Driving Performance Variables Research Articles

The use of transcutaneous Vagal Nerve Stimulation as an effective countermeasure for Simulator Adaptation Syndrome

This research focused on investigating the effectiveness of Transcutaneous Vagal Nerve Stimulation (tVNS) as compared to Galvanic Cutaneous Stimulation (GCS) at mitigating Simulator Adaptation Syndrome (SAS). Fifty drivers (mean age = 23.04 ± 17.71 years old, twenty-two men) participated in a driving simulation experiment. The total scores of the Simulator Sickness Questionnaire, head movements (body balance index), and driving performance variables were measured under five stimulation conditions: i) baseline (no stimulation delivered), ii) sham GCS, iii) sham tVNS, iv) active GCS, and v) active tNVS. The results showed that tVNS alleviated SAS and improved driving performance variables more effectively than GCS. We conclude that GCS and tVNS have similar neurological mechanisms to reduce SAS, providing possible explanations for the greater effectiveness of tVNS. We encourage the use of tVNS to decrease SAS.

Preliminary Eye-Tracking Data as a Nonintrusive Marker for Blood Δ-9-Tetrahydrocannabinol Concentration and Drugged Driving.

Background: Cannabis is one of the drugs most often found in drivers involved in serious motor vehicle collisions. Validity and reliability of roadside cannabis detection strategies are questioned. This pilot study aimed to investigate the relationship between eye characteristics and cannabis effects in simulated driving to inform potential development of an alternative detection strategy. Materials and Methods: Multimodal data, including blood samples, eye-tracking recordings, and driving performance data, were acquired from 10 participants during a prolonged single-session driving simulator experiment. The study session included a baseline driving trial before cannabis exposure and seven trials at various times over ∼5 h after exposure. The multidimensional eye-tracking recording from each driving trial for each participant was segmented into nonoverlapping epochs (time windows); 34 features were extracted from each epoch. Blood Δ-9-tetrahydrocannabinol (THC) concentration, standard deviation of lateral position (SDLP), and mean vehicle speed were target variables. The cross-correlation between the temporal profile of each eye-tracking feature and target variable was assessed and a nonlinear regression analysis evaluated temporal trend of features following cannabis exposure. Results: Mean pupil diameter (r=0.81-0.86) and gaze pitch angle standard deviation (r=0.79-0.87) were significantly correlated with blood THC concentration (p<0.01) for all epoch lengths. For driving performance variables, saccade-related features were among those showing the most significant correlation (r=0.61-0.83, p<0.05). Epoch length significantly affected correlations between eye-tracking features and speed (p<0.05), but not SDLP or blood THC concentration (p>0.1). Temporal trend analysis of eye-tracking features after cannabis also showed a significant increasing trend (p<0.01) in saccade-related features, including velocity, scanpath, and duration, as the influence of cannabis decreased by time. A decreasing trend was observed for fixation percentage and mean pupil diameter. Due to the lack of placebo control in this study, these results are considered preliminary. Conclusion: Specific eye characteristics could potentially be used as nonintrusive markers of THC presence and driving-related effects of cannabis. clinicaltrials.gov (NCT03813602).

Joint and individual effectiveness of galvanic cutaneous stimulation and tactile stimulation at decreasing Simulator Adaptation Syndrome.

This research was focused on investigating the effectiveness of galvanic cutaneous stimulation and tactile stimulation jointly and individually at mitigating Simulator Adaptation Syndrome. Forty drivers (mean age = 23.1 ± 3.4 years old, twenty women) participated in a driving simulation experiment. Total scores of the Simulator Sickness Questionnaire, head movements (an index of body balance), and driving performance variables were compared across four different stimulation conditions: i) baseline (where no stimulation was presented), ii) galvanic cutaneous stimulation and iii) tactile stimulation deployed individually, and iv) both techniques deployed jointly. The results showed that both techniques presented in conjunction alleviate Simulator Adaptation Syndrome and improve driving performance more effectively than when they are presented in isolation. Importantly, reduced head movements were only revealed when galvanic cutaneous stimulation was applied. We concluded that the reduction of this syndrome is due to an improvement of body balance (elicited by galvanic cutaneous stimulation), and a distraction from the symptoms (elicited by tactile stimulation). We encourage the use of both techniques simultaneously to decrease Simulator Adaptation Syndrome.

