Developing a realistic-prototyping road user cost evaluation tool for FDOT.
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Developing a realistic-prototyping road user cost evaluation tool for FDOT.

Filetype[PDF-727.76 KB]


  • English

  • Details:

    • Alternative Title:
      Developing a realistic-prototyping RUC evaluation tool for FDOT.
    • Corporate Contributors:
    • Resource Type:
    • Geographical Coverage:
    • OCLC Number:
      503162731
    • Abstract:
      The objective of this project is to develop a realistic-prototyping RUC (Road User Cost) calculation tool that is userfriendly

      and utilizing limited number of data inputs that are easy to use. The tool can help engineers to estimate RUC on

      specific construction projects for determining the incentive/disincentive values for contractors. The development of such

      a tool is necessitated by the need to simplify data requirements for RUC calculations, making the RUC calculations more

      geographical related, by designing a user-friendly software tool.

      In addition to the review of existing literature related, comparisons were performed among FDOT methodologies,

      and also among the existing tools (such as the Arizona Department of Transportation (ADOT) DOT model, the Queue

      and User Cost Evaluation of Work Zones (QUEWZ) model and the Quick Zone model. The above models were

      developed by the ADOT, the Texas Transportation Institute, and the Federal Highway Administration.

      The new RUC calculation procedure is developed based on concepts and methods published in recognized sources

      such as American Association of State Highway Transportation Officials (AASHTO)’s User Benefit Analysis of

      Highway and Bus-Transit Improvements,” “Red Book” and the Transportation Research Board’s Highway Capacity

      Manual(HCM). Data from seven projects are collected to validate the new procedure by comparing it with the ADOT

      model and the QUEWZ model.

      The validations show that the new procedure can generate consistent results that are comparable with those

      produced by the Arizona model and the QUEWZ model, while using a small set of localized data inputs.

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