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A time series analysis framework for transportation infrastructure management

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  • Durango-Cohen, Pablo L.

Abstract

We present an integrated framework to address performance prediction and maintenance optimization for transportation infrastructure facilities. The framework is based on formulating the underlying resource allocation problem as discrete-time, stochastic optimal control problem with linear dynamics and a quadratic criterion. Facility deterioration is represented as a time series which provides an attractive and rigorous approach to specify and estimate performance models. The state and decision variables in the framework are continuous which allows the framework to overcome important computational and statistical limitations that do not allow existing optimization models to address various problems that arise the management of transportation infrastructure. To illustrate the advantages of the proposed approach, we conduct a numerical study where we examine the case of multiple technologies being used simultaneously to collect condition data. Specifically, we illustrate how the framework can be used to quantify the effect of the capabilities of inspection technologies, i.e., precision, accuracy and relationships, on life-cycle costs. This information can be used to compute the operational value of combining technologies, and thus, to guide in their selection based on economic criteria.

Suggested Citation

  • Durango-Cohen, Pablo L., 2007. "A time series analysis framework for transportation infrastructure management," Transportation Research Part B: Methodological, Elsevier, vol. 41(5), pages 493-505, June.
  • Handle: RePEc:eee:transb:v:41:y:2007:i:5:p:493-505
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    References listed on IDEAS

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    Cited by:

    1. Chen, Yikai & Durango-Cohen, Pablo L., 2015. "Development and field application of a multivariate statistical process control framework for health-monitoring of transportation infrastructure," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 78-102.
    2. Zhi-Chun Li & Dian Sheng, 2014. "Pavement rehabilitation scheduling and toll pricing under different regulatory regimes," Annals of Operations Research, Springer, vol. 217(1), pages 337-355, June.
    3. Gu, Weihua & Ouyang, Yanfeng & Madanat, Samer, 2012. "Joint optimization of pavement maintenance and resurfacing planning," Transportation Research Part B: Methodological, Elsevier, vol. 46(4), pages 511-519.
    4. Sathaye, Nakul & Madanat, Samer, 2011. "A bottom-up solution for the multi-facility optimal pavement resurfacing problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 1004-1017, August.
    5. Rita Justo-Silva & Adelino Ferreira & Gerardo Flintsch, 2021. "Review on Machine Learning Techniques for Developing Pavement Performance Prediction Models," Sustainability, MDPI, vol. 13(9), pages 1-27, May.
    6. Chu, Chih-Yuan & Durango-Cohen, Pablo L., 2008. "Estimation of dynamic performance models for transportation infrastructure using panel data," Transportation Research Part B: Methodological, Elsevier, vol. 42(1), pages 57-81, January.
    7. Kobayashi, Kiyoshi & Kaito, Kiyoyuki & Lethanh, Nam, 2012. "A statistical deterioration forecasting method using hidden Markov model for infrastructure management," Transportation Research Part B: Methodological, Elsevier, vol. 46(4), pages 544-561.
    8. Zhang, Le & Fu, Liangliang & Gu, Weihua & Ouyang, Yanfeng & Hu, Yaohua, 2017. "A general iterative approach for the system-level joint optimization of pavement maintenance, rehabilitation, and reconstruction planning," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 378-400.
    9. Seyedshohadaie, S. Reza & Damnjanovic, Ivan & Butenko, Sergiy, 2010. "Risk-based maintenance and rehabilitation decisions for transportation infrastructure networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(4), pages 236-248, May.
    10. Mishalani, Rabi G. & Gong, Liying, 2009. "Optimal infrastructure condition sampling over space and time for maintenance decision-making under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 43(3), pages 311-324, March.
    11. Andrzej Raszkowski & Bartosz Bartniczak, 2019. "On the Road to Sustainability: Implementation of the 2030 Agenda Sustainable Development Goals (SDG) in Poland," Sustainability, MDPI, vol. 11(2), pages 1-20, January.

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