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Lane Surface Identification Based on Reflectance using Laser Range Finder
dc.contributor.author | Cáceres Hernández, Danilo | |
dc.contributor.author | Hyun Jo, Kang | |
dc.contributor.author | Dung Hoang, Van | |
dc.date.accessioned | 2018-06-27T20:55:24Z | |
dc.date.accessioned | 2018-06-27T20:55:24Z | |
dc.date.available | 2018-06-27T20:55:24Z | |
dc.date.available | 2018-06-27T20:55:24Z | |
dc.date.issued | 12/13/2014 | |
dc.date.issued | 12/13/2014 | |
dc.identifier | https://ieeexplore.ieee.org/abstract/document/7028110/ | |
dc.identifier.uri | http://ridda2.utp.ac.pa/handle/123456789/5081 | |
dc.identifier.uri | http://ridda2.utp.ac.pa/handle/123456789/5081 | |
dc.description | In striving to achieve autonomous navigation the problem of guidance is a major difficulty faced by fully autonomous vehicle. In this paper, the authors focus on unconventional methods of identifying lane markings on a road surface through Laser Measurement System (LMS). This was achieved by taking advantage of the reflection of the laser beam. This method was executed in three steps, firstly to detect lane markings we employed the spatial clustering of applications with noise (DBSCAN) method. Secondly, in order to determine the surface course a distance clustering analysis was implemented and lastly, the road geometry design was estimated with preliminary results being gathered and tested on a group of consecutive frames to prove its effectiveness. | en_US |
dc.description.abstract | In striving to achieve autonomous navigation the problem of guidance is a major difficulty faced by fully autonomous vehicle. In this paper, the authors focus on unconventional methods of identifying lane markings on a road surface through Laser Measurement System (LMS). This was achieved by taking advantage of the reflection of the laser beam. This method was executed in three steps, firstly to detect lane markings we employed the spatial clustering of applications with noise (DBSCAN) method. Secondly, in order to determine the surface course a distance clustering analysis was implemented and lastly, the road geometry design was estimated with preliminary results being gathered and tested on a group of consecutive frames to prove its effectiveness. | en_US |
dc.format | application/pdf | |
dc.format | text/html | |
dc.language | eng | |
dc.rights | info:eu-repo/semantics/embargoedAccess | |
dc.subject | Roads | en_US |
dc.subject | Laser beams | en_US |
dc.subject | Surface emitting lasers | en_US |
dc.subject | Navigation | en_US |
dc.subject | Vehicles | en_US |
dc.subject | Measurement by laser beam | en_US |
dc.subject | Roads | |
dc.subject | Laser beams | |
dc.subject | Surface emitting lasers | |
dc.subject | Navigation | |
dc.subject | Vehicles | |
dc.subject | Measurement by laser beam | |
dc.title | Lane Surface Identification Based on Reflectance using Laser Range Finder | en_US |
dc.type | info:eu-repo/semantics/article | |
dc.type | info:eu-repo/semantics/publishedVersion |
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