U.S. Department of Transportation

FEDERAL AVIATION ADMINISTRATION

Office of Aviation Policy and Plans

Washington, D.C. 20591

REGULATORY IMPACT ANALYSIS

Flightcrew Member Duty and Rest Requirements

PART 117

NOTICE OF PROPOSED RULEMAKING

OFFICE OF AVIATION POLICY AND PLANS

September 3, 2010
Table of Contents

EXECUTIVE SUMMARY........................................................................................................... 1

BENEFITS ANALYSIS ............................................................................................................................... 2

BACKGROUND & HISTORY ....................................................................................................................... 2

SUMMARY OF SCIENTIFIC PRESENTATIONS............................................................................................. 7

BENEFITS ..................................................................................................................................................11

BENEFIT OVERVIEW.................................................................................................................................12

RECEIVE ADEQUATE REST (SLEEP) BETWEEN DUTY PERIODS .............................................................13

DUTY TIME LIMITS ..................................................................................................................................18

TIME AWAKE............................................................................................................................................28

CHRONIC FATIGUE...................................................................................................................................32

LATE NIGHT DUTY FATIGUE ...................................................................................................................35

SIMULATION RESULTS .............................................................................................................................40

EFFECTIVENESS ANALYSIS ......................................................................................................................65

SENSITIVITY ANALYSIS: VALUE OF STATISTICAL LIFE ESTIMATES FOR FAA REGULATORY 

PROGRAMS ...............................................................................................................................................71

COST ANALYSIS.......................................................................................................................................73

COST OVERVIEW......................................................................................................................................73

FLIGHT OPERATIONS – OVERVIEW.........................................................................................................75

SCHEDULE RELIABILITY........................................................................................................................104

FATIGUE TRAINING - OVERVIEW ..........................................................................................................106

REST FACILITIES – OVERVIEW..............................................................................................................113

SUMMARY OF BENEFITS AND COSTS.............................................................................................119

APPENDIX A ............................................................................................................................................121

APPENDIX B.............................................................................................................................................127

APPENDIX C ............................................................................................................................................139
1

Executive Summary

This report documents a benefit/cost analysis of FAA’s proposed amendments to 

its flight, duty and rest regulations applicable to certificate holders and their flight crew 

members. The proposal recognizes the growing similarities between the types of 

operations and the universality of factors that lead to fatigue in most individuals. Fatigue 

threatens aviation safety because it increases the risk of pilot error that can lead to an 

accident. The proposed requirements would eliminate the current distinctions between 

domestic, flag and supplemental operations. The proposal provides different requirements 

based on the time of day, whether an individual is acclimated to a new time zone, and the 

likelihood of being able to sleep under different circumstances.

FAA has determined the proposed rule: (1) has benefits that justify its costs, (2) 

is an economically ―significant regulatory action‖ as defined in section 3(f) of Executive 

Order 12866, (3) is ―significant‖ as defined in DOT's Regulatory Policies and 

Procedures; (4) would have a significant economic impact on a substantial number of 

small entities; (5) would not create unnecessary obstacles to the foreign commerce of the 

United States; and (6) would impose an unfunded mandate on the private sector.

Based on the FAA safety effectiveness assessment for this proposed rule to 

prevent pilot fatigue accidents, we estimate a total benefit of $659 million ($ million at 

present value, over 10 years). Our rule requirements began with the recommendation 

from labor and industry and we then applied fatigue science to maximize benefits relative 

to costs. The total estimated costs of the proposed rule over 10 years are $1.25 billion 
2

($804 million at present value). There is over a 7 percent probability that undiscounted 

benefits of averting passenger airplane accidents would exceed $1.25 billion and over a 

10 percent probability the present value of the benefits of averting cargo airplane 

accidents would exceed $804 million. The benefits from a single near-term prevented 

catastrophic accident of a common 150-passenger airplane with an average load factor 

would exceed the present value cost of this rule. If the value of an averted fatality were 

increased to $12.6 million, the present value of the benefits would equal the present value 

of compliance costs. The FAA invites comments on the methodology, data, and 

assumptions employed in this analysis. 

Nominal Costs PV Costs

 (millions) (millions)

Total Costs 

(over 10 years) $1,254.1 $803.5 

Benefits Nominal Benefits

 (millions)

 PV Benefits

 (millions)

$6.0 million VSL $659.40 $463.80 

$8.4 million VSL $837 $589

Benefits Analysis

Background & History

The NTSB’s list of Most Wanted Transportation Safety Improvements includes 

safety recommendations about pilot fatigue. These recommendations are based on 

accident investigations and an NTSB safety study on commuter airline safety. The first 
3

NTSB recommendations to the FAA about pilot fatigue rulemaking occurred after the 

Guantanamo Bay, Cuba, accident on August 18, 1993. In that accident, three flight crew 

members were seriously injured and the airplane was destroyed. The captain lost control 

of the airplane while on approach to the U.S Naval Air Station at Guantanamo. The 

NTSB listed as a probable cause of the accident the impaired judgment, decision-making, 

and flying abilities of the captain and flight crew because of fatigue. The flight crew had 

been on duty for 18 hours and had flown for 9 hours. The NTSB recommended the FAA 

revise part 121 to require that ―tail end‖ ferry flights be included in flight crews’ flight 

time and duty time (A-94-105). The NTSB also recommended the FAA revise the 

flight/duty time limitations in its regulations to ensure the regulations incorporate the 

results of the latest research on fatigue and sleep issues (A-94-106).

The NTSB’s list of Most Wanted Transportation Safety Improvements includes 

another safety recommendation on pilot fatigue and ferry flights conducted under 14 CFR 

part 91. On February 19, 1995, three flight crew members died after a Douglas DC–8–63 

operated by Air Transport International was destroyed by ground impact and fire during 

an attempted three engine takeoff at Kansas City International Airport in Kansas City, 

Missouri. The NTSB noted the flight crew conducted the flight as a maintenance ferry 

flight under part 91 after a shortened rest break following a demanding round-trip flight 

to Europe that crossed multiple time zones. The NTSB further noted the international 

flight, conducted under part 121, involved multiple legs flown at night following daytime 

rest periods. In addition, the NTSB found the captain’s last rest period before the 

accident was repeatedly interrupted by the certificate holder.
4

In issuing its 1995 recommendations, the NTSB stated the flight time limits and 

rest requirements under part 121 that applied to the flight crew before the ferry flight did 

not apply to the ferry flight operated under part 91. The NTSB found the regulations 

allowed a substantially reduced flight crew rest period for the nonrevenue ferry flight. 

Because of the investigation, the NTSB reiterated earlier recommendations to (1) finalize 

the review of current flight and duty time limitations to ensure the limitations consider 

research findings in fatigue and sleep issues and (2) prohibit certificate holders from 

assigning a flight crew to flights conducted under part 91 unless the flight crew meets the 

flight and duty time limits under part 121 or other applicable regulations (A–95–113). 

Since this recommendation there have been additional accidents in which flight crew 

fatigue was a contributing factor in the accident.

On July 26, 2002, a Federal Express flight 1478, B727-232F, struck trees on 

approach and crashed short on the runway at the Tallahassee Regional Airport, 

Tallahassee, FL. The NTSB determined that the probable cause of the accident was the 

flight crew’s failure to establish and maintain a proper glidepath during the night visual 

approach to landing. The NTSB also determined that the captain’s and first officer’s 

fatigue contributed to the accident. Three flight crew members were seriously injured 

and the airplane was destroyed. The NTSB mentioned flightcrew fatigue as a factor 

contributing to the accident. In February 2006, the NTSB issued safety recommendations 

after a BAE–J3201 operated under part 121 by Corporate Airline struck trees on final 

approach and crashed short of the runway at Kirksville Regional Airport, Kirksville, 

Missouri. The captain, first officer, and 11 of the 13 passengers were fatally injured. The 
5

NTSB determined that the probable cause of the accident was the pilots’ failure to follow 

established procedures and properly conduct a nonprecision instrument approach at night 

in instrument meteorological conditions. The NTSB concluded that fatigue likely 

contributed to the pilots’ performance and decision making based on the less than optimal 

overnight rest time available to the pilots, the early reporting time for duty, the number of 

flight legs, and the demanding conditions faced during the long duty day.

Because of these accidents, the NTSB issued the following safety 

recommendations related to flight and duty time limitations: (1) modify and simplify the 

flight crew hours-of-service regulations to consider factors such as length of duty day, 

starting time, workload, and other factors shown by recent research, scientific evidence, 

and current industry experience to affect crew alertness (A–06–10); and (2) require all 

part 121 and part 135 certificate holders to incorporate fatigue-related information similar 

to the information being developed by the DOT Operator Fatigue Management Program 

into initial and recurrent pilot training programs. The recommendation notes that this 

training should address the detrimental effects of fatigue and include strategies for 

avoiding fatigue and countering its effects (A–06–11).

There have also been some incidents in which the NTSB cited flight crew fatigue 

as a cause. On February 18, 2007, Delta Connection flight 6448, operated by Shuttle 

America, Inc., overran the runway at Cleveland-Hopkins International Airport, 

Cleveland, OH (no fatalities and no serious injuries). On April 12, 2007, Pinnacle 

Airlines flight 4712 overran the runway at Cherry Capital Airport, Traverse City, 

Michigan (no fatalities and no serious injuries). On February 13, 2008, Go! Flight 1002, 
6

operated by Mesa Airlines, flew past its destination airport at Hilo, Hawaii – the flight 

crew fell asleep while in-flight (no fatalities and no serious injuries).

The current FAA rules in part 121 do not prescribe duty limits; rather they focus 

on flight time limits and rest requirements. Flight time limits and rest requirements vary 

based on the type of operation. The requirements in these subparts apply to domestic, 

flag, and supplemental operations. Under the current rules for domestic operations, 

flightcrew members must receive at least an 8-hour rest period during the 24-hour period 

before the end of each flight. Flightcrew members conducting flights under part 121 for 

domestic operations are limited to 30 hours of flight time in any seven consecutive days. 

The 7-consecutive-day limit for flag operations is 32 flight hours, and there is no 7-

consecutive-day limit for supplemental operations. In addition, part 121 limits the flight 

time of flightcrew members engaged in domestic operations to 1,000 hours in any 

calendar year. Flightcrew members engaged in flag and supplemental operations are 

limited to 1,000 hours in any 12-calendar-month period. There is a quarterly and semiannual limit of 500 hours and 800 hours, respectively, for unscheduled operations. 

Operators are required to provide each crewmember a minimum of 24 consecutive hours 

of rest during any seven consecutive days for all domestic, flag, and supplemental 

operations conducted under part 121.

On June 10, 2009, Federal Aviation Administration (FAA) Administrator 

J. Randolph Babbitt testified before the Senate Committee on Commerce, Science, and 

Transportation, Subcommittee on Aviation Operations, Safety, and Security on 

Aviation Safety on the FAA’s role in the oversight of certificate holders. He addressed 
7

issues on flightcrew member training and qualifications, flightcrew fatigue, and 

consistency of safety standards and compliance between air transportation certificate 

holders. He also committed to assess the safety of the air transportation system and to 

take appropriate steps to improve it.

In June 2009, the FAA convened the Flight and Duty Time Limitations and Rest 

Requirements Aviation Rulemaking Committee (ARC). The FAA tasked the ARC to 

develop recommendations for an FAA rule based on current fatigue science and a review 

of international approaches to the issue. The ARC submitted its recommendations to the 

FAA on September 10, 2009.

Summary of Scientific Presentations

To achieve the goal of developing proposed rules to enhance flightcrew member 

alertness and employ fatigue mitigation strategies, the ARC reviewed scientific 

information presented by experts in sleep, fatigue, and human performance research. 

Below is a summary of the scientific presentations:

1. Fatigue

Fatigue is characterized by a general lack of alertness and degradation in mental 

and physical performance. There are three types of fatigue: transient, cumulative, and 

circadian. Transient fatigue is acute fatigue brought on by extreme sleep restriction or 

extended hours awake within 1 or 2 days. Cumulative fatigue is fatigue brought on by 

repeated mild sleep restrictions or extended hours awake across a series of days. 
8

Circadian fatigue refers to the reduced performance during nighttime hours, particularly 

during the window of circadian low (WOCL).

There is no direct measure or physiological marker that shows when a person is 

fatigued, although biomedical data may indicate physiological conditions favorable to 

fatigue. Fatigue is often accompanied by drowsiness but is more than just being sleepy or 

tired. Common symptoms of fatigue include:

Measurable decrease in speed and accuracy of performance,

Lapses of attention and vigilance,

Delayed reactions,

Impaired logical reasoning and decision making, including a reduced ability to 

assess risk or understand effects of actions,

Reduced situational awareness, and

Low motivation to perform optional activities.

Various factors contribute to whether an individual experiences fatigue and the 

severity of fatigue experienced. The major factors affecting fatigue include:

Time of day. Fatigue is, in part, a function of circadian rhythms. Human 

waking and sleep cycles follow a 24-hour cyclical wave pattern known as the 

internal body clock (circadian rhythm). The circadian rhythm is closely 

correlated to core body temperatures. All other factors being equal, fatigue is 

most likely, and, when present, most severe, during the WOCL, when body 

temperatures are at their lowest, during a four hour period between the hours 

of 12:00 AM and 6:00 AM. Studies have found that subjects remaining 

awake through the WOCL and into the daytime hours experience 

improvements in performance once past the WOCL, relative to their 

performance during the WOCL.

Amount of recent sleep. If a person has had significantly less than 8 hours of 

sleep in the past 24 hours, he or she is more likely to be fatigued.

Time awake. A person who has been continuously awake more than 17 hours 

since his or her last major sleep period is more likely to be fatigued.

Cumulative sleep debt. Sleep debt refers to the impact of receiving less than a 

full night’s sleep for multiple days. For the average person, cumulative sleep 

debt is the difference between the sleep a person has received over the past 

several days, and the sleep they would have received if they obtained 8 hours 
9

of sleep per night. For example, a person who has received 10 hours of sleep 

over the past 2 nights has a cumulative sleep debt of 6 hours. A person with a 

cumulative sleep debt of more than 8 hours since his or her last full night of 

sleep is more likely to be fatigued. 

Time on task. The longer a person has continuously been doing a job without 

a break, the more likely he or she is to be fatigued.

Individual variation. Different individuals will respond to fatigue factors 

differently. Different individuals may become fatigued at different times, and 

to different degrees of severity, under the same circumstances.

There often is interplay between various factors contributing to fatigue. For 

example, the performance of a person working night and early morning shifts is impacted 

by the time of day. Also, because of difficulty in obtaining normal sleep during other 

than nighttime hours, such a person is more likely to have a cumulative sleep debt or to 

not have obtained a full night’s sleep within the past 24 hours.

2. Fatigue in Aviation

Several aviation-specific work schedule factors1can affect sleep and subsequent 

alertness. These include early start times, extended work periods, insufficient time off 

between work periods, insufficient recovery time off between consecutive work periods, 

amount of work time within a shift or duty period, insufficient time off between work 

periods, number of consecutive work periods, night work through one’s window of 

circadian low, daytime sleep periods, and day-to-night or night-to-day transitions.

 

1

Rosekind, MR. Managing work schedules: an alertness and safety perspective. In: Kryger MH, Roth T, 

Dement WC, editors. Principles and Practice of Sleep Medicine; 2005:682. 
10

3. Preventing and Mitigating Sleep Debt

Scientific research and experimentation has consistently showed that adequate 

sleep sustains performance. For most people, 8 hours of sleep in each 24 hours sustains 

performance indefinitely. Sleep opportunities during the WOCL are preferable, although 

some research suggests the total amount of sleep obtained is more important than the 

timing of sleep within the day. When a person has accumulated a sleep debt, recovery 

sleep is necessary. Recovery sleep requires an opportunity to obtain enough sleep to 

fully restore the person’s ―sleep reservoir.‖ Recovery sleep should include at least one 

physiological night, that is, one sleep period during nighttime hours in the time zone in 

which the individual is acclimated. Recovery sleep does not require additional sleep 

equal to the cumulative sleep debt; that is, an 8-hour sleep debt does not require 8 

additional hours of sleep. However, sleep on recovery days should be extended beyond 

the usual sleep amount. The average person needs over 9 hours of sleep per night to 

recover from a sleep debt.

This analysis looks at the projected costs and benefits of the FAA’s NPRM on 

flight duty and rest requirements for flightcrew members of air carriers in part 121. The 

proposal is primarily based upon the work and discussions within the ARC along with the 

NTSB recommendations. For the detailed discussion of the proposal and the discussion 

of the exact requirements the reader should see the NPRM that is filed in the docket. 
11

Benefits

The scientific community recognizes there is a complex relationship between pilot 

performance and safety risk, and how the performance is impacted by pilot schedules. 

Investigations of pilot work variables have explored how they affect crewmember 

alertness, how alertness affects crew performance under differing workloads and 

operational environments, and how pilot work variables and alertness combine to affect 

safety performance that is measured by accidents and incidents.2 

In 1980, in response to a congressional request, the NASA Ames Research Center 

created a Fatigue/Jet Lag Program to study fatigue. In a Technical Memorandum in 

1995, the Center concluded the average sleep requirement is 8 hours in a 24-hour period.3 

As another example, a study by Rosekind and others states that most humans need about 

eight hours of sleep per night.4 In addition, Battelle Memorial Institute reviewed the 

scientific literature on fatigue in a study for the FAA. This review found that most 

researchers recommend an adult needs an average of 7.5 to 8 hours sleep a day. The 

available scientific literature has identified several symptoms that indicate the presence of 

fatigue, including: increased anxiety, decreased short-term memory, slowed reaction 

time, decreased work efficiency, decreased vigilance, and increased errors. 

 

2

Battelle Memorial Institute, JIL Information Systems, “ An Overview of the Scientific Literature 

Concerning Fatigue, Sleep, and the Circadian Cycle,” January, 1998, prepared for the Office of the Chief 

Scientific and Technical Advisor for Human Factors, Federal Aviation Administration. 

3

Principles and Guidelines for Duty and Rest Scheduling in Commercial Aviation, NASA Technical 

Memorandum, 1995.

4

Rosekind, Neri and Dinges, “From Laboratory to Flightdeck: Promoting Operational Alertness” in Fatigue 

and Duty Limitations—An International Review, (download 1-25-99, 

http/olicas.arc.nasa.gov/Zteam/FCP/subs/raes.html), page 1.
12

Benefit Overview

The approach of this benefits analysis begins with a search of the historical record 

of accidents to establish the extent of the fatigue problem. First, there is some evidence 

that pilots are knowingly flying tired or should know that they are flying tired. Since 

1990, the NTSB has identified five pilot error accidents in which lack of adequate sleep 

was a contributing factor in causing the accident. Second, comparing pilot error 

accidents to length of pilot duty periods indicates that pilot error accidents are more likely 

to occur after long periods on duty. We have calculated the increased accidents occurring 

late in duty periods. Third, if the duty period begins late in day, then pilots might be 

tired even though they are at the beginning of their duty period. We have found accidents 

where this was the case. Fourth, there is also evidence in the accident record where 

chronic fatigue may have been a contributing factor to the accident. Last, the accident 

rate for takeoffs and landings that occur between midnight and 6:00 am is much higher 

than the accident rate for those operations that occur during the day time. We have 

calculated the increased accidents that occur between midnight and 6:00 am. 

 Having projected the possible extent of fatigue based on the historical record, 

we estimate the likelihood of accidents happening in the future using simulation 

techniques. We also use simulation techniques to estimate future casualties, which we 

monetize. In this way, we estimate the potential benefits of the proposed rule.
13

. Finally, we model risk of fatigue for current pilot schedules, and compute the 

number of hours in higher risk categories with and without the rule. The projected 

reduction in fatigue exposure is corroborating evidence supporting this proposal.

Receive Adequate Rest (Sleep) Between Duty Periods 

One of the goals of this rulemaking is to require part 121 operators to provide 

flightcrew members the opportunity to acquire an adequate rest before the start of their 

flight duty period. In the past 20 years, there have been at least five accidents where the 

flightcrew members did not have an adequate amount of sleep prior to the start of their 

flight duty period.

The first accident in the 20-year analysis period occurred at Pine Bluff, AR at 

3:55 PM on April 29, 1993. An Embraer EMB120 RT, Brasilia, N24706, (operated by 

Continental Express, Inc.) was substantially damaged when it collided with rough terrain 

during an overrun following a forced landing. The forced landing was executed 

following a stall and loss of control at 17,412 feet during climb. After regaining control 

of the airplane the flightcrew noticed that the left engine nacelle was damaged and that 

three propeller blades were missing. The airplane was unable to maintain level flight. 

After the flightcrew landed the airplane, it hydroplaned off the wet runway. The airplane 

was substantially damaged as a result of overrunning the runway. There were three 

crewmembers and 27 passengers on board the airplane. The flight attendant and 12 

passengers received minor injuries; the others were uninjured. The NTSB determined 

that pilot error was the cause of the accident.
14

Contributing to the accident was fatigue induced by the flightcrew’s failure to 

properly manage their provided rest periods. The flightcrew got off duty at 11:30 AM the 

day before the accident. The captain went to bed between midnight and 12:30 AM and 

awoke about 5:00 AM (receiving only 4 1⁄2 to 5 hours sleep) for a departure at 6:30 AM. 

