Lane Position Variability Research Articles

Heart rate variability as an indicator of fatigue: A structural equation model approach

Driver fatigue significantly impairs performance and is a major risk factor for road crashes. However, fatigue is difficult to objectively measure and quantify. This study aimed to elucidate associations between heart rate variability (HRV) metrics and multidimensional fatigue construct encompassing objective and subjective measures in young drivers with self-reported short sleep. Eighty-four young adults underwent assessments during simulated driving. HRV indices RMSSD and LF/HF ratio were derived from an electrocardiogram, while relative Theta power, oculography drowsiness, lane position variability, and Karolinska Sleepiness Score measured fatigue. RMSSD negatively correlated with Theta power, and LF/HF ratio positively correlated with position variability. Exploratory factor analysis extracted three factors, with RMSSD and LF/HF loading onto one. Structural equation modelling tested the prediction of a latent fatigue construct from HRV. Two models demonstrated an acceptable fit. RMSSD negatively predicted fatigue, explaining 6.4 % of the variance, while the LF/HF ratio positively predicted fatigue, accounting for 3.7 % of the variance. In summary, HRV, particularly RMSSD, showed significant relationships with multidimensional fatigue. Lower RMSSD and higher LF/HF ratio are associated with greater fatigue levels. This study demonstrates that HRV indices exhibit significant relationships within a multidimensional model of fatigue incorporating objective performance, ocular, and subjective measures. The findings provide initial evidence towards using HRV for monitoring complex manifestations of fatigue, rather than single dimensions. Further applied research should investigate translating these findings to naturalistic settings and validating HRV thresholds predictive of on-road impairment.

Neuroanatomical correlates of distracted straight driving performance: a driving simulator MRI study across the lifespan.

Driving is the preferred mode of transportation for adults across the healthy age span. However, motor vehicle crashes are among the leading causes of injury and death, especially for older adults, and under distracted driving conditions. Understanding the neuroanatomical basis of driving may inform interventions that minimize crashes. This exploratory study examined the neuroanatomical correlates of undistracted and distracted simulated straight driving. One-hundred-and-thirty-eight participants (40.6% female) aged 17-85 years old (mean and SD = 58.1 ± 19.9 years) performed a simulated driving task involving straight driving and turns at intersections in a city environment using a steering wheel and foot pedals. During some straight driving segments, participants responded to auditory questions to simulate distracted driving. Anatomical T1-weighted MRI was used to quantify grey matter volume and cortical thickness for five brain regions: the middle frontal gyrus (MFG), precentral gyrus (PG), superior temporal cortex (STC), posterior parietal cortex (PPC), and cerebellum. Partial correlations controlling for age and sex were used to explore relationships between neuroanatomical measures and straight driving behavior, including speed, acceleration, lane position, heading angle, and time speeding or off-center. Effects of interest were noted at an unadjusted p-value threshold of 0.05. Distracted driving was associated with changes in most measures of straight driving performance. Greater volume and cortical thickness in the PPC and cerebellum were associated with reduced variability in lane position and heading angle during distracted straight driving. Cortical thickness of the MFG, PG, PPC, and STC were associated with speed and acceleration, often in an age-dependent manner. Posterior regions were correlated with lane maintenance whereas anterior and posterior regions were correlated with speed and acceleration, especially during distracted driving. The regions involved and their role in straight driving may change with age, particularly during distracted driving as observed in older adults. Further studies should investigate the relationship between distracted driving and the aging brain to inform driving interventions.

