


    Format / Umfang :

    1214636 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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