Deviation Of Lateral Position Research Articles

Exploring driving anger-caused impairment of takeover performance among professional taxi drivers during partially automated driving

Partially automated systems are expected to reduce road crashes related to human error, even amongst professional drivers. Consequently, the applications of these systems into the taxi industry would potentially improve transportation safety. However, taxi drivers are prone to experiencing driving anger, which may subsequently affect their takeover performance. In this research, we explored how driving anger emotion affects taxi drivers’ driving performance in various takeover scenarios, namely Mandatory Automation-Initiated transition (MAIT), Mandatory Driver-Initiated transition (MDIT), and Optional Driver-Initiated transition (ODIT). Forty-seven taxi drivers participated in this 2·3 mixed design simulator experiment (between-subjects: anger vs. calmness; within-subjects: MAIT vs. MDIT vs. ODIT). Compared to calmness, driving anger emotion led to a narrower field of attention (e.g., smaller standard deviations of horizontal fixation points position) and worse hazard perception (e.g., longer saccade latency, smaller amplitude of skin conductance responses), which resulted in longer takeover time and inferior vehicle control stability (e.g., higher standard deviations of lateral position) in MAIT and MDIT scenarios. Angry taxi drivers were more likely to deactivate vehicle automation and take over the vehicle in a more aggressive manner (e.g., higher maximal resulting acceleration, refusing to yield to other road users) in ODIT scenarios. The findings will contribute to addressing the safety concerns related to driving anger among professional taxi drivers and promote the widespread acceptance and integration of partially automated systems within the taxi industry.

Driving performance of long-term users of sedating antidepressants and benzodiazepines

Objective Using benzodiazepines and certain antidepressants is associated with an increased risk of motor vehicle crashes due to impaired driving skills. Hence, several countries prohibit people who use these drugs from driving. Traffic regulations for driving under the influence of these drugs are, however, largely based on single-dose studies with healthy participants. The effects of drugs on chronic users may be different because of potential development of tolerance or by adapting behavior. In this study, we test the effects of anti-depressants, hypnotics, or anxiolytics use on driving performance in patients who use these drugs for different durations and compare the effects to healthy controls’ performance. Methods Sixty-six healthy controls and 82 medication users were recruited to perform four drives in a driving simulator. Patients were divided into groups that used anti-depressants, hypnotics, or anxiolytics, for shorter or longer than 3 years (i.e. LT3− or LT3+, respectively). The minimum term of use was 6 months. Driving behavior was measured in terms of longitudinal and lateral control (speed variability and Standard Deviation of Lateral Position: SDLP), brake reaction time, and time headway. Impaired driving performance was defined as performing similar to driving with a Blood Alcohol Concentration of 0.5‰ or higher, determined by means of non-inferiority analyses. Results Reaction time analyses revealed inconclusive findings in all groups. No significant performance differences between matched healthy controls, LT3− (n = 2), and LT3+ (n = 8) anxiolytics users were found. LT3+ antidepressants users (n = 12) did not perform inferior to their matched controls in terms of SDLP. LT3− hypnotics users (n = 6) showed more speed variability than their matched healthy controls, while this effect was not found for the LT3+ group (n = 14): the latter did not perform inferior to the healthy controls. Regarding Time Headway, no conclusions about the LT3− hypnotics group could be drawn, while the LT3+ group did not perform inferior compared to the control group. Conclusions The small number of anxiolytics users prohibits drawing conclusions about clinical relevance. Although many outcomes were inconclusive, there is evidence that some elements of complex driving performance may not be impaired (anymore) after using antidepressants or hypnotics longer than 3 years.

Examining the impact of different LED road stud layouts on driving performance and gaze behaviour at night-time

