The impact of cognitive functioning on driving performance of older persons in comparison to younger age groups: A systematic review

Older drivers are at a severely higher risk for motor vehicle crash involvement. Due to the global aging of the population, this increased crash risk has a significant impact on society, as well as on an older individual’s quality of life. For this reason, there is a need for understanding how normal age-related changes in cognition and underlying brain dynamics impact driving performance to identify the functional and neurophysiological biomarkers that could be used to design strategies to preserve or improve safe driving behavior in older persons. This review provides an overview of the literature on age-related changes in cognitive functioning and brain dynamics that impact driving simulator performance of healthy persons. A systematic literature search spanning the last ten years was conducted, resulting in 22 eligible studies. Results indicated that various aspects of cognition, most importantly executive function, complex attention, and dual tasking, were associated with driving performance, irrespective of age. However, there was a distinct age-related decline in cognitive and driving performance. Older persons had a more variable, less consistent driving simulator performance, such as more variable speed adaptation or less consistent lane keeping behavior. Only a limited number of studies evaluated the underlying brain dynamics in driving performance. Therefore, future studies should focus on implementing neuroimaging techniques to further unravel the neural correlates of driving performance.     

Rewards decrease risky decisions for adolescent drivers: Implications for crash prevention

Motor vehicle crashes (MVCs) are a major contributor to adolescent mortality. Adolescent drivers are more likely to make risky decisions in the presence of peers. However, rewards have also been shown to improve decision making in adolescence. Our goal was to determine if peer observation and reward effects on decision-making were dependent upon adolescent driving styles.Twenty-four healthy adolescents played a driving game in a 2 (no peer; peer) × 2 (no rewards; rewards) within-subjects experiment. Driving styles were measured by self-report.Rewards favoring safe choices reduced risky decision making, but this effect was especially robust for adolescents with driving styles that increase risk of MVCs (i.e., dangerous, fast, angry, or distracted styles). Findings suggest that rewards for safe driving can be an effective mechanism for reducing MVCs, especially for the most at-risk drivers, if they can be made appetizing to adolescents.     

Distressed in the queue? Psychophysiological and behavioral evidence for two alternative car-following techniques

BackgroundNature offers numerous examples of animal species exhibiting harmonious collective movement. Unfortunately, the motorized Homo sapiens sapiens is not included and pays a price for it. Too often, drivers who simply follow other drivers are caught in the worst road threat after a crash: congestions. In the past, the solution to this problem has gone hand in hand with infrastructure investment. However, approaches such as the Nagoya Paradigm propose now to see congestion as the consequence of multiple interacting particles whose disturbances are transmitted in a waveform. This view clashes with a longlasting assumption ordering traffic flows, the rational driver postulate (i.e., drivers’ alleged propensity to maintain a safe distance). Rather than a mere coincidence, the worldwide adoption of the safety-distance tenet and the worldwide presence of congestion emerge now as cause and effect. Nevertheless, nothing in the drivers’ endowment impedes the adoption of other car-following (CF) strategies. The present study questions the a priori of safety-distance, comparing two elementary CF strategies, Driving to keep Distance (DD), that still prevails worldwide, and Driving to keep Inertia (DI), a complementary CF technique that offsets traffic waves disturbances, ensuring uninterrupted traffic flows. By asking drivers to drive DD and DI, we aim to characterize both CF strategies, comparing their effects on the individual driver (how he drives, how he feels, what he pays attention to) and also on the road space occupied by a platoon of DD robot-followers.MethodsThirty drivers (50% women) were invited to adopt DD/DI in a driving simulator following a swinging leader. The design was a repeated measures model controlling for order. The CF technique, DD or DI, was the within-subject factor. Order (DD-DI / DI-DD) was the between-subjects factor. There were four blocks of dependent measures: individual driving performance (accelerations, decelerations, crashes, distance to lead vehicle, speed and fuel consumption), emotional dimensions (measures of skin conductance and self-reports of affective states concerning valence, arousal, and dominance), and visual behavior (fixations count and average duration, dwell times, and revisits) concerning three regions of the driving scene (the Top Rear Car –TRC- or the Bottom Rear Car –BRC- of the leading vehicle and the surrounding White Space Area -WSA). The final block concerned the road space occupied by a platoon of 8 virtual DD followers.ResultsDrivers easily understood and applied DD/DI as required, switching back and forth between the two. Average speeds for DD/DI were similar, but DD drivers exhibited a greater number of accelerations, decelerations, speed variability, and crashes. Conversely, DI required greater CF distance, that was dynamically adjusted, and spent less fuel. Valence was similar, but DI drivers felt less aroused and more dominant. When driving DD visual scan was centered on the leader’s BRC, whereas DI elicited more attention to WSA (i.e., adopting wider vision angles). In spite of DI requiring more CF distance, the resulting road space occupied between the leader and the 8th DD robot was greater when driving DD.     

