A human reliability analysis method based on STPA-IDAC and BN-SLIM for driver take-over in Level 3 automated driving

IF 9.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL Reliability Engineering & System Safety Pub Date : 2024-10-18 DOI:10.1016/j.ress.2024.110577

Wenyi Liao , Yidan Qiao , Tongxin Dong , Zhiming Gou , Dengkai Chen

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Abstract

Human factors play an important role in the take-over process of Level 3 (L3) automated driving. This paper combines Systems Theoretic Process Analysis (STPA) and Information, Decision and Action in Crew context (IDAC) for qualitative analysis and Bayesian Network (BN) and Success Likelihood Index Method (SLIM) for quantitative calculation to obtain the main performance shaping factors (PSFs) and evaluation indicators that cause human errors. Firstly, the STPA-IDAC method is used to analyze unsafe control actions (UCAs) for take-over process and form the mapping relationship of UCAs-IDA-PSFs. Secondly, the BN of human reliability analysis for take-over process is constructed based on the BN-SLIM method. Uncertainty in rates of PSFs and evaluation indicators is addressed in a probabilistic manner using expert opinions and empirical data. After diagnostic reasoning of BN, mean variation is used to identify the main PSFs and evaluation indicators. This method can effectively identify the main PSFs and evaluation indicators that cause human errors, facilitate risk assessment and management, and reduce the human error probability (HEP).

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基于 STPA-IDAC 和 BN-SLIM 的人类可靠性分析方法，用于 3 级自动驾驶中的驾驶员接管

人的因素在三级（L3）自动驾驶的接管过程中发挥着重要作用。本文结合系统理论过程分析法（STPA）和乘员信息、决策与行动分析法（IDAC）进行定性分析，结合贝叶斯网络（BN）和成功可能性指数法（SLIM）进行定量计算，得出导致人为失误的主要性能影响因素（PSF）和评价指标。首先，利用 STPA-IDAC 方法分析接管过程中的不安全控制行为（UCA），形成 UCA-IDA-PSFs 的映射关系。其次，基于 BN-SLIM 方法构建了接管过程的人为可靠性分析 BN。利用专家意见和经验数据，以概率方式解决 PSFs 和评价指标比率的不确定性问题。经过 BN 诊断推理后，利用均值变化来识别主要 PSF 和评价指标。该方法可有效识别导致人为错误的主要 PSF 和评价指标，便于风险评估和管理，并降低人为错误概率（HEP）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Reliability Engineering & System Safety 管理科学-工程：工业

CiteScore

15.20

自引率

39.50%

发文量

621

审稿时长

67 days

期刊介绍： Elsevier publishes Reliability Engineering & System Safety in association with the European Safety and Reliability Association and the Safety Engineering and Risk Analysis Division. The international journal is devoted to developing and applying methods to enhance the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure, and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to balance academic material and practical applications.