The risks associated with night-time driving on dimly lit roads are substantial and are attributable to the limitations of human visual abilities. As a result, drivers often struggle to distinguish road geometry from ordinary road markings, thus increasing the likelihood of mistakes. These circumstances contribute to a 60 % higher likelihood of road crashes compared to daytime conditions. To mitigate these risks, active LED road studs, which previous studies have shown to have a positive influence on driving performance, can be used. However, there remains a gap in research regarding the optimal arrangement of these studs along road markings for an improvement in driver behaviour and traffic safety. In this study, we assessed the influence of five different LED road stud layouts (unlit, edge, centre, edge-centre, and lane) during night-time driving on two-lane rural highways with curves of different radii (120, 210, 300, 440 m) and directions (left, right). Following a within subject design, thirty-five participants drove in a simulator along a road track with 8 spiralled curves (4 radii × 2 directions) linked to straights. We monitored the longitudinal (i.e., speed), transversal (i.e., lateral position and standard deviation of lateral position) and gaze behaviours.Our findings indicate that the presence of LED road studs promotes safer driving, by helping drivers to adjust their speed when negotiating curves. Transversal behaviour analysis revealed layout-dependent effects on lateral position. The presence of road studs both at the lane centreline and edge allows drivers to maintain centred trajectories and improve steering control. Gaze behaviour analysis uncovered interesting patterns, demonstrating a strong correlation between road stud layout and the driver's focus on specific road targets. Illuminated markings prompt drivers to concentrate their gaze on distinct points, subsequently altering their transversal behaviour.

Residual effects of medications for sleep disorders on driving performance: A systematic review and network meta-analysis of randomized controlled trials: NMA driving and hypnotics

Sleep medications often carry residual effects potentially affecting driving safety, warranting network meta-analysis (NMA). PubMed/EMBASE/TRID/Clinicaltrials.gov/WHO-ICTRP/WebOfScience were inquired for randomized controlled trials of hypnotic driving studies in persons with insomnia and healthy subjects up to 05/28/2023, considering the vehicle's standard deviation of lateral position - SDLP (Standardized Mean Difference/SMD) and driving impairment rates on the first morning (co-primary outcomes) and endpoint. Risk-of-bias, global/local inconsistencies were measured, and CINeMA was used to assess the confidence in the evidence. Of 4,805 identified records, 26 cross-over RCTs were included in the systematic review, of which 22 entered the NMA, focusing on healthy subjects only. After a single administration, most molecules paralleled the placebo, outperforming zopiclone regarding SDLP. In contrast, ramelteon 8 mg, daridorexant 100 mg, zolpidem 10 mg bedtime, zolpidem middle-of-the-night 10 mg and 20 mg, mirtazapine 15–30 mg, and triazolam 0.5 mg performed significantly worse than placebo. Lemborexant 2.5–5 mg, suvorexant 15–20 mg, and zolpidem 3.5 mg middle-of-the-night associated with lower impairment than zopiclone. Repeated administration (maximum follow-up time of ten days) caused fewer residual effects than acute ones, except for flurazepam. Heterogeneity and inconsistency were negligible. Confidence in the evidence was low/very low. Sensitivity analyses confirmed the main analyses. Most FDA-approved hypnotics overlapped placebo at in-label doses, outperforming zopiclone. Repeated administration for 15 days or less reduced residual effects, warranting further research on the matter.

A semi-naturalistic open-label study examining the effect of prescribed medical cannabis use on simulated driving performance.

Despite increasing medical cannabis use, research has yet to establish whether and to what extent products containing delta-9-tetrahydrocannabinol (THC) impact driving performance among patients. Stable doses of prescribed cannabinoid products during long-term treatment may alleviate clinical symptoms affecting cognitive and psychomotor performance. To examine the effects of open-label prescribed medical cannabis use on simulated driving performance among patients. In a semi-naturalistic laboratory study, 40 adults (55% male) aged between 23 and 80 years, consumed their own prescribed medical cannabis product. Driving performance outcomes including standard deviation of lateral position (SDLP), the standard deviation of speed (SDS), mean speed and steering variability were evaluated using the Forum8 driving simulator at baseline (pre-dosing), 2.5 h and 5 -h (post-dosing). Perceived driving effort (PDE) was self-reported after each drive. Oral fluid and whole blood samples were collected at multiple timepoints and analysed for THC via liquid chromatography-mass spectrometry. A significant main effect of time was observed for mean speed (p = 0.014) and PDE (p = 0.020), with patients displaying modest stabilisation of vehicle control, increased adherence to speed limits and reductions in PDE post-dosing, relative to baseline. SDLP (p = 0.015) and PDE (p = 0.043) were elevated for those who consumed oil relative to flower-based products. Detectable THC concentrations were observed in oral fluid at 6-h post-dosing (range = 0-24 ng/mL). This semi-naturalistic study suggests that the consumption of medical cannabis containing THC (1.13-39.18 mg/dose) has a negligible impact on driving performance when used as prescribed.

