Perceptions of driver distraction among teenage drivers

Teenage drivers have been shown to have some of the highest crash risks. Crash data provide some insights on factors related to crash likelihood, but rarely capture all issues that can arise from driver distraction. The goal of this study was to assess teenage drivers’ opinions and perceptions of driver distraction. A survey of 1893 Iowa teenagers was conducted to determine and compare the frequency of engagement in distracting activities while driving to their opinions of what they actually consider to be distractions. A cluster analysis was conducted based on their indicated engagement in distracting activities with three groups emerging and classified as INFREQUENT, MODERATE, and FREQUENT engagers. Across all cluster groups, the majority (over 80%) indicated that they considered text messaging to be a distracting task. However, those clustered as FREQUENT engagers still reported a high level of texting while driving even though they considered this task to be distracting. A binary logistic regression model (adjusted for miles driven and license type) showed that FREQUENT and MODERATE engagers were more likely to be involved in a crash when compared to INFREQUENT engagers. The study demonstrates that not all teenagers place themselves at risk. There are subgroups of teenage drivers that often engage in activities they know are distracting, potentially putting themselves in danger. However, this is not the case for all teenage drivers and it is important to target interventions appropriately as well as foster a culture of safety both in schools and at home.     

The impact of an in-vehicle display on glance distribution in partially automated driving in an on-road experiment

One of the major challenges of designing an HMI for partially automated vehicles is the trade-off between a sufficient level of system information and avoidance of distracting the driver. This study aimed to investigate drivers’ glance behavior as an indicator of distraction when vehicle guidance is partially automated. Therefore, an on-road experiment was conducted comparing two versions of an in-vehicle display (during partially automated driving) and no display (during manual driving) on a heavy congested highway segment. The distribution of drivers’ total glance durations on the HMI showed that visual attention was shifted away from monitoring the central road scene towards looking at the in-vehicle display to a considerable extent. However, an analysis of the distribution of single glance durations supports the view that using partial automation and a respective HMI does not lead to a critical increase in distraction. Driving with a simplified version of the HMI had the potential to reduce glance duration on and thus potential distraction of the in-vehicle display.     

Driver performance effects of simultaneous visual and cognitive distraction and adaptation behavior

Driver distraction has become a major concern for transportation safety due to increasing use of infotainment systems in vehicles. To reduce safety risks, it is crucial to understand how fundamental aspects of distracting activities affect driver behavior at different levels of vehicle control. This study used a simulator-based experiment to assess the effects of visual, cognitive and simultaneous distraction on operational (braking, accelerating) and tactical (maneuvering) control of vehicles. Twenty drivers participated in the study and drove in lead-car following or passing scenarios under four distraction conditions: without distraction, with visual distraction, with cognitive distraction, and with simultaneous distraction. Results revealed higher perceived workload for passing than following. Simultaneous distraction was most demanding and also resulted in the greatest steering errors among distraction conditions during both driving tasks. During passing, drivers also appeared to slow down their responses to secondary distraction tasks as workload increased. Visual distraction was associated with more off-road glances (to an in-vehicle device) and resulted in high workload. Longer headway times were also observed under visual distraction, suggesting driver adaptation to the workload. Similarly, cognitive distraction also increased driver workload but this demand did not translate into steering errors as high as for visual distraction. In general, findings indicate that tactical control of a vehicle demands more workload than operational control. Visual and cognitive distractions both increase driver workload, but they influence vehicle control and gaze behavior in different ways.     

Real-time detection of drivers’ texting and eating behavior based on vehicle dynamics

With rapid advancement in cellphones and intelligent in-vehicle technologies along with driver’s inclination to multitasking, crashes due to distracted driving had become a growing safety concern in our road network. Some previous studies attempted to detect distracted driving behaviors in real-time to mitigate their adverse consequences. However, these studies mainly focused on detecting either visual or cognitive distractions only, while most of the real-life distracting tasks involve driver’s visual, cognitive, and physical workload, simultaneously. Additionally, previous studies frequently used eye, head, or face tracking data, although current vehicles are not commonly equipped with technologies to acquire such data. Also those data are comparatively difficult to acquire in real-time during traffic monitoring operations. To address the above issues, this study focused on developing algorithms for detecting distraction tasks that involve simultaneous visual, cognitive, and physical workload using only vehicle dynamics data. Specifically, algorithms were developed to detect driving behaviors under two distraction tasks – texting and eating. Experiment was designed to include the two distracted driving scenarios and a control with multiple runs for each. A medium fidelity driving simulator was used for acquiring vehicle dynamics data for each scenario and each run. Several data mining techniques were explored in this study to investigate their performance in detecting distraction. Among them, the performance of two linear (linear discriminant analysis and logistic regression) and two nonlinear models (support vector machines and random forests) is reported in this article. Random forests algorithms had the best performance, which detected texting and eating distraction with an accuracy of 85.38% and 81.26%, respectively. This study may provide useful guidance to successful development and implementation of distracted driver detection algorithms in connected vehicle environment, as well as to auto manufacturers interested in integrating distraction detection systems in their vehicles.     

Sensitivity to reward and risky driving,risky decision making,and risky health behaviour: A literature review

Young driver road safety has persisted as a global problem for decades, despite copious and diverse intervention. Recently the influence in reward sensitivity, which refers to the individual’s personal sensitivity to rewards, has received attention in health-related research, including more generally through decision making in risky circumstances, and in risky driving behaviour specifically. As such, a literature review and synthesis of the literature regarding reward sensitivity in relation to risky driving, risky decision making, and risky health behaviour, with a focus on literature in which adolescents and young adults feature, is timely. Thirty-one papers were identified, and the literature revealed that young drivers with greater reward sensitivity engage in more risky driving behaviours including speeding, crashes and traffic violations; and that individuals with greater reward sensitivity engage in more risky decision making and other risky health-related behaviours (such as drinking and drug use). Adolescents and young adults exhibit heightened sensitivity to rewards in the presence of peers, which has considerable implications for young driver road safety as research consistently demonstrates that carrying peer passengers places all vehicle occupants at greater risk of being involved in a road crash. Consideration of the influence of reward sensitivity in young driver road safety, and other adolescent/young adult health-related safety, appears to be a promising avenue of intervention, with gain-framed messages more likely to be accepted by young drivers with greater reward sensitivity. Future research in jurisdictions other than Australia and Europe will increase our understanding of the influence of reward sensitivity, and exploration of the differential impacts of reward-responsiveness and fun-seeking specifically are warranted.     

Comparison of contributing factors in hit-and-run crashes with distracted and non-distracted drivers

Among different types of crashes, hit-and-run is driver’s failure to stop after a vehicle crash. There are many accidents where drivers could actually be at fault or totally innocent, and leaving the scene would turn an innocent driver into a criminal. The current paper aims to contribute to the literature by exploring the association of different variables pertaining to the condition of infrastructure, environment, driver, population of the area, and crash severity and type with hit-and-run crashes. The analysis is performed for two data sets: (i) crashes where the driver was distracted; and (ii) crashes where driver was not distracted. Hit-and-run crash data with corresponding factors are police-reported data for crashes within Cook County, Illinois, occurring between 2004 and 2012. A logistic regression model assessed 43 variables within 16 categories for statistically significant association with hit-and-run crashes, for drivers with and without distraction. For both driver distraction statuses, 17 variables were associated with a significant increased probability of a hit-and-run crash and 10 variables were associated with a significant decreased probability. Additionally, it was found that crashes on curve level and curve hillcrest road alignment types were associated with increased likelihood of a hit-and-run crash when the driver was distracted and decreased likelihood when the driver was not distracted. Variables related to hit-and-run crashes vary depending on driver’s distraction status. When comparing likelihood to flee the scene after a crash, non-distracted drivers are 27% less likely to do so compared to distracted drivers.     

