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1714570 Vol 9 · Issue 8 Download Paper

Automatic Traffic Signal by Using Artificial Intelligence

Shahzeb Ahmed G. Kiran Kumar S. Chandra Shekhra Dr. Kavita Singh

Subject area: Science,Engineering and Technology  ·  Area of research: Artificial Intelligence

DOI: https://doi.org/10.64388/IREV9I8-1714570

Abstract

The rapid growth of urban populations and the increasing number of vehicles have led to congestion, traffic jams, and inefficiencies in road networks. Traditional traffic signal systems, which rely on fixed timing or manual control, often fail to address the dynamic and unpredictable flow of traffic. This paper outlines an automatic traffic signal system that enhances traffic management by using real -time data to adjust signal timings based on traffic density and flow. The proposed system employs sensors, cameras, or inductive loops to monitor vehicle movement and congestion levels at intersections. The signals are then controlled by an intelligent algorithm that dynamically adjusts the green, yellow, and red phases to optimize traffic flow, reduce waiting times, and minimize fuel consumption and emissions.

Keywords

Automatic Traffic Signal, Artificial Intelligence, Real -time Data, Traffic Density, Optimize Traffic Flow.

References

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[2] Sharma Moolchand and Bansal, Ananya and Kashyap,Vaibhav C Goyal, Pramod C Sheakh, Dr.Tariq (2020).“Intelligent Traffic Light Control System Based on Traffic Environment Using Deep Learning”.

[3] Abbas, Aymen C Sheikh, Usman C Al-Dhief, Fahad C Haji Mohd, Mohd Norzali. (2021). “ A comprehensive review of vehicle detection using computer vision”.TELKOMNIKA (Telecommunication Computing Electronics And Control). 19. 838- 850.10.12928/TELKOMNIKA.v19i3.12880.

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[5] Tanvi Sable, Nehal Parate, Dharini Nadkar, Swapnil Shinde. “Density and Time based Traffic Control System Using Video Processing”. ITM Web of Conferences 32,03028 (2020).

[6] S. Zhao and F. You, “Vehicle Detection Based on Improved Yolov3 Algorithm,” 2020 International Conference on Intelligent Transportation, Big Data CSmart City (ICITBS), 2020, pp. 76-79, doi:10.1109/ICITBS49701.2020.00024.

[7] A. S. Shaikat, R. -U. Saleheen, R. Tasnim, R.Mahmud, F. Mahbub and T. Islam, “An Image Processing And Artificial Intelligence based Traffic Signal Control System of Dhaka,” 2019 Asia Pacific Conference on Research in Industrial and Systems Engineering (APCoRISE), 2019, pp. 1-6, doi:10.1109/APCoRISE46197.2019.9318966.

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How to cite this paper

Shahzeb Ahmed, G. Kiran Kumar, S. Chandra Shekhra, Dr. Kavita Singh "Automatic Traffic Signal by Using Artificial Intelligence" Iconic Research And Engineering Journals Volume 9 Issue 8 2026 Page 1832-1838 https://doi.org/10.64388/IREV9I8-1714570
Shahzeb Ahmed, G. Kiran Kumar, S. Chandra Shekhra, Dr. Kavita Singh "Automatic Traffic Signal by Using Artificial Intelligence" Iconic Research And Engineering Journals, vol. 9, no. 8, Feb. 2026, doi: https://doi.org/10.64388/IREV9I8-1714570
Shahzeb Ahmed, G. Kiran Kumar, S. Chandra Shekhra, Dr. Kavita Singh (2026). Automatic Traffic Signal by Using Artificial Intelligence. Iconic Research And Engineering Journals, 9(8). doi: https://doi.org/10.64388/IREV9I8-1714570
Shahzeb Ahmed, G. Kiran Kumar, S. Chandra Shekhra, Dr. Kavita Singh "Automatic Traffic Signal by Using Artificial Intelligence" Iconic Research And Engineering Journals, vol. 9, no. 8, Feb. 2026. Crossref, https://doi.org/10.64388/IREV9I8-1714570
@article{1714570,
      author = {Shahzeb Ahmed, G. Kiran Kumar, S. Chandra Shekhra, Dr. Kavita Singh},
      title = {Automatic Traffic Signal by Using Artificial Intelligence},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {8},
      pages = {1832-1838},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1714570.pdf},
      abstract = {The rapid growth of urban populations and the increasing number of vehicles have led to congestion, traffic jams, and inefficiencies in road networks. Traditional traffic signal systems, which rely on fixed timing or manual control, often fail to address the dynamic and unpredictable flow of traffic. This paper outlines an automatic traffic signal system that enhances traffic management by using real -time data to adjust signal timings based on traffic density and flow. The proposed system employs sensors, cameras, or inductive loops to monitor vehicle movement and congestion levels at intersections. The signals are then controlled by an intelligent algorithm that dynamically adjusts the green, yellow, and red phases to optimize traffic flow, reduce waiting times, and minimize fuel consumption and emissions.},
      keywords = {Automatic Traffic Signal, Artificial Intelligence, Real -time Data, Traffic Density, Optimize Traffic Flow.},
      month = {February},
      doi = {https://doi.org/10.64388/IREV9I8-1714570}
  }