Smart Traffic Control System Using Artificial Intelligence

• Author(s): Ananya A G; Bhoomika S N; Manju U; Vinay Gowda K P; Abdul Rahaman
• Paper ID: 1712513
• Page: 2287-2291
• Published Date: 01-12-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 5 November-2025

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.

Citations

IRE Journals:
Ananya A G, Bhoomika S N, Manju U, Vinay Gowda K P, Abdul Rahaman "Smart Traffic Control System Using Artificial Intelligence" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 2287-2291 https://doi.org/10.64388/IREV9I5-1712513

IEEE:
Ananya A G, Bhoomika S N, Manju U, Vinay Gowda K P, Abdul Rahaman "Smart Traffic Control System Using Artificial Intelligence" Iconic Research And Engineering Journals, 9(5) https://doi.org/10.64388/IREV9I5-1712513