Although driver distraction can be considered as part of everyday driving it constitutes a basic contributory factor for increased risk for road accidents internationally. Within this content, cell-phone use and conversation with passenger are two critical in-vehicle distraction conditions with respect to driver behavior and safety. The objective of this research is the investigation of the effect of area and traffic conditions on driving performance of drivers while talking on the mobile phone or conversing with the passenger. For this purpose, a large driving simulator experiment is carried out, in which 95 drivers from all different age groups (young, middle aged and older) were asked to drive under different types of distraction (no distraction, conversation with passenger, cell phone use) in rural and urban road environment, in low and high traffic. In the next step, an appropriate modelling methodology has been developed, including first descriptive analysis in order to explore the large database. Then generalized linear models as well as generalized linear mixed models regarding average speed and reaction time were implemented in order to estimate the effect of the examined distraction sources as well as area and traffic characteristics on driving behaviour and road safety. Results indicate that female drivers, especially in rural areas, were found to have the worst reaction times, while being distracted (either conversing with a passenger or talking on the cell phone). This is probably explained by the fact that in urban area, the complex road environment alerts the drivers in order to self-regulate their driving to compensate for any decrease in attention to the driving task. Furthermore, regarding average speed, it is observed that in rural areas drivers reduce the speed while distracted either by talking on the mobile phone (older drivers) or by conversing with the passenger (young and middle aged drivers), especially at high traffic volume while in urban areas suggesting a driver's compensatory behaviour. The next steps of the present research could focus on the investigation of the impact of mobile phone use, not only when the drivers talk on mobile phone using a hand-held device, but also when they use a hands-free device, a Bluetooth, or when they type messages.@en

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

Objectives In-vehicle distraction is considered to be an important cause of road accidents. Drivers with Mild Cognitive Impairment (MCI), because of their attenuated cognitive resources, may be vulnerable to the effects of distraction; however, previous relevant research is lacking. The main objective of the current study was to explore the effect of in-vehicle distraction on the driving performance of MCI patients, by assessing their reaction time at unexpected incidents and accident probability. Methods Thirteen patients with MCI (age: 64.5 ± 7.2) and 12 cognitively intact individuals (age: 60.0 ± 7.7), all active drivers were introduced in the study. The driving simulator experiment included three distraction conditions: (a) undistracted driving, (b) conversing with passenger and (c) conversing through a hand-held mobile phone. Results The mixed ANOVA models revealed a greater effect of distraction on MCI patients. Specifically, the use of mobile phone induced a more pronounced impact on reaction time and accident probability in the group of patients, as compared to healthy controls. On the other hand, in the driving condition “conversing with passenger” the interaction effects regarding reaction time and accident probability were not significant. Notably, the aforementioned findings concerning the MCI patients in the case of the mobile phone were observed despite the effort of the drivers to apply a compensatory strategy by reducing significantly their speed in this driving condition. Conclusion Overall, the current findings indicate, for the first time, that a common driving practice, such as the use of mobile phone, may have a detrimental impact on the driving performance of individuals with MCI.@en

The objective of this paper is to analyze the self-reported driving behaviour of older drivers with and without brain pathologies affecting cognition, in order to explore possible differences in self-perception of driving behaviour, through an extensive questionnaire assessment. The diagnostic categories examined include Alzheimer׳s disease, Parkinson׳s disease, and Mild Cognitive Impairment. The questionnaire was answered by 137 drivers with similar demographic characteristics, out of which 44 were healthy individuals and 93 had a brain pathology. It included questions about their driving routines, possible avoidance of driving, and their emotions and behaviours while driving. The participants were also asked about their opinion about in-vehicle driver distraction and how they deal with it. A comparison of the two groups with Kruskal-Wallis and One-Way ANOVAs, produced several statistically significant results. Patients tended to report that they were more likely to avoid using their vehicle because they were afraid of their driving abilities than healthy drivers. Regarding distraction, patients considered it too dangerous to converse with a passenger and even more so, to use the mobile phone and for that reason they reported avoiding to do so. Patients with brain pathologies reported being quite calm while driving. Overall, drivers with brain pathologies were aware of deterioration in their driving performance, and reported trying to compensate for their driving difficulties either by conservative driving or by driving avoidance.@en