87 Virtual Driving Relates to Real-World Risky Driving

Objective:Driving is a cognitively demanding activity commonly affected by brain injury and illness. Accurate driving assessment is essential for reducing risk, optimizing independence, and informing driving-related interventions. Virtual reality driving simulation (VRDS) enables safe, sensitive, objective, and standardized measurement of driving abilities. VRDS has been validated in relation to self-reports and driver records. However, self-reports are subjective, and driver records include only major events (collisions, violations). Video telematics platforms can measure naturalistic driving in a more objective and sensitive manner. The present study used video telematics to examine relationships between VRDS performance and directly observed naturalistic driving.Participants and Methods:20 healthy adult drivers (ages 23-61, mean age=36; 75% women) completed a VRDS assessment that included 1) driving on a straight road, 2) following a truck on a highway, and 3) reacting to a child running into a street to retrieve a ball. Primary VRDS measures were 1) speed and lane management on the straight road; 2) speed and following distance management in the truck-following task; and 3) reaction time, stopping, and distance from the child in the child-ball task. Participants also completed 28 days of naturalistic driving with a video telematics platform in their vehicle. Driving events were detected automatically using accelerometer, GPS, and video data, and driving behaviors were coded by driving risk analysts. The primary naturalistic measure was the number of unsafe driving behaviors per hour driven; specific driving behaviors served as exploratory variables. We examined correlations between VRDS and naturalistic driving variables. Given limited statistical power, we reported correlations that were small-to-medium or greater (r>.2) in primary analyses and medium-to-large or greater (r>.4) in exploratory analyses.Results:On average, drivers exhibited approximately one unsafe driving behavior per hour (M=0.9, SD=0.9, range=0.1-2.7). Common behaviors were failing to stop, unsafe following distance, speeding, and cell phone use. No collisions occurred. Average lane position in VRDS (specifically, leftward deviation from the center of the lane) was correlated with more real-world unsafe driving behaviors per hour (r=.35, p=.13), as were higher average straight road speed (r=.26, p=.27), greater straight road speed variability (r=.28, p=.24), and failing to stop for the child in the child-ball task (r=.22, p=.36). In exploratory analyses, failing to stop for the child was associated with real-world distracted driving (r=.45, p=.047), greater lane position variability in VRDS was associated with real-world unsafe following distance (r=.57, p=.009), and greater speed variability in VRDS was associated with real-world seat belt non-use/misuse (r=.49, p=.03).Conclusions:The present findings provide preliminary evidence that VRDS variables are related to directly observed naturalistic driving, supporting the potential utility of VRDS as a sensitive, ecologically valid driving evaluation tool. As the present study used a small sample of healthy drivers, further research will explore this topic in larger samples and in clinical populations, such as acquired brain injury. Future work will also investigate whether incorporating VRDS with conventional driving evaluation tools (e.g., neuropsychological tests, behind-the-wheel assessments) can enhance the ability of clinical driving evaluations to predict real-world risky driving.

A - 86 Using Virtual Reality Driving Simulation to Determine Cognitive Correlates of Turning Behaviors among Drivers with and without Multiple Sclerosis.

This study uses a virtual reality driving simulator (VRDS) to 1) compare turning behavior between adults with or without MS; 2) identify cognitive correlates of turning behavior. 64 community-dwelling adult drivers, including 38 people with MS (PwMS) and 26 healthy controls (HCs) (ages 21-60, 78% women, 69% White), completed neuropsychological and VRDS assessments. Key VRDS turning variables were lane position, speed, acceleration, and braking. Cross-sectional analyses included 1) analysis of variance and chi-square tests; 2) Pearson and Spearman's correlations. HCs took sharper left turns than PwMS (p < 0.05, η2 = 0.08). There were no other between-group differences. Weaker visuospatial functioning [r = -0.301, 95% CI = (-0.512,-0.050), p = 0.018], and slower gait [r = 0.0328, CI = (0.063,0.55), p = 0.014], manual motor speed [r = 0.378, CI = (0.130,0.582), p = 0.03], and psychomotor speed [r = -0.334, CI = (-0.545,-0.077), p = 0.011] were associated with greater lane position variability. Greater relative acceleration before the turn was linked to worse performance in psychomotor speed [r = 0.397, CI = (0.148,0.593), p = 0.002], time-based working memory [r = 0.452, CI = (0.221,0.631), p < 0.001], and visuoperceptual judgment time [r = -0.482, CI = (-0.660,-0.244), p < 0.001]. Slower cognitive/motor speed and poorer visuospatial abilities/memory were associated with slower driving and more braking (all p < 0.05). Drivers with and without MS exhibited similar turning behavior, but PwMS were more cautious during left turns, possibly reflecting a compensatory strategy. Despite few group differences, several cognitive domains commonly affected by MS were associated with turning behaviors. Slower cognitive/motor speed and worse visuospatial abilities were associated with less smooth control of spatial position and less safe turn preparation, but slower driving. Future studies will include larger samples and other clinical populations and may inform clinical driving recommendations.

