A fuzzy approach to addressing uncertainty in Airport Ground Movement optimisation
- Submitting institution
-
The University of Leicester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2388
- Type
- D - Journal article
- DOI
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10.1016/j.trc.2018.04.020
- Title of journal
- Transportation Research Part C: Emerging Technologies
- Article number
- -
- First page
- 150
- Volume
- 92
- Issue
- -
- ISSN
- 0968-090X
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
https://doi.org/10.1016/j.trc.2018.04.020
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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5
- Research group(s)
-
-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The algorithm is based on an adaptive Mamdani Fuzzy Rule based System and has been applied to real world instances from Manchester Airport to estimate taxi times and their uncertainties, leading to a reduction (by 10-20%) in delays due to uncertain taxi times. Work was an outcome of EPSRC grant EP/H004424/2 (2011-2014), EP/J017515/1 (2012-2019), EP/N029496/2 (2016-2020) and EP/N029577/1 (2016-2019). Work attracted further funding three times from QMUL-EPSRC/IAA (https://www.sems.qmul.ac.uk/news/5002/funding-awarded-to-develop-a-simulation-tool-for-airside-operations-incorporating-intelligent-autonomous-taxiing), AVISU (stephen.oflynn@avisu.co.uk), and National Air Traffic Services (richard.cannon@nats.co.uk).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -