Abstract
Urban traffic congestion remains a critical challenge, driven by increasing vehicle numbers and limitations in state of art traffic control systems. Conventional traffic management approaches often lack the flexibility to respond dynamically to real-time conditions, leading to increased congestion, greater energy consumption, and prolonged travel times. To address this, this paper proposes an Intelligent Traffic System (ITS) that leverages computer vision to enable real-time traffic control. The system uses Closed Circuit Television (CCTV) cameras strategically placed at traffic intersections to capture live streams, from which vehicle counts in each lane are determined through image processing techniques. Based on these counts, adaptive signal timings are allocated to optimize traffic flow. The results show that the proposed system saved 75.42% of the commute time as compared to a conventional traffic system. This approach not only enhances traffic fluidity but also paves the way for more responsive and efficient urban traffic management infrastructure.
Keywords
Computer Vision (CV), Dynamic Traffic Management, Intelligent Traffic System (ITS), Vehicle Detection.
Citations
IRE Journals:
Obi-Obuoha Abiamamela , Rizama Victor Samuel
"Computer Vision for Intelligent Traffic Monitoring and Control" Iconic Research And Engineering Journals Volume 8 Issue 5 2024 Page 392-405
IEEE:
Obi-Obuoha Abiamamela , Rizama Victor Samuel
"Computer Vision for Intelligent Traffic Monitoring and Control" Iconic Research And Engineering Journals, 8(5)
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IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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