Detecting Traffic Rule Violations and Promoting Road Safety through Artificial Intelligence

https://doi.org/10.55529/jaimlnn.36.29.41

Authors

  • Sanjid Bin Karim Sezan Department of Computer Science, American International University-Bangladesh, Kuratoli, Dhaka, Bangladesh.
  • Tisha Rahman Department of Computer Science, American International University-Bangladesh, Kuratoli, Dhaka, Bangladesh.
  • Kazi Tanvir School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
  • Nishat Tasnim Department of Computer Science, American International University-Bangladesh, Kuratoli, Dhaka, Bangladesh.
  • Al -Jobair Ibna Ataur Department of Computer Science, American International University-Bangladesh, Kuratoli, Dhaka, Bangladesh.

Keywords:

Violation Detection System, Artificial Intelligence (AI), Speed Detection, Vehicle Detection, Machine Learning Algorithms.

Abstract

Bangladesh faces significant traffic rule violation problems due to chaotic and overcrowded roads, where drivers often ignore traffic signals, switch lanes without warning, and overload vehicles. Pedestrian safety is also a concern, with jaywalking being common. Illegal parking, speeding, and reckless driving contribute to frequent accidents, and there's a lack of awareness and consistent enforcement of traffic rules. In this challenging scenario, YOLOv5 stands out as a practical solution. It's like having a sharp traffic officer who can quickly spot rule violations like running red lights or illegal parking. YOLOv5's abilities help enforce traffic rules more effectively, making the roads safer for everyone in Bangladesh, where road safety is a pressing concern.

Published

2023-10-18

How to Cite

Sanjid Bin Karim Sezan, Tisha Rahman, Kazi Tanvir, Nishat Tasnim, & Al -Jobair Ibna Ataur. (2023). Detecting Traffic Rule Violations and Promoting Road Safety through Artificial Intelligence. Journal of Artificial Intelligence,Machine Learning and Neural Network , 3(06), 29–41. https://doi.org/10.55529/jaimlnn.36.29.41

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