Combined Road Tracking for Paved Roads and Dirt Roads: LiDAR Measurements and Image Color Modes

Much research has been done on the detection and tracking of paved, preferably marked roads. Less work is available on the detection of dirt roads. The challenge is to provide a framework to track both paved roads and dirt roads. In this paper, we are addressing the problem of developing measurement approaches working for both kinds of roads likewise. For that we fuse LiDAR with vision: First, we present indirect measurements from a static environment model populated with LiDAR data, as well as a new approach for LiDAR measurements from a segmented point cloud. Second, we investigate different image color modes to improve the effectiveness of locating dirt road boundaries using local oriented edge detection. We demonstrate the robustness of our measurements on difficult roads by showing qualitative results from our autonomous vehicles.