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
• DOI: https://doi.org/10.64388/IREV9I5-1712513

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, vol. 9, no. 5, Nov. 2025, doi: https://doi.org/10.64388/IREV9I5-1712513

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

MLA:
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, vol. 9, no. 5, Nov. 2025. Crossref, https://doi.org/10.64388/IREV9I5-1712513

BibTeX

@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}
}