Perceived effects of cannabis: Generalizability of changes in driving performance.

OBJECTIVE: The objective of this analysis was to determine the generalizability of the relationship between different samples of a driver's perceived state after cannabis use and related performance while operating a motor vehicle. METHODS: Data were collected from 52 subjects in a study examining the effects of cannabis on driving performance. Data were analyzed using the SAS GLM Select procedure, using stepwise selection, with subjective effects, dosing condition (placebo vs. 6.18% delta-9-tetrahydrocannabinol [THC]), and driving context as independent measures. Correlation matrices of measures of driving performance against subjective responses and dosing condition used Pearson's and Spearman's test statistics, respectively. Results were compared to a prior study from a sample of 10 subjects. RESULTS: Subjective perceptions of acute cannabis impairment remain significant predictors of driving performance and explain individual variability in driving performance degradation as well as the data, beyond that which can be explained by acute use of cannabis alone. However, the significant subjective predictors of driving performance differ between the current and prior studies. To better understand these differences, correlations between subjective effects and performance measures were evaluated, which revealed that most correlations matched directionally (e.g., an increase in "good drug effect" was correlated with an increase in standard deviation of lane position [SDLP]). When there was a mismatch, 1 or more correlations were insignificant. Dosing condition and "stoned" were perfectly consistent; "high" and "sedated" contained 1 mismatch; and "anxious," "good drug effect" and "restless" contained 3 or more mismatches. CONCLUSIONS: The results indicate that across both studies, differences in the perceived effects of cannabis are reflected in changes in both lateral and longitudinal control beyond the acute effects of cannabis, which may help explain individual variability in response to acute intoxication. However, the generalizability of these findings is lacking, as shown by inconsistencies in when and where subjective effects were significant. Other factors such as frequency of use, usage type, the evolving profile of a cannabis user, as well as other individual differences should be considered to explain this additional variability.

Mechanisms of cannabis impairment: Implications for modeling driving performance.

Past research on cannabis has been limited in scope to THC potencies lower than legally available and efforts to integrate the effects into models of driving performance have not been attempted to date. The purpose of this systematic review is to understand the implications for modeling driving performance and describe future research needs. The risk of motor vehicle crashes increases 2-fold after smoking marijuana. Driving during acute cannabis intoxication impairs concentration, reaction time, along with a variety of other necessary driving-related skills. Changes to legislation in North America and abroad have led to an increase in cannabis' popularity. This has given rise to more potent strains, with higher THC concentrations than ever before. There is also rising usage of novel ingestion methods other than smoking, such as oral cannabis products (e.g., brownies, infused drinks, candies), vaping, and topicals. The PRISMA guidelines were followed to perform a systematic search of the PubMed database for peer-reviewed literature. Search terms were combined with keywords for driving performance: driving, performance, impairment. Grey literature was also reviewed, including congressional reports, committee reports, and roadside surveys. There is a large discrepancy between the types of cannabis products sold and what is researched. Almost all studies that used inhalation as the mode of ingestion with cannabis that is around 6% THC. This pales in comparison to the more potent strains being sold today which can exceed 20%. Which is to say nothing of extracts, which can contain 60% or more THC. Experimental protocol is another gap in research that needs to be filled. Methodologies that involve naturalistic (real world) driving environments, smoked rather than vaporized cannabis, and non-lab certified products introduce uncontrollable variables. When considering the available literature and the implications of modeling the impacts of cannabis on driving performance, two critical areas emerge that require additional research: The first is the role of cannabis potency. Second is the route of administration. Does the lower peak THC level result in smaller impacts on performance? How long does potential impairment last along the longer time-course associated with different pharmacokinetic profiles. It is critical for modeling efforts to understand the answers to these questions, accurately model the effects on driver performance, and by extension understand the risk to the public.

Simulated and self-reported driving among young adults with and without prenatal cocaine exposure.

