SAFTE/FAST
Evidence-based Aviation
Fatigue Risk Management
Steven R. Hursh, Ph.D.
President, IBR and
Professor, Johns Hopkins University School of Medicine
September 1, 2011
Copyright 2010,
2008, IBR
Major Fatigue Factors
● Time of Day: between midnight and 0600 hrs.
● Recent Sleep: less than eight hours in last 24
hrs.
● Continuous Hours Awake: more than 17 hours
since last major sleep period.
● Cumulative Sleep Debt: more than eight hours
accumulation since last full night of sleep
(includes disrupted sleep).
● Time on Task/Work Load: continuous work
time without a break or intensity of work
demands.
Copyright 2008, IBR
An Objective Fatigue Metric
● No Blood Test for fatigue, yet
● The conditions that lead to fatigue are well
known.
● A fatigue model simulates the specific
conditions and determines if fatigue could be
present.
● The model can estimate the level of
degradation in performance and provide an
estimate of schedule induced fatigue risk.
Copyright 2008, IBR
SAFTE
● The Sleep, Activity, Fatigue, and Task
Effectiveness (SAFTE) Model is based on 12
years of fatigue modeling experience.
● Validated against laboratory and simulator
measures of fatigue.
● Validated and calibrated to predict accident risk by
the Department of Transportation.
● Peer reviewed and found to have the least error of
any available fatigue model.
● Accepted by the US DOD (Air Force, Army,
Navy, Marines) as the common warfighter
fatigue model.
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SAFTE Model Components
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Least Error for Conditions of
Sleep Restriction
2002 Seattle Fatigue & Performance Modeling
Workshop, of all models tested against laboratory
measurements:
● SAFTE had least error predicting objective vigilance
performance.
● SAFTE had least error predicting subjective ratings of
fatigue.
● Advances since 2002 have further validated the
sleep and performance assumptions and prediction
of accident risk and severity.
Von Dongen, Aviation, Space, and Environmental Medicine, March, 2004, vol. 75, no. 3,
6
section II
Copyright 2008, IBR
Accuracy of Predicting Sleep
Pattern and Duration
Measure
Signalman Maintenance
of Way
Dispatchers
(less night workers)
Train and
Engine
Mean
Agreement
92%
92%
90%
88%
Daily Sleep
(Est.- Log)
-24 min
-21 min
-3 min
- 10.8 min
7
Copyright 2008, IBR
Economic Risk and Effectiveness
Railroad Accident Relative Risk
6
Economic Risk - Damage & Casualty Cost
5
516%
Accident Risk
Relative Risk
4
3
2
1 = Unchanged relative risk
$
142%
#
103%$
#
1
$
#
70%
0
25%
Greater than 90
No Fatigue
49%
77 to 90
Less than or equal to 77
Crew Effectiveness Score
High Fatigue
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Validated Fatigue
Modeling Tools
SAFTE/FAST
Fatigue Science has the exclusive license from the US Army to commercialize SAFTE model.
Copyright 2008, IBR
Practical Software for Implementation
● Fatigue Avoidance Scheduling Tool (FAST)
 Fatigue assessment tool using the SAFTE model
 Developed for the US Air Force and the US Army
 DOT / FRA sponsored work has lead to
enhancements for transportation applications
● FAST Features
 Sleep estimation algorithm
 Graphical analysis tools
 Dashboard of fatigue factors
 Data based of all effectiveness scores
Copyright 2008, IBR
FAST Aviation Sleep Estimation
● Accurate estimation of sleep is critical:
 Measure: actigraphy or log books
 Estimate: algorithm to simulate sleep behavior
● Aviation specific estimates that can be refined
with actrigraphic measurement.
● Considers time zone changes and is valid for
any city pair.
