Impact of mobile phone use on car-following behaviour of young drivers

Individual differences, ADHD diagnosis, and driving performance: effects of traffic density and distraction type

The present study examined the impact of individual differences, attention, and memory deficits on distracted driving. Drivers with ADHD are more susceptible to distraction which results in more frequent collisions, violations, and licence suspensions. Consequently, the present investigation had 36 participants complete preliminary questionnaires, memory tasks, workload indices, and four, 4-min simulated driving scenarios to evaluate such impact. It was hypothesised ADHD diagnosis, type of cellular distraction, and traffic density would each differentially and substantively impact driving performance. Results indicated traffic density and distraction type significantly affected the objective driving facets measured, as well as subjective and secondary task performance. ADHD diagnosis directly impacted secondary task performance. Results further showed significant interactions between distraction type and traffic density on both brake pressure and steering wheel angle negatively impacting lateral and horizontal vehicle control. Altogether, these findings provide substantial empirical evidence for the deleterious effect of cellphone use on driving performance.Practitioner summary: This study examined how ADHD diagnosis, traffic density, and distraction type affect driver behaviour. Participants completed driving behaviour questionnaires, memory tasks, workload indices, and driving scenarios. Results showed that ADHD diagnosis impacted secondary task performance, while traffic and distractions significantly impacted driving performance as well secondary task performance and workload.

Evaluation of the visual-manual resources required to perform calling and navigation tasks in conventional mode with a portable phone and in full- touch mode with an embedded system

This study investigates the differences in a driver's visual-manual behaviour when performing secondary tasks while driving under the full-touch mode (FTM) and the conventional mode (CM). To this end, 30 participants were recruited to perform secondary tasks while driving two vehicles equipped with different HMI system interaction modes. The results show that compared to the CM, in the FTM, fewer visual-manual resources are required to perform the calling task, but for the navigation task, this requirement is higher. Additionally, in both modes, the driver exhibited self-regulation visual-manual behaviour when performing secondary tasks as the driving speed increased. However, the effect of the driving speed on visual-manual behaviour was greater in the FTM than in the CM. The main limitation of this study is that the effect of the difference between the two experimental vehicles on the findings was not considered, however, this does not affect the generalisation of the findings. Practitioner summary: Potential applications of this study include improving drivers' knowledge about the effect of performing secondary tasks in different modes on driving safety, and this study also provides useful insights human-machine co-driving systems to develop user-friendly control strategies and for automotive companies to improve the full-touch interactive mode for automotive companies.

Modelling braking behaviour of distracted young drivers in car-following interactions: A grouped random parameters duration model with heterogeneity-in-means

Braking is an important characteristic of driving behaviour that has a direct relationship with rear-end collisions in a car-following task. Braking becomes more crucial when drivers' cognitive workload increases because of using mobile phones whilst driving. This study, therefore, investigates and compares the effects of using mobile phones whilst driving on braking behaviour. Thirty-two young licenced drivers, evenly split by gender, faced a safety-critical event, that is, leader's hard braking, in a car-following situation. Each participant drove the CARRS-Q Advanced Driving Simulator and was required to respond to a braking event in the simulated environment in three phone conditions: baseline (no phone conversation), handheld, and hands-free. A random parameters duration modelling approach is employed to (i) model drivers' braking (or deceleration) times using a parametric survival model, (ii) capture unobserved heterogeneity associated with braking times, and (iii) account for repeated experiment design. The model identifies the handheld phone condition as a random parameter whilst vehicle dynamics variables, hands-free phone condition, and driver-specific variables are found as fixed parameters. The model suggests that most distracted drivers (in the handheld condition) reduce their initial speeds more slowly than undistracted drivers, reflecting their delayed initial braking that may lead to abrupt braking to avoid a rear-end collision. Further, another group of distracted drivers exhibits faster braking (in the handheld condition), recognising the risk associated with mobile phone usage and delayed initial braking. Provisional licence holders are found to be slower in reducing their initial speeds than open licence holders, indicating their risk-taking behaviour because of their less experience and more sensitivity to mobile phone distraction. Overall, mobile phone distraction appears to impair the braking behaviour of young drivers, which poses significant safety concerns for traffic streams.

Persistent effects of mobile phone conversation while driving after disconnect: Physiological evidence and driving performance

Cognitive workload has been known as a key factor in traffic accidents, which can be highly increased by talking on the phone while driving. A wide range of studies around the world investigated the effects of mobile phone conversations on driving performance and traffic accidents. But less noticed is the durability of cognitive effects of mobile phone conversations. This study aimed to determine the effects of different types of mobile phone conversations on physiological response and driving performance during and after the conversation. Heart rate, heart rate variability (physiological response), Standard deviation of lane position (SDLP), and the relative distance between two cars (driving performance) of 34 samples (male and female) in the driving simulator were recorded. In this study, three types of conversations (neutral, cognitive, and arousal) were used. Neutral conversation did not pursue specific purpose questions. Cognitive conversations were simple mathematical problem-solving questions and arousal conversations aimed at arousing participant emotions. Each conversation was used as a secondary task in a condition. The study had three conditions; in each condition the participant drove for 15 min. Each condition consisted of 5 min of driving (Background), 5 min of driving and conversation (dual tasks) and 5 min of driving after conversation to trace the effects of the conversation. Vehicle speed was 110 km/h in each of the three conditions using car-following scenario. The results showed that neutral conversations had no significant effects on physiological response. Though, arousal conversations had significant effects on physiological responsiveness and driving performance during conversations, where it was even more significant after disconnection. Therefore, the content of the conversation determines the amount of cognitive load imposed on the driver. Considering the persistence of cognitive effects caused by conversation, the risk of traffic accidents is still high even after disconnection.

Alcohol impairs driver attention and prevents compensatory strategies

While the negative effects of alcohol on driving performance are undisputed, it is unclear how driver attention, eye movements and visual information sampling are affected by alcohol consumption. A simulator study with 35 participants was conducted to investigate whether and how a driver's level of attention is related to self-paced non-driving related task (NDRT)-engagement and tactical aspects of undesirable driver behaviour under increasing levels of breath alcohol concentration (BrAC) up to 1.0 ‰. Increasing BrAC levels lead to more frequent speeding, short time headways and weaving, and higher NDRT engagement. Instantaneous distraction events become more frequent, with more and longer glances to the NDRT, and a general decline in visual attention to the forward roadway. With alcohol, the compensatory behaviour that is typically seen when drivers engage in NDRTs did not appear. These findings support the theory that alcohol reduces the ability to shift attention between multiple tasks. To conclude, the independent reduction in safety margins in combination with impaired attention and an increased willingness to engage in NDRTs is likely the reason behind increased crash risk when driving under the influence of alcohol.