Objective: This exploratory study aimed to examine associations between executive function and simulated and self-reported driving behavior among young adults with and without a history of prenatal cocaine exposure (PCE).Methods: Young adult drivers with PCE (n = 38) and with no drug exposure (NDE; n = 25) were recruited from an ongoing longitudinal birth cohort study assessing effects of PCE on development (Mean age = 23.7; 60.3% male; 61.9% with a valid U.S. driver's license, 38.1% report independent driving without a license). Participants completed executive function tasks (i.e., the Stop Signal Task and Groton Maze Learning Task) and self-reported driving measures (i.e., Checkpoints Risky Driving Scale (C-RDS)) outside the cab. Average stop signal reaction time(s) measured inhibitory control, number of exploratory errors measured visuo-spatial working memory, and the total C-RDS score measured self-reported risky driving. Participants completed a high-fidelity driving simulation scenario in a miniSim™ ½ cab National Advanced Driving Simulator (NADS) that yielded indicators of driving performance shown in previous research to correlate with inhibitory control (e.g., average speed, standard deviation lane position (SDLP)) and working memory (minimum headway time, lane departures). Multivariate linear regression models tested whether PCE status, licensure status and executive function measures were associated with simulated driving measures or C-RDS, controlling for sex.Results: Multivariate regression models demonstrated inhibitory control, working memory and PCE group status was not significantly associated with driving outcomes. Licensure was significantly associated with total lane departures (ß = -0.66, SE = 0.19; p < 0.01) and C-RDS (ß = 5.86, SE = 1.4; p ≤ 0.001).Conclusions: This exploratory study suggests that young adults with PCE have similar neurocognitive performance and driving behaviors as their non-drug exposed (NDE) peers. These findings add to the growing literature demonstrating that the effect of PCE on cognitive functions in childhood may not persist to young adulthood. Further research with similar groups of young drivers in a naturalistic driving context (i.e., instrumented vehicles) is needed to more definitively translate and confirm our findings.

Alterations in Electroencephalography Theta as Candidate Biomarkers of Acute Cannabis Intoxication.

The trend toward cannabis legalization in the United States over the past two decades has unsurprisingly been accompanied by an increase in the number of cannabis users and use patterns that potentially pose wider risks to the public like driving under the influence. As such, it is becoming increasingly important to develop methods to accurately quantify cannabis intoxication and its associated impairments on cognitive and motor function. Electroencephalography (EEG) offers a non-invasive method for quantitatively assessing neurophysiological biomarkers of intoxication and impairment with a high degree of temporal resolution. Twelve healthy, young recreational cannabis users completed a series of neurocognitive tasks with concurrent EEG acquisition using the ABM STAT X24 EEG headset in a within-subject counterbalanced design. The 1-h testbed consisted of resting state tasks and tests of attention and memory. Spectral densities were computed for resting state tasks, and event-related potentials (ERPs) were obtained for the attention and memory tasks. Theta band power (3-5 Hz) was decreased during cannabis intoxication compared to placebo during resting state tasks, as were average P400 and late positive potential (LPP) amplitudes during attention and memory tasks. Cannabis intoxication was also associated with elevated frontal coherence and diminished anterior-posterior coherence in the Theta frequency band. This work highlights the utility of EEG to identify and quantify neurophysiological biomarkers from recordings obtained during a short neurocognitive testbed as a method for profiling cannabis intoxication. These biomarkers may prove efficacious in distinguishing intoxicated from non-intoxicated individuals in lab and real-world settings.

Modeling and prediction of driving performance measures based on multi-output convolutional Gaussian process.

Driving performance measures (DPMs) are important indices for driving and personal safety in vehicle operation. The DPMs are collected under various controlled driving conditions to demonstrate different driving behaviors so that mitigating technology interventions can be studied and designed. However, significant costs are involved in the DPM acquisition, and there are a very limited number of controlled driving condition data. Thus, the modeling and prediction of the DPMs under unobserved driving conditions are critical, and many methods have been developed. However, existing literature in this area suffer a common limitation: The interactions among different DPMs are not fully considered (each DPM is modeled individually), although the existence of such interactions is widely reported. This paper proposes a novel DPM modeling and prediction method, i.e., multi-output convolutional Gaussian process (MCGP), that incorporates the interactions among different DPMs. The method features the modeling flexibility for different DPMs and the interpretable modeling structure for integrating the DPM interactions. The method is compared with three benchmark methods on the DPM data set under four different settings, and the results demonstrate the superiorities of the method. Discussions and interpretations of the results are also provided.

