The Impact of Heterogeneity on Operator Performance in Futuristic Unmanned Vehicle Systems

Abstract

Recent studies have shown that with appropriate operator decision support and with sufficient automation, inverting the multiple operators to single-unmanned vehicle control paradigm is possible. These studies, however, have generally focused on homogeneous teams of vehicles, and have not completely addressed either the manifestation of heterogeneity in vehicle teams, or the effects of heterogeneity on operator capacity. An important implication of heterogeneity in unmanned vehicle teams is an increase in the diversity of possible team configurations available for each operator, as well as an increase in the diversity of possible attention allocation schemes that can be utilized by operators. To this end, this paper introduces a resource allocation framework that defines the strategies and processes that lead to alternate team configurations. The framework also highlights the sub-components of operator attention allocation schemes that can impact overall performance when supervising heterogeneous unmanned vehicle teams. Subsequently, a discrete event simulation model is presented as a means to model a single operator supervising multiple heterogeneous unmanned vehicles. Results from an experimental case study are then used to validate the model, and make predictions about operator performance for various heterogeneous team configurations.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2009
Accession Number
ADA567805

Entities

People

  • B. Mekdeci
  • C. E. Nehme
  • J. W. Crandall
  • M. L. Cummings

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Human Systems

DTIC Thesaurus Topics

  • Aircrafts
  • Automation
  • Case Studies
  • Cognitive Systems Engineering
  • Control Systems
  • Human Behavior
  • Psychology
  • Random Variables
  • Simulations
  • Situational Awareness
  • Supervision
  • Supervisory Control
  • Swarming Technologies
  • Unmanned Aerial Vehicles
  • Unmanned Systems
  • Unmanned Underwater Vehicles
  • Unmanned Vehicles

Fields of Study

  • Computer science

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Theoretical Analysis.

Technology Areas

  • Autonomy
  • Autonomy - Human-Robot Interaction