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The rapid developing volume of urban activity has made an urgent need for smart arrangements to oversee congestion and improve road safety. This paper presents a Smart Traffic Management System (STMS) that utilizes computer vision to optimize real-time traffic flow. By analyzing live video streams from various traffic cameras, the system is able to evaluate vehicle congestion, classify different types of vehicles, and detect traffic violations. From the various application of methods such as object detection, motion tracking, and deep learning, the STMS alters traffic signals dynamically, making a difference to ease traffic congestion and improve traffic flow. Moreover the system can identify accidents and alarm the appropriate authorities to encourage convenient intervention. The system’s execution was tested over various urban conditions showing impressive advancements in both traffic management and traffic congestion reduction.

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Optimization of Smart Traffic Management System Using Machine Vision-Based Functionalities with CNN Model

  • 会议论文

  • 发表日期：

    2025年

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  • Surya Pratap Singh Varma,
  • Aadrika Jaiswal,
  • Nirupam Das,
  • Tiansheng Yang,
  • Ruikai Sun,
  • Rajkumar Singh Rathore

摘要

The rapid developing volume of urban activity has made an urgent need for smart arrangements to oversee congestion and improve road safety. This paper presents a Smart Traffic Management System (STMS) that utilizes computer vision to optimize real-time traffic flow. By analyzing live video streams from various traffic cameras, the system is able to evaluate vehicle congestion, classify different types of vehicles, and detect traffic violations. From the various application of methods such as object detection, motion tracking, and deep learning, the STMS alters traffic signals dynamically, making a difference to ease traffic congestion and improve traffic flow. Moreover the system can identify accidents and alarm the appropriate authorities to encourage convenient intervention. The system’s execution was tested over various urban conditions showing impressive advancements in both traffic management and traffic congestion reduction.