Robust and Fast Stereovision Based Obstacles Detection for Driving Safety Assistance

摘要

This paper deals with a first evaluation of the efficiency and the robustness of the real-time "v-disparity" algorithm in Stereovision for generic road obstacles detection towards various types of obstacles (vehicle, pedestrian, motorbike, cyclist, boxes) and under adverse conditions (day, night, rain, glowing effect, noise and false matches in the disparity map). The theoretical good properties of the "v-disparity" algorithm -accuracy, robustness, computational speed - are experimentally confirmed. The good results obtained allow us to use this stereo algorithm as the onboard perception process for Driving Safety Assistance: conductor warning and longitudinal control of a low speed automated vehicle (using a second order sliding mode control in difficult and original situations, at frame rate using no special hardware. Results of experiments - Vehicle following at low speed, Stop'n'Go, Stop on Obstacle (pedestrian, fallen motorbike, load dropping obstacle) - are presented.