  In this paper, we studied a SLAM method for vector-based road structure
mapping using multi-beam LiDAR. We propose to use the polyline as the primary
mapping element instead of grid cell or point cloud, because the vector-based
representation is precise and lightweight, and it can directly generate
vector-based High-Definition (HD) driving map as demanded by autonomous driving
systems. We explored: 1) the extraction and vectorization of road structures
based on local probabilistic fusion. 2) the efficient vector-based matching
between frames of road structures. 3) the loop closure and optimization based
on the pose-graph. In this study, we took a specific road structure, the road
boundary, as an example. We applied the proposed matching method in three
different scenes and achieved the average absolute matching error of 0.07. We
further applied the mapping system to the urban road with the length of 860
meters and achieved an average global accuracy of 0.466 m without the help of
high precision GPS.