Drivers’ attitudes toward imperfect distraction mitigation strategies

Studies were conducted to assess driver acceptance of and trust in distraction mitigation strategies. Previous studies have shown that in-vehicle tasks undermine driver safety, and that there is a need for strategies to reduce the effects of in-vehicle distractions. Trust and acceptance of such strategies strongly influence their effectiveness. Different strategies intended to reduce distraction were categorized in a taxonomy. Focus groups were conducted to help refine this taxonomy and explore driver acceptance issues related to these strategies. A driving simulator experiment was then conducted using two of the strategies: an advising strategy that warns drivers of potential dangers and a locking strategy that prevents the driver from continuing a distracting task. These strategies were presented to 16 middle-aged and 12 older drivers in two modes (auditory, visual) with two levels of adaptation (true, false). Older drivers accepted and trusted the strategies more than middle-aged drivers. Regardless of age, all drivers preferred strategies that provided alerts in a visual mode rather than an auditory mode. When the system falsely adapted to the road situation, trust in the strategies declined. The findings show that display modality has a strong effect on driver acceptance and trust, and that older drivers are more trusting and accepting of distraction mitigation technology even when it operates imperfectly.     

How drivers adapt their behaviour to changes in task complexity: The role of secondary task demands and road environment factors

The present study investigates the impact of different sources of task complexity such as driving demands and secondary task demands on driver behaviour. Although much research has been dedicated to understanding the impact of secondary task demands or specific road traffic environments on driving performance, there is little information on how drivers adapt their behaviour to their combined presence. This paper aims to describe driver behaviour while negotiating different sources of task complexity, including mobile phone use while driving (i.e., calling and texting) and different road environments (i.e., straight segments, curves, hills, tunnels, and curves on hills). A driving simulator experiment was conducted to explore the effects of different road scenarios and different types of distraction while driving. The collected data was used to estimate driving behaviour through a Generalized Linear Mixed Model (GLMM) with repeated measures. The analysis was divided into two phases. Phase one aimed to evaluate driver performance under the presence and absence of pedestrians and oncoming traffic, different lanes width and different types of distraction. The second phase analysed driver behaviour when driving through different road geometries and lane widths and under different types of distraction. The results of the experiment indicated that drivers are likely to overcorrect position in the vehicle lane in the presence of pedestrians and oncoming traffic. The effect of road geometry on driver behaviour was found to be greater than the effect of mobile phone distraction. Curved roads and hills were found to influence preferred speeds and lateral position the most. The results of this investigation also show that drivers under visual-manual distraction had a higher standard deviation of speed and lateral position compared to the cognitive distraction and the non-distraction condition.     

Driver glance behavior towards displayed images on in-vehicle information systems under real driving conditions

Intelligent vehicle technologies like driver assistance systems and in-vehicle information systems, enhance convenience of the driving experience for drivers and passengers. At the same time, these systems may increase driver distraction and workload. Guidelines developed for this purpose include principles, methods, and assessments which are widely agreed upon, with some being singled out for a particular recommendation or requirement. Especially the display of graphical or photographic images are generally assumed to distract the driver from safely operating the vehicle and should be blocked during driving under all circumstances (so called per se lock outs). This study investigates the effect of displaying graphical and photographical images during driving on driveŕs glance behavior during real-world driving. Findings presented in this paper provide empirical evidence for the unobtrusiveness of these stimuli: Participants didn’t exhibit longer glance durations towards in-vehicle information systems, nor a deterioration of driver distraction parameters such as total eyes off road time and long glance proportion when being compared to driving without displaying any photographic images.     

Roadside digital billboard advertisements: Effects of static,transitioning, and animated designs on drivers’ performance and attention

The aim of this study was to analyze and compare the effects of different types of digital billboard advertisements (DBAs) on drivers’ performance and attention allocation. Driver distraction is a major threat to driver safety. DBAs are one form of distraction in drivers’ outside environment. There are many different types of DBAs, such as static images, changing images, or videos. However, it is not clear to what extent each of these contributes to driver distraction. A total of 100 students participated in a controlled driving simulator experiment in an urban environment. Measures of driving performance were collected, as well as eye tracking and EEG as windows into attention allocation. The different types of DBAs investigated were static (a single image), transitioning (one static DBA replaces another), and animated (short videos). The statistical analysis demonstrated that there were significant differences in the effect of each type of DBA on drivers' performance (deviation from the center of the lane and reaction time), visual attention to the road (percent of fixations on the road, percent of fixations on DBAs, fixation duration on DBAs, and number of gazes on DBAs), and the EEG theta band and beta band. These results show that driving performance and attention to the road were both more negatively affected when drivers were exposed to transitioning and animated DBAs as compared to static DBAs. The results of this study provide guidance for the better design and regulation of DBAs in order to minimize driver distraction.     

