DEVELOPMENT OF POS PREDICTION MODELS USING PROJECT, HISTORICAL AND PROJECT-GENERATED QUALITY ASSURANCE DATA

The KDOT Pavement Management System includes a Project Optimization System (POS). For each pavement distress, the POS requires models which predict the probability that a given distress level occurs at some time in the future. An interim regression model was developed during the initial development of the POS. These models were considered interim subject to modification and/or replacement as better mechanistic models, statistical models, or historical data becomes available. This K-TRAN project investigated the mechanistic and empirical-mechanistic models and techniques advanced in research conducted by the National Cooperative Highway Research Program (NCHRP) and the Strategic Highway Research Program (SHRP). In addition, the project specific data developed for the models were reanalyzed using SHRP sensitivity analysis and regression procedures to determine if improved models could be developed. The statistical studies were successful in developing alternative regression models. However, the binary nature of the response variable imposes a significant limitation on the ability of regression techniques to estimate probabilities of accurance between these two limits.

• Record URL:
  http://kdot1.ksdot.org/idmws/DocContent.dll?Library=PublicDocs^dt00mx38&ID=003670363
• Corporate Authors:

  University of Kansas, Lawrence

  Department of Civil, Environmental and Architectural Engineering
  1530 West 15th Street
  Lawrence, KS  United States  66045-7609

  Kansas Department of Transportation

  Docking State Office Building
  Topeka, KS  United States  66612
• Authors:
  • Moore, R K
  • Huang, Y
  • Frantzen, J
• Publication Date: 1996-11

Language

• English

Media Info

• Features: Appendices; Figures;
• Pagination: 100 p.

Subject/Index Terms

• TRT Terms: Defects; Empirical methods; Mechanical analysis; Mechanistic design; Pavement distress; Pavement management systems; Pavements; Quality assurance; Regression analysis
• Subject Areas: Data and Information Technology; Highways; Pavements; I23: Properties of Road Surfaces;

Filing Info

• Accession Number: 00732042
• Record Type: Publication
• Report/Paper Numbers: K-TRAN:KU-94-2
• Files: TRIS, ATRI, STATEDOT
• Created Date: Feb 27 1997 12:00AM