Input modality matters: A comparison of touch, speech, and gesture based in-vehicle interaction

Innovative input devices are being available for in-vehicle information systems (IVISs). While they have the potential to provide enjoyable driving by enabling drivers to perform non-driving related tasks (NDRTs) in more natural ways, the associated distracting effects should be paid with more attention. The purpose of this exploratory study was to compare the effects of three novel input modalities, i.e., touchscreen-based interaction (TBI), speech-based interaction (SBI), and gesture-based interaction (GBI), on driving performance and driver visual behaviors. Moreover, we examined if the influence of different modalities would be moderated by the difficulty level of NDRTs. A total of 36 participants were invited to a simulated driving experiment where they were randomly assigned to one of the four groups (TBI, GBI, SBI or baseline) and completed three driving trials. The results showed that TBI led to the worse driving performance, as indicated by the significantly prolonged reaction time, reduced minimum time-to-collision, and increased variations in both longitudinal and lateral vehicle control. The deteriorated driving performance could be attributed, at least partially, to the intense visual demand induced by looking towards the touchscreen, as indicated by more and longer off-the-road glances. The adverse impacts of GBI were relatively smaller, but it still posed great crash risk by leading to a shorter minimum time-to-collision and less stable vehicle control compared to the baseline. SBI, although not completely equivalent to the baseline group, showed the minimum influence on driving and visual performance. Only very few interaction effects were found, suggesting that the effects of modality were quite robust across different NDRTs. It was concluded that SBI and GBI provided safer alternatives to in-vehicle interaction than TBI.

Analysis of mobile phone use engagement during naturalistic driving through explainable imbalanced machine learning

While driver distraction remains an issue in modernized societies, technological advancements in data collection, storage and analysis provide the means for deeper insights of this complex phenomenon. In this research, factors influencing when driver distraction through mobile phone use occurs during naturalistic driving are investigated. Naturalistic data from a 6-stage, 230-driver experiment are exploited, in which drivers installed a non-intrusive driving recording application in their devices and conducted their trips normally across a 21-month timespan, coupled with corresponding questionnaire data. The various experiment stages involved providing progressively more behavioral feedback to drivers while continuing to record them. Subsequently, supervised Machine Learning XGBoost algorithms were employed to model the contributions of naturalistic driving and questionnaire features to the decision to engage mobile phone use. Mobile phone use percentages were heavily skewed towards zero, therefore imbalanced ML with a minority-oversampling approach in a binary format was employed. To increase the explainability offered by the algorithm, SHAP values were calculated for the informative features. Results indicate that the decision of drivers to use a mobile while driving is governed by a number of complex, non-linear relationships. Total trip distance is the most significant predictor variable by a wide margin, with mean SHAP values of 0.79 towards affecting the model decisions for the probability of mobile phone use of each driver. However, other variables influence the final predictions as well, such as the number of tickets in the last three years (m.SHAP = 0.30), declared mobile phone use (m.SHAP = 0.26), the amount and variety of provided feedback (m.SHAP = 0.17) (i.e. experiment phase number) and family member numbers (m.SHAP = 0.09) decrease the probability of using a mobile phone while driving. Conversely, increases in driver experience (m.SHAP = 0.22), driver age (m.SHAP = 0.11), engine capacity (m.SHAP = 0.11) and total kilometers driven annually (m.SHAP = 0.08) increase the probability of using a mobile phone in naturalistic driving conditions. SHAP dependency plots reveal non-linear effects present in almost all variables. Fuel consumption had a particularly strong non-linear effect, as higher values of this variable lead to both higher and lower probability of drivers using a mobile phone, deviating from the safer average. Legislation, campaigns and enforcement measures can be restructured to take advantage of gains margins in terms of understanding and predicting driver distraction behavior, as explored in the present study.

The effect of different mobile uses on crash frequency among young drivers: application of statistical models and clustering analysis

This study focuses on investigating the use of mobile phones among young drivers by employing an online questionnaire survey data. Ordinal logistic regression model was used for modelling the probabilities of crashes due to different uses of mobile phone while driving. Moreover, binary logistic regression models were used for predicting the probabilities of different uses of mobile phone. Logistic regression models revealed that texting and internet use have the same likelihood of causing crashes. Drivers having prior experience of being fined for mobile phone use, also showed a higher tendency to be involved in 2 crashes. Moreover, these drivers had a higher likelihood of being involved in texting, as compared to other uses of mobile phones. Drivers with more education had a higher tendency for internet use during driving. Drivers who use mobile phone for long periods during driving have a lesser tendency to get involved in texting, internet use or GPS navigation. Moreover, drivers with a previous crash record have less likelihood of being involved in texting. The models of this study can be useful in developing effective road safety measures. Clustering was also applied in this study which reinforced the findings of the statistical analysis and models.

Texting While Driving: A Literature Review on Driving Simulator Studies

Road safety is increasingly threatened by distracted driving. Studies have shown that there is a significantly increased risk for a driver of being involved in a car crash due to visual distractions (not watching the road), manual distractions (hands are off the wheel for other non-driving activities), and cognitive and acoustic distractions (the driver is not focused on the driving task). Driving simulators (DSs) are powerful tools for identifying drivers' responses to different distracting factors in a safe manner. This paper aims to systematically review simulator-based studies to investigate what types of distractions are introduced when using the phone for texting while driving (TWD), what hardware and measures are used to analyze distraction, and what the impact of using mobile devices to read and write messages while driving is on driving performance. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) guidelines. A total of 7151 studies were identified in the database search, of which 67 were included in the review, and they were analyzed in order to respond to four research questions. The main findings revealed that TWD distraction has negative effects on driving performance, affecting drivers' divided attention and concentration, which can lead to potentially life-threatening traffic events. We also provide several recommendations for driving simulators that can ensure high reliability and validity for experiments. This review can serve as a basis for regulators and interested parties to propose restrictions related to using mobile phones in a vehicle and improve road safety.

