Abstract
Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average completeness, correctness, and F-measure of 0.96, 0.93, and 0.94, respectively. The time complexity analysis shows that the scan line based road markings extraction method proposed in this paper provides a promising alternative for offline road markings extraction from MLS data.
Highlights
Mobile Mapping Technology (MMT) emerged during the nineties in the twentieth century inspired by the availability of GPS technology for civilian uses
In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, full road points are extracted from the point clouds by moving least squares line fitting
In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake
Summary
Mobile Mapping Technology (MMT) emerged during the nineties in the twentieth century inspired by the availability of GPS technology for civilian uses. There are two typical types of methods to extract road markings from mobile LiDAR point clouds. In [31], In [30], geo-referenced intensity image is generated first by extended IDW method, and thenroad road points are into using a nearest neighbor algorithm to assign intensity to a markings arerasterized recognized by images a point-density-dependent multi-threshold segmentation of thedata intensity regular zebra crossings detected In by[31], Standard. [34], a method that extracts road marking points from 3D road marking points areInextracted fromroad eachpoints segment by multi-thresholding methodand and refined by directly is reported.
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