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Aircraft taxi time prediction: comparisons and insights

Version 2 2024-03-12, 12:14
Version 1 2023-10-18, 07:56
journal contribution
posted on 2024-03-12, 12:14 authored by Stefan Ravizza, Jun Chen, Jason A. D. Atkin, Paul Stewart, Edmund K. Burke

The predicted growth in air transportation and the ambitious goal of the European Commission to have on-time performance of flights within 1 minute, makes efficient and predictable ground operations at airports indispensable.Accurately predicting taxi times of arrivals and departures serves as an important key task for runway sequencing, gateassignment and ground movement itself. This research tests different regression approaches to more accurately predicttaxi times. Historic data from two major European airports is utilised for cross-validation. Detailed comparisons showthat a TSK fuzzy rule-based system outperformed the other approaches in terms of prediction accuracy. Insights fromthis approach are then presented, focusing on the analysis of taxi-in times, which is rarely discussed in literature.

Funding

EPSRC (The Engineering and Physical Sciences Research Council)

History

School affiliated with

  • School of Engineering (Research Outputs)

Publication Title

Applied Soft Computing

Volume

14

Issue

c

Pages/Article Number

397-406

Publisher

Elsevier Science Ltd.

ISSN

1568-4946

eISSN

1872-9681

Date Submitted

2013-10-07

Date Accepted

2013-10-06

Date of First Publication

2013-10-23

Date of Final Publication

2013-10-23

ePrints ID

12084