Driving after marijuana use among U.S. adolescents: Prevalence profiles and related behaviors

OBJECTIVES

The interplay between marijuana legislation, perceptions of risks associated with marijuana use, and marijuana-related risk behaviors is an ever changing and complex issue. Marijuana impaired driving is of concern as legalization continues to expand in the United States. While driving after using marijuana has been shown to be prevalent among adults, little research has examined the behavior in adolescents. The aim of the present study was to examine the prevalence of driving after using marijuana among U.S. adolescents, with an examination of the relationship to age of marijuana initiation and marijuana usage patterns.

METHODS

We analyzed data from the 2017 Youth Risk Behavior Survey, a nationally representative sample of high schools students in the U.S. The sample was current marijuana users, defined as past 30 day use. Driving after using marijuana was the main outcome variable, with analyses examining the association between the outcome and age of initiation and patterns of use. Prevalence ratios were obtained by modeling Poisson regression to examine factors associated with driving under the influence of marijuana.

RESULTS

Nearly half of all marijuana users reported driving after use during the past 30 days, and did not differ between males and females. Prevalence of driving after using marijuana was significantly higher among heavy users (PR = 2.8; 95% CI 2.1-3.6). A higher prevalence of driving after drinking alcohol (PR = 1.7; 95% CI 1.5-1.9) was also found among those who had driven after using marijuana.

CONCLUSIONS

Among adolescent marijuana users, the prevalence of driving after using marijuana was high. Enhanced surveillance, prevention, and control measures are necessary to mitigate the negative impacts of marijuana consumption and related behaviors.

Analysis of drink-driving behavior: Considering the subjective and objective factors of drivers

OBJECTIVE

Drink-driving is one of the key behavioral risk factors in road traffic safety. The main purposes of this study are the identification of the influence of drivers' subjective and objective factors on drink-driving behavior and the correlation between subjective and objective factors to design targeted measures for the prevention and control of drink-driving behavior.

METHODS

To analysis the influence of the subjective and objective factors on the behavior of alcohol value simultaneously. A Bayesian structural equation model is conducted with the data collected via questionnaire issued on the Internet in China.

RESULTS

The results using the Bayesian structural equation model reveals that the subjective factors (e.g., drivers' behavior intention and perceived behavioral control) and objective factors (e.g., age, gender, and driving years of drivers) significantly affect drink-driving behaviors. Drivers' behavior intention is the strongest predictor, and perceived behavioral control also has a significant influence on drink-driving. Drivers who are male, older, lower driving years, driving a motorcycle or car and noncommercial vehicle have a higher probability in drink-driving. The results also suggest that there is a certain correlation between the driver's subjective and objective factors. For instance, male drivers have a more positive attitude toward drink-driving behaviors, drivers over thirty years old more cling to the region's alcohol culture and feel less guilty about drink-driving than youngsters, and truck or bus drivers perceived more disapproval of drink-driving behavior from their significant others.

CONCLUSIONS

A more nuanced understanding of the influence of drivers to drink-driving behavior can be found in these results. These results about the influence mechanism of subjective and objective factors on drink-driving behavior of this study have implications for governments and other interested bodies for better targeting and delivery of public education campaigns and interventions.

Investigating the effects of driving environment and driver characteristics on drivers' compliance with speed limits

OBJECTIVE

Speed compliance of drivers plays a significant role in influencing crash risks, and remains a major road safety issue. Majority of the speed compliance behavioral studies have been conducted in the western world; relatively little knowledge is available about the speed compliance of the drivers of developing nations. The present study aims to investigate the speed compliance behavior of Indian drivers in changing driving environment, and to identify the significant predictors influencing their speed compliance.

METHOD

The driving scenario (consisting of rural and urban driving environments) representing heterogenous Indian driving conditions was designed on a driving simulator where eighty-two licensed drivers completed the driving task. Driver attributes (demographics and driving characteristics) were recorded with the help of a self-reported questionnaire. Speed compliance of drivers was estimated as an indication of the difference of driving speed from the posted speed limit of a particular driving environment, averaged over the duration of driving. The low speed difference indicated better speed compliance of drivers and vice-versa. A Generalized Linear Model (GLM) was developed using speed difference as the dependent variable along with driving environments and driver attributes as predictor variables.

