2026-09-19T21:55:32Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/671872022-01-13T07:54:11Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Hamsa Balakrishnan.
Khadilkar, Harshad (Harshad Dilip)
Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
2011-11-18T20:57:52Z
2011-11-18T20:57:52Z
2011
2011
http://hdl.handle.net/1721.1/67187
758648140
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 97-99).
The focus of research in air traffic control has traditionally been on the airborne flight phase. Recently, increasing the efficiency of surface operations has been recognized to have significant potential benefits in terms of fuel and emissions savings. To identify opportunities for improvement and to quantify the consequent gains in efficiency, it is necessary to characterize current operational practices. This thesis describes a framework for analysis of airport surface operations and proposes metrics to quantify operational performance. These metrics are then evaluated for Boston Logan International Airport using actual surface surveillance data. A probabilistic model for real-time prediction of aircraft taxi-out times is described, which improves upon the accuracy of previous models based on queuing theory and regression. Finally, a regression model for estimation of aircraft taxi-out fuel burn is described. Together, the modules described here form the basis for a surface operations optimization tool that is currently under development.
by Harshad Khadilkar.
S.M.
99 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Aeronautics and Astronautics.
Analysis and modeling of airport surface operations
Thesis
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<Abstract>The focus of research in air traffic control has traditionally been on the airborne flight phase. Recently, increasing the efficiency of surface operations has been recognized to have significant potential benefits in terms of fuel and emissions savings. To identify opportunities for improvement and to quantify the consequent gains in efficiency, it is necessary to characterize current operational practices. This thesis describes a framework for analysis of airport surface operations and proposes metrics to quantify operational performance. These metrics are then evaluated for Boston Logan International Airport using actual surface surveillance data. A probabilistic model for real-time prediction of aircraft taxi-out times is described, which improves upon the accuracy of previous models based on queuing theory and regression. Finally, a regression model for estimation of aircraft taxi-out fuel burn is described. Together, the modules described here form the basis for a surface operations optimization tool that is currently under development.</Abstract>
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