Campus Units

Civil, Construction and Environmental Engineering

Document Type

Conference Proceeding

Conference

2015 Conference on Autonomous and Robotic Construction of Infrastructure

Publication Version

Published Version

Publication Date

2015

Journal or Book Title

Proceedings of the 2015 Conference on Autonomous and Robotic Construction of Infrastructure

First Page

21

Last Page

33

Conference Title

Conference on Autonomous and Robotic Construction of Infrastructure

Conference Date

June 2-3, 2015

City

Ames, IA

Abstract

Road roughness is a key parameter for controlling pavement construction processes and for assessing ride quality of both paved and unpaved roads. This paper describes algorithms used in processing three-dimensional (3D) stationary terrestrial laser scanning (STLS) point clouds to obtain surface maps of point wise indices that characterize pavement roughness. The backbone of the analysis is a quarter-car model simulation over a spatial 3D mesh grid representing the pavement surface. Two case studies are presented, and results show high spatial variability in the roughness indices both longitudinally and transversely (i.e., different wheel path positions). It is proposed that road roughness characterization using a spatial framework provides more details on the severity and location of roughness features compared to the one-dimensional methods. This paper describes approaches that provide an algorithmic framework for others collecting similar STLS 3D spatial data to be used in advanced road roughness characterization.

Comments

This is a paper from Proceedings of the 2015 Conference on Autonomous and Robotic Construction of Infrastructure, which can be found in full at: http://lib.dr.iastate.edu/intrans_reports/141/.

Copyright Owner

Iowa State University

Language

en

File Format

application/pdf

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