Effects of route familiarity on drivers’ psychological conditions: Based on driving behaviour and driving environment

Route familiarity affects a driver’s mental state and indirectly affects traffic safety; however, this important factor is easily overlooked. Previous research on route familiarity has only analysed psychological states in terms of unfamiliarity and familiarity, the influence of driving behaviour and driving environment on psychological states has been ignored. As a result, the mechanisms through which the route familiarity influence driver psychological states, and vice versa, are unclear. This study proposes a quantitative framework for studying driver psychological condition and route familiarity using experimental data from a real driving task and driving environment data. The experimental data included 1022 observations obtained by 23 participants over 7 consecutive trials on 6 unfamiliar experimental routes with large differences in scenarios; environmental data were automatically extracted after segmenting a driving video through the Dilated Residual NetWorks model. The results reveal that (1) the relationship between the driver’s psychological condition and route familiarity is not monotonic and is different for straight and turning sections; (2) the driver’s psychological condition is influenced by the visual scene elements and the type of road section, and the results of the multivariate regression analysis quantified the variability of the influence; and (3) unlike a majority of findings on distracted driving, our study suggest that the driver’s attention to the external environment in the urban distracted driving state will gradually approach a ‘distraction threshold’, and the time and size of the ‘distraction threshold’ are influenced by the driver. This study can further the development of urban traffic safety research and help urban designers plan and improve urban landscapes to ensure drivers maintain stable mental states when they drive.     

Psychometric properties of the Driving Behaviour Scale (DBS) among polish drivers

Anxiety can negatively affect an individual’s psychological wellbeing and lead to mild-to-moderate functional impairment in various areas of their lives. Despite this, the relationship between anxiety and driving performance has received very little empirical attention. The Driving Behaviour Scale (Clapp, Olsen, Beck, et al., 2011, Clapp, Olsen, Danoff-Burg, et al., 2011) was developed as a measure of anxious driving behaviours to support research in this area. The current study details adaptation and validation of the Driving Behaviour Scale (DBS; Clapp, Olsen, Beck, et al., 2011, Clapp, Olsen, Danoff-Burg, et al., 2011) in 310 university students in Poland. The overall internal consistency for the DBS was 0.76, while the two subscales demonstrated acceptable internal consistency (safety/cautious = 0.75 and hostile/aggressive behaviours = 0.85). The reliability estimates for performance deficit returned a lower coefficient of 0.65. Factor analysis produced a three-factor solution that supported the original structure of the DBS. The DBS may be utilised as a measure of driving anxiety in samples drawn from the general population.     

Learning from the law to address uncertainty in the precautionary principle

Environmentalists have advocated the Precautionary Principle (PP) to help guide public and private decisions about the environment. By contrast, industry and its spokesmen have opposed this. There is not one principle, but many that have been recommended for this purpose. Despite the attractiveness of a core idea in all versions of the principle—that decision-makers should take some precautionary steps to ensure that threats of serious and irreversible damage to the environment and public health do not materialize into harm—even one of the most widely endorsed principles needs considerable specification and refinement before it can be used. Moreover, the PP is an approach or guide to utilizing scientific evidence in social or legal decision-making contexts. In this it does not differ in kind from other approaches to using factual information such as in the law. The law provides some models for different strategies to guide decision-making under uncertainty when factual issues cannot be resolved with certainty. These in turn can help guide the formulation of different versions of PP and help clarify some presuppositions of the principle. Once some plausible versions of PP are articulated, I suggest some applications to existing environmental problems.