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Point Cloud Based Road Surface Modelling and Assessment

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Link to refer to this document:
10.3311/BMEZalaZONE2022-015
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  • Conference on BME ZalaZONE 2022 [22]
Abstract
Creating digital twins of the built environment based on point clouds broadens its application area; point clouds of buildings support BIM (Building Information Modeling) while the digital twins of road surfaces support transportation applications. Point clouds acquired by current TLS (Terrestrial Laser Scanning) or by MLS (Mobile Laser Scanning) systems represent the road surface with high accuracy, and resolution (i.e. with small point spacing). In particular applications extreme high accuracy and robustness is required; the paper discusses surveying and assessment of vehicle test track, including a braking platform. Both the surveying method (TLS supported by Total Station measurements) and the data processing workflow are presented. The potential evaluation results are discussed in detail; semi-automatically created 2D sections and deviation maps shows how the current state of the pavement differs from the as-designed geometry. The investigations proved that point-cloud based data acquisition methods enable deriving high accuracy and high-resolution road surface models.
Title
Point Cloud Based Road Surface Modelling and Assessment
Author
Lovas, Tamás
Baranyai, Dániel
Somogyi, Árpád
Date of issue
2022
Access level
Open access
Copyright owner
Budapest University of Technology and Economics
Conference title
The First Conference on ZalaZONE Related R&I Activities of Budapest University of Technology and Economics 2022
Conference place
Budapest University of Technology and Economics
Conference date
2022.03.31
Language
en
Page
71 - 74
Subject
MLS, OpenCRG, point cloud, TLS
Version
Kiadói változat
Identifiers
DOI: 10.3311/BMEZalaZONE2022-015
Title of the container document
Proceedings of The First Conference on ZalaZONE Related R&I Activities of Budapest University of Technology and Economics 2022
ISBN, e-ISBN
ISBN 978-963-421-873-9
University
Budapest University of Technology and Economics
Faculty
Faculty of Transportation Engineering and Vehicle Engineering
Department
Department of Automotive Technologies

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DSpace software copyright © 2002-2016  DuraSpace
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Contact Us | Send Feedback
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