Cognitive functioning and simulated driving in older adults with and without cognitive impairment

AbstractBackgroundAge‐related changes in cognitive functions affect complex task engagement such as driving. Studies have demonstrated high occurrences of driving errors and crashes among older adults, particularly those with mild cognitive impairment (MCI). We have previously demonstrated that fatigue contributes to detriments in driving ability, especially among MCI, and that attention‐maintenance tasks (AMT) improve older cognitively normal (OCN) but not MCI performance. This study considers which cognitive deficits predict driving performance across AMT conditions.MethodsParticipants included 34 OCN and 21 MCI adults age 60+ years diagnosed through consensus conference, who completed tests of memory (HVLT‐R delayed recall), executive functioning (Trail Making Test B; TMB), working memory (CogState One Back Test, ONB), simple reaction time (CogState Detection Test, DET), and choice reaction time (CogState Identification Test, IDN). Computerized driving scenarios were presented on a 45” flat screen monitor, which included a 50‐minute simulated drive designed to induce fatigue, followed by four 10‐minute sessions alternating between driving with and without AMT. Lane position, velocity, lane and velocity variability, and driving errors (e.g., leaving the road, crossing midline) were compared across 10‐minute driving segments. Cognitive measures and diagnosis were used to predict driving performance.ResultsParticipants with MCI 1) maintained significantly slower average speed, 2) demonstrated higher variability in lane‐keeping, and 3) had greater velocity variability, only in the non‐AMT condition. OCN participants performed significantly better on all cognitive measures, except DET. Linear regressions showed that TMB, alone, predicted average velocity during the AMT driving condition with no significant predictors for the non‐AMT. Velocity variability during the non‐AMT driving condition was predicted by the main effect of Diagnosis, TMBxDiagnosis, and ONBxDiagnosis interactions. TMB and HVLT‐R predicted velocity variability during the AMT condition. Lane variability during both driving conditions was predicted by DETxDiagnosis and IDNxDiagnosis.ConclusionsPerformance on TMB and its interactions are predominantly important predictors for velocity‐related driving conditions. Reaction time decrements among those with MCI predict lane variability. This suggests that executive functions are particularly needed in maintaining velocity, while monitoring is critical for maintaining lane position. Our findings demonstrate that higher cognitive burden likely accentuates driving difficulty, especially in MCI.

Modeling the influence of 0.03%, 0.05% and 0.08% blood alcohol concentrations on lane positioning and steering control of Indian drivers

