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140 FATIGUE EFFECTS REFERENCES REVIEW SELECTION CRITERIA ing and quality of sleep. The researchers found that while the night shifts made drivers feel more tired than day shifts, they The 25 references included in this part were derived from a did not produce significantly poorer performance on tests of total of 266 references included in comments on the advanced PVT and Mackworth Clock, "suggesting that night drivers NPRM. Of the 266 references, 86 pertained to health effects can manage their fatigue." Over a typical workweek of five and were passed on to Dr. Peter Orris for evaluation. The consecutive 10- to 12-hour shifts, there was a significant remaining 180 articles were rated on a scale of 1 to 4 for rel- increase in subjective ratings of fatigue by all drivers. evance, with 34 given a score of 1, 25 a score of 2, and the Night shift drivers worked longer shifts than day shift driv- remaining 121, scores of 3 or 4. The most relevant (score of ers and spent much more of their working time driving than 1) 34 articles on performance, crash risk, and fatigue were day shift drivers "which might predict that night shifts would selected for review, of which 25 could be obtained. Articles be more tiring than day shifts." However, the authors suggest considered most relevant were those involving epidemiolog- that night shift drivers may have performed as well as day ical studies of CMV crash risk or field studies of performance shift drivers as they may be "especially tolerant of fatigue or of commercial drivers in relation to fatigue issues such as skilled at managing fatigue" and because they organize their daily and weekly hours, time of day, and short sleep, or stud- sleep differently (e.g., napping in the hours before their first ies of non-CMV drivers showing the effects of sleep loss and shift of the week) which may partly explain how they could comparing sleep loss and alcohol impacts. In Part I, no crash maintain performance. For example, the authors noted that studies were reviewed. night drivers "endeavored to capitalize on the sleep propen- The reasons for not reviewing the remaining articles sug- sity influences of the circadian rhythm by getting as much gested by commentators included the following: sleep as they could as close as possible to the early morning circadian trough when sleep is most likely." · The article was not published as a report of a recognized All drivers had restricted sleep (4 to 6 hours) and worked agency or in a peer-reviewed journal (e.g., a website long hours (50 to 55 hours arranged in five 10- to 12-hour only or popular magazine). shifts), which the authors believe may have overshadowed · The article was very general in nature (e.g., Sleep and any circadian differences. However, it could be argued this Circadian Disturbances in Shift Work: Strategies for would be more likely to exacerbate them. They note a prob- Their Management). lem of missing data. Also all tests were done when the vehi- · The article was not sufficiently relevant to the task of cle was stopped which may have re-alerted drivers. Other CMV driving and to the issue of fatigue and health studies which have used performance measures that were (e.g., A Photograph-Based Study of the Incidence of integral to the driving task, such as lane tracking control and Fatal Truck Underride Crashes in Indiana; Census of critical incidents, have found poorer performance at night, Fatal Occupational Injuries Summary; Effects on Per- compared with during the day, most notably the U.S.-Canada formance of High and Low Energy-Expenditure During study by Wylie et al. 1997, which compared different driving Sleep Deprivation). schedules as well as the study of long-haul single and team drivers by Dingus et al. 2001. Nonetheless the Williamson EXECUTIVE SUMMARY et al. (2004) findings are surprising given other studies where the PVT was sensitive to circadian effects (Dinges et al. 1997). Fatigue, Time of Day, and Performance The impacts of shift schedule on subjective fatigue and Scheduling Flexibility and Fatigue performance were measured in a field study by Williamson et al. (2004). In addition to permanent day shift and night Williamson et al. (2004) report further analysis of their shift drivers, drivers working alternating weeks of day and 1996 study (Williamson et al. 1996) in which 27 commercial night shifts participated in the study. Fifty-four drivers were drivers participated in each of three work practices: staged measured repeatedly over a 2-week period. Actigraph data trip driving (two drivers from different points of origin meet were also collected to provide objective measures of the tim- mid-trip and exchange loads), flexible trip driving (single
