Vehicle Detection for Accident Prevention

Abstract

Abstract: One of the key components of the smart traffic concept is vehicle detection and tracking. Modern city planning and development is impossible to achieve without a thorough understanding of the city's existing traffic flows. Surveillance video is an underutilized source of traffic data that can be discovered using a wide range of information technology tools and solutions, including machine learning techniques. A critical step in these systems is robust and reliable vehicle detection. It employs an object detection model to locate vehicles in images captured by an outdoor surveillance camera. A review of recent vision-based on-road vehicle detection systems is presented in this paper. YOLO generates a region proposal network and classifies these region proposals at the same time. The purpose of this paper is to address the issues raised above. This model has good performance in object detection.