To address human errors in collision avoidance tasks of remotely controlled ships, this study aims to develop a comprehensive framework for human error analysis within the context of autonomous ships. Firstly, the Hierarchical Task Analysis method is utilized to identify crew collision avoidance tasks associated with the traditional ship, and these tasks are then dissected into different operational stages using the Information Decision Action in a Crew cognitive model. Secondly, a combination of the fault hypothesis method and expert opinions are used to identify potential human error that may occur during collision avoidance operations of remotely controlled ships. Thirdly, an integrated approach is proposed to build a quantitative risk assessment model, which combines Failure Mode and Effects Analysis, Evidential Reasoning, and Belief rules-based Bayesian Network. Then, axiomatic analysis is used to verify the robustness and applicability of the risk assessment model. Finally, based on the results of quantitative risk assessment, specific measures are proposed for enhancing the safety of collision avoidance process of remotely controlled ships. The findings show that uncoordinated interactions of human-computer systems during the decision-making stage are a pivotal factor in the collision avoidance process. Therefore, future design efforts for remote-control centre should prioritize improving the clarity of human-computer interaction interfaces.

中文翻译：

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在避免碰撞期间对远程控制船舶进行人为错误分析


为了解决遥控船舶避碰任务中的人为错误，本研究旨在开发一个在自主船舶背景下进行人为错误分析的综合框架。首先，利用分层任务分析方法识别与传统船舶相关的船员避碰任务，然后使用船员认知模型中的信息决策行动将这些任务分解为不同的操作阶段。其次，将故障假设方法与专家意见相结合，识别遥控船舶避碰操作中可能发生的潜在人为错误。第三，提出了一种构建定量风险评估模型的综合方法，该模型结合了失效模式和影响分析、证据推理和基于信念规则的贝叶斯网络。然后，采用公理分析验证风险评估模型的稳健性和适用性。最后，基于定量风险评估的结果，提出了提高遥控船舶避碰过程安全性的具体措施。研究结果表明，在决策阶段人机系统不协调的交互是避免碰撞过程中的关键因素。因此，未来远程控制中心的设计工作应优先考虑提高人机交互界面的清晰度。