A Real-Time Collision Detection System for Vehicles

A real-time collision detection system has become a crucial safety feature in vehicles today, mainly after the evolution of autonomous and self-driving vehicles. It is proved to be very effective in minimizing the number of road accidents. This paper presents an algorithm for a real-time detection system using the deep learning technology based on Mask-RCNN (Mask-Region based Convolutional Neural Network). We prepared a custom dataset from scratch to experiment with our algorithm and a detailed analysis of the results are provided. Experiments indicate that the developed algorithm gives highly accurate results. We achieved more than 95% accuracy with overall prediction score of greater than 0.90.