Fatigue Modeling in Support of Flight and Duty Time Rule-making 

1. Introduction 

During the development of proposed new rules governing flight and duty time limitations for aircrew, the ARC and 

the FAA utilized fatigue modeling as one tool to assist with the evaluation of the relative safety risk of alternative 

rules. Modeling can compare scenarios within a common set of fatigue assumptions and provide a way to evaluate 

the relative risk of alternative scheduling rules. Fatigue risk is a continuous process; fatigue risk is said to increase 

as performance declines and the risk of attention lapses or cognitive errors increase. Rule-making, by its nature, 

defines discrete limits based on relative levels of risk between alternatives. Fatigue modeling can assist with that 

process by providing relative comparisons of alternatives to guide limitations that will ultimately be expected to 

improve safety. 

2. Fatigue Science and Modeling Methodology 

The science of sleep and fatigue has evolved significantly. This evolution has led to an understanding of factors that 

influence fatigue, the related effects on crewmember performance effectiveness, and the necessary mitigation 

techniques. There are several scientific models of human performance versus fatigue available to the industry, and 

any may be used to assist in the planning and implementing of flight operations. The FAA has selected the Sleep, 

Activity, Fatigue, and Task Effectiveness (SAFTE) fatigue model and associated Fatigue Avoidance Scheduling 

Tool (FAST) software (SAFTE/FAST) as its tools to assist in evaluating flight and duty time limits. This model 

currently is used by the Department of Transportation and the Department of Defense to assess fatigue risk factors. 

The SAFTE/FAST model has demonstrated the ability to accurately identify fatigue risk factors when the model is 

properly used. This model has been demonstrated to incorporate the elements of fatigue and performance

effectiveness with the highest accuracy and resolution of available programs and is easily applied to specific city pair 

operations. This modeling, combined with real-world experience, data collection, fatigue management studies, and 

scientific review form the basis for FAA decision-making 

3. Background on the SAFTETM Model and FASTTM Modeling Software 

During the past ten years, the US Air Force, the US Army, and the Federal Railroad Administration (FRA) have 

sponsored the development of a model of human fatigue and circadian variation, as well as a scheduling tool based 

upon the model that will be used to minimize aircrew fatigue. The software was developed by companies involved in 

an Air Force project and is called the Fatigue Avoidance Scheduling Tool (FASTTM). Fatigue predictions are 

derived from the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTETM) model invented by Dr. Steven Hursh 

of the Institutes for Behavior Resources, Inc. The model has undergone considerable testing and validation against 

available human performance data. Predictions are highly correlated with speed on a psychomotor vigilance test, 

lapse frequency, and overall performance on a battery of cognitive tests. Importantly, the model has been shown to 

be valid for conditions of chronic sleep restriction as well as acute sleep deprivation. The SAFTETM model has 

received a broad scientific review by a group sponsored by the US Department of Defense and Department of 

Transportation. In an independent evaluation of six existing fatigue models, the most recent version of SAFTETM 

was found to be most accurate for predicting effects of restricted sleep on both cognitive performance and subjective 
evaluation of fatigue (Von Dongen, Aviation, Space, and Environmental Medicine, March, 2004, vol. 75, no. 3, 

section II). Recent studies conducted by the Federal Railroad Administration have validated that the model can 

predict accident likelihood and cost (severity) based on evaluation of the sleep and performance effects of work 

schedules (DOT/FRA/ORD-08/04 and DOT/FRA/ORD-11/13). The FAST tool has also been shown to make good 

estimates of the amount of sleep likely to be achieved by the average person under irregular work schedules (FRA 

brief report RR11-02). 

The SAFTETM model predicts cognitive effectiveness, which ranges from 100 to zero, with 100 representing the 

typical well rested person’s best daily performance. The model assumes that the average person can be awake for 16 

hrs and sleep for eight hours each day during their circadian night without suffering a cumulative sleep debt. 