RESULTS

Speed compliance of drivers was found to be better in urban driving environment compared to rural driving environment, indicating that drivers were less able to adapt to the corresponding speed limits in rural environment. Drivers' age was positively associated with the speed compliance. For male drivers, speed compliance was found to be lower than the female drivers. Compared to the drivers who studied till their secondary education, speed compliances of post-graduate and graduate drivers were found to be better. Moreover, driving experience was observed as a negative predictor of speed compliance. Drivers who had prior crash history were found to have better speed compliance compared to the other drivers. Other predictors such as vehicle type and preferred time of driving did not show any significant influence on the speed compliance of drivers.

CONCLUSION

This is the first exploratory study which investigated the speed compliance behavior of Indian drivers. Findings of the present study may assist the road safety strategies and policy interventions in reducing the speed-related crashes.

Driving errors that predict simulated rear-end collisions in drivers with multiple sclerosis

OBJECTIVE

Drivers with Multiple Sclerosis (MS) may have an increased crash risk. However, the driving performance deficits that contribute to crashes are not fully understood. Based on the extant literature, adjustment to stimuli errors indicate failing an on-road assessment. This study examines whether adjustment to stimuli errors can detect the occurrence of collisions in a driving simulator in drivers with MS.

METHODS

As part of a quasi-experiment, 38 participants with MS and 21 participants without MS completed visual-cognitive and driving simulator assessments, which also recorded their adjustment to stimuli maneuvers. We quantified participants' adjustment to stimuli maneuvers via initial pedal reaction time (seconds), time to collision (seconds), mean speed (meters per second), and the occurrence of rear-end collisions (collide vs. did not collide) when a simulated vehicle cut across the lane in front of them.

RESULTS

Logistic regression analyses indicated that, compared to drivers without MS, those with MS had a shorter time to collision (OR= .04, p= .001, 95% CI= [.006, .27]) and a faster mean speed (OR= 1.32, p= .04, 95% CI= [1.01, 1.74]) which increased the odds of experiencing a rear-end collision. Receiver operating characteristic curve analyses indicated that, for MS and control groups, time to collision (MS group = AUC= .94, p<.0001, Control group = AUC= .86, p<.0001) and mean speed (MS group = AUC= .76, p=.005, Control group = AUC = .78, p= .005) differentiated between participants who collided vs. did not collide. For drivers with MS, a time to collision of ≤1.81 seconds (85% sensitivity, 100% specificity, 15% error rate), and a mean speed of ≥7.83 meters per second (77% sensitivity, 76% specificity, 47% error rate) predicted the occurrence of collisions with the lowest error rate.

CONCLUSIONS

During a driving simulator assessment, adjustment to stimuli errors predicted the occurrence of rear-end collisions in drivers with MS (vs. without MS). Driving assessors may target scenarios that measure participants' adjustment to stimuli, via time to collision and mean speed, to make decisions about their visual-cognitive deficits and driving performance.

Safety outcomes for incident responders operating on high speed roads: An analysis of the relationship with behaviour, motivation and role clarity

High-speed roads present a considerable level of risk for frontline workers operating in these environments. To optimise safety, prevention activities need to target the key skills required to mitigate risk. The aim of this research was to explore the behavioural (compliance, participation, voice), motivational (safety motivation) and work demand (role clarity) factors that influence safety outcomes for incident responders working on high-speed roads. Safety outcomes included secondary incidents and near misses with passing vehicles. A total of 295 complete survey responses were received from six emergency service and incident response agencies in one Australian state. Data were analysed using structural equation modelling. The results showed that higher levels of safety voice, safety motivation and, role clarity were significantly associated with safer self-reported safety outcomes after controlling for the number of incidents attended. The findings from this study will be used to guide the development of a training program to improve the cognitive, behavioural and perceptual skills of incident responders operating on high-speed roads. Some insight into the structure and format of this program is provided.

Is organized carpooling safer? Speeding and distracted driving behaviors from a naturalistic driving study in Brazil

Carpooling consists of drivers and passengers sharing a journey and its costs. Nowadays, in the context of mobility as a service, organized carpooling encompasses a service and trust relationship between drivers and passengers, by matching common routes and splitting cost through mobile phone applications. Therefore, passengers expect a certain level of travel quality and safety. In this context, this research aims to verify the hypothesis that drivers in an organized carpooling situation (CP) show safer driving behavior in terms of speeding (SP) and mobile phone use while driving (MPU) in comparison with non-carpooling (NCP) drivers. The research is based on data from the Brazilian Naturalistic Driving Study (NDS-BR) conducted in the City of Curitiba, with 40.45 driving hours and a traveled distance of 895.87 km. Methodology included the selection of safety performance indicators on SP and MPU, use of nonparametric Wilcoxon signed rank test for safety performance indicator comparisons and Pearson Chi-Square to test the association between CP or NCP and low or high indicator values. Hypothesis test results point in the same direction and partially confirm the initial assumption that CP induces safer behavior in terms of speeding. The statistically sound results showed that CP drivers engaged in less speeding episodes and mobile phone use duration in comparison to NCP drivers, as well as lower speed while using a mobile phone. In addition, driver behavior in CP and NCP situations also differed in terms of the type of MPU, with the proportion of types of use that demand a higher level of visual and manual distraction being higher among NCP drivers. In summary, these results confirm the initial hypothesis of safer driving behavior during carpooling in terms of MPU while driving.

A taxonomy of driving errors and violations: Evidence from the naturalistic driving study

Driving errors and violations are identified as contributing factors in most crash events. To examine the role of human factors and improve crash investigations, a systematic taxonomy of driver errors and violations (TDEV) is developed. The TDEV classifies driver errors and violations based on their occurrence during the theoretically based perception-reaction process and analyzes their contributions in safety critical events. To empirically explore errors and violations, made by drivers of instrumented vehicles, in diverse built environments, this study harnesses unique and highly detailed pre-crash sensor data collected in the Naturalistic Driving Study (NDS), containing 673 crashes, 1,331 near-crashes and 7,589 baselines (no-event). Human factors are categorized into recognition errors, decision errors, performance errors, and errors due to the drivers' physical condition or their lack of contextual experience/familiarity, and intentional violations. In the NDS data, built environments (measured by roadway localities) are classified based on roadway functional classification and land uses, e.g., residential areas, school zones, and church zones. Based on the crash percentage to baseline percentage in a specific locality, interstates and open country/open residential (rural and semi-rural settings) may pose lower risks, while urban, business/industrial, and school zone locations showed higher crash risk. Human errors and violations by instrumented vehicle drivers contributed to 93% of the observed crashes, while roadway factors contributed to 17%, vehicle factors contributed in 1%, and 4% of crashes contained unknown factors. The most common human errors were recognition and decision errors, which occurred in 39% and 34% of crashes, respectively. These two error types occurred more frequently (each contributing to nearly 39% of crashes) in business or industrial land use environments (but not in dense urban localities). The findings of this study reveal continued prevalence of human factors in crashes. The distribution of driving errors and violations across different roadway environments can aid in the implementation of driver assistance systems and place-based interventions that can potentially reduce these driving errors and violations.

Long-term effectiveness of the alcohol ignition interlock programme: A retrospective cohort study in the Netherlands

This article provides an evaluation of the long-term effectiveness of the Alcohol Ignition Interlock Programme (AIIP) on recidivism. A retrospective cohort design was used to compare the known reoffending behaviour of 1676 AIIP participants with that of 907 persons in a control group, consisting of offenders who committed an AIIP-worthy driving-under-the-influence (DUI) offence that was not reported to the Dutch driving license authority. Persons in the control group were not sanctioned with an AIIP, but had their case settled in the criminal court. Our outcome measure was the percentage of offenders who committed at least one new DUI offence within the follow-up period. Results indicate that the percentage of repeat offenders in the AIIP group was lower than in the control group. Additional analyses indicate that were an AIIP to be imposed alongside a criminal settlement, a recidivism reduction of 4 percentage points (4 % versus 8 %) could be expected. This would translate to a relative decrease of 54 %. Explanations for these findings are discussed.

Cannabis and crash risk among older drivers

The purpose of this research was to reanalyze data collected from the National Highway Traffic Safety Administration's Drug and Alcohol Crash Risk Study to investigate whether driving under the influence of cannabis (THC-positive) was associated with elevated crash risk for younger and older drivers. The data came from a case-control relative risk study collected from Virginia Beach, VA, over a 20-month period. Data collectors gathered driver information from the scene of vehicle crashes and, in some cases, from hospitals. Non-crash controls were sampled from the same locations, days, and times as crashes. Key data items included driver demographics and oral fluid and blood samples, which were assayed for licit and illicit drugs. We found no overall association between cannabis use and risk of crash involvement. However, when age and age² were allowed to interact with THC, significant interaction effects emerged. THC was associated with increased risk of crash involvement for older drivers. Difference between THC-positive and sober drivers emerged as significant at age 64. The research underscores the value of examining drugged driving in the context of driver age. Age-related declines in neurocognitive and psychomotor functioning were not measured but might be important in explaining the results.