Analysis of vehicle-based lateral performance measures during distracted driving due to phone use

Distracted driving due to mobile phone use has been identified as a major contributor to accidents; therefore, it is required to develop ways for detecting driver distraction due to phone use. Though prior literature has documented various visual behavioural and physiological techniques to identify driver distraction, comparatively little is known about vehicle based performance features which can identify driver’s distracted state during phone conversation and texting while driving. Therefore, this study examined the effects of simple conversation, complex conversation, simple texting and complex texting tasks on vehicle based performance parameters such as standard deviation of lane positioning, number of lane excursions, mean and standard deviation of lateral acceleration, mean and standard deviation of steering wheel angle and steering reversal rates (for 1°, 5° and 10° angle differences). All these performance measures were collected for 100 licensed drivers, belonging to three age groups (young, mid-age and old age), with the help of a driving simulator. Effects of all the phone use conditions and driver demographics (age, gender and phone use habits) on the measures were analysed by repeated measures ANOVA tests. Results showed that 1°, 5° SRRs are able to identify all the distracted conditions except for simple conversation; while, 10° SSR can detect all the distracted conditions (including simple conversation). The results suggest that 10° SRR can be included in intelligent in-vehicle devices in order to detect distraction and alert drivers of their distracted state. This can prevent mobile phone use during driving and therefore can help in reducing the road accidents due to mobile phone distractions.     

Driver distraction in long-haul truck drivers

Research on driver distraction has typically been conducted by means of epidemiology or experimental testing. The study presented here uses a naturalistic approach, where real-world driving data were collected from truck drivers as they worked their normal delivery runs. Crash, near-crash, and crash-relevant conflict data from 41 long-haul truck drivers, driving approximately 140,000 miles, were examined. Of the 2737 crashes, near-crashes, and crash-relevant conflicts (collectively termed “critical incidents”) that were recorded, 178 were attributed to “driver distraction”. The 178 distraction-related critical incidents were analyzed and 34 unique distraction types were identified. Results showed that a small number of long-haul drivers were involved in a disproportionate number of distraction-related critical incidents. For example, two of the drivers accounted for 43 of the 178 distraction incidents. Important insight was also gained into the relative safety impacts of different distracting agents and behaviors. The frequency and duration of a task, along with the visual demand associated with performing the task, were found to contribute in combination to the prevalence of critical incidents. Finally, it was found that simply because a task does not necessarily require visual attention does not mean that long-haul drivers will not look (sometimes often) away from the roadway. However, it is also clear that visually demanding tasks carry the highest degree of risk, relative to other categories of tasks.     

Attention all ‘drivers’: You could be to blame,no matter your behaviour or the level of vehicle automation

Vehicle crashes are one of the leading causes of human deaths worldwide, with crashes predominately attributed to failures of human drivers. Whilst increasing vehicle automation is argued to reduce road crashes via decreased driver involvement, automation also raises concerns around driver blame and stakeholder responsibility. This study examines blame for crash scenarios across four different forms of driver distraction behaviours (phone, sleep, work and driving under the influence), and across four levels of vehicle automation (no automation [manual], partially automated, highly automated, fully automated), using a mixed (qualitative and quantitative) methods approach. Participants (n = 205) were randomised into one of the four levels of vehicle automation and were presented with vignette crash scenarios involving a pedestrian being hit by a vehicle. Results revealed that scenarios varying driver behavior at the time of the crash, had no significant impact on participants’ blame attribution or selected course of action. The qualitative analysis revealed that despite semantic distinction between some driver behaviours, drivers were deemed responsible for the crash. As automation increased, attribution of blame towards the driver decreased, but did not disappear. Blame simultaneously increased towards other stakeholders including the manufacturer and the government, as level of automation increased. These findings mirror that of previous research and further highlight the need for legal frameworks for crashes with automated vehicles, irrespective of driver behaviours.     

