Hierarchical Bayesian Models to Estimate the Number of Losses of Separation between Aircraft in Flight

Air transport is considered to be the safest mode of mass transportation. Air traffic management (ATM) systems constitute one of the fundamental pillars that contribute to these high levels of safety. In this paper we wish to answer two questions: (i) What is the underlying safety level of ATM syste...

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Bibliographic Details
Published in:Applied sciences 2021-02, Vol.11 (4), p.1600
Main Authors: Valdés, Rosa María Arnaldo, Comendador, Victor Fernando Gómez
Format: Article
Language:English
Subjects:
Air navigation
Air traffic control
Air traffic management
Air transportation
Aircraft
Aviation
Bayesian analysis
Efficiency
hierarchical
Mathematical models
regression
risk
Safety
separation minima infringements
Structural hierarchy
Traffic management
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Summary:Air transport is considered to be the safest mode of mass transportation. Air traffic management (ATM) systems constitute one of the fundamental pillars that contribute to these high levels of safety. In this paper we wish to answer two questions: (i) What is the underlying safety level of ATM systems in Europe? and (ii) What is the dispersion, that is, how far does each ATM service provider deviate from this underlying safety level? To do this, we develop four hierarchical Bayesian inference models that allow us to infer and predict the common rate of occurrence of SMIs, as well as the specific rates of occurrence for each air navigation service provider (ANSP). This study shows the usefulness of hierarchical structures when it comes to obtaining parameters that enable risk to be quantified effectively. The models developed have been found to be useful in explaining and predicting the safety performance of 29 European ATM systems with common regulations and work procedures, but with different circumstances and numbers of aircraft, each managing traffic of differing complexity.
ISSN:2076-3417
2076-3417
DOI:10.3390/app11041600