Narrative persuasion and stigma: Using news accounts to denormalize texting while driving

Despite nearly universal texting while driving bans in U.S. states, distracted driving still poses a major risk for American motorists and pedestrians on a daily basis. We argue texting while driving behavior, due to its cultural, social, and psychological motivations, may be addressed by cultivating a stigma to denormalize TWD much in the same way public health campaigns and bans did with tobacco use. While extant strategies may similarly stigmatize this risky behavior, we contend the stigmatizing effect of news narratives offers an untapped and unexamined resource. In this paper we draw on emergent findings in narrative persuasion work to present an exploratory analysis and evidence indicates news narratives, through narrative engagement, can both stigmatize TWD behavior and diminish attitudes toward distracted driving. These initial findings are then validated against an independent sample. If applied widely, this method may be applied to increase social pressure against distracted driving, leading to fewer people engaging in TWD behavior, and making roads safer.

Performance of ground-level signal detection when using a phone while walking

Ground-level traffic lights or safety signs have been introduced recently as a prevention measure for smartphone-related pedestrian accidents. However, quantitative evaluation of smartphone users' detection performance during distracted walking has been scarce. A laboratory experiment was conducted to evaluate the performance of detecting ground-level visual cues during the concurrent use of a smartphone while walking. Thirty-eight young smartphone users performed ground-level visual cue detection trials, 1) while walking upright on a treadmill without using a smartphone; 2) when conducting one-handed browsing while walking; and, 3) when conducting two-handed texting while walking. Visual cues were presented on the ground at 24 locations by a ceiling-mounted projector, and participants were asked to respond verbally when they perceived the appearance of each cue. Study results show that the concurrent use of a smartphone decreased the detection rate significantly (p < 0.05) from 93.5 % to 76.3∼74.1 %, and increased the reaction time from 0.90 s to 1.04∼1.15 s. Among the 24 cue locations, cues that were presented closer to participants were detected significantly (p < 0.05) more often and faster than cues that were shown at further locations. The results of this laboratory-based study imply that the ground-level signals might not be detected well by smartphone users, specifically when they were conducting more demanding tasks such as texting while walking. However, the laboratory conditions were confined to a specific usage environment; therefore, future research should be focused on the situation awareness of smartphone users under various usage scenarios and more realistic environments.

Analysis of Street-Crossing Behavior: Comparing a CAVE Simulator and a Head-Mounted Display among Younger and Older Adults

Interactive pedestrian simulators have become a valuable research tool for investigating street-crossing behavior and developing solutions for improving pedestrian safety. There are two main kinds of pedestrian simulators: one uses a technology based on rear-projection screens (Cave Automatic Virtual Environment, or CAVE), the other a head-mounted display (HMD). These devices are used indiscriminately, regardless of the research objective, and it is not yet known whether they are equally effective for studying street crossing. The present study was aimed at comparing the street crossing behavior and subjective evaluations of younger and older adult pedestrians when they are using a CAVE-like or HMD-based (HTC Vive Pro) pedestrian simulator. Thirty younger adults and 25 older adults performed 36 street-crossing trials (combining different speeds, two-way traffic conditions, and gap sizes) on each of the two types of simulators. The results indicated that participants in the HMD condition crossed the street significantly more often (58.6 %) than in the CAVE condition (42.44%) and had shorter safety margins. The most striking difference pertained to crossing initiation, which occurred considerably earlier (1.78 s) in the HMD condition than in the CAVE condition. Synchronization of crossing initiation with oncoming traffic was not as good in the CAVE condition because visual information in front of the pedestrian was missing due to the absence of ground projection. In both simulators, older adults caused more collisions than did younger ones, had shorter safety margins, and a slower crossing speed. Hence, the HMD reproduced classical age-related differences in most street-crossing behaviors already found on the CAVE. Usually observed speed effects were also found for both simulators. Neither cybersickness nor any adverse effects on stereoacuity or postural balance were found for either simulator. The HMD produced a higher level of presence and preference than the CAVE did. These findings provide evidence that HMDs have a clear potential for studying pedestrian behaviour.

