A project candidate selection and ranking model (PCSRM) is commonly applied in pavement maintenance and rehabilitation planning. Typically, these models use empirical mathematical expressions that do not have a clear physical meaning and cannot accurately assess the priority of transportation agencies or pavement engineers. To overcome this limitation, this study developed a method, based on the analytical hierarchy process (AHP), to identify pavement-related factors and improve the accuracy of the PCSRMs currently used by the Austin District (Texas Department of Transportation) in its 4-year plan. The aim was to identify pavement-related factors that reflected the engineering judgment of transportation agencies and pavement engineers. The proposed method had three major components: AHP design, AHP survey and results analysis, and factors selection. A three-tier hierarchy structure of one objective, five goals, and 18 alternatives was defined. Additionally, a system to check for consistency was developed on the basis of literature recommendations. An Excel-based survey tool was developed with the objective of providing a relatively easy visual interface for the participants. The design and development of the survey tool were carried out in collaboration with the district pavement preservation engineer. Seventeen Texas Department of Transportation pavement experts completed the AHP survey with the required consistency ratio. Clustering analysis was performed to identify the pavement-related factors that showed the highest priorities. The factors with the highest overall weights should be considered in future PCSRM improvement.


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    Title :

    Analytical Hierarchy Process to Improve Project Prioritization in the Austin District, Texas


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2017-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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