This paper investigates the safety margins of drivers along tangent to curved road sections. A vehicle dynamics model is presented, allowing to assess the vehicle speed variation at impending skid conditions from tangent to curve on the basis of several parameters. This model returns the theoretical curve corresponding to the driver’s maximum efficiency, i.e. the maximum safe speed and acceleration along the tangent to curve section when utilizing the outmost of the available vehicle horse power. On the basis of actual vehicle speed profiles, the model also returns the respective curve for the actual efficiency i.e. the utilized share of vehicle horse power, which reflects the driver’s safety margin. Data from a driving simulator experiment are used to test the proposed methodology and identify the parameters affecting drivers’ efficiency / safety margins. The results suggest that drivers’ safety margins towards the examined curve are considerable, with the majority of the drivers using less than 55% of the available vehicle horse power. Higher initial speed was positively correlated with driving efficiency i.e. lower safety margins. On the contrary, a higher safety margin was associated with earlier deceleration before the curve. Driver characteristics were not found to significantly affect the safety margins, except from age <35 years old who were associated with higher share of vehicle motion used. The proposed method has advantages over existing methods; it allows for a better understanding of driver speeding behaviour and a more objective and insightful calculation of the safety margin through the vehicle dynamics, along the entire road section from tangent to curve, which may assist in improving design and interventions at curves. Keywords: speed variation; safety margin; horizontal curve; driving simulator @en

This paper presents a novel definition of drivers’ safety margins reflected in speed profiles on a tangent to curved road design. These safety margins are based on a vehicle dynamics model, which is implemented to assess the speed variation at impending skid conditions from tangent to curve on the basis of several parameters. This model returns the theoretical speed-distance curve corresponding to the driver’s maximum safe speed and acceleration when utilizing the outmost of the available vehicle horse power. On the basis of actual vehicle speed profiles, the model also returns the respective curve for the actual speed-distance i.e. the utilized share of vehicle horse power, which reflects the driver’s safety margin. Data from a driving simulator experiment are used to test the proposed methodology, explore driver’s speed profiles and the parameters affecting drivers’ safety margins. The results suggest that drivers’ safety margins towards the examined curve are considerable, with the majority of the drivers using less than 55% of the available vehicle horse power. Drivers can be grouped into “aggressive”, “moderate” and “conservative” speeding behaviour, each group exhibiting distinct initial speed, “breakpoint” distance and acceleration / deceleration patterns. Higher initial speed is positively correlated with more aggressive driving i.e. lower safety margins. On the contrary, a higher safety margin was associated with earlier deceleration before the curve. The proposed approach yields a continuous and objective assessment of driver speeding behaviour from tangent to curve and the related safety margins, both for individual drivers, as well as for groups of drivers with similar speeding patterns.@en

The objective of this research was the analysis of the driving performance of drivers with Mild Cognitive Impairment (MCI) or Alzheimer’s disease (AD), in different road and traffic conditions, on the basis of a driving simulator experiment. In this experiment, healthy “control” drivers, patients with MCI, and patients with AD, drove at several scenarios at the simulator, after a thorough neurological and neuropsychological assessment. The scenarios include driving in rural and urban areas in low and high traffic volumes. The driving performance of healthy and impaired drivers was analysed and compared by means of Repeated Measures General Linear Modelling techniques. A sample of 75 participants was analysed, out of which 23 were MCI patients and 14 were AD patients. Various driving performance measures were examined, including longitudinal and lateral control measures. The results suggest that the two examined cerebral diseases do affect driving performance, and there were common driving patterns for both cerebral diseases, as well as particular characteristics of specific pathologies. More specifically, cognitively impaired drivers drive at lower speeds and with larger headway compared to healthy drivers. Moreover, they appear to have difficulties in positioning the vehicle on the lane. The group of patients had difficulties in all road and traffic environments, and especially when traffic volume was high. Most importantly, both cerebral diseases appear to significantly impair reaction times at incidents. The results of this research suggest that compensatory behaviours developed by impaired drivers are not adequate to counterbalance the direct effects of these cerebral diseases on driving skills. They also demonstrate that driving impairments increase as cognitive impairments become more severe (from MCI to AD).@en