Passing behavior on two-lane highways

Two-lane highways make up a substantial proportion of the road network in most of the world. Passing is among the most significant driving behaviors on two-lane highways. It substantially impacts the highway performance. Despite the importance of the problem, few studies attempted to model passing behavior. In this research, a model that attempts to capture both drivers’ desire to pass and their gap acceptance decisions to complete a desired passing maneuver is developed and estimated using data on passing maneuvers collected with a driving simulator. Sixteen different scenarios were used in the experiment in order to capture the impact of factors related to the various vehicles involved, the road geometry and the driver characteristics in the model.A passing behavior model is developed that includes choices in two levels: the desire to pass and the decision whether or not to accept an available passing gap. The probability to complete a passing maneuver is modeled as the product of the probabilities of a positive decision on both these choices. The estimation results show that modeling the drivers’ desire to pass the vehicle in front has a statistically significant contribution in explaining their passing behavior. The two sub-models incorporate variables that capture the impact of the attributes of the specific passing gap that the driver evaluates and the relevant vehicles, the geometric characteristics of the road section and the driver characteristics and account for unobserved heterogeneity in the driver population.     

The impact of navigation system display size and environmental illumination on young driver mental workload

Driver distraction is a major cause of road crashes and has a great influence on road safety. In vehicles, one of the common distracting sources is navigation systems (NSs). The navigation system (NS) can distract the driver due to following directions and reading the provided information through its display. These tasks take the driver’s attention from the primary task of driving and may cause poor driving performance, increasing the risk of crashes. In this paper, the effect of the environment (i.e., urban areas and rural areas), the navigation system display (NSD) size, environmental illumination, and gender on young drivers between the ages of 18 and 29 years mental workload was investigated using a simulated driving experiment. To evaluate each driving condition, the NASA-TLX (NASA Task Load Index) workload assessment tool, and a distraction evaluation element, were introduced and used to assess the overall workload, the workload subscales and the distraction by the NSD. The assessment showed a higher perceived overall workload for urban areas and night driving as compared to a rural areas and daytime driving. Moreover, the results showed a greater perceived distraction by the NSD in urban areas compared to driving in rural areas. The subjects also felt distracted when using the small NS compared to using the large NS. The study concluded that urban areas driving, and night driving creates higher perceived workload than rural areas and daytime driving. Furthermore, small NSD leads to more perceived distraction than large NSD while driving. The NSD designers may utilize this research findings to optimize NSD designs to improve driving safety, performance and comfort. Moreover, this study contributes to our understanding of the effect of the NSD size on driving workload and distraction.     

The role of drivers’ social interactions in their driving behavior: Empirical evidence and implications for car-following and traffic flow

Models for describing the microscopic driving behavior rarely consider the “social effects” on drivers’ driving decisions. However, social effect can be generated due to interactions with surrounding vehicles and affect drivers’ driving behavior, e.g., the interactions result in imitating the behavior of peer drivers. Therefore, social environment and peer influence can impact the drivers’ instantaneous behavior and shift the individuals’ driving state. This study aims to explore empirical evidence for existence of a social effect, i.e., when a fast-moving vehicle passes a subject vehicle, does the driver mimic the behavior of passing vehicle? High-resolution Basic Safety Message data set (N = 151,380,578) from the Safety Pilot Model Deployment program in Ann Arbor, Michigan, is used to explore the issue. The data relates to positions, speeds, and accelerations of 63 host vehicles traveling in connected vehicles with detailed information on surrounding environment at a frequency of 10 Hz. Rigorous random parameter logit models are estimated to capture the heterogeneity among the observations and to explore if the correlates of social effect can vary both positively and negatively. Results show that subject drivers do mimic the behavior of passing vehicles –in 16 percent of passing events (N = 18,099 total passings occurred in freeways), subject vehicle drivers are observed to follow the passing vehicles accelerating. We found that only 1.2 percent of drivers normally sped up (10 km/hr in 10 s) during their trips, when they were not passed by other vehicles. However, if passed by a high speed vehicle the percentage of drivers who sped up is 16.0 percent. The speed change of at least 10 km/hr within 10 s duration is considered as accelerating threshold. Furthermore, the acceleration of subject vehicle is more likely if the speed of subject driver is higher and more surrounding vehicles are present. Interestingly, if the difference with passing vehicle speed is high, the likelihood of subject driver’s acceleration is lower, consistent with expectation that if such differences are too high, the subject driver may be minimally affected. The study provides new evidence that drivers’ social interactions can change traffic flow and implications of the study results are discussed.     

