Designing automation for human use: empirical studies and quantitative models
Designing automation for human use: empirical studies and quantitative models
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DOI：
10.1080/001401300409125
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发表时间：
2000-07-01
期刊：
影响因子：
2.4
通讯作者：
Parasuraman, R
中科院分区：
文献类型：
--
作者：
Parasuraman, R
人类绩效研究的新兴知识库可以为设计自动化提供指导，供复杂系统的人类操作员有效使用。在给定系统中哪些功能应该自动化以及自动化程度如何？描述了自动化类型和级别的模型，该模型为做出此类选择提供了框架和客观基础。使用该模型时，特定类型和水平的自动化对人类绩效的影响构成了自动化设计的主要评估标准。考虑了四个人类绩效领域：脑力负荷、态势感知、自满和技能退化。次要评估标准包括自动化可靠性、决策/行动后果的风险以及系统集成的难易程度等因素。除了这种定性方法之外，定量模型也可以为设计提供信息。回顾了各种研究人员提出的人类与自动化交互的几种计算和形式模型。未来的一个重要研究需求是定性和定量方法的整合。这些模型的应用为设计自动化以供人类有效使用提供了客观基础。
An emerging knowledge base of human performance research can provide guidelines for designing automation that can be used effectively by human operators of complex systems. Which functions should be automated and to what extent in a given system? A model for types and levels of automation that provides a framework and an objective basis for making such choices is described. The human performance consequences of particular types and levels of automation constitute primary evaluative criteria for automation design when using the model. Four human performance areas are considered-mental workload, situation awareness, complacency and skill degradation. Secondary evaluative criteria include such factors as automation reliability, the risks of decision/action consequences and the ease of systems integration. In addition to this qualitative approach, quantitative models can inform design. Several computational and formal models of human interaction with automation that have been proposed by various researchers are reviewed. An important future research need is the integration of qualitative and quantitative approaches. Application of these models provides an objective basis for designing automation for effective human use.