Welcome to ROSA P | Asset management inventory and data collection. - 5731 | BTS Data Directory
Stacks Logo
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.
 
 
Help
Clear All Simple Search
Advanced Search
Asset management inventory and data collection.
  • Published Date:
    2009-10-01
  • Language:
    English
Filetype[PDF-3.65 MB]


Details:
  • Publication/ Report Number:
    FHWA/NC/2008-15
  • Resource Type:
  • Geographical Coverage:
  • OCLC Number:
    664030830
  • Edition:
    Final report; Apr. 2008-Dec. 2008.
  • NTL Classification:
    NTL-ECONOMICS AND FINANCE-ECONOMICS AND FINANCE ; NTL-HIGHWAY/ROAD TRANSPORTATION-Bridges and Structures ; NTL-HIGHWAY/ROAD TRANSPORTATION-HIGHWAY/ROAD TRANSPORTATION ; NTL-PLANNING AND POLICY-PLANNING AND POLICY ; NTL-REFERENCES AND DIRECTORIES-Statistics ;
  • Format:
  • Abstract:
    An efficient and accurate inventory of a state highway agency’s assets, along with the means to assess the condition

    of those assets and model their performance, is critical to enabling an agency to make informed investment decisions

    in a Transportation Asset Management (TAM) environment. Today, new technologies provide fast and improved

    ways to gather, process, and analyze data. The key is to identify and gather the most useful, reliable, cost-effect

    information and use it to make informed decisions for asset management.

    Four key infrastructure areas have been identified as primary asset components; pavements, bridges, geotechnical

    features, and roadside appurtenances. Each area contains multiple categories and data elements important for sound

    decision making. Although some similarities exist in these four primary categories, the nature of data collection may

    differ, depending on the asset type. The, sheer number of data elements and the length of asset networks for

    pavements and roadside appurtenances render the automated highway speed data collection method a necessity

    rather than a luxury. However, the discrete nature of bridges and geotechnical features make the automated mobile

    data collection method on a network level unfeasible with today’s technology.

    Important issues in the collection process include precision, subjectivity and variability of the process itself, as well

    as speed, safety of the survey crew, proximity of the public, cost, etc. Although previous research has attempted to

    address these issues and determine the most appropriate method(s), the question remains as to which roadway data

    collection system is best for state highway agencies given real world constraints. This research set up a “sealed

    envelope” experiment wherein the identification, location, description, and quality of the asset data elements are

    known only to NCSU researchers. Vendors are informed of only the data necessary to perform their evaluation. To

    support this effort at 95-mile test course near Raleigh, North Carolina was identified, which contained a sampling of

    pavement, roadside, geotechnical and bridge elements. This document reports on the findings from the study.

  • Collection(s):
  • Supporting Files:
    No Additional Files
No Related Documents.
You May Also Like:
Submit Feedback >