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141 driver, trip scheduled without reference to HOS regulations) · HOS regulations permit no discretion for different freight and single trip driving (single driver, within HOS regulations). tasks and environments. A range of fatigue measures were used including performance · HOS do not take account of the influence of the driver's tests, physiological and subjective measures. The authors circadian cycle. found that "a 1012 hour trip is tiring no matter how the work · HOS regulations take no account of time zone changes. is organized, and that the effects of accumulated fatigue may · HOS may restrict access to sleep. overshadow the effects of fatigue on a single 1012 hour trip." · There is no commercial incentive to restrict driving "Differences between driving types were not sufficient to to HOS. account for changes in fatigue or performance in this study. All drivers reported more fatigue over the trip, but not all driv- The numerous factors affecting fatigue and the difficulty ers showed poorer performance. It seems that the 12-hour trip of regulating hours of work to minimize it are discussed by is relatively immune to any effects of differences in work Moore-Ede and Schlesinger (2005). They argue that risk relat- practices. It is possible that studying such relatively short ing to work and rest hours is multi-factorial and that simplis- trips will not provide clear findings . . . It is certainly note- tic regulations based on only one or two factors have limited worthy that flexible trips produced no worse an outcome than value in minimizing this risk. Over 30 factors that determine either of the other two ways of doing the same trip. In fact, a level of sleepiness and fatigue-related accident risk are listed, more exhaustive evaluation of flexibility, where drivers have with the most important being circadian phase followed by the opportunity to learn about manipulating the timing of the number of consecutive hours spent continuously awake work and rest during several trips, might reveal that flexibil- since the previous sleep episode. Other important factors are ity is of benefit in managing fatigue. . . . It should be noted, the length of the sleep episode, the quality of sleep, job work- however that flexible drivers did tend to select work-rest load, and moment to moment stimulants or depressants of schedules which were quite similar to the regulated working alertness. The authors use two case studies to illustrate the hours. It would be interesting to determine whether this sim- problem with the current (11-hour driving) HOS regulations. ilarity persists when the trip is longer." In particular, they note the disincentive for drivers to take a Decrements in performance may be more detectable when nap when they are tired as daytime naps are only allowed to driving performance is measured as opposed to the alerting be excluded from a driver's hours on duty in certain situations situation of stopping to carry out a special performance test when the nap is followed by driving, which is in turn imme- as was done in this study. diately followed by an extended period of rest. The authors The findings of this study suggest that drivers do not make suggest that the efficacy of "alternative, less punitive, risk use of flexible schedules in a manner that reduces fatigue. management strategies based upon the science of fatigue Fatigue management programs may assist, especially if not management" should be demonstrated to provide the basis of only drivers but also dispatchers and managers are involved. HOS regulation. The authors suggest alternative paradigms A limitation is suggested by the Williamson study that indi- to the current work-rest regulations: fatigue management pro- cates little difference in fatigue effects on different schedules grams, fatigue risk models, alertness monitors. if sleep is restricted and hours are long. Regulated and unregulated HOS regimes were also com- pared using survey data by Hartley (1999). The Hartley et al. Long Weekly Hours and HOS Violations (1996) study on the impact of fatigue on heavy vehicle driv- ers in Western Australia (where there are no HOS regula- A number of studies have shown that despite the lengthy tions), was compared with Williamson and Feyer's 1992 hours allowed by HOS regulations (60 hours in 7 days or study, which contained a comparable survey of drivers work- 70 hours in 8 days), significant numbers of drivers work even ing under HOS in the eastern states. Drivers whose hours longer. Beilock et al. (1995) use self-reported data to estimate were not regulated were no more likely to exceed the HOS the frequency of HOS violation-inducing schedules for a sam- regulations that the drivers for whom those regulations were ple of 498 long-distance drivers. Twenty-six percent of the enforced. Drivers whose hours were not regulated were less drivers, assuming average legal speed limits of 55 mph, were likely to consider fatigue a problem than those whose hours found to have violation-inducing schedules. Drivers most were regulated. This may be due to less fatigue or to less likely to have these schedules included solo drivers, drivers awareness of the association of fatigue with poorer perfor- hauling refrigerated loads, regular route drivers, and those mance and increased crash risk. The authors list the follow- with longer current trip distances. The findings indicate that ing problems with HOS: the very large majority of long-distance drivers have more than 40-hour work weeks (82%, assuming average maintained · HOS prescribe what a driver should be capable of doing speeds of 50 mph), and extremely lengthy work weeks are (i.e., no flexibility). common. For example, assuming 50-mph average maintain- · HOS regulations do not inform organizations about ing speed, half the drivers work more than 65 hours weekly fatigue and safety. and one-quarter work over 81 hours.
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142 Hertz et al. (1990) found for 130 long-haul tractor trailer as the baseline. The accident risk of driving between 4:00 and drivers that at "assumed trip speeds of 40 mph and 50 mph, 6:00 p.m. was significantly higher (approximately 60% higher) 90% and 51% of the drivers, respectively, were in violation than that of the baseline. This was attributed to two effects: of the hours of service rules by more than one hour." evening rush hour and reduced alertness because of a low cir- cadian period for some drivers. The accident risks from mid- night to 2:00 a.m., 6:00 to 8:00 a.m., and 8:00 to 10:00 p.m. Long Hours, Time of Day, and Crash Risk were significantly higher than during the baseline. Two peri- ods involve night driving; the other involves part of the dawn Studies of the impact of long hours and time of day on crash period. Rest breaks, particularly those taken before the 6th or risk are methodologically challenging for a number of rea- 7th hr of driving, appeared to lower accident risk significantly sons. First, the distribution of trip lengths is such that there are for many times of day. more 4-hour trips than 8-hour or 12-hour trips. Consequently, Park et al. (2005) used pre-existing crash data from the there will be more crashes associated with 4-hour trips than 1980s and measurements from the Driver Fatigue and Alert- with 12-hour trips. This is a different issue from the risk per ness Study (DFAS) conducted in the mid-1990s. The total 4-hour trip or per 12-hour trip. Thus, it is important to control sample size was 5,050 drivers (i.e., 954 accident-involved for exposure in order to determine per trip risk. Secondly, time drivers and 1,506 non-accident drivers in 1984; 887 accident of day and long hours both impact fatigue, and it is difficult to drivers, and 1,604 non-accident drivers in 1985). The research separate these impacts. Campbell (2002) reports that more appears to use a larger data set but similar methods to the Lin than 25% of the accidents occurred in the first hour, and two- et al. study described previously. The study explores "whether thirds in the first 4 hours, and that "only about 4 percent of all a more detailed examination of time of day of driving, par- medium and heavy truck drivers involved in a fatal crash ticularly over multiple days, indicates associations with crash reported driving more than 8 hours at the time of the accident." risk." Night and morning driving and irregular schedules with The authors note that this pattern is driven "by exposure, not primarily night and early morning driving, have significantly risk" as the "nature of the exposure distribution will always elevated crash risk of 20 to 70%, 30 to 80%, respectively, keep the number of accidents after many hours driving a small compared with daytime driving. proportion of the total, even with dramatic increases in risk A case-control approach was used in New Zealand to deter- with hours driving." When differences in exposure were con- mine the effect of work schedule variables on crash risk sidered the authors found the following: (Frith 1994). A `case' group of drivers and heavy vehicles involved in crashes (1988 to 1990) were compared with a `con- 1. "The relative risk of fatigue given involvement in a trol' group of drivers and vehicles (1992 to 1993). The crash- fatal accident follows the circadian rhythm." involved drivers were 2.6 times more likely, as compared 2. The relative risk of fatigue given involvement in a fatal with non-crash involved drivers, to have driven 8 or more accident "gradually increases during the first 8 hours, hours since the last compulsory 10-hour off-duty period (as doubles during the ninth hour and is higher by a factor recorded in the log book). However, no other scheduling vari- of 6 by the 12th hour." ables were found to be associated with crash risk. Drivers involved in crashes tended to be younger than control drivers. Lin et al. (1994) formulated an elapsed time-dependent Once trip length is controlled for exposure, three crash logistic regression model to assess the safety of motor carrier studies show an increase in crash risk with hours of driving. operations. The data were obtained from a national less-than Campbell (2002) concludes that the relative risk of fatigue truckload firm that operated coast-to-coast with no sleeper given involvement in a fatal accident "gradually increases berths. The total number of observations used for modeling during the first 8 hours, doubles during the ninth hour and is was 1,924 cases, of which 694 were accidents and 1,230 were higher by a factor of 6 by the 12th hour." Lin et al. shows that non-accidents. The model "estimates the probability of hav- "accident risk increases significantly after the 4 hr, by ing an accident at time interval, t, subject to surviving (i.e., approximately 50 percent or more, until the 7th hr. The 8th not having an accident) until that time." The model was then and 9th hr show a further increase, approximately 80 and 130 tested with data from trips involving and not involving percent higher than the first 4 hr." Frith (1994) shows crash crashes from trucking company operations. Analysis showed involved drivers to be 2.6 times more likely than non-crash that driving time had the strongest direct effect on crash risk. involved drivers to