Single Point Probabalistic Estimation of Remaining Service Life for Pavements Using LTPP Data

In order to provide safe and efficient surface transportation under ever increasing budgetary constraints, modern pavement planning methods emphasize an established and regularly utilized pavement management system (PMS) for state highway agencies (SHAs). Through long term record keeping it becomes possible to forecast future pavement conditions and distresses to effectively plan future projects and budgets. However, not all SHAs maintain a PMS database with sufficient records to forecast pavement behavior. This paper details a probabilistic method of forecasting the remaining service life (RSL) based on International Roughness Index (IRI) when limited time series data are available. The paper is based on data from the Federal Highway Administration (FHWA) Long-Term Pavement Performance (LTPP) program Special Pavement Study (SPS)-1. The method, described herein as Single Record Pavement Life Estimate (SRPLE), is a promising means for SHAs to estimate RSL of specific pavement sections or for the pavement network when pavement condition and distress sampling has not yet occurred or if records are too few to perform pavement condition forecasting. Further, this method may be applicable for local highway agencies who do not regularly collect condition and distress data or do not have capabilities to model time series data. Once calibrated to local practices and environment, the established method will help pavement managers to better estimate pavement RSL with limited data points.