4Review on Machine Learning‐based Traffic Rules Contravention Detection System

Jahnavi1 and Urvashi2

1Department of Computer Science, Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, India

2Department of Computer Science and Engineering, Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, India

4.1 Introduction

The primary goal of developing a traffic rule violation system is to detect numerous offenses committed by defaulters on the road so that severe action can be taken against them to lower the number of fatalities brought on by accidents. Initially, monitoring a large volume of traffic on the roads was done by a single individual, which was problematic as it was more prone to errors due to limited human memory capacity [1]. To solve this issue, a system was introduced that operates 24/7 without the need for human intervention and can accurately detect multiple traffic violations with a high degree of precision. The traffic rule violation detecting system works in conjunction with a surveillance system established along highways and roads. To obtain vital information, these surveillance cameras record images of license plates from vehicles involved in infractions. Computer vision techniques and machine learning algorithms are used to process and analyze the collected photos and videos. This entails collecting relevant information from visual data, such as vehicle position, speed, lane adherence, and traffic signal status [18]. To detect instances ...

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