AN IMPROVED METHOD TO PREDICT ASPHALTIC AIRPORT PAVEMENT REPAIR HOURS: A CASE STUDY OF CHANGI AIRPORT

Abstract

Airport pavement often requires many repair hours to sustain certain levels of pavement condition for aircraft safety. However, the repair windows at busy airports are usually inadequate, which makes the repair tasks difficult. Hence, this study attempts to develop an improved model to predict airport pavement repair hours. The research methodology is based on the regression design and a case study of Singapore Changi Airport. Because of endogeneity, the Vector-Autoregression modeling method without any a priori restrictions on the model is used to estimate the equations. The results show that the major determinants of repair hours are lagged repair hours and rainfall. Also, traffic conditions do not affect repair hours because the monthly increments in aircraft traffic are cyclical and not large. Technical change is used as a new variable to model the change progress in pavement repairs, which is new to the existing pavement repair literature.