The Conditional Probability for Human Error Caused by Fatigue, Stress and Anxiety in Seafaring

Abstract

Human error caused by the interaction and effect of fatigue, stress and anxiety in seafarers is the subject of this research. The human element is a major part of the maritime system. We used Bayesian networks to predict human error in maritime affairs by analysing interactions between people, technology, organisational and environmental factors which make up the specificity of the maritime system. Bayesian networks are graphical structures developed to represent the conditional dependencies among a number of variables and to make conditional conclusions related to the selected variables. Through the analysis of psychic causes such as stress, fatigue, anxiety and so on, the model can produce graphic diagrams indicating which rank on which type of vessel at which seafarers age contributes to an increase in conditional probability of human error. The contribution of the paper is to find the worst combinations of influencing variables that can lead to an increase in the risk of human error. The results show a significant level of fatigue and stress in all officers (engine and nautical), regardless of the type of vessel they serve. A strong presence of anxiety is also reported in all surveyed officers, with a higher degree between engine officers.

Keywords

• Bayesian networks
• human errors
• fatigue
• stress
• anxiety
• maritime affairs