The Cognition of Multiaircraft Control (MAC): Cognitive Ability Predictors, Working Memory, Interference, and Attention Control in Radio Communication

Abstract

As the number of U.S. Air Force missions requiring UAVs has rapidly increased without commensurate increases in manpower, systems which permit a single operator to supervise and control multiple, highly-automated aircraft are being considered. The operator of such a system may be required to monitor and respond to voice communications for multiple UAVs, each of which can have aircraft specific call signs. The need to monitor this array of call signs may impose excessive requirements on constrained operator attention, working memory, and cognitive processing. The current research investigates the cognitive load (number of aircraft call signs) an individual can handle and explores the effect of proactive interference (PI) within this application. The results indicate a reduction in performance as the number of call signs are increased from 5 to 7 in the presence of PI. Additionally, this study seeks to understand if individual differences in working memory and attention predict performance on the multiaircraft control radio communication task through the application of the Operations Word Span test, Attention Control Scale, and GRE scores. Hierarchical linear modeling was used to determine the relationships among these and other variables.

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Document Details

Document Type
Technical Report
Publication Date
Mar 26, 2015
Accession Number
ADA616375

Entities

People

  • Kelly M. Amaddio

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Aircrafts
  • Cognition
  • Cognitive Science
  • Cognitive Workload
  • Engineers
  • Human Factors Engineering
  • Human Systems Integration
  • Human-Machine Interaction
  • Information Processing
  • Psychology
  • Radio Communications
  • Students
  • Systems Engineering
  • United States
  • Unmanned Aerial Vehicles

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computer Networking
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.