Fatigue, due to sleep loss, is linked to an increased risk of human error-related incidents¹, and can be attributed to 20-30% of all fatal road crashes in Australia². These accidents can occur due to the driver falling asleep, or an impairment in their driving ability due to deteriorations in cognition or vigilance³, ⁴. Fatigue detection technologies (FDT) have been described as an effective way to manage fatigue behind the wheel. They can continuously monitor drivers for signs of sleepiness, alerting them when dangerous levels are detected⁵. However, with the FDT industry moving away from camera-based devices to wearables⁶, an important indicator of fatigue is being neglected, distraction.
Sleep loss has been shown to increase susceptibility to distraction, with lab studies finding even without the presence of peripheral distractors, sleep-deprived participants were more likely to divert their attention away from a monotonous task (i.e. driving) than when they were well-rested⁷. This is important as distracted drivers are more likely to be involved in collisions, failing to stop at stop signs or red lights and deviating out of their lane⁸, ⁹. Additionally, as sleepiness can alter a driver’s gaze allocation, making it more unpredictable and dispersed beyond essential driving tasks, this indicator can serve as an early warning sign of sleepiness and has the potential to directly reduce sleepiness-related crashes¹⁰.
In practice, heavy vehicle operators utilising camera-based technologies reported the occurrence of distraction events was 4 times more likely than sleepiness events, further stating the safety benefits they observed from their devices were largely attributed to distraction management¹¹. Distraction detection is especially beneficial for older drivers, due to the changes in healthy sleep we see with ageing.
As a direct consequence of ageing, older adults exhibit a reduced ability to initiate and maintain sleep, shorter total sleep duration, reduced need to sleep and increased awakenings overnight¹², ¹³. However, laboratory studies have found their reaction time performance remains relatively stable following sleep loss, especially when compared to younger adults¹⁴, ¹⁵. Older adults additionally report lower subjective sleepiness (a good indicator of actual sleepiness¹⁶) and record fewer lapses in attention following sleep loss¹⁷.
While this highlights how older adults are significantly less vulnerable to sleep loss, they still show driving impairment¹⁸, likely through an increased likelihood of getting distracted. As healthy ageing makes falling asleep less likely, it can make distraction more likely¹⁹, ²⁰. In a laboratory-based fMRI study, researchers found a decrease in engagement of the brain’s frontoparietal attention network due to ageing was directly linked to an upsurge in distractibility²¹.
These findings are particularly relevant given that 59% of heavy vehicle operators are 45 or older²², and may soon be at risk of an increased vulnerability to distraction, through no fault of their own. Drowsy driving risk within this group is especially amplified as a direct consequence of 24-hour operations. The extended duration shifts and nighttime driving practices common across the industry are directly linked to a 2-5 times increase in crash risk²³, with drivers who consistently report poor sleep being 7 times more likely to crash on the road²⁴.
This emphasises the importance of considering factors beyond just sleepiness when assessing fatigue detection technologies. Especially given the unique challenges faced by older adults such as their increased susceptibility to display distraction instead of sleepiness behind the wheel when driving impaired.