Embedded and Parallel Implementation of the Stereo-Vision System for the Autonomous Vehicle

Stereo-vision is the most widely used technique in the development of environmental perception systems for intelligent transportation. The main requirement for the application of stereo vision on a vehicle is the processing time which must be very fast for autonomous driving in real time, whereas the computation of the correspondence of the images in the algorithm of stereo-vision requires a more computing power. This article presents an implementation of the stereo vision system to generate a scene disparity map using the sum of absolute differences (SAD), and the triangulation method for calculating the distance between the obstacle and the stereoscopic system. A parallel treatment is used to speed data processing and this algorithm is implemented in embedded platform. Several experiments are performed from a profiling analysis to have a statistical analysis for optimization.