Perceived effects of cannabis and changes in driving performance under the influence of cannabis.

OBJECTIVE: Reports indicate that cannabis users will adapt their driving to compensate for the perceived drug effects of cannabis. This analysis examined the relationship between driver perceptions of their state contrasted with objective measures of their performance while operating a motor vehicle. METHODS: Data was collected from ten subjects in a study examining the effects of cannabis on driving performance. Driving performance was collected on the NADS quarter-cab miniSim, a limited field of view non-motion simulator, approximately two hours after cannabis inhalation. Driving measures of both lateral and longitudinal control were included in our analysis. Subjective measures of the effects of cannabis were collected at peak and prior to driving, using visual analog scales. Data were analyzed using the SAS GLM Select procedure with subjective effect, dosing condition (placebo vs 6.9% THC), and driving event as independent measures. The stepwise selection method was used. RESULTS: The analysis of each of the subjective effects showed significant differences between the placebo and the active cannabis dosed conditions. While we found variance in difference between group means, there was greater variability between subject values. We found that subjective measures were predictive of variance in driver inputs, such as steering frequency and steering reversal rate. Variance in SDLP and other driving performance measures, however, were predicted by dosing condition. CONCLUSIONS: Overall, some of the effects perceived by the driver were better related to changes in driver inputs rather than the presence of cannabis itself. Changes in performance measures such as SDLP are better explained by dosing condition. Thus, driver's perceptions may result in changes to driving behavior that could mitigate the effect of cannabis. For both lateral and longitudinal control, an increasing perception of stimulation produced a positive effect on performance. Our results provide a better understanding of how different strains of cannabis, which produce different subjective experiences for users, could impact driving safety. Specifically, we found drug effects that produce more stimulation results in less impact on driving, while those that produce a more stoned or high feeling results in a greater negative effect on driving.

Driver monitoring systems (DMS): The future of impaired driving management?

OBJECTIVE: Driver monitoring systems (DMS) are the next generation of vehicle safety technology. Broadly, these refer to the embedded, aftermarket wearable or vehicle-mounted devices that collect observable information about the operator to make real-time assessment of their capacity to perform the driving task. Integrating biobehavioral monitoring (primarily ocular metrics) with driving performance assessments, these systems function to infer driver state in real time to identify operator conditions that negatively affect driving (such as fatigue, inattention, or distraction). METHOD: We review available methods used to infer driver state, as referenced against accepted models for optimal performance. Modeling our observations on deviation from predetermined performance thresholds used to trigger graded safety alerts, we suggest that many psychoactive substances produce alterations to biobehavioral processes including attentional and motor control, which affect performance indices in a manner already arguably captured by these technologies. RESULTS: Using these existing frameworks, there is considerable potential to similarly catalogue the effect of many common intoxicants known to negatively affect driving ability. This will provide safety-relevant and practical biological models for the development of next-generation multimodal DMS that integrate ocular and physiological variables sensitive to the effects of common and emergent psychoactive substances. CONCLUSION: These devices have tangible potential application across all areas of transportation, including aviation, rail, and all commercial and private vehicle systems.

Consumer experiences of care coordination for people living with chronic conditions and other complex needs: an inclusive and co-produced research study.

