CVROIVApr 16, 2023

Vehicle Safety Management System

arXiv:2304.14497v1h-index: 1
Originality Synthesis-oriented
AI Analysis

This system addresses safety issues for drivers during overtaking maneuvers, particularly on busy roads, but it is incremental as it applies existing methods to a specific driving scenario.

The study tackled the problem of overtaking safety by developing a real-time assistance system that combines YOLO object detection and stereo vision to identify vehicles and estimate distances, achieving an approximate error of 4.107% in distance accuracy.

Overtaking is a critical maneuver in driving that requires accurate information about the location and distance of other vehicles on the road. This study suggests a real-time overtaking assistance system that uses 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. The system then signals the vehicles behind the driver using colored lights to inform them of the safe overtaking distance. The proposed system has been implemented using Stereo vision for distance analysis and You Only Look Once (YOLO) for object identification. The results demonstrate its effectiveness in providing vehicle type and the distance between the camera module and the vehicle accurately with an approximate error of 4.107%. Our system has the potential to reduce the risk of accidents and improve the safety of overtaking maneuvers, especially on busy highways and roads.

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