Abstract

Due to air traffic growth and especially hubs development, major European airports can easily become bottlenecks in the global air transportation network. Therefore, accurate models of airport traffic prediction become more and more necessary for ground controllers. In this paper, a ground traffic simulation tool is proposed and applied to Roissy Charles De Gaulle airport. Two global optimization methods, using genetic algorithms at the airport, are developed to minimize taxiing time while respecting aircraft separation and runway capacities. In order to compare the efficiency of the different methods, simulations are carried out on a one day traffic sample, and ground delay is correlated to the traffic density at the airport.


Original document

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

http://dx.doi.org/10.1109/cec.2003.1299623
https://hal-enac.archives-ouvertes.fr/hal-00938059/document,
https://hal-enac.archives-ouvertes.fr/hal-00938059/file/cec2003.pdf
https://dblp.uni-trier.de/db/conf/cec/cec2003-1.html#GottelandD03,
https://hal-enac.archives-ouvertes.fr/hal-00938059,
https://ieeexplore.ieee.org/document/1299623,
https://doi.org/10.1109/CEC.2003.1299623,
https://academic.microsoft.com/#/detail/2110757811
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Document information

Published on 01/01/2003

Volume 2003, 2003
DOI: 10.1109/cec.2003.1299623
Licence: CC BY-NC-SA license

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