PAVEMENT CONDITION DATA ANALYSIS AND MODELING.

To maximize the benefits of pavement management, a reliable method of pavement condition forecasting is extremely important. Described is a methodology for pavement condition data analysis and a modeling technique for use in the PAVER pavement management system. The latest PAVER data bases from 18 civilian agencies and 2 military installations were used to verify this methodology. Several models were developed for each location to account for the wide variety of factors affecting pavement performance. Relevant information of the pavement sections was organized into pavement families; a family is defined by the pavement type, pavement rank, and pavement functional classification. A screening procedure was designed to examine the data retrieved for obvious errors. A statistical outliers analysis was implemented to detect any unusual observations. The family model accepted for pavement condition index prediction was developed from the pavement AGE variable averaged every 3 years to obtain a representative point for each 3-year period. This point was then used in the final polynomial regression analysis.