International Journal of Scientific Research and Engineering Development

In this paper, an artificial intelligence based adaptive traffic signal control system has been proposed using computer vision systems to detect vehicles and change the timing of the signal dynamically based on the density of traffic. The system utilizes a mixture of video feed from traffic cameras and object detection in the form of deep learning models to approximate the real time situation traffic conditions and signals. A simulation based evaluation is made for performance analysis of the proposed system for different traffic scenarios. The results revealed that proposed the method can greatly improve the waiting time of the vehicles and increase the efficiency of traffic flow as compared with the conventional fixed-time signal systems. The system is also a scalable and cheap solution for smart city applications and smart transportation systems.

Shifa Bilal Tamboli, Simeen Phiroj Mulani, Arman Tajuddin Shiakh,"Intelligent Traffic Signal Optimization Using Computer Vision and Real-Time Vehicle Density Analysis" International Journal of Scientific Research and Engineering Development, V9(2): Page(2370-2381) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.