Asset management inventory and data collection.

Details

• Creators:
  Kim, Y. Richard ; Hummer, Joseph E. ; Gabr, Mohammed ; Johnston, David ; Underwood, B. Shane ; Findley, Daniel ; Cunningham, Christopher M.
• Corporate Creators:
  North Carolina State University. Department of Civil, Construction, and Environmental Engineering
• Corporate Contributors:
  North Carolina. Dept. of Transportation. Research and Analysis Group
• Subject/TRT Terms:
  • Bridges
  • Roads
  • Asset management
  • Inventory
  • Data collection
  • Automatic data collection systems Bridges--North Carolina
  • Roads--North Carolina
  • Automatic data collection systems
• Publication/ Report Number:
  FHWA/NC/2008-15
• Resource Type:
  Tech Report
• Geographical Coverage:
  North Carolina
• Edition:
  Final report; Apr. 2008-Dec. 2008.
• Corporate Publisher:
  North Carolina. Department of Transportation. Research and Analysis Group
• 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.
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• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/5731/dot_5731_DS1.pdf
• File Type:
  [PDF - 3.65 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:2a17d195aaeabb21c8dbd3cb7e55ce00b3d8554291046c2b146948c3def5fe8e28c8068d6059cfe82d7d07152aa19acc9068763b23f0ca75716230d25f463aa5