Comparison of roadway roughness derived from LIDAR and SFM 3D point clouds.

Alhasan, Ahmad; Younkin, Kyle; White, David J.; Iowa State University. Earthworks Engineering Research Center

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ROSA P serves as an archival repository of USDOT-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by USDOT or funded partners. As a repository, ROSA P retains documents in their original published format to ensure public access to scientific information.

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Comparison of roadway roughness derived from LIDAR and SFM 3D point clouds.

2015-10-01
By Alhasan, Ahmad ; Younkin, Kyle ; White, David J.

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English

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Creators:

Alhasan, Ahmad ; Younkin, Kyle ; White, David J.

Alhasan, Ahmad ; Younkin, Kyle ; White, David J. Less -
Corporate Creators:

Iowa State University. Earthworks Engineering Research Center
Corporate Contributors:

Iowa. Dept. of Transportation
Subject/TRT Terms:

[+]

Asphalt Concrete Evaluation Gravel Roads Laser Radar Pavements Photogrammetry Portland Cement Concrete Roughness Test Sections
Publication/ Report Number:

InTrans Project 15-543
Resource Type:

Tech Report
Geographical Coverage:

Iowa
Corporate Publisher:

Iowa State University. Institute for Transportation
Abstract:

This report describes a short-term study undertaken to investigate the potential for using dense three-dimensional (3D) point

clouds generated from light detection and ranging (LIDAR) and photogrammetry to assess roadway roughness. Spatially

continuous roughness maps have potential for the identification of localized roughness features, which would be a significant

improvement over traditional profiling methods. This report specifically illustrates the use of terrestrial laser scanning (TLS) and

photogrammetry using a process known as structure from motion (SFM) to acquire point clouds and illustrates the use of these

point clouds in evaluating road roughness. Five roadway sections were chosen for scanning and testing: three gravel road

sections, one portland cement concrete (PCC) section, and one asphalt concrete (AC) section. To compare clouds obtained from

terrestrial laser scanning and photogrammetry, the coordinates of the clouds for the same section on the same date were matched

using open source computer code. The research indicates that the technologies described are very promising for evaluating road

roughness. The major advantage of both technologies is the large amount of data collected, which allows the evaluation of the full

surface. Additional research is needed to further develop the use of dense 3D point clouds for roadway assessment.
Format:

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US Transportation Collection
Main Document Checksum:

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urn:sha256:63102d03296b2a74f73c63c714fe1a4a1d860e9e6d052da1ac5f19eaf3de35ab
Download URL:

https://rosap.ntl.bts.gov/view/dot/29591/dot_29591_DS1.pdf
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Comparison of roadway roughness derived from LIDAR and SFM 3D point clouds.

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