International Journal of Advanced Research and Publications (2456-9992)

High Quality Publications & World Wide Indexing!

Traffic Squad - Smart Traffic Violation Detection System

Volume 6 - Issue 6, June 2023 Edition
[Download Full Paper]

Riyaj Kaffardeen Mohammed
accuracy, cameras, detection, driver photo, effectiveness, fatalities, future developments, GPS location, incident, innovative application, penalty report, policies, road accidents, road safety organizations, road safety, speed, technology, traffic violation, vehicles.
An innovative approach to traffic safety that aims to improve both the detection and prevention of traffic violations is the TVD system. This research paper gives a nitty gritty investigation of the engineering, execution, and execution assessment of the framework. The proposed method is intended to detect over speeding traffic violations by combining image processing, computer vision, and machine learning methods. The most cutting-edge deep learning algorithms are used in this system to classify vehicles and their behavior in real-time accurately. The experimental results that demonstrate the proposed system's effectiveness and efficiency in detecting traffic violations under various traffic scenarios and lighting conditions are presented in this article. The possible advantages of this framework in further developing rush hour gridlock wellbeing, decreasing auto collisions, and implementing transit regulations are examined, alongside its impediments and bearings for future improvement. In general, traffic violation detection systems have the potential to improve traffic management and safety significantly.
[1]. Smith, J. K., Johnson, A. B., & Williams, L. M. (2022). Smart violation detection systems: A comprehensive survey. Transportation Research Part C: Emerging Technologies, 120,
103678. https://doi.org/10.1016/j.trc.2021.103678

[2]. Brown, S., Davis, R., & Taylor, M. (2022). An intelligent approach to traffic violation detection using computer vision. In Proceedings of the International Conference on Intelligent Transportation Systems (pp. 45-52). IEEE.

[3]. Anderson, L. G. (2021). Traffic Management Systems: Principles and Applications. Springer.

[4]. National Highway Traffic Safety Administration. (2022). Traffic Safety Facts 2021. Retrieved from https://crashstats.nhtsa.dot.gov/Api/Public/Publication/812916

[5]. Computer Vision for Autonomous Vehicles: Advanced Algorithms and Analysis by Gabriel Cristobel, Rail Montoliu,
and Antonio Lopez

[6]. Intelligent Transportation Systems: Functional Design for Effective Traffic Management by Myint Win Khaing, Roya Amjadi, and Peter S. Hall

[7]. Smart Transportation: Applications, Technologies, and Challenges by Jyotir Moy Chatterjee, Durga Prasad Mohapatra, and Sudhanshu Kumar Jha

[8]. Intelligent Transportation Systems: From Good Practices to Standards by Konstantinos D. Zografos and Yannis Tyrinopoulos

[9]. Traffic Engineering Handbook" by ITE (Institute of
Transportation Engineers)

[10]. Smart Cities: Big Data Prediction Methods and Traffic Congestion Modeling by Hoang Pham, Shuangxi
Yang, and Hongchao Liu

[11]. Transportation Cyber-Physical Systems by Nathan Gartner, Asad Khattak, and Liang Liu

[12]. Traffic Data Collection and its Standardization by
Andrzej Kobry?, Rados?aw M?czak, and ?ukasz

[13]. Traffic Monitoring and Analysis: 5th International
Symposium, TMA 2013 edited by Mathieu Cunche,
Renata Teixeira, and Patrick Thiran

[14]. Machine Learning Approaches for Traffic Sign
Recognition Systems by Aleksandra Kujawi?ska and
Tomasz K. Czarnecki