Objective The aim of this study was to explore consumer experiences of care coordination within Barwon Health's Hospital Admission Risk Program (HARP) located in Geelong, Victoria. Methods The study design was qualitative description informed by phenomenology and inclusive and co-production methodology. Semi-structured interviews were conducted with a purposive sample of six consumers living with chronic conditions and other complex needs. Participants were asked about their lived experience related to accessing the service, communication, and health and supports before and after accessing the service using an interview guide. Interviews were audio-recorded and transcribed verbatim for thematic analysis. Results Five themes were identified: (1) experiencing authentic, values-based care; (2) collaborative care and working together; (3) gaining independence; (4) improved health and quality of life; and (5) limited understanding of HARP at the start. Overall, participants' experiences were positive, which related to improved health, quality of life, and sustainable supports. Although gains were experienced, most of the participants identified that their knowledge of HARP was limited when services commenced, which is an area for service improvement. Conclusion This research begins to address the knowledge gap related to consumer experiences of care coordination. Findings highlight the importance of providing person-centred, authentic and values-based care, listening authentically, and promoting consumer voice within services. The study demonstrates that inclusive, co-design research is feasible in this service context, and further research is recommended into how stakeholders understand the function of care coordination services to promote health and prevent hospital readmissions, and improve consumer participation. What is known about the topic? Care coordination is multifaceted, with the primary purpose of facilitating person-centred care through appropriate and timely delivery of healthcare services. Despite the effectiveness of care coordination programs in preventing avoidable hospital admissions and reducing hospital length of stay, there is a paucity of research that has investigated consumer perspectives. There is also limited research that has adopted an inclusive research design of knowledge co-production where clinicians and consumers are included as equal members of the research team. What does this paper add? The study findings provide evidence into the value of care coordination from the perspective of consumers living with chronic conditions and other complex health and psychosocial issues. The findings also extend evidence into person- and consumer-centred care through understanding the qualities of care coordination practice that promote authenticity, integrity and positive health outcomes. Listening is identified as a critical element of authentic, values-based care, and as a care coordination intervention. Finally, the study demonstrates that inclusive, co-design research is feasible in this service context, and a larger-scale Experience-Based Co-Design study is recommended to investigate how stakeholders understand the function of care coordination services to promote health and prevent hospital readmissions and improve consumer participation. What are the implications for practitioners? The study informs practitioners of consumer lived experience of care coordination. Practitioners are recommended to apply the findings to practice by adopting an authentic, values-based and person-centred care approach described in the study findings. Service improvement initiatives are recommended to focus on increasing awareness of care coordination services through consumer participation and the meaningful inclusion of consumer voice, which could focus on education for referring health and social care professionals.

Designing for the Extremes: Modeling Drivers' Response Time to Take Back Control From Automation Using Bayesian Quantile Regression.

OBJECTIVE: Understanding the factors that affect drivers' response time in takeover from automation can help guide the design of vehicle systems to aid drivers. Higher quantiles of the response time distribution might indicate a higher risk of an unsuccessful takeover. Therefore, assessments of these systems should consider upper quantiles rather than focusing on the central tendency. BACKGROUND: Drivers' responses to takeover requests can be assessed using the time it takes the driver to take over control. However, all the takeover timing studies that we could find focused on the mean response time. METHOD: A study using an advanced driving simulator evaluated the effect of takeover request timing, event type at the onset of a takeover, and visual demand on drivers' response time. A mixed effects model was fit to the data using Bayesian quantile regression. RESULTS: Takeover request timing, event type that precipitated the takeover, and the visual demand all affect driver response time. These factors affected the 85th percentile differently than the median. This was most evident in the revealed stopped vehicle event and conditions with a longer time budget and scenes with lower visual demand. CONCLUSION: Because the factors affect the quantiles of the distribution differently, a focus on the mean response can misrepresent actual system performance. The 85th percentile is an important performance metric because it reveals factors that contribute to delayed responses and potentially dangerous outcomes, and it also indicates how well the system accommodates differences between drivers.

Alcohol use patterns and their association with sober driver vehicle control in high fidelity driving simulation.

