Estimating Flight Departure Delay Distributions - a Statistical Approach with Long-Term Trend and Short-Term Pattern

29 Pages Posted: 11 Aug 2006

See all articles by Yufeng Tu

Yufeng Tu

University of Maryland - Decision and Information Technologies Department

Michael O. Ball

University of Maryland - Decision and Information Technologies Department

Wolfgang Jank

University of Maryland - Decision and Information Technologies Department

Date Written: December 2005

Abstract

In this paper, we develop a model for estimating flight departure delay distributions required by air traffic congestion prediction models. We identify and study major factors influencing flight departure delays, and develop a strategic departure delay prediction model. This model employs nonparametric methods for daily and seasonal trends. In addition, the model uses a mixture distribution to estimate the residual errors. In order to overcome problems with local optima in the mixture distribution, we develop a global optimization version of the Expectation Maximization algorithm, borrowing ideas from Genetic Algorithms. The model demonstrates reasonable goodness of fit, robustness to the choice of the model parameters, and good predictive capabilities. We use flight data from United Airlines and Denver International Airport from the years 2000/01 to train and validate our model.

Keywords: Smoothing spline, mixture model, Expectation Maximization (EM), Genetic Algorithm (GA), airline delay, airspace congestion, delay distribution

Suggested Citation

Tu, Yufeng and Ball, Michael O. and Jank, Wolfgang, Estimating Flight Departure Delay Distributions - a Statistical Approach with Long-Term Trend and Short-Term Pattern (December 2005). Robert H. Smith School Research Paper No. RHS 06-034. Available at SSRN: https://ssrn.com/abstract=923628 or http://dx.doi.org/10.2139/ssrn.923628

Yufeng Tu (Contact Author)

University of Maryland - Decision and Information Technologies Department ( email )

Robert H. Smith School of Business
4313 Van Munching Hall
College Park, MD 20815
United States

Michael O. Ball

University of Maryland - Decision and Information Technologies Department ( email )

Robert H. Smith School of Business
4313 Van Munching Hall
College Park, MD 20815
United States
301-405-2227 (Phone)
301-405-8655 (Fax)

Wolfgang Jank

University of Maryland - Decision and Information Technologies Department ( email )

Robert H. Smith School of Business
4300 Van Munching Hall
College Park, MD 20742
United States
301-405-1118 (Phone)

HOME PAGE: http://www.smith.umd.edu/faculty/wjank/

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