Human-Machine Teaming Systems Engineering Guide

Abstract

This guide was written to help system developers design autonomy and automation that works in partnership with the human operator. With increased complexity, automation, AI, and autonomy of systems playing out in robotics, unmanned vehicles, cognitive assistance, and more across the MITRE sponsor space, it is critically important to provide research-based guidance on human-machine teaming. Autonomy should act seamlessly within a human operators workflow, aiding performance by alerting them about behavior that deviates from normal, suggesting alternative solutions that they may not have considered, autonomously reorganizing priorities in response to their changing goals, or other collaborative activities. There is a wealth of published guidance on how to support human-machine teaming (HMT), but that guidance is rarely used to design operational systems. To bridge this gap between researchers and developers, MITRE surveyed and analyzed the existing literature to develop a set of General HMT Requirements. These are evidence-based requirements that address the span of autonomy from autonomous vehicles to cognitive assistants. Because not all General HMT Requirements are relevant to each specific type of system that employs automation and autonomy, and also because each system employs these technologies towards different goals, it is necessary to adapt the requirements for specific systems. This guide describes the system engineering methods for tailoring the General HMT Requirements into specific requirements for your system.

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Document Details

Document Type
Technical Report
Publication Date
Dec 11, 2018
Accession Number
AD1108020

Entities

People

  • Alexander Nelson
  • Cindy Dominguez
  • Isabel Trhan
  • Matthew Ryan
  • Nicholas Kasdaglis
  • Patricia Mcdermott

Organizations

  • MITRE Corporation

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Aircrafts
  • Autonomous Systems
  • Autonomous Vehicles
  • Cognition
  • Cognitive Systems Engineering
  • Cognitive Workload
  • Collision Avoidance Systems
  • Control Systems
  • Engineering
  • Engineers
  • Human-Machine Systems
  • Psychology
  • Robotics
  • Situational Awareness
  • Systems Engineering
  • Task Performance And Analysis
  • Unmanned Aerial Vehicles

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Software Engineering.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Human-Robot Interaction
  • Space
  • Space - Spacecraft Maneuvers