Objective Alcohol-impairment of drivers has significant influence on road traffic safety; however, no experimental research has been conducted on the lateral driving control of Indian drivers. Therefore, the present study investigates the effects of different Blood Alcohol Concentration (BAC) levels (0%, 0.03%, 0.05% and 0.08%) and driver attributes on the lane positioning and steering control of Indian drivers. Method A driving simulator experiment was designed where 82 adult licensed drivers (62 males, 20 females) completed driving on the simulated urban arterial road environment under the influence of varying BACs. Lateral driving performance measures associated with lane positioning (lane position variability) and steering control of drivers (steering angle variability and steering reversal rates (SRR)) were analyzed. Results The findings reported that lane position variability was significantly influenced only at 0.08% BAC (5.8% increment); no significant influence was observed at 0.03% and 0.05% BACs. Compared to 0% BAC, steering angle variability increased by 0.105 degrees or 15.7%, 0.142 degrees or 21.4%, and 0.176 degrees or 25.7% at 0.03%, 0.05% and 0.08% BACs respectively. No significant differences were observed between the sober-state driving and alcohol-impaired driving at 1ο and 5ο SRR. However, 10ο SRR was found to be higher by 36%, 65% and 92% at 0.03%, 0.05% and 0.08% BACs compared to 0% BAC. Among the driver attributes, male drivers displayed higher impairment in lane positioning behavior as compared to female drivers. One-year increase in drivers’ age reduced the lane position variability by 0.6%. Drivers who performed regular physical exercise were found to have better lateral control on the vehicle, as observed in their steering angle variability. Prior crash history had negative association with the steering reversal rates, indicating that drivers who have previous experience of crash involvement show better steering control than the drivers without any crash experience. Conclusion In conclusion, the outcomes of this study provide novel insights into the alcohol-impaired lateral vehicle control of Indian drivers which can assist in policy interventions aiming to reduce crashes with alcohol as a major crash causation factor.

Identifying the distracting aspects of electronic advertising billboards: A driving simulation study

The aim of the study was to investigate the impact of digital billboards on driving performance and visual attention. The impact of dwell time, location and content of digital billboards on driving behaviour was also examined. A 3 × 2 × 2 × 2 experimental study was undertaken using a laboratory driving simulator and data analysed using factorial four-way analysis of variance. A total of 96 participants completed the study, ranging in age from 18 to 76 years. On sections of roads containing billboards, participants drove at lower mean speeds (p < 0.001), had more speed variability (p < 0.001), more variability in lane position (p < 0.001), more time spent at high risk headway < two seconds (p = 0.013), more time spent at high risk headway <0.25 s (p = 0.002) and had more visual fixations (p = 0.01), compared to control sections of road with no billboards. Billboards with simple (versus complex) content presented at a long dwell time (60 s versus 40 or 20 s) had the least negative impact on driving outcomes. Billboards with complex content had similar negative effects on driving, regardless of dwell time. In addition, post-mounted roadside billboards (versus bridge mounted) with 60 s dwell times had the least negative impact on driving. While the presence of digital billboards negatively affected driving performance, simple billboard content and longer dwell times were safer. The results of the study will assist in the development of evidence-based guidelines for digital billboards.

Driving after pediatric traumatic brain injury: Impact of distraction and executive functioning.

The objective of the current study was to examine the driving performance of young drivers with a history of moderate to severe traumatic brain injury (TBI) compared with an uninjured control group. The impact of cell phone related distraction (conversation and texting) and executive functioning (EF) were also explored. Individuals aged 16-25 years with (n = 19) and without (n = 19) a history of TBI engaged in a simulated drive under 3 distraction conditions (no distraction, cell phone conversation, and texting). Mean speed, maximum speed, standard deviation of speed, standard deviation of lane position, and crash rates were used as outcomes. The Global Executive Composite (GEC) from the Behavior Rating Inventory of Executive Functioning (BRIEF) was used to measure EF. Significant Injury × Distraction × GEC interaction effects were noted on max speed and speed variability, with a trending Distraction × GEC interaction noted for lane position variability. The effect of distraction was most notable among individuals with greater GEC scores, across both injury groups. A history of pediatric TBI did not specifically impact driving performance independent of EF, with EF playing a central role in functioning across domains of driving performance. Consistent effect of EF suggests that deficits in driving performance may be associated with EF specifically, with individuals with EF difficulties following TBI at greater risk for poor driving performance. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Exploring driving characteristics of fit- and unfit-to-drive neurological patients: a driving simulator study

