Development of a Knowledge-Based Formula to Prioritize Pavement Rehabilitation Projects

Abstract

The development of a formula to prioritize pavement rehabilitation projects based on experts’ opinion is presented. This formula is used for the preparation of the Arizona Department of Transportation (ADOT) 5 yr pavement preservation program. The knowledge to determine the prioritization formula and treatment assignment criteria was captured from a group of experts using a survey design based on the rational factorial methodology. The survey questionnaire provided a set of pavement sections with different characteristics and asked the experts to indicate which sections should receive a rehabilitation treatment, what type of treatment they would recommend for each section, and which priority should be assigned to the resulting preservation project. Eight pavement characteristics (functional classification, geographical region, structural number, traffic, pavement rideability, cracking, rutting, and average maintenance cost for the past 3 yr) were identified as influence variables. A fractional factorial experiment design with four blocks was selected for the study. A questionnaire with a different set of pavement sections was prepared for each experimental block. The questionnaires were sent to pavement experts from ADOT headquarters and maintenance districts. The responses were analyzed, using linear regression analysis, to select the best models for the priority and treatment selection equations. The study showed that the rational factorial methodology is a powerful tool for capturing and quantifying expert opinions. The average opinion of the experts surveyed indicated that rutting, functional classification, roughness, cracking, traffic, and maintenance cost significantly influence the priority assigned to a preservation project. The treatment assignment model was less reliable; a larger panel of experts would be required to obtain a reliable model.