Laboratory Overview MIT Humans and Automation Lab February 2006

Laboratory Overview Laboratory Overview

MIT Humans and Automation LabMIT Humans and Automation Lab

February 2006February 2006

Overview of the MIT Humans and Automation LaboratoryOverview of the MIT Humans and Automation Laboratory

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History

• Created in 2004

• Director: Dr. Mary (Missy) Cummings

• Post Doctorate Associates: Dr. Stacey Scott, Dr. Jake Crandall

• Students: Sylvain Bruni, Jessica Marquez, Carl Nehme, Yves Boussemart, Amy Brzezinski, Angela Ho, Cristin Smith, Chris Tsonis, Patrick Laney, Jim McGrew

• and an army of undergraduate researchers!


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HAL Director

Former U.S. Navy officer and pilot

Systems engineer with a cognitive focus

Research Interests: Human supervisory control, decision support design, human interaction with

autonomous systems, design of experiments technology development, social impact of

technology


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Research and Current Projects• Research in the Humans and Automation Lab (HAL) focuses on the multifaceted interactions of human and computer decision-making in complex sociotechnical systems.

• Time-Sensitive Operations for Distributed Teams

• Human Supervisory Control Issues of Multiple Unmanned Vehicles

• Reduced manning

• Measurement of Display Complexity

• Collaborative Human Computer Decision Making

• Integrated Sensor Decision Support

Sponsors: Office of Naval Research, NASA, Boeing, U.S. Army, FAA, Lincoln Labs, AAI.


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0

4.5

1.5

Workload

Pe

rfo

rma

nc

e

Low HighModerate

Good

Poor

Task

Displays

Human Operator(Supervisor)

Computer Actuators

Sensors

Controls

Human Supervisory Control

• Humans on the loop vs. in the loop

• Supporting knowledge-based versus skill-based tasks

• Network-centric operations & cognitive saturation


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Boeing & the MIT Humans and Automation Laboratory• Collaborative Time Sensitive Targeting 2005-2009

• Phantom Works, Seattle• Mary Hornsby, Paul Parks, (formerly Dave Graeber)

• Activity awareness technology development

• Supervisor workload management support

• Team transition/handoff support

• Upcoming conference paper at CCRTS in San Diego

• Teaming with AFRL

• Human Supervisory Control Issues in Network Centric Warfare

• Multi-UAV control test bed

• 2 journal articles (one selected as top ten of conference)

• 1 book chapter

• 5 conference papers


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Collaborative Time-Sensitive Operations for Distributed Teams

• What aspects of collaborative TST would be best served by collaborative technologies?• Can we develop technology to facilitate collaborative decision-making in time-critical settings?


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Supporting Supervisors of Teams of HSC Operators

Supporting the Control of Teams of Heterogeneous Unmanned Vehicles


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Human Supervisory Control Issues in Network Centric Warfare• How do operators manage multiple supervisory control processes?

• What effects do human performance limitations have on the overall system?

• Mitigating workload

• Reduced Manning

• Combining Shadow positions

• Multiple UV control for a single operator

• Boeing, Mitre, Lincoln Labs


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Decision-Making

Decision-Making

Collaborative Human Computer Decision Making

• Three projects:

• TLAM Mission Planning Tool

• Decision Support for Planetary Exploration

• Decision Support for control of multiple UAVs

• Both humans and computers bring different strengths and limitation to problems solving in large problems spaces with many variables, some changing dynamically

• Determine how humans and computer optimization algorithmscan complement each other

Decision-Making


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• Tomahawk Strike Planning: missions and missiles

• Integration of temporal & spatial elements, resource allocation, managing assets, and performing contingency planning in a high workload environment.

• Cognitive Strategies


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Managing Multiple UAVs

• Replanning under time pressure with “intelligent” autonomy

• Multivariate optimization problem with no real optimal solution

• How much and where should automation be inserted?


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• Decision Support for Planetary Exploration

• Astronaut traversal replanning task

• Path replanning with increasingly complex constraints

• Affect of level of automated decision support


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Measurement of ATC Display Complexity

• Air Traffic Control display complexity metrics.

• Ran experiments to understand the effect ofspecific complexity factors (color, # aircraft,structure, environmental change).

• To better understand various scales ofcomplexity in the ATC system.

• Environmental, organizational,interface, & cognitive complexity

• Quantifying display complexity.

• Develop design guidelines for ATC displays.

• Relevance to future UAV operations


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Thank you!

• [email protected]

• http://halab.mit.edu

Documents

Laboratory Overview MIT Humans and Automation Lab February 2006