The prediction models in the network optimization system (NOS) are exhibited in the form of transition probability matrices (TPMs) in the newly implemented NOS (AZNOS) in the Arizona Department of Transportation. Due to variability in pavement performance parameters over time, it is necessary to study the effect of the influencing factors causing this variability. One such factor is annual expenditure on pavement rehabilitation, which is determined with the help of AZNOS results. In addition, rehabilitation budgets recommended by AZNOS are determined by the existing pavement network conditions, performance standards, and, more importantly, the prediction models through the use of the linear optimization routine. Even though it is evident that variations of transition probabilities from and to particular condition states will affect the recommended rehabilitation budgets from AZNOS, there is a lack of quantitative analysis in this relationship. AZNOS performance models' sensitivity to variations in transition probabilities and current pavement conditions is analyzed. This sensitivity study demonstrates the inherent relationship among prediction models (TPMs), rehabilitation needs, and current pavement conditions. This analysis also reveals an important property of AZNOS that large future savings in the pavement rehabilitation program may be obtained through the applications of effective preventive maintenance actions to existing pavements.


  • English

Media Info

  • Features: Figures; References; Tables;
  • Pagination: p. 22-30
  • Monograph Title: Pavement performance data
  • Serial:

Subject/Index Terms

Filing Info

  • Accession Number: 00715598
  • Record Type: Publication
  • ISBN: 0309062004
  • Files: TRIS, TRB
  • Created Date: Jan 18 1996 12:00AM