Bayesian Network Model and Causal Analysis of Ship Collisions in Zhejiang Coastal Waters

<div>For taking counter measures in advance to prevent accidental risks, it is of significance to explore the causes and evolutionary mechanism of ship collisions. This article collects 70 ship collision accidents in Zhejiang coastal waters, where 60 cases are used for modeling while 10 cases are used for verification (testing). By analyzing influencing factors (IFs) and causal chains of accidents, a Bayesian network (BN) model with 19 causal nodes and 1 consequential node is constructed. Parameters of the BN model, namely the conditional probability tables (CPTs), are determined by mathematical statistics methods and Bayesian formulas. Regarding each testing case, the BN model’s prediction on probability of occurrence is above 80% (approaching 100% indicates the certainty of occurrence), which verifies the availability of the model. Causal analysis based on the backward reasoning process shows that H (Human error) is the main IF resulting in ship collisions. The causal chain that maximizes the likelihood of an accident occurring is: H1 (improper lookout) → H4 (underestimation of collision) → H7 (failure of taking effective collision-avoidance measures) → H (human error) → C (ship collision). By implementing sensitivity analysis process, key IFs of ship collisions are found and are ranked as: H9 (improper emergency handling), H7 (failure of taking effective collision-avoidance measures), H6 (without using safe speed), H4 (underestimation of collision), H1 (improper lookout), H3 (nonstandard duty), H8 (failure of fulfilling “giving way” responsibility), H5 (unaware of target ships), and H2 (crew incompetence). Among them, H9 (improper emergency handling) and H7 (failure to take effective collision-avoidance measures) have relatively high sensitivity and greater impact on collision accidents. Results show that the BN model can be used to analyze the causes of ship collisions in Zhejiang coastal waters and to predict the probability of occurrence of accidents. The research will provide theoretical and practical support for exploring the causes and revealing the evolutionary mechanism of accidents, and for taking targeted risk control measures to prevent future accidents.</div>