Manual Operations of 4th Generation Airliners

Man4Gen - Situation Awareness on Modern Airliner Flight Decks
Operational Flight Simulator Campaign
Lars Fucke
Bruno J. Correia Grácio
Man4Gen Partners:
This research is funded as part of the FP7 2012 Aeronautics and Air Transport
programme under EC contract ACP2-GA-2012-314765-Man4Gen
What is the situation?
Commercial jet transports are extremely
safe...
• 25+ million departures per year (2013)
• Less than 2 accidents per million
departures
However...
– ...what about when systems fail?
– ...what if something unexpected
happens?
– ...we rely on the pilot.
Is the pilot ready to take control?
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What is the situation?
The task of the flight crew has changed from
manual flying to strategic planning, tactical
management and monitoring of aircraft systems
→
Change in tasks, roles and cognitive
demands on the flight deck
Advanced systems increase reliability and
minimize faults and disturbances
→
Less exposure to unexpected events in
normal operations
Training programs focus on small selection of
pre-determined scenarios
→
Limited preparation for the truly
unexpected
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Problem Statement
Despite the substantial and proven safety benefits of automation
systems in 3rd and 4th generation aircraft, evidence indicates
that when faced with unexpected and challenging situations,
pilots sometimes have difficulties in quickly responding to
situations which require a rapid transition in their activity from
monitors of very reliable systems, to active and authoritative
decision-makers exercising manual control of the aircraft.
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Project Goals
• Identify the cognitive processes that lead to the loss
•
•
of Situation Awareness on modern airliner flight
decks,
Develop methods to model cognitive performance
in crew-aircraft systems,
Identify recommendations for procedure, training
and flight-deck design that help regaining Situation
Awareness or prevent the loss thereof.
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What have we done so far?
• Review of previous studies
• Analysis of automation on the
flight deck
• Simulator campaign studying
flight-crew behavior in
operational scenario
• fMRI experiment aiming at
studying neural processes
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Scenario Characteristics
Problem Statement:
Despite the substantial and proven safety benefits of automation
systems in 3rd and 4th generation aircraft, evidence indicates
that when faced with unexpected and challenging situations,
pilots sometimes have difficulties in quickly responding to
situations which require a rapid transition in their activity from
monitors of very reliable systems, to active and authoritative
decision-makers exercising manual control of the aircraft.
But:
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Operationally Relevant!
Simulator Scenario – Exploratory Phase
•
•
•
•
•
•
Familiar airfield
Time pressure: all engine op G/A; fuel @
diversion limit
Ambiguity: a/c state, a/p
Multiple decision points
Multiple options for landing
Transition to manual
Bird strike
A/P Hdg
Fail
ATC
Instruction
Autoland
No RWY vis
Wind cross
 tail
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VMC, vis on
RWYs
Experimental Campaign
Goals
• When/why is SA lost? Indicators?
• How do crews recover?
• What makes a crew more successful?
…
Facilities
• GRACE (NLR/747-like research cab)
• AVES (DLR/A320-like research cab)
Participants
• 12 flight crews at NLR
• 8 flight crews at DLR
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Data
• TRE/I PI/competency
ratings
• Cab video
• Eye tracking
• Interviews
Pilot Behavior Analysis
• Go-around due to tailwind:
2 / 20 crews
• Identified and verbalized engine surge:
15 / 20
• Operated engines below surge limit
11 / 20
• Verbalized surge, operated eng’s in surge
8 / 20
• Second landing with tailwind
14 /20
• Unstabilized 2nd approach (500ft)
7 / 12
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(NLR only)
Video Analysis
Desired Flight Crew Performance (DFCP) scoring scheme:
• Actions expected from flight crew for given situation
• 2 weights: normal, potentially unsafe
Pilot Behavior analysis based on the pilot core competencies (Airbus Pilot
Assessment and Grading System) by flight phase:
• Application of procedures
• Communication
Team of evaluators:
• Flight path management – automation
• 1 TRI/E,
• Flight path management - manual
• 1 Flight Deck Ops/
• Knowledge
Systems expert,
• Leadership and teamwork
• 1 Aeronautical expert
• Problem solving and decision making
• Situational awareness
• Workload management
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Pilot Behavior Analysis
• Extract the two highest and the one lowest performing crew
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•
from each experiment (DFCPs: 17 (3) .. 7(1) out of 22/20 (4))
Comment/rate crew performance by flight phase
• Good performance (Green)
• Below average performance (Amber)
• Poor performance (Red)
Match each comment to a core competency/PI (or several)
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Heat Maps for High-performing Crews (n=4)
General:
• Always high and low performance
•
characteristics
Shift to lower performance under high
work load
Good performance:
• More consistent performance under
•
high work load/in challenging
situations
Most notable competencies:
•
•
•
•
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Communication
Problem Solving and Decision
Making
Leadership and Teamwork
Workload Management
Heat Maps for Low-performing Crews (n=2)
Poor performance:
• Difficulties in SOPs already in low•
•
•
workload situations (Application of
Procedures)
Difficulties in manual Flight Path
Management throughout
Poor performance in Problem Solving
and Decision making during highworkload situations (bird-strike)
Difficulties in the following
competencies during the last flight
phase (execution of approach and
landing):
•
•
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Communication (e.g., open ended)
Problem Solving and Decision
Making
Summary
• Crew performance is a range
• Under high workload this range shifts to lower
•
•
average performance
In contrast to low-performing, high-performing
crews exhibit the following competencies under
high work load:
• Communication
• Problem Solving and Decision Making
• Leadership and Teamwork
• Workload Management
Low-performing crews show weaknesses in
application of procedures under low workload
and have difficulties in manual flying
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Conclusions from Exploratory Campaign
• Strengths of high-performing crews and weaknesses
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•
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of low-performing crews were identified
If competencies carry over to other scenarios,
focused training is possible
Procedures that reinforce required behaviors can be
developed
Flight deck features supporting essential
competencies can be designed
(decision-support, aircraft state/environment
awareness, etc.)
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Next Steps
Second experimental campaign to:
• Provide evidence that competency-based
performance can be measured, performance
translates to other scenarios requiring same
competencies and that exposure improves
performance
• Explore effectiveness of procedural
recommendations
• Test new flight-deck features
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Man4Gen Partners:
This research is funded as part of the FP7 2012 Aeronautics and Air Transport
programme under EC contract ACP2-GA-2012-314765-Man4Gen