Attention Distribution While Detecting Conflicts between Converging Objects: An Eye-Tracking Study

In many domains, including air traffic control, observers have to detect conflicts between moving objects. However, it is unclear what the effect of conflict angle is on observers’ conflict detection performance. In addition, it has been speculated that observers use specific viewing techniques while performing a conflict detection task, but evidence for this is lacking. In this study, participants (N = 35) observed two converging objects while their eyes were recorded. They were tasked to continuously indicate whether a conflict between the two objects was present. Independent variables were conflict angle (30, 100, 150 deg), update rate (discrete, continuous), and conflict occurrence. Results showed that 30 deg conflict angles yielded the best performance, and 100 deg conflict angles the worst. For 30 deg conflict angles, participants applied smooth pursuit while attending to the objects. In comparison, for 100 and especially 150 deg conflict angles, participants showed a high fixation rate and glances towards the conflict point. Finally, the continuous update rate was found to yield shorter fixation durations and better performance than the discrete update rate. In conclusion, shallow conflict angles yield the best performance, an effect that can be explained using basic perceptual heuristics, such as the ‘closer is first’ strategy. Displays should provide continuous rather than discrete update rates.

[1]  Markus Lienkamp,et al.  Hail-a-Drone: Enabling teleoperated taxi fleets , 2016, 2016 IEEE Intelligent Vehicles Symposium (IV).

[2]  J. Y. C. Chen,et al.  Review of Low Frame Rate Effects on Human Performance , 2007, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[3]  A Bisseret,et al.  Application of signal detection theory to decision making in supervisory control The effect of the operator's experience , 1981 .

[4]  Carl Kirschner,et al.  An Information-Processing Interpretation of Air Traffic Control Stress , 1980 .

[5]  J. Tresilian,et al.  Perceptual and cognitive processes in time-to-contact estimation: Analysis of prediction-motion and relative judgment tasks , 1995, Perception & psychophysics.

[6]  D. Gilden On the origins of dynamical awareness. , 1991, Psychological review.

[7]  Peter Brauchli,et al.  Effects of work demands on immunoglobulin A and cortisol in air traffic controllers , 1996, Biological Psychology.

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

[9]  Hervé Abdi,et al.  Signal Detection Theory (SDT) , 2007 .

[10]  J. Pellegrino,et al.  Perceptual and cognitive factors governing performance in comparative arrival-time judgments. , 1993, Journal of experimental psychology. Human perception and performance.

[11]  Shayne Loft,et al.  A theory and model of conflict detection in air traffic control: incorporating environmental constraints. , 2009, Journal of experimental psychology. Applied.

[12]  Kenneth Holmqvist,et al.  Eye tracking: a comprehensive guide to methods and measures , 2011 .

[13]  Raja Sengupta,et al.  Drones in smart cities: Overcoming barriers through air traffic control research , 2015, 2015 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS).

[14]  Peter A. Hancock,et al.  Time-to-contact , 1998 .

[15]  Eric Ruthruff,et al.  Visual Search in Complex Displays: Factors Affecting Conflict Detection by Air Traffic Controllers , 2000, Hum. Factors.

[16]  Miriam Spering,et al.  Directional asymmetries in human smooth pursuit eye movements. , 2013, Investigative ophthalmology & visual science.

[17]  José J. Cañas,et al.  Air traffic control: Ocular metrics reflect cognitive complexity , 2016 .

[18]  Brian Hilburn,et al.  COGNITIVE COMPLEXITY IN AIR TRAFFIC CONTROL: A LITERATURE REVIEW , 2004 .

[19]  Pieter Padmos,et al.  Image parameters for driving with indirect viewing systems , 2003, Ergonomics.

[20]  Paul A. Kirschner,et al.  Identification of effective visual problem solving strategies in a complex visual domain , 2014 .

[21]  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 .

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

[23]  Wen-Chin Li,et al.  How much is too much on monitoring tasks? Visual scan patterns of single air traffic controller performing multiple remote tower operations , 2018, International Journal of Industrial Ergonomics.

[24]  Eric Raufaste,et al.  The Intervention Trigger Model: Computational Modelling of Air Traffic Control , 2009 .

[25]  Jean-Baptiste Gotteland,et al.  Impact of ATCO Training and Expertise on Dynamic Spatial Abilities , 2019 .

[26]  Kent A. Kimball,et al.  Estimation of Intersection of Two Converging Targets as a Function of Speed and Angle of Target Movement , 1970 .

[27]  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.

[28]  Edgar Erdfelder,et al.  G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences , 2007, Behavior research methods.

[29]  Jun Ota,et al.  Human-supervised multiple mobile robot system , 2002, IEEE Trans. Robotics Autom..

[30]  Andrew Neal,et al.  An Evidence Accumulation Model for Conflict Detection Performance in a Simulated Air Traffic Control Task , 2009, Hum. Factors.

[31]  Raja Parasuraman,et al.  Effects of Automated Conflict Cuing and Traffic Density on Air Traffic Controller Performance and Visual Attention in a Datalink Environment , 2006 .

[32]  Alison McGann,et al.  Self-Separation from the Air and Ground Perspective , 1998 .

[33]  E. Raufaste,et al.  Extrapolation of the Intersection of Two Trajectories on a 2D Display: Evidence of Biases , 2007 .

[34]  Esa M. Rantanen,et al.  Hierarchical Conflict Detection in Air Traffic Control , 2005 .

[35]  Esa M. Rantanen,et al.  CONFLICT DETECTION IN AIR TRAFFIC CONTROL: A TASK ANALYSIS, A LITERATURE REVIEW, AND A NEED FOR FURTHER RESEARCH , 2003 .

[36]  M A Just,et al.  A theory of reading: from eye fixations to comprehension. , 1980, Psychological review.

[37]  Avi Parush,et al.  Using Eye Movements to Uncover Conflict Detection Strategies , 2009 .

[38]  J. Gagné Literature Review , 2018, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[39]  K. A. Kimball,et al.  Differential Velocity and Time Prediction of Motion , 1973, Perceptual and motor skills.

[40]  Christopher D. Wickens,et al.  Visual Attention Control, Scanning, and Information Sampling , 2007, Applied Attention Theory.