Holistic Modeling for Human-Autonomous System Interaction

Abstract

For complex systems that embed automation but also rely on human interaction for guidance and contingency management holistic models are needed that provide for an understanding of the individual human and computer elements and address the critical interactions of such complex systems. Discrete event simulation (DES) models and system dynamics (SD) models are two different approaches that can be used to address these requirements. Both modeling approaches can support the designers of future autonomous vehicle (AV) systems by simulating the impact of alternate designs on vehicle operator and system performance. However the DES modeling approach is likely best suited for using probabilistic distributions to accurately model an operator who is a serial processor of discrete tasks as well as an environment with randomly occurring events. The SD modeling approach is better suited for modeling continuous performance feedback that is temporally dependent and is affected by qualitative variables such as trust.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2015
Accession Number
ADA619386

Entities

People

  • A. Clare
  • M. L. Cummings

Organizations

  • Duke University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Air Force
  • Automation
  • Autonomous Systems
  • Autonomous Vehicles
  • Cognitive Systems Engineering
  • Cognitive Workload
  • Complex Systems
  • Control Systems
  • Engineering
  • Human Factors Engineering
  • Operations Research
  • Psychology
  • Simulations
  • Situational Awareness
  • Systems Engineering
  • Unmanned Systems
  • Unmanned Vehicles

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Software Engineering.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control
  • Autonomy - Human-Robot Interaction