have driven 8 or more hours. Accident risk increased "significantly after the 4 hr, by With respect to hours driving and crash risk, these studies approximately 50 percent or more, until the 7th hr. The 8th are consistent with earlier studies by Jones and Stein (1985) and 9th hr show a further increase, approximately 80 and and Harris (1978). Using a case-control approach to examine 130 percent higher than the first 4 hr." Drivers with more than the relative risk associated with long hours of driving, Jones 10 years of driving experience had the lowest accident risk. and Stein (1987) found that tractor-trailer drivers who drove Daytime driving, particularly around noon, was associated in excess of 8 hours, who violated log book regulations, and with significantly lower risk of an accident and was defined who were aged 30 and younger had an increased risk of crash
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143 involvement. In particular, the relative risk of crash involve- sive shifts. (There were about 20 studies of accident and ment for drivers who reported a driving time in excess of injuries referenced, and only a sub-sample of relevant stud- 8 hours was almost twice (i.e., almost 100% higher) that for ies could be used for each analysis.) There was a highly sig- drivers who had driven fewer hours. Lin et al. 1994 found a nificant main effect of shift, in that risk increased by 18.3% 50% increase in risk after 4 hours of driving. In samples of on afternoon shifts and by 30.4% on night shifts relative to dozing driver and single-vehicle crashes, Harris (1978) found the morning shift. that the changeover to more accidents than expected from There was also a consistent trend in accident risk over four fewer accidents than expected, occurred after about 5 hours successive nights. On average, risk was about 6% higher on of driving. the second night, 17% higher on the third night, and 36% With respect to time of day of driving, Park et al. found that higher on the fourth night. Although the effect was not signif- night and morning driving and irregular schedules with pri- icant, there was also increased risk, though to a lesser degree, marily night and early morning driving, have significantly associated with successive day shifts. Risk was about 2% elevated crash risk of 20 to 70%, 30 to 80%, respectively, higher on the second morning/day, 7% higher on the third compared with daytime driving. Lin et al. found some asso- morning/day, and 17% higher on the fourth morning/day shift ciation with time of day. However, as noted by the authors, than on the first shift. These findings are consistent with the there was no control for exposure, hence the finding that the Jovanis and Kaneko (1990) findings for truck drivers, in that highest accident risk occurred between 4:00 and 6:00 p.m., cumulative shifts at night had a greater impact on crash risk peak hour with respect to traffic volume. than cumulative shifts worked during the day. Time of day was controlled for exposure in the earlier Folkard and Lombardi found that risk also increased with study reported by Harris (1978). In a sample of single-vehicle the length of the shift. Relative to 8-hour shifts, 10-hour shifts crashes, the circadian effect was evident as 46% of the acci- were associated with a 13.0% increase, and 12-hour shifts dents occurred between midnight and 0800, almost "2.5 times with a 27.5% increase in risk. These findings are also consis- as many as would be expected from the exposure data (19%). tent with findings for CMV drivers, showing increases in In a sample of "dozing driver" crashes, approximately 70% crash risk after work exceeds 4 or 5 hours. occurred between midnight and 0800. In contrast, approxi- mately 25% of the accidents for the multi-vehicle crash sam- ple occurred between midnight and 0800. Sleep Restriction and Performance Time of day of driving has also been shown to impact crash risk of passenger car drivers. When exposure is accounted for, A number of studies have shown that CMV drivers, espe- as it has been in three studies in different countries, of single- cially long-haul drivers suffer from sleep restriction and thus vehicle passenger car crashes, without alcohol involvement, a the impact of sleep restriction on performance is a concern. very strong association with time of day is found, with 13 to Van Dongen et al. (2003) studied effects of chronic and total 25 times the risk of a crash per mile driven in the 2:00 to sleep restriction on cognitive performance and found that 4:00 a.m. period as compared with during typical working "chronic restriction of sleep periods to 4 h or 6 h per night over hours (see Smiley 2002 for a summary). 