Evaluating the effects of the route guidance variable message signs on driving behaviors-a driving simulation study

OBJECTIVE

Route guidance variable message signs (VMS) are widely applied in traffic incident management on highways by providing real-time spatiotemporal guidance information. The improper panel of route guidance VMS is likely to diminish the compliance with guidance and induce risky driving behaviors, disrupting the traffic flow or even causing crashes. This article aims to investigate the effects of route guidance VMS on driving behaviors in three aspects, vehicle operation, visual perception, and route choice.

METHODS

A driving simulation study with 32 participants was carried out to investigate the driving performance under four different VMS recognizing conditions: baseline (a typical guide sign) and three route guidance VMS panel schemes.

RESULTS

Significant differences in average speed, speed fluctuation, average acceleration, and fixation proportion were found under various VMS recognition conditions. VMS3 had the least negative effects on vehicle operation and visual perception, and the compliance rate under VMS3 was the highest. The possible reasons are as follows: VMS3 has the simplified highway network structure and highlights the road directions with an eye-catching symbol, which can increase the comprehensibility of the guidance information while driving.

CONCLUSIONS

Drivers need to take multiple actions under high-speed driving conditions while recognizing VMS, including reading the route guidance VMS, remaking route decisions, and operating the vehicle concurrently. Under such circumstances, the improper VMS panel would attract more drivers' attention and induce excessive risk compensatory behaviors, reducing drivers' compliance with guidance and situation awareness, and increasing crash risks. In addition, some VMS related traffic management strategies were proposed to improve safety and mobility of highways and further provide a basis for the formulation of related standards.

How do the type and duration of distraction affect speed selection and crash risk? An evaluation using naturalistic driving data

Distracted driving is among the leading causes of roadway crashes worldwide. However, due to limitations of police-reported crash data, it is often challenging to understand the nature and magnitude of this problem. Distraction has also been shown to affect driver speed selection, which is important as both mean speed and speed variance have substantive impacts on crash risk. This study utilizes naturalistic driving data to investigate the relationship between the engagement in various secondary (non-driving) tasks and driver speed selection under different driving contexts. Separate analyses were conducted for low-speed and high-speed driving environments. Two-way random effects linear regression models were estimated for both speed regimes, while controlling for driver, roadway, and traffic characteristics. The differences were assessed based upon ten types of secondary tasks. In general, engagement in all tasks was found to decrease speeds in high-speed environments while the effects were mixed in low-speed settings. The changes in speeds were much pronounced for secondary tasks that include a combination of visual, manual, and cognitive distractions, such as cell phone use. Among all secondary tasks, an average episode of a driver talking on a handheld cellphone was associated with a 6-mph speed reduction in high-speed environments, but a 3.5-mph increase in low-speed settings. In addition to examining impacts on speed selection, the risk of involvement in crash and near-crash events was also evaluated in consideration of the type and duration of distraction. Interestingly, distractions tended to show similar relationships, in both direction and magnitude, with the risk of involvement in both crash and near-crash events. From a policy standpoint, this study provides further motivation for legislation and other programs aimed at curbing distracted driving.

Talking on the Phone While Driving: A Literature Review on Driving Simulator Studies

Distracted driving is a growing concern around the world and has been the focus of many naturalistic and simulator-based studies. Driving simulators provide excellent practical and theoretical help in studying the driving process, and considerable efforts have been made to prove their validity. This research aimed to review relevant simulator-based studies focused on investigating the effects of the talking-on-the-phone-while-driving distraction on drivers' behavior. This work is a scoping review which followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) guidelines. The search was performed on five databases, covering twenty years of research results. It was focused on finding answers to three research questions that could offer an overview of the main sources of distraction, the research infrastructure, and the measures that were used to analyze and predict the effects of distractions. A number of 4332 studies were identified in the database search, from which 83 were included in the review. The main findings revealed that TPWD distraction negatively affects driving performance, exposing drivers to dangerous traffic situations. Moreover, there is a general understanding that the driver's cognitive, manual, visual, and auditory resources are all involved, to a certain degree, when executing a secondary task while driving.

The use of risk homeostasis theory to reduce smartphone use during low-speed driving

Driving while distracted by smartphones is an unsafe behavior and constitutes a serious worldwide road safety issue. In line with the risk homeostasis theory, during high-speed driving, drivers perceive smartphone usage as an unwarranted risk and in most cases refrain from doing so. During low-speed driving, however, drivers often use their smartphones, as they do not perceive this as inherently unsafe, even though it is. The goal of this study was to examine an intervention, based on the risk homeostasis theory, aimed at decreasing the use of smartphones while driving at low speeds. Thirty-seven young drivers participated in the research group that aimed to alter drivers' risk perceptions, decision making, and behavior. The study also included a control group of 33 young drivers. All of the participants' smartphone usage was monitored using a dedicated application that measured both the number of times drivers touched their smartphone screens while driving and the driving speed each time the screen was touched. The results indicate that drivers in the research group decreased their smartphone usage while driving, unlike the control group drivers who did not alter their behavior. In conclusion, a risk homeostasis-based intervention can decrease dangerous and unsafe driving behavior, even when such behavior is not perceived as significantly dangerous. Furthermore, additional types of risky and unsafe driving behaviors may be decreased using this type of intervention.

Effects of Gesture-Based Interaction on Driving Behavior: A Driving Simulator Study Using the Projection-Based Vehicle-in-the-Loop

OBJECTIVE

We observe the driving performance effects of gesture-based interaction (GBI) versus touch-based interaction (TBI) for in-vehicle information systems (IVISs).

BACKGROUND

As a contributing factor to a number of traffic accidents, driver distraction is a significant problem for traffic safety. More specifically, visual distraction has a strong negative impact on driving performance and risk perception. Thus, the implementation of new interaction systems that use midair gestures to encourage glance-free interactions could reduce visual distraction among drivers.

METHODS

In this experiment, participants drove a projection-based Vehicle-in-the-Loop. The projection-based technology combines a visual simulation with kinesthetic, vestibular, and auditory feedback from a car on a test track. While driving, participants used GBI or TBI to perform IVIS tasks. To investigate driving behavior related to critical driving situations and car-following maneuvers, vehicle data based upon longitudinal and lateral driving were collected.

