Human errors analysis for remotely controlled ships during collision avoidance

IF 2.8 2区 生物学 Q1 MARINE & FRESHWATER BIOLOGY
Ying Zhou, Zhengjiang Liu, Xinjian Wang, Hui Xie, Juncheng Tao, Jin Wang, Zaili Yang
{"title":"Human errors analysis for remotely controlled ships during collision avoidance","authors":"Ying Zhou, Zhengjiang Liu, Xinjian Wang, Hui Xie, Juncheng Tao, Jin Wang, Zaili Yang","doi":"10.3389/fmars.2024.1473367","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":12479,"journal":{"name":"Frontiers in Marine Science","volume":"156 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Marine Science","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3389/fmars.2024.1473367","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MARINE & FRESHWATER BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

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.
遥控船舶在避碰过程中的人为失误分析
为解决遥控船舶避碰任务中的人为失误问题,本研究旨在开发一个自主船舶背景下的人为失误分析综合框架。首先,利用层次任务分析法确定与传统船舶相关的船员避碰任务,然后利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,结合故障假设法和专家意见,确定遥控船舶避碰操作过程中可能出现的人为错误。第三,提出了一种建立定量风险评估模型的综合方法,该方法结合了失效模式与效应分析、证据推理和基于信念规则的贝叶斯网络。然后,利用公理分析验证风险评估模型的稳健性和适用性。最后,根据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,人机系统在决策阶段的不协调交互是避碰过程中的一个关键因素。因此,未来遥控中心的设计工作应优先考虑提高人机交互界面的清晰度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Frontiers in Marine Science
Frontiers in Marine Science Agricultural and Biological Sciences-Aquatic Science
CiteScore
5.10
自引率
16.20%
发文量
2443
审稿时长
14 weeks
期刊介绍: Frontiers in Marine Science publishes rigorously peer-reviewed research that advances our understanding of all aspects of the environment, biology, ecosystem functioning and human interactions with the oceans. Field Chief Editor Carlos M. Duarte at King Abdullah University of Science and Technology Thuwal is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, policy makers and the public worldwide. With the human population predicted to reach 9 billion people by 2050, it is clear that traditional land resources will not suffice to meet the demand for food or energy, required to support high-quality livelihoods. As a result, the oceans are emerging as a source of untapped assets, with new innovative industries, such as aquaculture, marine biotechnology, marine energy and deep-sea mining growing rapidly under a new era characterized by rapid growth of a blue, ocean-based economy. The sustainability of the blue economy is closely dependent on our knowledge about how to mitigate the impacts of the multiple pressures on the ocean ecosystem associated with the increased scale and diversification of industry operations in the ocean and global human pressures on the environment. Therefore, Frontiers in Marine Science particularly welcomes the communication of research outcomes addressing ocean-based solutions for the emerging challenges, including improved forecasting and observational capacities, understanding biodiversity and ecosystem problems, locally and globally, effective management strategies to maintain ocean health, and an improved capacity to sustainably derive resources from the oceans.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信