Incremental nonlinear model for predicting pavement serviceability

Jorge A. Prozzi, Samer M. Madanat

Research output: Contribution to journalArticle

Abstract

A recursive nonlinear model was developed for the prediction of pavement performance as a function of traffic characteristics, pavement structural properties, and environmental conditions. The model highlights some of the advantages of relaxing the linear restriction that is usually placed on the specification form of pavement performance models. First, a functional form that better represents the physical deterioration process can be used. Second, the estimated parameters are unbiased, owing to a proper specification and the use of sound statistical techniques. Finally, the standard error of the prediction is reduced by half that of the equivalent existing linear model. This improved accuracy has important economic implications in the context of pavement management. The model developed as part of this research enables the determination of an unbiased exponent of the so-called power law and of the equivalent loads for different axle configurations. The estimated exponent confirms the value of 4.2 traditionally used. However, it should be noted that this exponent is only to be used for determining damage in terms of serviceability. On the other hand, equivalent loads estimated for different axle configurations tend to differ from traditionally used values.

Original languageEnglish (US)
Pages (from-to)635-641
Number of pages7
JournalJournal of Transportation Engineering
Volume129
Issue number6
DOIs
StatePublished - Nov 2003

Keywords

  • Cost allocations
  • Models
  • Pavements
  • Serviceability

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation

Fingerprint Dive into the research topics of 'Incremental nonlinear model for predicting pavement serviceability'. Together they form a unique fingerprint.

Cite this