Effects of Pavement Spatial Variability on Contractor’s Management Strategies
Publication: Journal of Infrastructure Systems
Volume 16, Issue 4
Abstract
Performance-based maintenance contracts are becoming an increasingly popular method of outsourcing pavement maintenance work. These contracts transfer performance-related risks to contractors with the objective of reducing the total cost of maintenance over the pavement life cycle by leveraging on the efficiencies of private sector management. In such contractual settings, transportation agencies hedge their exposure to poorly performing pavements that require frequent attention. However, this comes with a price. Contractors price in their bids a premium to account for such scenarios. This paper presents a model for contractors to determine optimal management strategies by taking into account the inherent spatial variability in pavement’s structural characteristics. The model considers a tradeoff between economies of scale associated with managing longer pavement sections and the risk reduction benefits with managing relatively smaller, e.g., more homogeneous sections. The results indicate that the length of optimal management sections depends not only on the expected contract penalty costs (disincentive costs), but also the ability of the contractor to explore economies of scale. The model is illustrated using typical data available to transportation agencies.
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References
Alsherri, A., and George, K. P. (1988). “Reliability model for pavement performance.” J. Transp. Eng., 114(3), 294–306.
Anastasopoulos, P., Labi, S., and McCullouch, B. (2009). “Analyzing duration and prolongation of performance-based contracts using hazard-based duration and zero-inflated random parameters Poisson models.” Proc., Transportation Research Board 88th Annual Meeting, Transportation Research Board, Washington, D.C.
Austroroads. (2003). “Development of performance contracts and specifications.” Full Rep., Sydney, Australia.
Carey, P. D., Preston, C. D., Hill, M. O., Usher, M. B., and Wright, S. M. (1995). “An environmentally defined biogeographical zonation of Scotland designed to reflect species distributions.” J. Ecol., 83(5), 833–845.
Chua, K. H., Der Kiureghian, A., and Monismith, C. L. (1992). “Stochastic model for pavement design.” J. Transp. Eng., 118(6), 769–786.
Damnjanovic, I., and Zhang, Z. (2008). “Risk-based model for valuation of performance-specified pavement maintenance contracts.” J. Constr. Eng. Manage., 134(7), 492–500.
Darter, M., Khazanovich, L., Yu, T., and Mallela, J. (2005). “Reliability analysis of cracking and faulting prediction in the new mechanistic-empirical design procedure.” Transp. Res. Rec., 1936, 150–160.
Dlesk, R., and Bell, L. (2006). “Outsourcing versus in-house highway maintenance: Cost comparison and decision factors.” SCDOT research project 653: Maintenance outsourcing, Dept. of Civil Engineering, Clemson Univ., Clemson, S.C.
Estivill-Castro, V. M. (1997). “Mining spatial data via clustering.” Technical Rep., Univ. of Queensland, St. Lucia, QLD, Australia.
Federal Highway Administration (FHWA). (2004). “Performance specifications strategic roadmap: A vision for the future.” U.S. DOT, ⟨http://www.fhwa.dot.gov/construction/pssr04.pdf⟩ (Dec. 3, 2007).
Fwa, T. F., and Sinha, K. C. (1986). “Routine maintenance and pavement performance.” J. Transp. Eng., 112, 329–334.
Kalpakis, K., Gada, D., and Puttagunta, V. (2001). “Distance measures for effective clustering of ARIMA time-series.” Proc., IEEE Int. Conf. on Data Mining, IEEE, New York, 273–280.
Kanungo, T., Mount, D. M., Netanyahu, N. S., Piatko, C. D., Silverman, R., and Wu, A. Y. (2002). “An efficient K-means clustering algorithm: Analysis and implementation.” IEEE Trans. Pattern Anal. Mach. Intell., 24(7), 881–892.
Kiureghian, A. D., and Liu, P. L. (1986). “Multivariate distribution models with prescribed marginals and covariances.” Probab. Eng. Mech., 1(2), 105–112.
Labi, S. (2001). “Impact evaluation of highway pavement maintenance activities.” Ph.D. thesis, Purdue Univ., West Lafayette, Ind.
MacQueen, J. (1967). “Some methods for classification and analysis of multivariate observation.” Proc., 5th Berkeley Symp. on Mathematical Statistics and Probability, Univ. of California, Berkeley, Calif., 281–297.
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.
Manion, M., and Tighe, S. (2007). “Performance-specified maintenance contracts, adding value through improved safety performance.” Transp. Res. Rec., 2007(1990), 72–79.
Mishalani, R. G., and Koutsopoulos, H. N. (1995a). “Role of the spatial dimension in infrastructure condition assessment and deterioration modeling.” Transp. Res. Rec., 1508, 45–52.
Mishalani, R. G., and Koutsopoulos, H. N. (1995b). “Uniform infrastructure fields: Definition and identification.” J. Infrastruct. Syst., 1(1), 44–55.
Mishalani R. G., and Koutsopoulos H. N. (2002). “Modeling the spatial behavior of infrastructure condition.” Transp. Res., Part B: Methodol., 36, 171–194.
Ozbek, M. E. (2004). “Development of performance warranties for performance-based road maintenance contracts.” M.S. thesis, Virginia Tech, Blacksburg, Va.
Prozzi, J. A., and Madanat, S. M. (2000). “Using duration models to analyze experimental pavement failure data.” Transp. Res. Rec., 1699(1), 87–94.
Queiroz, C. (2000). “Contractual procedures to involve the private sector in road maintenance and rehabilitation.” Proc., 24th Int. Baltic Road Conf., World Bank, Washington, D.C.
Saatchi, S., and Hung, C. C. (2005). “Hybridization of the ant colony optimization with the K-means algorithm for clustering.” Lect. Notes Comput. Sci., 3540, 511–520.
Salvador, S., and Chan, P. (2004). “Determining the number of clusters/segments in hierarchical clustering/segmentation algorithms.” Proc., 16th IEEE Int. Conf. on Tools with AI, IEEE Computer Soc., Washington, D.C., 576–584.
Stankevich, N., Qureshi, N., and Queiroz, C. (2005). “Performance-based contracting for preservation and improvement of road assets.” World Bank Transport Note TN-27, World Bank, Washington, D.C.
Tibshirani, R., Walter, G., and Hastie, T. (2001). “Estimating the number of clusters in a data set via the gap statistic.” J. R. Stat. Soc. Ser. B, 63(2), 411–423.
World Bank Group. (2006). “Performance-based contracting for roads in USA.” Performance-based contracting for preservation and improvement of road assets, Resource Guide, ⟨http://www.worldbank.org/transport/roads/resource-guide/Case-USA.htm⟩ (Dec. 29, 2006).
Zhang, Z., and Damnjanovic, I. (2006). “Applying method of moments to model reliability of pavements infrastructure.” J. Transp. Eng., 132, 416–424.
Zietlow, G. (2007). “Cutting costs and improving quality through performance-based road management and maintenance contracts—The Latin American and OECD experiences.” Proc., Restructuring Road Management, Senior Road Executives Programme, Univ. of Birmingham, Birmingham, U.K.
Information & Authors
Information
Published In
Journal of Infrastructure Systems
Volume 16 • Issue 4 • December 2010
Pages: 231 - 240
Copyright
© 2010 ASCE.
History
Received: Nov 3, 2008
Accepted: Jun 11, 2009
Published online: Jun 13, 2009
Published in print: Dec 2010
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