OBJECTIVE: To examine the relationship between patterns of alcohol use, as determined by the Alcohol Use Disorders Identification Test, and vehicle control measures in high fidelity driving simulation among adult sober drivers. METHODS: Baseline data (BAC = 0.00%; N = 108) from a larger study aimed at using high-fidelity driving simulation (National Advanced Driving Simulator) to evaluate the feasibility of vehicle-based sensors to identify alcohol impairment were analyzed. Driving simulation scenarios included driving on urban, interstate, and rural roadways. The independent variable was the pattern of alcohol use measured with the Alcohol Use Disorder Identification Test (AUDIT). Dependent variables included one lateral vehicle control measure (i.e., standard deviation of lane position (SDLP)) and one longitudinal vehicle control measure (i.e., average speed relative to the speed limit) in high fidelity driving simulation. Multivariable linear regression was used to examine the associations between patterns of alcohol use and vehicle control measures. RESULTS: Total AUDIT scores ≥8 was positively associated with SDLP. Increased frequency of drinking was associated with decreased SDLP and increased average speed relative to the speed limit. Increased reports of blackouts and alcohol-related injury were associated with increased average speed relative to the speed limit. Driver performance (SDLP, average speed relative to the speed limit) was related to additional factors such as driver experience, age, marital status, and driving context. CONCLUSIONS: The findings support our hypothesis that the AUDIT score and responses to individual AUDIT questions, among sober drivers, relates to vehicle control measures. Overall, our data highlight two important themes: 1) a need to further integrate alcohol use metrics with high-fidelity driving simulation studies to understand how drinking experience can relate to driver behavior and vehicle control and 2) the opportunity to integrate clinical perspectives with driving simulation research to strengthen clinically oriented alcohol-misuse prevention efforts.

Impact of cannabis and low alcohol concentration on divided attention tasks during driving.

OBJECTIVE: To assess divided-attention performance when driving under the influence of cannabis with and without alcohol. Three divided-attention tasks were performed following administration of placebo, cannabis, and/or alcohol. METHODS: Healthy adult cannabis users participated in 6 sessions, receiving combinations of cannabis (placebo/low-THC/high-THC) and alcohol (placebo/active) in randomized order, separated by washout periods of ≥1 week. At 0.5 hours post-dosing, participants performed simulator drives in the University of Iowa National Advanced Driving Simulator (NADS-1), a full vehicle cab simulator with a 360° horizontal field of view and motion base that provides realistic feedback. Drives contained repeated instances of three tasks: a side-mirror task (reaction to a triangle appearing in the side-mirrors), an artist-search task (select a specified artist from a navigable menu on the vehicle's console), and a message-reading task (read aloud a message displayed on the console). Blood THC and breath alcohol concentration (BrAC) were interpolated using individual power curves from samples collected approximately 0.17, 0.42, 1.4, and 2.3 hours post-dose. Driving measures during tasks were compared to equal-duration control periods occurring just prior to the task. Performance shifts, task completion, and lane departures were modeled relative to blood THC and BrAC using mixed-effects regression models. RESULTS: Each 1 µg/L increase in blood THC concentration predicted increased odds of failing to complete the artist-search task (OR: 1.05, 95% CI: 1.01-1.11, p = 0.046), increased odds of selecting at least one incorrect response (OR: 1.05, 95% CI: 1.00-1.09, p = 0.041), declines in speed during the side-mirror task (0.005 m/s, 95% CI: 0.001-0.009, p = 0.023), and longer lane departure durations during the artist-search task (0.74% of task-period, 95% CI: 0.12-1.36 p = 0.020). BrAC (approximately 0.05%) was not associated with task performance, though each 0.01 g/210 L increase predicted longer departure durations during the side-mirror task (1.41% of task-period, 95% CI: 0.08-2.76, p = 0.040) and increased standard deviation of lane position in the message-reading task (0.61 cm, 95% CI: 0.14-1.08, p = 0.011). CONCLUSIONS: With increasing medical and legal cannabis use, understanding the impact of acute cannabis use on driving performance, including divided-attention, is essential. These data indicate that impaired divided-attention performance is a safety concern.

EEG biomarkers acquired during a short, straight-line simulated drive to predict impairment from cannabis intoxication.