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Sleep Estimator
Tailored to Aviation Environment:
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FAST Aviation Specific AutoSleep
●
●
●
●
●
●
●
Mimics typical sleep patterns
Tailored to workgroup and schedule demands
Considers total duty period and commuting
Naps prior to anticipated late starts
Considers time zones
Slits sleep when appropriate
Automatically inserts in-flight sleep for augmented
crews. User defined parameters:
 amount of augmentation and
 quality of sleep environment
● Adjustable settings can be saved to file
13
Copyright 2008, IBR
Fatigue
RiskImprovement
ManagementProcess
System
Continuous
Measure
Define the situation
Schedule evaluation
Actigraph recordings
Monitor
Model & Analyze
Assess operational indicators
Individual self-evaluation
Feedback to process
FRM
Steering Committee
Involves all
stakeholders
at each stage:
management, labor,
aided by science
Model the fatigue problem
Analyze sources and
Fatigue factors
SAFTE/FAST
Modify/Mitigate
Shared Responsibility
• Operating practices
• Labor agreements
• Individual “life style”
Manage
Collaborate for solutions
Obtain commitment to
solve problem
Enablers
Employee training
Medical screening
Economic analysis
Technology aids
Copyright 2008, IBR
FAST Aviation
Fatigue Assessment Process
Airline Specific Schedule Database
XML format
City-pairs/Trips or
30-day Bids
Aviation AutoSleep
SAFTE Model
Output results to folder
Links to Manager
Standard FAST
schedule is created by
FAST Aviation Modeler
FAST Aviation
Manager
FAST Aviation
Modeler
•
•
•
•
Translation Tools
available for any
scheduling system
•
•
•
•
Sorts by Criterion
Displays results
Links to Analyzer
Fleet level reports
FAST Analyzer
Individual
Schedules
•
•
•
•
•
Examine schedules
Effectiveness Graph
Fatigue Factors
“What-If” Drills
Individual reports
Modular Process for Speed and Flexibility
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FAST Aviation Modeler
Model the schedules:
1. Set AutoSleep parameters if necessary
2. Name the Output folder a unique name
3. Choose either a City Pairs file or a Bid
Schedules file for modeling
Airline Schedule Database
Processed Schedules Modeling
Results
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FAST Aviation Manager
Sort by:
 Flight Time Below Criterion Level (FTBCL)
 Critical TBCL (30 min associated with takeoff/landing)
 Average Effectiveness
 Minimum Effectiveness overall
 Minimum Effectiveness during critical periods
 Maximum Workload (high workload score in schedule)
 Median Workload (central score across schedule)
Save table to text file
Click on any line in Aviation Manager and schedule opens in FAST
for detailed analysis.
Copyright 2008, IBR
If fatigue is present, what do
you do about it?
●Modeling tools must do more than give
you a fatigue score:
It must estimate fatigue risk
It must show detail of each schedule
It must calculate fatigue factors
It must suggest conditions that lead to
fatigue so mitigations can be
implemented by an FRMS
18
Copyright 2008, IBR
Detailed Analysis Results
● Creates detailed database that shows:
 All duty periods and estimated sleep intervals
 Effectiveness in each half hour of each duty period
 Effectiveness at each half hour of the clock
 Distribution of duty time in effectiveness categories
 Allows results be sorted based on user defined
categories
 Individual ID reports with effectiveness at the 1 min
resolution
19
Copyright 2008, IBR
FAST Aviation Analyzer
San Francisco to Sydney Pairing
14.5 hr flight
Pre-flight nap
Sleep Timing based on both
physiological and social cues
In-flight sleep
Dashboa
Fatigue
Pre-flight nap
Schedules in Aviation Manager link to FAST for detailed analysis.
Copyright 2008, IBR
Dashboard Information
Content based on fatigue analysis workshop hosted by NTSB and
conducted by Drs. Mark Rosekind & David Dinges,
funded by FRA Office of Safety.
 Sleep (last 24


Flags are fatigue indicators



hrs)
Chronic Sleep Debt
Hours Awake
Time of Day
Out of Phase
Performance Values



Value at point
in schedule
Criteria


Effectiveness (vigilance)
Mean Cognitive
Lapse Index
Reaction Time
Reservoir
Copyright 2008, IBR
Schedule Files for Evaluation
A: 90 Short haul pairings, 1094 active flights
B: 56 Short haul monthly rosters, 3963 active flights
C: 47 Long haul pairings, 188 active flights
D: 64 Long haul monthly rosters, 1006 active flights
● Translated the spread sheets using Access database into the required
XML file structure.
● Batch processed through FAST Aviation
● Used FAST Manager to rank order Pairings and Rosters
● Used output spread sheet to rank order segments
22
Copyright 2008, IBR
Fatigue Metrics
● Typically, FAST is used to assess the “tail of the
distribution” – how much critical duty time is spent at
low effectiveness.
● For this exercise, we were asked to rank order all
segments and schedules, not just the extreme cases.
● We rank ordered segments by minimum effectiveness
at critical times of flight – take-offs and landings.
● We rank ordered pairings and rosters by minimum
effectiveness and “critical time below criterion” which
is more useful for entire schedules.
