Volume List  / Volume 9 (4)

Article

CHARACTERIZATION OF AIRPORT DELAY

DOI: 10.7708/ijtte.2019.9(4).01


9 / 4 / 358 - 364 Pages

Author(s)

Bianka Karoly - HungaroContorl Ltd. H-1185 Budapest, Igló utca 33-35, Hungary and Budapest University of Technology and Economics, Faculty of Transport Engineering and Vehicle Engineering, Department of Control for Transportation and Vehicle Systems, H-1111, Muegyetem rkp 3, Hungary -

Balazs Saghi - Budapest University of Technology and Economics, Faculty of Transport Engineering and Vehicle Engineering, Department of Control for Transportation and Vehicle Systems, H-1111, Muegyetem rkp 3, Hungary -


Abstract

Scheduling and coordinating the departures and arrivals at the airport can be difficult if there is a delay that has to be taken into account, but relying on a statistical model that bases on historical data could result in better prediction for the future. Therefore, in this study the authors investigate the nature of the airport delays with statistical tools. First the airport delay is defined and the hypothesis was formed. In this paper authors investigated if airport delay follows a normal distribution. Moreover detailed description of used statistical tools are mentioned. In third paragraph the results are examined briefly. As conclusion authors found that generally airport delay not followed normal distribution.


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References:

ÄŒokorilo, O. 2008. Risk management implementation in aircraft accident cost analysis. In Proceedings of the 12th Air Transport Research Society (ATRS) World Conference, 98-102.

 

ÄŒokorilo, O.; Dell'Acqua, G. 2013. Aviation Hazards Identification Using Safety Management System (SMS) Techniques. In Proceedings of 16th International conference on transport science (ICTS 2013), 66-73.

 

Čokorilo, O.; Gvozdenović, S.; Mirosavljević, P.; Vasov, L. 2010. Impact of aircraft emissions on the environment, Journal of Applied Engineering Science 8(3): 123-138.

 

Ford, C. 2018. Understanding Q-Q Plots. Available from Internet: https://data.library.virginia.edu/understanding-q-q-plots/.

 

Ghasemi, A.; Zahediasl, S. 2012. Normality Tests for Statistical Analysis: A Guide for Non-Statisticians, International Journal of Endocrinology and Metabolism 10(2): 486–489. doi: 10.5812/ijem.3505.

 

Kling, F.; Somosi, V.; Pokorádi L.; Rohács D. 2017. Budapest Liszt Ferenc International Airport Aircraft Traffic Analysis with Markov Processes [in Hungarian: Budapest Liszt Ferenc Nemzetközi RepülÅ‘tér légijármű forgalmának elemzése Markov-folyamatokkkal], Aviation Science Letters [in Hungarian: Repüléstudományi Közlemények] 29(3): 115-126.

 

Madácsi, R. 2015. Applying data science techniques to increase runway efficiency [in Hungarian: Data science technikák alkalmazása a futópálya-hatékonyság növelésében], Aviation Science Letters [in Hungarian: Repüléstudományi Közlemények] 27(3): 159-170.

 

Mirosavljević, P.; Gvozdenović, S.; Čokorilo, O. 2011. A model of air traffic assignment as part of airport air pollution management system, Aviation 15(4): 92-100. doi: doi.org/10.3846/16487788.2011.651792.

 

Sipos, T. 2017. Spatial Statistical Analysis of the Traffic Accidents, Periodica Polytechnica Transportation Engineering 45(2): 101-105. doi: 10.3311/PPtr.9895.

 

Serhan, D.; Lee, H.; Yoon, S.W. 2018. Minimizing airline and passenger delay cost in airport surface and terminal airspace operations, Journal of Air Transport Management 73: 120-133. doi: 10.1016/j.jairtraman.2018.07.001.


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