The ability of young,middle-aged and older drivers to inhibit visual and auditory distraction in a driving simulator task

Driver distraction is one major cause of road traffic accidents. In order to avoid distraction-related accidents it is important to inhibit irrelevant stimuli and unnecessary responses to distractors and to focus on the driving task, especially when unpredictable critical events occur. Since inhibition is a cognitive function that develops until young adulthood and decreases with increasing age, young and older drivers should be more susceptible to distraction than middle-aged drivers. Using a driving simulation, the present study investigated effects of acoustic and visual distracting stimuli on responses to critical events (flashing up brake lights of a car ahead) in young, middle-aged, and older drivers. The task difficulty was varied in three conditions, in which distractors could either be ignored (perception-only), or required a simple response (detection) or a complex Go-/NoGo-response (discrimination). Response times and error rates to the critical event increased when a simultaneous reaction to the distractor was required. This distraction effect was most pronounced in the discrimination condition, in which the participants had to respond to some of the distracting stimuli and to inhibit responses to some other stimuli. Visual distractors had a stronger impact than acoustic ones. While middle-aged drivers managed distractor inhibition even in difficult tasks quite well (i.e., when responses to distracting stimuli had to be suppressed), response times of young and old drivers increased significantly, especially when distractor stimuli had to be ignored. The results demonstrate the high impact of distraction on driving performance in critical traffic situations and indicate a driving-related inhibition deficit in young and old drivers.     

Influence of traffic conditions on driver behavior before making a right turn at an intersection: Analysis of driver behavior based on measured data on an actual road

This paper describes an investigation of the influence of the position of a forward vehicle and following vehicle on the onset of driver preparatory behavior before making a right turn at an intersection. Four experimental vehicles with various sensors and a driving recorder system were developed to measure driver behavior before making a right turn at a specific intersection on a public road. The experimental term was eight weeks to collect data on natural driving maneuvers. The relationships between the remaining distances to the center of the intersection when releasing the accelerator pedal, moving the right foot to cover the brake pedal, and activating the turn signal and the relative distances from the forward and following vehicles were analyzed based on the measured data. The time it took to reach the center of the turn and the driving speed when each behavioral event occurred were also evaluated from the viewpoint of the relative position between the driver’s vehicle and the leading or following vehicles. The results suggest that the drivers approached the target intersection in a car-following condition, and that the positions of the front and rear vehicles and the vehicle velocity influence the onset location and timing of releasing the accelerator pedal and covering the brake pedal. Drivers began to decelerate closer to the center of the intersection when they approached the intersection close to a leading or following vehicle at a reduced driving speed. However, these influences were not reflected in the turn signal operation, indicating that drivers intend to make a right turn at a constant location while approaching a target intersection and that intention appears in the turn signal activation. The findings of this observational study imply that the method of providing route guidance instruction, in which the traffic conditions surrounding the driver’s vehicle are taken into consideration, is effective in reducing driver errors in receiving instruction and following the correct route. The results also indicate that measuring and accumulating different behavioral indices based on traffic conditions contribute to determining the criteria for the presentation timing just before reaching the intersection, which can assist drivers in preparing to make a right turn at a usual location. Driver decelerating maneuvers are used while driving without leading or following vehicles and while driving with a lead and/or following vehicle at long range, and driver turn signal operations are used when approaching an intersection under close car-following conditions.