Evaluation of Technologies for Road Profile Capture, Analysis, and Evaluation
Publication: Journal of Surveying Engineering
Volume 141, Issue 1
Abstract
Many transportation agencies in the United States are transitioning to using the International Roughness Index (IRI) in pavement smoothness evaluation as part of an incentive/disincentive program for contractors paving roads. This study evaluates the use of digital levels, inertial profilers, inclinometer-based profilers, and terrestrial laser scanning (TLS) in pavement profile capture and analyses. Traditionally, analyses evaluated elevation differences between profiles. However, evolving standards and procedures perform incremental slope-based analyses to calculate IRI and correlate between profiles, which correspond better to vehicle response. The results of this study show consistent elevation profiles between all of the devices, when operated properly. However, digital levels cannot be used efficiently to capture the road profile at high sampling () intervals for long profiles. Thus, TLS shows additional advantages compared with the other techniques, including the ability to collect a large, dense set of data relatively quickly for the entire roadway and surrounding areas; hence, the data can serve multiple purposes, including validation of other design parameters such as transverse and longitudinal slope. However, TLS requires substantially more processing and training.
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Acknowledgments
The Oregon DOT (ODOT) and the Federal Highway Administration (FHWA) funded this research through SPR-744. The authors thank George Chang from Transtec Group for his comments and insights. Keith Williams, Jeremy Conner, John Raugust, Hamid Mahmoudabadi, William White, Mahyar Sharifi-Mood, and Kris Puderbaugh assisted in the field work. Dean Chess at ODOT was instrumental in helping this project get started. Norris Shippen (ODOT), Michael Stennett (ODOT), Larry Ilg (ODOT), Jim Huddleston (Asphalt Pavement Association of Oregon), and Anthony Boesen (FHWA) served on the Technical Advisory Committee. Leica Geosystems and David Evans and Associates provided the equipment and software used in this study. Maptek I-Site also provided software used in this study. The authors appreciate the anonymous reviewers who provided helpful feedback to this paper.
References
AASHTO. (2010a). “Accepting pavement ride quality when measured using inertial profiling systems.” AASHTO-R54-10, Washington, DC.
AASHTO. (2010b). “Certification of inertial profiling systems.” AASHTO-R56-10, Washington, DC.
AASHTO. (2010c). “Standard specification for inertial profiler.” AASHTO-M328-10, Washington, DC.
Armstrong, M. L. (2010). Oregon coordinate reference system handbook and user guide version 2.00, 〈http://www.oregon.gov/ODOT/HWY/GEOMETRONICS/docs/ocrs_handbook_user_guide.pdf〉 (May 14, 2013).
ASTM. (2005). “Standard test method for measuring road roughness by static level method.” E1364-95, West Conshohocken, PA.
Chang, J., Chang, K., and Chen, D. (2006). “Application of 3D laser scanning on measuring pavement roughness.” J. Test. Eval., 34(2), 83–91.
Dyer, S. A., and Dyer, J. S. (2008). “Implementation problems in inertial road-profiling: An overview.” Proc., Int. Instrumentation and Measurement Technology Conf., IEEE, Los Alamitos, CA, 1520–1525.
Hays, J. D. (2006). “Comparison of new technology for measuring ride quality.” M.S. thesis, Auburn Univ.
Jaselskis, E. J., Gao, Z., and Walters, R. C. (2005). “Improving transportation projects using laser scanning.” J. Constr. Eng. Manage., 377–384.
Johnson, W. H., and Johnson, A. M. (2012). “Operational considerations for terrestrial laser scanner use in highway construction applications.” J. Surv. Eng., 214–222.
Karamihas, S. M. (2004). “Development of cross correlation for objective comparison of profiles.” Int. J. Veh. Des., 36(2/3), 173–193.
Karamihas, S. M. (2005). “Critical profiler accuracy requirements.” Rep. No. 2005-24, Univ. of Michigan Transportation Research Institute, Ann Arbor, MI.
Karamihas, S. M. (2011). “Improving the quality of pavement profiler measurement.” Benchmark Test Evaluation Rep. TPF-5(063), Federal Highway Administration, Washington, DC.