RESULTS

Participants reacted faster to critical driving situations when using GBI compared to TBI. For drivers using TBI, steering performance decreased and time headway to a preceding vehicle was higher.

CONCLUSION

Gestures provide a safe alternative to in-vehicle interactions. Moreover, GBI has fewer effects on driver distraction than TBI.

APPLICATION

Potential applications of this research include all in-vehicle interaction systems used by drivers.

Mental health and behavioural factors involved in road traffic crashes by young adults: analysis of the Raine Study

BACKGROUND

Road traffic crashes (RTC) are a leading cause of mortality and morbidity in young people. Severe mental health and behavioural conditions increase the likelihood of RTC, as do a range of driving-risk activities.

METHOD

We used data from the Raine Study, a prebirth cohort from Perth, Australia, to assess the relationship between measures of common mental health or behavioural conditions (Child Behavior Checklist Internalising and Externalising scores) at age 17 and subsequent RTC by 27 years, controlling for substance use and driving-risk activities.

RESULTS

By 27 years of age, of 937 participants, 386 (41.2%) reported zero crashes and 551 (58.8%) reported ≥1 crashes. In the baseline Poisson model, increased Externalising scores (eg, aggression and delinquency) were associated with increased RTC (incidence rate ratio (IRR)=1.02, 95% CI 1.01 to 1.02): increased Internalising scores (eg, anxiety and depression) were associated with fewer RTC (IRR=0.99, 95% CI 0.98 to 1.00). In the fully adjusted model, the mental health measures were not significant (Externalising IRR=1.01, 95% CI 0.99 to 1.02: Internalising IRR=0.99, 95% CI 0.99 to 1.00). Risky driver activities, such as falling asleep while driving (IRR=1.34), more frequent use of a hands-free telephone (IRR=1.35) and more frequent hostility towards other drivers (IRR=1.30) increased the rate of RTC.

CONCLUSION

Measures of mental health scores at age 17 were not predictive of subsequent RTC, after adjusting for measures of driving-risk activities. We need to better understand the determinants of externalising and risky driving behaviours if we are to address the increased risk of RTC.

Impact of antiepileptic drugs on simulated driving in patients with epilepsy

OBJECTIVE

Results of observational investigations have demonstrated that the risk of a traffic accident is independent of use of AEDs. However, no reports of driving tests conducted with patients administered AEDs have been presented. This study examined this scenario in a simulated driving setting.

METHODS

Driving performance of 43 patients with epilepsy (PWE) and prescribed an AED, who were licensed to drive and drove regularly (subject group), was assessed, with the results compared to 40 age- and gender-matched healthy volunteers (control group). Daily driving skills associated with a traffic accident were examined using two different tests provided by a driving simulator software package, road-tracking and car-following. Standard deviation of lateral position (SDLP) and distance coefficient of variation (DCV) were determined as primary and exploratory outcomes, respectively.

RESULTS

There was no statistically significant difference for primary outcome shown by SDLP between the subject and control groups (p = 0.906), nor for exploratory outcome shown by DCV (p = 0.063). Multiple regression analysis revealed that age (ß=0.967, p = 0.001), female gender (ß=0.469, p<0.001), and duration of driving experience (ß=-0.583, p = 0.038) were correlated with SDLP.

SIGNIFICANCE

The present results demonstrated that the driving performance of PWE taking AEDs was not different from that of healthy volunteers.

Sleep-deprived car-following: Indicators of rear-end crash potential

Safety assessment among sleep-deprived drivers is a challenging research area with only a few sleep-related studies investigating safety performance during car-following. Therefore, this study aimed to measure the effects of partial sleep deprivation on driver safety during car-following. Fifty healthy male drivers with no prior history of any sleep-related disorders, drove the driving simulator in three conditions of varying sleep duration: a baseline (no sleep deprivation), test session (TS1) after one night of PSD (sleep ≤4.5 h/night) and TS2 after two consecutive nights of PSD. The reduced sleep in PSD sessions was monitored using an Actiwatch. Karolinska Sleepiness Scale was used to indicate loss of alertness among drivers. Each drive included a car-following task to measure longitudinal safety indicators based on speed and headway management: normalized time exposed to critical gap (TECG'), safety critical time headway and speed variability with respect to leading vehicle's speed (SPV). Crash potential index (CPI) was also determined from deceleration rate of drivers during car-following and was found correlated with other indicators. Therefore, to determine the aggregate influence of PSD on safety during car-following, CPI was modelled in terms of TECG, SPV, THW and other covariates. All safety metrics were modelled using generalized mixed effects regression models. The results showed that compared to the baseline drive, critical time headway decreased by 0.65 and 1.08 times whereas speed variability increased by 1.34 and 1.28 times during the TS1 and TS2, respectively, both indicating higher crash risk. However, decrease in TECG' by 64 % and 56 % during TS1 and TS2, respectively indicate compensatory measures to avoid risks due to sleep loss. A fractional regression model of crash potential revealed that low time-headway and higher speed variability and high time exposed to critical gap (TECG') significantly contribute to higher CPI values indicating higher safety risk. Other covariates such as sleep duration, professional driving experience and history of traffic violations were also associated with safety indicators and CPI, however no significant effects of age were noticed in the study. The study findings present the safety indicators sensitive to rear-end crashes specifically under PSD conditions, which can be used in designing collisions avoidance systems and strategies to improve overall traffic safety.

Distractive Tasks and the Influence of Driver Attributes

Driver distraction is a major problem nowadays, contributing to many deaths, injuries, and economic losses. Despite the effort that has been made to minimize these impacts, considering the technological evolution, distraction at the wheel has tended to increase. Not only tech-related tasks but every task that captures a driver’s attention has impacts on road safety. Moreover, driver behavior and characteristics are known to be heterogeneous, leading to a distinct driving performance, which is a challenge in the road safety perspective. This study aimed to capture the effects of drivers’ personal aspects and habits on their distraction behavior. Following a within-subjects approach, a convenience sample of 50 drivers was exposed to three unexpected events reproduced in a driving simulator. Drivers’ reactions were evaluated through three distinct models: a Lognormal Model to make analyze the visual distraction, a Binary Logit Model to explore the adopted type of reaction, and a Parametric Survival Model to study the reaction times. The research outcomes revealed that drivers’ behavior and perceived workload were distinct when they were engaged in specific secondary tasks and for distinct drivers’ personal attributes and habits. Age and type of distraction showed statistical significance regarding the visual behavior. Moreover, reaction times were consistently related to gender, BMI, sleep patterns, speed, habits while driving, and type of distraction. The habit of engaging in secondary tasks while driving resulted in a cumulative better performance.

