We outline a model for types and levels of automation that provides a framework and an objective basis for deciding which system functions should be automated and to what extent. Appropriate selection is important because automation does not merely supplant but changes human activity and can impose new coordination demands on the human operator. We propose that automation can be applied to four broad classes of functions: 1) information acquisition; 2) information analysis; 3) decision and action selection; and 4) action implementation. Within each of these types, automation can be applied across a continuum of levels from low to high, i.e., from fully manual to fully automatic. A particular system can involve automation of all four types at different levels. The human performance consequences of particular types and levels of automation constitute primary evaluative criteria for automation design using our model. Secondary evaluative criteria include automation reliability and the costs of decision/action consequences, among others. Examples of recommended types and levels of automation are provided to illustrate the application of the model to automation design.

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A model for types and levels of human interaction with automation

Automation is often problematic because people fail to rely upon it appropriately. Because people respond to technology socially, trust influences reliance on automation. In particular, trust guides reliance when complexity and unanticipated situations make a complete understanding of the automation impractical. This review considers trust from the organizational, sociological, interpersonal, psychological, and neurological perspectives. It considers how the context, automation characteristics, and cognitive processes affect the appropriateness of trust. The context in which the automation is used influences automation performance and provides a goal-oriented perspective to assess automation characteristics along a dimension of attributional abstraction. These characteristics can influence trust through analytic, analogical, and affective processes. The challenges of extrapolating the concept of trust in people to trust in automation are discussed. A conceptual model integrates research regarding trust in automation and describes the dynamics of trust, the role of context, and the influence of display characteristics. Actual or potential applications of this research include improved designs of systems that require people to manage imperfect automation.

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Trust in Automation: Designing for Appropriate Reliance

This paper addresses theoretical, empirical, and analytical studies pertaining to human use, misuse, disuse, and abuse of automation technology. Use refers to the voluntary activation or disengagement of automation by human operators. Trust, mental workload, and risk can influence automation use, but interactions between factors and large individual differences make prediction of automation use difficult. Misuse refers to over reliance on automation, which can result in failures of monitoring or decision biases. Factors affecting the monitoring of automation include workload, automation reliability and consistency, and the saliency of automation state indicators. Disuse, or the neglect or underutilization of automation, is commonly caused by alarms that activate falsely. This often occurs because the base rate of the condition to be detected is not considered in setting the trade-off between false alarms and omissions. Automation abuse, or the automation of functions by designers and implementation by man...

Humans and Automation: Use, Misuse, Disuse, Abuse

Humans and automation: Use, misuse, disuse, abuse

EIGHT members of the Yale Institute of Human Relations have co-operated to produce this book The result is not a mere juxtaposition of uncoordinated viewpoints but a unity of aim and consistency in presentation which make the multiple authorship almost undetectable Whatever judgment one may make about the value of the hypothesis elaborated in the book, there can be little doubt that the intimate collaboration of a team of specialists, each with a distinctive training, is a profitable way of examining a problem which has no clear-cut frontiers and which does not fall neatly into one of the conventional compartments of social study Frustration and Aggression By John Dollard Neal E Miller Leonard W Doob O H Mowrer Robert R Sears, in collaboration with Clellan S Ford, Carl Iver Hovland and Richard T Sollenberger (International Library of Sociology and Social Reconstruction) Pp ix + 150 (London: Kegan Paul and Co, Ltd, 1944) 10s 6d net

Frustration and Aggression

The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

Effects of adaptive task allocation on monitoring of automated systems

Measure twice, cut once. Although applicable to all areas of human factors research, this old adage is especially relevant to simulation and training. As a tool, simulation is an aid to the imagination; however, if incorrectly or inadequately used, it can lead to inaccurate outcomes that not only limit the possibilities, but potentially cause harm. A comprehensive overview of the topic from a human factor perspective, Human Factors in Simulation and Training not only reflects the state-of-the art, but also integrates the literature on simulation into one cohesive resource. Experts Share their Insight The editors have solicited chapters on a wide variety of topics, beginning with theory and application in areas ranging from traditional training to augmented and virtual reality. This coverage includes surface ships, submarines, naval aviation, commercial aviation, space, and medicine. The theory based section focuses on human factors aspects of simulation and training ranging from the history of simulators and training devices, to future trends in simulation from both a civilian and military perspective. The chapters expand on concepts regarding simulator usage particularly with respect to the validity and functionality of simulators as training devices. They contain in-depth discussions of specific issues, including fidelity, interfaces and control devices, transfer of training, simulator sickness, effects of motion in simulated systems, and virtual reality. As more, and more sophisticated, simulation tools and training technologies become available, a complete understanding of how to use them appropriately will be even more crucial. Elucidating theory and application, the book addresses numerous issues and concepts pertaining to human factors in simulation and training, making this volume an important addition to the bookshelf of any human factors professional.