The fatiguing effect of broadband noise: An EEG-based study

Fatigue continues to be identified as one of the primary contribution factors in aircraft and motor vehicle crashes. The aim of the present study was to examine the fatiguing effect of continuous noise, noise that is present in the cabin of a truck, or an aircraft during flight. In pursuit of this aim, a monotonous driving scenario that has previously been shown to induce fatigue was employed, along with broadband noise set at 75dBA. Changes in participants brain wave activity as measured using an Electroencephalography (EEG), along with subjective measures and driving performance were analysed. Forty-five drivers were randomly assigned to one of three experimental groups (ambient noise group at 40 dBA and broadband noise groups at 55 dBA and 75 dBA) and asked to complete a 90 min monotonous drive. Alpha brain wave activity, subjective fatigue response and deteriorating driving performance all indicate the monotonous drive to be fatiguing. Noise effects were evident with theta brain wave activity where the two noise groups (55 dBA and 75 dBA) had higher levels of theta activity than the ambient noise group. However, no interactions for time by noise were evident in any of the recorded brain activity frequency bands, although trends were evident with alpha activity. These results are discussed from both a theoretical and applied perspective.

Suicide by crashing into a heavy vehicle: a focus group study of professional drivers

Professional heavy vehicle drivers can experience a traumatic event at work when suicidal drivers deliberately crash into their vehicles or a pedestrian jumps in front of them. This study adopts a qualitative approach, aiming to gain an understanding about the psychological and other consequences that these crashes have for this occupational group. We organized a semi-structured focus group meeting with six drivers who reported experiencing a deliberate crash into their vehicle. The meeting was moderated by two psychologists. The participants reported that avoiding the crash was difficult. These events can have long-lasting effects on drivers' well-being although individual differences in the response to the event and coping strategies do exist. Participation in our meeting was regarded as a positive experience. This encourages us to believe that organizing similar meetings that allow drivers under the supervision of professionals to share their own experiences with those who experienced similar events, could perhaps be one way of providing support to such drivers who experienced a traumatic event at work.

Car drivers coping with hazardous events in real versus simulated situations: Declarative, behavioral and physiological data used to assess drivers' feeling of presence

More than 1.3 million people lose their lives every year in traffic accidents. Improving road safety requires designing better vehicles and investigating drivers’ abilities more closely. Driving simulators are constantly being used for this purpose, but the question which often arises as to their validity tends to be a barrier to developments in this field. Here we studied the validity of a simulator, defined as how closely users’ behavior under simulated conditions resembles their behavior on the road, based on the concept of drivers’ feeling of presence. For this purpose, the driving behavior, physiological state and declarative data of 41 drivers were tested in the Sherpa2 simulator and in a real vehicle on a track while driving at a constant speed. During each trial, drivers had to cope with an unexpected hazardous event (a one-meter diameter gym ball crossing the road right in front of the vehicle), which occurred twice. During the speed-maintenance task, the simulator showed absolute validity, in terms of the driving and physiological parameters recorded. During the first hazardous event, the physiological parameters showed that the level of arousal (Low Heart Rate/High Heart Rate ratio x10) increased up to the end of the drive. On the other hand, the drivers’ behavioral (braking) responses were 20% more frequent in the simulator than in the real vehicle, and the physiological state parameters showed that stress reactions occurred only in the real vehicle (+5 beats per minute, +2 breaths per minute and the phasic skin conductance increased by 2). In the subjects’ declarative data, several feeling of presence sub-scales were lower under simulated conditions. These results suggest that the validity of motion based simulators for testing drivers coping with hazards needs to be questioned.

Risk to workers or vehicle damage: What makes drivers slow down in work zones?

OBJECTIVE

Speeding in work zones is common and poses significant safety hazards to motorists and workers. Previous studies have demonstrated that speeding is reduced when workers are visible to the drivers, suggesting that concern for the safety of workers influences drivers' speed choice. Conversely, the extent of speeding when workers are not visible suggests that drivers underestimate the increased risk of crashes or other damage to their vehicles associated with the poorer road conditions common at roadworks (loose surfaces and debris, narrower lane width and drop-offs etc.). To better understand the factors influencing drivers' speeds in work zones, this paper examined the extent to which drivers' speed choices are influenced by their perceived likelihoods of injuring workers and damaging their own vehicles.

