Smart Traffic Control System Using Artificial Intelligence

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@article{1712513,
      author = {Ananya A G, Bhoomika S N, Manju U, Vinay Gowda K P, Abdul Rahaman},
      title = {Smart Traffic Control System Using Artificial Intelligence},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {5},
      pages = {2287-2291},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712513.pdf},
      abstract = {Urban traffic congestion is increasing at an alarming rate due to fixed-time traffic signals that fail to adapt to real-time variations in vehicle density. This research proposes an AI-based Smart Traffic Control System that uses YOLO object detection and weighted density computation to dynamically adjust green-signal duration for each lane. The system continuously captures live video feeds from cameras installed at intersections, detects and classifies vehicles, calculates lane-wise density scores and allocates signal time proportionally. Experimental analysis demonstrates high detection accuracy (92.5%), reduced average waiting time, improved vehicle throughput and efficient emergency vehicle prioritisation. The proposed architecture is scalable, cost-effective and suitable for deployment in heterogeneous traffic conditions in modern smart cities.},
      month = {November},
      doi = {https://doi.org/10.64388/IREV9I5-1712513}
  }