Development and Implementation of a Network-Level Pavement Optimization Model for Ohio Department of Transportation

Optimal use of pavement maintenance and rehabilitation budget is essential in a constrained budget environment such as now. This paper presents the development and implementation of a network-level optimization model within a pavement management information system (PMIS) for the Ohio Department of Transportation (ODOT). Future pavement condition is predicted based on historical pavement data using a Markov transition probability model. Such transition probabilities are updated automatically when new condition data become available each year. The network-level optimization model integrates a linear programming model and the Markov transition probability model. This optimization tool is capable of (1) calculating the minimum budget required to achieve a desired level of pavement network condition, (2) maximizing the improvements of pavement network condition with a given amount of budget, and (3) determining the corresponding optimal treatment policy and budget allocations. It can be used by highway agencies as a decision support tool for network-level pavement management decisions.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AFD10 Pavement Management Systems.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Wang, Shuo
    • Chou, Eddie Yein-Juin
    • Williams, Andrew
  • Conference:
  • Date: 2013

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 17p
  • Monograph Title: TRB 92nd Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01473056
  • Record Type: Publication
  • Report/Paper Numbers: 13-2035
  • Files: PRP, TRIS, TRB, ATRI
  • Created Date: Feb 19 2013 3:03PM