METHODS

Driver-nominated speeds and perceived likelihoods of worker injury and vehicle damage were collected in an online survey of 405 drivers from Queensland, Australia, by showing photographs of 12 real-world work zones. The data were analyzed using regression techniques to examine the factors influencing driver-nominated speeds and likelihood of speeding.

RESULTS

The results supported the hypothesis that both drivers' perceived likelihood of injuring workers and damaging vehicles strongly influence their nominated speeds (p < 0.001). Young and middle-aged drivers nominated 2.5-6.3 km/h higher speeds than older drivers (p < 0.001). Car drivers who also held truck licenses nominated 4.5 km/h higher speeds (p < 0.001) and 81% higher odds of nominating speeds higher than posted limits (p < 0.001) than car-only licensed drivers. Drivers nominated lower speeds at road curves (12.1 km/h lower speed and 53% lower odds of speeding, p < 0.001), if adjacent areas of travel lanes were unpaved or had loose materials (11.5 km/h lower speed and 66% lower odds, p < 0.001), and when workers were visible in work zones (1.4 km/h lower speed, p = 0.004, and 27% lower odds, p = 0.041).

CONCLUSIONS

In addition to driver demographic and work zone characteristics, drivers' perceptions of safe speeds depend on their perceptions of the likelihood of worker injury and vehicle damage at work zones. These findings suggest that interventions to heighten drivers' perceptions of the likelihood of damage to their vehicles may be useful in moderating speeds at roadworks.

Driving under the influence of drugs or alcohol: Predicting the intentions of young drivers

Objectives: Driving under the influence (DUI) of drugs or alcohol impairs driving performance and, as a result, increases the risk of crashes. The risk of DUI is five-fold higher for young drivers (aged 18-25 years), but little is known about what determines their DUI intentions. This study applied an extended model of the Theory of Planned Behavior (TPB) to address the research question of what factors might influence young drivers' future intentions to DUI. Methods: This study used a survey obtaining data from 329 young drivers (Mage = 20.92 years, SD = 2.16) in Australia. Beyond the standard TPB measures of attitudes, subjective norms and perceived behavioral control (PBC), the current study included demographic variables and additional predictors (i.e., moral norm, peers' norm, perceived risk, impulsivity and past DUI behavior). Results: A vast majority of the participants (85.1%) selected the maximum (9, never), meaning that they had no intention to DUI in the future. Overall, a stepwise multilevel logistic regression analysis (Step 1: demographics, Step 2: TPB measures, and Step 3: additional predictors) explained between 30.1% and 52.9% of the variance in DUI intentions. It showed past DUI behavior as the strongest predictor of DUI intention, followed by instrumental attitude and descriptive norms. Conclusions: This study explored an extended TPB model to understand young drivers' DUI intentions better. With this new knowledge of understanding the factors that influence DUI, researchers and practitioners can create interventions and strategies that are better tailored to the population of young drivers at higher risk.

Comparing driving behavior of humans and autonomous driving in a professional racing simulator

Motorsports have become an excellent playground for testing the limits of technology, machines, and human drivers. This paper presents a study that used a professional racing simulator to compare the behavior of human and autonomous drivers under an aggressive driving scenario. A professional simulator offers a close-to-real emulation of underlying physics and vehicle dynamics, as well as a wealth of clean telemetry data. In the first study, the participants' task was to achieve the fastest lap while keeping the car on the track. We grouped the resulting laps according to the performance (lap-time), defining driving behaviors at various performance levels. An extensive analysis of vehicle control features obtained from telemetry data was performed with the goal of predicting the driving performance and informing an autonomous system. In the second part of the study, a state-of-the-art reinforcement learning (RL) algorithm was trained to control the brake, throttle and steering of the simulated racing car. We investigated how the features used to predict driving performance in humans can be used in autonomous driving. Our study investigates human driving patterns with the goal of finding traces that could improve the performance of RL approaches. Conversely, they can also be applied to training (professional) drivers to improve their racing line.

Studying freeway merging conflicts using virtual reality technology

INTRODUCTION

This research aims to investigate the perceptions and reactions of drivers regarding freeway merging situation, utilizing a new approach with the basis of a multilevel simulation platform which incorporates virtual reality (VR) technology.

