Augmented Visual Feedback: Cure or Distraction?

Objective The aim of the study was to investigate the effect of augmented feedback on participants’ workload, performance, and distribution of visual attention. Background An important question in human–machine interface design is whether the operator should be provided with direct solutions. We focused on the solution space diagram (SSD), a type of augmented feedback that shows directly whether two aircraft are on conflicting trajectories. Method One group of novices (n = 13) completed conflict detection tasks with SSD, whereas a second group (n = 11) performed the same tasks without SSD. Eye-tracking was used to measure visual attention distribution. Results The mean self-reported task difficulty was substantially lower for the SSD group compared to the No-SSD group. The SSD group had a better conflict detection rate than the No-SSD group, whereas false-positive rates were equivalent. High false-positive rates for some scenarios were attributed to participants who misunderstood the SSD. Compared to the No-SSD group, the SSD group spent a large proportion of their time looking at the SSD aircraft while looking less at other areas of interest. Conclusion Augmented feedback makes the task subjectively easier but has side effects related to visual tunneling and misunderstanding. Application Caution should be exercised when human operators are expected to reproduce task solutions that are provided by augmented visual feedback.

[1]  Raja Parasuraman,et al.  Humans and Automation: Use, Misuse, Disuse, Abuse , 1997, Hum. Factors.

[2]  Christopher D. Wickens,et al.  Head Up versus Head Down: The Costs of Imprecision, Unreliability, and Visual Clutter on Cue Effectiveness for Display Signaling , 2003, Hum. Factors.

[3]  Christopher D. Wickens,et al.  Display Dimensionality, Conflict Geometry, and Time Pressure Effects on Conflict Detection and Resolution Performance Using Cockpit Displays of Traffic Information , 2006 .

[4]  Gabriele Wulf,et al.  Continuous Concurrent Feedback Degrades Skill Learning: Implications for Training and Simulation , 1997, Hum. Factors.

[5]  Clark Borst,et al.  Will Controllers Accept a Machine That Thinks like They Think? The Role of Strategic Conformance in Decision Aiding Automation , 2014 .

[6]  Charles H. Shea,et al.  Understanding the role of augmented feedback : The good, the bad and the ugly , 2004 .

[7]  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 .

[8]  Alex M. Andrew,et al.  Humans and Automation: System Design and Research Issues , 2003 .

[9]  René van Paassen,et al.  Air traffic controller decision-making support using the solution space diagram , 2010, IFAC HMS.

[10]  D. Whitfield,et al.  The Air-Traffic Controller , 1978 .

[11]  Yke Bauke Eisma,et al.  Visual Sampling Processes Revisited: Replicating and Extending Senders (1983) Using Modern Eye-Tracking Equipment , 2018, IEEE Transactions on Human-Machine Systems.

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

[13]  Dimitra Dodou,et al.  When will most cars be able to drive fully automatically? Projections of 18,970 survey respondents , 2019, Transportation Research Part F: Traffic Psychology and Behaviour.

[14]  Max Mulder,et al.  Exploring Short-Term Training Effects of Ecological Interfaces: A Case Study in Air Traffic Control , 2019, IEEE Transactions on Human-Machine Systems.

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

[16]  Paul M. Fitts,et al.  Eye movements of aircraft pilots during instrument-landing approaches. , 1950 .

[17]  Thomas B. Sheridan,et al.  Humans and Automation: System Design and Research Issues , 2002 .

[18]  Michael E. Maddox CRITIQUE AND RESPONSE: Critique of “A Longitudinal Study of the Effects of Ecological Interface Design on Skill Acquisition” by Christoffersen, Hunter, and Vicente , 1996, Hum. Factors.

[19]  Y. B. Eisma,et al.  Attention Distribution While Detecting Conflicts between Converging Objects: An Eye-Tracking Study , 2020, Vision.

[20]  David Crundall,et al.  Driving simulator validation with hazard perception , 2011 .

[21]  Thomas B. Sheridan Human centered automation: oxymoron or common sense? , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[22]  Ian J Reagan,et al.  Exploring relationships between observed activation rates and functional attributes of lane departure prevention , 2019, Traffic injury prevention.

[23]  C. Winstein,et al.  Effects of physical guidance and knowledge of results on motor learning: support for the guidance hypothesis. , 1994, Research quarterly for exercise and sport.

[24]  Max Mulder,et al.  Ecological Interface Design: Sensor Failure Diagnosis in Air Traffic Control , 2016 .

[25]  G. R. J. Hockey,et al.  Applied Attention Theory , 2009 .