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Leveraging Human-Computer Collaboration for Decision Making in Complex Systems

This research focuses on the supervisory control of complex systems, exploring the interaction and decision making between humans and automation. It investigates methods for applying interactive decision aiding strategies and information visualization to allow humans to explore the automation decision space. The study also examines the challenges of information overload, adaptive automation, complexity measures, and human interaction with autonomous vehicles.

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Leveraging Human-Computer Collaboration for Decision Making in Complex Systems

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  1. Leveraging Human-Computer Collaboration for Decision Making in Complex Systems Mary (Missy) Cummings Humans & Automation Lab Aeronautics & Astronautics MissyC@mit.edu

  2. Focus Areas • Supervisory Control • Humans vs. automation in complex systems • Mixed initiative approach to decision making • How to apply interactive decision aiding strategies to allow a human to explore the automation decision space? • Information Visualization • Cost functions, constraints & variables • Sensitivity analysis

  3. Computer Task Human Supervisory Control Sensors Controls • Planning a computer-based task • Communicating to the computer what was planned • Monitoring the computer’s actions for errors and/or failures • Intervening when the plan has been completed or the computer requires assistance • Human & computer learn from the experience Human Operator (Supervisor) Displays Actuators

  4. Research Motivation: Tactical Tomahawk Project

  5. Branch Point Time-critical (emergent) Target Alternate (Flex) Target Loiter Pattern Default Target Proposed Tactical Tomahawk Missions Primary (Default) Target Default Mission Flex Mission Preplanned Health and Status points Emergent Mission Guidance Waypoint Launch Basket

  6. Sheridan & Verplank’s 10 Levels of Automation

  7. Supervisory Command & Control • Operators effectively controlled up to 12 missiles • Original “guestimate” was 4, FAA results similar • Automation bias and communication management were issues

  8. Human Supervisory Control & Network Centric Warfare • Appropriate levels of automation • Information overload • Adaptive automation • Distributed decision-making through team coordination • Complexity measures • Decision biases • Attention allocation • Supervisory monitoring of operators

  9. Information Overload

  10. Adaptive Automation • Dynamic role allocation • Mixed initiatives • System constraints • Skill Rule Knowledge-based behaviors • Cueing mechanisms • Psychophysiological • Noisy • Decision theoretic

  11. Complexity Measures in HSC Complexity of Environment Complexity of Goals Complexity of Procedures Complexity of Displays Cognitive Complexity Direct relationship Indirect relationship

  12. Human Interaction with Autonomous Vehicles • Human interaction with anytime path planning algorithms • Time-critical domains • Windows into automation • Multiple vehicle task management decision support • Levels of automation • Preview times • Stopping rules • Swarming behavior

  13. Command & Control: Rapid Replanning

  14. Resource Allocation

  15. Formation Flying in the Future

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