By Topic

Planning aircraft taxiing trajectories via a multi-ojective immune optimisation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jun Chen ; Sch. of Eng., Univ. of Lincoln, Lincoln, UK ; Stewart, P.

Airport operations include departure sequencing, arrival sequencing, gate/stand allocation and ground movements (taxiing). During the past few decades, air traffic at major airports has been significantly increased and is expected to be so in the near future, which imposes a high requirement for more efficient cooperation across all airport operations. A very important element of this is an accurate estimation of the ground movement, which serves as a link to other operations. Previous researches have been concentrated on the estimation of aircraft taxi time. However, such a concept should be stretched more than just predicting time. It should also be able to estimate the associated cost, e.g. fuel burn, for it to achieve such an expected time. Hence, in this paper, an immune inspired multi-objective optimisation method is employed to investigate such trade-offs for different segments along taxiways, which leads to a set of different taxiing trajectories for each segment. Each of these trajectories, on the one hand, provides an estimation of aircraft taxi time, and on the other hand, has great potential to be integrated into the optimal taxiway routing and scheduling process in a bid to find out the optimal taxiing not only in terms of reducing total taxi time but also in terms of lowering fuel consumption.

Published in:

Natural Computation (ICNC), 2011 Seventh International Conference on  (Volume:4 )

Date of Conference:

26-28 July 2011