A Novel Vision- and Radar-Based Line Tracking Assistance System for Drone Transmission Line Inspection

This paper introduces a position controller for drone transmission line inspection (TLI) utilizing the integral sliding mode control (SMC) method. The controller, leveraging GNSS and visual deviation data, exhibits high accuracy and robust anti-interference capabilities. A deviation correction strategy is proposed to capture high-voltage transmission line information more robustly and accurately. Lateral position deviation is calculated using microwave radar data, attitude angle data, and deviation pixels derived from transmission line recognition via MobileNetV3. This approach enables accurate and stable tracking of transmission lines in diverse and complex environments. The proposed inspection scheme is validated in settings with 10-kilovolt and 110-kilovolt transmission lines using a drone with a diagonal wheelbase of 0.275 m. The experimental process is available in the YouTube link provided. The validation results affirm the effectiveness and feasibility of the proposed scheme. Notably, the absence of a high-precision positioning system in the validation platform highlights the scheme’s versatility, indicating applicability to various outdoor visual-based tracking scenarios using drones.

Exploratory` study on driving ability of people with schizophrenia: Relationships among cognitive function, symptoms, and brain activity

BackgroundThis study aimed to examine the relationships among cognitive function, symptoms, prefrontal activation, basic driving skills, and collision risk factors using a hazard prediction task in simulated driving. MethodsParticipants included 42 people with schizophrenia aged 20–50 years who had actual experience of driving. The Trail making test (TMT) A and TMTB, Wechsler Memory Test–Revised (WMS-R), and Zoo Map test (ZMT) were used to evaluate cognitive function. Positive and negative syndrome scale was used to assess symptoms, and brain activity was assessed by evaluating cerebral blood flow during a visual working memory task using functional near-infrared spectroscopy. Driving tasks that tested basic skills, such as brake reaction, steering wheel skills, and standard deviation of lateral position, were analyzed using multiple regression analysis. Three hazard prediction tasks were performed using discriminant analysis. ResultsBrake reaction associated with cerebral blood flow and TMT-A. Steering wheel skills associated with WMS-R, driving experience and depression. Significant differences were found between the collision and noncollision groups in the hazard prediction task, as shown by the ZMT, driving experience, and brake reaction. ConclusionsBrain activity in the frontal lobe during a desk task may be useful data for driving assessment. Assessment of processing speed and learning ability may be particularly important in the evaluation of basic skills for safe driving. In addition, for people with schizophrenia, foresight, as represented by proactive planning, experience, and quick braking may be an essential characteristic to anticipate danger and react quickly enough to avoid collisions.

Interrelatedness of steering and lateral position parameters: Recommendations for the assessment of driving performance

Introduction: Loss of attention leads to less steady driving within the lane and is one of the main causes of road accidents. To improve road safety, vehicle-based parameters such as steering wheel angle and lateral position are used to objectively assess driving performance, especially in monotonous driving tasks. Method: The present driving simulator study investigated the extent to which eight commonly used parameters are independent indicators of driving performance. Fifteen participants undertook a monotonous highway driving task for 1 h. Four steering angle parameters were examined: average steering angle (ASA), standard deviation of steering angle (SDSA), steering angle range (SAR), and steering reversal rate (SRR); as well as four lateral position parameters: mean lateral position (MLP), standard deviation of lateral position (SDLP), lateral position range (LPR), and the out-of-lane duration. Measurements were averaged across 2-minute epochs. Repeated measures correlation analysis evaluated the similarity between each parameter, and the variance inflation factor test evaluated the multicollinearity of all the parameters. Results: The results demonstrated that some parameters are highly correlated and should not be used together to assess driving performance. It is recommended that the optimal combination is ASA and SAR to assess steering angle, and SDLP and out-of-lane to assess lateral position. Out-of-lane, as a factor directly contributing to road safety, is recommended because it has the least correlation with other parameters. Practical Applications: If implemented, these recommendations may improve the assessment of driving performance in future studies.

