IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v27y1993i2p174-193.html
   My bibliography  Save this article

An Approach for Predicting Latent Infrastructure Facility Deterioration

Author

Listed:
  • Moshe Ben-Akiva

    (Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Rohit Ramaswamy

    (AT&T Bell Laboratories, Holmdel, New Jersey 07733)

Abstract

A pavement deterioration model predicts the performance of a pavement over time as a function of traffic, pavement characteristics and environmental factors. The most important performance characteristics of a pavement are its ability to bear traffic loads and its ability to provide a smooth ride. However, there is no unambiguous approach to directly measure these performance characteristics. Therefore, we consider pavement performance to be unobservable. The problem of designing pavement deterioration models is the problem of defining the above unobservable characteristics in terms of what is observed, i.e., in terms of measured extents and severities of different damage components. The methodology presented in this paper describes a statistical technique to estimate latent pavement performance from observed pavement damage. No constraints are placed on the number or type of measurements required, so the methodology is flexible enough to include different measurement techniques and data collection strategies. The estimation procedure simultaneously fits a deterioration model and a performance index calibration model to data, thereby producing much better fits to data than traditional deterioration models. The methodology presented in this paper will be useful for deriving more realistic predictive models of pavement deterioration and for defining better data collection strategies.

Suggested Citation

  • Moshe Ben-Akiva & Rohit Ramaswamy, 1993. "An Approach for Predicting Latent Infrastructure Facility Deterioration," Transportation Science, INFORMS, vol. 27(2), pages 174-193, May.
  • Handle: RePEc:inm:ortrsc:v:27:y:1993:i:2:p:174-193
    DOI: 10.1287/trsc.27.2.174
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/trsc.27.2.174
    Download Restriction: no

    File URL: https://libkey.io/10.1287/trsc.27.2.174?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Swei, Omar & Gillen, David & Onayev, Anuarbek, 2021. "Improving productivity measures of producing transportation infrastructure using quality-adjusted price indices," Transport Policy, Elsevier, vol. 114(C), pages 372-381.
    3. Li, Sirui & Liu, Ying & Wang, Pengfei & Liu, Peng & Meng, Jun, 2020. "A novel approach for predicting urban pavement damage based on facility information: A case study of Beijing, China," Transport Policy, Elsevier, vol. 91(C), pages 26-37.
    4. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ortrsc:v:27:y:1993:i:2:p:174-193. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.