A Queuing Model of the Airport Departure Process

This paper presents an analytical model of the aircraft departure process at an airport. The modeling procedure includes the estimation of unimpeded taxi-out time distributions and the development of a queuing model of the departure runway system based on the transient analysis of D/E/1 queuing syst...

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Bibliographic Details
Main Authors: Balakrishnan, Hamsa (Contributor), Simaiakis, Ioannis (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor)
Format: Article
Language:English
Published: Institute for Operations Research and the Management Sciences (INFORMS), 2016-11-18T15:35:01Z.
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Online Access:Get fulltext
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100 1 0 |a Balakrishnan, Hamsa  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Aeronautics and Astronautics  |e contributor 
100 1 0 |a Balakrishnan, Hamsa  |e contributor 
100 1 0 |a Simaiakis, Ioannis  |e contributor 
700 1 0 |a Simaiakis, Ioannis  |e author 
245 0 0 |a A Queuing Model of the Airport Departure Process 
260 |b Institute for Operations Research and the Management Sciences (INFORMS),   |c 2016-11-18T15:35:01Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/105359 
520 |a This paper presents an analytical model of the aircraft departure process at an airport. The modeling procedure includes the estimation of unimpeded taxi-out time distributions and the development of a queuing model of the departure runway system based on the transient analysis of D/E/1 queuing systems. The parameters of the runway service process are estimated using operational data. Using the aircraft pushback schedule as input, the model predicts the expected runway schedule and takeoff times. It also estimates the expected taxi-out time, queuing delay, and its variance for each flight in addition to the congestion level of the airport, sizes of the departure runway queues, and the departure throughput. The proposed approach is illustrated using a case study based on Newark Liberty International Airport. The model is trained using data from 2011 and is subsequently used to predict taxi-out times in 2007 and 2010. The predictions are compared with actual data to demonstrate the predictive capabilities of the model. 
520 |a National Science Foundation (U.S.) (Award 0931843) 
546 |a en_US 
655 7 |a Article 
773 |t Transportation Science