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

2021 ◽  
pp. 001872082110374
Author(s):  
Gloria Calhoun
Keyword(s):  
Situation Awareness ◽  
Perceived Control ◽  
Systematic Research ◽  
Automation System ◽  
Adaptive Automation ◽  
Hybrid Approaches ◽  
Control Versus ◽  
Automation Level ◽  
Automated Support ◽  
Flexible Application

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.

A brain-based adaptive automation system and situation awareness: The role of complacency potential

2003 ◽  
Author(s):  
Nathan R. Bailey ◽  
Mark W. Scerbo ◽  
Frederick G. Freeman ◽  
Peter J. Mikulka ◽  
Lorissa A. Scott
Keyword(s):  
Situation Awareness ◽  
Automation System ◽  
Adaptive Automation

A Brain-Based Adaptive Automation System and Situation Awareness: The Role of Complacency Potential

2003 ◽  
Vol 47 (9) ◽  
pp. 1048-1052 ◽  
Author(s):  
Nathan R. Bailey ◽  
Mark W. Scerbo ◽  
Frederick G. Freeman ◽  
Peter J. Mikulka ◽  
Lorissa A. Scott
Keyword(s):  
Situation Awareness ◽  
Automation System ◽  
Adaptive Automation

scholarly journals Initiators and Triggering Conditions for Adaptive Automation in Advanced Small Modular Reactors

2014 ◽  
Author(s):  
Katya L. Le Blanc ◽  
Johanna H. Oxstrand
Keyword(s):  
Situation Awareness ◽  
System Performance ◽  
Human Performance ◽  
Hybrid Methods ◽  
Empirical Literature ◽  
Physiological Measurement ◽  
Adaptive Automation ◽  
Small Modular Reactors ◽  
Levels Of Automation ◽  
Triggering Mechanisms

It is anticipated that Advanced Small Modular Reactors (AdvSMRs) will employ high degrees of automation. High levels of automation can enhance system performance, but often at the cost of reduced human performance. Automation can lead to human out-of the loop issues, unbalanced workload, complacency, and other problems if it is not designed properly. Researchers have proposed adaptive automation (defined as dynamic or flexible allocation of functions) as a way to get the benefits of higher levels of automation without the human performance costs. Adaptive automation has the potential to balance operator workload and enhance operator situation awareness by allocating functions to the operators in a way that is sensitive to overall workload and capabilities at the time of operation. However, there still a number of questions regarding how to effectively design adaptive automation to achieve that potential. One of those questions is related to how to initiate (or trigger) a shift in automation in order to provide maximal sensitivity to operator needs without introducing undesirable consequences (such as unpredictable mode changes). Several triggering mechanisms for shifts in adaptive automation have been proposed including: operator initiated, critical events, performance-based, physiological measurement, model-based, and hybrid methods. As part of a larger project to develop design guidance for human-automation collaboration in AdvSMRs, researchers at Idaho National Laboratory have investigated the effectiveness and applicability of each of these triggering mechanisms in the context of AdvSMR. Researchers reviewed the empirical literature on adaptive automation and assessed each triggering mechanism based on the human-system performance consequences of employing that mechanism. Researchers also assessed the practicality and feasibility of using the mechanism in the context of an AdvSMR control room. Results indicate that there are tradeoffs associated with each mechanism, but that some are more applicable to the AdvSMR domain than others. The two mechanisms that consistently improve performance in laboratory studies are operator initiated adaptive automation based on hierarchical task delegation and the Electroencephalogram (EEG)–based measure of engagement. Current EEG methods are intrusive and require intensive analysis; therefore it is not recommended for an AdvSMR control rooms at this time. Researchers also discuss limitations in the existing empirical literature and make recommendations for further research.

Designing an Adaptive Automation System for Human Supervision of Unmanned Vehicles: A Bridge from Theory to Practice

2008 ◽  
Vol 52 (4) ◽  
pp. 221-225 ◽  
Author(s):  
Ewart J. de Visser ◽  
Melanie LeGoullon ◽  
Amos Freedy ◽  
Elan Freedy ◽  
Gershon Weltman ◽  
...  
Keyword(s):  
Unmanned Vehicles ◽  
Automation System ◽  
Adaptive Automation ◽  
Theory To Practice

An evaluation of an adaptive automation system using a cognitive vigilance task

2004 ◽  
Vol 67 (3) ◽  
pp. 283-297 ◽  
Author(s):  
Frederick G Freeman ◽  
Peter J Mikulka ◽  
Mark W Scerbo ◽  
Lorissa Scott
Keyword(s):  
Vigilance Task ◽  
Automation System ◽  
Adaptive Automation

Research of Human Factors under Automatic ATC System

2014 ◽  
Vol 513-517 ◽  
pp. 2799-2803
Author(s):  
Wei Jun Pan ◽  
Wen Bo Wang ◽  
Dan Wu ◽  
Chen Yu Huang
Keyword(s):  
Correlation Analysis ◽  
Situation Awareness ◽  
Work Experience ◽  
Significant Positive Correlation ◽  
Automation System ◽  
Mutual Trust ◽  
Significance Analysis ◽  
New Generation ◽  
The Impact ◽  
The Relationship

This paper is to assess the impact of ATC automation on controller workload, situation awareness, teamwork and mutual trust, and solve the relationship between human and ATC automation system collaboration. Based on experiment statistics, the method of mathematical statistics has been used to carry on overall analysis, significance analysis and correlation analysis. As a result, in the new generation ATC automation system, the overall level of controllers workload, situation awareness, teamwork and mutual trust is relatively higher than that under traditional condition, along with the increase of the controller work experience, the teamwork consciousness and situation awareness are stronger, the workload is lower, the ATC automation system of mutual trust is higher. Teamwork, workload and mutual trust have a significant positive correlation.

Automation-Level Transference Effects in Simulated Multiple Unmanned Aerial Vehicle Control

2011 ◽  
Vol 5 (1) ◽  
pp. 55-82 ◽  
Author(s):  
Gloria L. Calhoun ◽  
Heath A. Ruff ◽  
Mark H. Draper ◽  
Evan J. Wright
Keyword(s):  
Situation Awareness ◽  
Supervisory Control ◽  
Human Interaction ◽  
The Other ◽  
Primary Control ◽  
Secondary Tasks ◽  
Research Issues ◽  
Level Of Automation ◽  
Automation Level ◽  
The Impact

Supervisory control of multiple unmanned aerial vehicles (UAVs) raises many questions concerning the balance of system autonomy with human interaction for effective operator situation awareness and system performance. The reported experiment used a UAV simulation environment to evaluate two applications of autonomy levels across two primary control tasks: allocation (assignment of sensor tasks to vehicles) and router (determining vehicles’ flight plans). In one application, the autonomy level was the same across these two tasks. In the other, the autonomy levels differed, one of the two tasks being more automated than the other. Trials also involved completion of other mission-related secondary tasks as participants supervised three UAVs. The results showed that performance on both the primary tasks and many secondary tasks was better when the level of automation was the same across the two sequential primary tasks. These findings suggest that having the level of automation similar across closely coupled tasks reduces mode awareness problems, which can negate the intended benefits of a fine-grained application of automation. Several research issues are identified to further explore the impact of automation-level transference in supervisory control applications involving the application of automation across numerous tasks.

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