Decreases from 100 can be interpreted as percent reductions in vigilance speed relative to this hypothetical well 

rested person. For an average person with a bedtime of 2300 and a wakeup time of 0700, a score of 90 is 

approximately the level of effectiveness immediately prior to going to bed at the end of the day. If that person 

remains awake for 18.5 hrs, then effectiveness will decline to about 77. Effectiveness will reach a typical circadian 

low of about 70 after being awake 22 hrs or at about 0500 in the morning. These benchmarks represent the joint 

effect of time awake and circadian oscillation in performance. 

For comparison purposes, it is low effectiveness in the model that represents fatigue risk. For any given schedule, 

effectiveness varies and can be plotted as a distribution of values. The majority of time is usually well above 80, 

often above 90. It is time in the lower tail of that effectiveness distribution that represents risk. One way to calculate 

the size of that exposure to risk is to set a benchmark effectiveness value and calculate the percent of duty time 

below that benchmark. For the studies reported here, the benchmark for this calculation of exposure time was 77. 

An effectiveness level of 77 was chosen as a benchmark because it is approximately equivalent to the effectiveness 

of someone with a blood alcohol concentration of 0.05. However, this value should not be interpreted as a 

demarcation between safe and unsafe; but rather, it is a convenient way to assess risk exposure with the assumption 

that, all else being constant, a schedule with less duty time below 77 represents less fatigue risk relative to a schedule 

with more duty time below 77. This approach is appropriate for comparison of individual schedules, as reported 

below, using the model as a representative of the average person. 

Purpose 

The purpose of this document is to review the fatigue modeling studies that were conducted in support of flight 

and duty time rule-making. The following sections of this report review the basic modeling assumptions and 

findings relative to consecutive nights of duty and the effects of split duty. 

4. Consecutive Nights without and with Breaks and Naps

4.1. Modeling Approach

4.1.1. Duty period started with a report time of 2200. Total duty time was 11 hrs, including any break 

time. 

4.1.1.1. Examined five consecutive nights in a week. 

4.1.1.2. Considered a series of cases in which a mid-duty break was specified and assumed all sleep 

during the break was of good value: 83.5% restorative, considering the quality of the 

environment. 

4.1.1.3. All breaks started at 0200 and after the break, the duty period resumed to a total of 11 hrs. 

4.1.1.4. Considered 1.5, 2, 2.5, 3 and 4 hr mid-duty breaks.
4.1.1.5. Time in bed was assumed to be 30 min less than the break: 15 min to get to sleep and 15 min 

to recover from inertia. 

4.1.1.6. Daytime sleep was assumed to be 6.5 hrs, consistent with reports of sleep in night duty shift 

workers (Thorne, et al. 2008, Budnick, et al. 1994, Knauth, et al. 1980; Wilkinson, R. T. 

1992). 

4.1.1.7. No waypoints were considered, assumed entrainment to local time and normal phase, and 

examined one week of operations. 

4.1.2. Each of the combinations of mid-duty (night) sleep and daytime sleep was evaluated with the 

SAFTE/FAST model. 

4.1.3. Overall patterns of performance ranging from 100 (normal best) to below 70 were plotted and 

compared. 

4.1.4. As a basis of comparison, time below a criterion of 77 was calculated, excluding the time during 

the breaks. 

4.1.5. A summary of the break conditions considered is shown in Table 1. 

Table 1: Summary of break conditions considered. 

Break Duration Break Start Break end Time in Bed

Duration

4 hr 0200 0600 3:30

3 hr 0200 0500 2:30

2.5 hr 0200 0430 2:00

2 hr 0200 0400 1:15

1.5 hr 0200 0330 1:00

4.1.6. For comparison, considered a base case without breaks or mid-duty nap opportunities. 

4.1.6.1. FTP was eleven hours starting at 2200, no split duty. 

4.1.6.2. Daytime time in bed (TIB) was 6.5 hrs. 

4.1.6.3. Prior to first night duty, evening nap of 2 hrs at 1700. 

4.2. Summary of results 

4.2.1. Results for the base case is shown in the Figure 1 and summarized in subsequent charts and tables 

as the no break case. 