OBJECTIVE: As cannabis use becomes more widely accepted, there is growing interest in its effects on brain function, specifically how it may impact daily functional activities such as driving, operating machinery, and other safety-related tasks. There are currently no validated methods for quantifying impairment from acute cannabis intoxication. The objective of this study was to identify neurophysiological correlates associated with driving simulator performance in subjects who were acutely intoxicated with cannabis. These signatures could help create an EEG-based profile of impairment due to acute cannabis intoxication. METHODS: Each subject completed a three-visit study protocol. Subjects were consented and screened on the first visit. On the second and third visits, subjects were administered either 500 mg of cannabis with 6.7% delta-9-tetrahydrocannabinol (THC) or placebo using a Volcano© Digit Vaporizer in a counterbalanced fashion. EEG was acquired from subjects as they performed a series of neurocognitive tasks and an approximately 45-minute simulated drive that included a rural straight-away absent of any other cars or obstacles during the final 10 minutes.EEG data was acquired using a STAT X24 wireless sensor headset during a simulated driving scenario from 10 subjects during the THC and placebo visits. Metrics of driving performance were extracted from the driving simulator and synchronized with EEG data using a common clock. RESULTS: A within-subjects analysis showed that the standard deviation of lane position (SDLP) was significantly worse and heart rate was elevated during the dosed visit compared to the placebo visit. Consistent with our prior findings, EEG power in the Theta frequency band (4-7 Hz) in the dosed condition was significantly decreased from the placebo condition. Theta power was negatively correlated with the SDLP driving performance metric, while there were no significant correlations between any EEG measure and SDLP in the placebo condition. CONCLUSIONS: These results, in combination with prior work on the effect of cannabis intoxication during neurocognitive tasks, suggest that neurophysiological signatures associated with acute cannabis intoxication are robust and consistent across tasks, and that these signatures are significantly correlated with impaired performance in a driving simulator. Taken together, EEG data acquired during a short neurocognitive testbed and during a simulated drive may provide specific profiles of impairment associated with acute cannabis intoxication. Further research is needed to establish the impaired cognitive processes associated with these EEG biomarkers.

Gaze position modulates the effectiveness of forward collision warnings for drowsy drivers.

Advanced driver assistance systems (ADAS) have the potential to prevent crashes and reduce their severity. Forward collision warnings (FCW) are quickly becoming standard across vehicle lineups and may prevent frontal crashes by alerting drivers. Previous research has demonstrated the effectiveness of FCW for distracted drivers, but their effectiveness for other types of impairment remains unknown. Like distraction, drowsiness can impair driver response time and lead to crashes. The goal of the present study was to evaluate the effectiveness of FCW for moderately and severely drowsy drivers using a high-fidelity driving simulator. Drowsy drivers were divided into three warning conditions during a revealed stop vehicle forward collision event: An auditory alert, a haptic seat vibration, and a no warning baseline. Results indicate that FCW were effective at speeding drowsy driver response, but only when the drowsy drivers were looking away from the forward roadway at the onset of the event. These results have important implications for ADAS technology and driver state monitoring systems.

Evaluating drugged driving: Effects of exemplar pain and anxiety medications.

OBJECTIVE: Distracted and drug-influenced driving presents a major risk for traffic safety morbidity and mortality. As part of an ongoing research program, we examined the effects of a commonly prescribed combination of medications for pain relief: alprazolam, a benzodiazepine, and a hydrocodone preparation, a combination opiate and acetaminophen, on a simulated driving protocol. METHODS: Utilizing a within-subjects design, we recruited 8 healthy experienced drivers without major physical and psychological histories. Using a double-blind, placebo-controlled crossover design, we administered placebo, alprazolam alone, hydrocodone/acetaminophen, and the combination of the 2 drugs in a standardized simulated driving protocol. Measures of lateral and longitudinal control were collected and the data were reduced and statically analyzed. RESULTS: The study observed clear detrimental effects of alprazolam on driving measures of lateral control and longitudinal control. Driving appeared to more aberrant at higher speeds and in rural scenarios. There were no statistical differences between hydrocodone and placebo. A measure of sedation showed that subjects rated alprazolam as more sedating than both hydrocodone and placebo. CONCLUSIONS: The findings suggest that impairing effects of this commonly prescribed combination of pharmacologic agents impact simulated driving performance. Negative changes in driving performance included measures of lateral and longitudinal control, although the deleterious effects on lateral control measures such as standard deviation of lane position (SDLP) were larger and more robust. Although the number of subjects was small, thus making it more difficult to draw conclusions on the narcotic effects, these results suggest that in this combination of central nervous system (CNS)-active drugs the benzodiazepine alprazolam accounted for the majority of impairing drug effects. The effect sizes associated with the hydrocodone preparation ranged from very small to medium. These results have potential implications for prescribing physicians and dispensing pharmacists, traffic safety experts, law enforcement officers, and patients themselves.

