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 Journal of Statistics and Management Systems cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0014·ISSN (Print): 0972-0510

Monthly Journal: Publishes peer-reviewed aticles on theoretical and applied statistics and management systems, expoloring industrial statistics, actuarial and decision sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
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Open Access Research Article

AI-driven traffic signal system with YOLO for dynamic congestion control

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pp. 517–527Vol. 29Issue 5May 2026DOI: 10.47974/JSMS-1557XML
Received:
01 May 2025
Published Online:
27 Apr 2026
Article type:
Research Article
Language:
EN
Article no.:
JSMS-1557
Pages:
517–527

Abstract

This project develops an AI-powered Smart Traffic Light System utilizing YOLOv8 (You Only Look Once) for real-time vehicle detection to improve and better traffic management. The system dynamically adjusts green light durations based on the number of vehicles detected. If there are five or less then five vehicle detected, the green light duration is calculated as the number of vehicles multiplied by five seconds. If there are more than five vehicles, a fixed 40-second green light duration is applied. Additionally, the system prioritizes emergency vehicles, immediately providing them with a 40-second green light when detected, ensuring faster emergency response times. The system was implemented using Python, OpenCV, and Ultralytics YOLOv8, with inference accelerated through GPU processing. The results demonstrate the effectiveness of the system in real-world traffic management, with improvements in both traffic flow and emergency vehicle prioritization.

Keywords

Subject Classifications

68T05

References

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