A fast and robust vision based road following algorithm

Abstract

This article presents a fast and robust method designed to detect and track a road lane from images provided by an on-board monocular monochromatic camera. The detection method is based upon a model driven algorithms. It uses a statistical model of the lane which permits to manage the occlusions or imperfections of road marking. This model is obtained by an off-line training phase. The detections are made in optimal interest zones deduced from the model. The tracking process permits to locate the vehicle on its lane and gives the confidence interval of the roadside for the next image. The method has been applied both on marked and unmarked roads images. The results obtained on image sequences of real road scenes show the robustness and precision of the proposed approach.