Proposed Pavement Performance Models for Local Government Agencies in Michigan
Abstract
The state of Michigan has 191 432 km (118,950 mi) of roadway (paved and unpaved), including highways, roads, and streets. Local government agencies, which are responsible for 176 270 km (109,529 mi) of these roads and streets, commonly use a pavement management system (PMS) called RoadSoft to assist in managing their pavement network. A key element of any PMS is its ability to predict future pavement performance. A study is described in which various deterministic and probabilistic models were evaluated using data from two Michigan counties. It was found that the logistic growth model and the Markov model provided the best combination of predictive ability and potential for applicability in Michigan counties. A comparison between these models found that their predictive ability for four pavement segments with different deterioration rates was good, with the Markov model offering the added advantage of representing future performance as a probability distribution, not as a single condition state. Current plans are to implement the logistic growth model in RoadSoft by the end of 1999 and to add the Markov model as local organizations gather sufficient pavement condition data over the next 5 years. It is hoped that these two pavement deterioration models can be implemented in the RoadSoft PMS to improve pavement performance prediction.
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References
1. Calomeni D. A. The Development of RoadSoft, the Beginning of an Integrated Roadway Management System. Master’s thesis. Michigan Technological University, Houghton, 1996.
2. Walker D., Entine L., and Kummer S. Asphalt-Pavement Surface Evaluation and Rating (PASER) Manual. Transportation Information Center, University of Wisconsin-Madison, Madison, 1994.
3. Shahin M. Y. Pavement Management for Airports, Roads, and Parking Lots. Chapman and Hall, New York, 1994.
4. Current Application and Successful Implementation of Local Agency Pavement Management in the United States. Report FHWA-SA-97-057. FHWA Turner-Fairbank Highway Research Center, McLean, Va., 1997.
5. Li N., Haas R., and Xie W.-C. Investigation of Relationships Between Deterministic and Probabilistic Prediction Models in Pavement Management. In Transportation Research Record 1592, TRB, National Research Council, Washington, D.C., 1997, pp. 70–79.
6. Kuo W. H. Pavement Performance Models for Pavement Management System of Michigan Department of Transportation. Internal Report. Michigan Department of Transportation, Lansing, 1995.
7. Butt A. A. Application of Markov Process to Pavement Management Systems at the Network Level. Ph.D. thesis. University of Illinois at Urbana-Champaign, 1991.
8. Van Dam T., and Bildili J. Performance Trends for Portland Cement Concrete General Aviation Pavements in Illinois. In Transportation Research Record 1524, TRB, National Research Council, Washington, D.C., 1996, pp. 194–202.
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Article first published: January 2000
Issue published: January 2000
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This article was published in Transportation Research Record: Journal of the Transportation Research Board.
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