human supervisory control issues in unmanned vehicle operations mary (missy) cummings
DESCRIPTION
Human Supervisory Control Issues in Unmanned Vehicle Operations Mary (Missy) Cummings Humans and Automation Laboratory http://halab.mit.edu Aeronautics & Astronautics (617) 252-1512 [email protected]. Humans & Automation Lab. HAL Director. Former U.S. Navy officer and pilot - PowerPoint PPT PresentationTRANSCRIPT
Human Supervisory Control Issues in Unmanned Vehicle
Operations
Mary (Missy) CummingsHumans and Automation Laboratory
http://halab.mit.eduAeronautics & Astronautics
(617) [email protected]
Humans & Automation Lab
•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
HAL Director
Task
Displays
Human Operator(Supervisor)
Computer Actuators
Sensors
Controls
• Humans on the loop vs. in the loop
• Supporting knowledge-based versus skill-based tasks
• Network-centric operations & cognitive saturation
Human Supervisory Control
Ten Areas of Concern
• Information overload • Attention allocation• Appropriate levels of automation• Adaptive automation • Decision biases• Distributed decision-making through team
coordination• Complexity • Supervisory monitoring of operators • Trust and reliability• Accountability
Information Overload
0
4.5
1.5
Workload
Pe
rfo
rma
nc
e
Low HighModerate
Good
Poor
1414 1313 1414N =
Target Interarrival Time
2 Minutes4 Minutes
Ove
rall
Pe
rfo
rma
nce
Me
an
(+
/- 1
Sta
n.
De
v)
260
240
220
200
180
160
140
Missiles
8
12
16
Attention Allocation
• Multiple HSC tasks = Divided attention problem
• Information uncertainties & time latencies• Preview times & stopping rules• Primary task disruption by secondary task
– Chat
Level Automation Description
1 The computer offers no assistance: human must take all decision and
actions.
2The computer offers a complete set of
decision/action alternatives, or
3 narrows the selection down to a few, or
4 suggests one alternative, and
5executes that suggestion if the human
approves, or
6 allows the human a restricted time to veto before automatic execution, or
7 executes automatically, then necessarily informs humans, and
8 informs the human only if asked, or
9 informs the human only if it, the computer, decides to.
10 The computer decides everything and acts autonomously, ignoring the
human.
Appropriate Levels of Automation
Adaptive Automation
• Dynamic role allocation– Mixed initiatives
• A problem of intent
• Cueing mechanisms– Psychophysiologi
cal– Decision
theoretic– Performance-
based
Decision Biases
• Naturalistic Decision Making– Dynamic ill-
structured problems with shifting goals (i.e., NCW)
– Heuristics good & bad
• Biases– Confirmation– Recency– Automation
Distributed Decision-making & Team Coordination
• The move from hierarchical, centralized to decentralized control
• Team mental models & shared situation awareness (SA)
• Decision support– Automated agents as
team members
• Not just an issue for human teams– Swarming UAVs
Complexity
Supervisory Monitoring• Nested supervisory control• Two basic issues: Recognizing &
intervening• Interventions
– Redistribute workload– Adding team members (both human &
computer)– Modify mission objectives
Trust & Reliability
Accountability
The Future of UVs and NCO
• We can’t do it without automation & intelligent autonomy– Bounded Collaboration
• Human-centered design vs. mission-centered design– Unmanned systems do not really exist– The systems engineering process must
consider humans early– Robust systems are needed for both human
and automation brittleness considerations