Extraction of road boundary from MLS data using laser scanner ground trajectory
Various means of extracting road boundary from mobile laser scanning data based on vehicle trajectories have been investigated. Independent of positioning and navigation data, this study estimated the scanner ground track from the spatial distribution of the point cloud as an indicator of road locat...
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doaj-342ba11202804680a621701aa837abc32021-10-03T07:42:32ZengDe GruyterOpen Geosciences2391-54472021-06-0113169070410.1515/geo-2020-0264Extraction of road boundary from MLS data using laser scanner ground trajectorySui Lichun0Zhu Jianfeng1Zhong Mianqing2Wang Xue3Kang Junmei4College of Geological Engineering and Geomatics, Chang’an University, Xi’an, Shaanxi 710054, ChinaCollege of Geological Engineering and Geomatics, Chang’an University, Xi’an, Shaanxi 710054, ChinaFaculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, ChinaCollege of Resources Environment and History Culture, Xianyang Normal University, Xianyang, 712025, ChinaCollege of Geological Engineering and Geomatics, Chang’an University, Xi’an, Shaanxi 710054, ChinaVarious means of extracting road boundary from mobile laser scanning data based on vehicle trajectories have been investigated. Independent of positioning and navigation data, this study estimated the scanner ground track from the spatial distribution of the point cloud as an indicator of road location. We defined a typical edge block consisting of multiple continuous upward fluctuating points by abrupt changes in elevation, upward slope, and road horizontal slope. Subsequently, such edge blocks were searched for on both sides of the estimated track. A pseudo-mileage spacing map was constructed to reflect the variation in spacing between the track and edge blocks over distance, within which road boundary points were detected using a simple linear tracking model. Experimental results demonstrate that the ground trajectory of the extracted scanner forms a smooth and continuous string just on the road; this can serve as the basis for defining edge block and road boundary tracking algorithms. The defined edge block has been experimentally verified as highly accurate and strongly noise resistant, while the boundary tracking algorithm is simple, fast, and independent of the road boundary model used. The correct detection rate of the road boundary in two experimental data is more than 99.2%.https://doi.org/10.1515/geo-2020-0264edge blockscanner ground trackpseudo-mileage spacing mapboundary tracking |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sui Lichun Zhu Jianfeng Zhong Mianqing Wang Xue Kang Junmei |
spellingShingle |
Sui Lichun Zhu Jianfeng Zhong Mianqing Wang Xue Kang Junmei Extraction of road boundary from MLS data using laser scanner ground trajectory Open Geosciences edge block scanner ground track pseudo-mileage spacing map boundary tracking |
author_facet |
Sui Lichun Zhu Jianfeng Zhong Mianqing Wang Xue Kang Junmei |
author_sort |
Sui Lichun |
title |
Extraction of road boundary from MLS data using laser scanner ground trajectory |
title_short |
Extraction of road boundary from MLS data using laser scanner ground trajectory |
title_full |
Extraction of road boundary from MLS data using laser scanner ground trajectory |
title_fullStr |
Extraction of road boundary from MLS data using laser scanner ground trajectory |
title_full_unstemmed |
Extraction of road boundary from MLS data using laser scanner ground trajectory |
title_sort |
extraction of road boundary from mls data using laser scanner ground trajectory |
publisher |
De Gruyter |
series |
Open Geosciences |
issn |
2391-5447 |
publishDate |
2021-06-01 |
description |
Various means of extracting road boundary from mobile laser scanning data based on vehicle trajectories have been investigated. Independent of positioning and navigation data, this study estimated the scanner ground track from the spatial distribution of the point cloud as an indicator of road location. We defined a typical edge block consisting of multiple continuous upward fluctuating points by abrupt changes in elevation, upward slope, and road horizontal slope. Subsequently, such edge blocks were searched for on both sides of the estimated track. A pseudo-mileage spacing map was constructed to reflect the variation in spacing between the track and edge blocks over distance, within which road boundary points were detected using a simple linear tracking model. Experimental results demonstrate that the ground trajectory of the extracted scanner forms a smooth and continuous string just on the road; this can serve as the basis for defining edge block and road boundary tracking algorithms. The defined edge block has been experimentally verified as highly accurate and strongly noise resistant, while the boundary tracking algorithm is simple, fast, and independent of the road boundary model used. The correct detection rate of the road boundary in two experimental data is more than 99.2%. |
topic |
edge block scanner ground track pseudo-mileage spacing map boundary tracking |
url |
https://doi.org/10.1515/geo-2020-0264 |
work_keys_str_mv |
AT suilichun extractionofroadboundaryfrommlsdatausinglaserscannergroundtrajectory AT zhujianfeng extractionofroadboundaryfrommlsdatausinglaserscannergroundtrajectory AT zhongmianqing extractionofroadboundaryfrommlsdatausinglaserscannergroundtrajectory AT wangxue extractionofroadboundaryfrommlsdatausinglaserscannergroundtrajectory AT kangjunmei extractionofroadboundaryfrommlsdatausinglaserscannergroundtrajectory |
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1716846096885481472 |