Traffic Rules Violation Detection using Machine Learning Techniques

Abstract

Due to the growing population and people's need for comfort, more automobiles are being purchased, particularly in urban areas. This can result in heavy traffic, indicating that traffic violations are becoming more dangerous in every corner of the world. As a result, people's awareness decreases, and there are more accidents, which may result in the loss of many lives. These situations necessitate the need to develop traffic violation detection systems to automate traffic regulations and eliminate the unawareness among human population. The proposed traffic violation detector can identify signal violations, and the individuals are informed that they will be apprehended if they break a traffic law. The proposed system is faster and efficient than human, as known already traffic police is the one who captures the image of individuals violating traffic rule but the traffic police will not be able to capture more than one violation simultaneously. The proposed system can detect most common types of traffic violations in real-time through computer vision techniques and it also leverages good results with great accuracy.