Predicting changes in driving performance in individuals who use cannabis following acute use based on self-reported readiness to drive

ObjectiveIt is unclear to what extent individuals who use cannabis can accurately assess their ability to drive safely following cannabis use, and lack of understanding as to what factors influence changes in driving performance following cannabis use. This research explores whether self-reported readiness to drive (RTD) and previous experience (PE) using cannabis within 2 h of driving can predict observed changes in driving performance following acute cannabis use. MethodsIndividuals who used cannabis at least monthly completed a baseline simulated drive, were dosed with cannabis of approximately 6.18% THC, then drove at approximately 30-minutes, 90-minutes, and 180-minutes post-dose. Before each drive, participants were asked if they felt safe to drive (on real roadways, not the simulator), a yes/no question (RTD-yes/RTD-no). Venous blood was drawn at baseline and approximately 15-minutes post-dose. Cannabis use history was obtained and included whether the participant had ever driven within 2 h of use (PE-yes/PE-no) and how many days out of the past 30 they had done so (NPD).Drives were segmented into events delineated by changes in the driving environment. Within events, standard deviation of lateral position (SDLP), average speed, and number of lane departures were calculated, and differences from baseline were modeled using mixed-effects regression. Models considered covariates of time, event, and speed, and used RTD-yes/RTD-no, PE-yes/PE-no, NPD, and their interactions as potential predictors. Conditional R2 was used to compare the predictive ability of RTD versus change in Delta-9-THC. Data SourcesData were collected from 30 individuals who use cannabis and included cannabis use patterns, driving behaviors after use, self-reported RTD, measures of driving performance, and cannabinoid blood levels. ResultsRTD-no predicted a 2.60 cm increase in SDLP relative to baseline (95 % CI: 0.43, 4.73, p = 0.018). Average speeds generally decreased relative to baseline, except for RTD-yes with PE-yes (+1.08 mph, 95 % CI: 0.05, 2.11). NPD predicted increased speed among RTD-yes (+0.11 mph per additional day, 95 % CI: 0.01, 0.22) and decreased speed among RTD-no (-0.06 mph per additional day, 95 % CI: −0.18, 0.32). The difference in these effects was statistically significant (p = 0.038). RTD, PE, and NPD were not significant predictors of changes in number of lane departures. For all outcomes, models using RTD achieved higher conditional R2 than models that replaced this variable with change in Delta-9-THC. Differences were most prominent when modeling change in speed with NPD (R2=0.544 with RTD vs. R2=0.481 with change in Delta-9-THC). Significance of ResultsThese results suggest individuals who use cannabis can somewhat self-identify when they are likely to exhibit greater degraded lateral control, although RTD does not fully explain observed degradation in performance.Past research suggests drivers may reduce speed to compensate for recognized impairment following acute cannabis use. Our findings suggest this to be true for those who reported never having previously driven within 2 h of cannabis use or reported RTD-no, but not for those who had previously driven within 2 h of cannabis use and reported RTD-yes. This indicates compensatory behavior is not uniform and helps focus public health outreach efforts.

Sleepless on the road: Are mothers of infants with insomnia at risk for impaired driving?

Infant sleep problems have been associated with a myriad of adverse child and parent outcomes, yet whether these problems may pose a risk for parents on the road has received little research attention. This study sought to test whether mothers of infants with insomnia are at an elevated risk for vehicular crashes, by comparing their objectively measured driving performance with that of mothers of well-sleeping infants and with that of women without children. Fifty-four women from these three groups completed a simulated driving task. Outcome measures included standard deviation of lateral position, number of lane crossings, standard deviation of speed, average speed and maximum speed. Women additionally reported on their driving behaviour using the Driving Behaviour Questionnaire, and on sleep, sleepiness and insomnia symptoms using 7-day sleep diaries and questionnaires. Mothers of infants with insomnia demonstrated greater lane deviation (Wald = 9.53, p = 0.009), higher maximum speed (Wald = 6.10, p = 0.04) and poorer self-rated driving behaviour (Wald = 7.44, p = 0.02) compared with control groups. Analyses also indicated that driving performance in mothers of infants with insomnia tended to be poorer relative to control groups with the progression of time on task. While further research is needed to assess the scope of these effects, our findings suggest that parents, healthcare providers and policymakers should be aware of the potential consequences of infant sleep problems on road safety, and collaborate to establish strategies to mitigate these risks.

