Vehicle Safety Management System

The issue of road safety has been of critical importance globally, as road traffic accidents have caused significant harm to individuals and society. Road traffic accidents are estimated to be the cause of 1.35 million deaths annually, according to the World Health Organization[1], making them the eighth leading cause of death worldwide. Overtaking has been one of the key contributors to road accidents, particularly on highways and rural roads. To address this problem, a new overtaking assistance system was proposed in this research paper that provided clear and timely signals to vehicles behind the host vehicle. In recent years, advances in computer vision and sensing technologies have led to the development of intelligent transportation systems that could enhance driving safety and efficiency. In this paper, a real-time overtaking assistance system was proposed that used a combination of the You Only Look Once (YOLO) object detection algorithm and stereo vision techniques to accurately identify and locate vehicles in front of the driver and estimate their distance. Using this information, the vehicles behind the host vehicle were signaled by means of colored signals, helping drivers make informed decisions on the overtaking procedure. The system was developed and tested in real-world scenarios, and the results demonstrated its effectiveness in detecting vehicles and accurately calculating their distances. The details of the system design and testing will be presented in this research paper, and the potential benefits and limitations of the approach will also be discussed.