Kumar, Pankaj and Lewis, Paul and McElhinney, Conor P. and Rahman, Alias Abdull (2015) An Algorithm for Automated Estimation of Road Roughness from Mobile Laser Scanning Data. The Photogrammetric Record, 30 (149). pp. 30-45. ISSN 1477-9730

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Abstract

Road roughness is the deviation of a road surface from a designed surface grade that influences safety conditions for road users. Mobile laser scanning (MLS) systems provide a rapid, continuous and cost-effective way of collecting highly accurate and dense 3D point-cloud data along a route corridor. In this paper an algorithm for the automated estimation of road roughness from MLS data is presented, where a surface grid is fitted to the lidar points associated with the road surface. The elevation difference between the lidar points and their surface grid equivalents provides residual values in height which can be used to estimate roughness along the road surface. Tests validated the new road-roughness algorithm by successfully estimating surface conditions on multiple road sections. These findings contribute to a more comprehensive approach to surveying road networks.

Item Type:	Article
Keywords:	elevation residual; lidar; mobile laser scanning; roughness; surface grid;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
Item ID:	8079
Identification Number:	https://doi.org/10.1111/phor.12090
Depositing User:	Dr. Paul Lewis
Date Deposited:	28 Mar 2017 09:56
Journal or Publication Title:	The Photogrammetric Record
Publisher:	Wiley
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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