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A hybrid HEART method to estimate human error probabilities in locomotive driving process

机译：估计机车驾驶过程中人为错误概率的混合HEART方法

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摘要

Human reliability assessment is an essential work to guarantee the safety of locomotive driving process. Human Error Assessment and Reduction Technique (HEART) is a well-known approach applied to determine human error probability (HEP). However, the deficiencies of HEART are that the list of Error-producing conditions does not include many relevant railway operating performance shaping factors, and HEART does not provide the practitioners with a concrete method to determine the assessed proportion of affect (APOA), which force a heavy reliance on the judgement of single rater in the field. To overcome this problem and to obtain a more accurate APOA, we propose a hybrid HEART method which utilizes the evidence theory to fuse raters' opinions to EPCs determination and APOA for each corresponding EPC and quantify the subjective judgment. A complete locomotive driving process is performed to evaluate HEP. Finally, we apply Monte Carlo simulation to obtain system reliability and validate proposed method. The calculated results are consistent with the experience and knowledge of safety management and simulation results. This hybrid HEART approach is useful to reduce the likelihood of occurrence of errors, and improve the overall safety level in locomotive driving operation and other industries.
机译：人的可靠性评估是确保机车驾驶过程安全的一项重要工作。人为错误评估和减少技术（HEART）是一种用于确定人为错误概率（HEP）的众所周知的方法。但是，HEART的不足之处在于，产生错误的条件列表中没有包括许多相关的铁路运营绩效塑造因素，并且HEART没有为从业人员提供确定影响评估比例（APOA）的具体方法。在现场严重依赖单一评估者的判断。为了克服这个问题并获得更准确的APOA，我们提出了一种混合HEART方法，该方法利用证据理论将评估者的意见融合到EPC的确定和每个相应EPC的APOA中，并对主观判断进行量化。执行完整的机车驾驶过程以评估HEP。最后，我们应用蒙特卡洛仿真来获得系统可靠性并验证所提出的方法。计算结果与安全管理和模拟结果的经验和知识相一致。这种混合式HEART方法可用于减少发生错误的可能性，并提高机车驾驶操作和其他行业的总体安全水平。

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  • 来源
    《Reliability Engineering & System Safety》 |2019年第8期|80-89|共10页
  • 作者

    Zhou Jian-Lan; Lei Yi; Chen Yang;

  • 作者单位

    Huazhong Univ Sci & Technol, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Hubei, Peoples R China|Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Hubei, Peoples R China|Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Hubei, Peoples R China|Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Hubei, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Railway system; Human error probability; Human error assessment and reduction technique; Multi-source information fusion; Fault tree analysis; Monte Carlo simulation;

    机译：铁路系统;人为错误概率;人为错误评估与减少技术;多源信息融合;故障树分析;蒙特卡洛模拟;

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