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First published January 2000

Investigation of Relationship Between Roughness and Pavement Surface Distress Based on WesTrack Project

Abstract

Modern pavement rehabilitation and design methodologies require an adequate evaluation of the functional capacity of pavements. A key component of this functional capacity is the roughness of the pavement. The current standard for characterization of a pavement’s roughness is the international roughness index (IRI). Pavement roughness measurements were conducted at regular intervals during the application of approximately 5 million equivalent single-axle loads at the WesTrack Project, a full-scale flexible pavement accelerated loading facility located near Reno, Nevada. The results are presented of an investigation into the relationship between pavement roughness and pavement surface distress using WesTrack data. With a sample population of 317 observations, a relationship was found among the roughness (IRI) and the initial IRI, percentage of fatigue cracking, and average rut depth. A test of the relationship with data collected as a part of the Long-Term Pavement Performance Program indicates favorable results.

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References

1. AASHTO Guide for Design of Pavement Structures. American Association of State Highway and Transportation Officials, Washington, D.C., 1993.
2. Haas R., Hudson W. R., and Zaniewski J. Modern Pavement Management. Krieger Publishing Company, Malabar, Fla., 1994.
3. Perera R. W., Byrum C., and Kohn S. D. Investigation of Development of Pavement Roughness. Report FHWA-RD-97-147. FHWA, U.S. Department of Transportation, 1998.
4. Smith K. L., Smith K. D., Evans L. D., Hoerner T. E., Darter M. I., and Woodstrom J. H. Smoothness Specifications for Pavements. Final Report. NCHRP Web Document 1. TRB, National Research Council, Washington, D.C., March 1997.
5. Ksaibati K., McNamara R., and Armaghani J. A Comparison of Roughness Measurements from Laser and Ultrasonic Road Profilers. Presented at the 78th Annual Meeting of the Transportation Research Board, Washington, D.C., 1999.
6. Khazanovich L., Darter M., Bartlett R., and McPeak T. Common Characteristics of Good and Poorly Performing PCC Pavements. Report FHWA-RD-97-131. FHWA, U.S. Department of Transportation, 1998.
7. Dore G., and Savard Y. Analysis of Seasonal Pavement Deterioration. Presented at the 77th Annual Meeting of the Transportation Research Board, Washington, D.C., 1998.
8. Sayers M. W., and Karamihas S. M. The Little Book of Profiling. University of Michigan Transportation Research Institute, Oct. 1996.
9. AASHO Interim Guide for Design of Pavement Structures. Association of State Highway Officials, Washington D.C., 1972.
10. Parsley L., and Robinson R. The TRRL Road Investment Model for Developing Countries (RTIM2). Laboratory Report 1057. U.K. Transport and Road Research Laboratory, Crowthorne, England, 1982.
11. Lytton R. L., Michalek C. H., and Scullion T. The Texas Flexible Pavement System. Proc., Fifth International Conference on Structural Design of Asphalt Pavements, Vol. 1, University of Michigan and Delft University of Technology, Ann Arbor, 1982.
12. Way G. B., and Eisenberg J. Pavement Management System for Arizona Phase II: Verification of Performance Prediction Models and Development of Data Base. Arizona Department of Transportation, Phoenix, 1980.
13. Potter D. W. The Development of Road Roughness with Time: An Investigation. Internal Report AIR 346-1. Australian Road Research Board, Melbourne, 1982.
14. Cheetham A., and Christison T. J. The Development of RCI Prediction Models for Primary Highways in the Province of Alberta. Department of Transportation, City of Edmonton, Alberta, Canada, 1981.
15. Lucas J., and Viano A. Systematic Measurement of Surface Evenness on the Road Network. Bulletin de Liaison 101. Laboratoire des Ponts et Chaussées, Paris, 1979.
16. Queiroz C. A. V. Performance Prediction Models for Pavement Management in Brazil. Ph.D. dissertation. University of Texas, Austin, 1981.
17. Jordan P. G., Ferne B. W., and Cooper D. R. C. An Integrated System for the Evaluation of Road Pavements. Proc., Sixth International Conference on Structural Design of Asphalt Pavements, Vol. 1, University of Michigan, Ann Arbor, 1987.
18. Paterson W. D. O. A Transferable Causal Model for Predicting Roughness Progression in Flexible Pavements. In Transportation Research Record 1215, TRB, National Research Council, Washington, D.C., 1989, pp. 70–84.

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Article first published: January 2000
Issue published: January 2000

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© 2000 National Academy of Sciences.
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Authors

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Joseph A. Mactutis
Nichols Consulting Engineers, 1885 South Arlington Avenue, Suite 111, Reno, NV 89509
Sirous H. Alavi
Nichols Consulting Engineers, 1885 South Arlington Avenue, Suite 111, Reno, NV 89509
Weston C. Ott
Nichols Consulting Engineers, 1885 South Arlington Avenue, Suite 111, Reno, NV 89509

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