人为因素分析与分类系统- AHP无人机模型评估

S. Al-Rabeei, Omar Alharasees, Utku Kale
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引用次数: 2

摘要

无人机系统已经越来越多地应用于各种商业、技术、农业和军事部门。随着无人机事故在许多情况和领域的发生频率产生重大影响,形成无人机系统和使用限制变得越来越必要。要做到这一点,第一步是突出当前过程中事故的根源。人为因素分析与分类系统(HFACS)是无人机系统事故风险评估的主要技术,它将事故关键因素归为4个基本域。在这项研究中,有4类无人机专家参与了研究。该研究采用了一种新的方法,将分析层次决策模型与HFACS相结合,用于无人机事故原因调查。研究结果显示了不同组无人机操作员之间的差异,并确定了组织因素和不安全行为是评估中的关键问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human Factors Analysis and Classification System - AHP Drone Model Assessment
Drone systems have become increasingly applied to various commercial, technical, agricultural, and military sectors. With the emerging significant effects on the frequency of drone accidents in many situations and areas, it has become increasingly necessary to form unmanned aircraft systems and usage limitations. The first step to do that is by highlighting the sources of accidents in the current process. The Human Factors Analysis and Classification System (HFACS) is the main technique for accident risk assessments in drone systems which clusters the accident key factors causes into 4 basic domains. In this study, 4 categories of drone experts participated in the study. The research utilized a new approach that integrates an analytical hierarchical decision-making model with the HFACS for drone accident causation investigation. The results of the study showed discrepancies among the different groups of drone operators and identified organizational factors and unsafe actions as being key issues in the evaluation.
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