Self-regulation differences across learner and probationary drivers: The impact on risky driving behaviours

Risky driving behaviours are a known contributor to young drivers' overrepresentation in road trauma, with self-regulation suggested as an important associated construct, but yet to be extensively explored. The aims of this study were to examine the utility of self-determination theory in explaining risky driving behaviours and to explore differences between young Learner and Provisional (P1)- licensed drivers in regard to their self-regulated safety orientation and engagement in risky driving behaviours. Learners (n = 1038) and P1(n = 589) drivers, aged 16-19 years, responded to a 91-item online survey, including self-regulated safety orientation items adapted from self-determination theory and inattentive and intentional risky driving behaviour items. Results showed that self-determination theory had good predictive power for the two types of risky driving behaviours for both licence groups. Learner and P1 drivers' engagement in risky behaviours was similar, however, the relative importance of self-regulated safety orientation elements to reduced engagement in these behaviours differed. Learners' engagement in intentional risky behaviours reflected greater perceived effort/importance and pressure/tension compared to P1 drivers. Greater effort/importance is an overarching indicator of internalised regulation concerning safe driving behaviours, which might be primed when first exposed to driving. However, greater perceived pressure/tension suggests that internalisation of self-regulatory processes is being suppressed during the Learner phase. This might stem from the required presence of driver trainers and supervisory drivers, as well as interactions with other road users. Whilst only tentative explanations in this first exploration, the findings suggest there is potential for greater efforts in Learner driver training and supervision to encompass the types of skills and learning that encourage the development of self-regulation to reduce risky driving behaviours during both the Learner and P1 stage. These findings contribute to the limited research regarding self-regulation by young novice drivers and informs a better understanding of the psychological influences of engagement in risky driving behaviours, including the first such examination among early independent licensed drivers.

Drivers' Attention Strategies before Eyes-off-Road in Different Traffic Scenarios: Adaptation and Anticipation

The distribution of drivers’ visual attention prior to diverting focus from the driving task is critical for safety. The object of this study is to investigate drivers’ attention strategy before they occlude their vision for different durations under different driving scenarios. A total of 3 (scenarios) × 3 (durations) within-subjects design was applied. Twenty-three participants completed three durations of occlusion (0, 1, and 2 s) test drive in a motion-based driving simulator under three scenarios (urban, rural, motorway). Drivers’ occlusion behaviour, driving behaviour, and visual behaviour in 6 s before occlusion was analyzed and compared. The results showed that drivers tended to slow down and increased their attention on driving task to keep safety in occlusion 2 s condition. The distribution of attention differed among different driving scenarios and occlusion durations. More attention was directed to Forward position and Speedometer in occlusion conditions, and a strong shift in attention from Forward position to Road users and Speedometer was found in occlusion 2 s condition. Road users was glanced more frequently in urban road with a higher percentage of attention transitions from Forward position to Road users. While gaze switching to Speedometer with a higher intensity was found on motorway. It suggests that drivers could adapt their visual attention to driving demand and anticipate the development of upcoming situations by sampling enough driving-related information before eyes-off-road. Moreover, the adaptation and anticipation are in accordance with driving situation and expected eyes-off-road duration. Better knowledge about attentional strategies before attention away from road contributes to more efficient and safe interaction with additional tasks.

Factors affecting behavior of mobile phone use while driving and effect of mobile phone use on driving performance

This study analyzed factors affecting behavior of mobile phone use while driving and its effects on driving performance, in terms of speed, lateral position, steer deviation, steer speed, following distance, perception-reaction time, and occurrence of a near miss situation. To investigate the factors affecting behavior of mobile phone use while driving, 1106 respondents from four different regions in Thailand participated in the questionnaire survey study. Theory of Planned Behavior (TPB) was used to explain these factors including two additional extended factors which are risk perception and law enforcement knowledge. The outcome of this part shows that attitude, norm, and law enforcement knowledge significantly affect the intention and behavior of the drivers. Even though approximately 90 percent of drivers realized that using a mobile phone while driving was dangerous and against the law, they have reported that they still use mobile phone while driving. To determine the effect of mobile phone use on driving performance, a 2-lane, straight rural highway, with a leading vehicle and an unexpected "STOP" sign, were simulated in order to examine the driving performance of drivers "without a phone", "talking on a phone call", and "texting a message" conditions. The results found that using mobile phone while driving can reduce speed and following distance, but increase lateral deviation, steer deviation, steer speed, perception-reaction time, and number of near misses leading to higher risks for road crashes.

Drivers' Braking Behavior Affected by Cognitive Distractions: An Experimental Investigation with a Virtual Car Simulator

In this study, a cohort of 78 university students performed a driving experience in a virtual urban scenario, by means of a car driving simulator, to examine effects of a planned hands-free mobile phone conversation on young drivers’ braking behaviors. To this aim, a control group was left free to drive without any imposed cognitive task. An experimental group faced the same scenario while engaged in a phone call. The conversation via earphones was arranged to diminish the amount of cognitive resources allocated to the driving task. For both groups, the analyses focused on the moment at which a child entered a pedestrian crossing from a sidewalk. The results of a mixed two-way ANOVA showed the presence of a significant difference for distracted and non-distracted drivers with the absence of gender-related differences across the two groups. Distracted participants assumed lower initial speeds, took the first action to stop at shorter distances from the zebra crossing, and had more difficulty in keeping speed variations under control. These findings suggest that the distraction induced by the use of earphones may induce risk compensation behaviors and delay pedestrian perception. Moreover, the effects on the participants’ braking behavior suggest that the procedure adopted to increase cognitive load, based on a story retelling, is an effective method to analyze the impact of hands-free cellphone use on driving skills in a car simulation experiment.

