Detection of Traffic Rule Violations Using Machine Learning: An Analytical Review


  • Kaushik Biswas Computer Science Department, American International University-Bangladesh. Dhaka, Bangladesh.
  • Niloy Kanti Paul Computer Science Department, American International University-Bangladesh. Dhaka, Bangladesh
  • Dipanwita Saha Computer Science Department, American International University-Bangladesh. Dhaka, Bangladesh.
  • Tanvir Ahmed Computer Science Department, American International University-Bangladesh. Dhaka, Bangladesh.
  • Rifath Mahmud Computer Science Department, American International University-Bangladesh. Dhaka, Bangladesh.



Image Processing, Automated Traffic Monitoring, Traffic Violation Detection, Machine Learning, Artificial Intelligence


This research paper focuses on current and previous efforts to detect traffic rule violations. So far, some remarkable works have been discovered, and many approaches for detecting traffic rule violations have been introduced from the current situation. Hence, machine learning has been the main target to detect traffic rule violations. A summary of the frameworks and methods that have been used to solve this problem so far is also provided in this study. This study has been divided into two parts. In the first part, the recent works on traffic rule violations have been portrayed. Moreover, the algorithms and frameworks that have been used so far and major works on violation detection using machine learning can be found in this section. In the second part, this study summarizes a brief discussion based on the image quality, camera resolution, device performance, and accuracy level of the works, as well as the algorithms and frameworks that have been used to conduct the detection of traffic rule violation problems using machine learning.


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How to Cite

K. . Biswas, N. K. Paul, D. Saha, T. Ahmed, and R. Mahmud, “Detection of Traffic Rule Violations Using Machine Learning: An Analytical Review”, Malaysian J. Sci. Adv. Tech., vol. 3, no. 1, pp. 37–47, Mar. 2023.