Driving performance acutely after mTBI among young drivers

ObjectiveMild traumatic brain injury (mTBI) can impair executive function, learning, and memory, which can negatively impact driving ability. However, little is known how the driving performance of young drivers may be impacted acutely after mTBI. This study aimed to evaluate simulated driving within 96 h of mTBI among young drivers as compared to matched healthy controls, and assess the effects of increased cognitive load on driving performance. MethodsInjured young drivers ages 16 to 24 with physician-confirmed mTBI were enrolled from two sites (University of Alabama at Birmingham and Ohio State University) and completed the assessment on a high-fidelity driving simulator within 96 h of injury. Matched healthy controls were young drivers without mTBIs matched with an index mTBI by age, sex, athlete status, and driving experience. Participants drove four scenarios in a 2x2 design: with/without cognitive load and with/without critical events. Linear mixed models were used to compare the driving outcomes between mTBI drivers and healthy controls. ResultsA total of 38 participants were included, with 25 cases and 13 controls. Standard deviation of lateral position, following distance and reaction time were analyzed. The preliminary findings indicated that mTBI drivers tended to maintain more distance to the car in front of them than healthy controls. High cognitive load was associated with slower reaction time regardless of TBI status. ConclusionsThis study is the first to assess simulated driving performance among young drivers with mTBI acutely post-injury. The findings will have important clinical implications on when young drivers may return to driver post-mTBI and at what conditions. Additional research is warranted to confirm these results.

Skin temperature as a predictor of on-the-road driving performance in people with central disorders of hypersomnolence.

Excessive daytime sleepiness is the core symptom of central disorders of hypersomnolence (CDH) and can directly impair driving performance. Sleepiness is reflected in relative alterations in distal and proximal skin temperature. Therefore, we examined the predictive value of skin temperature on driving performance. Distal and proximal skin temperature and their gradient (DPG) were continuously measured in 44 participants with narcolepsy type 1, narcolepsy type 2 or idiopathic hypersomnia during a standardised 1-h driving test. Driving performance was defined as the standard deviation of lateral position (SDLP) per 5 km segment (equivalent to 3 min of driving). Distal and proximal skin temperature and DPG measurements were averaged over each segment and changes over segments were calculated. Mixed-effect model analyses showed a strong, quadratic association between proximal skin temperature and SDLP (p < 0.001) and a linear association between DPG and SDLP (p < 0.021). Proximal skin temperature changes over 3 to 15 min were predictive for SDLP. Moreover, SDLP increased over time (0.34 cm/segment, p < 0.001) and was higher in men than in women (3.50 cm, p = 0.012). We conclude that proximal skin temperature is a promising predictor for real-time assessment of driving performance in people with CDH.

Longitudinal Assessment of Postconcussion Driving: Evidence of Acute Driving Impairment.

Current medical practices and recommendations largely ignore the safety of postconcussion driving, even though commonly used measures of neurocognition, balance, and vestibulo-ocular function show impairment. To compare simulated driving between patients with concussion and controls throughout concussion recovery using a case-control design. Cohort study; Level of evidence, 2. A total of 26 concussed and 23 control Division I collegiate athletes completed a driving simulation assessment at 3 time points (within 72 hours, asymptomatic, and return to sport). Cumulative driving simulation outcome variables included total number of collisions, speed exceedances, stop signs missed, lane excursions, total drive time, percentage of time over the speed limit, and percentage of time out of the lane. The mean speed, standard deviation of speed (SDS), lateral lane position, and standard deviation of lateral lane position (SDLP) were examined for each of the 11 drive segments. Outcomes were compared using generalized linear mixed models with random intercepts by participant with Poisson or normal distributions. Within 72 hours of injury, the concussion group committed more lane excursions (median difference, 2; P = .003), exhibited greater SDS while avoiding a child pedestrian crossing the road (Cohen d = 0.73; P = .011), drove ~7 inches (~18 cm) closer to the centerline during a residential left curve (d = 0.90; P = .015), and had greater SDLP while navigating around a car crash compared with controls (d = 0.72; P = .016). When asymptomatic, the concussion group committed fewer speed exceedances (median difference, 2; P = .002) and had lower SDLP while navigating through a traffic light compared with controls (d = 0.60; P = .045). No differences were evident at return to sport. Groups did not differ in total collisions at any time point. The concussion group showed more impaired driving patterns within 72 hours of injury, drove more conservatively once asymptomatic, and had similar driving performance at the time they returned fully to sport. Clinicians should consider these findings when discussing driving with patients acutely after concussion. Further research is needed to determine whether on-road collision risk is elevated after concussion.