Optimising sleep and performance during night float: A systematic review of evidence and implications for graduate medical education trainees.

Graduate medical education (GME) training commonly requires residents and fellows to engage in night float shift work. This review aims to assess the effectiveness of interventions for trainees when preparing for, completing, and recovering from working night float shifts. We reviewed all available studies published prior to September 2019 using PubMed, Scopus, CINAHL, the Cochrane library, PsycINFO, and Google Scholar databases. We included all original, primary research articles assessing either non-pharmacological or pharmacological interventions on the chronobiological and physiological effects of night float shift work among GME trainees. Five studies (n=179 patients) met inclusion criteria. Interventions included melatonin in the morning before sleep after night float shifts, napping during night float shifts, modafinil after a night of sleep deprivation, and caffeinated energy drinks after 6 consecutive night float shifts. Melatonin improved one measure of attention. A 2-hr nap was associated with improved speed related to task switching. Modafinil improved performance in tests of cognition. Caffeinated energy drinks led to improvement in select driving performance variables and reaction time. Effect sizes for outcome variables were calculated. Heterogeneity among the studies precluded combining the data in a meta-analysis. According to GRADE criteria, the quality of the evidence in these studies was low or very low. Our findings suggest GME trainees may benefit from utilising a limited number of interventions when preparing for or recovering from night float shift work. More investigation is needed to identify interventions that could help GME trainees adapt to and recover from working night float shifts.

In Response.

We thank Drs Charchaflieh and Zafar1 for their interest in our article2 regarding the effect of caffeine consumption on resident physician’s driving performance variables in a high-fidelity, immersive driving simulator. While Charchaflieh and Zafar1 are correct that we did not measure baseline caffeine consumption in the participants, we would submit that there is limited and conflicting evidence whether regular intake of caffeine alters caffeine pharmacokinetics.3–5 In contrast, there is pronounced variability in CYP1A2 activity influencing caffeine clearance related to sex, race, genetic polymorphisms, liver disease, and exposure to agents that further induce the cytochrome system.6–8 Caffeine is primarily metabolized in the liver by cytochrome P450 enzymes, principally by CYP1A2.6 We did not evaluate for genetic polymorphisms nor construct a caffeine dose-response effect. We did, however, incorporate a self-reported caffeine sensitivity measure from all participants. The dose of caffeine (160 mg) administered in this study is considered a pharmacologic dose, such that the difference between people who are perceived to be more or less resistant to the effects of caffeine is not likely to be relevant. In our study of residents at a single institution, it would have been challenging to control for all of the variables that may have impacted caffeine sensitivity, and for that reason, we used perceived caffeine sensitivity. Most importantly, we used a crossover design where each resident served as their own control, completing both arms of the study (caffeinated versus noncaffeinated energy beverage). To the extent that it is possible, this suggests that any observed effect resulted from the caffeine. Drs Charchaflieh and Zafar1 are correct that we did not use the word “simulated” in the title. We feel very strongly that this is not misleading as the aim of our study, stated in both the Introduction and the Conclusion, was to evaluate the impact of a caffeinated energy beverage on driving performance in a high-fidelity driving simulator. The Methods section clearly indicates that the study was performed in the simulator, and the Results section refers directly to improved driving performance variables in the driving simulator. Finally, we note that the words “simulated,” “simulation,” and “simulator” occur 37 times in the article, including 4 times in the Abstract alone! We do not agree with Charchaflieh and Zafar’s1 statement at the end of their letter that suggests that our title or reporting of results within sections of the article are at all misleading or “considered less than accurate.” Julie L. Huffmyer, MDDepartment of AnesthesiologyUniversity of Virginia HealthCharlottesville, Virginia[email protected]Edward C. Nemergut, MDDepartments of Anesthesiology and NeurosurgeryUniversity of Virginia HealthCharlottesville, Virginia

The Impact of Alcohol Hangover on Simulated Driving Performance During a 'Commute to Work'-Zero and Residual Alcohol Effects Compared.

