Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human–Automation Interaction

Sebok, Angelia; Wickens, Christopher D.

doi:10.1177/0018720816665201

Cited by 65 publications

(51 citation statements)

References 55 publications

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“…From the literature, it is evident that the task a person is performing can compete for their limited attention and comprehension resources and by doing so, impact the stages of information processing. In turn, cognitive resources devoted to the failure have an impact on the task: an increase in automation during failure condition reduces operator performance (the “lumberjack analogy”; Sebok and Wickens, 2017 ). Several studies seem to indicate that task performance is significantly influenced by robotic failures.…”

Section: A Unified Information Processing Model For User Centered Faimentioning

confidence: 99%

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development

2018

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While substantial effort has been invested in making robots more reliable, experience demonstrates that robots operating in unstructured environments are often challenged by frequent failures. Despite this, robots have not yet reached a level of design that allows effective management of faulty or unexpected behavior by untrained users. To understand why this may be the case, an in-depth literature review was done to explore when people perceive and resolve robot failures, how robots communicate failure, how failures influence people's perceptions and feelings toward robots, and how these effects can be mitigated. Fifty-two studies were identified relating to communicating failures and their causes, the influence of failures on human-robot interaction (HRI), and mitigating failures. Since little research has been done on these topics within the HRI community, insights from the fields of human computer interaction (HCI), human factors engineering, cognitive engineering and experimental psychology are presented and discussed. Based on the literature, we developed a model of information processing for robotic failures (Robot Failure Human Information Processing, RF-HIP), that guides the discussion of our findings. The model describes the way people perceive, process, and act on failures in human robot interaction. The model includes three main parts: (1) communicating failures, (2) perception and comprehension of failures, and (3) solving failures. Each part contains several stages, all influenced by contextual considerations and mitigation strategies. Several gaps in the literature have become evident as a result of this evaluation. More focus has been given to technical failures than interaction failures. Few studies focused on human errors, on communicating failures, or the cognitive, psychological, and social determinants that impact the design of mitigation strategies. By providing the stages of human information processing, RF-HIP can be used as a tool to promote the development of user-centered failure-handling strategies for HRIs.

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Section: A Unified Information Processing Model For User Centered Faimentioning

confidence: 99%

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development

2018

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“…Drawing on studies investigating the performance of pilots and control systems, with operators using systems capable of varying degrees of automation, Kaber and Endsley (1997) argue that "When an operator is removed from a control loop due to allocation of system functions to an automated/computer controller, the level of human-system interaction is limited and, consequently, operator awareness of system states may be reduced". In such situations, operators are more likely to make errors when interacting with, or when taking control from, the system (see Sebok and Wickens 2017, for a recent overview). Linked to this original reference in the aviation domain, the term "loop" likely originates from the "open-and closedloop" concepts described by Control Theory in Systems Engineering.…”

Section: Current Use Of the Out Of The Loop (Ootl) Concept: The Need mentioning

confidence: 99%

The “Out-of-the-Loop” concept in automated driving: proposed definition, measures and implications

Seppelt²,

et al. 2018

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Despite an abundant use of the term "Out of the loop" (OOTL) in the context of automated driving and human factors research, there is currently a lack of consensus on its precise definition, how it can be measured, and the practical implications of being in or out of the loop during automated driving. The main objective of this paper is to consider the above issues, with the goal of achieving a shared understanding of the OOTL concept between academics and practitioners. To this end, the paper reviews existing definitions of OOTL and outlines a set of concepts, which, based on the human factors and driver behaviour literature, could serve as the basis for a commonly-agreed definition. Following a series of working group meetings between representatives from academia, research institutions and industrial partners across Europe, North America, and Japan, we suggest a precise definition of being in, out, and on the loop in the driving context. These definitions are linked directly to whether or not the driver is in physical control of the vehicle, and also the degree of situation monitoring required and afforded by the driver. A consideration of how this definition can be operationalized and measured in empirical studies is then provided, and the paper concludes with a short overview of the implications of this definition for the development of automated driving functions.

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“…Although direct evidence on factors that influence the operation of this special task is limited, studies on other process control operations with similar working requirements can provide valuable information. The fault diagnosis and resolution process has been studied intensively in the nuclear power plant, air traffic control (Langer and Braithwaite, 2016;Trapsilawati et al, 2016;Borst et al, 2017), submarine (Roberts et al, 2017), and many other backgrounds (Vicente et al, 2004;Wickens et al, 2009;Sebok and Wickens, 2016). Operator performance of safety-critical and highly automated environments monitoring has also been studied (Funke et al, 2016;Cymek, 2018).…”

Section: Introductionmentioning

confidence: 99%

Human Performance Analysis of Processes for Retrieving Beidou Satellite Navigation System During Breakdown

Zhang

et al. 2020

Front. Psychol.

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Satellite navigation systems provide continuous, timely, and accurate signals of location, speed, and time to users all over the world. Although the running of these systems has become highly automated, the human operator is still vital for its continued operation, especially when certain equipment failures occur. In this paper, we examined 180 incidents of one particular type of equipment failure and the whole recovery process as recorded in the log files from a ground control center of the Beidou satellite navigation system. We extracted the information, including the technical description of the failure, the time when the fault occurred, the full recovery time, and the demographic information of the team members on the shift responsible for responding to the failure. We then transformed these information into the cognitive complexity of the task, time of day, shift handover period, and team skill composition. Multiple regression analysis showed that task complexity and shift handover were key predictors of recovery time. Time of day also influenced the recovery time, during midnight to 4 a.m., operators made longer responses. We also found that the fault handling processes could be improved if the team's most adept member is more skillful at that role than in other teams. We discussed the theoretical and practical implication of this study.

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Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human–Automation Interaction

Abstract: The three tools offer ways to predict the effects of different automation designs on operator performance.

Cited by 65 publications

References 55 publications

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development

The “Out-of-the-Loop” concept in automated driving: proposed definition, measures and implications

Human Performance Analysis of Processes for Retrieving Beidou Satellite Navigation System During Breakdown

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