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首页> 外文期刊>Accident Analysis & Prevention >Application of a human error framework to conduct train accident/incident investigations
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Application of a human error framework to conduct train accident/incident investigations

机译：应用人为错误框架进行火车事故/事故征候调查

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摘要

Accident/incident investigations are an important qualitative approach to understanding and managing transportation safety. To better understand potential safety implications of recently introduced remote control locomotive (RCL) operations in railroad yard switching, researchers investigated six railroad accidents/incidents. To conduct the investigations, researchers first modified the human factors analysis and classification system (HFACS) to optimize its applicability to the railroad industry (HFACS-RR) and then developed accident/incident data collection and analysis tools based on HFACS-RR. A total of 36 probable contributing factors were identified among the six accidents/incidents investigated. Each accident/incident was associated with multiple contributing factors, and, for each accident/incident, active failures and latent conditions were identified. The application of HFACS-RR and a theoretically driven approach to investigating accidents/incidents involving human error ensured that all levels of the system were considered during data collection and analysis phases of the investigation and that investigations were systematic and thorough. Future work is underway to develop a handheld software tool that incorporates these data collection and analysis tools.
机译：事故/事故征候调查是了解和管理运输安全的重要定性方法。为了更好地了解最近在铁路堆场切换中采用的远程控制机车（RCL）操作的潜在安全隐患，研究人员调查了六起铁路事故/事故。为了进行调查，研究人员首先修改了人为因素分析和分类系统（HFACS），以优化其在铁路行业的适用性（HFACS-RR），然后开发了基于HFACS-RR的事故/事件数据收集和分析工具。在所调查的六起事故/事件中，总共确定了36种可能的影响因素。每次事故/事件都与多个影响因素相关联，对于每次事故/事件，都可以识别出主动故障和潜在条件。 HFACS-RR的应用和一种理论驱动的方法来调查涉及人为错误的事故/事故征候，确保了在调查的数据收集和分析阶段都考虑了系统的各个级别，并且调查是系统而彻底的。正在进行开发包含这些数据收集和分析工具的手持式软件工具的工作。

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