Objective: To identify driving characteristics of fit-, unfit-, and conditionally fit-to-drive neurological patient populations using a driving simulator with three high-risk scenarios comprising rural, highway, and urban environments.Methods: The study included 91 neurological patients undergoing a multidisciplinary assessment for driver’s license revalidation, consisting of a clinical, neuropsychological, functional, and on-road evaluation. The groups drove through three independent driving scenarios, during which a variety of measures describing reaction time, vehicular control, and traffic rule compliance were performed. One-way analysis of variance (ANOVA) with Bonferroni correction was used for group comparison, independently for each driving scenario, and Pearson correlations were calculated between simulator variables and neuropsychological test scores.Results: The fit- and unfit-to-drive population significantly differed (p < .05) in reaction times, regardless of the scenario. No significant differences in traffic rule compliance or vehicular control parameters were observed in the rural environment (p > .05). On the highway, the unfit group exhibited greater variability of steering wheel angle, higher steering reversal rate, and a higher rate of turn signal errors. In the urban environment, the unfit group oversped more, had more collisions, and exhibited greater lane position variability. The latter, along with reaction times in the rural and highway scenarios, was also shown to significantly differ between the conditional and unfit group (p < .05). No significant differences were observed between the fit and the conditional group (p > .05). Weak to moderate associations (range: −0.5 to 0.29) between neuropsychological tests and various simulator variables were also observed.Conclusions: Our results show that driving simulators are able to capture differences between (fit- and unfit-to-drive) neurological patient populations and therefore bear the potential for being used as a deficit-independent screening, assessment, or rehabilitation tool. The conditionally-fit-to-drive group exhibited less discriminative features, which points to greater importance of human judgment for this population. The observation that differences in most of the parameters were environment-dependent suggests that developers of future driver simulation tools should carefully design scenarios in order to fully exploit their assessment potential.

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.

Effects of roadside distractors on performance of drivers with and without attention deficit tendencies

As roadway systems become more complex, with increased visual clutter, new automation technologies, and mixed modes of transportation, it is increasingly important to understand the effects of roadside distractors on driver performance. While driver distraction negatively impacts driver performance and crash rates for all drivers, it is especially important for vulnerable road users who may have an increased risk of distraction. This research was aimed at identifying the influence of roadside distractors on the performance of drivers with and without attention deficit tendencies, and it used a driving simulator to obtain performance metrics in the vicinity of distractors. Overall, the study found that roadside events have statistically significant effects on variability of lane position and speed, and drivers with attention deficit tendencies displayed more lane position variability than control group drivers for all roadway segments examined. Of the distractors tested, billboards and work zones were shown to have the most significant impacts on driver inattention, as evidenced by decreased detection time margins and error rates, respectively. This study is one of the first to examine the effects of roadside distractors on drivers with and without attention deficit disorders, and the results lend insight to the effects that external distractions can have on driver performance.

Effects of primary task predictability and secondary task modality on lane maintenance

The objective of this work was to investigate the effects of auditory and visuo-spatial secondary tasks on variability in lane position in predictable and unpredictable driving conditions. Sixty-six participants drove a simulated vehicle. Predictability was manipulated by adding wind gusts, and the secondary task load by either an auditory task (Experiment 1) or a visuo-spatial task (Experiment 2). Results demonstrated that in the predictable driving condition, lane position variability decreased when auditory secondary task load was given, but it was not affected by visuo-spatial secondary task load. In the unpredictable driving condition; however, while the auditory secondary task load did not affect lane position variability, visuo-spatial secondary task load increased it. The data suggests that the effects of cognitive load on lane maintenance may depend on the type of the secondary task beside predictability of primary task.

