Citation

Goodheart B. Transp. Res. Rec. 2013; 2400: 9-20.

Copyright

(Copyright © 2013, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.3141/2400-02

PMID

unavailable

Abstract

In the United States and worldwide, runway incursions are acknowledged as a critical concern for aviation safety. Despite efforts to the contrary, however, the rate at which these events occur in the United States has steadily risen. Analyses of the causes of runway incursions have frequently been limited to discrete events and have not addressed the dynamic interactions that led to breaches of runway safety. This paper emphasizes the need for cross-domain methods of causation analysis applied to runway incursions in the United States. A holistic modeling technique using Bayesian belief networks to interpret causation in the presence of sparse data is outlined, with intended application at the systems level. Further, the importance of investigating runway incursions probabilistically and of incorporating information from human factors, technological, and organizational perspectives is supported. A method for structuring Bayesian networks with quantitative and qualitative event analyses in conjunction with structured expert probability estimation is outlined, and results are presented for propagation of evidence through the model as well as for causal analysis. The model provides a dynamic, inferential platform for future evaluation of the causes of runway incursions. The results in part confirm what is known about the causes of runway incursions, but more important shed light on multifaceted causal interactions in a modeling space that allows causal inference and evaluation of changes to the system in a dynamic setting. Suggestions for additional research are discussed; the prominent suggestion is a need for future testing coupled with a focus on higher levels of quantification while exploring means of enhancing availability of relevant data.