Segmentation of Vehicles and Roads by a Low-Channel Lidar

An effective method to segment vehicles and roads is proposed for autonomous vehicles using low-channel 3D lidar. The distance-view transformation is newly proposed to overcome the low density of top-view data of lidar. In addition, a dilated convolution structure is proposed to expand the receptive field of a convolutional neural network. The proposed network improves the accuracy of segmentation. The experimental results are presented to verify the usefulness of the proposed method.