How Does an Extra-Long Freeway Tunnel Influence Driving Performance? A Comparative Study of Driving Simulation

Extra-long tunnels have adverse effects on driving performance since drivers will be affected by the enclosed, dimly lit, and monotonous environment for a longer time. In the context of the increasing number of extra-long tunnels, this study aims to investigate the effects of extra-long freeway tunnels with a length of 20 km on driving performance using driving simulation tests. Factors including the tunnel environment, driving time, traffic flow, and gender were considered as influencing factors. Performance indicators including the brake reaction time, standard deviation of driving speed, and standard deviation of lateral position were collected. A total of 60 drivers were recruited for the driving simulation study, and the relationships between the driving performance indicators and influencing factors were analyzed by establishing linear mixed models with random intercept. The results demonstrate that driving performance significantly degraded after 5 – 6 min of driving in the extra-long tunnel although drivers were more cautious and presented a better performance when just entering the tunnel. Moderately higher traffic flow could improve driving performance in the extra-long tunnel but not on the open road. Meanwhile, female drivers had better lateral and longitudinal stability in the extra-long tunnel, while no significant difference was witnessed in reaction ability and driving performance on the open road.

Agricultural machinery photoelectric automatic navigation control system based on back propagation neural network

So as to study the influence of speed factors on the stability of tractor automatic navigation system, combined with neural network control theory, the author proposed a dual-objective joint sliding mode control method based on lateral position deviation and heading angle deviation, using back propagation neural network to establish two-wheel tractor-path dynamics model and straight-line path tracking deviation model, the overall system simulation was carried out by using Matlab/Simulink, and the reliability of the control method was verified. The experimental results showed: when the tractor was tracked with the automatic control of linear path under the condition of the variable speed, the maximum deviation of the lateral position deviation was 12.7cm, and the average absolute deviation was kept within 4.88cm; the maximum deviation of the heading angle deviation was 5°, and the average absolute deviation was kept within 2°; the maximum value of the actual rotation angle was 3.13°, and the standard deviation of the fluctuation was within 0.84°. Under the condition of constant speed and variable speed, using the joint sliding mode control method designed by the author, the dual-objective joint control of lateral position deviation and heading angle deviation could be realized, the controlled overshoot was small, the controlled deviation was small after reaching a stable state, and the adaptability to speed factors was strong, which basically could meet the accuracy requirements of farmland operations.

Longitudinal and Lateral Control Strategies for Automatic Lane Change to Avoid Collision in Vehicle High-Speed Driving.

The vehicle particle model was built to compare and analyze the effectiveness of three different collision avoidance methods. The results show that during vehicle high-speed emergency collision avoidance, lane change collision avoidance requires a smaller longitudinal distance than braking collision avoidance and is closer to that with a combination of lane change and braking collision avoidance. Based on the above, a double-layer control strategy is proposed to avoid collision when vehicles change lanes at high speed. The quintic polynomial is chosen as the reference path after comparing and analyzing three polynomial reference trajectories. The multiobjective optimized model predictive control is used to track the lateral displacement, and the optimization objective is to minimize the lateral position deviation, yaw rate tracking deviation, and control increment. The lower longitudinal speed tracking control strategy is to control the vehicle drive system and brake system to track the expected speed. Finally, the lane changing conditions and other speed conditions of the vehicle at 120 km/h are verified. The results show that the control strategy can track the longitudinal and lateral trajectories well and achieve effective lane change and collision avoidance.

Preliminary study of the interactive effects of THC and ethanol on self-reported ability and simulated driving, subjective effects, and cardiovascular responses.

Drug- and alcohol-related motor vehicle accidents are a leading cause of morbidity and mortality worldwide. Compared to alcohol, less is known about the effects of cannabis on driving and even less about their combined effects. To characterize the combined and separate effects of ethanol and tetrahydrocannabinol (THC) on perceived ability to drive, subjective effects, and simulated driving. In a within-subject (crossover), randomized, placebo-controlled, double-blind, 2 × 2 design, the effects of oral THC (10mg [dronabinol] or placebo) and low-dose intravenous ethanol (clamped at BAC 0.04% or placebo) on perceived ability to drive, simulated driving (standard deviation of lateral position [SDLP]), subjective effects (e.g., "high"), and physiological effects (e.g., heart rate) were studied in healthy humans (n = 18). Subjects reported reductions in perceived ability to drive (THC < ethanol < combination) which persisted for ~ 6h (placebo = ethanol, THC < combination). Ethanol and THC produced synergistic effects on heart rate, significant differences compared to either drug alone on perceived ability to drive and feeling states of intoxication (e.g., high), as well increases in SDLP compared to placebo. Perceived ability to drive is reduced under the influence of THC against the backdrop of blood alcohol levels that are below the legal limit. People should be aware that the effects of oral THC on driving may persist for up to six hours from administration. Findings are relevant to the increasingly common practice of combining alcohol and cannabinoids and the effects on driving.

