Development of a Vision-Based Driver Assistance System with Lane Departure Warning and Forward Collision Warning Functions

The objective of this research is to develop an advanced driver assistance system with lane departure warning and forward collision warning functions. The main input of this system is a CMOS camera, which is used to acquire roadway image in front of vehicle. In order to extract lane markings and vehicles from roadway image, the image processing methods such as coordinate systems transformation, object detection and object tracking are applied to recognize the lane boundaries and the preceding vehicles. In lane marking recognition, gray scale statistics, dynamic range of interesting (ROI) and featured-based approaches are used to detect lane boundaries successfully. For vehicle recognition, a Sobel edge-enhancement filter and optical flow algorithm are used to implement vehicle detection and tracking. Besides, by means of the roadway and headway physical estimation models, the circumstances of lane departure and forward collision can be detected. The experimental results indicate that the hardware and the implemented algorithm used in this research are able to recognize the lane markings and headway distance precisely, and meet the requirements of real-time computing and high reliability.