A Traffic Accident Detection Model using Metadata Registry

In this research, we suggested a traffic accident detection model and installed a system for automatically detecting, recording, and reporting traffic accidents at intersections. A system with these properties would be beneficial in determining the cause of accidents and the features of the intersection that impact safety. Additionally, we suggested and designed the metadata registry for the system to improve the interoperability. In a field test, the suggested model achieved a false alarm rate (FAR) of 0.34 times 10^-6 percent. Considering that a California #7a algorithm (expressway incident detection algorithm) showed a FAR of 0.08 ~ 0.34 percent, our result is a remarkable achievement