Estimation of the Effects of Influential Factors on Pavement Service Life with Cox Proportional Hazards Method

Abstract

Estimating the effects of influential factors on pavement service life is an important, but difficult task for highway agencies. In this paper, by specifying a particular pavement condition rating (PCR) as the terminal pavement status, survival curves were developed based on historical PCR data using the Cox proportional hazards (PH) method. Further, the estimated service lives of pavements are obtained from these survival curves. As an example, the survival data of asphalt overlays on flexible pavements in Ohio are analyzed for this study. The effects of influential factors, such as structure thickness, climate, traffic loading, and pavement conditions prior to repair on pavement service life were assessed. The results show that the Cox PH model is applicable in estimating the effects of influential factors on pavement service life. The service life obtained from this study can be used to assist with pavement rehabilitation decision-making, overlay design, and budget allocation.