A novel road traffic accidents recognition model for intersections in mixed-traffic environment using deep learning-based scene and feature understanding

This research investigated the complex combination of factors that describe road accidents in mixed-traffic scenarios: a point-of-view that is closer to real-world environments than the specific scope used in other contemporary studies. The developed state-of-the-art approach studies the overall traffic scene, identifies minute accident features and tracks the movement of observed road users to determine the probability of accident occurrences. This outcome has massive applications in smart cities and transportation, including automated accident detection, swifter emergency response dispatch, and smart vehicle navigation in accident scenarios, providing a platform for further research into contextually-deeper road behavior analytics in an AI-driven world.