Development of Improved Pavement Performance Prediction Models for the Indiana Pavement Management System

Abstract

The Indiana Department of Transportation (INDOT) is increasingly committed to the Pavement Management System. For this reason, updated simple pavement performance prediction models with the least number of explanatory (independent) variables are required to predict the performance of various pavement types for future planning of rehabilitation or replacement. In Indiana, the two main pavement types are jointed concrete pavement (JCP) and bituminous pavement (BIT). 1999 and 2000 year data were used to develop regression models for different pavement types for the Interstate and Non- Interstate Roads systems. The International Roughness Index (IRI), in inches per mile, was mainly used for dependent variables while the age (AGE) of pavement and the current average annual daily traffic (AADT) were used as independent variables in best model searching. The data from the road test sections, which were randomly selected for this study, did not yield statistically strong pavement performance prediction models more probably due to non-uniform construction and foundation of the test sections. However, a few f the following regression models with R2 close or higher than 0.50 were obtained and listed in the text for use by the INDOT. IRI=43+1.8*AGE+0.0004*AADT for Flexible pavements on Interstate Roads, R2 =0.70. IRI=65+1.9*AGE+0.0003*AADT for Jointed Concrete pavements (JCP) on Interstate Roads, R2 =0.50. IRI=37+10.4*AGE+0.0002*AADT for Thin Overlay pavements on Interstate Roads, R2 =0.34. IRI=65+8.1*AGE+0.0009*AADT for Overlay pavements on Non-Interstate Roads, R2 =0.90. IRI=93+1.1*AGE+0.0012*AADT for Jointed Concrete pavements (JCP) on Non-Interstate Roads, R2 =0.27. IRI=64+4.0*AGE+0.0008*AADT for asphalt pavements on Non-Interstate Roads, R2 =0.30. The rutting is recommended to be used as safety factors along with the pavement prediction model