Wang, X., Brownlee, A.E.I., Weiszer, M. et al. (3 more authors) (2021) A chance-constrained programming model for airport ground movement optimisation with taxi time uncertainties. Transportation Research Part C: Emerging Technologies, 132. 103382. ISSN 0968-090X
Abstract
Airport ground movement remains a major bottleneck for air traffic management. Existing approaches have developed several routing allocation methods to address this problem, in which the taxi time traversing each segment of the taxiways is fixed. However, taxi time is typically difficult to estimate in advance, since its uncertainties are inherent in the airport ground movement optimisation due to various unmodelled and unpredictable factors. To address the optimisation of taxi time under uncertainty, we introduce a chance-constrained programming model with sample approximation, in which a set of scenarios is generated in accordance with taxi time distributions. A modified sequential quickest path searching algorithm with local heuristic is then designed to minimise the entire taxi time. Working with real-world data at an international airport, we compare our proposed method with the state-of-the-art algorithms. Extensive simulations indicate that our proposed method efficiently allocates routes with smaller taxiing time, as well as fewer aircraft stops during the taxiing process.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Air traffic management; Airport ground movement; Chance-constrained programming; Quickest path search; Taxi time uncertainties |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council EP/N029356/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 27 Oct 2021 09:59 |
Last Modified: | 27 Oct 2021 09:59 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.trc.2021.103382 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:179694 |