This study involved over-the-road testing of four fatigue management technologies (FMTs) in trucking operations in Canada and the United States. Technologies bundled into a single intervention came from four fatigue management domains: one providing objective information on driver sleep need, one providing objective information on driver drowsiness, one providing objective information on lane tracking performance, and one reducing the work involved in controlling vehicle stability while driving. The objective was to determine driver reactions to such technologies and whether FMT feedback would improve alertness, especially during night driving, or increase sleep time on workdays or nonworkdays. A within-subjects crossover design was used to compare the effects of FMT feedback to no feedback. Each driver underwent the conditions in the same order: 2 weeks of no feedback (control) followed by 2 weeks of FMT feedback (intervention). Data from the devices and other driving performance variables were recorded every second of truck operation for 28 days for each driver, with a resulting 8.7 million data records among the 38 drivers. Support was found for FMT effects. During night driving, FMT feedback significantly reduced driver drowsiness (p = 0.004) and lane tracking variability (p = 0.007). However, there was evidence from probed psychomotor vigilance task testing that these improvements may have had cost because of the effort (in attention and compensatory behaviors) required to respond to information from the devices. In general, participants agreed that commercial drivers would benefit from FMT and were more positive about those involving vehicle monitoring than those involving driver monitoring.

This study involved over-the-road testing of a set of four fatigue management technologies (FMT) in trucking operations in Canada and the United States. Technologies bundled into a single intervention came from four domains of fatigue management: 1) one that provided objective information on driver sleep need; 2) one that provided objective information on driver drowsiness; 3) one that provided objective information on lane tracking performance; and 4) one that reduced the work involved in controlling vehicle stability while driving. The objective was to determine how drivers reacted to such technologies, and whether FMT FEEDBACK would improve their alertness, especially during night driving, and/or increase their sleep time on workdays and/or non-workdays. A within-subjects cross-over design was used to compare the effects of FMT FEEDBACK to NO-FEEDBACK. Each driver underwent the two conditions in the same order: 2-weeks of NO FEEDBACK (control) followed by 2-weeks of FMT FEEDBACK (intervention). Data from the FMT devices and other driving performance variables were recorder every second the trucks were operating for the 28 days each driver was in the study, resulting in 8.7 million data records among the 38 drivers in the combined study phases. Support was found for FMT effects. During night driving, FMT FEEDBACK significantly reduced drivers' drowsiness (p = 0.004) and lane tracking variability (p = 0.007). However, there was evidence from probed PVT testing that these improvements may have had "cost" due to the effort (in attention and compensatory behaviors) required to respond to the information from the devices. In general, participants agreed that commercial drivers would benefit from FMT, but they were more positive about technologies that involved vehicle monitoring more so than driver monitoring.

Critical information on the effects that truck parking shortages have on crucial stakeholders, truck drivers in particular, has historically been obtained through survey methods. However, survey methodologies rely heavily on generalizations, respondents’ memory, the recency effect in memory recall, or experiences that evoked strong feelings. To investigate detailed truck parking shortage impacts using a method less reliant on historical recollections, the researchers developed and implemented a 14-day truck parking travel diary study. A total of 148 U.S. drivers participated, providing detailed data for 2,035 days of parking activity and 4,763 unique stops. The analysis focused on truck parking topics that have a nexus to previous survey findings that relate to drivers, state departments of transportation and enforcement activities, and other stakeholders, to facilitate the comparison of truck parking survey data with the diary data. Generally, the truck parking diary findings corroborated survey results. Almost 90% of drivers parked in an unauthorized location at least once a week – supporting survey findings that a majority of drivers find parking is difficult at least once a week. Data on unauthorized parking demonstrated that time-of-day can affect the ease of finding available parking, with peak difficulty occurring during evening hours. Drivers primarily choose parking locations for the mandated 10-h hours-of-service breaks based on practical needs – proximity to route, restroom and shower access, and expected parking availability. The research findings can provide policy, regulatory, and infrastructure guidance to both private industry and public agencies.

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The American Transportation Research Institute and Cummins, Inc. teamed up to investigate the energy and emissions impacts from operating commercial vehicles at weights equal to or greater than existing federal limits. Six vehicle configurations and four gross vehicle weights (GVWs) were modeled over a representative route to estimate fuel usage and corresponding tailpipe emissions. The results provide a comparative estimate of the potential energy and emission impacts from operating different vehicle configurations at various weights. When six configurations were modeled over a representative route with the Cummins, Inc., vehicle mission simulation model and a simplified algorithm to estimate emissions, fuel consumption and emissions generally decreased for each ton-mile of freight transported when compared with two standard configuration vehicles at 80,000 lb GVW. With the exception of one configuration, decreases in fuel consumption and emissions per ton-mile were 4% to 19% at 100,000 lb GVW, 15% to 22% at 120,000 lb GVW, and 27% at 140,000 lb GVW. The lone exception was for the heaviest vehicle, which experienced an increase in fuel consumption and emissions per ton-mile at a GVW of 100,000 lb when compared with the two standard configurations. At this weight, the added payload weight was insufficient to offset the additional fuel consumption demands of the heavier vehicle. Other than this exception, operating higher-productivity vehicles to accommodate higher GVWs can be expected to decrease fuel consumption and emissions on a ton-mile basis when compared with standard configuration vehicles at 80,000 lb GVW.