23
Copyright 2008, IBR
SAFTE/FAST - Segment Analysis
A SH
Pairings
Rank
1
2
3
4
5
A10040
A10002
A10045
A10002
A10002
Start
End
Min Critical Time
Minimum E Rank
LAX
LPB
ATL
VVI
IQQ
ATL
IQQ
SEA
LPB
SCL
5/15/2010 5:55
2/4/2011 8:15
5/14/2010 1:30
2/4/2011 6:30
2/4/2011 10:10
5/15/2010 10:08
2/4/2011 9:19
5/14/2010 6:57
2/4/2011 7:44
2/4/2011 12:24
70.84
74.64
74.8
74.99
75.65
3
7
8
9
10
ANC
PDX
DFW
BRU
LAX
LAX
NRT
BRU
SHJ
AMS
9/16/2010 15:05
5/17/2010 21:10
9/23/2010 18:15
9/27/2010 16:40
9/16/2010 23:10
9/16/2010 20:09
5/18/2010 7:59
9/24/2010 3:34
9/27/2010 23:09
9/17/2010 9:49
70.32
70.45
72.06
73.62
73.81
1
2
4
5
6
ARI
IQQ
ANF
ARI
IQQ
SCL
SCL
SCL
SCL
SCL
12/22/2010 5:45
1/10/2011 5:30
1/8/2011 3:40
1/16/2011 2:55
1/10/2011 4:25
12/22/2010 8:09
1/10/2011 7:44
1/8/2011 5:29
1/16/2011 5:19
1/10/2011 6:39
72.59
72.84
73.66
74.17
74.39
6
7
8
9
10
66.82
67.76
67.78
68.59
68.88
1
2
3
4
5
C LH Pairings
1
2
3
4
5
C10027
C10014
C10033
C10025
C10030
B SH Rosters
1
2
3
4
5
B10049
B10046
B10052
B10049
B10044
1
2
3
4
5
D LH Rosters
D10029
GUM
D10032
LIM
D10024
SLC
D10052
HKG
D10024
SLC
NRT
5/26/2010 5:00
5/26/2010 8:54
SCL
1/4/2011 6:15
1/4/2011 9:34
ANC 5/18/2010 3:35
5/18/2010 8:29
HEL 11/17/2010 17:15 11/18/2010 4:19
ANC
6/2/2010 3:35
6/2/2010 8:29
24
Copyright 2008, IBR
SAFTE/FAST - Roster Analysis
Rank
A SH
1
2
3
4
5
Critical TBCL
(77)
TBCL Overall Rank
149
2
88
4
61
6
53
9
41
10
Pairings
A10002
A10001
A10008
A10040
A10000
C LH
1
2
3
4
5
Pairings
C10014
C10033
C10019
C10038
C10027
182
143
77
61
61
1
3
5
6
6
3
B SH
1
2
3
4
5
Rosters
B10049
B10050
B10046
B10045
B10047
201
194
126
124
123
1
2
4
5
6
1
D LH
1
2
3
4
5
Rosters
D10024
D10043
D10044
D10022
D10029
180
111
91
85
79
3
7
8
9
10
3
Minimum E Rank
2
4
5
1
8
4
7
1
2
6
2
8
5
9
6
16
25
1
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Minimum Critical Time Effectiveness
SEGMENTS
26
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Short Haul Pairing
A 10040 LAX to ATL Segment
Early Start Daytime Rest
Night flight
27
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LH Pairing - C 10027 Anchorage-LAX Segment
86% reservoir
5 hrs
28
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LH Pairing - C 10014 – Narita Segment
Narita
29
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Short Haul Pairing - A 10002
Santa Cruz, Bolivia – Santiago, Chile
1.5 hr Nap
30
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A 10002, continued
Santa Cruz, Bolivia – Santiago, Chile
Possible Mitigation
3 hr Nap
31
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Long Haul Pairing - C 10014
Honolulu to Salt Lake
93% Res
3:15 Base
Narita
Honolulu
Salt Lake
32
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C 10014 Honolulu to Salt Lake
Altered Sleep Pattern
Altered Sleep Pattern
33
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Long Haul Pairing
C 10033 Kuala Lumpur Based Pilot
34
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Greatest Time Below Criterion
ROSTERS
35
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Long Haul Roster - D 10029
11 Day - Closer Examination
36
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D 10029 Detroit– Narita- Guam
Segment
37
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Long Haul Roster
D 10029 Guam – Narita Segment
38
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Short Haul Roster - B 10049
92 Segments in 57 Days
25th Ranking Workload of 56
39
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B 10049
Early Start on 12/19
40
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B 10049
Multiple Segments at Night
on 12/21 starting 1730 to 0510
41
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B 10049
Multiple Segments at Night
42
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Long Haul Roster - D 10024
Salt Lake-Anchorage-Minn
43
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D 10024 Six Day Series
Salt Lake-Anchorage-Minn
44
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D 10024 Salt Lake-Anchorage-Minn
Explanation
Two Early Starts (0700 and 0500)
Two Consecutive Night Flights (2235 and 0020)
Daytime Recovery
6 hrs
5 hrs
45
Copyright 2008, IBR
Workload Factor
● According to the NTSB: “One factor that
contributes to self-reported pilot fatigue,
especially in short-haul flight operations, is
the number of legs flown in a duty period.”*
● The highest workload in a flight occurs at
take-off and landing; increasing segments
multiplies these high stress periods.