Evaluating driver drowsiness countermeasures

ABSTRACTObjective: Driver drowsiness contributes to a substantial number of fatal and nonfatal crashes, with recent estimates attributing up to 21% of fatal crashes to drowsiness. This article describes recent NHTSA research on in-vehicle drowsiness countermeasures. Recent advances in technology and state detection algorithms have shown success in detecting drowsiness using a variety of data sources, including camera-based eye tracking, steering wheel position, yaw rate, and vehicle lane position. However, detection is just the first step in reducing drowsy driving crashes. Countermeasures are also needed to provide feedback to the driver, modify driver behavior, and prevent crashes. The goal of this study was to evaluate the effectiveness of in-vehicle drowsiness countermeasures in reducing drowsy lane departures. The tested countermeasures included different warning modalities in either a discrete or staged interface.Methods: Data were collected from 72 young adult drivers (age 21–32) in the high-fidelity full-motion National Advanced Driving Simulator. Drivers completed a 45-min simulated nighttime drive at 2 time points, late night and early morning, where drowsiness was manipulated by continuous hours awake. Forty-eight drivers were exposed to one of 6 countermeasures that varied along 2 dimensions, type and modality. The countermeasures relied on a steering-based drowsiness detection algorithm developed in prior NHTSA research. Twenty-four drivers received no countermeasure and were used as a baseline comparison. System effectiveness was measured by lane departures and standard deviation in lateral position (SDLP).Results: There was a reduction in drowsy lane departure frequency and lane position variability for drivers with countermeasures compared to the baseline no-countermeasure group. Importantly, the data suggest that multistage alerts, which provide an indication of increasing urgency, were more effective in reducing drowsy lane departures than single-stage discrete alerts, particularly during early morning drives when drivers were drowsier.Conclusions: The results indicate that simple in-vehicle countermeasures, such as an auditory–visual coffee cup icon, can reduce the frequency of drowsy lane departures in the context of relatively short drives. An important next step is to evaluate the impact of drowsiness countermeasures in the context of longer, multiple-hour drives. In these cases, it may not be possible to keep drivers awake via feedback warnings and it is important to understand whether countermeasures prompt drivers to stop to rest. The next phase of this research project will examine the role of drowsiness countermeasures over longer drives using a protocol that replicates the motivational conditions of drowsy driving.

Smartwatches vs. Smartphones

This work seeks to understand whether the unique features of a smartwatch, compared to a smartphone, mitigate or exacerbate driver distraction due to notifications, and to provide insights about drivers' perceptions of the risks associated with using smartwatches while driving. As smartwatches are gaining popularity among consumers, there is a need to understand how smartwatch use may influence driving performance. Previous driving research has examined voice calling on smartwatches, but not interactions with notifications, a key marketed feature. Engaging with notifications (e.g., reading and texting) on a handheld device is a known distraction associated with increased crash risks. Two driving simulator studies compared smartwatch to smartphone notifications. Experiment I asked participants to read aloud brief text notifications and Experiment II had participants manually select a response to arithmetic questions presented as notifications. Both experiments investigated the resulting glances to and physical interactions with the devices, as well as self-reported risk perception. Experiment II also investigated driving performance and self-reported knowledge/expectation about legislation surrounding the use of smart devices while driving. Experiment I found that participants were faster to visually engage with the notification on the smartwatch than the smartphone, took longer to finish reading aloud the notifications, and exhibited more glances longer than 1.6 s. Experiment II found that participants took longer to reply to notifications and had longer overall glance durations on the smartwatch than the smartphone, along with longer brake reaction times to lead vehicle braking events. Compared to the no device baseline, both devices increased lane position variability and resulted in higher self-reported perceived risk. Experiment II participants also considered that smartwatch use while driving deserves penalties equal to or less than smartphone use. The findings suggest that smartwatches may have road safety consequences. Given the common view among participants to associate smartwatch use with equal or less traffic penalties than smartphone use, there may be a disconnect between drivers' actual performance and their perceptions about smartwatch use while driving.