METHODS

A VR driving environment integrated with traffic micro-simulation was developed to evaluate driving behaviors and the impact of merging decisions in terms of traffic conflicts. The driving experiments were conducted under a variety of circumstances, including varying traffic flows and the presence of ramp metering. The Surrogate Safety Assessment Model (SSAM) was utilized to extract the number of conflicts from the micro-simulation results.

RESULTS

The final results indicated that the probability of conflict has a positive correlation with traffic flow, while conflict frequency at freeway merges is affected by the presence of ramp metering due to its potentiality to enhance driver decisions and reduce the drivers' pressure when they make maneuvers. Practical Applications: The findings reveal that the proposed VR simulation platform is a useful tool to improve the safety of freeway merging. It has the potential to enhance driver skills and can also be used in the study of human-machine interaction.

Children's fear in traffic and its association with pedestrian decisions

INTRODUCTION

Research on risk for child pedestrian injury risk focuses primarily on cognitive risk factors, but emotional states such as fear may also be relevant to injury risk. The current study examined children's perception of fear in various traffic situations and the relationship between fear perception and pedestrian decisions.

METHOD

150 children aged 6-12-years old made pedestrian decisions using a table-top road model. Their perceived fear in the pedestrian context was assessed.

RESULTS

Children reported greater emotional fear when they faced quicker traffic, shorter distances from approaching traffic, and red rather than green traffic signals. Children who were more fearful made safer pedestrian decisions in more challenging traffic situations. However, when the least risky traffic situation was presented, fear was associated with more errors in children's pedestrian decisions: fearful children failed to cross the street when they could have done so safely. Perception of fear did not vary by child age, although safe pedestrian decisions were more common among the older children.

CONCLUSIONS

Children's emotional fear may predict risk-taking in traffic. When traffic situations are challenging to cross within, fear may appropriately create safer decisions. However, when the traffic situation is less risky, feelings of fear could lead to excessive caution and inefficiency. Practical applications: Child pedestrian safety interventions may benefit by incorporating activities that introduce realistic fear of traffic risks into broader safety lessons.

The effect of attention-deficit/hyperactivity disorder (ADHD) on driving behavior and risk perception

OBJECTIVE

To examine the effect of attention-deficit/hyperactivity disorder (ADHD) on differences in driving behavior and risk perception, in experienced drivers.

METHODS

A total of 147 experienced drivers participated in the study. Drivers with ADHD (n = 91) were compared to an age-matched control group of drivers (n = 56) with no neuropsychiatric diagnoses. A simulator driving test (SDT) was used in the study and included a driving scenario with various traffic environments to examine any differences in number of collisions, number of speedings, risk index (based on 12 risky situations), speed adaptation (based on 19 road sections), mean speed, and preferred speed, between the two groups. The participants also completed a questionnaire about their driving behavior.

RESULTS

No differences in the simulator driving test were found between the ADHD group and the control group. No adverse effects of ADHD were found for any of the measures, i.e., collisions, number of speeding, risk index, speed adaptation, mean speed and preferred speed. The only significant group difference was that drivers with ADHD rated themselves lower on concentration.

CONCLUSIONS

Participants with ADHD and the control group drove remarkably similarly in the simulator driving test and rated themselves similarly regarding how they drive. The results contribute to state that ADHD drivers are less deviant than asserted by previous research.

Associations of mental health with driving while impaired and risky driving in emerging adults

OBJECTIVE

Examined cross-sectional associations of driving while impaired (DWI) and risky driving with mental and psychosomatic health among U.S. emerging adults.

METHODS

Data were from years 1-4 after high school (waves 4-7) of the NEXT Generation Health Study, a nationally representative study starting with 10th grade (2009-2010). Outcome variables were DWI (dichotomous variable: ≥ 1 day vs. 0 days in the last 30 days) and risky driving Checkpoints Self-Reported Risky Driving Scale (C-RDS). Independent variables included depressive symptoms and psychosomatic symptoms. Multivariate logistic and linear regressions were conducted with complex survey features considered.

RESULTS

Higher depressive and psychosomatic symptoms were associated with modestly higher likelihood of DWI (Adjusted odds ratio [AOR] ranged from 1.02 to 1.03 and from 1.04 to 1.05, respectively) and higher C-RDS scores (b ranged from 0.06 to 0.12 and from 0.08 to 0.23, respectively) in years 1-4 after high school.

