DocumentCode :
3169914
Title :
Approximating the likelihood of historical airline actions to evaluate airline delay cost functions
Author :
Bloem, M. ; Haiyun Huang ; Bambos, Nicholas
Author_Institution :
NASA Ames Res. Center, Moffett Field, CA, USA
fYear :
2012
fDate :
10-13 Dec. 2012
Firstpage :
508
Lastpage :
513
Abstract :
Delay cost functions that quantify the cost of delay to airlines are essential to air traffic management research. Seventeen delay cost functions from previous research are evaluated with airline actions in Airspace Flow Programs. Airlines are assumed to solve a minimum cost perfect matching problem when matching flights to slots. Unobserved aspects of airline costs are accounted for by adding a noise term to the cost functions. The goal of this research is to find the cost function and corresponding noise parameters that maximize the likelihood of airline actions during 32 Airspace Flow Programs in the summer of 2006. A heuristic is developed that finds cost noise parameters that maximize an approximation of the log-likelihood of the airline actions. When applied to sample estimation problem instances generated by solving linear programming problems with known noise parameters, the heuristic can more accurately estimate noise parameters than a simple simulation-based approach. Validation efforts based on synthetic airline action data generated with known delay cost functions and noise parameters demonstrate that the heuristic is in many cases able to correctly identify as most likely the delay cost function that was in fact used to generate the synthetic data. However, the heuristic also under-estimates the magnitude of the cost noise variance on these estimation problem instances. Delay costs that are proportional to the length of delay, but with larger proportionality constants for flights bound for hub airports, maximize the approximation of the log-likelihood of the historical airline actions. The estimated standard deviations of the cost noise, expressed as a fraction of the average assignment cost for the historical matchings, ranged from 0.1 to 0.7 for cost functions that achieved relatively large approximate log-likelihoods.
Keywords :
air traffic control; approximation theory; cost reduction; linear programming; minimisation; parameter estimation; travel industry; air traffic management; airline action likelihood maximization; airline delay cost function evaluation; airspace flow programs; cost noise variance; estimation problem; historical airline action likelihood approximation; historical matchings; hub airports; linear programming problems; log-likelihood approximation; log-likelihood approximation maximization; minimum cost perfect matching problem; noise parameter estimation; synthetic airline action data; Approximation methods; Atmospheric modeling; Cost function; Delay; Estimation; Noise; Standards;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
ISSN :
0743-1546
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
Type :
conf
DOI :
10.1109/CDC.2012.6426333
Filename :
6426333
Link To Document :
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