A contextual and temporal algorithm for driver drowsiness detection.

This study designs and evaluates a contextual and temporal algorithm for detecting drowsiness-related lane. The algorithm uses steering angle, pedal input, vehicle speed and acceleration as input. Speed and acceleration are used to develop a real-time measure of driving context. These measures are integrated with a Dynamic Bayesian Network that considers the time dependencies in transitions between drowsiness and awake states. The Dynamic Bayesian Network algorithm is validated with data collected from 72 participants driving the National Advanced Driving Simulator. The algorithm has a significantly lower false positive rate than PERCLOS-the current gold standard-and baseline, non-contextual, algorithms under design parameters that prioritize drowsiness detection. Under these parameters, the algorithm reduces false positive rate in highway and rural environments, which are typically problematic for vehicle-based detection algorithms. This algorithm is a promising new approach to driver impairment detection and suggests contextual factors should be considered in subsequent algorithm development processes. It may be combined with comprehensive mitigation methods to improve driving safety.

Effects of alcohol at 0.05% blood alcohol concentration (BAC) on low speed urban driving.

OBJECTIVE: Alcohol-impaired driving presents a continued risk for traffic safety and results in a significant proportion of fatalities on the roadway. We examined how alcohol at a 0.05% blood alcohol concentration (BAC) compares to 0.10% BAC (above the current U.S. legal limit) in terms of impact on driving performance. METHODS: Utilizing a within-subjects design, we recruited 108 healthy experienced drivers who were moderate to heavy drinkers. In a double-blind, placebo-controlled crossover design, we administered placebo and alcohol at the 0.05% and 0.10% BAC levels in a standardized simulated driving protocol. Drives occurred on the descending limb of the blood alcohol curve. This analysis focuses on the urban portion of the drive Results: The study observed clear differences in performance for lateral and longitudinal driving performance and glance behavior. Variability in lane keeping and average speed increased with BAC level, with degraded performance observed at 0.05% BAC. The frequency of lane departures and percentage of time focused on the forward roadway at 0.05% BAC did not differ from placebo but differed from the 0.10% BAC level. CONCLUSIONS: Overall, our results show that there is degraded performance in the urban driving environment and that much of that begins at or below the 0.05% BAC level.

Evaluating driver drowsiness countermeasures.

OBJECTIVE: 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.

Cannabis effects on driving longitudinal control with and without alcohol.

Although evidence suggests cannabis impairs driving, its driving-performance effects are not fully characterized. We aimed to establish cannabis' effects on driving longitudinal control (with and without alcohol, drivers' most common drug combination) relative to psychoactive ∆(9) -tetrahydrocannabinol (THC) blood concentrations. Current occasional (≥1×/last 3 months, ≤3 days per week) cannabis smokers drank placebo or low-dose alcohol, and inhaled 500 mg placebo, low (2.9%), or high (6.7%) THC vaporized cannabis over 10 min ad libitum in separate sessions (within-subject, six conditions). Participants drove (National Advanced Driving Simulator, University of Iowa) simulated drives 0.5-1.3 h post-inhalation. Blood and breath alcohol samples were collected before (0.17 and 0.42 h) and after (1.4 and 2.3 h) driving. We evaluated the mean speed (relative to limit), standard deviation (SD) of speed, percent time spent >10% above/below the speed limit (percent speed high/percent speed low), longitudinal acceleration, and ability to maintain headway relative to a lead vehicle (headway maintenance) against blood THC and breath alcohol concentrations (BrAC). In N=18 completing drivers, THC was associated with a decreased mean speed, increased percent speed low and increased mean following distance during headway maintenance. BrAC was associated with increased SD speed and increased percent speed high, whereas THC was not. Neither was associated with altered longitudinal acceleration. A less-than-additive THC*BrAC interaction was detected in percent speed high (considering only non-zero data and excluding an outlying drive event), suggesting cannabis mitigated drivers' tendency to drive faster with alcohol. Cannabis was associated with slower driving and greater headway, suggesting a possible awareness of impairment and attempt to compensate. Copyright © 2016 John Wiley & Sons, Ltd.

