IEEE Control Systems · 2020 · 70 citations · 73 references
ComputingAutonomous SystemsComputer ScienceAutomationHuman-computer InteractionReal-time SystemsAutomated Feedback SystemsHuman ReliabilityHuman-cyber-physical InteractionHuman-machine InteractionHuman-machine InterfacesTrust In Human-robot InteractionAdaptive AutomationAutomation TransparencyFeedback PoliciesHuman-automation Decision MakingHuman-automation InteractionTrust Calibration In AutomationTrust DynamicsWorkload
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].
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R: A Language and Environment for Statistical Computing
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Fitting Linear Mixed-Effects Models Using <b>lme4</b>
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