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Adapting Automation Transparency to Allow Accurate Use by Humans

Adapting Automation Transparency to Allow Accurate Use by Humans
调整自动化透明度以允许人类准确使用
批准号:
FT190100812
负责人:
Prof Shayne Loft
金额:
$73.02万
依托单位国家:
澳大利亚
项目类别:
ARC Future Fellowships
财政年份:
2021
资助国家:
澳大利亚
项目状态:
未结题
起止时间:
2021-01-04 至 2025-01-31

项目摘要

项目成果

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中文摘要
翻译
该项目将进行迫切需要的人为因素研究,以发现如何最好地使高风险工作环境中的自动化更加透明和可供人类使用。在国防和航空等安全关键工作环境中,自动化决策辅助工具可以改善人类的决策。然而,不幸的是,灾难性的事故已经发生,因为人类操作员没有遵循正确的自动建议,或者遵循了不正确的自动建议。一系列使用无人驾驶车辆控制、空中交通管制和潜艇轨道管理任务(包括现场设置的测试专家)的人为因素研究将发现如何最好地设计透明的自动化,可以被人类安全有效地使用。
英文摘要
The project will conduct the human factors research urgently required to discover how best to make automation in high-risk work settings more transparent and usable by humans. In safety-critical work contexts such as defence and aviation, automated decision aids improve human decision-making. Unfortunately however, catastrophic accidents have occurred because human operators have either not followed correct automated advice, or followed incorrect automated advice. A series of human factors studies using unmanned vehicle control, air traffic control, and submarine track management tasks (including testing experts in field settings) will discover how best to design transparent automation that can be safely and efficiently used by humans.
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Modelling How Humans Adapt to Task Demands in Safety-Critical Workplaces
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  • 项目类别:
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  • 资助金额:
    $18.92万
  • 财政年份:
    2021
  • 负责人:
    Prof Shayne Loft
  • 依托单位:
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  • 财政年份:
    2016
  • 负责人:
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  • 财政年份:
    2012
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How attention and memory for past events interact in determining performance in an air traffic control conflict detection task
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