Driving is increasing across the world and road traffic accidents are a major cause of serious injuries and fatalities. The link between alcohol consumption and impaired driving has long been established and has led to legislation in many countries, with enforcement of legal limits based on blood alcohol concentration levels. Alcohol hangover research is an emerging field with a range of laboratory and naturalistic studies now clearly demonstrating the significant impairments that can result from hangover, even when alcohol levels are measured at or close to zero the day following a social drinking occasion. Driving is a commonplace activity but requires competency with a range of complex and potentially demanding tasks. Driving impaired can have serious consequences, including death and serious injury. There have been only limited alcohol hangover driving studies. The studies presented examined the consequences of alcohol hangover with a driving simulator contrasting a group with zero residual alcohol (N = 26) next day and another with residual alcohol (N = 26) assessed with breathalyzer in the morning before undertaking a 20 min commute to work. All participants completed a morning drive after a night without alcohol consumption and another after a night of social drinking. The driving scenarios were relatively demanding including traffic and pedestrians, traffic lights and other potential hazards in a mixed rural and urban journey. Subjective hangover and workload were assessed in addition to a range of driving performance variables, including divided attention, steering control and driving violations. Analyses contrasted driving in the no alcohol condition with the residual alcohol condition. The combined groups data (N = 52) was contrasted with the zero and residual alcohol groups. Significant contrasts were found for a range of driving measures, including divided attention, vehicle control, and driving violations as well as perceived workload. The pattern of impairment was broadly similar across both groups, indicating that whether or not residual alcohol was present, consistent driving impairment was seen. The relatively high number of significant variables may reflect the increased cognitive demand of the 20 min commute drive including busy and complex urban environments. This was also reflected in the significant increase in perceived workload recorded across the 6 dimensions of the National Aeronautics and Space Administration Task Load Index (NASA-TLX). Associations between subjective measures and driving performance with hangover suggested a potential lack of awareness of impairment, though were limited in number. The overall findings indicate that the levels of impairment seen reflect those seen with alcohol impaired driving, even when breath alcohol is zero.

Automatically Detected Microsleep Episodes in the Fitness-to-Drive Assessment

Study Objectives: Microsleep episodes (MSEs) are short fragments of sleep (1–15 s) that can cause dangerous situations with potentially fatal outcomes. In the diagnostic sleep-wake and fitness-to-drive assessment, accurate and early identification of sleepiness is essential. However, in the absence of a standardised definition and a time-efficient scoring method of MSEs, these short fragments are not assessed in clinical routine. Based on data of moderately sleepy patients, we recently developed the Bern continuous and high-resolution wake-sleep (BERN) criteria for visual scoring of MSEs and corresponding machine learning algorithms for automatic MSE detection, both mainly based on the electroencephalogram (EEG). The present study aimed to investigate the relationship between automatically detected MSEs and driving performance in a driving simulator, recorded in parallel with EEG, and to assess algorithm performance for MSE detection in severely sleepy participants.Methods: Maintenance of wakefulness test (MWT) and driving simulator recordings of 18 healthy participants, before and after a full night of sleep deprivation, were retrospectively analysed. Performance of automatic detection was compared with visual MSE scoring, following the BERN criteria, in MWT recordings of 10 participants. Driving performance was measured by the standard deviation of lateral position and the occurrence of off-road events.Results: In comparison to visual scoring, automatic detection of MSEs in participants with severe sleepiness showed good performance (Cohen’s kappa = 0.66). The MSE rate in the MWT correlated with the latency to the first MSE in the driving simulator (rs = −0.54, p < 0.05) and with the cumulative MSE duration in the driving simulator (rs = 0.62, p < 0.01). No correlations between MSE measures in the MWT and driving performance measures were found. In the driving simulator, multiple correlations between MSEs and driving performance variables were observed.Conclusion: Automatic MSE detection worked well, independent of the degree of sleepiness. The rate and the cumulative duration of MSEs could be promising sleepiness measures in both the MWT and the driving simulator. The correlations between MSEs in the driving simulator and driving performance might reflect a close and time-critical relationship between sleepiness and performance, potentially valuable for the fitness-to-drive assessment.

