Characterizing the Distribution of Safety Occurrences in Aviation

Abstract

The demand for air travel continues to grow rapidly, and by 2010, air traffic in Europe is expected to be twice the 1990 level. This increase in air traffic may adversely affect safety if appropriate measures are not taken. Regulators and Air Navigation Service Providers (ANSPs) analyze incidents to identify ways to prevent them from happening again. Incidents are rare events in airspace, and this poses problems with robust statistical testing and trend analysis. Aviation safety analysis uses the Poisson distribution where possible, but doubts remain as to its appropriateness. Incident data from ANSP were analyzed over 17 years in a logical quantitative manner using extreme value theory (EVT), a method that uses the limited amount of information available on incidents and defines a distribution that can be used to make statistical inferences. EVT has had considerable use in other fields but little in aviation. A statistical analysis and validation framework is outlined and used to test the data using Poisson, negative binomial, and EVT. The goodness-of-fit tests, as well as other statistical tests, indicate that by far the best fit of the data is achieved using EVT. Further analysis using EVT shows its efficacy as a tool for monitoring and predicting incidents, based on statistical hypothesis and the use of quantile information.

Extreme value theory-based integrity monitoring of global navigation satellite systems

“…Panagiotakopoulos et al (2009) proposed the use of EVT to model accidents and incidents in aviation.…”