Unified Pavement Distress Index for Managing Flexible Pavements
Publication: Journal of Transportation Engineering
Volume 118, Issue 5
Abstract
One of the innovative approaches for maintaining and rehabilitating the nation's highways is to develop and implement some form of pavement management system (PMS). This paper documents results of a survey on PMS use in the United States. In addition, a simple method for a PMS based on priority ranking is presented. The model uses the theory of fuzzy sets to process the information obtained from a typical pavement condition survey. An index, called unified pavement distress index (UPDI), is defined and used to measure the pavement distress condition. The new approach is presented in a few key elements: guidelines for rating of six types of distresses, weights among the different types of distresses, fuzzy‐set representations of the linguistic grades and fuzzy mathematics, and the definition of UPDI and its use in a pavement data base. An example is presented to show how the new approach can be employed to analyze data bases generated from a pavement condition survey. While the proposed approach has shown its potential in the example application, more positive feedbacks from large‐scale field tests are needed to demonstrate its reliability and ease of use.
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References
1.
“America's highways, accelerating the search for innovation.” (1984). Special Report 202, Transp. Res. Board, Washington, D.C.
2.
Butt, A. A., Shahin, M. Y., and Feighan, K. J. (1987). “Pavement performance prediction model using the Markov process,” presented at meeting, Transportation Research Board, Washington, D.C.
3.
“Distress identification manual for the long‐term pavement performance studies.” (1990). Report No. SHRP‐LTPP/FR‐90‐001, Strategic Highway Res. Program, Nat. Res. Council, Washington, D.C.
4.
Dong, W., and Wong, F. S. (1987). “Fuzzy weighted averages and implementation of the extension principle.” Fuzzy Sets and Systems, 21(2), 183–199.
5.
Elton, D. J., and Juang, C. H. (1988). “Asphalt pavement evaluation using fuzzy sets.” Transp. Res. Record, 1196, 1–7.
6.
Haas, R., and Hudson, W. R. (1982). Pavement management systems. Krieger Publishing Co., Malabar, Fla.
7.
Juang, C. H. (1988). “Development of a decision support system using fuzzy sets.” Int. J. Microcomputers in Civ. Engrg., 3(2), 157–165.
8.
Juang, C. H. (1990). “A performance index for the unified rock classification system.” Bull. Assoc. of Engrg. Geologists, 27(4), 497–504.
9.
Juang, C. H., Huang, X. H., and Elton, D. J. (1991). “Fuzzy information processing by the Monte Carlo simulation technique.” J. Civ. Engrg. Systems, 8(1), 19–25.
10.
“Manual for condition rating of flexible pavements—Distress manifestation.” (1982). SP‐004, Ontario Ministry of Transp. and Communications, Downsview, Ontario, Canada, Apr.
11.
Moore, R. E. (1966). Interval analysis. Prentice‐Hall, Englewood Cliffs, N.J.
12.
Murthy, S., and Sinha, K. C. (1990). “A fuzzy set approach for bridge traffic safety evaluation,” presented at meeting, Transportation Research Board, Washington, D.C.
13.
Schmucker, K.J. (1984). Fuzzy set, natural language computations and risk analysis. Computer Science Press, Rockville, Mass.
14.
Zadeh, L. A. (1965). “Fuzzy sets.” Information and Control, 8, 338–353.
15.
Zadeh, L. A., (1983). “The role of fuzzy logic in the management of uncertainty in expert systems.” Fuzzy Sets & Systems, 11, 199–227.
Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 118 • Issue 5 • September 1992
Pages: 686 - 699
Copyright
Copyright © 1992 ASCE.
History
Published online: Sep 1, 1992
Published in print: Sep 1992
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