Road perception and road line detection based on fusion of LiDAR and camera

In recent years, the research of intelligent transportation system has become more and more popular. Whether it was the environmental information around the vehicle, the landmarks on the road or the position of the vehicle itself. It played a very important role in the intelligent traffic control of autonomous mobile intelligent vehicle or vehicle driving assistance system. This paper analyzes the 3D point cloud data collecting and constructing by the radar to obtain the location and distance between the self-propelled vehicle and the road marking in the real environment space. In the part of detecting the road edge, it uses the characteristics of the height difference between the driving road and the sidewalk or fence, as well as the distance between two points in point cloud data and gradient filter to divide road area and non-Road area. In order to obtain more complete and accurate environmental data, the non-road data segmented uses to splice the feature points of the continuous picture through the previous method, and put calculated conversion matrix into the road area to obtain two kinds of information: the non-driving road environment map and the feasible driving road area map. In the 3D map information of drivable pavement area, the lane markings may be extracted from the asphalt pavement and road markings according to the different of LiDAR reflection intensity. Then the road edge detected on the point cloud image is projected onto the 2D color image. The detection and tracking of lane markings on the road area image are realized by image processing method, and the experiment results show that the marking machine or self-propelled vehicle can move along the lane marking accurately.