CONCLUSIONS

Depressive and psychosomatic symptoms were associated with greater DWI and risky driving in all 4 years after high school. Negative mental and psychosomatic health should be targeted components of DWI and risky driving prevention to lower fatal motor vehicle crashes among emerging adults.

Development of the pedestrian anger expression inventory

OBJECTIVE

There has been extensive research into road user behavior, although how pedestrians express their anger has yet to be explored. This is important given the high vulnerability of pedestrians and the additional risks that angry people often undertake. The present study developed a tool to measure one's tendency to engage in aggressive acts while walking: The pedestrian anger expression inventory (PAX).

METHODS

The survey consisted of 37 items adapted from the Driving Anger Expression Inventory as well as a subset of items from the Pedestrian Behavior Questionnaire. Ten items from the Trait Anger Scale (TAS) questionnaire were also used to assess the general anger tendencies of individuals. A total of 475 participants from Tehran provided complete responses to a questionnaire administered via paper and pencil.

RESULTS

A Principal Component Analysis showed a 30-item, 3-factor model describing three ways of expressing anger: 1) Anger Expression-In (internalizing anger), 2) Anger Expression-Out (in the form of aggression), and 3) Adaptive/Constructive Expression (dealing with anger in a constructive way). Hierarchical linear regression showed that trait anger was a significant predictor of pedestrian anger expression, above other demographic variables (age and gender). However, age and gender remained significant predictors of pedestrian anger. As age increased, the tendency to become angry while walking decreased. Male pedestrians were also significantly more likely to express their anger aggressively than female pedestrians.

CONCLUSIONS

In this study, we developed a questionnaire to measure anger expression in pedestrians, highlighting three broad ways pedestrians deal with their anger (internally, externally, or constructively). This questionnaire was used in Iran and therefore, further research is required to validate these tools among different samples and populations.

Physiological indices and driving performance of drivers at tunnel entrances and exits: A simulated driving study

The entrance and exit sections of a tunnel are the accident black-spots in an expressway. For a safe operation of road tunnels, it is necessary to understand a driver's physiological indices and driving performance when driving through tunnels. In this study, the UC-Win/Road simulation software was used to build 12 tunnel models of different lengths. A simulated driving experiment was carried out in a 6-DoF motion platform. The lateral position of vehicles characterizing the driving performance was measured using the motion platform. Electrocardiogram and eye movement data of 25 recruited drivers were collected simultaneously through the experiment. The spatial changes in a driver's heart rate (HR) growth rate, RMSSD, pupil diameter growth rate and vehicle lateral deviation within 300 m before and after the tunnel entrance and exit were analyzed to determine the variation rules in the different tunnels. The study identified the length range in the tunnel entrance and exit sections that influences the drivers. A quantitative analysis was further carried out to analyze the relationship between the physiological indices and the driving performance indicator. The results showed that a driver's heart rate fluctuates significantly 250 m before the tunnel entrance and 50 m before the exit. In this region, the pupil diameter increases gradually, and drivers tend to shift the vehicle to the left. At the tunnel exit, the HR and RMSSD are affected significantly by the tunnel length, and the variation is higher in longer tunnels. In comparison, the tunnel length has no significant effect on the physiological indicators and driving performance of the drivers at the entrance and exit.

Socio-demographic determinants of motorcycle speeding in Maha Sarakham, Thailand

Thailand has the highest road traffic fatality rate in Southeast Asia, making road safety a critical public health concern. A 2015 World Health Organization (WHO) Report showed that speeding behavior was the most important determinant for road traffic crashes in Thailand. Here, we aimed to examine associations of socio-demographic factors (gender, age, socioeconomic status) with self-reported motorcycle speeding behavior. Additionally, we examined a potential role of time discounting and risk preference as mediators in the association of socio-demographic factors with speeding. We used data obtained from the Mahasarakham University Social Network Survey 2018 (MSUSSS) (N = 150). We ran linear network autocorrelation models (lnam) to account for the data's social network structure. We found that males are more likely than females to engage in speeding behavior (β = 0.140, p = 0.001) and to discount the future (β = 5.175, p = 0.017). However, further causal mediation analysis showed that time discounting does not mediate the gender-speeding association (p for mediation = 0.540). Although socioeconomic status (subjective social class) was not associated with speeding (β = 0.039, p = 0.177), age was marginally associated with speeding (β = 0.005, p = 0.093). Future studies may consider using a larger sample.