Impact of Caffeine Ingestion on the Driving Performance of Anesthesiology Residents After 6 Consecutive Overnight Work Shifts.

Residency training in anesthesiology involves care of hospitalized patients and necessitates overnight work, resulting in altered sleep patterns and sleep deprivation. Caffeine consumption is commonly used to improve alertness when fatigued after overnight work, in preparation for the commute home. We studied the impact of drinking a caffeinated energy drink (160 mg of caffeine) on driving performance in a high-fidelity, virtual reality driving simulator (Virginia Driving Safety Laboratory using the Driver Guidance System) in anesthesiology resident physicians immediately after 6 consecutive night-float shifts. Twenty-six residents participated and were randomized to either consume a caffeinated or noncaffeinated energy drink 60 minutes before the driving simulation session. After a subsequent week of night-float work, residents performed the same driving session (in a crossover fashion) with the opposite intervention. Psychomotor vigilance task (PVT) testing was used to evaluate reaction time and lapses in attention. After 6 consecutive night-float shifts, anesthesiology residents who consumed a caffeinated energy drink had increased variability in driving for throttle, steering, and speed during the first 10 minutes of open-road driving but proceeded to demonstrate improved driving performance with fewer obstacle collisions (epoch 2: 0.65 vs 0.87; epoch 3: 0.47 vs 0.95; P = .03) in the final 30 minutes of driving as compared to driving performance after consumption of a noncaffeinated energy drink. Improved driving performance was most apparent during the last 30 minutes of the simulated drive in the caffeinated condition. Mean reaction time between the caffeine and noncaffeine states differed significantly (278.9 ± 29.1 vs 294.0 ± 36.3 milliseconds; P = .021), while the number of major lapses (0.09 ± 0.43 vs 0.27 ± 0.55; P = .257) and minor lapses (1.05 ± 1.39 vs 2.05 ± 3.06; P = .197) was not significantly different. After consuming a caffeinated energy drink on conclusion of 6 shifts of night-float work, anesthesiology residents had improved control of driving performance variables in a high-fidelity driving simulator, including a significant reduction in collisions as well as slightly faster reaction times.

Effects of acute alcohol consumption on measures of simulated driving: A systematic review and meta-analysis

