Applying Association Rules Mining to Investigate Risk Factors Contributing to Aircraft Runway Overshoot

As a high incidence of unsafe incidents, aircraft runway overshoot often causes heavy losses such as casualties or body damage, which poses a serious threat to the safety of aircraft operations. However, there are few studies focused on factors contributing to aircraft runway overshoot. Using aviation accident data collected (2008–2019) by the National Transportation Safety Board (NTSB), this study applied the Frequent Pattern Growth Algorithm to identify the hidden pattern of risk factors contributing to aircraft runway overshoot. The association rules were filtered by support, confidence, and lift. Based on the generated rules, the results show that aircraft runway overshoot are associated with tailwind, aircraft operating or performance parameters, pilot age, the presence of obstacles, and runway distance available. Additionally, pilot decision-making or judgment errors can result in severe outcomes, including casualties. The research findings are expected to provide an improved understanding of the underlying relationships between risk factors contributing to aircraft runway overshoot. Aviation safety experts can utilize these findings to conduct a decision-making process for selecting effective countermeasures to reduce aircraft runway overshoot strategically.