A Smart AI Based Solution Traffic Management with Real-Time Monitoring and Adaptation of Traffic Light Timings

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@article{1712839,
      author = {Samiksha Debe, Tanmay Patil, Saniya Gawande, Shivam Panzade, Prajwal Patil},
      title = {A Smart AI Based Solution Traffic Management with Real-Time Monitoring and Adaptation of Traffic Light Timings},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {6},
      pages = {2106-2113},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712839.pdf},
      abstract = {Traffic congestion in urban areas has become a critical challenge due to the increasing number of vehicles and inefficient signal management. Traditional traffic control systems lack adaptability, leading to delays and higher fuel consumption. This paper explores AI-driven traffic management using deep learning models like YOLOv8 for real-time vehicle detection and adaptive signal control. By integrating computer vision and machine learning, these systems optimize traffic flow, improve emergency response, and reduce environmental impact. While AI-based solutions offer significant advantages, challenges such as implementation complexity and scalability persist. This review highlights key advancements and future directions in intelligent traffic management.},
      keywords = {Smart Traffic Management, Artificial Intelligence (AI), YOLO Object Detection, Deep Learning, Reinforcement Learning},
      month = {December},
      doi = {https://doi.org/10.64388/IREV9I6-1712839}
  }