Driving simulators are used in a wide range of research settings to help develop an understanding of driver behavior in complex environments. Acute alcohol impairment is an important research topic for traffic safety and a large number of studies have indicated levels of simulated driving impairment imposed by alcohol across a range of performance outcome variables. The aim of the present study was to examine the impact of acute alcohol consumption on simulated driving performance by conducting a systematic review and meta-analysis of the available evidence. The online databases PubMed (MEDLINE), Web of Science (via Thomas Reuters) and Scopus were searched to identify studies that measured simulated car driving performance under control ('no alcohol' or ‘placebo alcohol’ ingestion) and intervention (acute alcohol ingestion) conditions, using repeated-measures experimental designs. Primary research outcomes were standard deviation of lane position (SDLP) and standard deviation of speed (SDSP); (total number of lane crossings (LC) and average speed (Speed) were secondary research outcomes). Meta-analytic procedures were used to quantify the effect of acute alcohol consumption on vehicle control, and to determine the influence of methodological variables (i.e. the duration of the simulated driving task, the limb of the BAC curve (ascending vs. descending) and the type of driving simulator employed (i.e. car vs. PC-based)) on the magnitude of the performance change due to alcohol consumption. 423 records were screened, and 50 repeated-measures trials (n=962 participants, 62% male) derived from 17 original publications were reviewed. 37 trials (n=721 participants) used a ‘placebo alcohol’ comparator to determine the effect of alcohol consumption on SDLP (32/37) and SDSP (22/37). Alcohol consumption significantly increased SDLP by 4.0±0.5cm (95% CI: 3.0, 5.1) and SDSP by 0.38±0.10km⋅h−1 (95% CI: 0.19, 0.57). Regression analyses indicate BAC (p=0.004) and driving simulator platform (p<0.001) influence the magnitude of the SDLP change, such that higher BAC levels and the use of PC-based driving simulators were associated with larger performance decrements (R2=0.80). The limb of the BAC curve and the duration of the driving task did not significantly alter the magnitude of the performance change. Eleven trials (n=205 participants) used a ‘no alcohol’ comparator to measure the effect of alcohol consumption on SDLP (10/11); few trials assessed SDSP (3/11). Alcohol consumption resulted in a small significant increase in SDLP under these conditions (standardized difference in means=0.23, 95% CI: 0.06, 0.39). These results demonstrate that lateral (SDLP and LC) and longitudinal (SDSP) vehicle control measures in a driving simulator are impaired with acute alcohol consumption. However, SDLP appears to be a more sensitive indicator of driving impairment than other driving performance variables and the results of the present study support its use as a performance outcome when examining alcohol-induced simulated driving impairment.

Mindfulness, inattention and performance in a driving simulator

The following study will explore the link between mindfulness, driver inattention and a number of driving performance variables that were tested using the SIMUVEG driving simulator. 67 subjects between the ages of 19 and 27 completed the mindful attention awareness scale, attention-related driving errors scale and attention-related cognitive errors scale questionnaires, and were evaluated in two driving performance measures: time to line-crossing and mean speed. The results did not show a correlation between driving performance and mindfulness measures; they did show low but significant correlations with driver inattention measures. A regression analysis suggested that the specific measure of driver inattention is a predictor of driving performance, but the more general measures are not. These results are relevant to the assessment of psychological variables associated with driving performance.

Self-Regulation of Driving Behavior in People with Parkinson Disease.

To determine the extent and nature of driving self-regulation in drivers with Parkinson disease (PD) and factors associated with self-regulatory practices. Although people with PD have consistently been shown to have driving impairments, few studies have examined self-regulatory driving practices and their relationship to driving performance. We used a self-report driving questionnaire to examine driving self-regulation in 37 drivers with PD and 37 healthy age-matched controls. We also analyzed factors associated with self-regulatory practices, primarily demographic, disease-related, psychological, and simulated driving performance variables. The drivers with PD reported significantly higher rates of self-perceived decline in their driving ability (P=0.008) and driving significantly shorter distances per week (P=0.004) than controls. Unfamiliar situations (P=0.009), in-car distractions (P<0.001), low visibility conditions (P=0.004), and long journeys (P=0.003) were particularly challenging for the drivers with PD, and their pattern of driving avoidance mirrored these difficulties. The use of self-regulatory strategies among drivers with PD was associated with female sex (rho=0.42, P=0.009) and perceived decline in driving ability (rho=-0.55, P<0.001), but not with age or objective measures of disease severity, cognition, or simulated driving performance. Drivers with PD reported driving less overall and restricting their driving to avoid particularly difficult circumstances. Further research is warranted on effective use of self-regulation strategies to improve driving performance in people with PD.