The first officer went to bed between 11:00 PM and midnight and woke up about 4:30 

AM (receiving between 5 and 5 1/2 hours sleep). Both pilots claimed they felt well 

rested prior to starting their flight duty for that day. The accident flight occurred during 

the seventh and last flight of the day.

The second accident occurred at 10:27 PM on February 16, 1995 at Kansas City, 

MO. A Douglas DC-8-63, N782AL, operated by Air Transport International (ATI), was 

destroyed by ground impact and fire. The accident occurred during a three-engine 

takeoff for a ferry flight under Part 91. Three crew members were fatally injured. The 

NTSB determined that the accident was due to pilot error. 

In addition to being inadequately trained, the flightcrew was suffering from 

fatigue as a result of limited opportunities for rest, disruption of their circadian rhythms, 

and lack of sleep in the days prior to the accident. Before their assignment to the accident 

trip, the flightcrew had completed a demanding round-trip to Europe. The flights crossed 

multiple time zones (12 in all) in a short period of time. The Dover-Ramstein-GanderDover legs were flown at night following daytime rest periods, which disrupted the 

flightcrew’s circadian rhythms. On the day of the accident, the flightcrew had checked 

into a hotel in Dover, DE, at 2:40 AM EST. The captain placed a short call from his 

room at 3:14 AM. At 8:02 AM (receiving not quite 5 hours sleep), he called home and 
15

spoke to his wife for 25 minutes. ATI Scheduling called the captain at 10:30 AM. There 

were other calls between ATI and the captain throughout the day (10:45 AM, 12:44 PM, 

2:00 PM, and 2:10 PM). The flightcrew departed Dover at 3:18 PM EST and arrived at 

Kansas City at 5:39 PM CST.

The flightcrew was required to take a 16 hour rest period before they could be 

assigned any additional part 121 duties. However, there are no flight time limits or rest 

requirements for Part 91 ferry flights that follow Part 121 revenue flights. So 12 hours 

after checking into a hotel at Dover, the flightcrew checked out to assume duty under Part 

91 ferry flight rules.

The third accident in the 20-year analysis period occurred on May 8, 1999 at 7:01 

AM EST. A Saab-Scania AB (Saab), N232AE, operated by American Eagle Airlines, 

INC., overran the runway at John F Kennedy International Airport, Jamaica, NY. The 

captain conducted an ILS approach with excessive altitude, airspeed, and rate of descent, 

while remaining above the glide slope. The airplane landed 7,000 feet beyond the 

approach end of the runway, at excessive speed (157 knots), and overran the runway. 

One passenger was seriously injured while exiting the airplane, the other passengers and 

crewmembers were uninjured. The airplane was substantial damaged by the accident.

The NTSB determined that pilot error caused the accident. During the post 

accident interviews, both pilots stated that they were fatigued. The flightcrew was 

working a continuous duty overnight schedule. The previous day, they both woke up 

during the morning, did not sleep during the day, and reported for duty at 11:00 PM for a 
16

flight scheduled at 11:46 PM. The day before the accident, the flight was delayed and 

arrived at BWI around 1:00 AM. They got to sleep around 1:30 AM and awoke at 4:45 

AM for the accident flight, which was scheduled to depart at 6:10 AM.

The fourth accident occurred at Tallahassee, FL on July 26, 2002 at 5:37 AM 

EST. A Boeing 727-23F, N497FE, operated by Federal Express (FedEx) struck some 

trees and landed short of the runway. All three flightcrew members were seriously 

injured. The airplane was destroyed by impact and the resulting fire. The NTSB 

determined that the accident was caused by pilot error. Both the captain and the first 

officer were fatigued at the time of the accident. The captain had only 3 1⁄2 hours of sleep 

prior to the accident. He had disturbed, interrupted sleep on the two previous nights. The 

first officer, who was on reserve duty, reported that he was having difficulty adjusting his 

sleep cycle to the reserve-duty schedule. His reserve-duty schedule caused him to 

frequently change his sleep pattern between sleeping during daytime hours and night 

hours. He had approximately 5 to 6 hours sleep before reporting for duty. The flight 

engineer had received about 6 1⁄2 hours sleep before he began his duty and had taken two 

naps (30 minutes on a commute to Memphis, TN, and 30 to 60 minutes at FedEx’s crew 

rest facility at Memphis airport).

The fifth accident occurred at 3:06 PM EST on February 18, 2007 at Cleveland, 

Ohio. An Embraer ERJ-170, N862RW, operated by Shuttle America, Inc. as Delta 

Connection flight 6448, landed during snow conditions and overran the end of the 

runway. Three passengers received minor injuries; the remaining 68 passengers and 4 
17

crew members were uninjured. The NTSB determined that the accident was caused by 

pilot error. Contributing to the accident was the captain’s fatigue.

On the day of the accident the captain had received only 45 minutes to an hour of 

sleep. The captain had reported that he was too tired to fly on July 30, 2006. The Shuttle 

America chief pilot and ERJ-170 program manager told him fatigue calls made outside 

duty times would result in an unavailable attendance mark. On January 16, 2007 Shuttle 

America notified the pilot in writing that his attendance had reached an unacceptable 

level – nine absences occurrences (seven sick and two unavailable attendance marks) 

totaling 18 days within the previous 12 months – and that future occurrences would result 

in corrective action, which could include termination from the company. According to

company policy eight absence occurrences would result in termination. Since the captain 

had not received any previous notification from Shuttle America about his attendance 

record he had not yet been terminated. The captain stated that he did not cancel his trip 

due to fatigue because he thought he would be fired.

In the five accidents discussed above, the captains (and sometimes the other 

flightcrew members) were operating their airplanes while they were fatigued and they 

knew that they were fatigued (or should have known that that they were fatigued). The 

new requirements of this rulemaking, including increased training, would prevent these 

accidents from happening in the future.
18

Duty Time Limits

In analyzing this rulemaking action, the FAA conducted an assessment of the 

risks of pilot work practices and the risk of a part 121 accident.5 Human factors-related 

accidents from the 1990 to 2009 time period were identified that involved, at a minimum, 

substantial damage to the aircraft or serious injuries to those on-board. All turbulencerelated accidents were excluded, as were accidents that did not have a 72-hour history of 

pilot activities before the accident. There were 43 accidents where the needed data were 

available (sometimes slightly more or fewer than 43 accidents depending on the 

schedule-related risk factor of interest). The FAA believes that these accidents are 

representative of all the major human factor-caused accidents that occurred during the 

period, including all accidents where fatigue was a factor.

As part of the analysis for this rulemaking, the FAA obtained data on pilot work 

patterns from six carriers covering two months of actual flight activity during 2009. The 

six carriers that provided flight crew duty schedule data included three large legacy 

passenger carriers that conduct both international and domestic operations (one of which 

includes elements of a low cost domestic carrier and two large cargo carriers that conduct 

both international and domestic air cargo services. For the following analysis, these data 

were used to create profiles of the work patterns of the pilots from these six airlines. The 

data were converted (for each month) into one record for each pilot with a line of actual 

flying for one or both of the months. Each pilot record tracked a pilot’s activity for every 

 

5

GRA, Incorporated, “Flight and Rest Time Safety and Cost Analyses (Phase 3),” October 30, 2000, 

prepared for FAA, Office of Aviation Policy and Plans under Work Order No. 1, Contract No. DTFA01-98-C00096.
19

hour in the entire month that the pilot was on duty. The beginning and end of each trip 

segment were recorded for each pilot and put into a database. Parameters of interest were 

then calculated such as the length of duty periods, the day within a duty trip on which 

duty hours take place and the numbers of takeoffs and landings within a duty period. The 

analysis tracked these activities in base time (defined as the time at the location where the 

pilot began a multi-day trip, which is often the pilot’s crew base). The analyses provide 

support for regulatory proposals to govern duty time.6 Specifically, it was found that the 

 

6

It is important to note that pilots are only at risk of suffering an air accident during those duty 

hours when they are actually operating an aircraft. Therefore, the first hour of a pilot’s duty day 

– spent (as indicated by industry practice and the data provided by carriers for this analysis) 

engaged in ground activities such as check in, flight and schedule information acquisition and 

pre-departure inspections of aircraft – does not represent duty time “at risk” of an air accident. 

Similarly, once each pilot has concluded the first flight segment of his or her duty day, some 

percentage of the pilot’s duty time is spent on the ground between actual flight segments. This 

time spent on duty but on the ground is also duty time that is not “at risk” of an air accident. 

After adjusting for the first duty hour, about 75 percent of pilot duty hours are spent operating 

an aircraft and thus “at risk” of an air accident. For the statistical analyses presented below, the 

pilot duty time data has been adjusted to reflect this. Adjustments are done on the reported 

pilot duty data in the following way. 

The first hour of the pilot duty day is excluded, since it is not an hour of duty “at risk” of 

an air accident

After this first hour each pilot begins his or her first flight segment of the day. The 

length of this first flight segment varies from pilot to pilot, depending on the day’s 

itinerary. Therefore the second duty hour of each pilot’s duty period is treated as if it is 

an “at risk” duty hour for each pilot, so the total number of second duty hours is not 

adjusted in any way.

During the third through eighth duty hours, some pilots are at times on the ground 

between segments (and thus are not “at risk”), some have resumed flying their second, 

third, fourth or greater flight segment of the day (and are therefore “at risk”), some 

continue to fly throughout a long first flight segment of the day (and are therefore “at 

risk”), and so forth. Over these hours of the duty period, individual pilots spend some 

duty time on the ground and not “at risk” and the remainder of the duty time operating 

an aircraft and therefore “at risk.” It is not possible to capture the actual variability in 
20

proportion of accidents is higher for more lengthy duty periods than is the proportion of 

lengthy duty periods in the pilot sample. This is illustrated in Table 1 where about 6 

percent of pilot duty hours are in the 11th or greater hour of a duty period while 16 

percent of accidents that occur happen in the 11th or greater hour of the pilot’s duty 

period. Similarly, nine percent of the accidents occur when a pilot has been on duty for 

13 or more hours whereas just a little over one percent of pilot duty hours occur during 

that time. This analysis points to increased accident risk with increased duty time, even 

though pilot scheduling was not cited as a factor in all 43 accidents.

This analysis is also consistent with a study of pilot deviations by duty time 

within the past 24-hours (see Appendix A). In this study the portion of pilot deviations 

was greater than the exposure portion when duty time exceeded 6 hours during the past 

24-hours. These findings and the analysis above suggest that more stringent limits on 

pilot duty time would be appropriate.7

 

the pilot duty data, so for the third, fourth, fifth, sixth, seventh and eighth duty hours, 

the reported duty hour counts are reduced by 30 percent to account for this 

“sometimes ‘at risk,’ sometimes not ‘at risk’” nature of this portion of the duty day. (This 

30 percent adjustment factor for those hours of the duty period exceeds the observed 

25 percent difference between flight time and duty time because no adjustment is 

made to the duty hours observed in the final hours of pilot duty periods.)

For the ninth and greater duty hours in the pilot duty day, it is assumed that all pilots 

still on duty have commenced and are completing their final flight segment of the day, 

and are therefore “at risk” of an air accident during these duty hours.

The adjusted exposure data set is reported in Table 1 and is used for calculations reported in Table 2.

7

It also should be noted that many union contracts today require periods of flight time, duty time, and 

rest time which are more stringent than the requirements established by the existing, and in some cases 

the proposed, Federal Aviation Regulations. However, our analysis is based on a mix of carriers including 

those with more stringent contracts.
21

Table 1: Captain Duty Hours and Accidents by Hour in Duty Period

Hour in 

Duty 

Period

Captains' 

Hours

Exposure 

Percentage Accidents Accident Percentage

Accident Proportion 

Relative Exposure 

Proportion

2

nd 192,786 19% 7 16% 0.88

3

rd

– 4th 310,045 30% 8 19% 0.62

5

th

– 6th 211,474 20% 6 14% 0.69

7

th

– 8

th 152,671 15% 11 26% 1.74

9

th

– 10th 108,084 10% 4 9% 0.89

11th– 12th 53,611 5% 3 7% 1.40

13th– 14th 10,010 1% 1 2% 2.33

15th + 1,003 <1% 3 7% 72.32

Total 1,039,684 43

It is possible to estimate the number of accidents that could have been avoided by 

limiting the duty time of pilots using the information in Table 2. If fatigue was not a 

contributing factor in the 36 accidents that occurred during one of the first ten hours of 

pilot duty, then the relationship between the exposure data compiled for captains and the 

―normal‖ frequency of occurrence of serious accidents can be estimated as 3.69 accidents 

per 100,000 hours of duty time. 8 There were 53,611 hours of duty in the exposure data 

set that occurred during the 11th and 12th duty hour of a pilot’s duty period; and based on 

 

8

To calculate the factor for accidents per 100,000 hours of exposure data, the total number of duty hours 

in the exposure data in the tenth hour of a duty period and earlier is calculated, as [(192,786 + 310,045 + 

211,474 + 152,671 + 108,084) = 975,060 duty hours] . Of the accidents, 36 occurred while the pilot was in 

the tenth or earlier hour of a duty period. This accident number of 36 divided by the exposure total of 

975,060 hours results in an accidents-per-100,000 exposure hours ratio of 3.69.
22

the calculated frequency relationship (3.69 accidents per 100,000 hours of duty time) 

1.98 accidents would be expected to occur, and three accidents did occur during those 

hours of a pilot’s duty period. In the 13th and 14th duty hour there were only 10,010 hours 

of duty. The expected number of accidents at the above rate would be 0.4 for that time 

period, while one accident occurred involving a pilot in that range of the duty period 

length. Since there were only 1,003 hours of duty occurring in the 15th and greater hours 

of duty, only 0.1 accidents would be expected during those hours of the duty period. In 

the dataset there are three accidents involving a pilot with a duty period of this length.

Table 2 shows the projected number of accidents estimated in this way in comparison with the actual 

number of accidents. The difference between the actual number of accidents and the projected number of 

accidents would be the number of accidents that may be avoided for that time in duty period category. For 

example, in the 11th and 12th hour, there were three accidents,9and 1.98 was projected to occur; so there is 

a difference of 1.02 accidents. Similarly, in the 13th and 14th hour, there was one accident,10 while only 0.4 

were projected to occur; the difference (or possible number of accidents avoided) is 0.6 accidents. Finally, 

in the 15th and greater hours of duty, there were three accidents,11 while only 0.1 were projected to occur 

based on the distribution of duty hours; the difference (or possible number of accidents avoided) is 2.9 

accidents. 

 

9

 Hyannis, MA (1/23/99), Oshawa, Canada (12/16/2004 and Laramie, WY (2/18/07).

10

 Little Rock, AR (6/1/99).

11 Guantanomo Bay (8/18/93), Kirksville, MO (10/19/04), and Traverse City, MI (4/12/07).
23

Table 2: Projected Number of Accidents Avoided by Limiting Duty Time

Hour in 

Duty 

Period

Projected 

Number of 

Accidents

Actual 

Number 

of 

Accidents

Possible 

Accidents 

Avoided

2

nd 7.12 7

3

rd

– 4th 11.45 8

5

th

– 6th 7.81 6

7

th

– 8

th 5.64 11

9

th

– 10th 3.99 4

11th– 12th 1.98 3 1.02

13th– 14th 0.37 1 0.63

15th + 0.04 3 2.96

Total 36.4 43 4.61

A rule that limits duty time to 14 hours could avoid 2.96 accidents. If the limit on 

duty time were set at 12 hours, then 3.6 accidents could be avoided. If the limit on duty 

time were set at 10 hours, then 4.6 accidents could be avoided.

In Appendix B, two methods were used to test the statistical significance of the 

relationship between length of duty time and accidents. Both tests showed that the 

relationship was statistically significant. The FAA requests comments on the content of 

Appendix B.

Since 1990, there have been seven serious accidents where pilot fatigue due to a 

long duty period was a contributing factor. These accidents resulted in 24 fatalities to 

passengers and crew members, 52 serious injuries to passengers and crew members, and 
24

65 minor injuries to passengers and crew members. There were also 76 passengers and 

crew members in these seven accidents who were not injured.

The first accident occurred on August 18, 1993, when a Douglas DC-8-61 

freighter operated by American International Airways collided with level terrain short of 

the runway at Leeward Point Airfield, Guantanamo. The accident happened at 1656 EDT 

when the pilot lost control of the airplane while on approach. All three crew members 

were seriously injured and the airplane was destroyed. The NTSB determined that pilot 

error was the probable cause of the accident and that pilot fatigue was a contributing 

factor.

This is the first Part 121 accident where NTSB cited pilot fatigue as a contributing 

factor. At the time of the accident, the flight crew had been on duty for about 18 hours. 

On the day of the accident, the captain had been awake for over 23 hours with only five 

hours of sleep prior to waking up. The first officer had been awake 19 hours with 8 hours 

of sleep, and the flight engineer had been awake 21 hours with 6 hours of sleep. The day 

before the accident, the captain and first office had only two hours of sleep prior to being 

awake for over 17 hours.

The second accident occurred on January 22, 1999, when a Beech 1900D 

operated by Colgan Air, Inc. was substantially damaged while landing at Barnstable 

Airport, Hyannis, MA. The accident happened at 1719 EST. There were no injuries to 

the two crew members and the two passengers. The NTSB determined that pilot error 
25

was the probable cause. On the day of the accident the captain had reported for duty at 

535 EST. At the time of the accident the captain had been on duty almost 12 hours.

The third accident occurred on June 1, 1999, when a McDonnell Douglas DC- 9-

82 (MD-82) operated by American Airlines crashed after it overran the end of runway 

during a landing at Little Rock National Airport, Little Rock, AR. The accident 

happened at 2350 CDT. At the time of the accident there were thunderstorms in the 

airport area and the runway was wet. The captain and 10 passengers were fatally injured; 

four crew members and 41 passengers were seriously injured, one crew member and 64 

passengers received minor injuries; and 24 passengers were uninjured. The airplane was 

destroyed by impact and a postcrash fire. The NTSB determined that pilot error was the 

probable cause and that fatigue was a contributing factor.

On the day of the accident, the captain awoke at 715 and reported for duty at 

1038. At the time of the accident he had been awake for over 16 hours and had been on 

duty for over 13 hours. The first officer had also been awake for over 16 hours and on 

duty for over 13 hours.

The fourth accident occurred on October 19, 2004, when a BAE-J3201 operated 

by Corporate Airlines as an American Connection struck some trees on final approach to 

Kirksville Regional Airport, Kirksville, MO and crashed short of the runway. The 

accident occurred at 1937 CDT. The crew and 11 passengers were fatally injured and 

two passengers received serious injuries. The airplane was destroyed by impact and post 
26

crash fire. The NTSB determined that pilot error was the probable cause of this accident 

and that fatigue was a contributing factor.

On the day of the accident, the pilots were flying their sixth flight of the day and 

had flown 6 hours and 14 minutes when the accident occurred. They had also been on 

duty for 14 hours and 31 minutes at the time of the accident. The night before the 

accident, the captain had not slept well and awoke with a headache, according to his 

fiancée who talked with him during the morning by telephone.

The fifth accident occurred on December 16, 2004, when a Short Brothers SD3-

60 aircraft operated by Air Cargo Carriers, Inc. as a chartered cargo flight attempted a 

landing at the Oshawa Municipal Airport, Oshawa, Canada. The crew rejected the 

landing after noticing poor breaking action and tried to conduct a go-around. After 

becoming airborne the aircraft crashed after striking the airport boundary fence. The 

accident happened about 2000 EST. The two pilots received serious injuries and the 

aircraft was substantially damaged. The Transportation Safety Board of Canada 

determined that pilot error was the probable cause of the accident.

The captain of the aircraft had been awake for 13 hours and had been performing 

duties as a flight crewmember for 10 hours before the accident. The captain was flying 

the aircraft at the time of the accident. The first officer had been awake for 12 hours and 

had been performing the duties as a flight crewmember for nine hours.

The sixth accident occurred on April 12, 2007, when a Bombardier/Canadair 

Regional Jet (CRJ) CL600-2B19 operated by Pinnacle Airlines ran off the departure end 
27

of runway 28 after landing at Cherry Capital Airport, Traverse City, MI. The accident 

occurred at 0043 EDT. There were no injuries, but the airplane was substantially 

damaged. The NTSB determined that pilot error was the probable cause of the accident 

and that fatigue was a contributing factor.

On April 11, the captain awoke about 0700 CDT and ate breakfast at the hotel. 

Both the captain and first officer left the hotel at 0800 CDT taking a shuttle to the airport. 

Both started their duty day at 0900 CDT on April 11, 2007. At the time of the accident 

both crew members had been on duty for 15 hours and 43 minutes (and the captain had 

been awake for over 17 hours.

The seventh accident occurred on June 20, 2007, when a Beech 1900D operated 

by Great Lakes Air ran off the runway after landing at Laramie Regional Airport, 

Laramie, WY. The accident occurred at 1620 MDT. There were no injuries, but the 

aircraft was substantially damaged. The NTSB determined that pilot error was the 

probable cause of the accident.

On the day of the accident, the captain and first officer were on the third day of a 

three day trip. The crew started their duty period at 0520 MDT. At the time of the 

accident, they had been on duty for 11 hours.

These seven accidents resulted in 24 fatalities to passengers and crew members, 

52 serious injuries to passengers and crew members, and 65 minor injuries to passengers 

and crew members. There were also 76 passengers and crew members in these seven 

accidents who were not injured.
28

Time Awake

While being on duty a long time can be fatiguing, simply being awake a long time 

(approximately 17 hours or more) can also be fatiguing. In some accidents, the pilots had 

been on duty less than 10 hours, but those hours occurred late in the day and one or more 

of the flight crewmembers had been awake close to 17 hours or more. In the three 

accidents described below, statements of probable cause indicated crew performance but 

in each case one or more of the flight crewmembers had been awake a long time. These 

three accidents resulted in 245 fatalities on board the airplane and one fatality on the 

ground. There were also 20 seriously injured passenger and crew members, and three 

crew members and a passenger that received minor injuries.

The first accident occurred on July 2, 1994, when a DC-9-31 airplane operated by 

USAir, Inc. collided with tree and a private residence near Charotte/Douglas International 

Airport. This accident occurred at about 1843 EDT shortly after the flightcrew executed 

a missed ILS approach. There were 37 passenger fatalities, 16 passenger and crew 

received serious injuries, and 4 crew and a passenger received minor injuries. The 

airplane was destroyed by impact and a postcrash fire. The NTSB determined that pilot 

error was the probable cause of the accident.

Fatigue likely affected the performance of the first officer, who was the pilotflying on the accident leg. The captain, who was off-duty the preceding 3 days, was less 

vulnerable to fatigue, but he too had already had a long day. The accident occurred 14 
29

hours into the captain’s day. He had risen at 0455, drove to Dayton from his home, then 

flew to Pittsburgh to begin his duty day. The accident occurred at 1843, at the end of the 

third of 4 scheduled legs. 

The first officer was more vulnerable to fatigue. He was on a four-day trip. On

July 30, he ended his duty day at Tri-City Regional Airport, Biountville, Tennessee, 

where he had arrived at 2230. The NTSB report does not state when that duty day began, 

nor when the first officer awoke that day. However, after having a light meal, he went to 

bed at 0130. On July 1, he awoke at 0900. His duty day ended July 1 in Saint Louis at 

2040 EDT. He went to bed at 2230 and awoke at 0615 on the accident day. He reported 

for duty at St. Louis for a flight to Pittsburgh. That flight, with the first officer as the 

pilot flying, departed at 0810. At Pittsburgh, the first officer joined the captain and they 

began their pairing. Like the captain, the first officer was nearly 14 hours into his day 

when the accident occurred. He was the pilot flying on the PIT-LGA leg and on the 

accident flight from CAE. 

The second accident occurred on December 20, 1995, when a Boeing 757-223 

operated by American Airlines crashed into mountainous terrain while on descent from 

cruise altitude in an attempt to land at Alfonso Bonilla Aragon International Airport in 

Cali, Columbia. The accident occurred at 2142 EST. There were 160 passenger and 

crew fatalities; only four passengers survived the accident with serious injuries. The 

airplane was destroyed by impact. The Aeronautica Civil of the Republic of Columbia 

determined that the probable cause was pilot error. 
30

The accident flight was the first flight for both pilots after several days off. The 

captain arose at 0500 after a bit more than 7 hours of sleep. The first officer awoke at 

0700. Both pilots appeared well rested. Both pilots reported to the operations manager at 

Miami more than an hour before their scheduled departure time of 1640. However, 

departure from the gate was delayed until 1714, followed by a lengthy ground delay due 

to ramp congestion. 

It is reasonable to assume that the crew would have been tired at the time of the 

accident, despite this flight’s being the first of their duty tour. The captain had been 

awake close to 17 hours, while the first officer had been awake 15 hours.

The third accident occurred on February 12, 2009, when a Bombardier DHC-8-

400 operated by Colgan Air, Inc. as a Continental Connection flight crashed into a 

residence in Clarence Center, NY while on approach to Buffalo-Niagara International 

Airport, Buffalo, NY. The accident occurred at 2217 EST. The crew and passengers (49 

people) were all killed and one person on the ground was also killed. The airplane was 

destroyed by impact and a postcrash fire. The NTSB identified probable cause and 

contributing factors as follows:

Both pilots performance was likely to have been impaired due to fatigue. Both 

pilots were based at Newark and both commuted. The captain lived near Tampa, FL and 

the first officer lived near Seattle, WA. Neither had a ―crash pad‖ in Newark and both 

regularly used the crew room for sleeping. The captain often tried to bid trips that would 

ensure some nights in hotels at out-stations. In Newark, he sometimes stayed with a 
31

friend but usually slept in the crew room. The first officer always slept in the crew room 

when in Newark and told several people she had no need for a crash pad because ―one of 

the sofas in the crew room has my name on it.‖

The duty tour began on February 10 for the recently upgraded captain. He 

commuted to EWR on February 9 from his home near Tampa, arriving at EWR at 2005. 

He apparently spent the night in the crew room. Multiple phone records and log-ins to 

the company’s crew tracking system indicate he got little sleep before reporting for duty 

at 0530 on February 10. The captain then flew 3 flights and arrived at BUF at 1300. He 

spent the rest of the day in a hotel. On February 11, he left the hotel at 0515 to report for 

duty at 0615. Again the captain flew 3 flights and terminated his duty day at EWR at 

1544. He apparently spent the rest of the day and that night in the crew room, where he 

was seen sleeping at 0630 on February 12, the day of the accident. Again, however, 

multiple phone records, log-ins to the crew tracking system, and contact with other 

employees indicate he got very limited sleep before reporting for duty at 1300.

The first officer commuted to EWR from SEA the day before the accident. She 

awoke on February 11 at 0900 and arrived at the airport at 1730 for a FedEx flight to 

MEM. The aircraft arrived in MEM at 0230 EST (2230 PST). She was said to have had 

about 90 minutes of sleep on the flight. She then took another flight to EWR, departing 

MEM at 0418 and arriving at EWR at 0623. She apparently slept for much of that twohour flight. Upon reaching EWR, she spent the day in crew room, where she was seen 

napping. However, multiple phone records and log-ins to the company’s crew tracking 

system indicate she got little sleep before reporting for duty at 1300.
32

The NTSB did not cite fatigue as a cause or as a factor. However, in its findings 

and conclusions, NTSB noted that the performance of both pilots ―was likely impaired 

because of fatigue, but the extent of their impairment and the degree to which it 

contributed to the performance deficiencies that occurred during the flight cannot be 

conclusively determined.‖ 

NTSB added that both pilots failed to manage their off-duty time and commute 

responsibly and both failed to ensure that they remained ―fit for duty.‖

The Captain was near the end of his fourth day since awakening on February 9. 

He had the opportunity for quality sleep only on the night of February 10, and that was 

cut short with a departure from the hotel at 0515 the next morning. Both pilots 

essentially stayed up all night on February 11, with no opportunities for deep sleep, and 

then found themselves operating a late-night flight after a day of cancellations and delays.

These three accidents resulted in 245 fatalities on board the airplane and one 

fatality on the ground. There were also 20 seriously injured passenger and crew 

members, and three crew members and a passenger that received minor injuries. 

Chronic Fatigue

Chronic fatigue can happen to a flight crewmember, if his or her duty periods 

covers several days of night flying, or several days of multiple time zone changes, or 

several days with a heavy schedule. Chronic fatigue could be a contributing factor to 

accidents where pilot error was the probable cause of the accident. In the two accidents 
33

described below, the NTSB determined that pilot error was the probable cause, but in 

each case one or more of the flight crewmembers was subject to chronic fatigue. These 

two accidents resulted in two passengers who were seriously injured, and 38 crew 

members and a passenger who received minor injuries.

The first accident occurred on April 14, 1993, when a DC-10-30 operated by 

American Airlines overran runway 17L following a landing at Dallas/Fort Worth 

International Airport. The accident happened at 0659 CDT. It was raining at the time of 

the accident and there were numerous thunderstorms in the airport area. The airplane 

sustained substantial damage. There were no fatalities, but two passengers received 

serious injuries, and 38 passengers and crew members received minor injuries. The 

NTSB determined that the probable cause was ―the failure of the captain to use proper 

directional control techniques to maintain the airplane on the runway.‖ 

Though the accident occurred just 46 hours into the crew’s duty tour, the crew 

was completing its second consecutive day of disrupted circadian rhythms. The crew 

likely had awoken no later than 0600 CDT in order to reach DFW and report for duty in 

advance of their first flight at 0900 from DFW to Honolulu (HNL). After a 10-hour duty 

day, the crew arrived at HNL at about 1900 CDT (1400 HAST) and began their sleep 

period around 2200 HAST, awakening around 0700 HAST, with additional naps of 

various lengths from 1600 to 2100 Local. Then the crew reported for duty and flew for 

more than 8 hours through the night to DFW. 
34

The first officer told investigators that he felt tired twice during the flight and 

briefly used oxygen to ―perk-up.‖ The captain and the flight engineer said they did not 

feel tired during the flight, but the literature on sleep indicates that people often fail to 

recognize when their performance deteriorates due to fatigue and disrupted circadian 

rhythms. 

The second accident occurred on August 25, 1996, when a Lockheed L-1011-100 

operated by Trans World Airlines was substantially damaged when the tail struck the 

runway while landing at John F. Kennedy International Airport. The accident occurred at 

0710 EDT. None of the crew or passengers were injured. The NTSB determined the 

probable cause of the accident was pilot error.

Pilot fatigue was also a probable contributing factor in this accident. The crew’s 

trip sequence began with an evening flight on August 23 from JFK to Las Vegas (LAS). 

The NTSB report is unclear about the time the crew arrived in LAS, but they appear to 

have reached their hotel around 2200 local time (0100 EDT), at which time the crew 

started a 24-hour rest period. The crew’s itinerary resumed at 2130 (PDT) the next night 

when they were picked up at the hotel. The crew therefore would have been awake at 

least since about 2000 (2300 EDT). Though the crew had an ostensibly adequate rest 

period, they had arrived at their hotel late on the preceding night and were resuming their 

itinerary on the back side of the clock for a 5-hour red-eye to New York.

These two accidents resulted in two passengers who were seriously injured, and 

38 crew members and a passenger who received minor injuries.
35

Late Night Duty Fatigue

Aviation accidents can also be examined how they vary through out the day. As 

can be seen in Table 3 showing the 43 accidents in our analysis by time of day, accidents 

are more likely to occur in the late afternoon and early evening (4:00 pm to 8:00 pm) than 

any other time of the day. During the rest of the day accidents are spread out fairly 

evenly among the four-hour categories. Throughout most of the day there is a close 

relationship between the percentage of accidents that occurred during each four-hour 

period and the percentage of operations that occurred during the same four-hour period. 

However, between midnight and 4:00 AM, the percentage of accidents (14%) greatly 

exceed the percentage of operations (3%). 

Table 3 Accidents by Time of Day

Time Period

Number 

of 

Human 

Factors

Accidents

Percentage 

of Human 

Factors 

Accidents 

Number of 

Operations

Percentage 

of 

Operations

mid to 4 6 14.0% 708,610 3.0%

4 to 8 6 14.0% 2,535,742 10.8%

8 to noon 7 16.3% 5,383,139 22.8%

noon to 4pm 6 14.0% 5,557,144 23.6%

4 to 8pm 11 25.6% 5,746,663 24.4%

8 to mid 7 16.3% 3,649,924 15.5%

 43 23,581,222 

This analysis is also consistent with a study of pilot deviations by time-of-day 

(see Appendix C). In this study the portion of pilot deviations was greater than the 

exposure portion between midnight and 4:00 am. Both this study and the above analysis 
36

suggest that should be regulated to reduce the number of pilot error accidents where pilot 

fatigue was a contributing factor.

It is possible to estimate the number of accidents that could have been avoided by 

regulating operations during the window of circadian low between 12:00 midnight and 

4:00 am using the information in Table 3. If fatigue was not a contributing factor in the 

13 accidents that occurred between 8:00 am and 4:00 pm, then the relationship between 

the exposure data compiled for captains and the ―normal‖ frequency of occurrence of 

serious accidents can be estimated as 1.19 accidents per million operations. There were 

708,610 operations between midnight and 4:00 am; and based on the calculated 

frequency relationship (1.19 accidents per million operations) 0.8 accidents would be 

expected to occur, and six accidents occurred during those hours. Between 4:00 am and 

8:00 am there were 2.536 million operations. The expected number of accidents at the 

above rate would be 3.0 accidents during those hours, but there were six accidents. The 

excess accidents that occur in the late afternoon and evening have already been taken into 

account the earlier discussion in the sections preceding this section.

Table 4 shows the projected number of accidents estimated in this way in 

comparison with the actual number of accidents. The difference between the actual 

number of accidents and the projected number of accidents would be the number of 

accidents that may be avoided by regulating operations during those hours. For example, 

between midnight and 4:00 am, there were six accidents,12 and 0.8 were projected to 

 

12

 Cleveland, OH (2/17/1991), Swanton, OH (2/15/1992), East Garnby, CT (11/12/1995), Newark, NJ 

(7/31/1997), Florence, KY (8/13/2004) and Traverse City (4/12/2007).
37

occur; so there is a difference of 5.2 accidents. Similarly, between 4:00 am and 8:00 am, 

there were six accidents,13 while 3.0 were projected to occur; the difference (or possible 

number of accidents avoided) is 2.98 accidents. 

Table 4 

Hour of Day Accidents

Projected 

Accidents Difference

mid to 4 6 0.8 5.2

4 to 8 6 3.0 3.0

8 to noon 7 6.4

noon to 4pm 6 6.6

4 to 8pm 11 6.8

8 to mid 7 4.3

 43 

A rule that regulated operations during the period of circadian low between 

midnight and 4:00 am could avoid 5.2 accidents. If the time was extended to 6:00 am, 

then possibly 3.0 accidents could be avoided. As it turns out, one of the accidents that 

occurred between midnight and 4:00 am, Traverse City (4/12/2007), has already been 

accounted for in the above analysis of length of duty time accidents, so it will not be 

claimed in this analysis. Concerning the time between 4:00 am and 8:00 am, only one of 

the six accidents occurred when the window of circadian low was possible (between 4:00 

am and 6:00 am). That accident happened at Tallahassee (7/26/2002), and it also was 

discussed above. None of the accidents between 4:00 am and 8:00 am will be claimed in 

this analysis.

 

13

 Dallas/Ft Worth (4/14/1993), Nashville, TN (7/08/1996), Jamaica, NY (8/25/1996), Jamaica, NY 

(5/8/1999), Tallahassee, FL (7/26/2002), and Lexington, KY (8/27/2006) .
38

Operating an aircraft during the window of circadian low can be fatiguing. The 

five accidents described below all occurred between midnight and 6:00 am. These five 

accidents resulted in seven fatalities. There were also 7 minor injuries passengers and 

crew members, and 77 crew members and a passenger that received minor injuries.

The first accident occurred on February 17, 1991, when a McDonnell Douglas 

DC-9-15 freighter operated by Ryan International Airlines flew through weather 

conducive to airframe ice contaminations 40 minutes prior to descending toward 

Cleveland, OH. During the 35 minute turnaround at Cleveland, the crew did not exit the 

airplane to conduct a preflight inspection of the airplane even though it was snowing at 

the time. The airplane stalled on the takeoff and crashed. The accident happened at 00:19 

EST. Both flight crewmembers were fatally injured. The NTSB determined that pilot 

error was the probable cause of the accident. 

The second accident occurred February 15, 1992, when a Douglas DC-8-63 

operated by Air Transport International crashed on approach to the airport at Toledo, OH. 

The first officer had attempted two ILS approaches but failed to capture the ILS localizer 

and/or glideslope. During the second approach the captain assumed control of the 

airplane. The captain apparently became spatially disoriented and failed to properly 

recognize and recover from an unusual aircraft attitude. The second officer assumed 

control of the aircraft but was unable to recover the airplane before it crashed. The 

accident occurred at 3:27 EST. The captain, first officer, and two other people were 

fatally injured. The NTSB determined that pilot error was the probable cause of the 

accident.
39

The third accident occurred on November 12, 1995, when a McDonnell Douglas 

MD-83 operated by American Airlines, Inc. struck some trees and then an ILS antenna as 

it landed short of the runway on approach to Bradley International Airport, Windsor 

Locks, CT. The accident happened at 00:57 EST. Only one passenger received minor 

injuries. The other 77 passengers and crew members were uninjured. The NTSB 

determined that pilot error was the probable cause of the accident.

The fourth accident occurred on July 31, 1997, when McDonnell Douglas MD-11 

operated by Federal Express, Inc. made a hard landing at Newark International Airport, 

Newark, NJ. The airplane bounced and made another hard landing. When the airplane 

came to a stop, a fire broke out and destroyed the airplane. The accident occurred 01:30 

EDT. The two flight crewmembers and three company personnel received minor 

injuries. The NTSB determined that pilot error was the probable cause of the accident.

The fifth accident occurred on August 13, 2004, when a Convair 580 crashed on 

approach to Cincinnati/Northern Kentucky International Airport, Covington, KY. The 

accident happened at 00:49 EDT. The accident was the result of fuel starvation because 

the flight crew did follow approved procedures. The first office received fatal injuries 

while the captain received minor injuries. The airplane was destroyed by the impact. 

The NTSB determined that pilot error was the probable cause of the accident.

These five accidents resulted in seven fatalities. There were also 7 minor injuries 

passengers and crew members, and 77 crew members and a passenger that received 

minor injuries.
40

Summary of Above Analyses

Pilot fatigue is a serious problem. If nothing is done about this problem, we can 

expect about one aviation accident a year (possibly over six accidents) where pilot fatigue 

will be a contributing factor. Pilot fatigue will be a contributing factor in many accidents 

that could potentially cost billions of dollars. 

During the past 20 years, there have been over 18 aviation accidents caused by 

pilot error where pilot fatigue was a factor. NTSB has identified five accidents where the 

flight crew started the day in a state of fatigue. We statistically identified 4.6 accidents 

where the flight crew became fatigued during a long flight-duty period (NTSB cited pilot 

fatigue as a contributing factor in three of those accidents). We have also statistically 

estimated that some of the 6.2 accidents that occurred between midnight and 6:00 am 

involved pilot fatigue. Two of these have already been accounted for in the previously 

discussed analyses. There were also three accidents where the pilot became fatigued due 

to being awake for many hours. Lastly, there were two accidents were chronic fatigue 

was a contributing factor. In summary, we project there would be at least 18.8 accidents 

(13 passenger airplane accidents and 5.8 cargo airplane accidents) during the next 20 

years where pilot fatigue would be a contributing factor to the accident. 

Simulation Results

Simulation is a tool that we can use to study how many future accidents might 

occur and how severe these future accidents might be. The passenger and crew casualties 

in the simulated accidents will be different from those in the past. The casualty estimates 
41

are based on 278 aviation accidents that occurred during the past 20 years because of 

pilot error. The exact pilot error that will cause these future accidents could be any one 

of the pilot errors that have occurred during the past 20 years, and need not be the same 

as those errors that caused the above 18.8 accidents. The aircraft in the simulated future 

accidents could also be different from those in the above accidents. 

Lower Estimated Results

Projected Passenger Airplane Accidents

From the above analysis, 13 passenger airplane accidents are expected to occur 

every 20 years, or 0.65 accidents a year. A 5,000 trial simulation analysis was run with a 

mean value of 0.65 to provide a distribution of the possible outcomes over any future 10-

year period. The median was 6 accidents; the mean was 6.5 accidents; and the range was 

from no accidents to 18 accidents.
42

Figure 1.Distribution of Possible Future Passenger Airplane Accidents

 

On the other hand, the distribution of future fatalities is not a normal distribution, 

but is skewed to the right (see figure 2). For at least 50 percent of the simulation trials 

there were no fatalities during any 10-year period. This is not surprising, since in over 90 

percent of the accidents used to develop the simulation model, there were no fatalities. 

However, the right tail of this distribution is long and heavy. There could be as many as 

828 fatalities during a future 10-year period – a catastrophic collision involving two fully 

loaded wide-body airplanes and one other catastrophic accident also involving a fully 

loaded wide-body airplane could produce this number of fatalities. The mean of the 

simulation distribution of possible future fatalities was 42. The simulation results suggest 
43

there is a 30 percent chance there could be 48 or more fatalities during a future 10-year 

period, a 20 percent chance there could be 91 or more fatalities, and a 10 percent chance 

there could be 144 or more fatalities.

Figure 2. Distribution of Possible Future Fatalities

The distribution of the undiscounted costs of the possible future passenger 

airplane accidents is shown in figure 3. The distribution of the costs, like the distribution 

for possible future fatalities, is heavily skewed to the right. The median for the costs is 

$158.9 million, while the mean is $352.5 million. The minimum cost is zero and the 

maximum cost is $5.080 billion. There is a 30 percent chance that costs would exceed 
44

$402 million; there is a 20 percent chance that costs would exceed $661 million; and a 10 

percent chance that costs would exceed $951 million.

Figure 3 Distribution of Benefits of Avoiding Possible Future Passenger Airplane 

Accidents

Figure 4 shows the distribution of the present value of the possible future 

accidents. It is similar to figure 3 though the values are a little lower. The median value 

is $110.8 million; mean value is $248.5 million; and the maximum value is $3.592 

billion.
45

Figure 4 Distribution of the Present Value of the Costs of Possible Future 

Passenger Airplane Accidents

Projected Cargo Airplane Accidents

Based on the accident analysis above, 5.8 cargo airplane accidents are expected to 

occur every 10 years, or 0.29 accidents a year. A 5,000 trial simulation analysis using a 

Poisson distribution with a mean value of 0.29 was run to provide a distribution of the 

possible outcomes over any future 10-year period. In this case, the distribution of 

possible future number of passenger airplane accidents during any 10-year period (see 
46

figure 5) had almost a normal distribution, though slightly skewed to the right. The 

median is 3 accidents; the mean was 2.9 accidents; and the range was from no accidents 

to 11 accidents.

Figure 5 Distribution of Possible Future Cargo Airplane Accidents

Figure 6 shows the distribution of fatalities for possible future cargo accidents. 

This simulation run projects few fatalities in cargo airplane accidents than for passenger 

airplane accidents. Over 60 percent of the simulation trials result in no fatalities during 

any 10-year period. Under 40 percent of the trail result in fatalities. The mean for this 
47

distribution is one fatality during a 10-year period. There could be as many as 11 

fatalities during a future 10-year period. The simulation results suggest there is a 30 

percent chance there could be 2 or more fatalities during a future 10-year period, and a 20 

percent chance there could be 3 or more fatalities.

Figure 6 Distribution of Fatalities from Possible Future Cargo Airplane 

Accidents

The undiscounted costs of these simulated future cargo accidents are shown in 

Figure 7. Since there few casualties, most of the cost will be the result damage to the 
48

airplane and to the cargo carried. The distribution of the costs is still skewed to the right. 

The median for the costs is $31.5 million, while the mean is $51.5 million. The 

minimum cost is zero and the maximum cost is $368.2 million. There is a 30 percent 

chance that costs would exceed $74 million; there is a 20 percent chance that costs would 

exceed $90 million; and a 10 percent chance that costs would exceed $118 million.

Figure 7 Distribution of the Undiscounted Benefits from Avoiding Possible 

Future Cargo Airplane Accidents
49

Figure 8 shows the distribution of the present value of the possible future 

accidents. It is similar to figure 7 though the values are a little lower. The median value 

is $22.3 million; mean value is $36.1 million; and the maximum value is $258.1 million.

Figure 8 Distribution of the Present Value of the Costs of Possible Future Cargo 

Accidents

S

ummary

If the simulation study is limited to just the number of possible accidents 

identified in the past 20-year period (which would be about 1.0 accidents per year), then 

there would be a mean of 9.4 airplane accidents in a 10-year period. These accidents 

would result in a mean of 43.1 deaths. The total estimated benefit from avoiding these 

simulated accidents has a mean value of $404.0 million ($284.6 million, present value).
50

Upper Estimate Results

Passenger Airplane Accidents

The passenger airplane accidents results above are based on the 33 passenger 

accidents where we have enough information in the accident report to make a judgment 

about the presence or absence of pilot fatigue. Pilot fatigue was present in 13 (or 39.4 

percent) of those accidents. There are, however, 196 additional pilot error accidents 

involving passenger airplanes where that information is not available. If the same ratio 

(39.4 percent) of these 196 accidents were in part due to pilot fatigue, then there would be 

an additional 77.2 accidents where pilot fatigue was a contributing factor. Including the 

additional accidents would mean there could be over 90 passenger airplane accidents 

during the past 20 years where pilot fatigue would be a contributing factor. If the future 

is like the past, then the expected number of passenger airplane accidents would be 4.51 

per year. 

A 5,000 trial simulation analysis using a Poisson distribution with a mean value of 

4.51 was run to provide a distribution of the possible outcomes of passenger airplane 

accidents over any future 10-year period. The distribution of possible future number of 

passenger airplane accidents during any 10-year period has almost a normal distribution. 

The mean is 45.15 accidents; and the standard deviation is 6.71 accidents. The range was 

from 22 accidents to 70 accidents.

Once again, the distribution of future fatalities is not a normal distribution, but is 

skewed to the right. This time, there are almost always some fatalities in each the 
51

simulation trial. There could be as many as 1,357 fatalities during a future 10-year 

period. The mean of the simulation distribution of possible future fatalities was 298. The 

simulation results suggest there is a 30 percent chance there could be 375 or more 

fatalities during a future 10-year period, a 20 percent chance there could be 448 or more 

fatalities, and a 10 percent chance there could be 551 or more fatalities.

The distribution of the undiscounted costs of the possible future passenger 

airplane accidents has a lognormal distribution (see figure 9). The median for the costs is 

$2.324 billion, while the mean is $2.483 billion. The minimum cost is $254.2 million 

and the maximum cost is $8.824 billion. There is a 30 percent chance that costs would 

exceed $2.957 billion; there is a 20 percent chance that costs would exceed $3.410 

billion; and there is a 10 percent chance that costs would exceed $4.057 billion.
52

Figure 9 Distribution of Undiscounted Benefits of Avoiding Possible Future 

Passenger Airplane Accidents

The distribution of the present value of the cost of the possible future accidents 

has a lognormal shape similar to that for undiscounted costs. However, the costs 

projections are a little lower. The mean value is $1.746 billion; and the maximum value 

is $6.839 billion. There is a 30 percent chance that costs would exceed $2.085 billion; 

there is a 20 percent chance that costs would exceed $2.406 billion; and a 10 percent 

chance that costs would exceed $2.875 billion. 
53

Projected Cargo Airplane Accidents

The cargo airplane accidents results above are based on the 10 cargo airplane 

accidents where we have enough information in the accident report to make a judgment 

about the presence or absence of pilot fatigue. Pilot fatigue was present in 5.8 (or 58.0 

percent) of those accidents. There are, however, 39 additional pilot error accidents 

involving passenger airplanes where that information is not available. If the same ratio 

(58.0 percent) of these 39 accidents were in part due to pilot fatigue, then there would be 

an additional 22.6 accidents where pilot fatigue was a contributing factor. Including the 

additional accidents would mean there could be over 28 cargo airplane accidents during 

the past 20 years where pilot fatigue would be a contributing factor. If the future is like 

the past, then the expected number of cargo airplane accidents would be 1.42 per year

A 5,000 trial simulation analysis using a Poisson distribution with a mean value 

of 1.42 was run to provide a distribution of the possible outcomes over any future 10-year 

period. The distribution of possible future number of cargo airplane accidents during any 

10-year period had almost a normal distribution. The mean was 14.22 accidents; and the 

standard deviation is 3.83 accidents. The range is from three accidents to 31 accidents.

This simulation run projects more fatalities in cargo airplane accidents than was 

the previous case for cargo airplane accidents. This time over 80 percent of the trails 

resulted in fatalities. The mean for this distribution is 4.8 fatalities during a 10-year 

period. There could possibly be as many as 22 fatalities during a future 10-year period. 

The simulation results suggest there is a 30 percent chance there could be 6 or more 
54

fatalities during a future 10-year period, a 20 percent chance there could be 8 or more 

fatalities, and a 10 percent chance there could be 10 fatalities.

The distribution of undiscounted costs of these simulated future cargo accidents 

has a lognormal shape. Once again, most of the cost will be the result damage to the 

airplane and to the cargo carried due to the low number of casualties in cargo airplane 

accidents. The mean is $251.8 million. The minimum cost is $12.4 million and the 

maximum cost is $752.2 million. There is a 30 percent chance that costs would exceed 

$299 million; there is a 20 percent chance that costs would exceed $339 million; and a 10 

percent chance that costs would exceed $398 million.

The distribution of the present value of the costs of the possible future accidents is 

similar to that for undiscounted costs, but the values are a little lower. The mean value is 

$176.6 million; and the maximum value is $533.4 million.

Summary

When the simulation study is expanded to include all the additional accidents, the 

expected number of accidents would be 59.4 airplane accidents in a ten-year period. 

These accidents would result in a mean of 303 deaths. The total estimated benefit from 

avoiding these simulated accidents has a mean value of $2.735 billion ($1.923 billion, 

present value).
55

Best Estimate

The annual number of pilot fatigue related passenger airplane accidents is 

probably somewhere between 0.65 and 4.51, and the annual number of pilot related cargo 

airplane accidents is between 0.29 and 1.42. These ranges in the number of these types 

of accidents can also be addressed using simulation analysis.

Passenger Airplane Accidents

A 5,000 trial simulation analysis using a Poisson distribution with a mean ranging 

between 0.65 and 4.51 was run to provide a distribution of the possible outcomes of 

passenger airplane accidents over any future 10-year period (see figure 10). The mean is 

25.96 accidents; and the standard deviation is 12.15 accidents. The range is between 1 

and 66 accidents. 
56

Figure 10 Distribution of Possible Future Passenger Airplane Accidents 

The distribution of future fatalities is shown in figure 11. There is over an 80 

percent chance there will be some fatalities during any given future 10-year period. 

There could possibly be as many as 1,081 fatalities during a future 10-year period. The 

mean of the simulation distribution of possible future fatalities was 172. The simulation 

results suggest there is a 30 percent chance there could be 228 or more fatalities during a 

future 10-year period, a 20 percent chance there could be 289 or more fatalities, and a 10 

percent chance there could be 386 or more fatalities.
57

Figure 11 Distribution of Fatalities from Possible Future Passenger Airplane Accidents

The distribution of the undiscounted costs of the possible future passenger 

airplane accidents has a lognormal distribution (see figure 12). The median for the costs 

is $1.219 billion, while the mean is $1.430 billion. The minimum cost is zero and the 

maximum cost is $7.225 billion. There is a 30 percent chance that costs would exceed 

$1.819 billion; there is a 20 percent chance that costs would exceed $2.241 billion; and a 

10 percent chance that costs would exceed $2.884 billion.
58

Figure 12 Distribution of Benefits of Avoiding Possible Future Passenger Airplane 

Accidents

The distribution of the present value of the cost of the possible future accidents 

has a lognormal shape similar to that for undiscounted costs, but the costs projections are 

a little lower. The mean value is $1.006 billion; and the maximum value is $5.322 

billion. There is a 30 percent chance that costs would exceed $1.273 billion; there is a 20 

percent chance that costs would exceed $1.584 billion; and a 10 percent chance that costs 

would exceed $2.051 billion. 
59

Figure 13 Distribution of the Present Value of the Costs of Possible Future Passenger 

Airplane Accidents

Cargo Airplane Accidents

A 5,000 trial simulation analysis using a Poisson distribution with a mean ranging 

between 0.29 and 1.42 was run to provide a distribution of the possible outcomes of 

passenger airplane accidents over any future 10-year period (see figure 14). The mean is 

8.47 accidents; and the standard deviation is 4.34 accidents. The range is between no 

accidents and 26 accidents.
60
61

Figure 14 Distribution of Possible Future Cargo Airplane Accidents

The distribution of future fatalities is shown in figure 15. There is over a 30 

percent chance there will be no fatalities in each the simulation trial. However, there 

could possible be as many as 19 fatalities during a future 10-year period. The mean of 

the simulation distribution of possible future fatalities was 2.89. The simulation results 

suggest there is a 30 percent chance there could be 4 or more fatalities during a future 10-

year period, a 20 percent chance there could be 5 or more fatalities, and a 10 percent 

chance there could be 7 or more fatalities.
62

Figure 15 Distribution of Fatalities from Possible Future Cargo Airplane Accidents

The distribution of the undiscounted costs of the possible future cargo airplane 

accidents is shown in figure 16. The median for the costs is $133.3 million, while the 

mean is $150.5 million. The minimum cost is zero and the maximum cost is $614.8 

million. There is a 30 percent chance that costs would exceed $193 million; there is a 20 

percent chance that costs would exceed $233 million; and a 10 percent chance that costs 

would exceed $289 million.
63

Figure 16 Distribution of Undiscounted Benefits of Avoiding Possible Future Cargo 

Accidents

The distribution of the present value of the cost of the possible future accidents 

has a shape similar to that for undiscounted costs, but the costs projections are a little 

lower (see figure 17). The mean value is $114.5 million; and the maximum value is 

$475.3 million. There is a 30 percent chance that costs would exceed $147 million; there 

is a 20 percent chance that costs would exceed $178 million; and a 10 percent chance that 

costs would exceed $220 million. 
64

Figure 17 Distribution of the Present Value of the Costs of Possible Future Cargo 

Airplane Accidents

Summary

When a range in the number of annual accidents is allowed in the simulation 

analysis, the mean is 28.9 airplane accidents in a ten-year period. These accidents would 

result in a mean of 174.7 deaths. The estimated cost of these accidents would be a mean 

value of $1.581 billion ($1.121 billion, present value). These numbers represent an 
65

estimate of the likely number of future accidents, deaths, and costs from future accidents 

with fatigue as a factor.

Effectiveness Analysis

The above analysis establishes an estimate of the number and range of fatigue 

related accidents if no action is taken to address the problem. It is seldom the case that a 

rule is 100 percent effective at addressing an identified problem. In particular, fatigue is 

rarely a primary or sole cause of an accident, and therefore this rule, if adopted, is not 

likely to prevent all future accidents that include fatigue as a factor.

FAA reviewed all NTSB accident reports on Part 121 accidents that occurred 

from 1990 through 2009 to assess the likely capacity of the NPRM to have averted those 

accidents. The dataset also included some Part 135 accidents prior to spring 1997 that 

occurred on flights which would have been subject to part 121 after spring 1997 under 

the Commuter Rule of that time. Most reports on major accidents (hull losses or non-hull 

losses that resulted in multiple fatalities) provided extensive data on flight crews’ duty 

tours and recent rest periods, which facilitated relatively strong assessments.

The FAA’s Office of Accident Investigation and Prevention (AVP) rated each 

accident by conducting a scoring process similar to that conducted by the Commercial 

Aviation Safety Team (CAST), a well-documented and well understood procedure. All 

the accidents that have had final National Transportation Safety Board (NTSB) reports 
66

published have been scored against the CAST safety enhancements. AVP used the 

NTSB recommendations along with narratives, probable cause, contributing factors and 

other pertinent data to score the accidents. 

When these accidents were not well defined in the probable cause or contributing 

factors statements of the NTSB reports, AVP used a Joint Implementation Monitoring 

Data Analysis Team (JIMDAT)-like method. The JIMDAT-type scoring system is from 

0 to 5, and the score is based on the likelihood that a proposed action would have 

mitigated that accident. The level and percentage of effectiveness criteria follows:

5- 90% effectiveness. The proposed requirement directly addresses the 

NTSB causal factors and would very likely prevent the accident in the future.

4- 75% effectiveness. The proposed requirement directly addresses the 

majority of the NTSB causal factors and would probably prevent or is likely to reduce the 

risk of the respective accident, given the circumstances that prevailed.

3- 50 % effectiveness. The proposed requirement directly addresses one of 

several NTSB causal factors and is likely to reduce the risk of the respective accident, 

given the circumstances that prevailed. 

2- 35% effectiveness. The proposed requirement generally addresses the 

NTSB causal factors and is likely reduce the risk of the respective accident, given the 

circumstances that prevailed. 
67

1- 15% effectiveness. The proposed requirement is likely to have reduced 

the risk of the respective accident, given the circumstances that prevailed.

0- 0% effectiveness. The proposed requirement would not reduce the risk of 

this type of accident in the future.

AVP applied the above methodology to the details of each such pilot fatigue 

accident to reach a qualitative assessment of the NPRM’s potential capacity to avoid each 

pilot fatigue accident. The qualitative assessments ranged from zero (0) to low (1), 

moderate (3), high (4) and very high (5). The qualitative assessments then were 

converted to quantitative effectiveness scores as follows: zero; 15%; 35%; 50%; 75%; 

and 90%. The effectiveness scores yielded about 8 accidents avoided over 20 years (see 

Technical Report submitted to the docket for the scoring results of the above accidents 

used in this analysis). According to this scoring, the proposed rule would be 40 percent 

effective at preventing passenger airplane accidents where pilot fatigue was a 

contributing factor and would be 58 percent effective at preventing cargo airplane 

accidents where pilot fatigue was a contributing factor.

Accordingly, the above estimate of the benefits of avoiding passenger airplane 

accidents where pilot fatigue was a causal factor have been reduced to 40 percent of their 

above stated values. The undiscounted mean benefit was reduced from $1.403 billion to 

$572.1 million and the maximum undiscounted benefit was reduced from $7.225 billion 

to $2.890 billion. The mean present value of the benefit was reduced from $1.006 billion
68

to $402.5 million and the maximum present value benefit was reduced from $5.322 

billion to $2.129 billion.

Next, the estimated benefits of avoiding cargo airplane accidents were reduced to 

58 percent of their above stated values. The undiscounted mean benefit was reduced 

from $150.5 million to $87.3 million and the maximum undiscounted benefit was 

reduced from $614.8 billion to $356.6 million. The mean present value of the benefit 

was reduced from $105.7 million to $61.3 million and the maximum present value 

benefit was reduced from $446.2 million to $258.8 million. 

The estimated benefit of avoiding passenger and cargo airplane accidents would 

be a mean value of $659.4 million ($463.8 million, present value).

Additional Benefits

The FAA has investigated other areas of potential benefit from this proposed rule. 

These areas are not quantified at this time, but are additional factors that should be 

considered when deciding whether to proceed with this rule.

The first area is in the area of minor aircraft and equipment damage on the ramp. 

By necessity, the focus on fatal accidents examines extremely remote events where 

something in the events leading to the accident did not reliably provide the necessary 

safety margin or back up. In part the focus on fatal accidents comes from the fact they are 

investigated in detail, event chains and causes are well defined, and assumptions can be 
69

made about cause and effect. However, there is a much larger universe of relatively 

minor accidents that may involve much larger annual dollar losses than the few fatal 

accidents that do occur. However, so few of these are investigated in much detail that 

they tend to be disregarded when looking at new safety regulations.

In the 170 Part 121 accidents from 2004-2008, there were a total of ten events that 

had a fatality. Overall, 90 fatalities occurred on those ten flights over the course of five 

years. Using a VSL of $6 million, the monetized value of loss of life is $540 million, and 

the average value of lost lives is about $100 million per year. This amount is only a small 

fraction of the overall cost of accidents on airport ramps. One estimate puts the cost of 

ground accidents and incidents which include injuries, fatalities and property damage at 

$5 billion per year worldwide. In the U.S. alone, total costs of ramp incidents and 

accidents exceed $3 billion per year. However, these events are not investigated in 

detail—i.e., there is a lack of causal information, no human factors report with work 

chronology, etc.

The fatigue literature suggests that the greatest benefits from fatigue reduction lie 

in increased productivity and in the reduction of human errors. Thus, we would expect to 

see a much larger number of events where pilot fatigue is a cause or factor, than is 

represented by fatal accidents alone. Preliminary research shows that the frequency of 

ground accidents during the evening (6:00 PM to midnight) and early morning (midnight 

to 6:00 AM) is higher than the distributions of scheduled takeoffs and landings would 

suggest. We observe a similar relationship when we look at Aviation Safety Reporting 

System (ASRS) reports citing pilot fatigue and related topics.
70

Of course not all the ground accidents involve pilot error, and not all instances of 

pilot error are cause by fatigue. However, the data on when these accidents occur suggest 

they are more prevalent when the potential for fatigue is greatest. In addition, the types of 

events such as taxiing a wing tip into another aircraft or gate, are symptomatic of poor 

decision making, poor spatial judgment, a focus on completing the flight quickly and 

other factors which may be more prevalent when fatigued. If even only a few percent of 

the losses from ground accidents are caused by pilot fatigue, the annual losses are large 

Three percent would be $90 million per year. These data suggest that the scope of 

accidents/incidents for valuing safety needs to be expanded to account for losses due to 

ground events where appropriate.

The second area is in the value of having well rested (and well-trained) pilots in 

the cockpit to solve minor problems before they become accidents. The aviation system 

is extremely complex, and aircraft are extremely complex machines. It is also extremely 

safe. When an accident occurs, it is generally the result of a long chain of multiple 

failures. The flightcrew in the cockpit is generally the last opportunity to break the chain 

and prevent an accident. It is well established that fatigued people are less likely to 

quickly and efficiently diagnose and solve problems than well-rested people. Every day, 

small events and mishaps are dealt with by the cockpit crew and they never become 

accidents, or the outcome is somewhat mitigated by the quick action of the crew. (The 

Flight 1549 that landed safely in the Hudson River is an example of how very quick 

reaction and decision making can avert catastrophes.) Some small number of incidents 

and accidents caused by things other than fatigue or human error maybe could have been 
71

prevented or mitigated if the crew had quickly behaved differently. While we have 

documented the likely size of the accident problem with fatigue as a factor, it is not 

possible to estimate the impact of increased problem solving capability from fewer 

fatigued pilots. It is, however, real and significant.

Sensitivity Analysis: Value of Statistical Life Estimates 

for FAA Regulatory Programs

Complex analyses for difficult public policy decisions typically employ 

sensitivity analyses to allow decision makers to see the impact of different values of key 

variables, to see how those different values impact the results of the analysis. The value 

of a statistical life (VSL) is an important policy measure as it is primarily used when 

federal agencies look to compare the costs and benefits of potential investment and 

regulatory policies and programs. In this regulatory impact analysis, FAA presented 

total benefits based on VSLs of $6 million, as suggested by 2009 guidance from DOT, 

and consistent with OMB Circular A-4. If $8.4 million were used for VSL, the 

undiscounted benefits would be $837 million and the present value of those benefits 

would be $589 million. A VSL value of $8.4 million is consistent with recent 

literature1415. The FAA requests public comment on whether decision-makers should 

 

14See Thomas J. Kniesner, W.Kip Viscusi, and James P. Ziliak, ―Policy Relevant Heterogeneity in the 

Value of Statistical Life: New Evidence from Panel Data Quantile Regressions,‖ Journal of Risk 

Analysis, Vol.40, No. 1, pp. 15-31

15W. Kip Viscusi, ―The Heterogeneity of the Value of Statistical Life: Introduction and Overview,‖ Journal 

of Risk Analysis, Vol.40, No. 1, pp. 1-13
72

consider using a VSL higher or lower than $6 million to evaluate commercial aviation 

safety proposals.
73

COST ANALYSIS

Cost Overview

The total estimated cost of the proposed rule is $1.25 billion ($804 million present 

value using a seven percent discount rate) for the ten year period from 2013 to 2022. 

The FAA classified costs into four main components and estimated the costs for each 

component.16 We obtained data from various industry sources; the sources of the data 

used in cost estimation are explained in each section. We were very fortunate that several 

carriers ran two alternatives to the proposed rule through their crew scheduling programs. 

Their estimates provided some comparison data to calibrate and validate our costing 

approach. Without their help, we would have likely missed some cost elements. The 

Cost Summary Table below identifies the four main cost components. Flight operations 

cost makes up about 60 percent of the total cost of the rule. Each of the main cost 

components are explained in-depth in the following sections of this document. 

Cost Summary

Cost Area Nominal Cost Present Value Cost

(in $ millions) (in $millions)

Flight Operations $760.3 $484.2

Scheduling Reliability $4.9 $3.0

Fatigue Training Costs $262.3 $167.2

Cost of Rest Facilities $226.6 $149.1

Total Cost $1,254.1 $803.5

 

16 The FAA also calculated alternative scheduling costs, which comprise the largest cost component of the 

proposed rule. Discussions of these alternatives follow the main cost section.
74

In addition to the costs presented in the Cost Summary Table, there may be costs 

of a fatigue risk management system (FRMS). The FAA is not imposing an FRMS 

program requirement on Part 121 carriers, but is allowing them the option of developing 

and implementing such a program. Operators might do this for ultralong flights, which 

have flight time over 16 hours. Operators might develop an FRMS program as an 

alternative to the flight and duty period rules proposed by this rulemaking when the crew 

scheduling cost savings equal or exceed the costs of the FRMS program. The FAA 

estimates that an FRMS program would cost between $0.8 and $10.0 million for each 

operator over ten years. The FAA believes that about 35 operators have at least partially 

adopted an FRMS program at this time. The FAA estimates the total cost would be 

$205.7 million ($144.9 million present value), which would be more than offset by a 

reduction in crew scheduling costs. Accordingly, the cost is not added to the total costs 

imposed by this rule. The FAA calls for comment on this aspect of the proposal as it has 

not assigned a cost to the cumulative maximums.17

Flight Operations – Overview

The flight operations cost component of the proposed rule is composed of five 

sub-components: crew scheduling costs, cost to supplement the flight engineer on 

augmented operations, crew management system computer programming costs, cost 

savings of reduced reserves, and cost savings of the elimination of the flight time limit for 

 

17 Cumulative maximums are limitations on the amount of duty or flight time that flightcrew members are 

allowed to work over a period of time greater than a single duty period; for instance, the proposed rule 

sets a maximum of 65 duty hours in any seven-day period and a maximum of 200 duty hours in a 28-day 

period.
75

augmented operations. Table 5 provides a summary of the five sub-components of the 

flight operations cost. Each of the sub-components is explained in-depth in the following 

sections of the document.

Table 5: Summary of Flight Operations Costs

Cost Sub-Component Nominal Cost

(millions)

PV Cost

(millions)

Crew Scheduling (Resource Cost Only) $ 1,366.7 $ 854.2

Augmented - Suppplement FE $ 66.7 $ 40.9

Computer Programming $ 10.0 $ 8.1

Reduced Reserves ($ 231.7) ($ 142.1)

Augmented - Eliminate Flight Time Limit ($ 451.4) ($ 276.9)

Total Flight Operations $ 760.3 $ 484.2

Flight Operations – Crew Scheduling

Analysis of Crew Schedule Data

Six air carriers18 provided actual crew schedule data to the FAA to assist in the 

cost analysis of the Flightcrew Member Duty and Rest Requirements Rulemaking. The 

data consisted of one spring month in 2009 and one summer month in 2009 of actual 

work history for each flightcrew member employed by each carrier. The specific months 

varied by carrier. The data included all duty time and flight time worked by each 

flightcrew member, and included both lineholder and reserve pilots.

 

18 Two of the carriers included data for related carriers operating under multiple business names.
76

The individual flightcrew member work histories were used to construct baseline 

summary data for each carrier. The total numbers of duty periods, duty hours, flight 

hours, and flight segments were summarized. The summary data were divided by the 

number of flightcrew members in each dataset to produce the average number of duty 

periods, duty hours, flight hours, and flight segments per flightcrew member per month. 

The baseline data was later used to estimate the number of noncompliant hours under the 

proposed rule.

Three types of crew scheduling limits were examined: flight duty, rest, and flight 

time limits. Only limits relating to individual flight duty periods were applied. 

Cumulative limits were not applied due to data limitations.. Flight duty limits impose a 

maximum number of hours that a flightcrew member may be on flight duty, based on the 

number of flight segments flown during the flight duty period (for unaugmented 

operations only), the starting time of the flight duty period, and, for augmented operations 

only, the rest facility onboard the aircraft and the number of crew operating the flight. 

Rest limits require that a flightcrew member have received a minimum number of rest 

hours (hours free from all duty) prior to beginning a flight duty period and vary 

depending on geographic location (domestic or international flights).19 Flight limits 

impose a maximum number of hours that a flightcrew member may operate an aircraft 

during a given flight duty period and vary depending on the starting time of the flight 

duty period (for unaugmented operations only). 

 

19 In the context of proposed minimum rest limits, “domestic” refers to a flight duty period beginning in 

the 48 contiguous states, territories, and District of Colombia. “International” refers to a flight duty 

period beginning outside of the 48 contiguous states, territories, and District of Colombia.
77

A computer program was used to apply flight duty, rest, and flight time limits to 

the actual crew schedule data. First, the maximum flight duty limits were applied to each 

individual duty period. If the flight duty period exceeded the relevant flight duty limit, 

the duty period was truncated at the limit. Next, the minimum rest limits were applied to 

each individual duty period. If a flight duty period was not preceded by the relevant 

minimum number of rest hours, then the preceding flight duty period was truncated at the 

point where the minimum number of rest hours was sufficient for the flight duty period in 

question. Finally, the flight limits were applied to each individual flight duty period. If 

the sum of all flight time within a flight duty period exceeded the relevant flight limit, the 

last flight segment of the flight duty period was eliminated from the data, with the 

elimination of flight segments continuing backwards, if necessary, until the sum of all 

flight time within the flight duty period was lower than the flight limit. For all of the 

types of limits, if the flight duty period was truncated while a flight segment was 

underway, then the entire flight segment was eliminated from the data.

The application of the proposed flight duty, rest, and flight time limits resulted in 

modified flightcrew member work histories. These modified work histories were used to 

construct modified summary data for each carrier, similar to the baseline summary data. 

The modified number of duty periods, duty hours, flight hours, and flight segments also 

were summarized. The modified summary data was divided by the number of flightcrew 

members in each dataset to produce the average number of duty periods, duty hours, 

flight hours, and flight segments per flightcrew member per month.
78

The modified average number of flight hours per flightcrew member was 

compared to the baseline average number of flight hours per flightcrew member for each 

carrier. The difference between the two numbers represented the average number of 

flight hours per flightcrew member that were not compliant with the applied flight duty, 

rest, and flight time rules. The assumption is that these extra hours result in needing to 

either hire new pilots or pay existing pilots for more hours of duty. This is a very 

conservative initial estimate, which is later adjusted.

The FAA evaluated the proposed flight duty, rest, and flight time limits to 

produce an estimated crew scheduling cost for the entire air transport industry. Table 6 

details the most significant differences between the proposed rule and current Part 121 

rules.

Table 6: Comparison of Proposed Rule to Current Part 121

Minimum Rest 

Prior to Duty -

Domestic

Minimum Rest 

Prior to Duty -

International

Maximum Flight 

Duty Time -

Unaugmented

Maximum Flight 

Duty Time -

Augmented

Maximum Flight 

Time -

Unaugmented

Maximum Flight 

Time -

Augmented

Current Part 121

Daily: 8-11 

depending on flight 

time

Minimum of 8 hours to twice the number of hours flown

16 16-20 depending 

on crew size

8

8-16 depending on 

crew size

NPRM 9 9

9-13 depending on 

start time and 

number of flight 

segments

12-18 depending 

on start time, crew 

size, and aircraft 

rest facility

8-10 depending on 

FDP start time

None

Scenario

Rest Time Duty Time Flight Time
79

Cost Estimates Using Crew Schedule Data

All Part 121 air carriers in the U.S. air transport industry were categorized into 

seven groups based on the size of the aircraft type with the most block hours in 200820

and operating characteristics. Table 7 defines the groups based on aircraft size and 

operating characteristics. The number of air carriers in each group and number of 

flightcrew members in each group are also presented. 

 

20 Department of Transportation, Bureau of Transportation Statistics, Air Carrier Summary Data (Form 41 

and 298C Summary Data), T2: U.S. Air Carrier Traffic and Capacity Statistics by Aircraft Type, 2008.

Minimum Rest 

Prior to Duty -

Domestic

Minimum Rest 

Prior to Duty -

International

Maximum Flight 

Duty Time -

Unaugmented

Maximum Flight 

Duty Time -

Augmented

Maximum Flight 

Time -

Unaugmented

Maximum Flight 

Time -

Augmented

Current Part 121

Daily: 8-11 

depending on flight 

time

Minimum of 8 hours to twice the number of hours flown

16 16-20 depending 

on crew size

8

8-16 depending on 

crew size

NPRM 9 9

9-13 depending on 

start time and 

number of flight 

segments

12-18 depending 

on start time, crew 

size, and aircraft 

rest facility

8-10 depending on 

FDP start time

None

Scenario

Rest Time Duty Time Flight Time
80

Table 7: Air Carrier Groups for NPRM Cost Analysis

Aircraft Type with Most Block Hours Part 121 

Air Carriers

Part 121

Flightcrew Members

1 Large Cargo Carrier Aircraft > 100 seats equivalent 26 10,125

2 Commercial Passenger Carrier Aircraft > 100 seats 8 39,406

3 Low Cost Carrier Aircraft > 100 seats 9 11,260

4 Regional Passenger Carrier Aircraft 20 < seats < 100 30 20,980

5 Small Cargo Carrier Aircraft < 100 seats equivalent 3 236

6 Small Passenger Carrier Aircraft < 20 seats 4 281

7 Charter Passenger Carrier Aircraft > 100 seats 12 1,230

92 83,518

Group

Total

Source: FAA OPSS, October 2009

Each of the six air carriers that provided crew schedule data to the FAA was 

assigned to one of the seven air transport industry groups. Each of the industry groups 

was represented in the data provided to FAA, except for the small passenger, small cargo, 

and charter passenger groups. The crew schedule data provided to the FAA represented 

23 percent of all Part 121 flightcrew members, as shown in Table 8.

Table 8: Coverage of Industry

Total Part 121 

Flightcrew Members

Flightcrew Members 

in Data Provided to 

FAA

Coverage 

Share

83,518 19,529 23.4%

Three industry groups were not represented in the data provided to the FAA and 

were assigned to a comparison group for purposes of cost estimation. The comparison 

group is the industry group that most closely resembles the unrepresented industry group. 

Table 9 presents the comparison group for each of the seven industry groups.
81

Table 9: Comparison Groups

Group Comparison Group

Large Cargo Large Cargo

Commercial Passenger Commercial Passenger

LCC LCC

Regional Regional 

Small Cargo Large Cargo

Small Passenger Regional 

Charter Passenger Large Cargo

To determine the crew scheduling costs of the proposed rule, the number of 

noncompliant flight hours for each air carrier in the air transport industry was first 

calculated. The number of noncompliant flight hours for each carrier was calculated by 

multiplying the number of flightcrew members employed by the carrier by the average 

number of noncompliant flight hours per flightcrew member for the carrier’s relevant 

comparison group. Table 10 presents the number of noncompliant flight hours and their 

share relative to the baseline for the proposed rule.

Table 10: Noncompliant Flight Hours

Noncompliant Flight Hours Share of Baseline

2,385,702 4.8%

After the total number of noncompliant flight hours was calculated for each 

carrier, costs were calculated based on the average hourly salary for each flightcrew 
82

member, for each carrier. The primary source of salary data was a 2006 report by AIR, 

Inc, an aviation industry publication. The report listed both annual salary and estimated 

credit hours for many carriers. This information was used to estimate the average hourly 

salary per flightcrew member. If salary data were unavailable for a carrier, the average 

hourly salary per flightcrew member for that carrier’s industry group was used as a 

proxy. The average hourly salaries were updated to 2009 values using the Air Transport 

Association (ATA) Passenger Airline Cost Index. The labor component of the cost index 

was used to update the salaries from Q3 2006 to Q3 2009.21 Table 11 presents the 

average hourly salary per flightcrew member for each industry group.

Table 11: Average Hourly Salary

Group Average Hourly 

Salary

Large Cargo $121

Commercial Passenger $129

LCC $107

Regional $60

Small Cargo $55

Small Passenger $45

Charter Passenger $92

The average hourly salary per flightcrew member for each carrier was multiplied 

by the noncompliant flight hours for each carrier, resulting in an estimated salary cost for 

each carrier. After estimating the additional crew scheduling salary cost, it was necessary 

 

21 Q3 2009 data was the most recent available at the time of publication.
83

to calculate the additional hotel and per-diem costs that would be incurred by carriers. 

During the rulemaking, one carrier had estimated its expected crew scheduling costs 

resulting from the flight duty, rest, and flight limits of one alternative to the proposed 

rule. As part of this analysis, the carrier allocated its total crew scheduling costs to 

salary, hotel, and per diem categories. We have used their costs proportions to estimate 

hotel and per diem for other scenarios.

The individual carrier salary, hotel, and per-diem costs were summarized based 

on the seven industry groups to result in unadjusted additional annual crew scheduling 

costs resulting from the application of NPRM flight duty, rest, and flight time limits, as 

shown in Table 12.

Table 12: Unadjusted Crew Scheduling Costs

Year Nominal Cost 

(millions)

PV Cost 

(millions)

2013 $ 338.3 $ 276.2

2014 $ 338.3 $ 258.1

2015 $ 338.3 $ 241.2

2016 $ 338.3 $ 225.4

2017 $ 338.3 $ 210.7

2018 $ 338.3 $ 196.9

2019 $ 338.3 $ 184.0

2020 $ 338.3 $ 172.0

2021 $ 338.3 $ 160.7

2022 $ 338.3 $ 150.2

Total $ 3,383.4 $ 2,075.6
84

 The FAA believes that substantial opportunity for re-optimization exists because 

many of the flight segments that are eliminated for non-compliance with the proposed 

rule are only non-compliant by small amounts of time. Approximately 86 percent of the 

eliminated flights are due to non-compliance with duty limits, rather than flight or rest 

limits. The FAA examined the amount of time by which the duty period associated with 

each eliminated flight segment exceeded the maximum allowable duty time. Chart 1 

presents these results. Nearly 40 percent of flights were eliminated due to their duty 

period exceeding the maximum allowable duty time by less than 60 minutes.

Chart 1: Duty Period Non-Compliance for Eliminated Flights

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Flights

0-30

31-6061-90

91-120

121-150151-180181-210211-240241-270271-300

301+

Flights Eliminated by Duty Limit:

Minutes Over Duty Limit

The FAA believes the crew scheduling costs calculated using this methodology 

substantially overestimate the probable actual cost impact of the proposed rule. Most 
85

airlines employ computer programs to optimize crew schedules – to minimize the number 

of crew hours, and hotel and per diem costs it takes to fly a given flight schedule within 

imposed constraints. The FAA accordingly has developed a methodology to adjust the 

estimate based on total non-compliant hours to a more realistic representation of costs 

after re-optimization. We ask for comments on the cost adjustments described in the next 

section and request a detailed explanation or justification for any and all comments.

Crew Scheduling Cost Adjustments

To approximate the reductions in cost that will occur when airlines optimize crew 

schedules following implementation of the rule, the FAA made several adjustments to the 

crew scheduling costs presented in Table 12. These adjustments include both short-term 

and long-term optimization that the FAA believes is likely to occur.

The FAA applied a short-term optimization factor of 25 percent to the unadjusted 

costs. This discount off of raw costs approximates the savings expected from the 

computer models used to build schedules; flight schedules will be rearranged into new 

trips that meet the new constraints of the rule. Typically, industry will experience from 10 

percent to 40 percent savings from reoptimizing in this fashion. FAA selected a factor of 

25 percent because it approximates the difference in costs submitted by a sample of 

carriers to FAA when they evaluated an alternative to the proposed rule, using their 

computer models, to the costs estimated by the FAA using the same cost estimation 

process described previously. Table 13 presents the annual costs after short-term 

optimization.
86

Table 13: Crew Scheduling Costs after Short-Term Optimization

Year Optimization 

Factor Nominal PV

2013 25% $ 253.8 $ 207.1

2014 25% $ 253.8 $ 193.6

2015 25% $ 253.8 $ 180.9

2016 25% $ 253.8 $ 169.1

2017 25% $ 253.8 $ 158.0

2018 25% $ 253.8 $ 147.7

2019 25% $ 253.8 $ 138.0

2020 25% $ 253.8 $ 129.0

2021 25% $ 253.8 $ 120.6

2022 25% $ 253.8 $ 112.7

Total $ 2,537.5 $ 1,556.7
87

After determining the crew scheduling costs after short-term optimization, FAA 

examined the salary component of the crew scheduling costs and identified the share that 

would be additional pay to existing crews versus salary for new hires. The initial shares 

are identical to those provided by one carrier that submitted a detailed cost estimate to 

FAA of an alternative to the proposed rule. Over time, FAA believes that the share of 

pay to existing crews will increase while the share of new hire salary will decrease, 

because carriers will continue to schedule crews ever more efficiently. Table 14 provides 

the annual shares of the crew scheduling cost components.

Table 14: Crew Scheduling Cost Components

Year Existing 

Crews New Hires Hotel & Per Diem

2013 41% 48% 11%

2014 43% 46% 11%

2015 45% 44% 11%

2016 47% 42% 11%

2017 49% 40% 11%

2018 51% 38% 11%

2019 53% 36% 11%

2020 55% 34% 11%

2021 57% 32% 11%

2022 59% 30% 11%

Once the share of salary costs between the existing crews and new hires was 

determined, FAA identified additional long-term optimization factors, independent of the 

previously described short-term optimization. The long-term optimization factors reflect 
88

changes to crew bases, flight schedules, and other similar changes that will be 

implemented over a number of years. These also include potential adjustments to 

contracts between pilots and airlines that govern pay and working conditions. In 

conjunction with this step, FAA identified costs as either transfer costs or resource costs. 

The sum of these represents the financial impact on the carrier. 

Transfer costs are defined as temporary cost increases resulting from short-term 

disruptions for the industry and its participants. These result in financial transfers 

between the carriers and flightcrew members. Resource costs are defined as true costs to 

society, due to inefficient use of resources. (The key difference between resource costs 

and transfers is whether the pilot ends up with free time that can be put to other 

productive uses. If a pilot does end up with additional free time for the same pay as 

before, this represents a transfer between the carrier and the pilot.) Tables 15 and 16 

identify the long-term optimization factors, transfer costs, and resource costs for existing 

crews and new hires, respectively. Over the longer term, we expect that carriers will be 

able to improve scheduling efficiency of existing crew members. In the case of new 

pilots, there is less of an opportunity to improve scheduling efficiency.
89

Table 15: Long-Term Optimization of Additional Pay to Existing Crews

Year Optimization 

Factor

Transfer

Cost

Resource 

Cost

2013 60% 67% 33%

2014 40% 50% 50%

2015 20% 0% 100%

2016 20% 0% 100%

2017 20% 0% 100%

2018 20% 0% 100%

2019 20% 0% 100%

2020 20% 0% 100%

2021 20% 0% 100%

2022 20% 0% 100%

Table 16: Long-Term Optimization of Pay to New Hires

Year Optimization 

Factor

Transfer

Cost

Resource 

Cost

2013 95% 0% 100%

2014 90% 0% 100%

2015 80% 0% 100%

2016 80% 0% 100%

2017 80% 0% 100%

2018 80% 0% 100%

2019 80% 0% 100%

2020 80% 0% 100%

2021 80% 0% 100%

2022 80% 0% 100%
90

Table 17 presents the total crew scheduling costs, including salary to existing 

crews and new hires, hotel, and per-diem. The costs are categorized as either transfer or 

resource costs. The final reported costs of the proposed rule include only the resource 

costs from Table 17, as they represent the true cost of the rule to society. 

Table 17: Final Crew Scheduling Costs

Nominal Cost 

(millions)

PV Cost 

(millions)

Nominal Cost 

(millions)

PV Cost 

(millions)

2013 $ 64.4 $ 52.5 $ 165.5 $ 135.1

2014 $ 33.6 $ 25.6 $ 156.0 $ 119.0

2015 $ 0.0 $ 0.0 $ 141.3 $ 100.8

2016 $ 0.0 $ 0.0 $ 138.3 $ 92.1

2017 $ 0.0 $ 0.0 $ 135.2 $ 84.2

2018 $ 0.0 $ 0.0 $ 132.2 $ 76.9

2019 $ 0.0 $ 0.0 $ 129.1 $ 70.2

2020 $ 0.0 $ 0.0 $ 126.1 $ 64.1

2021 $ 0.0 $ 0.0 $ 123.0 $ 58.5

2022 $ 0.0 $ 0.0 $ 120.0 $ 53.3

Total $ 97.9 $ 78.2 $ 1,366.7 $ 854.2

Year

Transfer Costs Resource Costs

Flight Operations – Additional Pilot to Supplement Flight Engineer

Carriers currently operating flights in excess of eight hours with a flightcrew of 

two pilots and one flight engineer will incur additional pilot salary costs on these flights 

under the proposed rule. Under current Part 121 rules, flight engineers are considered to 

be a crewmember for purposes of determining whether a flight can operate under 
91

augmented flight and duty rules. The proposed rule will not allow flight engineers to be 

considered as crewmembers when determining whether a flight can operate under 

augmented flight and duty rules. Therefore, carriers will need to add another pilot to the 

flightcrew for those flights that currently exceed eight hours and have a flightcrew of two 

pilots and a flight engineer.

The first step to estimating the cost impact of this aspect of the proposed rule was 

to examine the crew schedule data provided to the FAA and identify the flights affected 

by this rule change. Flights exceeding eight hours with a two pilot flightcrew were 

identified. Only those flights on aircraft types that utilize a flight engineer were 

considered. The only flights that met these criteria were operated by carriers in the large 

cargo group. The number of flight hours associated with these flights was then 

annualized. The annual number of flight hours was divided by the number of flight 

engineers for the relevant carriers to produce an average number of flight hours affected 

by the rule change per flight engineer. The result is 29.1 flight hours per flight engineer 

per year. The only aircraft types operated by flight engineers in the sample data that 

FAA received from the carriers are Boeing 727 and Boeing 747 aircraft.

The average number of flight hours affected per flight engineer was extrapolated 

to the entire air transport industry using the number of flight engineers listed on each air 

carrier’s operating certificate in OPSS. The average number of flight hours affected per 

flight engineer was multiplied by the number of flight engineers at each carrier. The 

result represents the total number of flight hours that must be flown by a pilot to comply 

with the proposed rule. The total number of flight hours for each carrier was multiplied 
92

by the average hourly pilot salary for the carrier’s industry group to obtain a total 

estimated cost of this aspect of the proposed rule. Table 18 summarizes the results by 

industry group. Industry groups that did not include a carrier with at least one flight 

engineer were excluded from Table 18.

Table 18: Annual Cost of Adding a Pilot to Supplement Flight Engineer on Augmented 

Flights

Industry Group Flight Engineers Flight Hours 

Affected

Average Pilot 

Hourly Salary

Additional Pilot 

Salary Cost

(millions)

Large Cargo 1,648 49,020 $121 $5.9

Charter Passenger 92 2,715 $92 $0.3

Commercial Passenger 125 3,690 $129 $0.5

Total 55,425 $6.7

Note: Analysis was conducted on a carrier-specific basis. Aggregated results are presented here.

The nominal annual cost of adding a pilot to supplement the flight engineer on 

augmented flights is $6.7 million. The nominal cost for the period of analysis is $66.7 

million and the present value cost for the period of analysis is $40.9 million, as shown in 

Table 19.
93

Table 19: Cost of Adding a Pilot to Supplement Flight Engineer on Augmented Flights

Year Nominal Cost

(millions)

PV Cost

(millions)

2013 $6.7 $5.4

2014 $6.7 $5.1

2015 $6.7 $4.8

2016 $6.7 $4.4

2017 $6.7 $4.2

2018 $6.7 $3.9

2019 $6.7 $3.6

2020 $6.7 $3.4

2021 $6.7 $3.2

2022 $6.7 $3.0

Total $66.7 $40.9

Flight Operations – Computer Programming

Carriers will incur computer programming costs as they will need to update their 

crew management systems and their schedule optimization systems with the constraints 

imposed by the proposed rule. This will be a one-time cost incurred in 2013 as carriers 

update their computer systems. Computer programming costs were estimated for each 

individual carrier, based on the number of flightcrew members listed on the carrier’s 

operating certificate. 

Carriers were assigned to one of three groups based on the number of flightcrew 

members. Costs were estimated based on the number of person-days required to 

complete the computer programming and a daily professional staff cost of $2,500. Table 

20 presents the nominal and present value computer programming costs. We invite 
94

specific comment on this estimate of the expected computer programming costs for 

carriers.

Table 20: Computer Programming Costs

Year Flightcrew 

Members Carriers Cost per Carrier

Nominal 

Cost 

(millions)

PV Cost 

(millions)

>1,000 21 $250,000 $ 5.3 $ 4.3

250-1,000 21 $100,000 $ 2.1 $ 1.7

>250 52 $50,000 $ 2.6 $ 2.1

Total 94 $ 10.0 $ 8.1

2013

Flight Operations – Cost Savings from Reduced Reserves

The proposed rule is designed to reduce the risk of fatigued flightcrew members 

by limiting the maximum number of hours they are permitted to be on duty, the number 

of hours they actually fly during duty periods, and by ensuring that they receive adequate 

rest periods before reporting for duty. It is expected that the proposed rule will result in 

better-rested flightcrew members. The proposed rule will reduce flight crew member 

fatigue, thus reducing the use of sick time. When a flightcrew member is scheduled for 

duty and calls in sick or fatigued, the airline must use a reserve flightcrew member to 

complete the scheduled duty. The proposed rule will reduce the use of reserve flightcrew 

members to cover fatigue-induced sick call-ins by flight crew members, which will 

reduce the flight operations cost associated with fatigue issues for carriers.
95

While the precise share of current sick time attributable to fatigue is unknown, it 

is most likely greater than zero. Similarly, while the precise amount by which the 

proposed rule will reduce sick time is unknown, it is also most likely greater than zero. 

For the purposes of this analysis, FAA assumes that sick time accounts for five percent of 

total industry flightcrew member pay. The proposed rule is expected to reduce the use of 

sick time by five percent. The nominal value of the cost savings is $231.7 million 

($142.1 million present value) over the ten-year period of analysis. Table 21 presents the 

annual cost savings. 

Table 21: Reduced Reserves Cost Savings

Year Nominal Cost 

Savings (millions)

PV Cost Savings 

(millions)

2013 $ 23.2 $ 18.9

2014 $ 23.2 $ 17.7

2015 $ 23.2 $ 16.5

2016 $ 23.2 $ 15.4

2017 $ 23.2 $ 14.4

2018 $ 23.2 $ 13.5

2019 $ 23.2 $ 12.6

2020 $ 23.2 $ 11.8

2021 $ 23.2 $ 11.0

2022 $ 23.2 $ 10.3

Total $ 231.7 $ 142.1
96

Flight Operations – Cost Savings from Augmented Operations

The proposed rule eliminates the existing maximum flight time limit for 

augmented operations, which creates a potential cost-saving opportunity for carriers. 

Carriers are required to operate some flights with four flightcrew members under existing 

maximum flight time limits. Some of these flights could be operated with three 

flightcrew members under the proposed rule, which would reduce carriers’ flight 

operations costs.

The existing maximum flight time limit for flag and supplemental carriers is 12 

hours for three flightcrew members and 16 hours for four flightcrew members. Although 

there are no maximum flight time limits in the proposed rule for augmented operations, 

flightcrew members’ flight time will be limited in practice by maximum flight duty time 

limits. The proposed rule sets the maximum flight duty time for a flightcrew member 

when operating a flight with three flightcrew members at 16 hours for flights on an 

aircraft with a Class 1 rest facility and when the flight duty period begins between 0700-

1259. This maximum flight duty time limit is lower if the aircraft has a lesser-quality rest 

facility and/or if the flight duty period begins at an earlier or later time.

To determine the potential cost savings resulting from the elimination of 

augmented maximum flight time limits, the FAA analyzed actual flightcrew member 

schedule data from six carriers. The data included complete duty and flight records for 

every flightcrew member (lineholder and reserve) for one spring month and one summer 
97

month in 2009. Due to the limited sample size, the FAA needed to make several 

assumptions and the resulting potential cost estimate is highly uncertain.

First, only flights conducted with four crewmembers with a flight duration of 12 

to 14 hours were considered for potential cost savings. Flights of less than 12 hours were

not considered because flag and supplemental carriers are allowed to operate flights of 

less than 12 hours with three flightcrew members under existing maximum flight time 

limits. Flights of more than 14 hours were not considered because the maximum flight 

duty time for a flightcrew member under the proposed rule is 16 hours when operating a 

flight augmented with one additional flightcrew member. The two hour difference is 

accounted for by check in preceding the flight and check out time following the flight. 

To the extent that actual check in/check out is greater than or less than the assumed two 

hours, this potential cost savings estimate may overestimate or underestimate the actual 

cost savings.

Second, it is assumed that flightcrew member labor agreements will permit the 

carriers to reduce the number of flightcrew members from four to three. To the extent 

that labor agreements restrict the flexibility of carriers to reduce the number of flightcrew 

members on these flights, this potential cost savings estimate will overestimate the actual 

cost savings.

Third, it is assumed that the crew scheduling needs of carriers will permit them to 

reduce the number of flightcrew members from four to three. To the extent that carriers 

desire to operate a flight with four flightcrew members rather than three flightcrew 
98

members for operational or schedule reliability purposes, this potential cost savings 

estimate will overestimate the actual cost savings.

Fourth, to extrapolate the potential cost savings of those carriers for which FAA 

had data to the entire US air transport industry, it was necessary to assume that the 

scheduling practices of other carriers were similar to the scheduling practices of those 

carriers for which FAA had data. If the scheduling practices of the remainder of the US 

air transport industry materially differ from the scheduling practices of those carriers for 

which FAA had data, this estimate of potential cost savings may over- or understate the 

actual cost savings.

To estimate the potential cost savings of those carriers for which FAA had data, 

flight segments of 12 to 14 hours operated by four flightcrew members were identified. 

Four carriers operated flights that met these criteria. The carriers represented the 

commercial passenger and large cargo industry groups. For the flights that met the 

criteria, the following data was collected: flight hours, flight duty period start hour, and 

aircraft rest facility.

A distribution of flight hours by flight duty period start hour and aircraft rest 

facility was calculated. The share of flight hours for which the maximum flight duty 

period limit applied (16 hours) was used to adjust the number of flight hours. This 

adjusted number of flight hours represented a realistic number of flight hours that could 

be reduced from four flightcrew members to three flightcrew members based on 
99

maximum flight duty period constraints. Table 22 displays the distribution of flight hours 

that was used to make the flight hours adjustment.

Table 22: Flights between 12 and 14 Hours Duration Operated by Four Flightcrew 

Members

Flight Duty 

Period Start 

Aircraft Rest 

Facility

Share of 

Flight Hours

NPRM 

Maximum 

Flight Duty 

Time

0000-0559 1 13.3% 14

0000-0559 2 14.9% 13

0600-0659 1 0.1% 15

0600-0659 2 0.0% 14

0700-1259 1 23.5% 16

0700-1259 2 16.9% 15.5

1300-1659 1 0.6% 15

1300-1659 2 6.8% 14

1700-2359 1 17.0% 14

1700-2359 2 6.9% 13

Next, the number of adjusted flight hours per flightcrew member was calculated. 

This was accomplished by dividing the total flightcrew members by the adjusted flight 

hours. This figure was then annualized. Table 23 presents the annual adjusted flight 

hours saved per flightcrew member.
100

Table 23: Annual Adjusted Flight Hours Saved per Flightcrew Member

Industry Group Hours Saved per 

Crewmember

Commercial Passenger 10.2

Large Cargo 0.6

The estimate of adjusted flight hours saved per flightcrew member was 

extrapolated to a subset of the entire US air transport industry. The subset consisted of 

those passenger carriers that had at least one flight segment exceeding eight hours in the 

year ended June 2009.22 The subset also included all carriers in the large cargo and 

charter passenger industry groups.

While aggregated results are reported in this section, the cost savings estimate 

was conducted on a carrier-specific basis. The adjusted number of flight hours saved per 

flightcrew member was multiplied by the total number of flightcrew members for each 

carrier.23 The total adjusted flight hours saved per flightcrew member was multiplied by 

the average hourly salary for that carrier to result in an estimated cost savings. Table 24 

presents the results of the potential cost savings by industry group.

 

22 These carriers were determined by FAA analysis of Official Airline Guide (OAG) data.

23 Flightcrew member data from FAA OPSS.
101

Table 24: Cost Savings Resulting From Elimination of Maximum Flight Time Limit for 

Augmented Operations

Industry Group Flight Hours 

Eliminated

Average 

Hourly 

Salary

Salary Cost 

Savings

(millions)

Large Cargo 5,890 $121 $0.8

Charter Passenger 702 $92 $0.1

Commercial Passenger 321,247 $129 $44.2

Total 327,839 $45.1

The nominal annual cost savings resulting from the elimination of maximum 

flight time limits on augmented flights is $45.1 million. The nominal cost savings for the 

period of analysis is $451.4 million and the present value cost savings for the period of 

analysis is $276.9 million, as shown in Table 25.
102

Table 25: Cost Savings Resulting from Elimination of Maximum Flight Time Limit for 

Augmented Operations

Year Nominal Cost

(millions)

PV

(millions)

2013 $45.1 $36.8

2014 $45.1 $34.4

2015 $45.1 $32.2

2016 $45.1 $30.1

2017 $45.1 $28.1

2018 $45.1 $26.3

2019 $45.1 $24.6

2020 $45.1 $22.9

2021 $45.1 $21.4

2022 $45.1 $20.0

Total $451.4 $276.9

Flight Operations – Total Cost

The total flight operations cost is composed of the additional crew scheduling 

costs (flightcrew member salary, hotel, and per diem), plus the cost of supplementing a 

two-pilot and flight engineer flightcrew with an additional pilot for flights greater than 

eight hours, plus the computer programming costs, less the cost savings from reduced 

reserves, and less the cost savings resulting from the elimination of maximum flight time 

limits for augmented operations. The net nominal value of the total flight operations cost 

for the period of analysis is $760.3 million, with a present value of $484.2 million. Table 

26 presents the annual nominal and present value total flight operations cost. Table 27 

provides breakdown of the total flight operations cost by cost sub-component. The FAA 
103

asks for comments regarding the flight operations cost, accompanied by a detailed 

justification. 

Table 26: Total Flight Operations Cost

Year Nominal Cost

(millions)

PV Cost

(millions)

2013 $ 113.8 $ 92.9

2014 $ 94.4 $ 72.0

2015 $ 79.7 $ 56.8

2016 $ 76.6 $ 51.1

2017 $ 73.6 $ 45.8

2018 $ 70.5 $ 41.1

2019 $ 67.5 $ 36.7

2020 $ 64.5 $ 32.8

2021 $ 61.4 $ 29.2

2022 $ 58.4 $ 25.9

Total $ 760.3 $ 484.2

Table 27: Total Flight Operations Cost Summary

Cost Sub-Component Nominal Cost

(millions)

PV Cost

(millions)

Crew Scheduling (Resource Cost Only) $ 1,366.7 $ 854.2

Augmented - Suppplement FE $ 66.7 $ 40.9

Computer Programming $ 10.0 $ 8.1

Reduced Reserves ($ 231.7) ($ 142.1)

Augmented - Eliminate Flight Time Limit ($ 451.4) ($ 276.9)

Total Flight Operations $ 760.3 $ 484.2
104

Schedule Reliability 

Schedule reliability refers to the accuracy of the scheduled flight duty period 

compared to the actual flight duty period. Carriers will be required to report the 

scheduling reliability and pairing-specific reliability to the FAA every two months.24 The 

FAA expects carriers to use existing software packages, but carriers will need to 

incorporate and write new reports, which will warn of potential compliance issues with 

the proposed rule. The FAA is aware of at least two smaller operators who run schedule 

reliability programs manually without the support of software. For operators who perform 

the analysis manually, there would be no software investment required. 

Although the reporting requirements would exist for all carriers, the only carriers 

who would incur any significant cost would be the ones who do not schedule reliably, 

that is, those having existing unrealistic scheduled vs. actual times. These carriers would 

have to publish more realistic crew schedules and might have to make some scheduling 

adjustments. The FAA believes that most carriers are already publishing realistic 

schedules overall and there would be a minimal impact on these carriers to publish and 

adjust an existing schedule.

The FAA estimates that each carrier would take about two days to modify their 

scheduling software to create the required report. We assume that the carriers will use 

the equivalent of a GS-14, step 5 employee to do this work. With a fully loaded hourly 

cost of $68.86 and roughly 98 operators, the industry cost would be roughly $108,000 

 

24 The report format would be either .xls or .xml.
105

($88,000 present value) in the first year to make the necessary changes to their 

scheduling programs.

Each operator would take roughly one more day to prepare, troubleshoot, and 

submit the report every two months (six reports per year) to the FAA. In this case the 

FAA assumes that each operator will use the equivalent of a GS-11, step 5 employee with 

a burdened hourly cost of $33.21. The annual cost per operator is $1,600. For the 

industry (98 operators) for the ten-year period of analysis, the total cost is $1.6 million 

($1.0 million present value).

The FAA believes the burden on it for imposing the reporting requirements would 

be 2.5 FTE’s. We assume these employees will be at the GS-13, step 5 grade level (at 

Washington DC locality pay rates) at a burdened annual cost of $130,500. The total 

government cost for the period of analysis is $3.3 million ($2.0 million present value).

The total estimated cost to implement scheduling reliability reporting is $4.9 

million ($3.0 million present value.) Annual costs are shown in Table 28.
106

Table 28: Schedule Reliability Costs25

Nominal

(millions)

P V

(millions)

Nominal

(millions)

P V

(millions)

Nominal

(millions)

P V

(millions)

Nominal

(millions)

P V

(millions)

2013 $0.2 $0.1 $0.3 $0.3 $0.1 $0.1 $0.6 $0.5

2014 $0.2 $0.1 $0.3 $0.2 $0.5 $0.4

2015 $0.2 $0.1 $0.3 $0.2 $0.5 $0.3

2016 $0.2 $0.1 $0.3 $0.2 $0.5 $0.3

2017 $0.2 $0.1 $0.3 $0.2 $0.5 $0.3

2018 $0.2 $0.1 $0.3 $0.2 $0.5 $0.3

2019 $0.2 $0.1 $0.3 $0.2 $0.5 $0.3

2020 $0.2 $0.1 $0.3 $0.2 $0.5 $0.2

2021 $0.2 $0.1 $0.3 $0.2 $0.5 $0.2

2022 $0.2 $0.1 $0.3 $0.1 $0.5 $0.2

Total $1.6 $1.0 $3.3 $2.0 $0.1 $0.1 $4.9 $3.0

Operator Annual Costs Government Cost Implement Report Total Costs

Year

Fatigue Training - Overview

The proposed rule amends existing flight, duty, and rest regulations by requiring 

Part 121 operators to develop fatigue training programs. The intent of the fatigue training 

will be to educate all employees responsible for developing air carrier schedules and 

safety of flight on the symptoms of fatigue, as well as the factors leading to fatigue and 

how to mitigate fatigue-based risk. The employees that will be required to complete 

fatigue training programs include flightcrew members, dispatchers, and management. 

The fatigue training will be incorporated into existing distance learning programs used by 

carriers. Table 29 provides a summary of fatigue training costs, which are explained in 

detail in the following sections.

 

25 Totals may not add due to rounding.
107

Table 29: Fatigue Training Costs Overview

Employee Group Nominal Cost

(millions)

PV Cost

(millions)

Flightcrew Members $ 234.2 $ 149.3

Dispatchers and Management $ 28.1 $ 17.9

Total Fatigue Training $ 262.3 $ 167.2

Fatigue Training – Flightcrew Members

This section describes the approach used to estimate the fatigue training costs for 

flightcrew members (captains, first officers, and flight engineers). Initial and recurring 

fatigue training costs were calculated for all flightcrew members from 2013 to 2022. The 

primary cost component is salary compensation for the time that flightcrew members 

spend in fatigue training. There will be no hotel or per-diem costs because the training 

will be conducted through distance learning programs. 

Flightcrew members’ data were derived from the FAA Operating Specification 

Subsystem (OPSS), which reports the number of flightcrew members as recorded on each 

carrier’s operating certificate. Table 30 shows the total number of captains, first officers, 

and flight engineers by air carrier group. The initial fatigue training cost for 2013 is 

based on the cost of training these flightcrew members.
108

Table 30: Air Carrier Groups for NPRM Cost Analysis

Aircraft Type with Most Block Hours Part 121 

Air Carriers

Part 121

Flightcrew Members

1 Large Cargo Carrier Aircraft > 100 seats equivalent 26 10,125

2 Commercial Passenger Carrier Aircraft > 100 seats 8 39,406

3 Low Cost Carrier Aircraft > 100 seats 9 11,260

4 Regional Passenger Carrier Aircraft 20 < seats < 100 30 20,980

5 Small Cargo Carrier Aircraft < 100 seats equivalent 3 236

6 Small Passenger Carrier Aircraft < 20 seats 4 281

7 Charter Passenger Carrier Aircraft > 100 seats 12 1,230

92 83,518

Group

Total

Source: FAA OPSS, October 2009

Initial fatigue training is five hours. Every flightcrew member will be required to 

undergo initial fatigue training in 2013. In subsequent years, newly qualified flightcrew 

members will be required to undergo initial fatigue training, in addition to previously 

qualified flightcrew members that change employers. The annual retirement rate for 

flightcrew members is 3.3 percent. It is assumed that an equivalent number of flightcrew 

members will be qualified to replace those that retire. The ―churn‖ rate (the share of 

flightcrew members that change employers within a given year) is one percent. 

After undergoing initial fatigue training, each flightcrew member will be required 

to complete two hours of recurring training every year. This training will also be 

incorporated into existing distance learning programs.

The total number of flightcrew members for each year from 2013 to 2022 is 

assumed to be equivalent to the total number of flightcrew members holding certificates 

in October 2009, as recorded by OPSS. Table 31 shows the annual number of flightcrew 

members required to undergo both initial and recurring fatigue training from 2013 to 

2022.
109

Table 31: Flightcrew Members in Fatigue Training

Year Initial 

Training

Recurring 

Training Total

2013 83,518 0 83,518

2014 3,591 79,927 83,518

2015 3,591 79,927 83,518

2016 3,591 79,927 83,518

2017 3,591 79,927 83,518

2018 3,591 79,927 83,518

2019 3,591 79,927 83,518

2020 3,591 79,927 83,518

2021 3,591 79,927 83,518

2022 3,591 79,927 83,518

The average hourly salaries of flightcrew members were then determined based 

on carrier-specific annual salary data from AIR, Inc. The salary data was then converted 

into an average hourly salary. The average hourly salary was calculated by dividing the 

average annual salary by the minimum guaranteed pay credit hours per month as defined 

in pilot labor agreements. The average hourly salaries were updated to 2009 values using 

the Air Transport Association (ATA) Passenger Cost Index. The labor component of the 

cost index was used to update the salaries from Q3 2006 to Q3 2009.

Flightcrew member fatigue training costs are equal to the number of flightcrew 

member training hours multiplied by the average hourly salary. Table 32 presents the 

nominal annual costs of fatigue training for flightcrew members. The total nominal cost 

over the ten-year period is $234.2 million. Table 33 presents the present value annual 
110

costs of fatigue training for flightcrew members. The total present value cost over the 

ten-year period is $149.3 million.

Table 32: Flightcrew Member Fatigue Training Nominal Annual Costs

Year Initial Cost

(millions)

Recurrent Cost

(millions)

Total Cost

(millions)

2013 $ 48.5 $ 0.0 $ 48.5

2014 $ 2.1 $ 18.6 $ 20.6

2015 $ 2.1 $ 18.6 $ 20.6

2016 $ 2.1 $ 18.6 $ 20.6

2017 $ 2.1 $ 18.6 $ 20.6

2018 $ 2.1 $ 18.6 $ 20.6

2019 $ 2.1 $ 18.6 $ 20.6

2020 $ 2.1 $ 18.6 $ 20.6

2021 $ 2.1 $ 18.6 $ 20.6

2022 $ 2.1 $ 18.6 $ 20.6

Total $ 67.2 $ 167.0 $ 234.2
111

Table 33: Flightcrew Member Fatigue Training Present Value Annual Cost

Year Initial Cost

(millions)

Recurrent Cost

(millions)

Total Cost

(millions)

2013 $ 39.6 $ 0.0 $ 39.6

2014 $ 1.6 $ 14.2 $ 15.7

2015 $ 1.5 $ 13.2 $ 14.7

2016 $ 1.4 $ 12.4 $ 13.8

2017 $ 1.3 $ 11.6 $ 12.9

2018 $ 1.2 $ 10.8 $ 12.0

2019 $ 1.1 $ 10.1 $ 11.2

2020 $ 1.1 $ 9.4 $ 10.5

2021 $ 1.0 $ 8.8 $ 9.8

2022 $ 0.9 $ 8.2 $ 9.2

Total $ 50.6 $ 98.7 $ 149.3

Fatigue Training – Dispatchers and Management

The proposed rule also requires that dispatchers and upper management having 

operational control over pilots be given fatigue training. The number of dispatchers in 

the U.S. air transport industry is equal to approximately three percent of the number of 

pilots. The number of management personnel is estimated to be three times the number 

of dispatchers. Therefore, the total number of dispatchers and management personnel 

required to receive fatigue training is estimated to be 12 percent of total flightcrew 

members. The corresponding increase in cost is assumed to be 12 percent. 

The estimated total net present value cost of the proposed fatigue training 

requirements for dispatchers and management personnel over the ten-year period from 
112

2013 to 2022 is $17.9 million. Table 34 lists both nominal and present value fatigue 

training annual costs for dispatchers and management. 

Table 34: Dispatcher and Management Fatigue Training Costs

Year Nominal Cost

(millions)

PV Cost

(millions)

2013 $ 5.8 $ 4.7

2014 $ 2.5 $ 1.9

2015 $ 2.5 $ 1.8

2016 $ 2.5 $ 1.7

2017 $ 2.5 $ 1.5

2018 $ 2.5 $ 1.4

2019 $ 2.5 $ 1.3

2020 $ 2.5 $ 1.3

2021 $ 2.5 $ 1.2

2022 $ 2.5 $ 1.1

Total $ 28.1 $ 17.9

Fatigue Training - Summary

The estimated total net present value cost of the proposed fatigue training 

requirements for flightcrew members, dispatchers, and management personnel over the 

ten-year period from 2013 to 2022 is $167.2 million. Table 35 lists both nominal and 

present value fatigue training annual costs.
113

 Table 35: Total Fatigue Training Costs

Year

Nominal Cost

(millions)

PV Cost

(millions)

2013 $ 54.3 $ 44.3

2014 $ 23.1 $ 17.6

2015 $ 23.1 $ 16.5

2016 $ 23.1 $ 15.4

2017 $ 23.1 $ 14.4

2018 $ 23.1 $ 13.5

2019 $ 23.1 $ 12.6

2020 $ 23.1 $ 11.7

2021 $ 23.1 $ 11.0

2022 $ 23.1 $ 10.3

Total $ 262.3 $ 167.2

Rest Facilities – Overview

The proposed rule establishes maximum flight duty time limits for augmented 

operations that are dependent on the start time of the flight duty period, the number of 

crew assigned to the flight, and the class of rest facility installed on the aircraft. There 

are two types of costs associated with the rest facility cost component of the proposed 

rule. First, there is the cost resulting from the physical installation of the rest facilities in 

the aircraft fleet. Second, there is the loss of passenger revenue when the use of the rest 

facility removes seats from passenger revenue service. Table 36 provides an overview of 

the ten-year costs of the rest facility component of the proposed rule.
114

Table 36: Rest Facility Cost Overview

Cost Area Nominal Cost

(millions)

PV Cost

(millions)

Installation $ 49.8 $ 40.7

Lost Passenger Revenue $ 176.8 $ 108.5

Total Rest Facilities $ 226.6 $ 149.1

The proposed rule establishes detailed specifications for each of the three classes 

of rest facilities. Class 1 rest facilities are most conducive to reducing the risk of fatigue 

in augmented operations; accordingly, the maximum flight duty time permitted for 

augmented operations conducted with Class 1 rest facility-equipped aircraft is greater 

than the maximum flight duty time permitted for augmented operations conducted with 

either Class 2 or 3 rest facility-equipped aircraft. The definitions of the rest facilities are 

as follows:

o A Class 1 rest facility is a bunk or other surface that allows for a flat 

sleeping position and is located separate from both the flight deck and 

passenger cabin in an area that is temperature-controlled, allows the 

crewmember to control light, and provides isolation from noise and 

disturbance.

o A Class 2 rest facility is a seat in an aircraft cabin that allows for a flat or 

near flat sleeping position; is separated from passengers by a minimum of 

a curtain to provide darkness and some sound mitigation; and is 

reasonably free from disturbance by passengers or crewmembers.
115

o A Class 3 rest facility is a seat in an aircraft cabin or flight deck that 

reclines at least 40 degrees and provides leg and foot support. 

Rest Facilities – Installation

There are three cost categories associated with the installation of rest facilities. 

First, there are one-time, non-recurring, design costs. These consist of system, 

development, engineering, analysis, and certification costs. Second, there are ―kit‖ 

equipment costs for the hardware required for each installation. Third, there is the cost of 

the labor required for rest facility installation.

The FAA obtained detailed cost estimates from two supplemental type certificate 

(STC) holders. Their estimates indicate that Class 1 facilities are much higher in cost 

relative to Class 2 and 3 facilities, which are roughly equivalent. For the purposes of this 

analysis, FAA averaged the cost estimates from the two STC holders and summarized the 

costs into a per-installation cost. Table 37 presents the cost per installation used for this 

analysis. 

Table 37: Cost per Rest Facility Installation

Rest Facility Class Cost per Installation

Class 1 $259,000 - $1,500,000

Class 2 $46,000

Class 3 $31,000
116

In order to estimate the total cost of on board rest facilities, the FAA multiplied 

the unit costs by the number of aircraft that could be affected by the rule (defined as 

aircraft that operate long range). FAA believes that in the long term it is more cost 

effective for carriers to install rest facilities than to add pilots to the flightcrew. FAA 

believes that no Class 2 or Class 3 rest facility will need to be added or upgraded on any 

of the aircraft currently used in international transportation because existing business or 

first class seats meet the requirements as Class 2 or Class 3 rest facilities. 

Rest facilities will need to be installed or upgraded on 104 aircraft used in 

international service. Installation will be completed by the end of 2013. Nineteen of 

these aircraft will have bunks installed at $1.5 million per aircraft and the remaining 85 

aircraft will have the single bunk facility upgraded to a double bunk facility at $250,000 

per aircraft. The total estimated cost is $49.8 million ($40.7 million present value). This 

cost estimate does not include any weight penalty costs. The FAA solicits public input 

regarding the weight penalty costs. . 

Rest Facilities - Loss of Passenger Revenue

There will be some passenger revenue loss associated with the use of rest 

facilities in augmented operations. The FAA found that it is always cheaper to use a 

higher level rest facility than to add a flightcrew member. As discussed in the previous 

section, Class 1 rest facilities will be installed in locations so that there is no impact on 

passenger revenue. Existing business and first class seats meet the criteria to serve as 

Class 2 and Class 3 rest facilities. Currently, most carriers assign flightcrew members to 
117

rest in coach seats during augmented operations. The proposed rule will result in the loss 

of passenger revenue because carriers will need to assign flightcrew members to rest in 

Class 2 or 3 rest facilities (i.e. business/first class seats) rather than cheaper coach seats. 

The loss of passenger revenue is thus equal to the fare difference between business/first 

class seats and coach seats.

FAA analyzed one year of actual flights to determine the categories and total 

number of aircraft and flights affected. We multiply the estimated number of affected 

flights by the revenue lost when Class 2 or Class 3 rest facilities are used. The weighted 

average additional incremental loss for a Class 2 rest facility26 is $2,034 and the weighted 

average cost for a Class 3 rest facility27 is $5,084. We multiply the estimated number of 

annual flights by the appropriate estimated cost of the revenue lost. The total cost would 

be $17.7 million.

Table 38 shows the estimated annual operations for the most cost effective 

solutions based upon the proposed constraints, equipment, and number of pilots. The 

FAA has analyzed the duty matrix and evaluated it in terms of the additional costs per 

pilot28 versus the costs of additional facilities and estimates that in the long run it would 

always be less costly to provide rest facilities rather than to add a pilot.29 Our analysis 

assumes that there are always three pilots available per flight and that carriers attempt to 

minimize the potential flightcrew costs. For the flights that are 15.5 hours or more, a 

 

26 Weighted average price difference between coach and business class

27 Weighted average price difference between coach and estimated first class 

28 To estimate the hourly pilot cost of $625, we divide the approximate annual burdened pilot cost of 

$300,000 by the estimated hours flown per year of 480 (40 hours per month times 12 months per year). 

29 Once the flight time exceeds 14 hours, additional crew would be required. 
118

Class 1 rest facility would be required, which would not result in any passenger revenue 

loss. 

Table 38: Estimated Annual Operations for the Most Cost Effective Solutions

Total

Annual 

Operations

Passenger 

Revenue 

Loss per 

Operation

Nominal 

Annual Cost

Annual 

Operations

Passenger 

Revenue 

Loss per 

Operation

Nominal 

Annual Cost

Nominal 

Annual Cost

0000-0559 157 $5,084 $797,082 144 $2,034 $293,453 $1,090,535

0600-0659 0 $5,084 $0 0 $2,034 $0 $0

0700-1259 835 $5,084 $4,247,137 760 $2,034 $1,544,990 $5,792,127

1300-1659 947 $5,084 $4,814,215 1,259 $2,034 $2,560,179 $7,374,394

1700-2359 550 $5,084 $2,795,734 309 $2,034 $628,148 $3,423,882

Total 2,489 $5,084 $12,654,167 2,472 $2,034 $5,026,770 $17,680,937

Duty Period 

Start Time

Class 2 Rest Facility Duty Time

Rest Facilities – Summary

The installation and upgrade of aircraft rest facilities and the lost passenger 

revenue resulting from the use of the rest facilities results in a ten-year nominal cost of 

$226.6 million ($149.1 million present value.) Table 39 presents the annual nominal and 

present value costs of the rest facility component of the proposed rule.
119

Table 39: Rest Facilities Cost Summary

Year Nominal Cost 

(millions)

PV Cost 

(millions)

2013 $ 67.5 $ 55.1

2014 $ 17.7 $ 13.5

2015 $ 17.7 $ 12.6

2016 $ 17.7 $ 11.8

2017 $ 17.7 $ 11.0

2018 $ 17.7 $ 10.3

2019 $ 17.7 $ 9.6

2020 $ 17.7 $ 9.0

2021 $ 17.7 $ 8.4

2022 $ 17.7 $ 7.9

Total $ 226.6 $ 149.1

Summary of Benefits and Costs

Following NTSB recommendations regarding pilot fatigue, labor and industry 

worked together to provide the basis of this rulemaking. Furthermore, Congress has 

directed the FAA to issue a rule addressing pilot fatigue. We have validated the need for 

this rule in the benefit discussion. Based on the expected effectiveness of this proposed 

rule at preventing fatigue accidents with an averted fatality valued at $6 million, the 

simulation methodology produced benefits of $659.4 million with $463.8 million in 

present value. The total estimated costs of the proposed rule over 10 years are $1.25 

billion ($804 million at present value). There is over a 7 percent probability that 

undiscounted cost of avertable passenger airplane accidents would exceed $1.25 billion 

and over a 10 percent probability the present value of the cost of avertable passenger 
120

airplane accidents would exceed $796 million. The benefits from a near term 

catastrophic accident in a 150-passenger airplane with average load factor exceeds the 

cost of this rule. If the value of an averted fatality were increased to $12.6 million, the 

present value of the benefits would equal the present value of compliance costs. 

In addition, the FAA has identified two additional areas of unquantified benefits: 

preventing minor aircraft damage on the ground, and the value of well rested pilots as 

accident preventors and mitigators. Due to data limitations, the FAA was unable to 

estimate the cumulative effect of preventing minor aircraft damage on the ground, but if 

the rule were to reduce damage by about $600 million over 10 years ($340 million 

present value) it would break even in terms of net benefits. These considerations lend 

weight towards moving ahead with this proposal. FAA invites comment on this issue. 
121

Appendix A

Pilot Deviations and Accidents by Duty Hours

a. Pilot Deviations

Between 1987 and the present, there were 686 records of pilot deviations in part 121 

operations that contain information on pilot duty time in the 24 hours preceding the 

deviation (cases where equipment failure was listed for the deviation were excluded from 

the data set). Table A-1 and Figure A-1 below show the frequency of pilot deviations in 

relation to duty time. 

As part of the analysis for this rulemaking, the FAA obtained data on pilot work patterns 

from ten carriers covering one month of flight activity during 1999.30 These data were 

used to create profiles of the work patterns of the pilot population. Data for nine carriers 

were provided by pilot labor unions. The FAA also obtained data on actual pilot use 

from one major part 121 air carrier that was added to data from the other carriers.31

 

30 Ibid.

31 FAA has also received more recent data on pilot work patterns from six carriers, covering two months of 

actual flight activity during 2009 for each carrier. These data on flight crew exposure to risk are currently 

being characterized and analyzed by FAA, and these data have not yet been organized around the “for 

each duty hour, how many duty hours have occurred in the prior 24 hours?” parameter. For this reason, 

the comparisons to occurrences of pilot deviations and accidents are made to the 1999 pilot work activity 

data. 
122

Table A-1. Distribution of Pilot Deviations by Duty Hours

Duty Time in the Last 24 hours Pilot Deviations Percent Cumulative Percent

0 – 2 hours 62 9.0 9.0

2 – 4 hours 103 15.0 24.0

4 – 6 hours 127 18.5 42.5

6 – 8 hours 136 19.8 62.3

8 – 10 hours 110 16.0 78.3

10 – 12 hours 82 12.0 90.3

13 – 14 hours 29 4.2 94.5

15 – 16 hours 20 2.9 97.4

16 + hours 17 2.5 99.9

Total 686 99.9

Figure A-1. Distribution of Pilot Deviations by Duty Hours

. 

The data was converted into one record for each pilot with a scheduled (or for one carrier, 

an actual) line of flying for the month. Each pilot record tracked a pilot’s activity for 

every hour in the entire month. The beginning and end of each trip segment were 

recorded for each pilot and put into a database. Parameters of interest were then 

calculated such as the length of duty periods, flight time and duty time per day or in the 

last 24 hours, rest time, and the numbers of takeoffs and landings. The analysis tracked 

these activities in local time as well as base time (defined as the time at the location 

where the pilot began a multi-day trip). 
123

Although some carriers provided data for both captains and first officers, other carriers 

provided data for captains only. The study used data only for captains in the accident 

analysis to prevent weighing one carrier’s responses more heavily than another in 

measuring exposure. The FAA found there were differences between the two sets of data 

in some work schedule parameters examined. . 
124

Table A-2. Distribution of Pilot Duty Time in Prior 24 Hours and Pilot Deviations

Figure A-2. 

Pilot Prior 

Duty Time 

Exposure v Pilot Deviations

0

0.05

0.1

0.15

0.2

0.25

0 to 22 to 44 to 66 to 8

8 to 10

10 to 1212 to 14

14 or more

Exposure

Proportion

Deviations

Proportion

Captain’s Duty Time Pilot Deviations

Hours Hours Percentage Deviations Percentage

0 to 2 284,128 23% 316 9%

2 to 4 279,531 22% 427 12%

4 to 6 261,051 21% 597 17%

6 to 8 212,764 17% 686 20%

8 to 10 138,749 11% 644 19%

10 to 12 64,147 5% 476 14%

12 to 14 14,798 1% 218 6%

14 or more 1,176 <1% 106 3%

Total 1,256,344 3,470
125

Table A-2 and Figure A-2 suggest that pilot deviations are less likely to occur when a 

pilot has less than 6 hours of duty time during the past 24 hours than if the pilot has more 

than 6 hours of duty time during the past 24 hours. Moreover, pilot deviations after 6 

hours of duty time are much higher than one would expect given exposure. This finding 

is consistent with the above fatigue science findings. 
126
127

Appendix B

Statistical Tests of Relationship between Length of Duty Time and Accidents

The Flight Crewmember Duty and Rest Requirements NPRM accident analysis for the 

United States air transportation industry is based on statistical comparison of domestic flight 

crew duty data from six operators, based on their flight crews’ actual activity during a spring and 

summer month of 2009. Two statistical testing methods were used to examine the distribution of 

pilot duty hours and the distribution of duty hour features of accident histories. The statistical 

comparisons were made for the hour within a pilot duty period that a accident occurs.32 If the 

 

32 To illustrate, suppose the total available pilot duty data are comprised of two pilots, one of whom serves a duty 

period that is seven hours in length, and the second of whom serves a duty period of nine hours in length. In this 

case, the data set characterizing pilot duty by hour in duty period contains two hours of duty in the first hour of 

the duty period, two hours of duty in the second hour of the duty period, and so forth, culminating in two hours of 

duty in the seventh hour of the duty period, one hour of duty in the eight hour of the duty period, and one hour of 

duty in the ninth hour of the duty period. If, to continue the example, one of the pilots experiences an occurrence 

of interest in the seventh hour of her duty period, then the data set for “occurrences of interest” would contain 

one instance, taking place in the seventh hour of the duty period.
128

likelihood of a human factors accident occurring is the same for all hours within a duty period, 

then the distribution of accident occurrence by the hour within a duty period should not be 

significantly different from the distribution of pilot duty hours by hour within the duty period, 

and the relative frequency of the occurrence of such accidents would be expected to resemble the 

relative frequency of hours within pilot duty periods. The purpose of the statistical tests is to 

compare these two distributions and assess their similarity to or dissimilarity from one another 

using accepted statistical tools.

There are 43 accidents in the data set. They include accidents involving FAR part 121 

operators that resulted in significant aircraft damage, serious injury to passengers or worse 

outcomes, and occurred between 1990 and 2009. They are accidents for which mechanical 

failures were not causal and in which human factors issues involving the flight crews were 

pertinent. NTSB investigations and reports on some of these accidents cited ―fatigue‖ or pilot 

rest and duty issues as relevant to the accident. The purpose of the statistical analysis is to 

examine the relationship if any between human factor accidents and duty patterns, the accident 

data set also includes human factors accidents for which no citation of ―fatigue‖ or similar 

factors was made.

Duty period characteristics from the accident pilot histories are then categorized in a 

comparable way, with a count of all accidents in the data set that occurred in the first or second 

hour of the pilot’s duty period, the third or fourth hour of the pilots duty period, and so forth. 

This initial data set for 2009 pilot work patterns and accident incidence is reported in Table B-1.
129

Table B-1. Pilot Duty and Accident Incidence by Hour in Duty Period

Hour 

Block

Exposure 

Duty Hrs

Percentage 

of Duty 

Hrs Accidents

Percentage 

of 

Accidents

0 to 1 195,691 13.34% 0 0.00%

1 to 2 192,786 13.14% 7 16.28%

2 to 3 187,372 12.77% 4 9.30%

3 to 4 175,247 11.95% 4 9.30%

4 to 5 160,567 10.95% 2 4.65%

5 to 6 141,538 9.65% 4 9.30%

6 to 7 119,601 8.15% 5 11.63%

7 to 8 98,501 6.71% 6 13.96%

8 to 9 76,547 5.22% 1 2.33%

9 to 10 54,501 3.72% 2 4.65%

10 to 11 34,533 2.35% 1 2.33%

11 to 12 19,078 1.30% 1 2.33%

12 to 13 8,143 0.56% 1 2.33%

13 to 14 1,867 0.13% 2 4.65%

14 to 15 631 0.04% 0 0.00%

15 to 16 238 0.02% 2 4.65%

16 to 17 93 0.01% 0 0.00%

17 to 18 41 0.00% 1 2.33%

Total 1,466,975 43

While hour by hour duty period characteristics represent a sensible approach to 

identifying pilot exposure to human factors accident risk, some adjustment to these data is 

necessary for a valid comparison, since in some cases specific duty hours (or percentages of duty 
130

hours) can be shown to be unrelated to the possibility of aviation accident or mishap. For this 

analysis, two specific adjustments are considered. 

First, it is nearly always the case that the first hour of a pilot’s duty day involves check-in 

and information gathering that takes place on the ground, prior to the first take off of the day. 

Naturally enough, every duty period has a first hour, and as can be seen in Table 1 above, the 

first hour makes up a significant percentage of total pilot duty hours, even though no flight 

activity occurs during it. For this reason, in the following statistical tests the first hour of pilot 

duty periods is omitted from consideration.

Second, once pilots have completed their first flight segment of the day (which lasts 

varying amounts of time depending on flight distance, itinerary, etc.), during any given hour of 

pilot duty periods, some percentage of pilots are on the ground between flight segments and 

involved in post-flight or pre-flight activities. Average flight segment lengths vary by airline and 

by airline business model, so it is not possible to develop specific modeling approaches to this 

issue.

In the pilot exposure data made available by airlines for this analysis, out of 1,271,284 

total duty hours served (a total which excludes duty hours that are the pilot’s first duty hour of 

the day), there are 985,566 flight hours. This suggests that about 77 per cent of duty hours 

actually involve accident risks stemming from flight activity, and that some adjustment to the 

distribution of duty hours counted over the duty period would be appropriate for accurately 

reflecting exposure to human factors accident risk. Since duty hours begin to fall off 

significantly after the eighth hour of duty, as shown in Table B-1 above, and since once the final 

hours of a duty period are reached it is more likely that the pilot is in flight and performing his or 

her final segment of the duty day, this adjustment in the exposure data is accomplished by 

reducing the duty hours reported between the third and eighth duty hours of the duty period by 

30 percent. The effect of this adjustment to exposure risk is illustrated in Table B-2, which 

updates the ―raw‖ exposure data from Table B-1.

Table B-2. “Risk Adjusted” Pilot Duty and Accident Incidence by Hour in Duty Period

Hour 

Block

Exposure 

Duty Hrs

Percentage 

of Duty 

Hrs Accidents

Percentage 

of 

Accidents

0 to 1 n/a

1 to 2 192,786 13.14% 7 16.28%
131

2 to 3 187,372 12.77% 4 9.30%

3 to 4 122,673 8.36% 4 9.30%

4 to 5 112,673 7.66% 2 4.65%

5 to 6 99,077 6.75% 4 9.30%

6 to 7 83,721 5.71% 5 11.63%

7 to 8 68,951 4.70% 6 13.96%

8 to 9 53,583 3.65% 1 2.33%

9 to 10 54,501 3.72% 3 6.98%

10 to 11 34,533 2.35% 1 2.33%

11 to 12 19,078 1.30% 1 2.33%

12 to 13 8,143 0.56% 1 2.33%

13 to 14 1,867 0.13% 1 2.33%

14 to 15 631 0.04% 0 0.00%

15 to 16 238 0.02% 2 4.65%

16 to 17 93 0.01% 0 0.00%

17 to 18 41 0.00% 1 2.33%

Total 1,039,684 43

The Pearson’s Chi Squared ―goodness of fit‖ test33 is a frequent approach to testing 

whether these two distributions – expressed as histograms reporting the percentage of each 

variable within each two hour time bucket – have a statistically significant difference. If there is 

no statistically significant difference between the two distributions, there is limited evidence to 

 

33 A description of the Chi Square goodness of fit test can be found in any introductory statistics text. A 

comprehensive discussion of the test, with references, can be found online at 

http://en.wikipedia.org/wiki/Pearson’s_chi-square_test
132

support a claim that accident likelihood changes with changes in duty hour. An interpretation of 

this outcome is that the risk of accident does not vary with duty time. Thus, for the statistical 

test, the null hypothesis is that there is not a statistically significant difference between the two 

distributions.

To conduct the Chi Squared test, pilot duty hours from the exposure data set 

(disregarding the first hour of each pilot duty period) are divided into distinct categories of two 

hours in length: duty hours that occurred in the second or third hour of a duty period, duty hours 

that occurred in the fourth or fifth hour of a duty period, and so forth, with the final bucket made 

up of duty hours that occurred in the 14th or greater hour of a duty period.

The test statistic is taken from a Chi Squared distribution with n-1 degrees of freedom, 

where n is the number of histograms used in the comparison of exposure and accident data. In 

this case there are seven degrees of freedom for the text. Table 3 reports these test results and 

the critical values for the Chi Squared test at the 5% and 10% significance levels. The calculated 

Chi Squared test value of 131.5 exceeds these critical values, indicating that the distribution of 

exposure hours and the distribution of accident incidence within duty periods are not the same, 

although it is important to recognize that this outcome is driven largely by the comparison 

between exposure hours in the 14th and greater hours of pilot duty periods and the frequency of 

accidents occurring during those later hours of pilot duty periods.

Table B-3. Chi Squared Results for Comparing Time in Duty Period Exposure and 

Accident Characteristics

Hour in Duty 

Period Pilot's Hours Exposure Proportion Accidents Accident Proportion

Relative 

Proportion

2nd & 3rd 380,158 0.37 11 0.26 0.70

4th & 5th 235,070 0.23 7 0.16 0.72

6th & 7th 182,797 0.18 9 0.21 1.19

8th & 9th 122,534 0.12 7 0.14 1.18

10th & 11th 89,034 0.09 4 0.09 1.09

12th & 13th 27,221 0.03 2 0.05 1.78

14th + 2,870 0.00 4 0.09 36.70

Total 1,039,684 43 
133

Calculated Chi2: 131.5 10% Chi2: 10.6

Degrees of 

Freedom: 6 5% Chi2: 12.6

The data underlying the Chi Squared comparison is shown graphically in Figure B-1. below.

Figure B-1. Pilot Duty Hours and Accidents by Hour in Duty Period – Accidents 1990 to 2009

A second statistical test was also used to assess the significance, if any, of differences 

between the distribution of pilot duty hours observed in the 2009 exposure data and the 
134

distribution of the set of human factors accidents by the time at which the accidents occurred in 

the pilot’s duty period. This test, which is also used to examine the similarity of distributions, is 

the two sample Kolmogorov-Smirnov test (henceforth, K-S test), which is used to test whether 

two samples can be regarded as samples from a single distribution.34 

The K-S test is performed by expressing the exposure data and accident data as two 

separate cumulative distribution functions, each running from 0 to 100 per cent. To make this 

comparison, some adjustment of the data sets being compared is made.

Because data on accident time (that is, time within a duty period) exists at the hour and 

minute level, the exposure data is converted from hourly to ―by minute‖ data by dividing the 

percentage share of duty hours within an hour block by 60. Consider a simple example where 

duty periods last 1 or 2 hours, and of 100 total duty hours, 60 are in the first hour block (from 0 

to 1 hours) and 40 are in the second hour block (from 1 to 2 hours). In this case, 60 percent of 

duty hours are within the first hour block, and 40 percent are within the second hour block. To 

convert this exposure profile from an hour basis to a minute basis, these percentages are divided 

by 60 (minutes per hour). Thus, each minute within the first hour block represents one percent 

of the total minutes contained by the 100 duty hours, and each minute within the second hour 

block represents 0.667 percent contained by the 100 total duty hours.

Table B-4 presents the ―risk adjusted‖ distribution of duty hours that is shown in TableB2 above along with the ―percentage of duty minutes within each duty hour‖ calculation described 

above. In the 2009 exposure dataset for duty hours, about 13.1 percent of observed duty hours 

occur in someone’s second hour within a duty period (when first flights of the day commence 

and exposure to risk begins, as discussed above), and if this percentage share is subdivided into 

minutes, each of the 60 minutes with this second duty hour represents about 0.219% of all duty 

minutes over the 17 hour span between the second hour and the 18th. The reported exposure data 

also includes the reduction by 30 per cent of duty hours between the third and ninth hours in duty 

periods, to reflect the fact that during the middle portions of the duty day, some percentage of 

pilots are on the ground between flights. They are actively engaged in their duties during these 

times, but they are not at risk of an in flight accident.

 

34 A description of the Kolmogorov-Smirnov test can be found in more advanced statistics texts. A comprehensive 

discussion of the test, with references, can be found online at http://en.wikipedia.org/wiki/KolmogorovSmirnov_test
135

Table B-4. Percentage Distribution of Duty Hours and Minutes, Domestic Pilot “Hour in 

Duty Period” Exposure Set

Hour 

Block

Exposure Duty 

Hrs

Percentage of 

Duty Hrs

Percentage per 

Duty Min Accidents Percentage of Accidents

0 to 1 n/a

1 to 2 192,786 13.14% 0.2190% 7 16.28%

2 to 3 187,372 12.77% 0.2129% 4 9.30%

3 to 4 122,673 8.36% 0.1394% 4 9.30%

4 to 5 112,397 7.66% 0.1277% 2 4.65%

5 to 6 99,077 6.75% 0.1126% 4 9.30%

6 to 7 83,721 5.71% 0.0951% 5 11.63%

7 to 8 68,951 4.70% 0.0783% 6 13.96%

8 to 9 53,583 3.65% 0.0609% 1 2.33%

9 to 10 54,501 3.72% 0.0619% 3 6.98%

10 to 11 34,533 2.35% 0.0392% 1 2.33%

11 to 12 19,078 1.30% 0.0217% 1 2.33%

12 to 13 8,143 0.56% 0.0093% 1 2.33%

13 to 14 1,867 0.13% 0.0021% 1 2.33%

14 to 15 631 0.04% 0.0007% 0 0.00%

15 to 16 238 0.02% 0.0003% 2 4.65%

16 to 17 93 0.01% 0.0001% 0 0.00%

17 to 18 41 0.00% 0.0000% 1 2.33%

Total 1,039,684 43
136

Also shown in Table B-4 are 43 accidents, which took place between 1990 and 2009, for which 

adequate data exists for identifying when within a duty period the accident occurred. Thus, each 

accident represents 1/43, or 2.33 percent, of the total data set of accidents. These accidents 

occurred at duty times up to 17 and a half hours, so the comparison constructed for the K-S test 

procedure looks at exposure data periods up to 18 hours in length, although there are relatively 

very few of these extremely long duty periods in the exposure data. A graphical comparison of 

the cumulative duty minute distribution and the cumulative distribution of accidents by duty 

minute is shown in Figure B-2. 

Figure B-2. Comparison of Exposure and Accident Cumulative Percentage Profiles

As shown in the figure, the two cumulative curves for exposure and accident duty times each rise 

to 100 percent, but do so along different paths or trajectories. The purpose of the K-S test (like 

that of the Chi Squared test) is to test whether the two curves can be regarded as representing 

samples from distinct probability distributions. In these tests, the statistical ―null hypothesis‖ is 

that the two distributions of events (duty hours served as a measure of exposure to risk, and 
137

accidents by the hour within the duty period at which the accident occurred) are the same. If the 

statistical test (Chi Squared or K-S) results in the rejection of this null hypothesis at some level 

of significance, then with that level of confidence it can be asserted that exposure to risk is not 

summed up by relative numbers of hours within specific hours within the duty period, and that 

other factors, such as whether the duty hour at which an accident occurs is early or late in a duty 

period, also contribute to accident risk. If the two curves are distinct from one another at a 

statistically significant level, it could be concluded that a pilot’s time within a duty period does 

influence the risk or likelihood of a human factors related accident occurring, and in this 

particular case, this risk increases with the duty time.

The testing procedure for the K-S test of significant difference between two curves involves 

measuring the distance between the curves at each point. The test statistic is the maximum of 

those distances, taken over the whole domain over which the two curves reach their terminal 

value of 100 percent. In the present example, the maximum value is 0.2107, which occurs at 

minute 309, where the cumulative percentage for the exposure data reaches 60.6 per cent and the 

cumulative percentage for the accident data reaches 39.5 per cent. (The point or minute at which 

the maximum distance between these cumulative percentage curves occurs is not relevant to the 

test result.) This distance is shown in Figure B-3.

Figure B-3. Test Statistic for Comparison of Exposure Duty Hour Curve and Accident Curve

The level of significance indicated by the test statistic depends on the number of accidents, since 

that sample size is much smaller than the sample size of exposure hours. For each significance 

level of interest, such as 0.20, 0.15, 0.10, 0.05 or 0.01, the critical value is calculated by dividing 

a specific factor by the square root of the sample size of 43. Table B-3, shows these factors and 

the associated critical value for the sample size of 43.

Kolmogorov-Smirnoff Comparison, Starting at Minute 61 of Duty Period with 30% Mid-Duty Day Adjustment 43 Accidents 1990 - 2009

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 61 121 181 241 301 361 421 481 541 601 661 721 781 841 901 961 1021

Minute of Duty Period Percentage of Total Duty Hours or Total Accidents

Empirical Distribution Duty Hours Empirical Distribution Accidents 

Dmax = 0.2107 > D0.05 = 0.2074
138

Table B-3. Critical Values for K-S Testing (Sample Size of 43)

Level of 

Significance

K-S Test 

Factor 1/root(43)

K-S Test 

Critical Value

Test 

Statistic

0.20 1.07 0.152 0.1632

0.15 1.14 0.152 0.1738

0.10 1.22 0.152 0.1860

0.05 1.36 0.152 0.2074 0.2107

0.01 1.63 0.152 0.2486

Comparison of these critical values with the test statistic at the 0.05 significance level of 0.2074 

indicates that at that level of significance, the difference between the cumulative curve of 

exposure times within duty periods and the cumulative curve of times within duty periods at 

which accidents occurred can be regarded as statistically significant. This can be interpreted as 

indicating that the frequency with which accidents from the recent past happened within specific 

hours within a duty period is not related simply to the proportion of duty hours that pilots serve 

within specific hours of their duty period, and that the risk of an accident is not uniform across 

all hours within duty periods. That is, with this level of significance, the hour of the duty period 

matters for accident risk.
139

Appendix C

Pilot Deviations by Time of Day

One way to study pilot deviations is examine how they vary throughout the day. Deviations 

represent multiple types of violations, ranging from serious runway incursions interfering with 

landings and takeoffs to simple airspace transgressions. Given their potential severity, they are 

recorded system-wide because they are all assumed to represent precursors to potential accidents. 

Each violation record contains multiple fields addressing the aircraft, the environment and the 

pilot involved in the incident. These incidents number in the thousands. These records provide a 

needed large sample to address the fatigue issue. In particular, pilot deviations carry several data 

fields considered related to pilot fatigue. They are: (a) duty time in the last 24 hours before the 

violation, (b) flight time in the past 24 hours before the violation, (c) leg time before the 

violation, (d) time of day, and (e) season of the year. 

Pilot deviations are actions of the pilot which violate the Code of Federal Regulations (CFR), 

previously called Federal Aviation Regulation (FAR). Pilot deviations also take place when the 

North American Aerospace Defense Command (NORAD), Air Defense Identification Zone 

(ADIZ) tolerance is neglected. Starting with 1987, pilot deviations have been documented by air 

traffic and flight standards on FAA Form 8020-17, Preliminary Pilot Deviation Report, and FAA 

Form 8020-18, Investigation of Pilot Deviation Report. The results are then coded into the Pilot 

Deviation System (PDS) database. The FAA uses the PDS database to monitor the number of 

events, type of events (e.g., air deviations, surface deviations, or airspace violation) and the 

factors related to the events. The FAA issues one report for each pilot deviation regardless of the 

number of aircraft involved. The information in the database reflects a mix of preliminary and 

final reports. Pilot deviations require 90 days to stabilize due to reporting procedures, volume, 

and workload.

A large sample from the database ranging from 1987 to present was secured and analyzed in 

multiple ways. To focus strictly on fatigue as the key issue, records with the following conditions 

were removed from the analysis:

(a) improbable values, blanks, ―zero‖ in the field of interest,

(b) non- Part 121 operations, and

(c) deviations caused by adverse weather or equipment failure, two causes not truly being 

pilot-related.
140

As can be seen in table C-1 and figure C-1 pilot deviations are more likely to occur in the 

afternoon than any other time of day. Also, there are few pilot deviations between 12:00 

midnight and 6:00 am. 
141

Table C-1. Distribution of deviations by local hour of the day.

Local hour of the day 

when deviation occurred

Pilot 

deviations Percent

Cumulative 

Percent

0:01 – 2:00 137 4.5 4.7

2:01 – 4:00 80 2.6 7.4

4:01 – 6:00 57 1.9 9.4

6:01 – 8:00 193 6.4 16.0

8:01 – 10:00 218 7.2 23.4

10:01 – 12:00 286 9.4 33.2

12:01 – 14:00 392 12.9 46.6

14:01 – 16:00 398 13.1 60.2

16:01 – 18:00 387 12.8 73.4

18:01 – 20:00 391 12.9 86.8

20:01 – 22:00 269 8.9 96.0

22:01 – 24:00 117 3.9 100.0

Total 2,925

Figure C-1. Distribution of deviations by local hour of the day.
142

Deviations

0

100

200

300

400

500

0:01 - 2:002:01 - 4:004:01 - 6:006:01 - 8:00

8:01 - 10:00

10:01 - 12:0012:01 - 14:0014:01 - 16:0016:01 - 18:0018:01 - 20:00

20:01- 22:0022:01 -24:00

Hour of Day

Number of Deviations

Deviations

The distribution of pilot deviations can be compared to the distribution of aircraft activity to see 

if pilot deviations are more than would be expected for any portion of the day. In this analysis 

the count of takeoffs and landings by time of day were used as a measure of aircraft activity. 

The results are presented in table C-2 and figure C-2.

Table C-2 Pilot Deviations and Take Off and Landing Operations By Time of Day
143

Hours Deviations Percent Operations Percent

0:01 - 2:00 137 4.7 468,610 2

2:01 - 4:00 80 2.7 240,000 1

4:01 - 6:00 57 1.9 441,659 1.9

6:01 - 8:00 193 6.6 2,094,083 8.9

8:01 - 10:00 218 7.5 2,594,592 11

10:01 - 12:00 286 9.8 2,788,547 11.8

12:01 - 14:00 392 13.4 2,784,202 11.8

14:01 - 16:00 398 13.6 2,772,942 11.8

16:01 - 18:00 387 13.2 2,917,272 12.4

18:01 - 20:00 391 13.4 2,829,391 12

20:01- 22:00 269 9.2 2,265,871 9.6

22:01 -24:00 117 4 1,384,053 5.9

Total 2,925 23,581,222
144

Figure C-2 Pilot Deviations and Take Off and Landing Operations By Time of Day

0

2

4

6

8

10

12

14

16

0:01 - 2:002:01 - 4:004:01 - 6:006:01 - 8:00

8:01 - 10:00

10:01 - 12:0012:01 - 14:0014:01 - 16:0016:01 - 18:0018:01 - 20:00

20:01- 22:0022:01 -24:00

Hour of Day

Percent

Deviations

Operations

Table C-2 and Figure C-2 show that a higher percentage of deviations occur late at night (0:001 

am to 4:00 am) than the percentage of takeoff and landing operations during those hours. The 

same can be said the afternoon and evening (12:01 pm to 10:00 pm). During the morning (4:01 

am to 12:00 n) and late evening (10:01 pm to 12:00 m), the percentage of pilot deviations is 

lower then the percentage of operations during those times. That pilot deviations are high 

relative to aircraft activity between midnight and 4:00 am is not too surprising given that people 

least alert during that period of time when they are in their window of circadian low, but it is a 

bit of a surprise that deviations are relatively low between 10:00 pm and midnight when many 

people go to sleep. Most people are rested from a night’s sleep and are most alert during the 

morning so deviation should be expected to be relatively low during that time. During the 

afternoon and evening, many people begin to become tired and less alert and deviations are 

expected to increase during that time.

Sometimes incidents have a more serious consequence than a deviation citation; sometimes the 

incident becomes an accident. The above findings for pilot deviation incidents also apply to 

accidents.