Testing Adaptive Levels of Automation (ALOA) for UAV Supervisory Control

Abstract

OR Concepts Applied has designed and implemented a human factors test bed to evaluate adaptive autonomy schemes and a range of levels of autonomy for UAV supervisory control. The test bed includes a high fidelity simulation that interfaces with a mission control element (MCE) that supports multi-vehicle control. The MCE uses OPUS mission planning tools to provide the operator with optimization and analysis decision aids. SA Technologies, Inc. was instrumental in helping to create user interface elements to help maintain high levels of situation awareness even when the level of automation is increased. The test bed provides a variety of tools for researchers to create scenarios, alter adaptive schemas, and collect experimental data.

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Document Details

Document Type
Technical Report
Publication Date
Mar 24, 2007
Accession Number
ADA470315

Entities

People

  • Daniel Goldberg
  • Michael Leen
  • Rubin Johnson

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Aircrafts
  • Automation
  • Cognitive Systems Engineering
  • Control Systems
  • Human-Computer Interaction
  • Remotely Piloted Vehicles
  • Robotics
  • Simulations
  • Situational Awareness
  • Supervisory Control
  • Target Recognition
  • Test Beds
  • Unmanned Aerial Vehicles
  • Unmanned Systems
  • Unmanned Vehicles
  • User Interface

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Database Systems and Applications
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.