A Comparative Study of Accident Risk Related to Speech-Based and Handheld Texting during a Sudden Braking Event in Urban Road Environments

The use of mobile phones while driving is a very common phenomenon that has become one of the main causes of traffic accidents. Many studies on the effects of mobile phone use on accident risk have focused on conversation and texting; however, few studies have directly compared the impacts of speech-based texting and handheld texting on accident risk, especially during sudden braking events. This study aims to statistically model and quantify the effects of potential factors on accident risk associated with a sudden braking event in terms of the driving behavior characteristics of young drivers, the behavior of the lead vehicle (LV), and mobile phone distraction tasks (i.e., both speech-based and handheld texting). For this purpose, a total of fifty-five licensed young drivers completed a driving simulator experiment in a Chinese urban road environment under five driving conditions: baseline (no phone use), simple speech-based texting, complex speech-based texting, simple handheld texting, and complex handheld texting. Generalized linear mixed models were developed for the brake reaction time and rear-end accident probability during the sudden braking events. The results showed that handheld texting tasks led to a delayed response to the sudden braking events as compared to the baseline. However, speech-based texting tasks did not slow down the response. Moreover, drivers responded faster when the initial time headway was shorter, when the initial speed was higher, or when the LV deceleration rate was greater. The rear-end accident probability respectively increased by 2.41 and 2.77 times in the presence of simple and complex handheld texting while driving. Surprisingly, the effects of speech-based texting tasks were not significant, but the accident risk increased if drivers drove the vehicle with a shorter initial time headway or a higher LV deceleration rate. In summary, these findings suggest that the effects of mobile phone distraction tasks, driving behavior characteristics, and the behavior of the LV should be taken into consideration when developing algorithms for forward collision warning systems.

Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior

The aim of this paper was to provide a methodological framework for estimating the amount of driving data that should be collected for each driver in order to acquire a clear picture regarding their driving behavior. We examined whether there is a specific discrete time point for each driver, in the form of total driving duration and/or the number of trips, beyond which the characteristics of driving behavior are stabilized over time. Various mathematical and statistical methods were employed to process the data collected and determine the time point at which behavior converges. Detailed data collected from smartphone sensors are used to test the proposed methodology. The driving metrics used in the analysis are the number of harsh acceleration and braking events, the duration of mobile usage while driving and the percentage of time driving over the speed limits. Convergence was tested in terms of both the magnitude and volatility of each metric for different trips and analysis is performed for several trip durations. Results indicated that there is no specific time point or number of trips after which driving behavior stabilizes for all drivers and/or all metrics examined. The driving behavior stabilization is mostly affected by the duration of the trips examined and the aggressiveness of the driver.

Mobile Phone Use in a Car-Following Situation: Impact on Time Headway and Effectiveness of Driver's Rear-End Risk Compensation Behavior via a Driving Simulator Study

Mobile phone use while driving has become one of the leading causes of traffic accidents and poses a significant threat to public health. This study investigated the impact of speech-based texting and handheld texting (two difficulty levels in each task) on car-following performance in terms of time headway and collision avoidance capability; and further examined the relationship between time headway increase strategy and the corresponding accident frequency. Fifty-three participants completed the car-following experiment in a driving simulator. A Generalized Estimating Equation method was applied to develop the linear regression model for time headway and the binary logistic regression model for accident probability. The results of the model for time headway indicated that drivers adopted compensation behavior to offset the increased workload by increasing their time headway by 0.41 and 0.59 s while conducting speech-based texting and handheld texting, respectively. The model results for the rear-end accident probability showed that the accident probability increased by 2.34 and 3.56 times, respectively, during the use of speech-based texting and handheld texting tasks. Additionally, the greater the deceleration of the lead vehicle, the higher the probability of a rear-end accident. Further, the relationship between time headway increase patterns and the corresponding accident frequencies showed that all drivers’ compensation behaviors were different, and only a few drivers increased their time headway by 60% or more, which could completely offset the increased accident risk associated with mobile phone distraction. The findings provide a theoretical reference for the formulation of traffic regulations related to mobile phone use, driver safety education programs, and road safety public awareness campaigns. Moreover, the developed accident risk models may contribute to the development of a driving safety warning system.

Tracing the physiological response and behavioral performance of drivers at different levels of mental workload using driving simulators

INTRODUCTION

The use of mobile phones while driving is known to be a distraction factor and a cause of accidents. The way in which different kinds of conversations affect the behavioral performance of the driver as well as the persistence of the effects are not yet fully understood.

METHOD

In this study, in addition to comparing brain function and behavioral function in dual task conditions in three conversations types, the persistent effects of these types of conversations have also been traced.

RESULTS

The results show that the content of the mobile phone conversation while driving is the cause of the persistent changes in behavioral and brain functions. Increased time headway and lane departure was observed during and up to 5 min after the emotional conversation was finished. EEG bands also varied in different types of conversations. Cognitive conversations caused an increase in the activity of the alpha and beta bands while emotional conversations enhanced the rate of gamma and beta bands. A meaningful correlation was found between changes in the theta and alpha bands and changes in behavioral performance both during the dual task condition and after the conversation was finished, was also observed.

CONCLUSIONS

The content of the conversation is one of the most important factors that increase the risk of road accidents. This can also deteriorate the behavioral performance of the driver and can have persistent effects on behavioral performance and the brain. Practical applications: The findings of this study provide a basis to measure and tracing drivers' cognitive distractions induced by different levels of mental workload through physiological and behavioral performances.

Mapping the knowledge domain of road safety studies: A scientometric analysis

As a way of obtaining a visual expression of knowledge, mapping knowledge domain (MKD) provides a vision-based analytic approach to scientometric analysis which can be used to reveal an academic community, the structure of its networks, and the dynamic development of a discipline. This study, based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) articles on road safety, employs the bibliometric tools VOSviewer and CitNetExplorer to create maps of author co-citation, document co-citation, citation networks, analyze the core authors and classic documents supporting road safety studies and show the citation context and development of such studies. It shows that road safety studies clustered mainly into four groups, whose we will refer to as "effects of driving psychology and behavior on road safety", "causation, frequency and injury severity analysis of road crashes", "epidemiology, assessment and prevention of road traffic injury", and "effects of driver risk factors on driver performance and road safety", respectively. Through our analysis, the core publications and their citation relationships were quickly located and explored, and "crash frequency modeling analysis" has been identified to be the core research topic in road safety studies, with spatial statistical analysis technique emerging as a frontier of this topic.

