International Journal of Scientific Research and Engineering Development

An AI-based smart traffic management system that can improve road safety, reduce traffic congestion, and automate traffic law enforcement. The system uses computer vision techniques such as OpenCV and YOLO- based models and analyse the traffic using captured lane-wise frames. A Django-based backend entails integration of modules such as adaptive traffic signal control, violation detection and accident detection. Traffic signals are dynamically adjusted based on a weighted vehicle density approach so as to optimize traffic flow. The system detects violations such as red light jumping, helmetless riding, triple riding and license plate recognition (using OCR) for vehicle identification. It also consists of an accident detection module for faster emergency response. Automated e-challan system for generating digital penalties with evidence images and send notification. A caching mechanism is implemented so that duplicate challans never occur. The system is a complete end-to-end solution with less human intervention and efficiency in traffic management.

Siddhi Jitkar, Atharva Shinde,"AI- Powered Smart Automated Traffic System with Accident Detection &Violation Detection with E-Challan" International Journal of Scientific Research and Engineering Development, V9(2): Page(1420-1427) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.