Human Factors in Simulation and Training

Contents: Foreword. Acknowledgments. Part I:Conference Keynote Address. T.B. Sheridan, Automation and Human Performance: Looking Ahead into the 21st Century. Part II:Human-Automation Interaction. N. Sarter, The Trend Towards Errors of Omission: Reasons for and Countermeasures Against It. A. Andre, A. Degani, Do You Know what Mode You're In? An Analysis of Mode Error in Everyday Things. K.H. Funk, II, E.A. Lyall, M.C. Niemczyk, Flightdeck Automation Problems: Perceptions and Reality. M.T. Schaffer, R. Baldwin, Automation and Human Performance: Implications for Cockpit and Air Traffic Control. Part III:Monitoring and Situation Awareness. R. Parasuraman, Human Use and Abuse of Automation. M.A. Eidelkind, S.A. Papantonopoulos, Operator Trust and Task Delegation: Strategies in Semi-Autonomous Agent Systems. L.C. Boer, Losing Task Situation Awareness. Part IV:Adaptive Automation. P.A. Hancock, Men Without Machines. L.J. Prinzel, III, M. Scerbo, F.G. Freeman, P.J. Mikulka, Behavioral and Physiological Correlates of a Bio-Cybernetic, Closed-Loop System for Adaptive Automation. Y.Y. Golikov, A.N. Kostin, The Human Factors Approaches to Automation and Allocation of Functions Between Man and Machine. B. Hillburn, P.G.A.M. Jorna, E.A. Byrne, R. Parasuraman, The Effect of Adaptive Air Traffic Control (ATC) Decision Aiding on Controller Mental Workload. C. Bubb-Lewis, M. Scerbo, Getting to Know You: Human-Computer Communication in Adaptive Automation. A.N. Kostin, Y.Y. Golikov, The Experimental Investigations of Mutual Reservation of Man and Machine. J.A. Duley, R. Molloy, R. Parasuraman, Display Configuration in Adaptive Automation: Integration and Dynamic Presentation. Part V:Vigilance, Workload, and Training. D.A. Vincenzi, B. Muldoon, M. Mouloua, Effects of Aging and Workload on Monitoring of Automation Failures. P.J. Moore, T. Farquharson, R.A. Telfer, Automation and Human Performance in Airline Pilot Training. B.S. Caldwell, A.D. Bayeh, A. Schein, T.A. Hodge-Diazt, Developing Supervisory Control Interface Tools for Task and Workload Management and Operator Response Dynamics. G.M. Pisanich, J. Kaneshige, S.T. Heers, A Laboratory Glass Cockpit Flight Simulator for Automation and Communication Research. G.M. Pisanich, K.M. Corker, Improving the Accuracy of Human-Machine Models: Interfacing Directly to Flight Automation. R.J. Molloy, E.A. Byrne, A.J. Masalonis, R. Parasuraman, Laboratory Flight Simulator for Automation and Display Design Research. Part VI:Cockpit Automation. J.M. Koonce, Automation Issues in General Aviation. K.L. Mosier, L.J. Skitka, M. Burdick, S. Heers, Patterns in the Use of Cockpit Automation. P.G.A.M. Jorna, Cockpit Automation: The Challenge for Enhanced Human Performance. J.A. Wise, V.D. Hopkin, Integrating Human Factors into the Certification of Systems. C.A. Miller, H.B. Funk, Knowledge Requirements for Information Management: A Rotorcraft Pilot's Associate Example. R.R. Tyler, R.D. Gilson, M. Mouloua, Pilot's Interaction with Alerting Systems in the Cockpit: A Large Scale Study. A.S.E. Barlow, D.P. McDonald, R.D. Gilson, M. Mouloua, Temporal Effect on Alarm Response. Part VII:Medical Systems. M.S. Bogner, Human Factors Research in Medical Systems. A.J. Moffa, A.F. Stokes, Trust in a Medical System: Can We Generalize Between Domains? J.H. Obradovich, P.J. Smith, S. Guerlain, S. Rudmann, P. Strohm, J. Smith, J. Svirbely, L. Sachs, The Role of Proactive and Embedded Training in the Design of an Expert System for Teaching Transfusion Medicine. M.B. Weinger, Human-User Medical Device Interactions in the Anesthesia Work Environment. Part VIII:Automation in Air-Traffic Control. V.D. Hopkin, Automation in Air-Traffic Control: Recent Advances and Major Issues. P.G.A.M. Jorna, Human-Machine Interfaces for ATM Automation: A European Strategy Towards Technology and Human Factors Validation. G. Pianalto, J. Vian, Synthetic Vision System for Low Visibility Airport Surface Movement. Part IX:Cultural Interactions in Complex Systems. M. Kaplan, An Analytic Approach to Cultural Interactions in Complex Systems. S.E. Infield, K.M. Corker, The Culture of Control: Free Flight, Automation and Culture. N. Meshkati, Cultural Context of the Safety Culture: A Conceptual Model and Experimental Study. B.S. Caldwell, Sociotechnical Factors Affecting Communication and Isolation in Complex Environments. K.M. Stanney, J. Maxey, G. Salvendy, Social Contexts in Systems Design. Part X:Concluding Remarks. C.E. Billings, Some Questions About Advanced Automation. List of Contributors. Subject Index.

Human–automation interaction: Research and practice.

Technology advances and increased application of UAVs will demand greater attention to human factors concerns in design, deployment, and training.

Mustapha Mouloua

Papers

Effects of adaptive task allocation on monitoring of automated systems

Effects of adaptive task allocation on monitoring of automated systems

Human Factors in Simulation and Training

Human–automation interaction: Research and practice.

Human-Centered Design of Unmanned Aerial Vehicles: