9.75 hours under a 10-hour limit to maintain the same cushion. Finally,
to the extent that FMCSA has overstated the effects of the options, the
effects would apply to both costs and benefits, that is, both would be
lower. The result would be that the actual impacts would be less costly
than estimated and that much easier for the industry and the economy to
absorb and adjust to, while not changing the relationship of benefits
to costs.
Comments and Responses on Impacts of the Proposed Rule on Carrier
Operations
    Edgeworth asserted that FMCSA's cost analysis is highly
inconsistent with its previous RIAs: ``In the 2007 RIA * * * FMCSA
tested the current rules against an option which reduced the maximum
consecutive driving time to 10 hours and eliminated the restart
provision--i.e., a policy similar to FMCSA's Option 2 in the proposed
rule. FMCSA estimated that the restrictions would reduce industry
productivity by 7.1 percent.''
    Edgeworth's assertion that reducing driving time to 10 hours and
eliminating the restart position is a policy similar to FMCSA's Option
2 in the proposed rule is incorrect. The option it refers to in the
2007 analysis eliminated the restart, reverting to the old limits of
60/7 or 70/8. Option 2 in the proposed rule allowed a 34-hour restart
every single week for the vast majority of drivers and every second
week for those driving maximum hours. Comparing the 2007 option with
the 2010 option is invalid because the options produce very different
effects on productivity. A better comparison is between the option that
did nothing but limit driving to 10 hours in the 2007 analysis and
FMCSA's current estimate of the impact of a 10-hour driving limit taken
by itself. The 2007 analysis estimated the incremental cost of limiting
driving hours to 10 at $686 million, or an increase of slightly over 2
percent.

Elimination of the 11th Hour of Driving in Option 2

    In addition to Options 1 and 2, we also examined a more
restrictive variant of Option 1. That option limited driving to 10
hours in a tour of duty. This more restrictive option was found to
provide more benefits than Option 1, but at substantially higher
cost. Crash risks were originally found to be reduced by about 0.3
percent relative to Option 1. As discussed in Sections 5.4.3, 5.4.4,
6.4 and Appendix (V), this variant is now estimated to reduce LH
[long-haul] crashes by 0.43 percent. This reduction is estimated,
using the recent updates to the number of crashes, the damages
caused by each crash, and the VSL described above, to be worth $146
million per year.
    The projected costs, however, are much higher. They were
originally estimated to be $586 million more per year than under
Option 1, which has been updated for inflation, industry growth, and
industry coverage to $686 million. This estimate was made by finding
the average reduction in driver productivity in shifting between a
case that assumed the characteristics of Option 1 and a variant that
capped driving hours at 10. The average change in productivity,
weighting by the fraction of all driving estimated to fall into each
operational case, was just over 2.0 percent. (See 2007 Interim Final
Rule RIA, pages 69-70, FMCSA-2004-19608-2529.)

    The 2010 NPRM analysis presents, in Exhibit C-7, an estimated cost
of $680 million, which translates to an increase of slightly less than
2 percent. These values, while not precisely the same, are entirely
compatible and do not indicate any material inconsistencies between the
complex and detailed approach used in 2007 and the approach FMCSA is
currently using (which, as mentioned in Section 3.1 of the RIA, was
designed to be simpler and more transparent than the previous analysis,
and better able to focus on the particular changes made in this
rulemaking). And again, to the extent that there are any differences in
estimates of the magnitude of the effects on hours of driving and
working, they would affect both costs and benefits in largely equal
measure.
    Edgeworth also claimed that FMCSA's current approach could
understate productivity impacts because it assumes that driving could
be seamlessly reassigned to other drivers, and that ``In the previous
RIA, FMCSA's carrier logistics model may have accounted for such issues
(we are unable to confirm this without access to the detailed workings
of the model). However, FMCSA's current methodology clearly does not.
For this reason, FMCSA's assumptions may underestimate the productivity
impacts of the proposed rule.''
    This concern is unwarranted, as demonstrated by the fact that the
results generated by the current methodology closely track the results
obtained from the 2007 model for the economically significant provision
(i.e., the impacts of elimination of the 11th driving hour)

where a direct comparison of the analyses is possible.
    Edgeworth then claimed that FMCSA's approach understates the impact
of the restart provisions because it assumes they will have no effect
on drivers averaging 60 hours per week or fewer. Edgeworth argued that
these drivers might occasionally exceed 70 hours and will be affected
at those times. Because the restart provisions actually allow a restart
every week, though, a driver who occasionally needed to work even as
much as 81 hours in a single 7-day period would be able to comply with
the rules (working 13.5 hours per day for 5 days, then taking a
restart, and working another 13.5 hour day, for a total of 81 hours
over that 7 day period). Only drivers who work intensely for 2 or more
weeks in a row will be affected. Thus, occasional intense but brief
periods of work would still not be affected by the rule. Furthermore,
some drivers who occasionally work intensely will have the capacity to
redistribute work from more intense weeks to weeks that do not come
close to the weekly limits. Edgeworth also pointed to data from the
2007 Field Survey showing that drivers frequently use the restart after
weeks in which they work only 65 hours, asserting that these drivers
(who fall into the less intense categories) would be affected by the
restart provisions. This assertion confused the use of the restart as a
bookkeeping convenience with the use of the restart for increasing
productivity. Drivers who do not reach their weekly limit do not need
the restart to maintain their productivity and will not lose
productivity if they cannot use the restart.
Comments and Responses on the Analysis of Fatigue-Reduction Benefits
    Turning to the analysis of fatigue-reduction benefits, Edgeworth
asserted that FMCSA's use of the estimated percentage of crashes
related to fatigue overstates the potential to reduce crashes by
reducing fatigue. Edgeworth pointed out that fatigue is, in many cases,
only one of a number of associated crash factors, not the single cause
of a given crash, and that therefore eliminating fatigue in a crash
that had other risk-increasing factors would not be enough to prevent
the crash. FMCSA believes, however, that in the absence of truck driver
fatigue, the chances of avoiding any given crash (even crashes in which
the critical responsibility lies with the driver of the other vehicle)
would be much greater. Furthermore, given the difficulty of detecting
driver fatigue in the aftermath of a crash, even the careful estimates
from the Large Truck Crash Causation Study (LTCCS) could be
substantially understated. For these reasons, FMCSA chose to stay with
the general approach it used in previous rulemakings, changing only its
baseline estimate of the prevalence of fatigue on the basis of LTCCS
data.
    Edgeworth offered no evidence for its assertion that an accurate
estimate of the incremental effects of fatigue could be derived by
dividing the number of fatigue-associated crashes by the total number
of associated factors.
    The moderate benefits that were attributed in two of the options to
tightening the daily driving limit, using FMCSA's Trucks Involved in
Fatal Accidents (TIFA) analysis, accord well with, or are actually more
modest than, the benefits implied by the two most recent studies of the
decline of performance over long work days. Blanco and Jovanis (2011)
were both conducted under the current HOS rules. The results do not
support Edgeworth's contention that fatigue has fallen to the point
where it is greatly overstated by FMCSA's use of the TIFA data, nor
that reductions in fatigue effects need to be discounted before they
are applied to reductions in crashes.
    Blanco's study provides clear evidence that there is a
statistically significant rise in the risks related to crashes as
driving hours increase. A strong trend is seen across all shifts. A
somewhat weaker trend, but one that is similar and still significant
using a one-tail test (which is the correct statistical approach to use
if there are very strong reasons to believe that long hours of driving
would not improve performance), is seen even for the smaller set of
data that go into the 11th hour.\11\ That latter trend shows that risk
in the 11th hour is about 36 percent higher than the risk in the first
hour (i.e., (0.1379 + 11*0.0052)/0.1379 + 1 * 0.0052) = 1.36). That is
actually a stronger effect than would be seen based on the baseline
time-on-task function used in the RIA, scaling the fatigue crashes to
13 percent (which is [(1 + 36.1 percent)/(1 + 7.4 percent)] = 1.27).
Given that both of these functions are uncertain because they are based
on statistical estimation, however, these values are entirely
consistent. The results are not, however conclusive on whether the 11th
hour is significantly different from the 10th, or on whether increases
in risk over the day are more attributable to long hours of driving or
long hours in the work shift. The Jovanis (2011) study shows risk
increases (not fatigue increases) for the 11th hour of driving in both
the TL and LTL segments that are clearly more substantial than the
increases estimated and used by FMCSA for the RIA, though it does
contain some results that are difficult to interpret.
---------------------------------------------------------------------------

    \11\ Tests of statistical significance are used to determine
whether a parameter estimate could have taken a value at least as
high as it appears to be, simply due to random variability in the
data. A standard ``two tail'' test is used if the parameter could be
either positive or negative, and takes account of both ``tails'' or
extremes of the distribution of a random variable. A ``one-tail''
test is appropriate if there are strong reasons to think that the
true value of the parameter cannot have one particular sign--e.g.,
if the true value cannot be negative. In this case, because there
are good reasons to believe that, if time on task has any effect on
driving performance that effect is deleterious, a one-tail test is
appropriate for assessing whether the time-on-task effect found in
the Blanco study is significant.
---------------------------------------------------------------------------

    Edgeworth claimed that the LTCCS overstates the prevalence of
fatigue-related crashes because it contains too many single-vehicle
crashes. In making this assertion they cite a previous submission to
the docket by Knipling. Knipling's submission contended that LTCCS has
an overrepresentation of single-vehicle crashes when compared to the
proportion of single-vehicle crashes estimated by the National Highway
Traffic Safety Administration's (NHTSA) General Estimates System (GES).
These comments err in one basic fact, according to Agency analysis of
the GES data. The Agency estimates that an average of roughly 20
percent of serious injury and fatal crashes are single-vehicle crashes
in the GES for the years in which LTCCS data were collected, not the 15
percent cited in the Knipling submission to the docket. The estimate of
the proportion of single-vehicle crashes in GES rises to 26-31 percent,
depending on the year chosen, if all crashes--including those that are
less severe--are included in the analysis. As Table 1 of the LTCCS
Summary tables posted on the Agency's web site shows, single-vehicle
crashes were 25 percent of all truck crashes sampled in LTCCS in the
raw data. Using the weighted data the percentage increases to 31
percent. Thus the LTCCS data are less biased with regard to sampling
single-vehicle truck crashes than the comments claim.
    It is not clear whether GES or the LTCCS would have the more
accurate estimate of the true single-vehicle crash representation. GES
sampling methods were set up to get an accurate assessment of passenger
vehicle crashes, not large truck crashes. It could be that the LTCCS,
because it was focused exclusively on crashes involving large trucks,
derived a more representative distribution of large-truck-involved
crashes than that generated by the GES. In addition, LTCCS crash
investigators were fairly conservative in coding crash

factors--roughly 12 percent of the crashes in the data were coded with
unknown causes. It is reasonable to assume that some of these crashes
were fatigue-involved, especially since evidence of fatigue is often
difficult to find in the aftermath of a crash.
    Finally, the Knipling submission went to great lengths to show the
effects that the overrepresentation of single-vehicle crashes would
have on the portion of crashes where asleep-at-the-wheel was coded as a
factor or critical reason. The Agency, however, did not use asleep-at-
the-wheel crashes in its analysis, but instead analyzed crashes where
the truck driver was coded as fatigued. This is an important
distinction because asleep-at-the-wheel overrepresentation in single-
vehicle crashes is significantly higher than fatigue
overrepresentation. As a result, overrepresentation of single-vehicle
crashes is a less significant problem when looking at fatigue
involvement than when one is looking at crashes where the driver
actually fell asleep. It is true that asleep-at-the-wheel crashes would
be a subset of fatigue-involved crashes, but many fatigue-involved
crashes are the result of impairments that fall short of actually
falling asleep. If one carries out Knipling's calculations showing the
effect of single-vehicle crash overrepresentation on asleep-at-the-
wheel representation for fatigue-involved crashes instead, the
differences are far smaller. Looking at the single-vehicle involvement
rate and multi-vehicle fatigue involvement rate for fatigue, and
correcting for the weighting issue using 20 percent single-vehicle
involvement from GES compared to 31 percent from LTCCS, a much smaller
overestimation is derived. At worst, the LTCCS overweighting of single-
vehicle crashes would result in an overestimate of fatigue involvement
in the neighborhood of 10-13 percent--i.e., at the worst, the Agency's
baseline estimate of 13 percent would be reduced to somewhere between
11 and 12 percent. However, given the variability inherent in any
statistical sample or estimate and the fact that LTCCS crash
investigators were conservative in coding crash factors, we feel that
the estimate from LTCCS is as accurate as any other estimate available,
and continue to use it as our baseline.
    Edgeworth also claimed that the baseline estimate of 13 percent for
fatigue-related crashes is ``substantially higher than any measure
previously used by the agency in its analysis of HOS rules or any other
publicly-available measure.'' This claim is not correct. For example,
the RIA for the 2000 NPRM used a 15 percent estimate and the RIAs for
the 2003 and 2007 rules used 15 percent in the sensitivity analyses. In
fact, estimates of fatigue-associated crashes run as high as NTSB's 31
percent (though that figure is for truck crashes fatal to the driver)
and their observation that ``truck driver fatigue may be a contributing
factor in as many as 30 to 40 percent of all heavy truck accidents.''
FMCSA continues to use a range of baseline fatigue estimates, similar
to that used in the past, giving a higher weight to the 13 percent
estimate because of the care with which the LTCCS analysis was
conducted.
    On the subject of cumulative fatigue, Edgeworth brought up FMCSA's
previous statements that the current rules provide enough time for
sleep to allow recovery from cumulative fatigue, and claims that the
introduction of a cumulative fatigue function represents a reversal.
However, the DC Circuit explicitly faulted FMCSA's previous analyses
for excluding the cumulative fatiguing effects of excessive work (as
opposed to insufficient time to sleep). FMCSA has since developed and
now applies a function relating work hours in the previous week to
fatigue levels in the current week, using the LTCCS. This function
shows that, for drivers pushing the outer limits of the on-duty hours
allowed under current rules, fatigue could still be a serious problem.
This problem might not show up in the nationwide data because of other
factors (such as the increased rest period between daily shifts) and
because maximum weekly hours are not the norm, but that does not mean
that safety could not be improved for those drivers who are truly
pushing the limits.
    Edgeworth pointed out that, in applying the cumulative fatigue
function to the regulatory options, FMCSA used a step function that,
essentially, rounded reductions in weekly hours up to the nearest hour.
This is a fact that FMCSA itself noticed during the comment period and
pointed out to ATA/Edgeworth.\12\ That approach did overstate estimated
benefits somewhat, but this overstatement applied roughly equally to
all options. We corrected for this in the regulatory analysis of the
final rule, by using a much finer-grained analysis. The corrected
analysis shows estimated benefits that are lower by a few percentage
points, but does not significantly change the net benefits of Options
2, 3, and 4 relative to each other.
---------------------------------------------------------------------------

    \12\ FMCSA sent this information to ATA in an email titled,
``Supplemental Information on HOS NPRM.'' FMCSA docketed the
contents of the attachments with the title ``Response to ATA Request
for Further Information on the Cumulative Fatigue Function Used in
the Regulatory Evaluation for the 2010 NPRM Proposing Revisions to
the Hours of Service Rules,'' January 28, 2011. It is in the docket
at FMCSA-2004-19608-6147.
---------------------------------------------------------------------------

    Edgeworth also asserted that FMCSA has ignored the likely
interaction between different sources of fatigue (daily driving and
weekly work hours), and that reductions in one will be likely to
decrease the effectiveness of reductions in the other. This potential
issue, however, cuts both ways: for options aimed at cutting work hours
and driving hours for the hardest-working drivers, its total effects
could well be even greater than its effects on each factor. For
example, the limits on the use of the restart will have a
disproportionate impact on the 11th hour of driving (because the
hardest working drivers can be expected to drive the most hours), and
these drivers will often be pushing into the 11th hour in a state of
cumulative fatigue.
    Edgeworth noted that, in calculating the impact of changes in
working hours, the benefits of redistributing hours to other drivers
should be based on the value of crash damages per hour on duty, not per
hour driving. We acknowledge that there is an inconsistency in this
calculation and have corrected it for the final rule. The change is
considerably smaller than estimated by Edgeworth. In the existing
analysis, the single crash reduction value used to calculate the
benefits of redistributing both driving and working hours was part-way
between the correct value for driving hours and the correct value for
working hours. Changing to a more specific value for each slightly
raises the value of reducing the daily driving hours per day while
slightly lowering the value of reducing weekly working hours.
    Edgeworth then claimed that the reduction in crashes since the
crash cost analysis was conducted means that the benefits of reducing
crash rates by a given percent has declined. We used the most up-to-
date comprehensive assessment of crash costs available. The substantial
declines seen in recent years coincided with a sharp drop in the
economy, which had a substantial effect on the number of trucks on the
road at any time, the miles driven, and the loads moved; the Economic
Census Service Sector Survey indicates that there were about 100,000
fewer for-hire trucks on the road in 2009 than in 2007, an 8 percent
decline.\13\ ATA's complete truckload-sector mileage index indicates
that mileage fell roughly 19 percent from 2007 to 2009, using
annualized

numbers. Reduced trucking activity implies reduced costs for any rule
that imposes a limit on productivity; it would be invalid to take
account of only one side of the equation. Furthermore, the recent
recession affected not only truck traffic but also the volume of other
vehicles on the road--and with fewer vehicles with which to collide,
the crash rate per 100 million miles traveled fell as well. Compounding
these effects, if the economic recession caused drivers to work fewer
hours, the lower levels of effort by truck drivers could be expected to
cut their levels of fatigue at the same time they cut the economic cost
of any restrictions. While it would be possible to attempt to estimate
the extent to which all of these transient conditions reduced both the
benefits and the costs of a given rule, the conclusions would apply
only to recessionary periods, which (fortunately) are relatively rare.
---------------------------------------------------------------------------

    \13\ http://www2.census.gov/services/sas/data/48/2009_NAICS48.pdf.
---------------------------------------------------------------------------

Comments and Responses on the Impact of the Proposed Rule on Driver
Health
    On the subject of the estimated benefits of the proposed rule for
driver health, Edgeworth noted that previous RIAs concluded that
insufficient evidence existed to support a connection between reduction
of maximum work or driving time and health of drivers. While that
remains true of many of the health factors discussed in the 2005 rule
(exposure to diesel exhaust, noise, and vibration), in recent years the
evidence has grown that excessive work and insufficient sleep (which
tends to accompany excessive work) are damaging to health. These points
are detailed in Chapter 5 and in Appendix B to the RIA. More recent
data on driver sleep, collected since the 2003 rules have been in
effect, prompted Agency concerns about the baseline average sleep
levels experienced by drivers.
    Edgeworth then questioned whether increased work is likely to lead
to reduced sleep, pointing to the fact that the drivers whose work and
sleep patterns were used as the basis for the estimates of the changes
in sleep per change in work hours were operating under somewhat
different rules. The relationship between additional time working and
the way that time cuts into the hours of sleep, though, is a general
relationship, and would not be expected to appear only under a
particular regulatory regime (especially if many of the drivers were
not even pressing hard against the limits in effect at the time).
Naturally, there will be some uncertainty in estimating exactly how
much average sleep will decline when average work increases, but the
risk of overstating the relationship is no greater than the risk of
understating it; we believe the Agency's estimate is reasonable.
    Edgeworth also pointed to FMCSA's prior statement that ``[t]he
Agency has no basis for estimating the extent to which drivers who have
an extra hour a day or extra hours per week off duty will use that time
to exercise and sleep.'' That statement, however, is strictly true only
insofar as both exercise and sleep are considered together, because
FMCSA did not search for a relationship between work hours and exercise
hours.
    The idea put forth by Edgeworth that changes in work hours do not
necessarily affect average sleep time is inconsistent with the
commonplace observation that workers sleep more on weekends than on
week nights as documented in the American Time Use Survey, National
Sleep Foundation surveys, and other research.
    Finally, Edgeworth also stated that FMCSA should have included the
negative effects of excess sleep, but failed to recognize that these
negative effects were included as an offset to the benefits of the
rule. In both cases, FMCSA is commenting on the difficulty of
predicting changes in sleep exactly, but nonetheless uses a consistent
methodology in applying the changes in work hours to its health
benefits method.
    Edgeworth also disputed FMCSA's use of Ferrie's findings of a U-
shaped relationship between sleep and mortality, offering several
arguments: that the study populations were different, that FMCSA
imputed too great a level of precision to the study, and that the very
small extra hours of sleep for some driver categories are too small to
make any real difference. Though one can raise questions about any
particular study population, Ferrie's study is only one of many that
find a U-shaped relationship--some stronger, some weaker--between sleep
above and below an ideal point (e.g., Grandner & Patel (2009),
Cappuccio (2010)). It is true that for some of the driver categories
the changes in average sleep are very small--but those are also the
categories for which FMCSA finds, and includes, a small negative
benefit of restricting hours; leaving them out of the analysis would
change the results very little. For the drivers in the more extreme
categories, the changes in average sleep are considerably larger. In
the real world not every driver will be exactly at the baseline sleep
level and will not have exactly the average change in sleep. Given the
wide variability in sleep across individuals, many drivers in a
category that has (for example) 6.2 hours of sleep on average will
actually be sleeping well below 6 hours, and for them the effects of
the rule may well be substantial. Although Cappuccio (one of the
authors of the study used by FMCSA for its quantitative analysis)
raised questions about the way FMCSA applied the Ferrie study (of which
he is a co-author) for its quantitative analysis, the lead author of
the study, Jane Ferrie, is on record as approving of FMCSA's use, and
even considered the Agency's approach conservative in terms of the
benefits that could be derived from improved sleep. (See the detailed
discussion of Cappuccio's criticism and Ferrie's response below under
Comments on Health Benefits.)
Other Comments on the Cost/Benefit Analysis
    Comments on Impacts to Shippers, Brokers, or Consumers. Commenters,
including ATA, National Association of Manufacturers, the Chamber of
Commerce, shipper and trucking associations, and major carriers stated
that FMCSA had not addressed the costs of the rule to shippers,
brokers, or consumers. They stated that the supply chain would have to
be re-engineered. A distributor association estimated costs for
changing routes of one carrier at $20 million and cited Kraft Foods as
saying that the number of routes that could be covered in one day would
drop from 75 percent to 60 percent.
    FMCSA Response. The costs of the rule are measured by the cost to
the carriers (which, in the case of private carriers, includes shippers
because they are the same in that case). We assume that these costs are
then shifted, largely, to the direct and indirect users of shipping
services: shippers, receivers, and ultimately consumers. We have
included costs for reprogramming routes, based on the clearest
quantitative estimates provided in past comments in listening sessions;
to the extent that the shippers do the work of altering the routes in
light of the rule changes, that should reduce the costs to carriers. We
have addressed costs to consumers in the RIA. Our cost estimates are
for carriers providing the same, or essentially the same, service using
more drivers and trucks each with slightly lower average productivity.
The costs of changing routes will be mitigated by the time allowed for
compliance. In a dynamic economy frequent changes in shipping and
routing are necessary; any changes necessitated by the new rules can be
phased in whenever they are most convenient. FMCSA believes that the
cost factors provided by the commenters are not adequately justified,
and they

are exaggerated compared to the averages.
    Comments on Impacts on LTL Carriers. ATA stated that the analysis
did not account for impacts on LTL carriers; it estimated the
productivity losses at 5 to 9 percent. Con-way said the rule would
require network changes.
    FMCSA Response. The analysis of the impact of the different options
did consider impacts on LTL carriers, as they were included in both the
population of drivers and power units, and in a survey that was the
basis for the estimates of the distribution of work effort. Though
there might be some LTL routes that could lose this much productivity
if driving were restricted to 10 hours per day, it is highly unlikely
that the industry-wide average impact would be that high. Only a driver
who drove 11 hours every day, and who was required to cut back to 10
hours, would lose as much as 9 percent of baseline productivity, and
ATA is on record stating that even FMCSA's estimate that the 11th hour
is used on only about a fifth of trips is substantially overstated. Any
segment that currently requires 10 hours or less, or more than 11
hours, would be unaffected by a change in the daily driving limit, and
any driver currently taking a full weekend off would be unaffected by
the changes in the restart provisions. It is true, as Con-way stated,
that some changes in networks might be necessary, and a cost has been
assigned to those changes. It should be noted, however, that Con-way
stated that its drivers averaged less than 8 hours of driving a day. In
any case, the final rule leaves daily driving hours unchanged.
    Comments on Reduction in Productivity. Schneider stated that the
rule would reduce its productivity by 4.72 percent. Drivers would get
home 25 percent less; the average run would drop from 501.7 miles to
478 miles, which would translate to $3,000 a year decrease in driver
pay to offset the loss in productivity. Other carriers stated that
those carriers that maximize hours would have an 8 to 10 percent
reduction in productivity.
    FMCSA Response. FMCSA's estimate of the nationwide productivity
impacts is close to an average of 1.2 percent; the Agency assumes there
is substantial variability across operations and firms. The estimated
reduction in productivity for the carriers allowing or requiring
drivers to work the longest hours is quite consistent with our
estimates--those working about 80 hours must cut back to something
below 70, which is a reduction of more than 12 percent.
    Comments on Costs to Short Haul. Three shipper associations stated
that FMCSA had ignored the costs to short-haul operations and that its
statement that they would not be affected was without foundation,
particularly as the provisions limited work time other than driving
time.
    FMCSA Response. The RIA for the 2003 HOS rules did calculate costs
and benefits for short-haul and local drivers, and the analysis for the
2005 HOS rules also looked at how longer driving windows could reduce
impacts on that segment. For the final rule, however, FMCSA considers
any potential impacts to be small. This conclusion is based largely on
the nature of the HOS rule changes considered in this rulemaking,
compared to the work patterns identified in previous rulemakings. The
2003 rules increased the daily driving hours from 10 to 11, increased
the required off-duty period from 8 to 10 hours, allowed restarting the
multi-day count of on-duty hours after a 34-hour period off-duty, and
limited driving to a 14-hour window after coming on duty. FMCSA's
review of work by short-haul and local drivers, which included
quantitative assessments of two driver surveys and discussions with
industry sources, concluded that most of the changes in the rules would
have essentially no effect on short-haul and local drivers. The ability
to work the maximum numbers of hours per week (through the restart) was
also considered unlikely to provide benefits to the short-haul and
local drivers, because they were judged to work much more moderate and
regular hours than longer-haul drivers, often with full weekends off.
    The only provision of the 2003 rule found to be likely to impose a
significant cost on short-haul and local drivers was the fixed 14-hour
limit on the driving window. FMCSA's data on the variability of daily
work by short-haul and local drivers, however, found that work in
excess of 14 hours was quite rare, even when drivers were permitted to
work beyond a 14-hour window. Furthermore, the provisions that allow
short-haul and local drivers to exceed the 14-hour driving window once
or twice a week should provide enough flexibility to prevent any
significant impact on the vast majority of these drivers. Finally, the
final rule has dropped the 13-hour limit on daily on-duty hours,
further reducing the chances that a short-haul or local driver's
operations will be constrained.
    Comments on Costs of Training Enforcement Personnel. CVSA and the
Oregon Department of Transportation stated that the RIA failed to take
into account the cost of training 14,000 enforcement personnel, which
they estimated to be between $2,682,680 (8-hour course) and $4,924,020
(12-hour course), not including travel and per diem. According to the
commenters, these costs will be an additional burden on State
resources. Carriers, ATA, and other trucking associations also stated
that the 2-hour estimate for training was too low.
    FMCSA Response. The proposed rule has been simplified, and the 11-
hour driving limit from the previous rule retained, which should
mitigate the length of the training needed to familiarize inspectors
and drivers with the new requirements. The Agency considered including
these costs, but found that they did not change the total cost of the
rule, which is rounded to the nearest $10 million. FMCSA also notes
that the lead time provided before the rule takes effect will allow
training to be incorporated into other on-going activities. For
industry costs, we used the clearest quantitative estimate available
from comments at listening sessions.
    Comments on Costs and Driver Additions. Advocates et al. stated
that fatigue-related truck crashes cost between $5.5 and $13 billion
annually. They also posited that the current HOS rule eliminated the
need to hire 60,000 drivers; the proposed rule would add 44,000 driver
jobs to the economy.
    FMCSA Response. This estimate is broadly consistent with FMCSA's
estimates for fatigue-related crashes, though higher than its estimates
for long-haul crashes alone. FMCSA's estimate of the number of new
drivers is lower, because it anticipates a small shift from truck to
rail, and leaves the daily driving limit at 11 hours.
    Comments on Cost Disaggregation. Another advocacy group stated that
FMCSA should have disaggregated the costs for each key provision, not
just driving time. The group also commented that FMCSA should estimate
the effects of changes in congestion.
    FMCSA Response. FMCSA analyzed the costs and benefits of the
provisions individually, as shown in RIA Appendix C, and summarized in
Table 3 of this preamble. FMCSA does not expect any significant net
effects on congestion. The requirement for two consecutive nighttime
periods off to qualify for a restart, which might be anticipated to
shift traffic into more crowded times of day, will affect only one day
per week for the fraction of drivers who routinely work all night and
routinely work very long hours per week. Any effect on congestion due
to these small shifts will be counterbalanced by the small

anticipated shift from truck to rail due to the rule's effect on
productivity.
    Comments on Safety Benefits. Two trade associations and the
Missouri Department of Transportation stated that the Agency has no
basis for projecting safety benefits. ATA stated that there were no
safety benefits. OOIDA stated that the analysis was flawed because it
is based on data collected under the pre-2003 rule.
    FMCSA Response. FMCSA has shown that reducing working, and building
in breaks in long days, will provide more time to rest and reduce the
buildup of fatigue. Because fatigue is known to be an important cause
of heavy-vehicle crashes, a regulation that reduces fatigue can be
expected to reduce crash risks. Some of the analysis did use data from
before 2003 along with more recent data, because the most recent data
are not yet extensive enough to form the basis of an entirely new set
of analyses. FMCSA has no reason to believe that basic relationships
between work and sleep, and between excessive work and fatigue, have
changed enough since 2003 to invalidate its analysis using data prior
to the current rule change. There is no reason why the use of pre-2003
data to examine time-on-task effects would produce spurious results.
Furthermore, the time-on-task function used in the current RIA was
incorporated into the RIAs accompanying the 2005 and 2008 rules and was
used in those rulemaking actions to evaluate the differences in safety
impacts between the various options considered. The use of that
function in previous rulemakings was tacitly accepted by all
commenters.
    On March 17, 2008, ATA submitted comments on FMCSA's December 7,
2007, Interim Final Rule's RIA.\14\ ATA commented ``that FMCSA had
taken diligent and extraordinary steps to assure the comprehensiveness
of the analysis and its parts. This included adequately explaining two
critical elements of the model in the RIA accompanying the 2005 rule--
the analysis of time-on-task and the analysis of whether the 34-hour
restart affects cumulative fatigue.'' FMCSA's 2007 RIA used the same
TIFA function to estimate benefits as the RIA for this final rule.
---------------------------------------------------------------------------

    \14\ See document item FMCSA-2004-19608-3437 for ATA's comment
on pages 13-14, and document item FMCSA-2004-19608-2924 for NERA's
paragraph on page 2.
---------------------------------------------------------------------------

    ATA noted in its 2008 comments that ``The regression analysis
(model) used by FMCSA to measure and project the effect on the risk of
crashes associated with driver fatigue of driver's time on task (TOT)
is reasonable and appropriate.'' In addition, a statistician hired by
ATA as a consultant to examine the Agency's TIFA-based time on task
function submitted the following comment: ``Based on my review of the
2007 RIA and related docket materials as well as the considerations set
forth in my September 2007 Declaration, it is my opinion that the form
and implementation of FMCSA's revised logistic regression model are
reasonable in the circumstances for the purpose for which FMCSA used
this calculation in the 2007 RIA'' (Marais). In light of the fact that
the function has been used twice in the past, and that even ATA and its
consultants have stated that use of this function is appropriate, it
seems reasonable for the Agency to have used it again for the December
2010 NPRM and this final rule to estimate safety benefits associated
with reducing allowed daily driving.
    More recent research has corroborated time-on-task and cumulative
fatigue effects for driving occupations. Two new studies sponsored by
the Agency and conducted with post-2003 data have found evidence of
increasing crash risk or SCEs as driving time increases through the day
(Blanco and Jovanis (2011)). In addition, other studies involving
transit bus operators have shown evidence that longer weekly work hours
are associated with an increase in crash risk for drivers working 45
hours per week or more (Sando (2010a and 2010b)). While these drivers
operate in a different setting than over-the-road truck drivers, the
fact remains that the increase in risk begins appearing at weekly work-
effort levels well within the current and previous HOS rules. Taken
together, these studies bolster the Agency's claim that limiting work
would reduce crashes related to time on task and cumulative fatigue.
Comments on Health Benefits
    Although drivers who work fewer hours than the maximum allowed by
the rule will experience only limited health benefits, those who
currently work the longest schedules must curtail their weekly work
hours--in some cases significantly--and will, therefore have additional
time off duty to sleep or exercise, both of which are associated with
improved health, lower medical costs and, ultimately, with longer life
expectancy.
    Comments on the Use of the Ferrie Study. ATA submitted an opinion
from Francesco Cappuccio that disputed the use of studies cited by
FMCSA in the 2010 NPRM to estimate changes in mortality based on sleep.
His points were the following:
     The studies used are based on epidemiological data, which
do not imply a causal relationship.
     Sleep duration is self-reported and does not differentiate
between naps and longer daily sleep. The studies also do not exclude
people with sleep disorders.
     The description of a so-called U-shaped relationship
between duration of sleep and risk of death is currently insufficient
to justify an interpretation of a `graded and continuous' relationship
between exposure (sleep duration) and outcome (death). There could be
threshold effects.
     The mapping of sleep time is not supported by data.
     The RIA did not consider the impact of more than 8 hours
of sleep.
     Sleep time between 6 and 8 hours is not associated with
harm. Most drivers appear to fall into this range.
     There is no evidence that increasing sleep by 5.5 minutes
per day would produce health benefits.
     FMCSA assumes that, if given extra time off, drivers would
use it to sleep. This is not supported by data.
    Cappuccio concluded:

    In these studies reduced weekly work hours led to an increase in
sleep time because other approaches were taken at the same time as
the reduction in work hours to encourage and facilitate the workers
to sleep longer and to recover better from previous shifts. These
measures include important components based on well-established
principles of sleep medicine and circadian biology: Limit
consecutive night shifts to reduce the build-up of chronic partial
sleep deprivation due to the limited sleep between night shifts;
limit shift duration to minimize acute sleep deprivation; design the
sequence of shifts to abolish `slam shifts'; instruct workers and
facilitate naps; and also reduce the proportion of long work weeks.
These approaches are effective on performance and reduce errors. No
evidence of efficacy on health outcomes is yet available.

    Jane Ferrie, the lead author of the study in question on which
Cappuccio collaborated, submitted a comment to the docket. She noted
that the RIA acknowledged that epidemiological data do not prove
causation. She cited a number of studies on self-reported sleep
indicating that such reports overstate sleep. Ferrie cited other
studies showing that self-reported sleep is strongly associated with
health outcomes. The projections in the RIA were very close to the
results derived from the data analysis of the Whitehall study. She
described the mortality ratios used in Exhibit 3 as robust and added
that the quadratic regression analysis used in the RIA is a relatively
good approximation within the range of 5-9 hours sleep duration.
Mortality rates in Exhibit 5-3 outside these ranges would be less

stable, but she noted that the Agency did not appear to have used them
in the cost-benefit analyses. She stated that the problem of covariates
appears to be quite minor. She also stated that the inferences in the
RIA on increased mortality seem to be in rough agreement with estimates
from her study. She noted that the RIA acknowledged that small changes
in the amount of sleep make little difference for individuals, but
``small changes at the population level, particularly in large
populations, can have significant effects.''
    On the unquantified health benefits, Ferrie cited an increasing
body of research documenting the effects of working more than 55 hours
a week on heart disease, cognitive function, depression, and sleep
disturbances. She stated that repeated exposure to long working hours
has been shown to be associated with a 3-fold increased likelihood of
shortened sleep, a nearly 7-fold increased likelihood of difficulty
falling asleep, and a 2-fold increased likelihood of early morning
waking. She noted that these effects are not related to shift work.
Ferrie concluded that the methods of analysis FMCSA used appear to be
robust and that the RIA takes a cautious approach to interpreting the
health benefits.
    FMCSA Response. In every instance, Cappuccio appears to have drawn
the narrowest possible conclusion from the available data, both in the
study that he co-authored and in the RIA, with the result that he finds
the connection between mortality and sleep duration tenuous or
contingent on further research and better data. According to Cappuccio,
some sleep scientists suggest that there may be an alternative
``threshold'' hypothesis for the relationship between sleep and
mortality. According to this hypothesis, individuals getting at least
as much sleep at some threshold level (e.g., 5 hours a night) would
gain nothing from small changes in sleep. Cappuccio, however, is on
record as stating that research shows that sleeping less than 7 hours a
night is likely to lead to greater mortality. In his comments (FMCSA-
2004-21675), Cappuccio mentioned his study Cappuccio (2010), which is
docket item FMCSA-2004-19608-4041. That report includes the sentences,
``Our study shows an unambiguous and consistent pattern of increased
risk of dying on either end of the distribution of sleep duration.
Pooled analyses indicate that short sleepers (commonly <7 h per night,
often <5 h per night) have a 12% greater risk.'') Thus, granting for
the sake of argument that there may be a threshold, even Cappuccio
likely would place it above the levels at which we are estimating
benefits. Ferrie, on the other hand, was more willing to trust the
available research, and to draw real-world conclusions from it. She
found FMCSA's use of her own research to be cautious and had no
objection to the use of those results as a partial rationale for HOS
policy. On the issue of fitting a continuous curve through data
collected on an ordinal scale, her comments supported the Agency. As
shown above, Ferrie thinks: ``Both the estimated increases in sleep
duration and decreases in mortality that result from the RIA are very
small, a point acknowledged by the FMCSA authors; the curvature of the
relationship `means that changing average sleep makes very little
difference for individuals.' However, small changes at the population
level, particularly in large populations, can have significant
effects.'' These comments show that the Agency's inferences regarding
increases in sleep and mortality reductions were reasonable. In
addition, both Ferrie and Cappuccio, along with other researchers on
this topic, have referred to a U-shaped curve rather than a step
function when discussing the relationship between sleep and mortality.
A curve generally connotes a continuous function in the scientific
literature, therefore references to a curve in the literature imply a
continuous relationship rather than a threshold or step function. While
FMCSA recognizes the need for improved data and is sponsoring a wide
range of research projects on sleep and fatigue, we are not prepared to
repudiate reasonable inferences from work already available because
more perfect work might someday be completed. We agree with Ferrie's
comments.
    FMCSA is, in fact, implementing three of Cappuccio's suggestions in
this final rule. This final rule is: (1) Regulating time to abolish
``slam shifts,'' which are shift schedules that cause sudden changes in
the sleep/wake cycles; (2) Facilitating naps by providing a 30-minute
break; and (3) Reducing the proportion of long work weeks.
    Other Comments on Health Benefits. An advocacy group noted that
there are underlying medical conditions that lead to lower sleep, such
as sleep apnea. A shipper association and a company stated that health
benefits are inflated by the change in the on-duty definition.
    FMCSA Response. FMCSA recognizes that sleep conditions can reduce
sleep, but many of these conditions are associated with obesity, which
is linked to long work hours and a sedentary lifestyle. The direction
of causality can be difficult to determine, but one likely sequence is
that long work hours reduce sleep, which causes biochemical changes
that facilitate obesity, which is associated with high blood pressure
and diabetes, all of which are associated with an increased incidence
of sleep apnea.
    The economic analysis did not look at the changes in the on-duty
definition or use it to change estimates of sleep time; the revised
definition is not expected to alter sleep time. The revision allowing 2
hours in the passenger seat to be logged as off-duty time mainly
affects team drivers, whose sleep is poor in any case according to
those drivers. Local drivers may ``rest'' in the truck if they are off
duty, but that rest will not necessarily include sleep, particularly as
local drivers usually work during daylight hours when sleep is
difficult even when someone is tired.
    Other Comments on Benefits. A trucking association stated that
FMCSA should demonstrate that the safety benefit of the 2-night
requirement for the restart provision outweighs the cost of increased
congestion. An advocacy group stated that the RIA should analyze the
costs and benefits of the 16-hour provision and the 30-minute break. It
stated that FMCSA should monetize the health impacts beyond mortality.
It noted that besides leading to premature death, the chronic diseases
associated with lack of sleep impair both quality of life and
productivity for a long period. The direct and indirect costs
associated with these conditions are high.
    FMCSA Response. As discussed earlier in this preamble, it is not
clear why commenters believed that the two-night requirement will lead
to increased congestion. They seem to assume that nighttime deliveries
will end, but they will in fact continue 5 nights a week for the
hardest working drivers and 6 or 7 nights a week for drivers who do not
need the restart. The final RIA does monetize the costs and benefits of
the break; the 16-hour provision has been dropped.
    As explained in the RIA, it is difficult to monetize the costs of
the chronic health impacts because to do so, FMCSA would need data that
linked these conditions to specific amounts of sleep. There are, for
example, data that indicate the increase in mortality associated with
increases in body mass index (BMI), but these vary considerably by sex
and race. To begin to monetize those costs we would need data that link
specific levels of sleep to BMI and then data that linked the BMI to
incidence of diseases.
    Comments on Fatigue Research. Thirteen commenters responded to the

WSU study on night drivers. ATA, OOIDA, CVSA, CHP, a State trucking
association, and several carriers stated that the number of subjects
was too small and the lab setting too artificial. Two drivers objected
to using young healthy subjects instead of trained drivers. Another
driver stated that the study did not consider drivers whose natural
rhythms are suited for working at night. Advocates stated that previous
research supported the findings of the WSU study. JB Hunt stated that
it surveyed 249 drivers, 82 percent of whom regularly drove at night;
79 percent of these drivers said they did not change their sleep
schedules when at home, which is contrary to the WSU assumption. JB
Hunt also stated that anyone who gets 10 hours of rest a day should not
develop a sleep debt.
    FMCSA Response. FMCSA addressed most of these comments above, in
Section IV. ``Discussion of All Comments'' G. ``Restart,'' under the 2-
night requirement heading. As for the assertion that 10 hours of rest a
day is sufficient to eliminate sleep debt, the commenter is assuming
that a driver with 10 hours off will use 7 to 8 hours of that time to
sleep. Research has shown that night drivers who are trying to sleep
during the day generally get less than 6 hours of poor quality sleep
even when they have more than 10 hours off.
    Comments on the Impact of Long Hours. On the issue of long hours,
Ferrie noted that a recent review concluded that work in excess of 8
hours carries an increasing risk of crashes, with the risk in the 12th
hour double that of the 8th. Sando reported that his study showed an
increased risk of collisions as hours worked increased.
    NIOSH cited a number of studies that indicate that sleep
deprivation produces performance deficits, including an inability to
assess risk and an increase in risk taking. It also cited studies on
fatigue and CMV crashes and sleep apnea. Advocates et al. stated that
research indicates that performance degrades when drivers have less
than 7 to 8 hours of sleep and that most drivers get less than 6 hours
of sleep on work days. They also cited a number of studies that
indicate people need 7 to 9 hours of sleep. They countered industry
arguments that the rule was based on pre-2003 data by noting that the
NIOSH study of drivers covered 2004-2006. They stated that the findings
of the 2005 Fatigue Management Survey on sleepy drivers indicate that
this problem is more common for CMV drivers than for other drivers.
    An association stated that fatigue literature does not address the
relative risk of the 11th hour. The Missouri Department of
Transportation cited the LTCCS as indicating that fatigue was the 10th
highest associated factor.
    FMCSA Response. FMCSA agrees with the commenters that the great
majority of research associates long hours of work with fatigue and
increased crash risk. FMCSA also agrees that fatigue literature does
not directly address the relative risk of the 11th hour of driving. The
new VTTI study indicates that it is difficult to isolate the relative
risk of any particular hour of driving because driving hours can occur
at differing times during the work day. For example, the 11th hour
cannot occur sooner than 11 hours into the work day, but it can occur
anytime from 11 to 14 hours into the work day. The fifth hour of
driving can occur anytime from 5 to 14 hours into the workday. This
affects the relative risk of any particular hour of driving. As for the
LTCCS, it may have found that fatigue was the 10th highest factor, but
it still was associated with 13 percent of crashes.
    Comments on Health Research. Relatively few commenters discussed
the health research reported in the NPRM and RIA. ATA and the Retail
Industry Leaders Association (RILA) stated that FMCSA has argued in
past HOS rulemakings that long hours do not affect health. RILA further
stated that the 2000 Balkin study on the relation of work time to sleep
time was not valid because the data were collected under the previous
HOS rule. It also questioned the assumption that a reduction in driving
time would lead to more sleep and exercise. Another State trucking
association and a carrier argued that FMCSA had not proven that changes
to the rule would have measurable positive impact on driver health. The
Minnesota Trucking Association stated that the studies did not answer
the question of whether long hours, shift work, or short sleep lead to
obesity and diabetes.
    NIOSH submitted a number of studies that address health issues.
NIOSH cited studies linking shift work to smoking and obesity, noting
that research has found that short and poor quality sleep periods alter
hormone levels and metabolic function and lead to insulin resistance.
NIOSH cited research linking shift work to a higher risk of
cardiovascular diseases, including studies of drivers. It noted that a
study of unionized U.S. drivers found an elevated rate of mortality
from ischemic heart disease. NIOSH stated that the International Agency
for Research on Cancer has designated shift work with circadian
disruption as a probable carcinogen. It also reported on studies
linking long hours to depression and finding that working less than 12
hours a day and 58 hours a week reduced depression and fatigue. It
cited a 2010 study of truck drivers associating disrupted sleep
patterns with increased obesity and several chronic diseases. Studies
of verifiable sleep of truck drivers found daily averages well below 7
to 8 hours (3.8 to 5.2 hours).
    Finally, Schneider National stated that FMCSA should address sleep
apnea among drivers, which it said is a more important cause of fatigue
than HOS. It also questioned the current rule allowing chiropractors to
serve as medical examiners. A safety group stated that FMCSA should
analyze the impact of diesel fumes.
    FMCSA Response. As FMCSA explained in the NPRM, the body of
research that finds a connection between long hours of work and worker
health has grown substantially in the past 6 years. Most of the health
issues that FMCSA reviewed for the 2005 rule--exposure to diesel fumes,
noise, and vibration--were not and still are not scientifically
associated with long hours. The findings on noise and vibration
indicated that the levels to which drivers are exposed were not great
enough to cause health effects. With diesel exposure, drivers who are
parked with trucks idling may be exposed to higher levels than when
they are driving. Altering work hours would not necessarily reduce
exposures.
    These issues are not the basis of the health impacts discussed in
the 2010 NPRM. As the studies submitted by NIOSH and others cited in
the NPRM and RIA have reported, long hours of work, particularly work
that is primarily sedentary, are associated with low sleep, obesity,
and cardiovascular disease. With many factors linked, it is not
possible to define a simple pathway for effects. There is, however, a
substantial body of research that has identified the chemical changes
caused by lack of sleep that can increase the likelihood of obesity and
diabetes and increase blood pressure. CMV drivers have a markedly
higher rate of obesity than adult male workers as a whole and have been
shown to have an elevated risk of dying of some cardiovascular
diseases. Interestingly, the commenters did not attempt to deny that
drivers have a higher incidence of chronic health conditions, each of
which is linked to higher mortality rates and higher on-going medical
costs. As mentioned above, this rule is unlikely to improve the health
of drivers who work moderate schedules. On the other hand, those
currently working the longest schedules will be required to reduce

their work hours, which is likely to increase their opportunity for
sleep and/or exercise, both of which are conducive to better health and
lower medical costs.
Final Rule Regulatory Impact Analysis
    For the analysis of the final rule, FMCSA considered and assessed
the consequences of four regulatory options. (A copy of the complete
RIA is available in the docket.) Option 1 is the no-action alternative,
which would retain the provisions of the current HOS rule. All costs
are relative to Option 1. Options 2 through 4 require at least one
break during the duty day (none is currently required), and limit the
use of the 34-hour restart provision to once every 168 hours with at
least 2 nights off duty. Options 2 through 4 differ only in driving
time allowed between 10-hour breaks. Option 2 limits allowable daily
driving to 10 hours, the driving limit that existed prior to the 2003
rule. Option 3 retains the 11 hours of driving allowed under the
current rule. Option 4 allows only 9 hours of driving, or 1 hour less
than Option 2. This RIA compares the costs and benefits (in 2008
dollars) of Options 2 through 4 relative to the current rule (i.e.,
Option 1) and assumes that there is full compliance with each of the
options.
    Compliance with HOS rules was assumed to be 100 percent for both
the baseline and options; no attempt was made to estimate real-world
compliance rates or to adjust costs and benefits for non-compliance.
This assumption was made to avoid understating the true costs of the
rule. To the extent that compliance rates fall short of 100 percent,
both costs and benefits would be lower. This approach allows for
analyses of supplementary rules aimed at improving compliance, which
would presumably move both costs and benefits closer to the levels
estimated in this analysis. These incremental changes in costs and
benefits would not duplicate the costs and benefits estimated for this
rule; rather they would indicate the extent to which the supplementary
rules ensured that the rule's costs and benefits were realized.
    To calculate the impact of the changes to the HOS rule, it is
necessary to develop a profile of the motor carrier industry and
estimate the degree to which drivers in various segments work up to or
close to the limits of the current rule. Drivers whose preferences or
work demands lead them to schedules well within the current limits for
reasons unrelated to those limits will not be affected by the rule
changes.
    The analysis concentrated on inter-city long-haul or regional, as
opposed to local, trucking operations. In general, short-haul trucking
work has far more in common with other occupations than it does with
regional or long-haul trucking. These local, short-haul trucking
operations are generally 5-day-a-week jobs, and much of the time on
duty is given to tasks other than driving. Typical work days are 8 to
10 hours or so and typical weeks are 40 to 55 hours. Many of these
drivers receive overtime pay past 8 hours in a day. Most of the work is
regular in character; drivers go to basically the same places and do
the same things every day. The rule is expected to have little effect
on such operations.
    Both for simplicity of presentation and because of the nature of
the available data, the analysis used 100 miles as the point of
demarcation between local and over-the-road (OTR) service. Much of the
information on working and driving hours is drawn from FMCSA's 2007
Field Survey.\15\ Companies and drivers were identified as operating
within or beyond a 100-mile radius. The Economic Census, which provided
data on revenue, defines a long-distance firm as one carrying goods
between metropolitan areas; this is roughly compatible with a 100-mile
radius for the distinction between local and OTR service. One hundred
miles is also compatible with the length-of-haul classes in the
Commodity Flow Survey.
---------------------------------------------------------------------------

    \15\ The ``2007 Field Survey'' is an alternate title for the
FMCSA, ``2007 Hours of Service Study,'' 2007. FMCSA-2004-19608-2538.
---------------------------------------------------------------------------

    To evaluate the impact of the rule changes, the analysis needed to
define the prevailing operating patterns in the industry. Of particular
interest is the extent to which drivers work close to the limits set by
the current rule. To analyze current patterns in work intensity,
drivers were assigned to four intensity groups, based on their average
weekly hours of work. For this purpose, the analysis used data on
weekly work hours from FMCSA's 2007 Field Survey to define intensity
groups as shown in Table 6.
    Moderate-intensity drivers are on duty an average of 45 hours per
week. High-intensity drivers are on duty an average of 60 hours per
week. The third group, very-high-intensity drivers, works an average of
70 hours per week. The fourth group, extreme-intensity drivers, is on
duty an average of 80 hours per week. The 2007 Field Survey indicated a
distribution of the driver population across these groups as shown
below.

             Table 6--Driver Groups by Intensity of Schedule
------------------------------------------------------------------------
                                                               Weighted
                                     Average     Percent of    average
       Work intensity group        weekly work   workforce    hours per
                                       time                      week
------------------------------------------------------------------------
Moderate.........................           45           66        29.70
High.............................           60           19        11.40
Very High........................           70           10         7.00
Extreme..........................           80            5         4.00
                                  --------------------------------------
    Total........................  ...........  ...........        52.10
------------------------------------------------------------------------

    The weighted average is obtained by multiplying the average work
time in each class by the fraction of the workforce in that class. The
sum, just over 52 hours, is the average hours of work per week based on
each group's share of the total population. The analysis made similar
calculations using the Field Survey data to determine the weighted
averages for use of the 10th and 11th hour of drive time and the 14th
hour of daily on-duty time. These figures can be found in the
accompanying RIA.
    To estimate the costs of operational changes, the basic approach is
to follow the chain of consequences from changes in HOS provisions to
the way they

would impinge on existing work patterns in terms of work and (where
relevant) driving hours per week, taking overlapping impacts of the
rule provisions into account. Estimated changes in productivity are
translated into changes in dollar costs using functions developed for
the regulatory analyses of previous HOS rules. Summing the different
cost components resulted in a total annualized cost of $1.00 billion
for Option 2, $470 million for Option 3, and $2.29 billion for Option
4. Though these costs are estimated using impacts on industry
productivity, they would most likely be passed along as increases in
freight transportation rates, and then ultimately to consumers in
increased prices for the goods that are transported by truck.
Rule Benefits
    The primary goal of the final rule is to improve highway safety in
the most cost-effective way by reducing driver fatigue and the
associated increase in the probability that fatigued drivers will be
involved in crashes. A second benefit expected from this rule is a
decrease in driver mortality due to health problems caused by long
working hours and the association of long working hours with inadequate
sleep.
    To analyze the safety impacts of the 2010 NPRM and 2011 final rule,
the Agency developed a series of functions that incorporate fatigue-
coded crashes to hours of daily driving and hours of weekly work. In
the pre-2010 HOS regulatory analyses, the effects on fatigue and
fatigue-related crashes of changing the HOS rules were calculated using
fatigue models. These models (the Walter Reed Sleep Performance Model
for the 2003 rules, and the closely related SAFTE/FAST Model for 2005,
2007, and 2008 analyses) took into account the drivers' recent sleeping
and waking histories, and calculated fatigue based on circadian effects
as well as acute and cumulative sleep deprivation. These models did not
incorporate functions that independently accounted for hours of driving
after an extended rest (i.e., acute time-on-task) or cumulative hours
of work (as opposed to off-duty time) over recent days. These effects
were assumed, instead, to be accounted for in the effects of long daily
and weekly work hours on the drivers' ability to sleep. For the 2005
and later analyses, a separate time-on-task function based on
statistical analysis of TIFA data was added to ensure that available
evidence for time-on-task effects was not ignored; those analyses were
still criticized as deficient for excluding consideration of cumulative
time-on-task effects.
    For the 2010 NPRM and the 2011 final rule analyses, FMCSA replaced
the use of the sleep-related fatigue models with a simpler approach
that explicitly relates the risk of a fatigue-coded crash to hours of
daily driving and hours of weekly work. The function used to model the
effects of daily driving hours is the same as the TIFA-based logistic
function used since 2005, while the function for modeling weekly work
hours is taken from FMCSA's analysis of the LTCCS. Other fatigue
effects, including the effects of insufficient sleep and circadian
effects of working and sleeping at sub-optimal times, are implicitly
assumed to be incorporated in the daily driving and weekly work-hour
functions because those effects were at work on the drivers involved in
the crashes recorded in TIFA and LTCCS. To add fatigue effects
calculated by a sleep/performance model on top of the empirically based
functions would, therefore, run the risk of double counting the
benefits of restrictions on work and driving. These functions, and the
uncertainty surrounding them, are described in detail in the RIA.
    The basic approach for using the empirically based fatigue risk
functions was to count the changes in hours worked and driven as a
result of the regulatory options. Each hour of driving that is avoided
results in a reduction in expected fatigue-related crashes. These
reductions were calculated using the predicted levels of fatigue-
related crashes indicated by the fatigue functions. The hours of
driving and working that are prevented by the options, though, were
assumed to be shifted to other drivers or to other work days rather
than being eliminated altogether. The fatigue crash risks for those
other drivers and other days were also calculated. Taking account of
these partially offsetting risks means that the predicted crash
reductions attributable to the options were really the net effect of
reducing risks at the extremes of driving and working while increasing
risks for other drivers and on other days.
    The changes in crash risks were monetized (i.e., translated into
dollars) using a comprehensive and detailed measure of the average
damages from large truck crashes. This measure takes into account the
losses of life (based on the DOT's accepted value of a ``statistical
life,'' $6 million when this rulemaking began); medical costs for
injuries of various levels of severity, pain, and suffering; lost time
due to the congestion effects of crashes; and property damage caused by
the crashes themselves.\16\
---------------------------------------------------------------------------

    \16\ Average large truck crash costs were obtained from the
report, ``Unit Costs of Medium and Heavy Truck Crashes,'' March
2007, by E. Zaloshnja and T. Miller. The cost of a crash was updated
to 2008 dollars and to reflect a value of a statistical life of $6
million. The report is in docket FMCSA-2004-19608-3995.
---------------------------------------------------------------------------

    The monetary value of each of the effects thought to affect the
safety of drivers was estimated under three different assumptions of
the baseline level of fatigue involvements in crashes: 7 percent, 13
percent, and 18 percent. The total benefits resulting from improvements
in the safety of long-haul (LH) drivers for Options 2 through 4 are
shown below in Tables 7 through 9 below.\17\
---------------------------------------------------------------------------

    \17\ Truck driver fatigue was coded as a factor in 13 percent of
all crashes in the Large Truck Crash Causation Study (LTCCS). As a
sensitivity analysis, FMCSA also used a lower value of 7 percent
involvement in fatigue-related crashes, based on the 8.15 percent
value used in the RIA for the 2003 HOS rule. A higher value of 18
percent involvement in fatigue-related crashes also was used as a
sensitivity analysis, chosen to be roughly as far above the LTCCS
value of 13 percent as the 8.15 percent pre-2003 estimate is below
13 percent.

            Table 7--Estimated Safety Benefits by Fatigue Crash Rate for Option 2 (10 Hours Driving)
                                                [Millions 2008$]
----------------------------------------------------------------------------------------------------------------
                                                          Benefits due to    Benefits due to
                                                           reduced daily      reduced weekly     Total benefits
     Assumed percent of crashes due to fatigue \17\         time on task       time on task      due to reduced
                                                             effect \a\         effect \b\          crashes
----------------------------------------------------------------------------------------------------------------
7......................................................               $110               $210               $320
13.....................................................                210                390                600
18.....................................................                290                540                830
----------------------------------------------------------------------------------------------------------------
\a\ Acute fatigue from long hours in a day.

\b\ Cumulative fatigue from long hours over many days.

            Table 8--Estimated Safety Benefits by Fatigue Crash Rate for Option 3 (10 Hours Driving)
                                                [Millions 2008$]
----------------------------------------------------------------------------------------------------------------
                                                          Benefits due to    Benefits due to
                                                           reduced daily      reduced weekly     Total benefits
       Assumed percent of crashes due to fatigue            time on task       time on task      due to reduced
                                                             effect \a\         effect \b\          crashes
----------------------------------------------------------------------------------------------------------------
7......................................................                $10               $150               $150
13.....................................................                 10                270                280
18.....................................................                 10                380                390
----------------------------------------------------------------------------------------------------------------
\a\ Acute fatigue from long hours in a day.
\b\ Cumulative fatigue from long hours over many days.
Note: Totals do not add due to rounding.

            Table 9--Estimated Safety Benefits by Fatigue Crash Rate for Option 4 (10 Hours Driving)
                                                [Millions 2008$]
----------------------------------------------------------------------------------------------------------------
                                                          Benefits due to    Benefits due to
                                                           reduced daily      reduced weekly     Total benefits
       Assumed percent of crashes due to fatigue            time on task       time on task      due to reduced
                                                             effect \a\         effect \b\          crashes
----------------------------------------------------------------------------------------------------------------
7......................................................               $290               $320               $610
13.....................................................                550                590              1,130
18.....................................................                760                810              1,570
----------------------------------------------------------------------------------------------------------------
\a\ Acute fatigue from long hours in a day.
\b\ Cumulative fatigue from long hours over many days.
Note: Totals do not add due to rounding.

    The analysis also calculated benefits associated with improvements
in driver health. The Agency has a statutory mandate to ensure that
driving conditions do not impair driver health. Research indicates that
reducing total daily and weekly work for the drivers working high-
intensity schedules should result in these drivers getting more sleep
on a daily and weekly basis. Recent research on sleep indicates that
inadequate sleep is associated with increases in mortality. This effect
appears to involve several complex pathways, including an increase in
the propensity for workplace (and leisure time) crashes and mortality
due to decrements in several health-related measures, such as an
increase in the incidence of high blood pressure, obesity, diabetes,
other cardiovascular disease (CVD), and other health problems. See
Appendix B of the RIA for the references for this statement. The
analysis attempted to model the workplace transportation crash effect
explicitly in the crash reduction benefits. However, explicit modeling
of all the other various ways that insufficient sleep increases
mortality becomes too complex and uncertain for this analysis. The
studies the analysis relied on to model health benefits, therefore, are
population-based studies that look at overall mortality, independent of
the cause of death, as a function of sleep. Because increases in hours
worked are associated with decreases in hours spent sleeping and truck
drivers working high-intensity schedules get significantly less than
the 7 to 8 hours of sleep that studies generally show are required for
optimal mortality. Cutting back somewhat on daily work hours and more
significantly cutting back on weekly work hours should, to some extent,
reduce mortality among these drivers.
    These benefit estimates depend on how much sleep CMV drivers
currently get and how much more sleep they are expected to get under
the proposed rule. The analysis developed a function that relates hours
worked to hours slept and used this function to predict how much more
sleep drivers would get under the proposed rule than they currently
obtain under the existing rule. The results of this analysis are
sensitive to the amount of sleep drivers are currently getting;
increases in sleep have less substantial health benefits if individuals
are already getting close to the optimal 7-8 hours per night than if
they average less sleep. Since there is a degree of uncertainty
surrounding how much sleep drivers currently get, a sensitivity
analysis varied the baseline amount of sleep drivers are currently
obtaining. This analysis showed that health improvement benefits are
greatest when drivers are getting the least sleep under the current
rule, because they have the most room for improvement.
    The sensitivity analysis scenarios are divided into the low sleep,
medium sleep, and high sleep categories. Under the low sleep scenario,
the benefits are greatest because it is the most pessimistic regarding
how much sleep drivers currently obtain. The high sleep scenario
assumed that drivers are getting close to the optimal amount; as a
result, there is little if any benefit to giving them opportunity for
more sleep. Results of this analysis indicate that the measurable
health benefits of reducing the maximum hours of work allowed per week
could well be as great as the costs, and other possible health benefits
(which have not been included in the quantitative analysis) could add
even further to these benefits. The health benefits of Options 2
through 4 were estimated for three different levels of baseline sleep
by drivers at 7 and 3 percent discounting of future health benefits
(shown in Table 10). For the assumption of a high level of baseline
sleep for Options 2 and 4, it is interesting to note that the benefits
are negative (to a relatively minor extent for Option 2), indicating
that it is not beneficial for individuals to get additional sleep if
they are already getting adequate sleep.

                                         Table 10--Estimated Health Benefits by Amount of Sleep for All Options
                                                            [3 and 7 Percent discount rates]
                                                                    [Millions 2008$]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Total benefits due to increased sleep
                                                         -----------------------------------------------------------------------------------------------
        Assumed baseline amount of nightly sleep                       7 Percent discounting                           3 Percent discounting
                                                         -----------------------------------------------------------------------------------------------
                                                             Option 2        Option 3        Option 4        Option 2        Option 3        Option 4
--------------------------------------------------------------------------------------------------------------------------------------------------------
Benefits with Low Sleep.................................            $810            $630          $1,110          $1,090            $850          $1,490
Benefits with Medium Sleep..............................             380             350             370             510             470             500
Benefits with High Sleep................................             -50              70            -370             -70              90            -500
--------------------------------------------------------------------------------------------------------------------------------------------------------

    In addition to the quantified and monetized benefits discussed
above, there may be other health benefits that shorter work days and
weeks could produce. Research indicates that the metabolic and
endocrine disruptions associated with short sleep time and long work
hours are significantly related to obesity (Van Cauter). Obesity is in
turn associated with higher incidences of diabetes, CVDs, hypertension,
and obstructive sleep apnea (Mokdad). These medical conditions impose
costs on drivers who suffer from them and affect the quality of their
lives. Sedentary work alone is also associated with obesity and
mortality impacts (Katzmarzyk).
    Research on the health of drivers and health costs found that CMV
drivers are both heavier for their height and less healthy than adult
males as a whole. Drivers are far more likely than adult male workers
as a whole to be obese. Table 11 presents the distribution of drivers
by weight category and the incidence of health conditions for drivers
in each weight group, taken from a study that used medical examination
records and health insurance claims of 2,950 LTL drivers (Martin). (The
national statistics for the incidence of health conditions among adult
males include men over 70, who may have higher incidences of some
conditions than the younger working population.)

                              Table 11--Driver Health Conditions by Weight Category
----------------------------------------------------------------------------------------------------------------
                                      Percent
                                    drivers in    Presence of at                                       High
            N = 2,950                 weight         least one     Hypertension      Diabetes       cholesterol
                                     category       health risk      (percent)       (percent)       (percent)
                                     (percent)        factor
----------------------------------------------------------------------------------------------------------------
Normal weight...................              13              26           21               5              11
Overweight......................              30              39           31              10              17
Obese...........................              55              59           51              21              26
Overall.........................  ..............              48           41              16              21
National adult male (CDC          ..............  ..............           31.80       \1\ 10.9            15.60
 statistics)....................
----------------------------------------------------------------------------------------------------------------
\1\ 7.4% diagnosed.

    FMCSA has not attempted to quantify the benefits of improved health
that may accrue to drivers who have more time off. First, the Agency
does not have dose-response curves that it can use to associate sleep
time with mitigation or exacerbation of the various health impacts
other than sleep loss itself. Second, many of the health impacts are
linked to obesity; given the difficulty most people have in losing
weight, it would be unjustifiably optimistic to attempt to estimate the
degree of potential weight loss.
    The health consequences of long hours, inadequate sleep, and long
stretches of sedentary work are, however, significant: they cause
serious health conditions that may shorten a driver's life and increase
healthcare costs. In addition, some studies have linked obesity to
increased crash risks, including a recent analysis of the VTTI data,
which found that obese CMV drivers were between 1.22 and 1.69 times as
likely to drive while fatigued, 1.37 times more likely to be involved
in an SCE, and at 1.99 times greater risk of being above the fatigue
threshold as measured by eye closure when driving (Wiegand).
Conclusion
    Net benefits (i.e., benefits minus costs) are likely to be
positive, but could range from a negative $730 million per year to more
than a positive $630 million per year for Option 2 (a negative $750
million to positive $920 million with 3 percent discounting), from a
negative $250 million to more than a positive $550 million for Option 3
(a negative $220 million to a positive $770 million with 3 percent
discounting), and from a negative $2.05 billion to more than a positive
$390 million for Option 4 (a negative $2.18 billion to a positive $780
million), as shown in Tables 12 through 14 below. The wide ranges in
estimates of benefits and net benefits are a consequence of the
difficulty of measuring fatigue and fatigue reductions, which are
complex and often subjective concepts, in an industry with diverse
participants and diverse operational patterns. Still, it seems clear
that the benefits could easily be substantial, and are on the same
scale as the costs. The costs, for their part, are large in absolute
terms but minor when compared to the size of the industry: $1.00
billion per year (the total annualized cost for Option 2) is less than
two thirds of 1 percent of revenues, $470 million per year (the total
annualized cost for Option 3) is less than one third of 1 percent of
revenues, and $2.29 billion per year (the total annualized cost for
Option 4) is less than 1.5 percent of revenues in the for-hire LH
segment of the industry. These total annual costs are an even smaller
fraction of revenues of the LH segment as a whole. As an additional
example, the costs of Option 3 are equivalent to about a $0.03 per
gallon increase in long-haul industry fuel costs, which is a minimal
increase in an industry used

to wide swings in fuel costs. Between 2006 and 2010, diesel fuel prices
ranged from $2.09 a gallon to $4.70 a gallon.\18\
---------------------------------------------------------------------------

    \18\ U.S. Energy Information Administration, Gasoline and Diesel
Fuel Update, http://www.eia.gov/oog/info/gdu/gasdiesel.asp#.

                                  Table 12--Net Benefits for Option 2 by Sleep Scenario, Crash Rate, and Discount Rate
                                                                    [Millions 2008$]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Assumed amount of nightly sleep
                                                         -----------------------------------------------------------------------------------------------
        Assumed percent of crashes due to fatigue                      7 Percent discounting                           3 Percent discounting
                                                         -----------------------------------------------------------------------------------------------
                                                             Low sleep     Medium sleep     High sleep       Low sleep     Medium sleep     High sleep
--------------------------------------------------------------------------------------------------------------------------------------------------------
7.......................................................            $130           -$300           -$730            $410           -$170           -$750
13......................................................             400             -20            -450             690             110            -470
18......................................................             630             210            -220             920             340            -240
--------------------------------------------------------------------------------------------------------------------------------------------------------

                                  Table 13--Net Benefits for Option 3 by Sleep Scenario, Crash Rate, and Discount Rate
                                                                    [Millions 2008$]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Assumed amount of nightly sleep
                                                         -----------------------------------------------------------------------------------------------
        Assumed percent of crashes due to fatigue                      7 Percent discounting                           3 Percent discounting
                                                         -----------------------------------------------------------------------------------------------
                                                             Low sleep     Medium sleep     High sleep       Low sleep     Medium sleep     High sleep
--------------------------------------------------------------------------------------------------------------------------------------------------------
7.......................................................            $310             $30           -$250            $530            $150           -$220
13......................................................             440             160            -120             660             280             -90
18......................................................             550             270             -10             770             390              20
--------------------------------------------------------------------------------------------------------------------------------------------------------

                                  Table 14--Net Benefits for Option 4 by Sleep Scenario, Crash Rate, and Discount Rate
                                                                    [Millions 2008$]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Assumed amount of nightly sleep
                                                         -----------------------------------------------------------------------------------------------
        Assumed percent of crashes due to fatigue                      7 Percent discounting                           3 Percent discounting
                                                         -----------------------------------------------------------------------------------------------
                                                             Low sleep     Medium sleep     High sleep       Low sleep     Medium sleep     High sleep
--------------------------------------------------------------------------------------------------------------------------------------------------------
7.......................................................           -$570         -$1,310          $2,050           -$180         -$1,180         -$2,180
13......................................................             -50            -790          -1,520             340            -660          -1,650
18......................................................             390            -350          -1,090             780            -220          -1,220
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Compared to the other two options that were analyzed, Option 2
would have roughly twice the costs of Option 3 (which allows 11 hours
of daily driving), and less than half the cost of Option 4 (which
allows 9). In keeping with their relative stringencies, Option 3 has
lower, and Option 4 has higher, projected benefits than Option 2.
Option 3's calculated net benefits appear likely to be somewhat higher
than the net benefits of Option 2 under some assumptions about baseline
conditions. Option 4's substantially larger costs, on the other hand,
did not appear to be justified by its generally higher range of
benefits. Based on the estimated net benefits of the options, FMCSA has
selected Option 3 as the Final Rule. The Agency's goal of improving
highway safety and protecting driver health, combined with the
potentially significant but unquantifiable health benefits of
reductions in maximum working and driving hours, make the functional
equivalent of Option 3--the final rule does not change a driving-time
limit but retains the current 11-hour limit--the most reasonable
choice.
Changes in the Analysis of HOS Options From the NPRM to the Final Rule
    There are two distinct categories of changes that result in
different estimates of the costs and benefits of the HOS options
between the NPRM and the Final Rule:
     Changes to the options, some of which change the cost/
benefit calculations for all of the options; and
     As recommended by commenters, refinements to the benefit
analyses, which change the estimated benefits, and thus the estimated
net benefits, for each of the options.
    The changes that fall into these two categories are discussed
below, followed by a description of how they affect the estimated costs
and benefits.
    After considering the comments received on the NPRM and new
research, as well as the President's Executive Order 13563 on
``Improving Regulation and Regulatory Review,'' FMCSA has made several
changes to the HOS options considered in the NPRM, including the
following:
     Eliminating a driving-time limit from the final rule.
     Dropping the 13-hour limit on on-duty time between breaks
of at least 10 hours, but keeping the provision requiring at least a
half-hour break part-way through long days.
     Shortening the 2-night restart window from two periods
including midnight and 6 a.m. to two periods including 1 a.m. through 5
a.m.

     Changing the break requirements to require a break of a
half-hour (or more) within the past 8 hours of continuous work, rather
than 7, to continue driving.
     Dropping the provision that would have allowed two 16-hour
driving windows per week.
    Only the first three of these changes affect the cost/benefit
calculations. The other two do not change the cost/benefit calculations
because the analyses for the NPRM were not sensitive to the particular
provisions involved: the effects of breaks were considered to be
subsumed within the effect of the daily limit on duty hours, and the
use of a 16-hour driving window was not modeled due to uncertainty
about how and how much it would be used and the small expected
magnitude of its effects.
    In response to comments and its own review of the analysis of
safety benefits, FMCSA has made three refinements to its benefits
analysis of the HOS options. First, as suggested by the Edgeworth
study, the safety benefits of reductions in cumulative fatigue are
being estimated using a finer-grained function. Because this change
affects all of the options to about the same extent, it has no real
effect on the relative rankings of the options. Similarly, in response
to the Edgeworth study, FMCSA has also refined its estimate of the
value of reducing crash damages per hour of effort reallocated from one
driver to another. Because this refinement affects all of the options
equally, it has no effect on their relative ranking. Third, the Agency
has made technical adjustments in the way it calculated and discounted
health benefits due to improvements in sleep duration. Careful re-
examination of the Ferrie study, occasioned by disagreements in docket
comments submitted by Ferrie and Cappuccio on the applicability of
their work to HOS rulemaking, suggested that a more refined estimate of
the health benefits was possible and should be undertaken. This new
analysis ultimately had minimal impact on the cost-benefit analysis,
and did not impact the Agency's decision to choose option 3 in the
final rule.
    Chapter 5 of the RIA presents in detail the methodology used to
make these changes. These changes have the effect of moderately
reducing benefits associated with improvements in driver health. The
size of the reduction in benefits is affected by the discount rate,
with a 3 percent discount rate having a smaller impact. Although the
Agency norm is to present all impacts in the RIA--including driver
health benefits--discounted at 7 percent, the Agency applies equal
weight to results using the 3 percent discount rate. Using a 3 percent
discount rate, the options rank the same with or without the
methodological refinements--Option 3 (11 hours) would be the preferred
option at medium sleep, but Option 2 (10 hours) would have higher net
benefits at low sleep. Discounted at 7 percent, Option 3 would have
higher net benefits at both low sleep and medium sleep than Option 2.
Option 4 (9 hours) would be the least likely to have positive net
benefits, and its net benefits would be lower than the other two
options under any scenario.

B. Regulatory Flexibility Act

    The Regulatory Flexibility Act (5 U.S.C. 601 et seq.) requires
Federal agencies to determine whether rules subject to notice and
comment could have a significant economic impact on a substantial
number of small entities. FMCSA completed a Final Regulatory
Flexibility Analysis (FRFA) to analyze the impact of the proposed
changes to the HOS regulations on small entities.
1. A Statement of the Need for, and Objectives of, the Rule
    The objectives of the today's changes to the HOS rule are to
improve safety in the most cost-effective manner while ensuring that
the requirements do not have an adverse impact on driver health. The
impact of HOS rules on CMV safety is difficult to separate from the
many other factors that affect heavy-vehicle crashes. While the Agency
believes that the data show no decline in highway safety since the
implementation of the 2003 HOS rule and its re-adoption in the 2005 HOS
rule, the 2007 IFR, and the 2008 HOS rule (73 FR 69567, 69572, Nov. 19,
2008), the total number of crashes, though declining, is still
unacceptably high. Moreover, the source of the decline in crashes is
unclear. FMCSA believes that the required break during long days, and
the limits on maximum weekly hours, coupled with FMCSA's many other
safety initiatives and assisted by the actions of an increasingly
safety-conscious motor carrier industry, will result in continued
reductions in fatigue-related CMV crashes and fatalities. Furthermore,
the changes in the rule are intended to protect drivers from the
serious health problems associated with excessively long work hours,
without significantly compromising their ability to do their jobs and
earn a living.
2. A Summary of the Significant Issues Raised by the Public Comments in
Response to the RFA, a Summary of the Assessment of the Agency of Such
Issues, and a Statement of Any Changes Made in the Proposed Rule as a
Result of Such Comments
    Comments. Very few commenters directly addressed the Initial RFA
analysis. Commenters generally stated that the rule would affect
revenues of carriers, but these impacts were not specific to small
entities. Shippers and receivers also argued that they would be
affected, but these entities are not subject to FMCSA regulations and
are not, therefore, considered in the RFA analysis. The Petroleum
Marketers Association of America stated that the changes to the restart
provision would have a serious impact on small heating oil and propane
suppliers. They would need to hire extra drivers to cover emergency
deliveries.
    FMCSA Response. As stated in previous responses, the restart
provision will affect only drivers working the longest hours. Without
information on the hours being worked by drivers for fuel retailers, it
is difficult to assess whether they will be affected, but most local
drivers do not work 60 to 70 hours a week and, therefore, are not
limited by the restart provision. In any case, drivers of CMVs used
primarily in the transportation of propane for winter heating are
statutorily exempt from most of the regulations in the FMCSRs if
compliance with those regulations would prevent the driver from
responding to an emergency condition requiring immediate response (see
49 CFR 390.3(f)(7)).
3. The Response of the Agency to Any Comments Filed by the Chief
Counsel for Advocacy of the Small Business Administration (SBA) in
Response to the Proposed Rule, and a Detailed Statement of Any Change
Made to the Proposed Rule in the Final Rule as a Result of the Comments
    The Office of Advocacy at SBA filed comments that were a summary of
concerns raised by industry at a roundtable that it hosted on February
9, 2011. As SBA indicated, the comments are ``nearly identical to many
of those expressed at FMCSA's public listening session on the proposed
rule * * *.'' Summarized, the points are as follows:
     The proposed rule is not supported by existing safety and
health data.
     The proposed rule would reduce flexibility and could
actually impede safety and driver health by increasing the stress on
drivers as they try to work within the limits.

     The proposed rule would be operationally disruptive and
costly.
     Truck related crashes are decreasing under the current
rules, even while truck miles driven have increased.
    FMCSA Response. As has been stated throughout this preamble, FMCSA
disagrees strongly with these industry claims. The rule is supported by
research on crashes and the health effects of long hours on health.
Research on the effects of long work hours on crash rates, both for
drivers and for other workers clearly indicate that risk rises after 8
hours of work. The research on the health effects of sleep loss and
long hours is also extensive.
    On the idea that the limits put stress on drivers, the Agency notes
that any limit will do this for a driver who is working to the limits.
The only way to remove this stress is to allow drivers and carriers to
work as many hours as they want regardless of the safety consequences.
Research has shown that drivers (and everyone else) have very little
ability to accurately assess their own fatigue levels, as is also
evidenced by the high percentage of CMV drivers who admit to falling
asleep at the wheel. Today's rule allows the hardest working drivers to
average 70 hours a week, which is surely enough.
    The claims of serious operational disruptions are unsupported by
any data and contradicted by the industry's own statements that the
provisions at issue are not used by most drivers. SBA noted that
carriers are subject to factors beyond their control, such as loading
dock availability. FMCSA recognizes that carriers cannot control
shippers and receivers, but allowing drivers to regularly work maximum
hours is not a reasonable solution to that problem. On SBA's final
point, Section IV. ``Discussion of All Comments'' A. ``Safety'' of this
preamble discusses the flaws in this argument at length.
    FMCSA has made changes to the final rule to reduce the complexity
of the rule and provide some flexibility. The periods required under
the 2-night restart provision are 2 hours shorter than proposed; this
change will provide more flexibility for drivers who work at night
irregularly. Most drivers who have regular nighttime schedules already
take 2 nights off a week and do not need to use the restart provision.
The final rule also changes the break requirement to make it easier for
drivers using the sleeper berth provision. Finally, FMCSA has removed
the 13-hour duty time limit to reduce the complexity of the final rule.
4. A Description and an Estimate of the Number of Small Entities to
Which the Rule Will Apply or an Explanation of Why No Such Estimate Is
Available
    The HOS regulations apply to both large and small motor carriers.
The SBA defines a small entity in the truck transportation sub-sector
(North American Industry Classification System [NAICS] 484) as an
entity with annual revenue of less than $25.5 million [13 CFR 121.201].
Using data from the 2007 Economic Census, FMCSA estimated that the
average carrier earns roughly $160,000 in annual revenue per truck for
firms with multiple power units,\19\ suggesting that a typical carrier
that qualifies as a small business would have fewer than 141 ($25.5
million/$160,000) power units (i.e., trucks or tractors) in its fleet.
From the 2007 Economic Census data on non-employer firms, sole
proprietorships earn approximately $107,700 in annual revenue.
---------------------------------------------------------------------------

    \19\ See the RIA Appendix A for the revenue per power unit. A
firm with one power unit and two drivers would have even higher
revenues per truck because the two drivers could drive more hours
than a firm with a single driver.
---------------------------------------------------------------------------

    To determine the number of affected small entities, we used the
analysis conducted by FMCSA for the Unified Carrier Registration (UCR)
rule.\20\ The economic analysis for the UCR rule divided carriers into
brackets based on their fleet size (i.e., number of power units), and
estimated the number of carriers in each bracket. These brackets and
their corresponding numbers of carriers are shown in Table 15.
According to these estimates and the above-mentioned characterizations
of small entities in the trucking industry, all of the carriers in
Brackets 1 through 4 would qualify as small entities, as would many of
the carriers in Bracket 5. Therefore, this analysis estimates that
between 422,196 (Brackets 1 through 4) and 425,786 (Brackets 1 through
5) small entities would be affected by the HOS rule changes. This range
overstates the number of affected small entities for several reasons.
First, many private carriers with small fleets may not qualify as small
businesses because their primary business is not the movement of
freight. These private firms have other sources of revenue and fall
under different NAICS codes; for example, one of the largest pharmacy
chains has fewer than 141 power units, but is not a small entity.
Second, the carriers are allowed to register by location so that a
single firm may have multiple DOT registrations, each of which appears
to be small, but which at the firm level represents a large entity.
Third, the carrier numbers include firms that are not subject to this
rule, such as passenger-carrying carriers and utilities, or are subject
to only part of the rule (e.g., construction firms have a different
restart provision).
---------------------------------------------------------------------------

    \20\ FMCSA, ``Regulatory Evaluation of the Fees for the Unified
Carrier Registration Plan,'' February 19, 2010. Available in the
docket: FMCSA-2009-0231-0181.

               Table 15--Number of Carriers by Fleet Size
  [From FMCSA's analysis of the unified carrier registration plan rule]
------------------------------------------------------------------------
                                                            Number of
               Bracket                   Fleet size         carriers
------------------------------------------------------------------------
1...................................                 1           194,425
2...................................               2-5           145,266
3...................................              6-20            65,155
4...................................            21-100            17,350
5...................................         101-1,000             3,590
6...................................            1,001+               292
                                     -----------------------------------
    Total...........................  ................           426,078
------------------------------------------------------------------------

    Table 16 below presents figures for private carriers by NAICS code
for industries with large numbers of drivers (and hence the likelihood
of large numbers of fleets). The table includes the total number of CMV
drivers

working in each industry, the percentage of payroll those drivers
account for, and the payroll of those industries as a percent of total
industry revenue. Some of these industries have SBA size thresholds
that are considerably lower than the threshold for truck
transportation, strongly suggesting that many firms in these industries
that would be considered small using the threshold of 141 power units
are actually large. For example, a wholesaler with 141 trucks is
certainly a large firm because it will have more than 100 employees.
Other industries have thresholds as high as 1,500 full-time equivalent
employees (FTEs); a firm in one of these industries might rank as small
with even more than 141 power units if the number of power units in its
fleet were large compared to the size of its workforce (e.g., if it had
300 power units, and only three employees per power unit, it could be
considered small in an industry with a threshold of 1,500 FTEs). From
Table 16, however, this circumstance is not likely to be common: in
firms in NAICS 21 and 31-33, which have high FTE thresholds, drivers
make up only a very small percentage of the workforce. Thus, firms with
a substantial numbers of power units are likely to have much larger
labor forces, and are therefore likely to rank as large firms. Given
these considerations, we are, if anything, over-counting the number of
private carriers that qualify as small businesses.

                                                   Table 16--Private Carriers and Drivers by Industry
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                Drivers as        Payroll as
                  NAICS                             Industry                   SBA standard             Number of      percent of all      percent of
                                                                                drivers          employees         revenues
--------------------------------------------------------------------------------------------------------------------------------------------------------
21......................................  Mining, Quarrying, and Oil   500 FTE....................            29,900              4.17                10
                                           and Gas Extraction.
23......................................  Construction...............  $14 million to $33.5                  127,200              1.76                19
                                                                        million.
31-33...................................  Manufacturing..............  500-1,500 FTE..............           238,600              1.78                11
42......................................  Wholesale..................  100 FTE....................           509,000              8.53               5.5
44-45...................................  Retail.....................  $7 million to $29 million..           307,900              2.01                10
53......................................  Real Estate and Leasing....  $7 million to $25 million..            40,500               1.9                18
56......................................  Administrative and Support   $7 million to $35.3 million           132,300              1.64                46
                                           and Waste Management and
                                           Remediation Services.
722.....................................  Food Services..............  $7 million.................           175,400              1.82                29
81......................................  Other Services.............  $7 million.................            44,000              0.80                24
--------------------------------------------------------------------------------------------------------------------------------------------------------

    The analysis of the impact of the HOS rule on small entities shows
that, while it is unlikely for the rule to have a significant impact on
most small entities, FMCSA cannot certify that there would be no
significant impacts. For a typical firm, the first-year costs of the
final rule are well below 1 percent of revenues, as are the average
annual costs when spread over 10 years.
    However, projecting the distribution of impacts across carriers,
few of which fit the definition of typical, is made more difficult by
the variability in both costs and revenues. The new HOS rule is
designed to rein in the most high-intensity patterns of work while
leaving more moderate operations largely unchanged. As a result, we
project a substantial majority of the costs of the rule to fall on the
sixth of the industry currently logging the most hours per week. Thus,
most carriers are likely to be almost unaffected, while a minority
could experience productivity impacts--and hence costs--well above the
industry average.
    Average revenues presumably range widely as well, meaning that the
ratio of costs to revenues is difficult to characterize. Because
greater work intensities are likely to generate greater revenues,
though, the impacts and revenues per power unit are likely to be
positively correlated: the carriers for which productivity is curtailed
the most and which could incur the greatest costs will, therefore, be
likely to have unusually large revenues per power unit as well.
5. A Description of the Projected Reporting, Recordkeeping, and Other
Compliance Requirements of the Rule, Including an Estimate of the
Classes of Small Entities Which Will Be Subject to the Requirement and
the Type of Professional Skills Necessary for the Preparation of the
Report or Record
    The rule does not change recordkeeping or reporting requirements.
Drivers are required by current rules to keep records of duty status
that document their daily and weekly on-duty and driving time, and
submit these records of duty status to their employing motor carrier on
a bi-weekly basis. This rule does not change or add to this
recordkeeping requirement for drivers or carriers. Drivers in all
segments of the industry, including independent owner-operators, are
well accustomed to complying with these recordkeeping and reporting
requirements, and no professional skill over and above those skills
that drivers already possess would be necessary for preparing these
reports. All small entities in the industry that operate in interstate
commerce are subject to these rules. The type and classes of these
small entities are described in the previous section of this analysis.
6. A Description of the Steps the Agency Has Taken To Minimize the
Significant Adverse Economic Impact on Small Entities Consistent With
the Stated Objectives of Applicable Statutes, Including a Statement of
the Factual, Policy, and Legal Reasons for Selecting the Alternative
Adopted in the Final Rule and Why Each of the Other Significant
Alternatives to the Rule Considered by the Agency Was Rejected
    The Agency did not identify any significant alternatives to the
rule that could lessen the burden on small entities without
compromising its goals. However, in response to docket comment from the
motor carrier industry, in which small entities are very heavily
represented, the Agency did modify the options proposed in the NPRM to
reduce both the cost and complexity of the rule adopted today. These
changes include retaining the 11-hour daily driving limit, and
shortening the 2 nighttime periods required by the new restart
provision by one-third, from 12 midnight-6 a.m. to 1 a.m.-5 a.m. This
rule is targeted at preventing driver fatigue, and the Agency is
unaware of any alternative to restricting driver work that the Agency
has authority to implement that would address driver fatigue. This rule
impacts motor carrier

productivity proportionally to the number of drivers a motor carrier
employs and the intensity of the schedules that motor carrier's drivers
work. It is not obvious that productivity losses would be greater for
small entities than for larger firms. To the extent that drivers
working for a small entity work more intense schedules, that entity may
experience greater productivity losses than a carrier whose drivers
work less intensely on a daily and weekly basis. However, there appears
to be no alternative available to the Agency that would limit driver
fatigue while allowing more work. To improve public safety, all
drivers, regardless of the size of the carrier they work for, must work
within reasonable limits.
    The recordkeeping and reporting burdens related to this rule will
also affect entities proportional to the number of drivers they employ,
and therefore do not disproportionately affect small motor carriers in
any way. As noted above, drivers in all segments of the industry,
working for entities of all sizes, are accustomed to compiling and
submitting records of duty status on a regular basis. This rule will
therefore not place an undue recordkeeping or reporting burden on
smaller entities.

C. Paperwork Reduction Act

    This rule would call for no new collection of information under the
Paperwork Reduction Act of 1995 (44 U.S.C. 3501-3520).

D. National Environmental Policy Act

    The Agency analyzed this rule for the purpose of the National
Environmental Policy Act of 1969 (NEPA) (42 U.S.C. 4321 et seq.) and
determined under our environmental procedures Order 5610.1, published
March 1, 2004 in the Federal Register (69 FR 9680), that this action
will not have a significant impact on the environment. FMCSA has also
analyzed this rule under the Clean Air Act, as amended (CAA) section
176(c), (42 U.S.C. 7401 et seq.) and implementing regulations
promulgated by the Environmental Protection Agency. Approval of this
action is exempt from the CAA's general conformity requirement since it
would not result in any potential increase in emissions that are above
the general conformity rule's de minimis emission threshold levels (40
CFR 93.153(c)(2)). The Agency received no comments on the draft
Environmental Assessment, published with the NPRM. A copy of the
Environment Assessment is available in the docket.

E. Executive Order 13132 (Federalism)

    A rule has implications for Federalism under Executive Order 13132,
Federalism, if it has a substantial direct effect on State or local
governments and would either preempt State law or impose a substantial
direct cost of compliance on them. This action has been analyzed in
accordance with E.O. 13132. FMCSA has determined this rule would not
have a substantial direct effect on States, nor would it limit the
policymaking discretion of States. Nothing in this document preempts
any State law or regulation.

F. Privacy Impact Assessment

    FMCSA conducted a Privacy Threshold Analysis (PTA) for the rule on
hours of service and determined that it is not a privacy-sensitive
rulemaking because the rule will not require any collection,
maintenance, or dissemination of Personally Identifiable Information
(PII) from or about members of the public.

G. Executive Order 12630 (Taking of Private Property)

    This rule would not effect a taking of private property or
otherwise have taking implications under Executive Order 12630,
Governmental Actions and Interference with Constitutionally Protected
Property Rights.

H. Executive Order 12988 (Civil Justice Reform)

    This rule meets applicable standards in sections 3(a) and 3(b)(2)
of Executive Order 12988, Civil Justice Reform, to minimize litigation,
eliminate ambiguity, and reduce burden.

I. Executive Order 13045 (Protection of Children)

    FMCSA analyzed this rule under Executive Order 13045, Protection of
Children from Environmental Health Risks and Safety Risks. This rule
would not create an environmental risk to health or risk to safety that
might disproportionately affect children.

J. Executive Order 13211 (Energy Supply, Distribution, or Use)

    FMCSA analyzed this rule under Executive Order 13211, Actions
Concerning Regulations That Significantly Affect Energy Supply,
Distribution, or Use. FMCSA determined that it is not a ``significant
energy action'' under that order. Though it is a ``significant
regulatory action'' under Executive Order 12866, it is not likely to
have a significant adverse effect on the supply, distribution, or use
of energy. The Administrator of the Office of Information and
Regulatory Affairs has not designated it as a significant energy
action. Therefore, it does not require a Statement of Energy Effects
under Executive Order 13211.

K. Executive Order 12898 (Environmental Justice)

    FMCSA evaluated the environmental effects of this NPRM in
accordance with Executive Order 12898 and determined that there are no
environmental justice issues associated with its provisions nor any
collective environmental impact that could result from its
promulgation. Environmental justice issues would be raised if there
were ``disproportionate'' and ``high and adverse impact'' on minority
or low-income populations. None of the alternatives analyzed in the
Agency's EA, discussed under NEPA, would result in high and adverse
environmental impacts.

L. Unfunded Mandates Reform Act

    The Unfunded Mandates Reform Act of 1995 (2 U.S.C. 1531-1538)
requires Federal agencies to assess effects of their discretionary
regulatory actions. In particular, the Act addresses actions that may
result in the net expenditure by a State, local, or tribal government,
in the aggregate, or by the private sector of $143.1 million or more in
any one year. Though this rule would not result in a net expenditure at
this level, the economic impacts of the rule have been analyzed in the
RIA.

VII. Bibliography

[Aring]kerstedt, T., ``Shift Work and Disturbed Sleep/Wakefulness,''
Occupational Medicine, Vol. 53, 2003, pp. 89-94. FMCSA-2004-19608-
4037.
[Aring]kerstedt, T. & Wright, K.P., ``Sleep Loss and Fatigue in
Shift Work and Shift Work Disorder,'' Sleep Medicine Clinics, Vol.
4, No. 2, pp. 257-271, June 2009. Retrieved June 17, 2011, from:
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2904525/pdf/nihms215779.pdf.
American Trucking Associations, ``Trucking Activity Report
Historical Truckload Sector Database,'' March 2011. Available online
at http://www.atabusinesssolutions.com/p-24-ata-trucking-activity-report-trac.aspx.
Balkin, T., Thorne, D., Sing, H., Thomas, M., Redmond, D.,
Wesensten, N., Williams, J., Hall, S., & Belenky, G., ``Effects of
Sleep Schedules on Commercial Motor Vehicle Driver Performance,''
FMCSA, Washington, DC, 2000. FMCSA-2004-19608-2007.
Belenky, G., Wesensten, N.J., Thorne, D.R., Thomas, M.L., Sing,
H.C., Redmond, D.P., Russo, M.B. & Balkin, T.J., ``Patterns of
Performance Degradation and Restoration During Sleep Restriction and
Subsequent Recovery: A Sleep Dose-Response Study,'' Journal of Sleep
Research, Vol. 12, No. 1, March 2003, pp. 1-12. FMCSA-2004-19608-
3959.

Blanco, M., Hanowski, R., Olson, R., Morgan, J., Soccolich, S., Wu,
S.C., & Guo, F., ``The Impact of Driving, Non-Driving Work, and Rest
Breaks on Driving Performance in Commercial Motor Vehicle
Operations,'' FMCSA, April 2011. FMCSA-2004-19608-27612.
Bureau of Labor Statistics, DOL, ``Household Data Annual Averages,
23. Persons at Work by Occupation, Sex, and Usual Full- or Part-Time