Round-trip driving effects on driving performances and mental workload under different traffic rules

This study investigates the effect of switching between different traffic rules (left-versus right-hand traffic) on driving performance and mental workload. A driving simulation environment was developed according to the real environment. Two urban roads with different traffic systems were simulated. Twenty participants executed intersection turns and continuous car-following behavior in four simulated driving stages, including driving with familiar, unfamiliar, second time unfamiliar, and back to familiar traffic rules. The mean and standard deviations for speed, distance headway, and the standard deviation of lateral position were recorded as driving performance. Mental workload was determined using the NASA-TLX and Rating Scale Mental Effort questionnaires. One-way analysis of variance was used to evaluate the differences between the four driving stages using subjective and objective measures. The results showed that significant differences were obtained in all measures when driving in the four driving situations, except for the speed standard deviation. The car-following behavior was the most unsafe (significantly larger standard deviations for distance headway and mental workload) when driving in unfamiliar road traffic compared with the other stages. When driving under unfamiliar traffic rules for the second time, the mental workload was significantly relieved and the lane-keeping ability significantly improved. The results indicated that providing an adaptive runway for drivers to familiarize themselves with different traffic rules is necessary to improve driving performance and safety. These findings provide useful information for designing bridges linking two places with different traffic rules to increase traffic safety.

The Effect of Partial Sleep Deprivation and Time-on-Task on Young Drivers’ Subjective and Objective Sleepiness

Despite sleepiness being considered one of the main factors contributing to road crashes, and even though extensive efforts have been made in the identification of techniques able to detect it, the assessment of fitness-to-drive regarding driving fatigue and sleepiness is still an open issue. In the literature on driver sleepiness, both vehicle-based measures and behavioral measures are used. Concerning the former, the one considered more reliable is the Standard Deviation of Lateral Position (SDLP) while the PERcent of eye CLOSure over a defined period of time (PERCLOS) seems to be the most informative behavioral measure. In the present study, using a within-subject design, we assessed the effect of a single night of partial sleep deprivation (PSD, less than 5 h sleeping time) compared to a control condition (full night of sleep, 8 h sleeping time) on SDLP and PERCLOS, in young adults driving in a dynamic car simulator. Results show that time-on-task and PSD affect both subjective and objective sleepiness measures. Moreover, our data confirm that both objective and subjective sleepiness increase through a monotonous driving scenario. Considering that SDLP and PERCLOS were often used separately in studies on driver sleepiness and fatigue detection, the present results have potential implications for fitness-to-drive assessment in that they provide useful information allowing to combine the advantages of the two measures for drowsiness detection while driving.

The Utility of THC Cutoff Levels in Blood and Saliva for Detection of Impaired Driving.

Background: Δ9-Tetrahydrocannabinol (THC) is the psychoactive component in cannabis and a relationship of THC to driving impairment is expected. Despite this, there are discrepant findings with respect to the relationship of blood THC to driving. This study investigated the relationship of blood, urine, and saliva THC/THC-COOH levels to "weaving," as measured by a driving simulator. Methods: Participants smoked cannabis alone or with alcohol. THC/THC-COOH levels in blood, urine, and saliva were correlated with standard deviation of lateral position (SDLP), measuring "weaving." In addition, SDLP after cannabis and/or alcohol were compared with SDLP after placebo when THC/THC-COOH levels were above or below specified thresholds in blood (5 ng/mL), urine (50 ng/mL), or saliva (25 ng/mL). Results: A clear linear relationship between blood THC concentration and SDLP was not observed based on calculation of Spearman coefficients. When compared with placebo, SDLP was significantly increased after cannabis and cannabis combined with alcohol when THC in the blood was above the legal limit. SDLP was increased in drug conditions when saliva cutoffs were above the legal limit. Conclusions: The findings of this study suggest that specified thresholds for THC in blood and saliva may be able to detect driving impairment, but future studies are needed. ClinicalTrials.gov ID: NCT03106363.