Enhancing decision support systems for airport ground movement
With the expected continued increases in air transportation, the mitigation of the consequent delays and environmental effects is becoming more and more important, requiring increasingly sophisticated approaches for airside airport operations. The ground movement problem forms the link between other...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2013
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| Online Access: | https://eprints.nottingham.ac.uk/13358/ |
| _version_ | 1848791714471346176 |
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| author | Ravizza, Stefan |
| author_facet | Ravizza, Stefan |
| author_sort | Ravizza, Stefan |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | With the expected continued increases in air transportation, the mitigation of the consequent delays and environmental effects is becoming more and more important, requiring increasingly sophisticated approaches for airside airport operations. The ground movement problem forms the link between other airside problems at an airport, such as arrival sequencing, departure sequencing, gate/stand allocation and stand holding. The purpose of this thesis is to contribute to airport ground movement research through obtaining a better understanding of the problem and producing new models and algorithms for three sub-problems. Firstly, many stakeholders at an airport can benefit from more accurate taxi time predictions. This thesis focuses upon this aim by analysing the important factors affecting taxi times for arrivals and departures and by comparing different regression models to analyse which one performs the best for this particular task. It was found that incorporating the information of the airport layout could significantly improve the accuracy and that a TSK fuzzy rule-based system outperformed other approaches. Secondly, a fast and flexible decision support system is introduced which can help ground controllers in an airport tower to make better routing and scheduling decisions and can also absorb as much of the waiting time as possible for departures at the gate/stand, to reduce the fuel burn and environmental impact. The results show potential maximum savings in total taxi time of about 30.3%, compared to the actual performance at the airport. Thirdly, a new research direction is explored which analyses the trade-off between taxi time and fuel consumption during taxiing. A sophisticated new model is presented to make such an analysis possible. Furthermore, this research provides the basis for integrating the ground movement problem with other airport operations. Datasets from Zurich Airport, Stockholm-Arlanda Airport, London Heathrow Airport and Hartsfield-Jackson Atlanta International Airport were utilised to test these sub-problems. |
| first_indexed | 2025-11-14T18:32:54Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-13358 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:32:54Z |
| publishDate | 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-133582025-02-28T11:24:40Z https://eprints.nottingham.ac.uk/13358/ Enhancing decision support systems for airport ground movement Ravizza, Stefan With the expected continued increases in air transportation, the mitigation of the consequent delays and environmental effects is becoming more and more important, requiring increasingly sophisticated approaches for airside airport operations. The ground movement problem forms the link between other airside problems at an airport, such as arrival sequencing, departure sequencing, gate/stand allocation and stand holding. The purpose of this thesis is to contribute to airport ground movement research through obtaining a better understanding of the problem and producing new models and algorithms for three sub-problems. Firstly, many stakeholders at an airport can benefit from more accurate taxi time predictions. This thesis focuses upon this aim by analysing the important factors affecting taxi times for arrivals and departures and by comparing different regression models to analyse which one performs the best for this particular task. It was found that incorporating the information of the airport layout could significantly improve the accuracy and that a TSK fuzzy rule-based system outperformed other approaches. Secondly, a fast and flexible decision support system is introduced which can help ground controllers in an airport tower to make better routing and scheduling decisions and can also absorb as much of the waiting time as possible for departures at the gate/stand, to reduce the fuel burn and environmental impact. The results show potential maximum savings in total taxi time of about 30.3%, compared to the actual performance at the airport. Thirdly, a new research direction is explored which analyses the trade-off between taxi time and fuel consumption during taxiing. A sophisticated new model is presented to make such an analysis possible. Furthermore, this research provides the basis for integrating the ground movement problem with other airport operations. Datasets from Zurich Airport, Stockholm-Arlanda Airport, London Heathrow Airport and Hartsfield-Jackson Atlanta International Airport were utilised to test these sub-problems. 2013-07-15 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/13358/1/PhD-Thesis_Stefan-Ravizza.pdf Ravizza, Stefan (2013) Enhancing decision support systems for airport ground movement. PhD thesis, University of Nottingham. airport operations ground movement routing scheduling optimisation operations research decision support systems taxi time estimation statistical analysis data mining multiple linear regression fuzzy rule-based system graph-based approach multi-objective routing environmental impact |
| spellingShingle | airport operations ground movement routing scheduling optimisation operations research decision support systems taxi time estimation statistical analysis data mining multiple linear regression fuzzy rule-based system graph-based approach multi-objective routing environmental impact Ravizza, Stefan Enhancing decision support systems for airport ground movement |
| title | Enhancing decision support systems for airport ground movement |
| title_full | Enhancing decision support systems for airport ground movement |
| title_fullStr | Enhancing decision support systems for airport ground movement |
| title_full_unstemmed | Enhancing decision support systems for airport ground movement |
| title_short | Enhancing decision support systems for airport ground movement |
| title_sort | enhancing decision support systems for airport ground movement |
| topic | airport operations ground movement routing scheduling optimisation operations research decision support systems taxi time estimation statistical analysis data mining multiple linear regression fuzzy rule-based system graph-based approach multi-objective routing environmental impact |
| url | https://eprints.nottingham.ac.uk/13358/ |