Abstract: Intelligent Traffic Rules Violation Detector uses artificial intelligence and deep learning techniques to detect vehicle violating traffic rules. The increasing number of vehicles on the road has led to a rise in traffic congestion and accidents. To address this issue, we propose an Intelligent Traffic Rules Violation Detector (ITRVD) system that uses computer vision and machine learning techniques to detect traffic rule violations in real-time. The system consists of cameras installed at traffic intersections, which capture images of vehicles and pedestrians. These images are then processed using object detection algorithms to identify vehicles, pedestrians, and traffic signals. Machine learning algorithms are used to analyse the behaviour of vehicles and pedestrians and detect traffic rule violations such as running red lights, speeding, and pedestrian non- compliance. The system alerts authorities in real-time, enabling swift action to be taken against violators. Experimental results show that the ITRVD system achieves high accuracy in detecting traffic rule violations, making it a valuable tool for improving road safety and reducing traffic congestion.

Keywords: Intelligent Transportation Systems, Traffic Rule Violation Detection, Computer Vision, Machine Learning, Road Safety.

| DOI: 10.17148/IARJSET.2024.111271