ATC Visual Search Patterns

PROJECT TITLE: Characterization and Application of Air Traffic Controllers Visual Search Patterns and Control Strategies for Efficient and Effective Training

Project completed Apr. 2018

Collaborators:

PI: Dr. Ziho Kang, Assistant Professor, Industrial and Systems Engineering, University of Oklahoma
Co-PI: Dr. John Dyer, Research Assistant Professor, Electrical and Computer Engineering, University of Oklahoma
Co-PI: Prof. Stephen West, Director of the University of Oklahoma Department of Aviation’s Controller Training Initiative (AT-CTI), University of Oklahoma
Student: Saptarshi Mandal, Ricardo Palma Fraga, Uchenna Kelvin Egwu, Sarah McClung
FAA Sponsor: Jason Demagalski, Technical Training (AJI-2)
FAA Technical Monitor: Rachel Seely

Abstract:

This proposed project aims to characterize and classify the visual scanning patterns and control strategies of expert air traffic control specialists (ATCSs) in order to support the efficient and effective training of air traffic control candidates. We will collect eye movement data and aircraft control commands from multiple expert ATCSs, and develop designs to better provide the characterized and classified visual search and control strategies.

Expected Project Outcomes:

Perform requirement analysis and development of scenarios.
Characterization and classification of expert ATCO’s visual search patterns.
Characterization and classification of expert ATCO’s aircraft control strategies.
Development of designs to better provide the characterization and classification results.

Value of Research:

The focus of this research was to develop a better understanding of the underlying motives behind the visual scanning and searching strategies, methods of conflict control and overall decision-making made by expert Air Traffic Controllers in a high fidelity simulation through the analysis of scanpaths from eye-tracking data and protocol.