A novel license plate detection based Time-To-Collision calculation for forward collision warning using Azure Kinect

Abstract

Forward Collision Warning (FCW) system constantly measures the relative position of the vehicle ahead and then predicts collisions. This paper proposes a new cost-effective and computationally efficient FCW method that uses a time-of-flight (ToF) camera to measure relevant distances to the front vehicle based on license plate detection. First, a Yolo V7 model is used to detect license plates to identify vehicles in front of the ego vehicle. Second, the distance between the front vehicle and the ego vehicle is determined by analyzing the captured depth map by the time-of-flight camera. In addition, the relative speed of the vehicle can be calculated by the direct distance change between the license plate and the camera between two consecutive frames. With a processing speed of 25–30 frames per second, the proposed FCW system is capable of determining relative distances and speeds within 26 meters in the real-time.