Primary insomnia patients' performances during simulated car following and urban driving in the afternoon

According to epidemiological studies, insomnia is associated with an increase in risk of traffic accidents. Recent investigations revealed that patients with insomnia had driving performance impairment under monotonous conditions. However, it is unclear whether other driving abilities may be impacted by insomnia, especially those needing more attentional resources than those involved in monotonous driving. Other findings revealed that impaired performances are more likely to occur with the increase of cognitive demands. However, such tests did not reflect difficulties in situations of everyday life expressed by patients with insomnia, such as driving in an urban environment with traffic and critical situations. Therefore, behaviour in situations encountered in everyday life has to be explored. The aim of the present study was to assess driving performances of patients with insomnia in daily routine tasks such as urban and car-following tests. For this purpose, 15 patients with insomnia and 16 good sleepers performed an urban test of driving with original risk scenarios and a car-following test during the middle afternoon. No significant behavioural difference between patients with insomnia and good sleepers has been found in both the urban test and the car-following test, showing that patients with insomnia have no impairment in behaviour implicated in daily contexts driving tasks of short period of time performed in the late afternoon. Although our results provide a first step towards knowledge of behavioural performance during daily routine driving tasks in patients with insomnia, future studies are needed using on-the-road driving tests and/or different population of patients with insomnia before generalisation.

Mobile phone involvement, beliefs, and texting while driving in Ukraine

There is extensive evidence that using a mobile phone whilst driving is one of the biggest contributors to driver distraction, which in turn increases the risk of motor vehicle collisions. Whilst most of the developed countries have been trying to deter this behaviour through legislation, enforcement and educational campaigns, in Ukraine, where the road fatality rate is the highest in Europe, this issue has only recently become publicised. The present study examined psychological factors that are associated with hand-held mobile phone use while driving among a sample of Ukrainian drivers, in particular writing or reading a text message while driving. This included drivers' behavioural, normative, and control beliefs relating to mobile phone use while driving, as well as the degree to which using a mobile phone is integral to one's everyday life (measured using the Mobile Phone Involvement Questionnaire; MPIQ). Almost one quarter to one third of the sample reported using their phone on a daily basis to write (22.2%) or read (38.2%) text messages while driving. A binary logistic regression showed that gender, higher MPIQ scores, perceived approval from family members, lower perceived likelihood of receiving traffic fines and less demanding traffic conditions were all significantly associated with mobile phone use while driving. These results suggest that dependence upon a mobile phone in everyday life may be an important factor to consider when developing interventions to reduce hand-held mobile phone use while driving.

"Mate! I'm running 10 min late": An investigation into the self-regulation of mobile phone tasks while driving

The adaptive behaviour of mobile phone distracted drivers has been a topic of much discussion in the recent literature, but the mechanisms of behavioural adaptation are still unclear. This study investigated the influence of driving demands, secondary task characteristics, and personal characteristics on behavioural adaptation of mobile phone distracted drivers. In particular, distracted drivers' self-regulation at strategic, tactical, and operational levels was investigated through a driving simulator experiment. In a high-fidelity driving simulator, participants driving through various driving conditions (e.g. interactions with pedestrian crossings, signalized intersections, merging ramps, roundabouts, etc.) needed to decide where and how to perform the following four mobile phone tasks: (a) ring a doctor and cancel an appointment, (b) text a friend and tell him/her that the participant will be arriving 10 min late, (c) share the doctor's phone number with a friend, and (d) take a 'selfie'. At a strategic level, the decision to pull over was modelled as a function of self-reported personal/attitudinal characteristics with a logistic regression model. Similarly, tactical self-regulation (decision to engage in a task while driving in a specific situation) and operational self-regulation (decision to temporarily stop the mobile phone task) were modelled as a function of driving demands and personal/attitudinal characteristics using a random-effects logistic regression model, which accounts for correlations resulting from multiple observations of a driver. Results suggest that tactical self-regulation is more common among distracted drivers followed by operational and strategic self-regulation. Personal beliefs regarding how safe it is to use the mobile phone for texting/browsing while driving were predictors of self-regulation for all levels. Drivers were observed to use the mobile phone more when the driving demands are low, e.g. while stopped at an intersection. This research suggests that distracted drivers engage in various levels of self-regulation, and future research could be focused on further theoretical refinement and development of technology-based interventions.

Should I Text or Call Here? A Situation-Based Analysis of Drivers' Perceived Likelihood of Engaging in Mobile Phone Multitasking

This study investigated how situational characteristics typically encountered in the transport system influence drivers' perceived likelihood of engaging in mobile phone multitasking. The impacts of mobile phone tasks, perceived environmental complexity/risk, and drivers' individual differences were evaluated as relevant individual predictors within the behavioral adaptation framework. An innovative questionnaire, which includes randomized textual and visual scenarios, was administered to collect data from a sample of 447 drivers in South East Queensland-Australia (66% females; n = 296). The likelihood of engaging in a mobile phone task across various scenarios was modeled by a random parameters ordered probit model. Results indicated that drivers who are female, are frequent users of phones for texting/answering calls, have less favorable attitudes towards safety, and are highly disinhibited were more likely to report stronger intentions of engaging in mobile phone multitasking. However, more years with a valid driving license, self-efficacy toward self-regulation in demanding traffic conditions and police enforcement, texting tasks, and demanding traffic conditions were negatively related to self-reported likelihood of mobile phone multitasking. The unobserved heterogeneity warned of riskier groups among female drivers and participants who need a lot of convincing to believe that multitasking while driving is dangerous. This research concludes that behavioral adaptation theory is a robust framework explaining self-regulation of distracted drivers.

Driving behaviour while self-regulating mobile phone interactions: A human-machine system approach

Mobile phone distracted driving is a recurrent issue in road safety worldwide. Recent research on driving behaviour of distracted drivers suggests that in certain circumstances drivers seem to assume safer behaviours while using a mobile phone. Despite a high volume of research on this topic, self-regulation by mobile phone distracted drivers is not well understood as many driving simulator experiments are designed to impose an equal level of distraction to participants being tested for their driving performance. The aim of this research was to investigate the relationship between self-regulatory secondary task performance and driving. By a driving simulator experiment in which participants were allowed to perform their secondary tasks whenever they feel appropriate, the driving performance of 35 drivers aged 18-29 years was observed under three phone conditions including non-distraction (no phone use), hands-free interactions and visual-manual interactions in the CARRS-Q advanced driving simulator. Drivers' longitudinal and lateral vehicle control observed across various road traffic conditions were then modelled by Generalized Estimation Equations (GEE) with exchangeable correlation structure accounting for heterogeneity resulting from multiple observations from the same driver. Results show that the extent of engagement in the secondary task influence both longitudinal and lateral control of vehicles. Drivers who engaged in a large number of hands-free interactions are found to select lower driving speed. In contrast, longer visual-manual interactions are found to result in higher driving speed among drivers self-regulating their secondary task. Among the road traffic conditions, drivers distracted by their self-regulated secondary tasks are found to select lower speeds along the s-curve compared to straight and motorway segments. In summary, the applied human-machine system approach suggests that road traffic demands play a vital role in both secondary task management and driving performance.

