Hong Kong’s port is one of the busiest in the world. Such heavy traffic is associated with a high accident rate. The present study uses Bayesian Networks to analyze accident risk in Hong Kong waters using 331 accident reports during the period of 1999-2017. The methodology adopted is comprised of an analysis of present literature and expert judgments for the determination of nodes and states. The calculation of probabilities and conditional probability tables (CPT) were done based solely on the real data in accident reports through parameter estimation. The results indicate that the highest portion of accidents was categorized as “other” with a probability of 0.5174. The majority of such accidents took place in port waters. The second highest category was “collision” with a probability of 0.2256. Both of these accident types were associated with the highest fatality rate-one or two people killed. Poor judgment, negligence and insufficient training were found to be the most influential factors with regard to human actions. The highest rate of injuries was associated with passenger ships. The results offer valuable insights into various accident scenarios which involve setting evidence at different states of consequences and accident types to determine the most prominent contributing factors. Sensitivity analysis was also conducted to recognize the most critical variables. This study should prove useful to decision and policy makers seeking to enhance sustainable safety in maritime traffic operations.

Safety has been a primary concern in every industry. It includes system, personnel, environmental safety, etc. Maritime transportation safety is of the utmost importance because a lot of economic and environmental damage has been caused by ship-related accidents. The majority of these accidents have resulted from human factors. For the analysis of accidents and future safety, various accident models have been created. In this study, human-based errors are analyzed and quantified by using the fuzzy fault tree analysis, which helps calculate the failure probability of the causes. A real-life case of a chemical tanker Key Bora was studied and analyzed, which happened on 28 March 2020, at Kyleakin Pier, Isle of Skye, Scotland. The ship’s hull was seriously damaged and was flooded. According to the analysis, two main human factors that contributed the most to the occurrence of this accident were found. These incidents can be avoided by ensuring proper measures are followed, and the results can be used as guidelines for future marine accident investigations and safety.

Maritime transportation has a pivotal role in the foreign trade and hence, the world’s economic growth. It augments the realization of “Maritime Silk Road” strategy. However, the catastrophic nature of the maritime accidents has posed a serious threat to life, property, and environment. Maritime transportation safety is a complex system and is prone to human, equipment, and environment-based risks. In the existing literature, the risk assessment studies aimed at the analysis of maritime traffic safety usually consider the state of system as two ultimate states—one is the normal state and the other is the complete failure state. In contrast to the conventional approaches, this study incorporates a multistate criterion for system state giving consideration to the near or partial failures also. A Markov Chain-based methodology was adopted to determine the variations in state system and define the instant at which a low probability incident transforms into a high-risk intolerable event. The analysis imparts critical time nodes that could be utilized to reduce the risk and evade accidents. This study holds practical vitality for the concerned departments to circumvent the potential dangers and devise systematic preemptive procedures before the accident takes place. The results of this study could be employed to augment safety and sustainability of maritime traffic and decrease the associated pollution.