5. Time below criterion (77) occurred on each day and increased across the first three days 

the week. 

6. Minimum effectiveness also consistently decreased across the week from 73 on the first 

day to 62 on the fifth day. 
Figure 1: Baseline cases for consecutive nights and no breaks.

6.1.1. Results for 6.5 hrs Daytime Time in Bed (TIB) with and without breaks are summarized in Table 2 

and Charts 2 and 3 (good break sleep), assuming 6.5 hrs of daytime TIB for sleep. 

7. Relative to no sleep (with or without a break), breaks between 2 and 4 hrs with sleep are 

superior to a 11 hr night duty period without sleep for the entire week. 

8. The 3 and 4 hr break cases remain above 77 throughout a five day sequence. 

9. The 2.5 hr break remains almost entirely above 77 for three day and is superior to no break 

for the entire week. 

10. The 2 hr breaks remain above 77 for one day and is superior to no break for the entire 

week. 

11. The 1.5 hr break does not avoid some time below 77 and is superior to no break for the 

first two days. 

Table 2: Percent Duty Time Below 77 for each day of five day sequence, good break sleep, 6.5 hr daytime TIB. The green 

shaded conditions all have less time below criterion than the base case without a break. 

Duration of Break w/ Good Sleep No Sleep

4 hrs 3 hrs 2.5 hrs 2 hr 1.5 hr No Break

1 0.0 0.0 0.0 0.4 12.5 41.7

2 0.0 0.0 0.0 7.4 38.4 50.2

Days 3 0.0 0.0 0.8 21.1 58.8 52.0

4 0.0 0.0 3.9 30.9 66.7 52.0

5 0.0 0.0 6.1 37.2 68.2 50.9
0

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Days of the Week

Consecutive Nights of Duty with Breaks

No break

1.5 hr

2 hr

2.5 hr

3 hr

4

Break Duration

Figure 2: Percent Duty Time Below 77 for each day of five day sequence, good break sleep, 6.5 hr daytime TIB 

3 hr Break 4 hr Break

2 hr Break 1.5 hr Break
Figure 3: Effectiveness across five days of duty with good break sleep and 6.5 hr daytime TIB. The duration of the mid-duty 

break is noted in each panel. 

12. Split Duty Analysis with 14 hr FDP 

12.1. Modeling Approach 

12.1.1. The modeling study was designed to assess for a flight duty period (FDP) of 14 hrs that started at 

2200, the potential benefits of inserting a break with a sleep opportunity. The objective was to 

evaluate if the benefits would be sufficient to justify a longer FDP and to determine the minimum 

break duration that would justify an FDP extension. The break durations considered were as 

follows: 

• 1 hr 

• 1.5 hr 

• 2 hr 

• 2.5 hr 

• 3 hr 

• 3.5 hr 

• 4 hr 

12.1.2. The following additional assumptions guided the modeling analysis: 

• Breaks were scheduled to be included in the hours between 2200 and 0500. 

• Assumed time in bed (TIB) with good sleep that started 15 min after start of break 

and ended 15 min prior to end of break. 

• Considered cases with a total FDP up to 14 hrs (including break) with total sleep held 

constant at 8 hrs per day. 

• Considered cases with a total FDP up to 14 hrs (including break) with daytime TIB 

of 6.5 hr at home, independent of the TIB during the break. 

12.2. Results: 

12.2.1. The results were evaluated in terms of duty time below an effectiveness of 77, a benchmark 

used for comparison purposes. Assuming a constant 6.5 hr daytime TIB, all breaks equal to or 

longer than 3 hrs and up to 4 hrs ensured no duty time below 77 across the entire week, see 

Figure 4.
Figure 4 Split duty – constant 6.5 hr daytime TIB and 3, 3.5, and 4 hr breaks - minimal time below 77.

