Vision-based driving environment identification for autonomous highway vehicles

In this paper, we propose an approach to identify the driving environment for autonomous highway vehicles by means of image processing and computer vision techniques. The proposed approach is mainly composed of two consecutive computational steps. The first step is the lane markings detection, used to identify the location of host vehicle and road geometry. The second one is the vehicle detection that can provide relative position and speed between host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenes. Herein, the experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.