Man-Man-Machine-Machine Etiquette: Towards an Environment to Investigate Behavioral Rules for Dynamic Man-Machine Teams

Abstract

In order for a defense organization to gain understanding of their performance in complex tactical situations it is important to accurately model the way opposing and own forces operate. It is a significant challenge to develop such models due to the increasing interdependence between personnel and technology. To gain a clear insight in how personnel and technology (or a man-machine network) together influence operational effectiveness one has to model environment, systems and human behavior at a very detailed level. TNO is performing research focused on maintaining or improving operational effectiveness with the introduction of new technologies such as smart sensors and unmanned systems. Simulation developers face the challenge of coupling environment, sensor, system and human behavior models in order to perform such research. There are currently not many standards and tools that support this kind of coupling, especially in the area of man-machine collaboration. TNO is developing the Man-Man-Machine-Machine Etiquette (M4E) toolbox that helps in integrating models of man and machine and allows them to run in concert in a simulated environment.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2010
Accession Number
ADA582158

Entities

People

  • A. Heuvelink
  • K. J. De Kraker
  • P. Langeslag
  • W. A. Van Doesburg

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Autonomous Systems
  • Control Systems
  • Detection
  • Detectors
  • Human Behavior
  • Human-Machine Interfaces
  • Information Systems
  • Intelligent Agents
  • Lessons Learned
  • Operational Effectiveness
  • Sensor Networks
  • Simulations
  • Standards
  • Unmanned Systems
  • User Interface
  • Virtual Reality

Fields of Study

  • Computer science
  • Engineering

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

  • Autonomy
  • Autonomy - Human-Robot Interaction
  • Autonomy - UAVs