● FAST Aviation is the first fatigue assessment
tool to provide an automated method to
assess this source of fatigue.
*NTSB Safety Recommendation, A-09-61 through -66, August 7, 2009
Copyright 2008, IBR
Sample Workload Pattern
Workload Calculation
14
12
Maximum
Number or Factor
10
8
Workload
6
Segments
4
2
Median
0
1
2
3
4
5
6
7
8
Days from Start of Schedule
Copyright 2008, IBR
B 10007
Top Ranking Workload
58 Segments in 12 Days
48
Copyright 2008, IBR
Advantages of Modeling Approach
● Validated model with history of outstanding
performance under independent review.
● Explicit Sleep Estimator (AutoSleep) tailored
to habits and policies of the airline.
● Aviation specific drivers of fatigue.
 Cognitive fatigue
 Workload related fatigue
● Analysis tools that lead to specific fatigue
factors and mitigation approaches.
● Modular design can be tailored to customers
needs.
Copyright 2008, IBR
Summary
Copyright 2008, IBR
Fatigue
RiskImprovement
ManagementProcess
System
Continuous
Measure
Define the situation
Schedule evaluation
Actigraph recordings
Monitor
Model & Analyze
Assess operational indicators
Model the fatigue problem
Involves all
Mitigations
are
Proportional
to
the
Risk
stakeholders
Individual self-evaluation
Analyze sources and
at
each
stage:
Feedback to process
Evolutionary,management,
Incremental
ImprovementFatigue factors
labor,
by science
Responsive toaided
Changing
Circumstances
Modify/Mitigate
Shared Responsibility
• Operating practices
• Labor agreements
• Individual “life style”
Manage
Collaborate for solutions
Obtain commitment to
solve problem
Enablers
Employee training
Medical screening
Economic analysis
Technology aids
Copyright 2008, IBR
Fatigue Risk Pyramid
Accidents
& Incidents
Fatigue Related
Errors
Subjective Awareness
Job Performance Changes
Level 3 Defense
Employee sleep habits, traits, & conditions
Level 2 Defense
Work demands, schedules, and sleep opportunities
Level 1 Defense
Based on James Reason, “Managing the Risks of Organizational Accidents”,
Figure 1.6, Stages in the development and investigation of an organizational accident.
Copyright 2008, IBR
If fatigue is present, what do
you do about it?
●Modeling tools must do more than
give you a fatigue score:
It must estimate fatigue risk
It must show detail of each schedule
It must calculate fatigue factors
It must provide context of conditions
that lead to fatigue so mitigations can
be implemented by an FRMS
53
Copyright 2008, IBR
Questions:
Steven R. Hursh, PhD and Reid Blank
Institutes for Behavior Resources
2104 Maryland Avenue
Baltimore, MD 21218
(410) 752-6080
shursh@ibrinc.org
rblank@ibrinc.org
Chris Hallman
Baines Simmons America
17 Greenville St., Suite 221
Newnan, GA 30263
(678) 343-1635 Office
(770) 251-5654 Fax
chris@bainessimmonsamericas.com
www.safetyfromknowledge.com
54
Copyright 2008, IBR
FS Actigraph Data Processing
Individual fatigue risk levels are
amalgamated into a group
report
SAFTE evaluates the fatigue risk
and effectiveness of each individual
driver
Personnel wear the actigraph
that measures wrist
movements
Daily sleep/wake/work times are
fed into the SAFTE risk evaluation
model
Wrist movements are recorded
24/7 and downloaded over the
internet
Downloaded data are converted to
daily sleep/wake/work
times
Copyright 2008, IBR