Predicting the Severity of Runway Excursions from Aviation Safety Reports

What is it about?

Despite all technological advances, runway excursions (RE) are among the most frequent aviation accidents. Several factors have been shown to contribute to RE incidents. While different studies have addressed the prediction of RE using quantitative data, the present contributes to RE research by applying advanced quantitative analysis methods using text mining of voluntarily submitted reports to predict aircraft damage as the outcome of a runway excursion event. Three algorithms are tested with the Random Forest Method, presenting the best performance. Some generalizable topics were identified in the reports, such as runway and touchdown zone characteristics, flight control during approach, aircraft malfunction, weather factors, and runway surface and braking action conditions.

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Photo by Avel Chuklanov on Unsplash

Photo by Avel Chuklanov on Unsplash