Effect of Blood Collection Time on Measured Δ9-Tetrahydrocannabinol Concentrations: Implications for Driving Interpretation and Drug Policy.

BACKGROUND: In driving-under-the-influence cases, blood typically is collected approximately 1.5-4 h after an incident, with unknown last intake time. This complicates blood Δ(9)-tetrahydrocannabinol (THC) interpretation, owing to rapidly decreasing concentrations immediately after inhalation. We evaluated how decreases in blood THC concentration before collection may affect interpretation of toxicological results. METHODS: Adult cannabis smokers (≥1×/3 months, ≤3 days/week) drank placebo or low-dose alcohol (approximately 0.065% peak breath alcohol concentration) 10 min before inhaling 500 mg placebo, 2.9%, or 6.7% vaporized THC (within-individuals), then took simulated drives 0.5-1.3 h postdose. Blood THC concentrations were determined before and up to 8.3 h postdose (limit of quantification 1 µg/L). RESULTS: In 18 participants, observed Cmax (at 0.17 h) for active (2.9 or 6.7% THC) cannabis were [median (range)] 38.2 µg/L (11.4-137) without alcohol and 47.9 µg/L (13.0-210) with alcohol. THC Cmax concentration decreased 73.5% (3.3%-89.5%) without alcohol and 75.1% (11.5%-85.4%) with alcohol in the first half-hour after active cannabis and 90.3% (76.1%-100%) and 91.3% (53.8%-97.0%), respectively, by 1.4 h postdose. When residual THC (from previous self-administration) was present, concentrations rapidly decreased to preinhalation baselines and fluctuated around them. During-drive THC concentrations previously associated with impairment (≥8.2 µg/L) decreased to median <5 µg/L by 3.3 h postdose and <2 µg/L by 4.8 h postdose; only 1 participant had THC ≥5 µg/L after 3.3 h. CONCLUSIONS: Forensic blood THC concentrations may be lower than common per se cutoffs despite greatly exceeding them while driving. Concentrations during driving cannot be back-extrapolated because of unknown time after intake and interindividual variability in rates of decrease.

Controlled vaporized cannabis, with and without alcohol: subjective effects and oral fluid-blood cannabinoid relationships.

Vaporized cannabis and concurrent cannabis and alcohol intake are commonplace. We evaluated the subjective effects of cannabis, with and without alcohol, relative to blood and oral fluid (OF, advantageous for cannabis exposure screening) cannabinoid concentrations and OF/blood and OF/plasma vaporized-cannabinoid relationships. Healthy adult occasional-to-moderate cannabis smokers received a vaporized placebo or active cannabis (2.9% and 6.7% Δ(9) -tetrahydrocannabinol, THC) with or without oral low-dose alcohol (~0.065g/210L peak breath alcohol concentration [BrAC]) in a within-subjects design. Blood and OF were collected up to 8.3 h post-dose and subjective effects measured at matched time points with visual-analogue scales and 5-point Likert scales. Linear mixed models evaluated subjective effects by THC concentration, BrAC, and interactions. Effects by time point were evaluated by dose-wise analysis of variance (ANOVA). OF versus blood or plasma cannabinoid ratios and correlations were evaluated in paired-positive specimens. Nineteen participants (13 men) completed the study. Blood THC concentration or BrAC significantly associated with subjective effects including 'high', while OF contamination prevented significant OF concentration associations <1.4 h post-dose. Subjective effects persisted through 3.3-4.3 h, with alcohol potentiating the duration of the cannabis effects. Effect-versus-THC concentration and effect-versus-alcohol concentration hystereses were counterclockwise and clockwise, respectively. OF/blood and OF/plasma THC significantly correlated (all Spearman r≥0.71), but variability was high. Vaporized cannabis subjective effects were similar to those previously reported after smoking, with duration extended by concurrent alcohol. Cannabis intake was identified by OF testing, but OF concentration variability limited interpretation. Blood THC concentrations were more consistent across subjects and more accurate at predicting cannabis' subjective effects. Copyright © 2015 John Wiley & Sons, Ltd.