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Adaptable (Not Adaptive) Automation: Forefront of Human–Automation Teaming

自动化 工作量 ISA100.11a 计算机科学 过程自动化系统 形势意识 任务(项目管理) 工程类 风险分析(工程) 系统工程 操作系统 医学 机械工程 航空航天工程
作者
Gloria L. Calhoun
出处
期刊:Human Factors [SAGE Publishing]
卷期号:64 (2): 269-277 被引量:42
标识
DOI:10.1177/00187208211037457
摘要

Objective Identify a critical research gap for the human factors community that has implications for successful human–automation teaming. Background There are a variety of approaches for applying automation in systems. Flexible application of automation such that its level and/or type changes during system operations has been shown to enhance human–automation system performance. Method This mini-review describes flexible automation in which the level of automated support varies across tasks during system operation, rather than remaining fixed. Two types distinguish the locus of authority to change automation level: adaptable automation (the human operator assigns how automation is applied) has been found to aid human’s situation awareness and provide more perceived control versus adaptive automation (the system assigns automation level) that may impose less workload and attentional demands by automatically adjusting levels in response to changes in one or more states of the human, task, environment, and so on. Results In contrast to vast investments in adaptive automation approaches, limited research has been devoted to adaptable automation. Experiments directly comparing adaptable and adaptive automation are particularly scant. These few studies show that adaptable automation was not only preferred over adaptive automation, but it also resulted in improved task performance and, notably, less perceived workload. Conclusion Systematic research examining adaptable automation is overdue, including hybrid approaches with adaptive automation. Specific recommendations for further research are provided. Application Adaptable automation together with effective human-factored interface designs to establish working agreements are key to enabling human–automation teaming in future complex systems.
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