A global model for estimating the block time of commercial passenger aircraft

This paper uses a two-stage statistical model to estimate the block time of commercial passenger aircraft. The model considers many of the factors contributing to airport congestion and provides a basis for future development of multivariate statistical models of the flight operation process. The model is tested using 2 million US domestic flights by six airlines in 2004. Model analysis provided insight regarding the relative impact of weather conditions and airport utilization on block time. In particular, population, arrival time, airport utilization, ice, and the interaction of poor weather conditions and traffic were found to be significant predictors of block time.