Efficient Traffic Signal Management using AI

Among the emerging problems of modern cities, urban traffic congestion takes the lead. It causes increased travel times, higher fuel consumption, and greater environmental pollution. The conventional traffic signal system operates at fixed time intervals, which fail to account for dynamic traffic patterns. The proposed work discussed here is AI-based smart traffic signal management. It dynamically modifies the timings of the signals in real-time that maximizes real-time data captured through cameras placed strategically, with the help of machine learning and computer vision algorithms that achieve dramatic reduction in congestion, improved fuel consumption, and higher reduction in emissions. The system creates an intelligent infrastructure which makes traffic management responsive, hence ensuring sustainable urban environments.

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Publication Details

Published
2025-03-06
DOI
https://doi.org/10.1109/icoeca66273.2025.00119
Citations
1
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
1.01
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article

Efficient Traffic Signal Management using AI

T. Kavitha, M. Thanga Subha Devi, K. Veeraj, H. M. Vinay et al.
1 citations
Traffic Prediction and Management Techniques
1.01
article

Efficient Traffic Signal Management using AI

T. Kavitha, M. Thanga Subha Devi, K. Veeraj, H. M. Vinay, R. S. Abhijit, Nithin Shiva Vanka
article en
1 citations

Abstract

Among the emerging problems of modern cities, urban traffic congestion takes the lead. It causes increased travel times, higher fuel consumption, and greater environmental pollution. The conventional traffic signal system operates at fixed time intervals, which fail to account for dynamic traffic patterns. The proposed work discussed here is AI-based smart traffic signal management. It dynamically modifies the timings of the signals in real-time that maximizes real-time data captured through cameras placed strategically, with the help of machine learning and computer vision algorithms that achieve dramatic reduction in congestion, improved fuel consumption, and higher reduction in emissions. The system creates an intelligent infrastructure which makes traffic management responsive, hence ensuring sustainable urban environments.

Horizon College and Seminary (CA)
Openalex Percentile: Top 22%
Traffic Prediction and Management Techniques
1.01
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