Human Trust-Based Feedback Control: Dynamically Varying Automation Transparency to Optimize Human-Machine Interactions

被引:33
作者
Akash, Kumar [1 ]
McMahon, Griffon [2 ]
Reid, Tahira [3 ]
Jain, Neera [3 ]
机构
[1] Honda Res Inst Inc, San Jose, CA 95134 USA
[2] Univ Penn, Robot, Philadelphia, PA 19104 USA
[3] Purdue Univ, Sch Mech Engn, W Lafayette, IN 47907 USA
来源
IEEE CONTROL SYSTEMS MAGAZINE | 2020年 / 40卷 / 06期
关键词
Automation; Hidden Markov models; Markov processes; Robots; Time factors; Feedback control; Autonomous systems; Trust management; Human factors; SELF-CONFIDENCE; MODEL; ALLOCATION; WORKLOAD; AGE;
D O I
10.1109/MCS.2020.3019151
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Aomation has become prevalent in the everyday lives of humans. However, despite significant technological advancements, human supervision and intervention are still necessary in almost all sectors of automation, ranging from manufacturing and transportation to disaster management and health care [1]. Therefore, it is expected that the future will be built around human?agent collectives [2] that will require efficient and successful interaction and coordination between humans and machines. It is well established that, to achieve this coordination, human trust in automation plays a central role [3]-[5]. For example, the benefits of automation are lost when humans override it due to a fundamental lack of trust [3], [5], and accidents may occur due to human mistrust in such systems [6]. Therefore, trust should be appropriately calibrated to avoid the disuse or misuse of automation [4].
引用
收藏
页码:98 / 116
页数:19
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