Research on vehicle collision traffic accident detection system based on YOLOv5 algorithm

As the number of vehicles in the world has soared, the rate of traffic accidents has increased, resulting in serious casualties, property damage and stress on transportation systems. Therefore, this project uses deep learning technology to develop vehicle collision detection methods, adopts YOLOv5 algorithm for vehicle target detection, and determines collision through intersection ratio. Based on Microsoft COCO dataset, a customized "Vehicle dataset" was constructed, and ring coding technology was added to improve the detection accuracy. The collision was detected by calculating the overlapping area of rectangular box IoU, and the GUI interface was designed by PyQt5, and the system was built for testing. The results proved the effectiveness of the system.