The effects of secondary tasks that involve listening and speaking on young adult drivers with traits associated with autism spectrum disorders: A pilot study with driving simulation

A driver’s license is key to independence for many young adults, including those with autism spectrum disorders (ASDs). However, individuals with ASDs may face special challenges when learning to drive. If effective driver training is to be devised for this demographic, it is important to determine the nature of these challenges. Driving inherently requires multitasking (e.g. steering, speed maintenance, navigation, hazard detection) and drivers are routinely obligated to combine driving with the demands of listening and responding to others, as occurs during driving lessons. Given that individuals who display traits associated with ASDs may have special difficulties with secondary tasks and especially those that involve socialization, we examined the effects of secondary tasks that involve listening and responding to questions while driving. We compared performance when simply driving (the control condition), driving while listening (the audiobook condition), and driving while listening and speaking (the prompt: answer condition). The autism spectrum quotient (AQ:Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001), a commonly used self-report questionnaire intended to measure traits associated with ASDs in research, was used to identify young drivers with more and fewer traits related to ASDs in a community sample, (None had a clinical diagnosis of ASD.) Consistent with studies of drivers clinically diagnosed with ASDs, we found that high AQ scorers reported greater mental and physical demand, effort, and frustration when driving, and showed more moment-to-moment variability in lane position and hazard reaction compared to low AQ scorers as measured in a driving simulator. Differences between the low and high scorers were typically largest when secondary tasks were imposed, but the predicted interaction between drive condition and AQ group only emerged in terms of steering variability.     

The effect of the emotional state on driving performance in a simulated car-following task

Emotion is an important factor that influences driving behavior, but the mechanism is unclear. This research explored the effect of the emotional state on simulated driving behavior. Thirty-five licensed drivers participated in this study and completed a car-following task. The angry, happy and neutral states were manipulated during the task. The participants’ driving performance and risk perception were recorded under each emotional state. Trait anger and driving experience were also measured to explore the possible mediating effect. The results showed that the drivers in an angry or happy emotional state tended to maintain less time to collision and take a longer time to brake while following a lead vehicle than the drivers under the neutral condition, suggesting that drivers in emotional states are more dangerous those in neutral states. Moreover, the happy state rendered the drivers more dangerous, which manifested as a lower perceived accident risk than that among the drivers in the angry and neutral states. More specifically, experienced drivers in happy states performed worse with respect to vehicle lateral position control. Recommendations and implications for safety education and further research are discussed.     

Identification of driving simulator sessions of depressed drivers: A comparison between aggregated and time-series classification

Depression has been found to significantly increase the probability of risky driving and involvement in traffic collisions. The majority of studies correlating depressive symptoms with driving, pursue to predict the differences in driving behavior if the driver has already been diagnosed. Little evidence can be found, however, on how mental and psychological disorders can be identified from driving data, and usually analyses utilize simple models and aggregated data. This study aims at utilizing microscopic data from a driving simulator to detect sessions belonging to “depressed” drivers by utilizing powerful machine learning classifiers. Driving simulator sessions from 11 older drivers with symptoms of depression and 65 healthy drivers were utilized towards that aim. Random Forests, an ensemble classifier, with proven efficiency among transportation applications, are then trained on highly disaggregated data describing the mean and standard deviation of speed and lateral or longitudinal acceleration of drivers in the simulator. The kinematic data were aggregated in 30-seconds, 1-minute and 5-minute intervals, but the corresponding time-series of the measurements were also taken into account. Furthermore, classifiers were treated with imbalanced learning techniques to address the scarcity of depressed drivers among the healthy. Time-series of mean speed and the standard deviation of longitudinal acceleration even with a duration of 30-seconds have proven to be the best predictors of driving sessions belonging to depressed drivers with a very low rate of false alarms. The results outperform previous approaches, and indicate that naturalistic driving data or deep learning could prove even more efficient in detecting depression.     

Mild functional decline and driving performance of older drivers without a diagnosed dementia: Study of leukoaraiosis and cognitive function

Motor vehicle collisions involving older drivers have increased and become an important social issue. It is known that the decline of cognitive function, including dementia, affects driving performance. A series of studies using the Mini-Mental State Examination (MMSE) and other tests of dementia have attempted to prevent motor vehicle collisions by identifying as early as possible older drivers who may be unable to maintain their driving performance. Further, the performance of older drivers may deteriorate even if they do not have a diagnosis of dementia. Therefore we focused on the relationship between cognitive functioning assessed by the MMSE and diagnosis of leukoaraiosis (LA), or changes in the cerebral white matter, with different aspects of driving behavior resulting from aging. Qualified driving instructors evaluated participants’ driving behaviors on an outdoor driving course at a driving school. Visual search duration and angle at intersections were obtained by wearable wireless sensors. Vehicle speed and minimum vehicle speed were recorded from vehicle speed pulse signals. Duration of signaling and visual searches at unsignalized intersections were recorded using an in-vehicle camera. We assessed instructors’ evaluations and the scores on two instruments to evaluate the effects of MMSE scores and the grade of LA on driving performance were verified. The results suggest that lower MMSE scores and higher LA grade can predict some aspects of poor driving performance in older drivers before they experience dementia or an evident decline in cognitive functioning. Based on these results, we discuss countermeasures that may prevent motor vehicle collisions involving older drivers.     

Aging drivers and post delineated express lanes: Threading the needle at 70 miles per hour

Post-delineated express lanes represent a combination of driving complexities that are particularly difficult for older drivers to navigate. The narrow geometry and high speeds that are common to this treatment reflect a critical test for drivers whose depth perception, contrast sensitivity, and visual processing speed are reduced. The present study was designed to empirically examine the effects of age and color of express lane delineators on driver behavior. Three groups of participants (aged 18–39, 40–64, and 65 + years old) were required to complete a series of simulated driving scenarios consisting of combinations of single and dual lane configurations, with speed and lane position measured at the beginning and midpoint of each express lane. All drivers were pre-screened on various visual functioning abilities. Drivers in the 65 and older group show significant age-related declines in depth perception, contrast sensitivity, and phoria which were subsequently correlated with a wide range of driving measures including deceleration rate, brake time, jerk, speed, and lane position. Age related perceptual declines were statistically correlated with slower driving speed and wider lane deviations, including a statistically significant increase in the number of excursions beyond the typical 12-foot lane width. Based on these findings, the behavior of senior drivers was identified as a distinct design condition that should govern the design of high-speed, narrow geometric conditions. This age group requires wider lane widths, particularly at the beginning of single-lane post delimited sections, wider buffer areas around the post markers, and dual lane configurations wherever possible.     

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.