在拥挤的终端空域集成无人机:给飞行员带来的挑战

IF 1.3 Q3 REMOTE SENSING
Julie Diiulio, L. Militello, Devorah E. Klein
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引用次数: 2

摘要

在拥挤的航站楼环境中操作无人驾驶飞机系统(UAS)的需求越来越大,例如繁忙的商业机场。伴随着这种需求,飞行员也面临着挑战。为了识别这些挑战,我们对飞行员进行了关键决策方法(CDM)访谈。CDM是一种认知任务分析方法,旨在揭示隐性认知挑战。八名来自美国的飞行员接受了采访,其中包括四名无人机飞行员和四名商业飞行员。使用主题分析对访谈进行分析,从而确定了四类认知挑战:(i)注意异常,(ii)诊断自动化行为,(iii)了解何时以及如何干预,以及(iv)与空中交通管制协调。在本文中,我们描述了每一个挑战,重点介绍了我们采访中的真实世界例子,并为解决在拥挤的终端空域集成无人机的影响提供了一些建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
UAS integration in congested terminal airspace: challenges posed to pilots
There is increasing demand to operate unmanned aircraft systems (UAS) in congested terminal environments, such as busy commercial airports. With this demand comes challenges to pilots. To identify these challenges, we conducted critical decision method (CDM) interviews with pilots. CDM is a cognitive task analysis method aimed at uncovering tacit cognitive challenges. Eight pilots from the U.S. were interviewed including four UAS pilots and four commercial pilots. Interviews were analyzed using thematic analysis, resulting in the identification of four categories of cognitive challenges: (i) noticing anomalies, (ii) diagnosing automation behavior, (iii) understanding when and how to intervene, and (iv) coordinating with air traffic control. In this paper, we describe each challenge, highlight real-world examples from our interviews, and provide some recommendations for addressing the implications of integrating UAS in congested terminal airspace.
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来源期刊
CiteScore
5.30
自引率
0.00%
发文量
2
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