Situation awareness implications of adaptive automation for information processing in an air traffic control-related task

Abstract The objective of this research was to assess the effectiveness of adaptive automation (AA) for supporting information processing (IP) in a complex, dynamic control task by defining a measure of situation awareness (SA) sensitive to differences in the forms of automation. The task was an air traffic control (ATC)-related simulation and was developed to present four different modes of automation of IP functions, including information acquisition, information analysis, decision making and action implementation automation, as well as a completely manual control mode. A total of 16 participants were recruited for a pilot study and primary experiment. The pilot assessed the sensitivity and reliability of the Situation Awareness Global Assessment Technique (SAGAT) for describing AA support of the IP functions. Half of the participants were used in the primary experiment, which refined the SA measure and described the implications of AA for IP on SA using the ATC-like simulation. Participants were exposed to all forms of automation and manual control. AA conditions matched operator workload states to dynamic control allocations in the primary task. The pilot did not reveal significant differences in SA among the various AA conditions. In the primary experiment, participant recall of aircraft was cued and relevance weights were assigned to aircraft at the time of simulation freezes. The modified measure of SA revealed operator perception and Total SA to improve when automation was applied to the information acquisition function. In both experiments, performance in the ATC-related task simulation was significantly superior when automation was applied to information acquisition and action implementation (sensory and motor processing), as compared to automation of cognitive functions, specifically information analysis. The primary experiment revealed information analysis and decision-making automation to cause higher workload, attributable to visual demands of displays. Industry relevance The results of this research may serve as a general guide for the design of adaptive automation functionality in the aviation industry, particularly for information processing support in air traffic control tasks.

[1]  Mica R. Endsley,et al.  Toward a Theory of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[2]  Marcel Leroux.  THE ROLE OF EXPERT SYSTEMS IN FUTURE COOPERATIVE TOOLS FOR AIR TRAFFIC CONTROLLERS. , 1993 .

[3]  Klaus Eyferth,et al.  Securing future ATM-concepts' safety by measuring situation awareness in ATC , 2003 .

[4]  Mark W. Scerbo,et al.  Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation , 2006, Hum. Factors.

[5]  David B. Kaber,et al.  Adaptive Automation of Human-Machine System Information-Processing Functions , 2005, Hum. Factors.

[6]  Gavriel Salvendy,et al.  A real-time interactive computer model of a flexible manufacturing system , 1987 .

[7]  V David Hopkin.  THE IMPACT OF AUTOMATION ON AIR TRAFFIC CONTROL SPECIALISTS. , 1998 .

[8]  J. G. Hollands,et al.  Engineering Psychology and Human Performance , 1984 .

[9]  David B. Kaber,et al.  Design of Automation for Telerobots and the Effect on Performance, Operator Situation Awareness, and Subjective Workload , 2000 .

[10]  L. Kaufman,et al.  Handbook of Perception and Human Performance. Volume 2. Cognitive Processes and Performance , 1994 .

[11]  P A Hancock,et al.  Pilot performance and preference for short cycles of automation in adaptive function allocation. , 1995, Applied ergonomics.

[12]  N. Moray,et al.  Adaptive automation, trust, and self-confidence in fault management of time-critical tasks. , 2000, Journal of experimental psychology. Applied.

[13]  Raja Parasuraman,et al.  Performance Consequences of Automation-Induced 'Complacency' , 1993 .

[14]  David B. Kaber,et al.  The effects of level of automation and adaptive automation on human performance, situation awareness and workload in a dynamic control task , 2004 .

[15]  Mica R. Endsley,et al.  The Out-of-the-Loop Performance Problem and Level of Control in Automation , 1995, Hum. Factors.

[16]  David B. Kaber,et al.  Adaptive Automation of a Dynamic Control Task Based on Secondary Task Workload Measurement , 1999 .

[17]  David B. Kaber,et al.  Comparison of Performance Effects of Adaptive Automation Applied to Various Stages of Human-Machine System Information Processing , 2002 .

[18]  Christopher D. Wickens,et al.  IMPERFECT AND UNRELIABLE AUTOMATION AND ITS IMPLICATIONS FOR ATTENTION ALLOCATION , INFORMATION ACCESS AND SITUATION AWARENESS , 2000 .

[19]  Jefferson M. Koonce,et al.  Human–automation interaction: Research and practice. , 1997 .

[20]  Mica R. Endsley,et al.  Automation and situation awareness. , 1996 .

[21]  J G Hollands,et al.  ENGINEERING PSYCHOLOGY AND HUMAN PERFORMANCE - THIRD EDITION , 2000 .

[22]  David B. Kaber,et al.  On the Design of Adaptive Automation for Complex Systems , 2001 .

[23]  Mica R. Endsley,et al.  Measurement of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[24]  Ashley Nunes,et al.  The Impact of Automation Use on the Mental Model: Findings from the Air Traffic Control Domain , 2003 .

[25]  Mica R. Endsley,et al.  Direct Measurement of Situation Awareness: Validity and Use of SAGAT , 2000 .

[26]  R Parasuraman,et al.  Designing automation for human use: empirical studies and quantitative models , 2000, Ergonomics.

[27]  Kim J. Vicente,et al.  Supporting knowledge-based behavior through ecological interface design , 1991 .

[28]  Neville Moray,et al.  Monitoring behavior and supervisory control , 1986 .

[29]  Christopher D. Wickens,et al.  A model for types and levels of human interaction with automation , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[30]  Mustapha Mouloua,et al.  Automation and Human Performance : Theory and Applications , 1996 .

[31]  Mica R. Endsley,et al.  Situation awareness information requirements for en route air traffic control. , 1994 .

[32]  Thomas B. Sheridan,et al.  Monitoring Behavior and Supervisory Control , 1976 .

[33]  Raja Parasuraman,et al.  Operator versus computer control of adaptive automation , 1993 .

[34]  V. David Hopkin.  Human Factors In Air Traffic Control , 1995 .

[35]  Makoto Itoh,et al.  A Microworld Approach to Identifying Issues of Human-Automation Systems Design for Supporting Operator's Situation Awareness , 2004, Int. J. Hum. Comput. Interact..

[36]  William M. Jones,et al.  Situation Awareness Information Dominance & Information Warfare. , 1997 .

[37]  Mustapha Mouloua,et al.  Adaptive function allocation reduces performance costs of static automation , 1993 .

[38]  Lawrence J. Prinzel,et al.  Research on Hazardous States of Awareness and Physiological Factors in Aerospace Operations , 2002 .

[39]  David B. Kaber,et al.  Authority in Adaptive Automation Applied to Various Stages of Human-Machine System Information Processing , 2003 .

[40]  Gary Klein,et al.  Sources of Power: How People Make Decisions , 2017 .

[41]  Christopher D. Wickens,et al.  The Future of Air Traffic Control: Human Operators and Automation , 1998 .