Naturalistic field study of the restart break in US commercial motor vehicle drivers: Truck driving, sleep, and fatigue

Commercial motor vehicle (CMV) drivers in the US may start a new duty cycle after taking a 34-h restart break. A restart break provides an opportunity for sleep recuperation to help prevent the build-up of fatigue across duty cycles. However, the effectiveness of a restart break may depend on its timing, and on how many nighttime opportunities for sleep it contains. For daytime drivers, a 34-h restart break automatically includes two nighttime periods. For nighttime drivers, who are arguably at increased risk of fatigue, a 34-h restart break contains only one nighttime period. To what extent this is relevant for fatigue depends in part on whether nighttime drivers revert back to a nighttime-oriented sleep schedule during the restart break. We conducted a naturalistic field study with 106 CMV drivers working their normal schedules and performing their normal duties. These drivers were studied during two duty cycles and during the intervening restart break. They provided a total of 1260days of data and drove a total of 414,937 miles during the study. Their duty logs were used to identify the periods when they were on duty and when they were driving and to determine their duty cycles and restart breaks. Sleep/wake patterns were measured continuously by means of wrist actigraphy. Fatigue was assessed three times per day by means of a brief psychomotor vigilance test (PVT-B) and a subjective sleepiness scale. Data from a truck-based lane tracking and data acquisition system were used to compute lane deviation (variability in lateral lane position). Statistical analyses focused on 24-h patterns of duty, driving, sleep, PVT-B performance, subjective sleepiness, and lane deviation. Duty cycles preceded by a restart break containing only one nighttime period (defined as 01:00–05:00) were compared with duty cycles preceded by a restart break containing more than one nighttime period. During duty cycles preceded by a restart break with only one nighttime period, drivers showed more nighttime-oriented duty and driving patterns and more daytime-oriented sleep patterns than during duty cycles preceded by a restart break with more than one nighttime period. During duty cycles preceded by a restart break with only one nighttime period, drivers also experienced more lapses of attention on the PVT-B and increased lane deviation at night, and they reported greater subjective sleepiness. Importantly, drivers exhibited a predominantly nighttime-oriented sleep schedule during the restart break, regardless of whether the restart break contained only one or more than one nighttime period. Consistent with findings in laboratory-based studies of the restart break, the results of this naturalistic field study indicate that having at least two nighttime periods in the restart break provides greater opportunity for sleep recuperation and helps to mitigate fatigue.

Distracted Driving in Teens With and Without Attention-Deficit/Hyperactivity Disorder

This study is among the first to examine the effect of talking on a cell phone or text messaging while driving in teens with and without attention deficit/hyperactivity disorder (ADHD). Teens (average age 17years) with a diagnosis of ADHD (N=16) were matched with typically developing controls (N=18). All participants operated a driving simulator while (1) conversing on a cell phone, (2) text messaging, and (3) with no distraction during a baseline condition. Six indicators of driving performance were recorded: (a) time to complete the drive; (b) lane deviations; (c) variability in lane position (i.e., root mean square [RMS]); (d) reaction time; (e) motor vehicle collisions; and, (f) speed fluctuation. Significantly greater variation in lane position occurred in the texting task compared to no task and the cell phone task. While texting, in particular, teens with ADHD took significantly less time to complete the scenario. No significant main effects of group were found. Generally, those with ADHD did not differ in regard to driving performance, when compared to controls, with the exception of one outcome: time to complete scenario. These findings suggest that distracted driving impairs driving performance of teen drivers, regardless of ADHD status. Texting while driving had the greatest negative impact on driving performance, particularly with regard to variability in lane position (i.e., RMS). This study sheds light on key issues regarding injury prevention, with the intent of providing pediatric care providers with the knowledge to inform teen drivers of risks associated with distracted driving which will ultimately result in reduced rates of motor vehicle crashes and concomitant injuries.

