Bayesian network for managing runway overruns in aviation safety

Abstract

Runway excursions at landing constitute a major threat to aviation safety. Among them, runway overruns, defined as those occurrences when an aircraft departs the end of a runway, are the most frequent events. Although their occurrence rate is low, the entailed consequences may be very severe in terms of lives and aircraft damage. The main contributing factors to this event and their relationships are studied with the aid of a Bayesian network, while also modeling the nodes' conditional distributions. Then, inferences and predictions are made for the quantities of interest. The issues uncovered suggest several operational recommendations to reduce the probability of facing a runway overrun when landing.