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Smart Control of Traffic Light Using Artificial Intelligence

  • 2026
  • OriginalPaper
  • Chapter
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Abstract

This chapter delves into the challenges of traffic congestion in metropolitan areas and the limitations of traditional traffic management systems. It introduces a novel approach using the YOLO algorithm for real-time vehicle detection and classification, enabling dynamic adjustment of traffic light timings. The methodology involves capturing live data from CCTV cameras at intersections and optimizing green light durations based on vehicle density. The text also discusses related work, including fuzzy logic-based controllers and image processing techniques for traffic management. The results demonstrate the potential of this AI-driven approach to improve traffic flow, reduce congestion, and decrease fuel consumption and emissions. Additionally, the chapter explores the broader implications of this technology for urban planning and transportation systems.

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Title
Smart Control of Traffic Light Using Artificial Intelligence
Authors
N. Sujata Kumari
K. Kavya
Bh. Sirisha
S. Bhoomika
Copyright Year
2026
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-95-0269-1_103
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