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Effect of Performance Model Accuracy on Optimal Pavement Design


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  • Madanat, S M
  • Prozzi, Jorge A
  • Han, Michael
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    In the first part of this paper, an analysis of the data collected during the American Association of State Highway Officials (AASHO) Road Test, based on probabilistic duration modeling techniques, is presented. Duration techniques enable the stochastic nature of pavement failure time to be evaluated as well as censored data to be incorporated in the statistical estimation of the model parameters. The second part of this paper presents the use of economic optimization principles for determining the optimal design of flexible pavements. We study the effect of deterioration model accuracy on optimal design and lifecycle costs, by comparing three models. The first is a simple regression model developed by the AASHO, which forms the basis of design standards in use today. The second is a regression model that was developed with the same AASHO data set, but that includes a correction for data censoring. The third model is the probabilistic model developed in the first part of this paper. The results show that the AASHO model, when used as an input to lifecycle cost minimization, produces a pavement structural number that is lower than that produced by using the other two deterioration models. This results in shorter pavement lives and higher costs due to more frequent resurfacing. The savings in lifecycle cost accrued by using optimal structural number are shown to be quite significant, offering a sound basis for revising current design practices.

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    Bibliographic Info

    Paper provided by University of California Transportation Center in its series University of California Transportation Center, Working Papers with number qt42b5n5j6.

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    Date of creation: 01 Sep 2002
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    Handle: RePEc:cdl:uctcwp:qt42b5n5j6

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    Keywords: Social and Behavioral Sciences;


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    1. Small, Kenneth A & Winston, Clifford, 1988. "Optimal Highway Durability," American Economic Review, American Economic Association, American Economic Association, vol. 78(3), pages 560-69, June.
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    Cited by:
    1. Sathaye, Nakul & Horvath, Arpad & Madanat, Samer, 2010. "Unintended impacts of increased truck loads on pavement supply-chain emissions," Transportation Research Part A: Policy and Practice, Elsevier, Elsevier, vol. 44(1), pages 1-15, January.
    2. Sathaye, Nakul & Horvath, Arpad & Madanat, Samer M, 2009. "Unintended Impacts of Increased Truck Loads on Pavement Supply-chain Emissions," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings, Institute of Transportation Studies, UC Berkeley qt1jf6v73z, Institute of Transportation Studies, UC Berkeley.
    3. Guerrero, Sebastian E. & Madanat, Samer M. & Leachman, Robert C., 2013. "The Trucking Sector Optimization Model: A tool for predicting carrier and shipper responses to policies aiming to reduce GHG emissions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, Elsevier, vol. 59(C), pages 85-107.
    4. Sathaye, Nakul & Madanat, Samer, 2011. "A bottom-up solution for the multi-facility optimal pavement resurfacing problem," Transportation Research Part B: Methodological, Elsevier, Elsevier, vol. 45(7), pages 1004-1017, August.
    5. Sathaye, Nakul & Horvath, Arpad & Madanat, Samer, 2009. "Unintended Impacts of Increased Truck Loads on Pavement Supply-Chain Emissions," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings, Institute of Transportation Studies, UC Berkeley qt5gt4r1k2, Institute of Transportation Studies, UC Berkeley.


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