Open AccessRibbon Road Surface Filtering in Vehicle-Borne Laser Scanning Point Cloud Data
Author(s) -
Min Chen,
Rufei Liu,
Shaopeng Ding
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/783/1/012135
Subject(s) - point cloud , terrain , computer science , laser scanning , intersection (aeronautics) , trajectory , road surface , computer vision , remote sensing , artificial intelligence , laser , geography , engineering , optics , physics , civil engineering , cartography , astronomy
Terrain data of road is the most commonly used basic data by the traffic department. The high-precision three-dimensional road data can restore the terrain features under the real scene, which has a wider application range. In order to obtain high-precision three-dimensional point cloud road data, taking the vehicle-borne laser scanning data as the research object, a method of ground filtering for ribbon road is proposed. First, the driving trajectory information of the road data collected by the vehicle is read. Then, according to the road characteristics, characteristics of the vehicle driving trajectory is used to control processing direction, and a grid index of the point cloud data is created. Second, feature descriptors based on the spatial distribution characteristics of road point cloud data are established, and rough road point cloud data is obtained. Finally, the profile data of the vehicle-borne laser point cloud in the vertical trajectory driving direction is extracted, and the accurate ribbon road and the micro-terrain data on both sides are obtained by the horizontal constraint line detection algorithm. The experiment and analysis are carried out by using two different ribbon road data. Experimental results show that the method can be applied to different road scenes.