14 consecutive days resulted in significant cumulative, dose- The effect of cumulative shifts in a sequence on crash risk dependent deficits in cognitive performance on all tasks." has received little attention. One study by Jovanis and Kaneko Lapses in behavioral alertness and reductions in working mem- (1990) examines this through an analysis of carriersupplied ory performance in the 4 h condition reached levels equiv- accident and nonaccident data for a 6-month period in 1984. alent to those observed after 2 nights without sleep. After The data were obtained from a "pony express" type opera- 14 days of sleep restriction, cognitive throughput performance tion, which operates coast to coast with no sleeper berths. was equivalent to that observed after 1 night without any Cluster analysis was used to identify nine distinct patterns of sleep. The authors note that the study results do not support driving hours over a 7-day period. The driving patterns of the notion of "core" and "optional" sleep." drivers who had an accident on the 8th day were compared Belenky et al. (2003) viewed the core versus optional sleep with drivers who had no accident on the 8th day. An issue slightly differently. They found that 7 days of sleep increased crash risk was found for night but not day drivers restriction degraded psychomotor vigilance performance in after 3 to 4 days of driving. a sleep-dose dependent manner. With mild to moderate sleep Industrial shift schedules are typically more rigid than CMV restriction (7 and 5 hours time in bed), performance initially driver schedules and studies using these are helpful in illu- declined and, after a few days, appeared to stabilize at a minating risks associated with various shift features. In a lower-than-baseline level for the remainder of the sleep restric- meta-analysis, Folkard and Lombardi (2004) examined stud- tion period. In contrast, with severe sleep restriction (3 hours ies of injuries and accidents which occurred in industrial set- time in bed) performance declined continuously across the tings and related them to the time of day; to the point within sleep restriction period, with no apparent stabilization of per- the shift system that they occurred; and to the shift features formance. Thus the 5 to 7 hours time in bed might be consid- such as type of shift, length of shift, and number of succes- ered "core" sleep, in that performance stabilized, but was not
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144 at a level to maintain maximum performance. Three days of Only 4% of the accidents were fatigue related according to recovery sleep did not restore performance to baseline levels first criterion. However, this figure rose to 17% if all criteria for subjects with mild to moderate sleep restriction (5 or 7 were applied. While the majority of accidents occurred during hours time in bed). the first 3 working hours, the authors note that length of trip Lenne et al. (1997) looked at the effects of sleep depriva- was not controlled for exposure, and that the sample was small. tion, time of day, and driving experience on driving simula- "The statistically significant analysis determined that the tor performance. Lane position and speed variability were most important measures in predicting a fatigue-related acci- significantly higher following sleep deprivation. Circadian dent in this sample are the duration of the last sleep period, effects were shown in that performance steadily improved the total hours of sleep obtained during the 24 hours prior to across the day between 0800 and 2000, after both normal the accident, and split sleep patterns." sleep and sleep deprivation. Inexperienced drivers had higher Rail accidents, like truck accidents associated with fatigue, reaction times than experienced drivers in both sleep-deprived are characterized by non-performance and are related to time and non-sleep deprived conditions." of day and restricted sleep. In less than one-quarter of the The results of these studies suggest that there are cumula- crashes did the engineer admit fatigue, suggesting only a tive performance consequences to limiting sleep to even as small number of police reports indicate fatigue as the cause. much as 6 hours per day, and that the effects of sleep depri- vation may be more for inexperienced drivers. Alcohol vs. Prolonged Wakefulness Sleep Restriction, Time of Day, and Crash Risk Arnedt et al. (2001) compared effects of alcohol with those of prolonged wakefulness on a simulated driving task. They NTSB (1995) focused on the sleep patterns of the 96 hours found that performance following 19 and 22 hours of wake- preceding 107 single-vehicle heavy truck crashes in which fulness (measured at 0230 and 0500) was equivalent to 0.05 the driver survived. Fifty-eight percent of the crashes were and 0.08% BAC, respectively (measured during the day). fatigue-related. Fatigue was considered a probable cause of Roehrs et al. (2003) looked at the effects of sleep loss the crash if the driver was estimated to have been on duty for (0, 2, 4, and 8 hours of sleep loss) as compared with those of more than 15 consecutive hours (the current legal limit), and ethanol ingestion in 32 adults (ages 21 to 35). "The study was if the driver's performance involved non-professional, irra- conducted in a mixed design with a between-subject factor, tional actions such as failure to brake or make appropriate ethanol or sleep loss, and a within-subject factor, dose of steering maneuvers. A statistical analysis determined that the either ethanol or sleep loss." The authors found that "sleep most important measures predicting a fatigue-related crash in loss was more potent than ethanol in its sedative effects but this sample were the "duration of the last sleep period, the comparable in effects on psychomotor performance. Ethanol total hours of sleep obtained during the 24 hours prior to the produced greater memory deficits, and subjects were less crash and the split-sleep patterns." aware of their overall performance impairment." Studies