Robust decision-support tools for airport surface traffic

Forecasts of departure demand are one of the driving inputs to tactical decision-support tools (DSTs) for airport surface traffic. While there are well-known results on average- or worst-case forecast uncertainty, it is the forecast errors which occur under best-case minimum-uncertainty conditions which constrain robust DST design and the achievable traffic benefits. These best-case errors have never previously been characterized. Several quantitative models and techniques for computing pushback forecasts are developed. These are tested against a dataset of 17,344 real-world airline ground operations covering 3 months of Lufthansa flights transiting Frankfurt International Airport. The Lufthansa dataset includes detailed timing information on all of the turn processes, including deboarding, catering, cleaning, fueling and boarding. The dataset is carefully filtered to obtain a sample of 3820 minimum-uncertainty ground events. The forecast models and techniques are tested against this sample, and it is observed that current pushback forecast errors (on the order of ±15min) cannot be reduced by a factor of more than 2 or 3. Furthermore, for each ground event, only 3 observations are necessary to achieve this best-case performance: the available ground-time between actual onblock and scheduled offblock; the time until deboarding begins; and the time until boarding ends. Any DST used in real-world operations must be robust to this "noise floor". To support the development of robust DSTs, a unified framework called ceno-scale modelling is developed.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2004

Author dc:creator

• Carr, Francis R. (Francis Russell), 1976-

Advisor dc:contributor.advisor

• Eric Feron.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/16610

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/16610