The Role of Operator State Assessment in Adaptive Automation

Abstract

Computer systems are capable to take over more and more tasks from human operators, but this does not always improve the performance of the human-machine system. Automation of which the level is made dependent on the situation may be an improvement for the performance. One of the parameters that might be used for this so-called adaptive automation is the state of the operator that can be estimated with physiological parameters. This report provides a literature review on physiological measures and adaptive automation, and a model that describes the relation between the state of the operator, the human information processing and the interaction with the outside world. Furthermore, the results of a laboratory experiment are discussed. In this experiment, several physiological measures were monitored during the task performance of operators from the Netherlands Navy. The literature review shows that physiological measures are promising for adaptive automation. The model is used to argue that there are many situations in which state estimators might not be useful for adaptive automation. Moreover, the results of the experiment show that it is difficult to measure the state within small time segments which is necessary for adaptive automation.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2005
Accession Number
ADA455055

Entities

People

  • C. Jansen
  • J. A. Veltman

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Adaptive Systems
  • Automation
  • Climate Change
  • Cognition
  • Cognitive Workload
  • Computers
  • Control Systems
  • Human Factors Engineering
  • Human-Machine Interaction
  • Human-Machine Systems
  • Information Processing
  • Information Systems
  • Literature Surveys
  • Psychology
  • Reasoning
  • Situational Awareness
  • Task Performance And Analysis

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Human-Computer Interaction (HCI).
  • Systems Analysis and Design