Driving requires possessing cognitive, motor and visual skills and drivers need to have adequate motor strength, coordination and speed. More importantly, cognitive skills including concentration, attention, adequate visual perceptual skills, insight and memory must be present. The normal ageing process leads to declines in these motor and cognitive skills, and when combined with a brain pathology, it may significantly impair the person's driving performance, especially when unexpected incidents occur. The objective of this paper is to identify the critical driving performance measures in which drivers with cognitive impairments significantly deviate from the general population, through a driving simulator experiment. The brain pathologies considered concern Alzheimer's disease (AD), Parkinson's disease (PD) and Mild Cognitive Impairment (MCI). More analytically, a full neurological and neuropsychological assessment was carried out at the “ATTIKON” General Hospital in Athens, by neurologists and neuropsychologists of the UoA. Then, participants drove at the driving simulator of the NTUA. The driving tasks included driving in urban and rural road environment, while various unexpected incidents were scheduled to occur during the drives. The driving performance of 109 drivers with cognitive impairments (MCI, AD or PD) was compared to the driving performance of 31 healthy drivers of similar demographics. For each driver, the following driving performance measures were calculated and examined: speed, speed variability, lateral position, lateral position variability, headway, headway variability, and reaction time. All these parameters were compared to the range of “typical” values of the respective distribution of healthy drivers, and significant deviations from the “typical” distribution were identified. Results indicated that group of patients had various difficulties in driving performance compared with the control drivers. More specifically, more than 50% of the patients had extremely low mean speeds, and they often had lower speed variability (in 40% of the cases) than controls. Regarding the lateral position, the patients had difficulty in positioning the vehicle in the lane, and more than 1 out of 5 patients had very large variability in their lateral position. Also, 44% of the drivers with a brain pathology kept very large mean headways from the vehicle ahead. Finally, 50% of patients had very slow reaction times in unexpected incidents; in rural area 70% of the patients had reaction times larger than 2 seconds.@en

Objectives: To examine the driving variables that predict accident probability in mild dementia due to Alzheimer's disease (AD), mild cognitive impairment (MCI) and healthy older control drivers in simulated driving. To compare the three groups in mean performance and in frequency of scores exceeding 1.5 SD from the mean. Methods/Design: Participants were 37 drivers with MCI, 16 drivers with AD, and 21 control drivers over the age of 52. Driving measures were derived from four rural driving conditions: moderate traffic without and with distraction and high traffic without and with distraction. The measures were z-transformed based on the performance of 90 control drivers of different ages. Two unexpected incidents occurred per condition, requiring the sudden breaking to avoid an accident. Results: Drivers with AD showed significantly lower average speed, speed variability, greater headway distance, headway variability and average reaction time (RT) than control drivers. Drivers with MCI showed significantly lower average speed, greater headway distance and average RT than control drivers in the two conditions of distraction. No differences were found in accident probability. Drivers with AD had more deviant scores than both control drivers and drivers with MCI in most comparisons. Predictors of accident probability were average RT, speed variability and lateral position variability but MCI and AD status were not significant predictors in any of the regression models. Conclusions: Despite significant differences in performance, drivers with MCI and AD did not differ in accident probability from control drivers. An individualized approach of examining individual driving performance is recommended.@en

Intraindividual variability is a fundamental behavioural characteristic of aging but has been examined to a very limited extent in driving. This study investigated intraindividual variability in driving simulator measures in healthy drivers of different ages using the coefficient of variation (COV) as a variability measure. Participants were healthy volunteers who were regular drivers, who were divided into a “young” group, a “middle-aged” group, and an “old” group. They drove in two environments (rural, 72 drivers; urban, 60 drivers), under conditions of moderate and high traffic load, without and with distraction (conversation). Significant differences in COV were observed in the rural condition for headway distance and lateral position as a function of traffic load, with high traffic (without and with distraction) resulting in increased COV of headway and decreased COV of lateral position. Significant differences in COV were observed in the urban condition for headway distance only, with high traffic (without and with distraction) resulting in increased COV of headway. No age effects were found for any of the driving conditions. The results indicate that traffic load affected headway distance and lateral position in opposite directions in all three age groups: high traffic resulted in increased variability of headway in both rural and urban conditions but in decreased variability of lateral position in the rural conditions compared to moderate traffic irrespective of distraction. The study indicates that driving conditions affect the intraindividual variability of driving measures in selective ways, which may be linked to the extent of automatization of the driving variables and to adaptive changes to traffic condition challenges.@en