Semi-Automated Generation of Road Transition Lines Using Mobile Laser Scanning Data

Abstract

This paper recognizes the research gaps and difficulties in generating transition lines (the paths that pass through a road intersection) in road intersections from mobile laser scanning (MLS) point clouds. The proposed method contains three modules: road surface detection, lane marking extraction, and transition line generation. First, the points covering the road surface are extracted using the voxel-based upward growing and the improved region growing. Then, lane markings are extracted and identified according to the multi-thresholding and the geometric filtering. Finally, transition lines are generated through a combination of the lane node structure generation algorithm and the cubic Catmull–Rom spline algorithm. The experimental results demonstrate that transition lines can be successfully generated for both T- and cross-intersections with promising accuracy. In the validation of lane marking extraction using the manually interpreted lane marking points, the method can achieve average precision, recall, and F1-score of 90.80%, 92.07%, and 91.43%, respectively. The success rate of transition line generation is 96.5%. Furthermore, the buffer-overlay-statistics (BOS) method validates that the proposed method can generate lane centerlines and transition lines within 20-cm-level localization accuracy from the MLS point clouds.