Description of Various Factors Contributing to Traffic Accidents in Youth and Measures Proposed to Alleviate Recurrence

Traffic accidents are the leading cause of hospitalization in adolescence, with the 18-24-year-old age group accounting for 23% of deaths by traffic accidents. Recurrence rate is also high. One in four teenagers will have a relapse within the year following the first accident. Cognitive impairments known in adolescence could cause risky behaviors, defined as repetitive engagement in dangerous situations such as road accidents. Two categories of factors seem to be associated with traffic accidents: (1) factors specific to the traffic environment and (2) "human" factors, which seem to be the most influential. Moreover, the establishment of a stronger relation to high speed driving increases traffic accident risks and can also be intensified by sensation seeking. Other factors such as substance use (alcohol, drugs, and "binge drinking") are also identified as risk factors. Furthermore, cell phone use while driving and attention deficit disorder with or without hyperactivity also seem to be important risk factors for car accidents. The family environment strongly influences a young person's driving behavior. Some interventional driving strategies and preventive measures have reduced the risk of traffic accidents among young people, such as the graduated driver licensing program and advertising campaigns. So far, few therapeutic approaches have been implemented. Reason why, we decided to set up an innovative strategy consisting of a therapeutic postaccident group intervention, entitled the ECARR2 protocol, to prevent recurrence among adolescents and young adults identified at risk, taking into account the multiple risk factors.

The antecedents, experience, and coping strategies of driver boredom in young adult males

INTRODUCTION

Road crash statistics are evidence of the severe consequences resulting from human error, especially among young adult males. Drivers perform best and safest when they are adequately engaged in the driving task. Boredom and a lack of engagement in the driving task may cause risk taking and phone use. However, the antecedents to driver boredom, the subjective experience itself, as well as the coping strategies to combat boredom are not well understood. The aim of this study was to investigate these aspects.

METHOD

We carried out a qualitative study in a simulated, safe, yet highly immersive driving environment. The 24 participants included male drivers aged 18 to 25 susceptible to risky driving and phone use. A phenomenological framework was used to analyze their accounts of the experience of boredom while driving.

RESULTS

Results indicate that situations giving rise to driver boredom include low traffic, slow or constant speed, and routine drives. Feelings comprising the experience were frustration, vigilance, relaxing, autopilot, mind wandering, and discomfort. Coping mechanisms manifest themselves in approach strategies related to the driving task such as speeding, which are often dangerous, and avoidance strategies, which include phone use.

CONCLUSIONS

We conclude that driver boredom bears similarities to the experience of boredom at work (unlike boredom at home) due to the situational constraints, where people feel stuck, trapped, or obliged to remain vigilant.

PRACTICAL APPLICATIONS

The findings present an opportunity for the road safety and automotive technology community to address the issue of under-stimulation through safety interventions aimed at increased task engagement. Our work can also aid in investigating driver experiences in partially automated driving, which is likely to induce boredom as well.

A rear-end collision risk assessment model based on drivers' collision avoidance process under influences of cell phone use and gender-A driving simulator based study

Driver's collision avoidance performance has a direct link to the collision risk and crash severity. Previous studies demonstrated that the distracted driving, such as using a cell phone while driving, disrupted the driver's performance on road. This study aimed to investigate the manner and extent to which cell phone use and driver's gender affected driving performance and collision risk in a rear-end collision avoidance process. Forty-two licensed drivers completed the driving simulation experiment in three phone use conditions: no phone use, hands-free, and hand-held, in which the drivers drove in a car-following situation with potential rear-end collision risks caused by the leading vehicle's sudden deceleration. Based on the experiment data, a rear-end collision risk assessment model was developed to assess the influence of cell phone use and driver's gender. The cell phone use and driver's gender were found to be significant factors that affected the braking performances in the rear-end collision avoidance process, including the brake reaction time, the deceleration adjusting time and the maximum deceleration rate. The minimum headway distance between the leading vehicle and the simulator during the rear-end collision avoidance process was the final output variable, which could be used to measure the rear-end collision risk and judge whether a collision occurred. The results showed that although cell phone use drivers took some compensatory behaviors in the collision avoidance process to reduce the mental workload, the collision risk in cell phone use conditions was still higher than that without the phone use. More importantly, the results proved that the hands-free condition did not eliminate the safety problem associated with distracted driving because it impaired the driving performance in the same way as much as the use of hand-held phones. In addition, the gender effect indicated that although female drivers had longer reaction time than male drivers in critical situation, they were more quickly in braking with larger maximum deceleration rate, and they tended to keep a larger safety margin with the leading vehicle compared to male drivers. The findings shed some light on the further development of advanced collision avoidance technologies and the targeted intervention strategies about cell phone use while driving.

Does family background impact driving attitudes and risky behaviours? An investigation on Chinese young drivers

The rapid pace of motorisation in China has been well documented, as has the large road trauma burden the Chinese citizens are facing as a result. China's unique political system represents an important consideration in helping reduce road trauma, yet political factors have not been previously investigated in this context. Recently, emerging issues on the road involving the adult children of politically powerful families have become a serious social problem in China, and have drawn widespread media and public attention. This study took a novel approach to examining factors associated with risky attitudes and risky road use in China by investigating the economic and political background status of a sample of young Chinese drivers. An online survey was conducted in May 2015 with a sample size of 476 Chinese young drivers from across the country, aged between 18 and 28, including 305 males and 171 females. The results suggest that for participants who reported having a familial political background, more risky driving behaviours were reported among those participants who reported more impact on their life from that political background; while for participants without political background, higher personal income was associated with more risky driving behaviours. The findings are discussed in light of China's political management system and potential education opportunities for young drivers.