Dynamic Panel Data Model for Predicting Performance of Asphalt Concrete Overlay
Publication: Journal of Transportation Engineering
Volume 134, Issue 2
Abstract
In order to identify the improvement needs on transportation facilities and the associated budget, the transportation agencies need to have a reasonable estimate of the facilities’ future condition. Using asphalt concrete overlay over fractured portland cement concrete pavement as an example, this paper shows how to use the existing pavement condition and other recorded information in a pavement management system to predict the future condition of pavements. A comprehensive pavement performance indicator, condition points, was used as the response variable of the prediction model. A dynamic panel data prediction method was employed to make the prediction model reflect the influence of the existing pavement condition, exogenous variables, and the heterogeneity of different pavement sections. The predicted condition points were compared with the actual values and the results indicated that the prediction accuracy was reasonable.
Get full access to this article
View all available purchase options and get full access to this article.
References
Abaza, K. A., Ashur, S., and Al-Khatib, I. A. (2004). “Integrated pavement management system with a Markovian prediction model.” J. Transp. Eng., 130(1), 24–33.
Abu-Lebdeh, G., Lyles, R., Baladi, G., and Ahmed, K. (2003). “Development of alternative pavement distress index models.” Technical Rep., Michigan DOT, Mich.
Allen, D. (1990). “Review and analysis of pavement practices in Kentucky.” Technical Rep., Kentucky Transportation Center, Ky.
Anderson, T. W., and Hsiao, C. (1982). “Formulation and estimation of dynamic models using panel data.” J. Econometr., 18, 47–82.
Arellano, M., and Bond, S. (1991). “Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations.” Rev. Econ. Stud., 58, 277–297.
Butt, A. A., Shahin, M. Y., Feighan, K. J., and Carpenter, S. H. (1987). “Pavement performance prediction model using the Markov process.” Transportation Research Record. 1123, Transportation Research Board, Washington, D.C., 12–19.
Cebon, D. (1993). Interaction between heavy vehicles and roads, Society of Automotive Engineers, Warrendale, Pa.
Federal Highway Administration (FHWA). (2001). “1999 Status of the nation’s highways, bridges, and transit: Conditions and performance, Report to congress.” Rep. No. FHWA-PL-08–017, U.S. Department of Transportation, Washington, D.C.
Federal Highway Administration (FHWA). (2003). “Improving pavements with long-term pavement performance: Products for today and tomorrow.” Winning Paper from the 2001–2002 International Contest on Long-Term Pavement Performance Data Analysis, U.S. Department of Transportation, Washington D.C.
Federal Highway Administration (FHWA). (2004). “Welcome to LTPP.” ⟨http://www.tfhrc.gov/pavement/ltpp/ltpp. htm⟩ (January 3, 2005).
Greene, W. H. (1999). Econometric analysis, 4th Ed., Prentice-Hall, Upper Saddle River, N.J., 583.
Haas, R., Hudson, W. R., and Zaniewski, J. (1994). Modern pavement management, Krieger, Malabar, Fla., 193–201.
Hsiao, C. (2003). Analysis of panel data, Cambridge University Press, New York, 71–75.
Jiang, Y., Saito, M., and Sinha, K. C. (1988). “Bridge performance prediction model using the Markov chain,” Transportation Research Record. 1180, Transportation Research Board, Washington, D.C., 25–32.
Kiviet, J. F. (1995). “On bias, inconsistency, and efficiency of various estimators in dynamic panel data models.” J. Econometr., 68, 53–78.
Lee, D. G., and Russell, J. S. (2004). “Panel data analysis of factors affecting as-built roughness of asphalt concrete pavements.” J. Transp. Eng., 130(4), 479–485.
Li, N., Xie, W., and Haas, R. (1996). “Reliability-based processing of Markov chains for modeling pavement network deterioration.” Transportation Research Record. 1524, Transportation Research Board, Washington, D.C., 203–213.
Madanat, S., Mishalani, R., and Ibrahim, W. H. W. (1995). “Estimation of infrastructure transportation probability from condition rating data.” J. Infrastruct. Syst., 1(2), 120–125.
Madanat, S., and Shin, H. C., (1998). “Development of distress progression models using panel data sets of in-service pavements.” Transportation Research Record. 1643, Transportation Research Board, Washington, D.C.
Nickel, S. J. (1981). “Biases in dynamic models with fixed effects.” Econometrica, 49, 1417–1426.
Sargan, J. D. (1958). “The estimation of economic relationships using instrumental variables.” Econometrica, 26, 393–415.
Information & Authors
Information
Published In
Copyright
© 2008 ASCE.
History
Received: Nov 14, 2006
Accepted: Jul 20, 2007
Published online: Feb 1, 2008
Published in print: Feb 2008
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.