Laefer, D. F., Fitzgerald, M., Maloney, E. M., Coyne, D., Lennon, D., and Morrish, S. W. (2009). “Lateral image degradation in terrestrial laser scanning.” Struct. Eng. Int., 19(2), 184–189.
Lee, M.-H., and Chou, C.-P. (2010). “Laboratory method for inertial profiler verification.” J. Chin. Inst. Eng., 33(4), 617–627.
Olsen, M. (2011). “Bin ‘N’ Grid: A simple program for statistical filtering of point cloud data.” 〈http://www.lidarnews.com/content/view/8378/206/〉 (May 15, 2013).
Olsen, M. J., and Chin, A. (2012). “Inertial and inclinometer-based profiler repeatability and accuracy using the IRI model.” Technical Rep. SPR-744, Oregon DOT, Salem, OR.
Olsen, M. J., Johnstone, E., Driscoll, N., Ashford, S. A., and Kuester, F. (2009). “Terrestrial laser scanning of extended cliff sections in dynamic environments: Parameter analysis.” J. Surv. Eng., 161–169.
Olsen, M. J., Johnstone, E., Kuester, F., Driscoll, N., and Ashford, S. A. (2011). “New automated point-cloud alignment for ground-based light detection and ranging data of long coastal sections.” J. Surv. Eng., 14–25.
Olsen, M. J., Roe, G. V., Glennie, C., Persi, F., and Reedy, M. (2013). “Guidelines for the use of mobile LIDAR in transportation applications.” NCHRP Rep. 748, Transportation Research Board, Washington, DC.
PROVAL [Computer software]. Austin, TX, Transtec Group.
Pulli, K. (1999). “Multiview registration for large data sets.” Proc., 2nd Int. Conf. on 3D Digital Imaging and Modeling, IEEE, Los Alamitos, CA, 160–168.
Robson, J. D. (1979). “Road surface description and vehicle response.” Int. J. Veh. Des., 1(1), 25–35.
Sayers, M. W., Gillespie T. D., and Paterson, W. D. O. (1986). “Guidelines for conducting and calibrating road roughness measurements.” World Bank Technical Paper No. 46, The World Bank, Washington, DC.
Sayers, M. W., and Karamihas, S. M. (1998). The little book of profiling, Regent of the Univ. of Michigan, Farmington Hills, MI.
Silvia, E. P., and Olsen, M. J. (2012). “To level or not to level: Laser scanner inclination sensor stability and application.” J. Surv. Eng., 117–125.
Slattery, K. T., Slattery, D. K., and Peterson, J. P. (2012). “Road construction earthwork volume calculation using three-dimensional laser scanning.” J. Surv. Eng., 96–99.
SurPRO. (2011). “SurPRO.” 〈http://www.surpro.com/〉 (Oct. 12, 2011).
Tang, P., Huber, D., and Akinci, B. (2011). “Characterization of laser scanners and algorithms for detecting flatness defects on concrete surfaces.” J. Comput. Civ. Eng., 31–42.
Transtec Group. (2008). “Smooth pavements.” 〈http://www.smoothpavements.com/〉 (May 15, 2013).
Vosselman, G., and Mass, H.-G., eds. (2010). Airborne and terrestrial laser scanning, Whittles, Caithness, U.K.
Yi, Z., and Rong-Gui, M. (2009). “A study of pavement roughness measurement system based on laser ranger finder.” Proc., Int. Conf on Image Analysis and Signal Processing (IASP), IEEE, Los Alamitos, CA, 295–299.
Yu, S.-J., Sukumar, S. R., Koschan, A. F., Page, D. L., and Abidi, M. A. (2007). “3D reconstruction of road surfaces using an integrated multi-sensory approach.” Opt. Lasers Eng., 45(7), 808–818.
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Published In
Journal of Surveying Engineering
Volume 141 • Issue 1 • February 2015
Copyright
© 2014 American Society of Civil Engineers.
History
Received: May 21, 2013
Accepted: Feb 12, 2014
Published online: May 2, 2014
Published in print: Feb 1, 2015
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