Abstract

Proceedings of the 48th IEEE Conference on Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009.

The accurate estimation of airport capacity is critical for the efficient planning of landing and takeoff operations, and the mitigation of congestion-induced delays. The analysis of tradeoffs between arrival and departure capacity at an airport, represented by the airport capacity envelope, has been the main focus of prior research. The increasing demand for air traffic operations has resulted in the growth of multi-airport systems, in which several major airports that are in close proximity of each other serve the same geographical region. The arrival and departure flows into these airports interact with each other, and it is necessary to consider inter-airport arrival-departure capacity tradeoffs while scheduling operations. This paper proposes a statistical technique based on quantile regression, for systematically analyzing arrival-departure capacity tradeoffs in multi-airport systems using observations of flight operations. The proposed technique enables the identification of key factors (such as, runway configuration geometry, weather conditions, etc.) that influence both the capacity envelopes of individual airports, and the capacity envelope of the multi-airport system as a whole. The approach is demonstrated through an analysis of the capacity envelopes of the New York area multi-airport system (comprising Newark (EWR), John F. Kennedy (JFK) and LaGuardia (LGA) airports).

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The different versions of the original document can be found in:

https://orcid.org/0000-0002-8624-7041 under the license cc-by-nc-sa
https://dblp.uni-trier.de/db/conf/cdc/cdc2009.html#RamanujamB09,
http://web.mit.edu/hamsa/www/pubs/RamanujamBalakrishnanCDC2009.pdf,
https://ieeexplore.ieee.org/document/5400462,
https://dspace.mit.edu/handle/1721.1/58731,
https://academic.microsoft.com/#/detail/2117604970 under the license http://creativecommons.org/licenses/by-nc-sa/3.0/
http://dx.doi.org/10.1109/cdc.2009.5400462
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Published on 01/01/2009

Volume 2009, 2009
DOI: 10.1109/cdc.2009.5400462
Licence: Other

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