Roads Performance Modeling and Management System from Two Condition Data Points: Case Study of Costa Rica
Publication: Journal of Transportation Engineering
Volume 135, Issue 12
Abstract
Initial implementation of a road management system will typically face the challenge of a lack of time-series data for performance modeling. This paper presents one approach for developing initial performance prediction models that are required to support trade-off and optimization analyses in a road management system. The paper demonstrates that starting performance models can be formulated based on as little as 2 years’ network-level data on condition and traffic. The paper builds a locally calibrated pavement condition index and subsequently uses it for network-level strategic planning and programming of works. The paper demonstrates a method of extracting initial estimates of treatments’ effectiveness from the condition data. The case study is based on the Costa Rican national road network. The model uses commercial software to allocate resources and optimize decisions. Several investment strategies were tested to investigate the sustainability of the road network value over time. The results demonstrate that optimization improves road conditions in a sustainable manner, which in the long run releases funds for other necessities.
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References
Abaza, K. A. (2006). “Iterative linear approach for nonlinear nonhomogeneous stochastic pavement management models.” J. Transp. Eng., 132(3), 244–256.
Abaza, K. A., Ashur, A. A., and Al-Khatib, I. A. (2004). “Integrated pavement management system with a Markovian prediction model.” J. Transp. Eng., 130(1), 24–33.
Baik, H. S., Jeong, H. S. D., and Abraham, D. M. (2006). “Estimating transition probabilities in Markov chain-based deterioration models for management of wastewater systems.” J. Water Resour. Plann. Manage., 132(1), 15–24.
Butt, 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.
George, K. P., Rajagopal, A. S., and Lim, L. K. (1989). “Models for predicting pavement deterioration.” Transportation Research Record. 1215, Transportation Research Board, Washington, D.C., 1–7.
Hajek, J. J. (1995). “General axle load equivalency factors.” Transportation Research Record. 1482, Transportation Research Board, Washington, D.C., 67–78.
Kim, Y. R. (1998). “Assessing pavement layer condition using deflection data.” Rep. Prepared for National Cooperative Highway Research Program (NCHRP) Project 10-48, Transportation Research Board, National Research Council. Washington, D.C.
LANAMME. (2006). “State of the network report.” Rep. Prepared for Laboratorio Nacional de Materiales y Modelos Estructurales, Universidad de Costa Rica.
Li, N., and Hass, 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 transition probabilities from condition rating data.” J. Infrastruct. Syst., 1(2), 120–125.
Mauch, M., and Madanat, S. (2001). “Semiparametric hazard rate models of reinforced concrete bridge deck deterioration.” J. Infrastruct. Syst., 7, 49–57.
Micevski, T., Kuczera, G., and Coombes, P. (2002). “Markov model for storm water pipe deterioration.” J. Infrastruct. Syst., 8(2), 49–56.
Ortiz-Garcia, J. J., Costello, S. B., and Snaith, M. (2006). “Derivation of transition probability matrices for pavement deterioration modeling.” J. Transp. Eng., 132(2), 141–161.
Pedigo, R. D., Hudson, W. R., and Roberts, F. L. (1981). “Pavement performance modeling for pavement management.” Transportation Research Record. 814, Transportation Research Board, Washington, D.C., 14–21.
Prozzi, J. A., and Madanat, S. M. (2003). “Incremental nonlinear model for predicting pavement serviceability.” J. Transp. Eng., 129(6), 635–641.
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© 2009 ASCE.
History
Received: Mar 24, 2009
Accepted: Jun 9, 2009
Published online: Jun 13, 2009
Published in print: Dec 2009
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