AN AUTOMATED ROAD ROUGHNESS DETECTION FROM MOBILE LASER SCANNING DATA
Rough roads influence the safety of the road users as accident rate increases with increasing unevenness of the road surface. Road roughness regions are required to be efficiently detected and located in order to ensure their maintenance. Mobile Laser Scanning (MLS) systems provide a rapid and cos...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-05-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1-W1/91/2017/isprs-archives-XLII-1-W1-91-2017.pdf |
| Summary: | Rough roads influence the safety of the road users as accident rate increases with increasing unevenness of the road surface. Road
roughness regions are required to be efficiently detected and located in order to ensure their maintenance. Mobile Laser Scanning
(MLS) systems provide a rapid and cost-effective alternative by providing accurate and dense point cloud data along route corridor.
In this paper, an automated algorithm is presented for detecting road roughness from MLS data. The presented algorithm is based on
interpolating smooth intensity raster surface from LiDAR point cloud data using point thinning process. The interpolated surface is
further processed using morphological and multi-level Otsu thresholding operations to identify candidate road roughness regions. The
candidate regions are finally filtered based on spatial density and standard deviation of elevation criteria to detect the roughness along
the road surface. The test results of road roughness detection algorithm on two road sections are presented. The developed approach
can be used to provide comprehensive information to road authorities in order to schedule maintenance and ensure maximum safety
conditions for road users. |
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| ISSN: | 1682-1750 2194-9034 |