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Time-series analysis and modelling to predict aviation safety performance index

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EN
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EN
Safety performance index is a tool with the potential to grasp the intangible domain of aviation safety, based on quantification of meaningful aviation safety system properties. The tool itself was developed in the form of Aerospace Performance Factor and is already available for the aviation industry. However, the tool turned out to be rather unsuccessful as its potential was not fully recognised by the industry. This paper introduces performed analysis on the potential and it outlines new features, utilising time-series analysis, which can improve both the recognition of the index by the industry as well as the motivations to further research and develop methodologies to evaluate overall aviation safety performance using its quantified system properties. This paper discusses not only the features but also their embedding into the existing approach for the development of aviation safety, highlighting possible deficiencies to overcome and relating the scientific work already performed in the domain. Various types of appropriate time-series methodologies are addressed and key specifications of their use with respect to the discussed issue concerning safety performance index are stated.
Czasopismo
Rocznik
Strony
51--58
Opis fizyczny
Bibliogr. 20 poz.
Twórcy
autor
  • Czech Technical University in Prague, Faculty of Transportation Sciences, Horská 3, Prague 2, 128 03, Czech Republic
Bibliografia
  • 1. IATA, 2016. Safety Fact Sheet. International Air Transport Association. Montreal. Canada. Available at: https://www.iata.org/pressroom/facts_figures/fact_sheets/Documents/fact-sheet-safety.pdf
  • 2. ICAO, 2013. 2014 -2016 Global Aviation Safety Plan: Doc 10004. International Civil Aviation Organization, Montréal, Quebec, Canada. ISBN 978-92-9249-355-4.
  • 3. Vittek, P. & Lališ, A. & Stojić, S. & Plos, V. 2016. Runway incursion and methods for safety performance measurement. In: Production Management and Engineering Sciences. Proceedings of the International Conference on Engineering Science and Production Management (ESPM 2015). Tatranská Štrba, High Tatras Mountains. Slovak Republic. 16th-17th April 2015. Bratislava: University of Economics in Bratislava. P. 321-326. ISBN 978-1-138-02856-2.
  • 4. Leveson, N. Engineering a safer world: systems thinking applied to safety. Cambridge, MA: MIT Press. Engineering systems. 2011. ISBN 978-0-262-01662-9.
  • 5. Novák, L. & Němec, V. & Soušek, R. Effect of Normobaric Hypoxia on Psychomotor Pilot Performance. In: The 18th World Multi-Conference on Systemics. Cybernetics and Informatics. Orlando, Florida: International Institute of Informatics and Systemics. 2014. Vol. II. P. 246-250. ISBN 978-1-941763-05-6.
  • 6. Regula, M. & Socha, V. & Kutílek, P. & Socha, L. & Hánaková, L. & Szabo, S. Study of heart rate as the main stress indicator in aircraft pilots. In: 16th Mechatronika 2014. Brno: Brno University of Technology. 2014. P. 639-643. ISBN 978-80-214-4816-2.
  • 7. ICAO, 2013. Safety Management Manual (SMM): Doc 9859. 3rd edition. International Civil Aviation Organization. Montréal. ISBN 978-92-9249-214-4.
  • 8. Kraus, J. & Vittek, P. & Plos, V. Comprehensive emergency management for airport operator documentation. In: Production Management and Engineering Sciences: Proceedings of the International Conference on Engineering Science and Production Management (ESPM 2015). Tatranská Štrba, High Tatras Mountains, Slovak Republic. 2016. Bratislava: University of Economics in Bratislava. P. 139-144. ISBN 978-1-138-02856-2.
  • 9. Fuchs, P. & Němec, V. & Soušek, R. & Szabo, S. & Šustr, M. & Viskup, P. The Assessment of Critica Infrastructure in the Czech Republic. In Proceedings of 19th International Scientific Conference Transport Means. Kaunas: Technologija. 2015. P. 418-424. ISSN 1822-296X.
  • 10. Post, W. ECCAIRS Survey. Presentation at [ECCAIRS Steering Committee Meeting, Brussels, 26-27 October 2015]. Joint Research Centre. Brussels, Belgium. Available at: http://eccairsportal.jrc.ec.europa.eu/index.php/Documents/39/0/.
  • 11. TRADE. A Handbook of Techniques and Tools: How to Measure Performance. 1995. U.S. Training Resources and Data Exchange Department of Energy, Washington, DC. Available at: Internet: http://www.orau.gov/pbm/handbook/handbook_all.pdf
  • 12. EUROCONTROL. The Aerospace Performance Factor (APF): Developing the EUROCONTROL ESARR 2 APF. 2009. European Organisation for the Safety of Air Navigation Brussels, Belgium. Available at: http://aloftaviationconsulting.com/publications/ECTL_APF_Implementation_Plan. pdf.
  • 13. Lintner, T.M. & Smith, S.D. & Licu, A. & Cioponea, R. & Stewart, S. & Majumdar, A. & Dupuy, M.D. The measurement of system-wide safety performance in aviation: Three case studies in the development of the aerospace performance factor (APF). 2009. Available at: https://www.eurocontrol.int/eec/gallery/content/public/document/other/conference/2009/safety_r_and_d_Munich/day_1/Tony-Licu-(EUROCONTROL)-Steve-Smith-(FAA)-Paper.pdf
  • 14. EASA, 2015. ECCAIRS Taxonomy and NoA Update. Presentation at [ECCAIRS Steering Committee Meeting, Brussels, 27th October 2015]. European Aviation Safety Agency, Brussels, Belgium. Available at: http://eccairsportal.jrc.ec.europa.eu/index.php/Documents/39/0/.
  • 15. Di Gravio, G. & Mancini, M. & Patriarca, R. & Costantino, F. Overall safety performance of Air Traffic Management system: Forecasting and monitoring. Safety Science. 2014. Vol. 72. P. 351-362.
  • 16. Rochelle, M.E. & Gurkaynak, R.S. How Useful are Estimated DSGE Model Forecasts for Central Bankers? Brooking papers on Economic Activity, Economic Studies Program. The Brooklins Institution. 2010. Vol. 41 (2 (Fall)). P. 209 -259.
  • 17. Nau, R.F. Statistical forecasting: notes on regression and time series analysis [online]. Duke University: Fuqua School of Business. Durham. 2016. Available at: http://people.duke.edu/~rnau/411home.htm.
  • 18. Chambers, J.C. & Mullick, S.K. & Smith, D.D. How to choose the right forecasting technique. Harvard Business Review. 1971. Vol. 49. No. 4. P. 45-74.
  • 19. Kutner, M.H. & Nachtsheim, Ch.J. & Neter, J. & Wasserman, W. Applied Linear Statistical Models: 5th Edition. Irwin, The McGraw-Hill Companies. 2005. ISBN 0-07-238688-6.
  • 20. Box, G.E.P. & Jenkins, G.M. & Reinsel, G.C., 1994. Time Series Analysis: Forecasting and Control. 3rd ed. Englewood Cliffs. NJ: Prentice Hall. 1994.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-681cada0-e8cc-4c59-8b50-7d59341ba9e8
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