described above indicate the negative effect of These two studies provide an appreciation of the impact of restricted sleep on performance. The NTSB study provides evi- sleep loss in terms of the effects of alcohol, the effects of dence that the performance changes resulting from restricted which on crash rates are well known. These studies suggest sleep can lead to crashes. that CMV drivers working long hours after restricted sleep may be as impaired with respect to driving performance as drivers at the legal limit of alcohol. Fatigue, Sleep Restriction, and Crash Risk Kecklund et al. (1999) examined 79 rail crashes, finding Fatigue, Drugs, and Crash Risk that approximately 17% were potentially related to fatigue or sleepiness. Indicators of suspected fatigue were considered to National Transportation Safety Board (NTSB) (1990) found be present when one of the following three criteria appeared "Thirty-three percent of the fatally injured drivers in 182 acci- in combination with the fourth criterion: dents tested positive for alcohol and other drugs of abuse." In approximately 8 of the 168 cases, urine samples were used to · "The driver admitted or the investigator observed fatigue. detect drugs of abuse. In the remainder of the 168 cases, · Time of the accident (between 3:00 a.m. and 6:00 a.m.). blood samples were used at NTSB's sensitivity thresholds, · Lack of sleep (less than 5 hours sleep) or a shift being which have substantially lower cutoff concentrations than the preceded by a brief period of off-duty time (less than DOT drug testing regulations, making it more likely that pos- 11 hours). itive test results would be found. A concern is whether the lev- · Accidents or incidents characterized by missed signals, els found indicate behavioral impairment due to the drug, or lack of attention or loss of memory. It is known that this merely its presence. This is because presence can be detected type of event is frequently triggered by fatigue. " in blood many hours after consumption, and in urine, days after
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145 consumption, in many cases long after effects on behavior ing a quantitative estimate, most expected 2 to 4 hours. Driv- can be detected. Alcohol/drugs positive results were more ers were interviewed and approximately 20% reported penal- likely to be present on or after the weekend, and were no more ties from their motor carriers for late deliveries. likely to be found in fatigued drivers than in drivers not so At the conference, Truck Safety: Perceptions and Reality, designated. the attendees concluded that current HOS regulations in The authors found that there was a strong association Canada and the United States are too narrowly focused to between violation of the federal HOS regulations and drug reduce the incidence of driver fatigue in truck accidents. There use. In addition, there was a significant relationship between is a need to establish a comprehensive set of standards that drug positive test results and a shipment deadline for the load reflect all types of driver fatigue for different driving situa- being carried. However, some of the drugs considered in this tions. The group also felt that low driver wages and lack of study are stimulants, which have been demonstrated to empowerment compelled drivers to drive longer hours with- improve performance. The presence of an illegal drug cannot out necessary rest ( Saccomanno et al. 1995). be considered as "impairing" unless there is evidence in the The above documents consider broader system issues ver- performance testing literature that the drug in the quantity sus individual trucker decisions. The Braver et al. study is found actually does impair performance. limited in not defining "tight delivery schedules." A possi- ble indicator of this is the dispatcher's estimate of time required for trucker's other duties of 2 to 4 hours. It would Impact of System Issues on CMV be interesting to compare dispatcher, driver, and fatigue Driver Fatigue expert opinions on what constitutes an appropriate delivery schedule. Virtually all studies of fatigue focus on the driver; few stud- ies have looked at fatigue from a system perspective. One such study is by Braver et al. (1999) who looked at the role of ship- Additional References per demands. Dispatchers were interviewed and reported that shippers rarely requested tight delivery schedules. However, Dinges, D.F., Pack, F., Williams, K., Gillen, K.A., Powell, there is a possibility that dispatchers may have responded to J.W., Ott, G.E., Aptowicz, C., and Pack, A.I. (1997) Cumu- questions about tight delivery schedules according to typical lative sleepiness, mood disturbance, and psychomotor vig- driver work schedules rather than HOS regulations. In partic- ilance performance decrements during a week of sleep ular, the authors note, that the study "did not attempt to quan- restricted to 45 hours per night. Sleep, 20(4): 2677. tify how a dispatcher defined `more than enough time,' `just Smiley, A. Chapter 6: Fatigue and driving. In Human Fac- enough time,' or `not enough time' to pickup and deliver." tors and Traffic Safety, Paul Olson and Robert Dewar The majority of dispatchers said that time allotted per ship- (eds.), Lawyers & Judges Publishing Company, Tucson, ment for non-driving duties was up to the driver. Of those giv- Arizona. 2002.