12.2.2. A similar result was found when we assumed a constant TOTAL TIB (break and daytime sleep) of 

8 hrs, breaks equal to or longer than 3 hrs have minimal and no duty time below 77 across the 

entire week. Breaks of 2 hrs or less have considerable duty time below 77 and a break of 2.5 hrs 

has duty time below 77 during the last three duty periods, Figure 5. 

Figure 5: Split Duty – 8 hrs total TIB, 3, 3.5, and 4 hr Breaks – Minimal Time Below 77. 

12.2.3. Breaks of 1 to 2.5 hrs are less effective in avoiding duty time below 77, Figure 6. For breaks of 1 

to 2 hrs, time below 77 is experienced across the entire week; for breaks of 2.5 hrs, time below 77 

begins to occur on day 3. Results are summarized in Table 3. 
7m 25m 38m BCL

1 hr Break 1.5 hr Break

2 hr Break 2.5 hr Break

Figure 6: Split Duty - 10 hr FTP plus Break, as indicated.

Table 3: Percent duty time below effectiveness 77 assuming 6.5 hrs daytime TIB. 

Percent Time Below Criterion (77) – 6.5 hrs Daytime TIB

Day Duration of Break (hrs) 

1 1.5 2 2.5 3 3.5 4 

1 35.5 2.0 0.3 0 0.0 0.0 0.0 

2 63.2 37.0 7.0 0 0.0 0.0 0.0 

3 64.7 57.5 21.7 1.2 0.0 0.0 0.0 

4 64.3 67.8 31.7 4.2 0.0 0.0 0.0 

5 62.8 69.0 37.8 6.3 0.0 0.0 0.0 
1.1.1. The results are summarized in Table 7 and Figure 7 in which there was a constant 6.5 hrs of 

daytime TIB. For breaks of duration 3 hrs to 4 hrs, there was no time during the week of five duty 

periods with effectiveness projected to be below effectiveness of 77.

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1 Hr Break

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2 Hr Break

2.5 Hr Break

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Figure 7: Percent duty time below effectiveness of 77 across five duty days with breaks from between 1 and 4 hrs in 

duration.

1.1.2. The results lead to the following conclusions: 

• The analysis was conducted with total duty time including the break extending up to 14 hrs. 

Since breaks greater than 3 hrs prevent all time below 77 and breaks end after the low point of 

the WOCL, extending duty up to 14 hrs does not increase risk provided the rest during breaks 

is good and additional daytime sleep is assumed to be constant with at least 6.5 hrs sleep. 

1.1.3. Increasing breaks beyond 4 hrs and FTP beyond 14 hrs creates complications because it is difficult 

to get the entire break within the 2200 to 0500 window AND have it follow a single flight segment. 

Such schedules (if permitted) could also induce a gradual phase shift because the duty period plus 

the required 10 hr rest sums to greater than 24 hrs. 

References: 

Budnick LD, Lerman SE, Baker TL, Jones H, Czeisler CA. (1994). Sleep and alertness in a 12-hour rotating shift work 

environment. Journal of Occupational Medicine, 36(12), 1295-300.

Knauth P., Landau K., Dröge C., Schwitteck M., Widynski M. & Rutenfranz J. Duration of sleep depending on the type of 

shift work, International Archives of Occupational and Environmental Health, 1980, Volume 46, Number 2, 167-177. 

Thorne H, Hampton S, Morgan L, Skene DJ, Arendt J. (2008). Differences in sleep, light, and circadian phase in offshore 

18:00-06:00 h and 19:00-07:00 hr shift workers. Chronobiology International, 25(2&3), 225-235. 

Wilkinson RT. How fast should the night shift rotate? Ergonomics 1992;35:1425–1446.