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Methods: A sample of 351 drivers aged 20 to 80 was assessed for their reaction times while driving between road cones. The drivers were exposed to 2 conditions varying according to task complexity. In single task conditions, the drivers performed a full stopping maneuver at a given signal; in dual task conditions, the drivers were distracted before the signal for stopping maneuver was triggered. Reaction times were compared across conditions and age groups.
Results: The results showed that both reaction times and variability of driving performance increased progressively between the ages of 20 and 80. The increase in both reaction times and variability was greater in the complex task condition. The high-performing quarter of elderly drivers performed equally well or better than younger drivers did.
Conclusions: The data clearly supported the claim that driving performance changes steadily across age groups: both mean reaction time and interindividual variability progressively increase with age. In addition, a significant group of older drivers was identified who did not show the expected age-related decrease in performance. The findings have important implications, suggesting that in relation to driving, aging is a progressive phenomenon and may lead to variety of driving performance; age-related studies of driving performance should put more emphasis on investigating changes across the whole driver age range rather than only comparing younger and older drivers. 相似文献
Methods: Twelve healthy professional drivers (45.58 ± 10.93 years) completed 2 randomized sessions: After a normal night of sleep and after 24 h of total sleep deprivation. Slow eye closure (PERCLOS) was measured while drivers performed a simulated driving task.
Results: Following sleep deprivation, drivers displayed significantly more eyelid closure (P < .05), greater variation in lane position (P < .01) and more attentional lapses (P < .05) compared to after normal sleep. PERCLOS was moderately associated with variability in both vigilance performance (r = 0.68, P < .05) and variation in lane position on the driving task (r = 0.61, P < .05).
Conclusions: Automated ocular measurement appears to be an effective means of detecting impairment due to sleep loss in the laboratory. 相似文献