Millions of dollars are spent to develop and enforce Hours-of-Service (HOS) rules for commercial truck and bus drivers. Most everyone agrees that HOS rules are necessary, and that repeat violators should be punished. But do the rules really matter? It’s my view that specific HOS rules don’t matter a great deal in terms of overall safety outcomes (i.e., crash rates). And the actual safety effects of rules may be quite different than those predicted by government fatigue studies.
HOS rules contain numerous provisions relating to driver schedules. These include minimum daily off-duty hours, maximum daily driving hours, maximum tour-of-duty (e.g., 14 hours for U.S. truck drivers), weekly maximum work hours, restart (i.e., 34-hour restart) provisions, and required breaks from driving. Governments base their HOS regulations primarily on factors affecting driver fatigue and alertness, yet there are many inherent differences between the profile of factors actually affecting alertness and the profile of HOS rules. Table 1 below presents two lists. The first column shows the physiological and task-related factors that actually affect driver alertness and performance. The second column lists HOS parameters. In some cases, there are clear and direct linkages; e.g., time-on-task and maximum daily driving hours. In other cases, the relationship is indirect. For example, recent sleep is a prime physiological fatigue factor, but HOS rules do not regulate sleep. They only afford the opportunity for sufficient sleep. Some major fatigue causes are not addressed at all, or only partially addressed, by HOS rules. Of all factors, time-of-day probably has the strongest effects on daily alertness changes. That’s because of the physiological rollercoaster called the circadian rhythm. HOS rules can’t change that. There are also large individual differences in fatigue susceptibility, even among healthy people. In the U.S./Canada Driver Fatigue and Alertness Study (Wylie et al., 1996), 54% of all the drowsy episodes were seen in just 14% of the drivers. Other drivers in the study were rarely or never seen to be drowsy. The same study, one of the best every conducted, found that hours-of-driving “was not a strong or consistent predictor of fatigue.” In FMCSA’s $20 Million Large Truck Crash Causation Study (LTCCS), there was no relation between hours-of-work or hours of driving and driver fault in crashes. Truck drivers were just as likely to make mistakes early in their shifts as they were later (Knipling, 2011). Yet HOS rules are built around restrictions to hours of work and driving.
Table 1. Human Alertness/Fatigue Factors and HOS Parameter
In 2011, FMCSA published two big studies reporting associations between hours-of-driving and risk. A fleet crash study at Penn State (Jovanis et al., 2011) found an association between hours-of-driving, especially the 11th hour, and relative crash risk. A naturalistic driving study at the Virginia Tech Transportation Institute (Blanco et al., 2011) reported similar associations for driver “Safety-Critical Events,” such as hard braking near-misses. But, from a scientific perspective, these studies were ridiculously bad. “Driver fatigue” was in the title of the Penn State (“Hours of Service and Driver Fatigue: Driver Characteristics Research”) but there were no measures of driver fatigue in the study! The study correlated hours-of-driving with relative crash rate, but, as everyone should know, correlation does not imply causation. Penn State ignored potential confounding factors, most notably time-of-day. Time-of-day affects alertness through the circadian rhythm, but its biggest effect on safety is through predictable changes in traffic density. In the course of daily trip, fluctuations in traffic density are the strongest factor in driving risk. Penn State has never documented a single crash as being fatigue-related, or even as due to any truck driver error. You can’t draw valid scientific conclusions from a study where there were no controls for confounding factors (especially time-of-day and associated traffic changes) and no proof that any truck driver was ever drowsy or ever even made a mistake.
The Virginia Tech study was even worse, if that’s possible. It had all the same scientific flaws as the Penn State work, but it used instrumented vehicle “Safety-Critical Events,” not real crashes. Only four (4) of the 2,197 SCEs (0.2%) were crashes, and “crash” was defined as “any contact.” Most SCEs are active driver responses, such as hard braking and swerving, but such active responses do not characterize drowsy drivers. A prior study from the same Virginia Tech group found that only one (1) of 915 SCEs involved an asleep-at-the-wheel truck driver. Further, research showed that SCEs were most likely when drivers were highly alert, not when they were highly drowsy. Yet, in essence, the study assumed that all SCEs were fatigue-related. In fact, with few exceptions, SCEs are not fatigue-related and not even crash-related.
The schematic below shows some of the many factors affecting CMV crash risk, and how HOS parameters like hours-of-driving are not likely to have much direct effect on CMV crashes. There are just too many other factors, most of which are stronger than driver fatigue in affecting crash outcomes. And, as we saw in the comparison table above, even driver alertness and fatigue variations cannot be attributed primarily to HOS rules.
Figure 1. The link between HOS rules and CMV crashes is tenuous because of the many other factors affecting crash risk (Source: Knipling, 2015)
A particular HOS rule change might reduce driver fatigue, but still cause other problems. That’s the case with the U.S. Restart rule recently rescinded by Congress. Requiring two 1:00am-to-5:00am periods within the 34-hours probably did reduce driver fatigue, but it put more truck drivers out on the roads during morning rush hours. As a risk factor, heavy traffic “trumps” driver fatigue, probably making the overall safety effect of that rule negative, not positive.
Therefore, I have concluded that stricter HOS rules probably have little beneficial effect on “bottomline” safety. Does this mean that you and your drivers should just ignore HOS rules? Probably not a good business plan! And there is a larger reality about rule compliance. Taken together, the various government safety rules and regulations do affect crash risk. People who chronically violate one rule usually violate others. That’s why so many different types of rule violations are associated statistically with crash risk. For a given rule, there may be a causal relation to safety, a correlation, or some combination of the two. Whatever the mechanism, rule violations usually signify elevated risk.
Violating HOS rules is bad, but simply obeying HOS rules won’t do much to reduce crashes or even fatigue. To really reduce fatigue, consider adopting a proactive Fatigue Management Program (FMP) approach, such as that provided by the North American Fatigue Management Program. FMPs take a comprehensive approach to mitigating the actual fatigue risks to driver safety and health. FMP elements include a corporate culture that fosters driver safety and health, fatigue education for managers and drivers, screenings and treatments for Obstructive Sleep Apnea and other medical conditions, and data-driven company risk management practices. As with other areas of enlightened safety management, fatigue management stands apart from simple rule compliance.
Blanco, M., Hanowski, R. J., Olson, R.L., Morgan, J. F., Soccolich, S. A., Wu, S-C, and Guo, F. The Impact of Driving, Non-Driving Work, and Rest Breaks on Driving Performance in Commercial Motor Vehicle Operations. Report No. FMCSA-RRR-11-017, May 2011.
Jovanis, P. P. Wu, K-F., Chen, C. Hours of Service and Driver Fatigue: Driver Characteristics Research, Report No. FMCSA-RRR-11-018, Contract #19079-425868, Task Order #6, May 2011.
Knipling, R.R. The Good, the Bad, and the Ugly: Three Large Truck Crash Categories and What They Tell Us About Driver Fatigue. Paper placed on the FMCSA Hours-of-Service (HOS) rulemaking docket (FMCSA-2004-19608), May 2011.
Knipling, R.R. Critical Review of Driver Fatigue & HOS-Related Research Methodologies. Commissioned paper for National Academy of Sciences Commercial Driver Fatigue Panel, 2015.
Wylie, C.D., Shultz, T., Miller, J.C., Mitler, M.M., & Mackie, R.R., Commercial Motor Vehicle Driver Fatigue and Alertness Study, Federal Highway Administration, U.S. Department of Transportation, Washington, DC, 1996.