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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | Real-Time Traffic Optimization Using Reinforcement and Deep Leaning |
| Authors Name: | Varun Gudem , Pathipaka Sai Krishna , Tanav Bolla |
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IJRTI_202227
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| Published Paper Id: | IJRTI2505255 |
| Published In: | Volume 10 Issue 5, May-2025 |
| DOI: | |
| Abstract: | Traffic congestion is a major issue in cities, leading to longer travel times, unnecessary fuel consumption, and higher pollution levels. Traditional traffic management systems fail to make adjustments in response to the real-time nature of road traffic, resulting in poor traffic flow and long waiting times. They depend on fixed-timer signals. In this paper, an adaptive traffic control system using YOLOv8-based object recognition and real-time picture processing for optimized traffic management is proposed. The proposed system utilizes surveillance cameras to capture live feed of the traffic flow and employs advanced deep-learning techniques for processing the captured data. To accurately recognize and count vehicles in real time, YOLOv8, a state-of-the-art object detection model, is employed. It automatically adapts the timing of traffic lights, optimizing traffic flow responsive to the situation to make it more effective. To enhance computational efficiency and reduce decision-making latency, edge computing techniques are also applied. When the adaptive system was compared to conventional fixed-timer systems, simulations as well as actual testing showed that total traffic efficiency increased by approximately 23 percentage due to significant reduction in time spent with signals on red and vehicles on approach to the signals waiting to cross. From the results, it can be inferred that the proposed approach outperforms both conventional traffic management systems, with a significant computational efficiency, as well as the recent adaptive traffic management systems by applying it to the smart city infrastructures. |
| Keywords: | Traffic management, Intelligent transportation system, YOLOv8, Deep learning, Real-time processing, Edge computing, Adaptive traffic control |
| Cite Article: | "Real-Time Traffic Optimization Using Reinforcement and Deep Leaning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.c468-c475, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505255.pdf |
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| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2505255
Registration ID:202227
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: c468-c475 Country: Medchal, Telangana, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505255 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505255 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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