Lane heading difference: An innovative model for drowsy driving detection using retrospective analysis around curves

Driving while sleepy is a serious contributor to automobile accidents. Previous research has shown that drowsy drivers produce systematic errors (variability) in vehicle behavior which are detectable using vehicle monitoring technology. The current study developed a new methodological approach using a vehicle heading difference metric to detect drowsy driving more effectively than other more commonly used methods. Twenty participants completed a driving scenario as well as several measures of fatigue in five testing sessions across a night of sleep deprivation. Each simulated highway driving session lasted 20min, and was analyzed for lateral lane position variability and vehicle heading difference variability with two statistical methods. Fatigue measures monitored reaction time, attention, and oculomotor movement. The results showed that examining lane heading difference using the absolute value of the raw data detected driving variability better across the night than other statistical models. The results from the fatigue measures indicated an increase in reaction time and response lapses, as well as a decrease in oculomotor reactivity across the night. These results suggest that in fatigued drivers the statistical model using the absolute value of lane heading could be an improved metric for drowsy driving detection that could accurately detect detriments in driving ability at lower levels of fatigue.

Extended Visual Glances Away from the Roadway are Associated with ADHD- and Texting-Related Driving Performance Deficits in Adolescents.

The purpose of the research study was to determine whether ADHD- and texting-related driving impairments are mediated by extended visual glances away from the roadway. Sixty-one adolescents (ADHD =28, non-ADHD =33; 62% male; 11% minority) aged 16-17 with a valid driver's license were videotaped while engaging in a driving simulation that included a No Distraction, Hands-Free Phone Conversation, and Texting condition. Two indicators of visual inattention were coded: 1) percentage of time with eyes diverted from the roadway; and 2) number of extended (greater than 2 s) visual glances away from the roadway. Adolescents with ADHD displayed significantly more visual inattention to the roadway on both visual inattention measures. Increased lane position variability among adolescents with ADHD compared to those without ADHD during the Hands-Free Phone Conversation and Texting conditions was mediated by an increased number of extended glances away from the roadway. Similarly, texting resulted in decreased visual attention to the roadway. Finally, increased lane position variability during texting was also mediated by the number of extended glances away from the roadway. Both ADHD and texting impair visual attention to the roadway and the consequence of this visual inattention is increased lane position variability. Visual inattention is implicated as a possible mechanism for ADHD- and texting-related deficits and suggests that driving interventions designed to address ADHD- or texting-related deficits in adolescents need to focus on decreasing extended glances away from the roadway.

Mutual Interferences of Driving and Texting Performance

Despite legislative and social campaigns to reduce texting while driving, drivers continue to text behind the wheel. There is abundant evidence demonstrating that texting while driving impairs driving performance. While past driver distraction research has focused on how texting influences driving, the influence of driving on texting behaviors is often ignored. This study used a classic Lane Change Task and a smartphone texting application to study the mutual influences of driving and texting. Results showed that concurrent texting impaired driving by increasing variability in lane position. Meanwhile, driving impaired texting by increasing the texting task completion time and texting errors, and reduced texting key entry speed. The finding of mutual interferences of driving and texting provides new knowledge for social campaigns, which intend to persuade drivers not to drive while texting, and importantly provides a scientific basis for the development of smartphone-based technology to reduce the risky behavior of driving while texting.

Auditory forward collision warnings reduce crashes associated with task-induced fatigue in young and older drivers

Driver fatigue poses a persistent threat to transportation safety. Auditory warnings provided prior to a potential collision event can reduce crash probability in alert drivers, but it is unclear whether they are effective in fatigued young and older drivers. In the present study fatigue was task-induced in young (18–29 yrs.) and older (65–85 yrs.) licensed drivers via a 1.5 hour simulated car following task. Upon meeting a fatigue criterion – based on individually assessed excessive lane position variability – a single potential collision event was triggered and drivers were either provided an auditory warning or not. The auditory warning significantly reduced overall crash probability and was particularly beneficial in reducing crashes in older drivers. Auditory collisions warnings can reduce fatigue-related rear-end crashes, particularly among older drivers – a population at greater risk of both fatigue and crashes.