Relationships between personality facets and accident involvement among truck drivers

Prior research on the personality characteristics of truck drivers and accident involvement has relied primarily on the Big Five personality factors (e.g., Extraversion), and has largely focused on self-reported number of accidents rather than more objective, independent records. We examined the association between personality characteristics and accidents among professional truck drivers at the facet level of personality using company records of accidents over time. Analyses suggested that more empathetic individuals had lower rates of accident involvement, whereas more anxious, guilt-prone, exhibitionistic, and risk-taking individuals had higher rates. We discuss implications for decreasing rates of accidents, the selection of drivers, and use in other industries where physical safety is a concern.     

Analysis of driver’s decision distance and merging distance in work zone area based on parametric survival models: With the aid of a driving simulator experiment

Work zones affect traffic safety and efficiency by changing the road condition and drivers’ maneuver. Therefore, it is important to fully understand drivers’ merging behavior in work zone related areas. In this study, a model framework composed of decision-distance analysis and merging-distance analysis was proposed, which could describe both decision-making and lane-changing process of merging behavior. A road environment with work zone was developed based on a driving simulator, and six scenarios composed of two levels of traffic volume and three different lane-end sign’s locations were designed. Forty-two licensed participants, including 21 females (10 professional drivers vs. 11 normal drivers) and 21 males (15 professional drivers vs. 6 normal drivers) finally completed the experiment. Based on the experimental data, parametric survival models were established to analyze the effects of traffic sign location, traffic situation and driver characteristics on drivers’ decision distance and merging distance. The results showed that: (i) the lane-end sign’s location affected the decision point of lane changing and further affected the merging distance. However, the effect was weakened when the sign was placed far away from the work zone; (ii) merging distance in high traffic volume condition was shorter than that in low traffic volume condition; (iii) work zone posed greater challenges for female drivers as they merged later than males, and females were reluctant to adjust their merging distance according to different gap conditions. The findings shed some light on the future improvement of traffic design and management in work zones.     

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.