Effect of drowsiness on driving performance variables of commercial vehicle drivers

Driver drowsiness is a major safety concern, especially among commercial vehicle drivers, and is responsible for thousands of accidents and numerous fatalities every year. The design of a drowsiness detection system is based on identifying suitable driver-related and/or vehicle-related variables that are correlated to the driver’s level of drowsiness. Among different candidates, vehicle control variables seem to be more promising since they are unobtrusive, easy to implement, and cost effective. This paper focuses on in-depth analysis of different driver-vehicle control variables, e.g., steering angle, lane keeping, etc. that are correlated with the level of drowsiness. The goal is to find relationships and to characterize the effect of a driver’s drowsiness on measurable vehicle or driving variables and set up a framework for developing a drowsiness detection system. Several commercial drivers were tested in a simulated environment and different variables were recorded. This study shows that drowsiness has a major impact on lane keeping and steering control behavior. The correlation of the number and type of accidents with the level of drowsiness was also examined. Significant patterns in lateral position variations and steering corrections were observed, and two phases of drowsiness-related degradation in steering control were identified. The two steering degradation phases examined are suitable features for use in drowsiness detection systems.

Crash dieting: The effects of eating and drinking on driving performance

Previous research suggests that compared to mobile phone use, eating and drinking while driving is more common and is seen as lower risk by drivers. Nevertheless, snacking at the wheel can affect vehicle control to a similar extent as using a hands-free phone, and is actually a causal factor in more crashes. So far, though, there has not been a controlled empirical study of this problem. In an effort to fill this gap in the literature, we used the Brunel University Driving Simulator to test participants on a typical urban scenario. At designated points on the drive, which coincided with instructions to eat or drink, a critical incident was simulated by programming a pedestrian to walk in front of the car. Whilst the driving performance variables measured were relatively unaffected by eating and drinking, perceived driver workload was significantly higher and there were more crashes in the critical incident when compared to driving normally. Despite some methodological limitations of the study, when taken together with previous research, the evidence suggests that the physical demands of eating and drinking while driving can increase the risk of a crash.

Pilot Test of Fatigue Management Technologies

This study involved over-the-road testing of four fatigue management technologies (FMTs) in trucking operations in Canada and the United States. Technologies bundled into a single intervention came from four fatigue management domains: one providing objective information on driver sleep need, one providing objective information on driver drowsiness, one providing objective information on lane tracking performance, and one reducing the work involved in controlling vehicle stability while driving. The objective was to determine driver reactions to such technologies and whether FMT feedback would improve alertness, especially during night driving, or increase sleep time on workdays or nonworkdays. A within-subjects crossover design was used to compare the effects of FMT feedback to no feedback. Each driver underwent the conditions in the same order: 2 weeks of no feedback (control) followed by 2 weeks of FMT feedback (intervention). Data from the devices and other driving performance variables were recorded every second of truck operation for 28 days for each driver, with a resulting 8.7 million data records among the 38 drivers. Support was found for FMT effects. During night driving, FMT feedback significantly reduced driver drowsiness (p = 0.004) and lane tracking variability (p = 0.007). However, there was evidence from probed psychomotor vigilance task testing that these improvements may have had cost because of the effort (in attention and compensatory behaviors) required to respond to information from the devices. In general, participants agreed that commercial drivers would benefit from FMT and were more positive about those involving vehicle monitoring than those involving driver monitoring.

Pilot Test of Fatigue Management Technologies

This study involved over-the-road testing of four fatigue management technologies (FMTs) in trucking operations in Canada and the United States. Technologies bundled into a single intervention came from four fatigue management domains: one providing objective information on driver sleep need, one providing objective information on driver drowsiness, one providing objective information on lane tracking performance, and one reducing the work involved in controlling vehicle stability while driving. The objective was to determine driver reactions to such technologies and whether FMT feedback would improve alertness, especially during night driving, or increase sleep time on workdays or nonworkdays. A within-subjects crossover design was used to compare the effects of FMT feedback to no feedback. Each driver underwent the conditions in the same order: 2 weeks of no feedback (control) followed by 2 weeks of FMT feedback (intervention). Data from the devices and other driving performance variables were recorded ...