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Title	Adaptive Traffic Signal Management Using Real-Time Vehicle Detection And Tracking
ID_Doc	6364
Authors	Shirulkar S.; Makode R.; Khandelwal R.
Year	2025
Published	2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2025
DOI	http://dx.doi.org/10.1109/IATMSI64286.2025.10984828
Abstract	Traffic congestion is a significant issue in urban cities, as it restricts traffic flow, increases fuel consumption, and produces high emissions. Traditional traffic signal systems work on fixed timing without considering real-time variations in traffic and often worsen the problem. This paper describes an adaptive traffic signal control system based on the YOLO (You Only Look Once) algorithm, using object detection for real-time signal timing in response to real-time traffic. The system applies real-time vehicle detection and tracking at intersections for dynamic management of green light time according to volume and vehicle type. The proposed approach makes vehicle recognition significantly efficient and responds quickly to the change in traffic situation. The paper discusses the design, implementation, and evaluation of performance in a simulated environment. The results demonstrate improved traffic management and reduced congestion, offering a promising solution to smart city traffic control. © 2025 IEEE.
Author Keywords	Adaptive traffic signal control; Real-time traffic management; Smart city traffic control; Traffic congestion; Vehicle detection and tracking; YOLO algorithm

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