A computer vision system for detection and avoidance for automotive vehicles

This paper presents a vision based algorithm for obstacle detection and avoidance for autonomous land vehicle. For an efficient algorithm it is necessary to know the information about surrounding environment of vehicle. The whole environment is classified in two groups as obstacle and path. This classification helps to find the space for avoiding the obstacle. Data is acquired by a high resolution digital camera. Relative distance of the obstacle, dimension of the obstacle, turning radius of the vehicle and required turning angle of the steering are estimated. The simulation is done using MATLAB 7.1 version.