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A hybrid human and organisational analysis method for railway accidents based on STAMP-HFACS and human information processing

机译:基于印章 - HFACS和人力信息处理的铁路事故混合人体和组织分析方法

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摘要

Safety is a constant priority for the railway industry and there are numerous hazards in and around the rail system which may result in damage to train and environment, human injury and fatalities. Low levels of human and organisational performance have been shown to be a prime cause of railway accidents and a number of accident models and methods have been developed in order to probe deeper into the role played by organisational factors in accident causation. The Systems-Theoretical Accident Modelling and Processes (STAMP) method for example, represents a promising systematic and systemic way of examining sociotechnical systems such as the railway. Another method, the Human Factors Analysis and Classification System (HFACS), based upon Reason's model of human error in an organisational context, has also proved popular as a human factors accident analysis framework. However, human factors elements are still somewhat limited and under-specified and these managerial and social issues within an organisation are simply regarded as sources of failure in the control constraints of STAMP. HFACS likewise, categorises accident data rather than analysing it in more depth. In this context, a hybrid human and organisational analysis method based on HFACS-STAMP (HFACS-STAMP method for railway accidents, HS-RAs) is proposed to identify and analyse human and organisational factors involved in railway accidents. Using the categories of human errors derived from HFACS and the structured systematic analysis process of STAMP, the HS-RAs method provides a mechanism by which active failures can promulgate across organisations and give a systemic analysis of human error in accidents. Combined with human information processing, the HS-RAs method gives a detailed causal analysis of human errors from receiving information to implement control actions. At last, the HS-RAs method is demonstrated using a case study of the 2011 Yong-Wen railway collision. A number of prominent accident causes of human factors are revealed and necessary countermeasures are proposed to avoid the recurrence of similar accidents. The HFACS-STAMP hybrid method has several advantages and can contribute to railway safety by providing a detailed analysis of the role of human error in railway accidents.
机译:安全性是铁路行业的持续优先级,铁路系统中有许多危险可能导致训练和环境,人类伤害和死亡损失。已经显示出低水平的人类和组织表现是铁路事故的主要原因,并且已经开发了许多事故模型和方法,以便更深地探讨了事故原因中的组织因素所扮演的作用。例如,系统 - 理论意外建模和过程(印章)方法,代表了检查诸如铁路等中科科技系统的有前途的系统和系统的方法。根据理性基于组织背景下的人类错误模型,另一种方法,人类因素分析和分类系统(HFACS)也被认为是人类因素事故分析框架的欢迎。然而,人为因素元素仍然有些有限,并且在组织内的这些管理和社会问题被视为邮票控制限制的失败来源。 HFAC同样,对事故数据进行分类而不是在更深入的深度分析。在这种情况下,提出了一种基于HFACS-邮票的混合人和组织分析方法(用于铁路事故的HFACS-RAS,HS-RAS),以确定和分析参与铁路事故的人和组织因素。使用从HFACS的人为错误的类别和邮票的结构化系统分析过程,HS-RAS方法提供了一种机制,主动故障可以跨组织颁布,并对事故中的人为错误进行系统分析。结合人类信息处理,HS-RAS方法给出了从接收信息来实现控制操作的人为错误的详细因果关系。最后,使用2011年永文铁路碰撞的案例研究证明了HS-RAS方法。揭示了许多人类因素的事故原因,并提出了必要的对策,以避免相似事故的复发。 HFACS-RIPL混合方法具有几个优点,通过提供对铁路事故中人为错误的作用的详细分析,可以有助于铁路安全。

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