The choice to text and drive in younger drivers: behavior may shape attitude

Following a previous study that reported a large number of young adult drivers text and drive, the current study investigated this behavior by looking at patterns of use and driver assessment of the risk of the behavior. The data from the current study converge with and extended the previous work showing 70% of the 348 young adult drivers surveyed report initiating texts while driving while higher numbers reply to texts (81%) and read texts (92%) while driving. Additional drivers also report doing these behaviors, but only while stopped in traffic, showing only 2% never text and drive under any circumstances. The drivers indicated that they perceived these behaviors to be very risky and riskier than talking on a cell phone while driving, but perception of risk was a very weak predictor of behavior (for initiating texts) or had no effect on texting (for replying or reading texts while driving). In addition, a factor analysis of the perception of road conditions while texting revealed that making the choice to engage in texting (initiating) led drivers to perceive road conditions as being safer than if they replied to a text or read a text, suggesting that choosing to engage in the behavior itself changes attitudes toward risk.     

An observational study of driving distractions on urban roads in Spain

The present research investigated the prevalence of driver engagement in secondary tasks and whether there were any differences by age and gender, as well as day of the week and time of the day. Two independent researchers observed 6578 drivers at nine randomly selected urban locations in Girona, Spain. Nearly 20% of the drivers observed were engaged in some type of secondary task, with the most common being: conversing with a passenger (11.1%), smoking (3.7%) and talking on a handheld mobile phone (1.3%). Surprisingly there were no differences by gender, but there were age-related differences with younger drivers being more frequently observed engaged in a number of different types of secondary tasks while driving (i.e. drinking, talking on a handheld mobile phone, and texting or keying numbers). Logistic regression showed that younger drivers, and to a lesser extent middle-age drivers, were significantly more likely to be observed engaged in a technological distraction than older drivers. Conversely, non-technological distractions were significantly predicted by day of the week, time of the day and location. A substantial number of the drivers observed in this study were putting themselves at an increased risk of becoming involved in a crash by engaging in non-driving related tasks at the same time as driving. Furthermore, the higher crash rate among young drivers may be partially accounted for by their more frequent engagement in some types of secondary tasks while driving.     

Differential impact of personality traits on distracted driving behaviors in teens and older adults

ObjectiveTo determine the impact of personality on distracted driving behaviors.MethodParticipants included 120 drivers (48 teens, 72 older adults) who completed the 45-item Big Five Personality questionnaire assessing self-reported personality factors and the Questionnaire Assessing Distracted Driving (QUADD) assessing the frequency of distracted driving behaviors. Associations for all five personality traits with each outcome (e.g., number of times texting on the phone, talking on the phone, and interacting with the phone while driving) were analyzed separately for teens and older adults using negative binomial or Poisson regressions that controlled for age, gender and education.ResultsIn teens, higher levels of openness and conscientiousness were predictive of greater reported texting frequency and interacting with a phone while driving, while lower levels of agreeableness was predictive of fewer reported instances of texting and interacting with a phone while driving. In older adults, greater extraversion was predictive of greater reported talking on and interacting with a phone while driving. Other personality factors were not significantly associated with distracted driving behaviors.ConclusionsPersonality traits may be important predictors of distracted driving behaviors, though specific traits associated with distracted driving may vary across age groups. The relationship between personality and distracted driving behaviors provides a unique opportunity to target drivers who are more likely to engage in distracted driving behavior, thereby increasing the effectiveness of educational campaigns and improving driving safety.     

Do German drivers use their smartphones safely?—Not really!

Research in the laboratory as well as in naturalistic driving studies has shown that texting while driving seems to be the most dangerous driver distraction. However, there is still some discussion about the extent to which drivers adapt their behavior to the traffic situation. Accordingly, they might use their phones only in easy driving situations but refrain from doing so when driving becomes more demanding. For Germany, no reliable data on these topics could be found although overall smartphone use has also increased exponentially in this country. As observational studies have proven to be an effective means to gather these data, such a study was done observing 11,837 drivers in three big German cities (Braunschweig, Hannover, Berlin) during daytime. An alarmingly high rate of texting while driving was found (4.5%) as compared to other international studies. This was even more frequent than the use of handheld (2.2%) and hands-free (1.7%) phones combined. Thus, there seems to be a special problem in Germany with texting which should be further examined as this activity is highly distracting. Finally, there was some indication that drivers adapt their secondary task activities to the requirements of the driving task (e.g. somewhat less texting when moving than when stationary at a red traffic light). However, these adaptations were not very strong. Thus, drivers seem to underestimate the dangers due to distraction. This could be a starting point for countermeasures which increase this awareness of danger.     

Engrossed in conversation: the impact of cell phones on simulated driving performance

The current study examined the effects of cognitively distracting tasks on various measures of driving performance. Thirty-six college students with a median of 6 years of driving experience completed a driving history questionnaire and four simulated driving scenarios. The distraction tasks consisted of responding to a signal detection task and engaging in a simulated cell phone conversation. Driving performance was measured in terms of four categories of behavior: traffic violations (e.g., speeding, running stop signs), driving maintenance (e.g., standard deviation of lane position), attention lapses (e.g., stops at green lights, failure to visually scan for intersection traffic), and response time (e.g., time to step on brake in response to a pop-up event). Performance was significantly impacted in all four categories when drivers were concurrently talking on a hands-free phone. Performance on the signal detection task was poor and not significantly impacted by the phone task, suggesting that considerably less attention was paid to detecting these peripheral signals. However, the signal detection task did interact with the phone task on measures of average speed, speed variability, attention lapses, and reaction time. The findings lend further empirical support of the dangers of drivers being distracted by cell phone conversations.     

Impact of distracted driving on safety and traffic flow

Studies have documented a link between distracted driving and diminished safety; however, an association between distracted driving and traffic congestion has not been investigated in depth. The present study examined the behavior of teens and young adults operating a driving simulator while engaged in various distractions (i.e., cell phone, texting, and undistracted) and driving conditions (i.e., free flow, stable flow, and oversaturation). Seventy five participants 16–25 years of age (split into 2 groups: novice drivers and young adults) drove a STISIM simulator three times, each time with one of three randomly presented distractions. Each drive was designed to represent daytime scenery on a 4 lane divided roadway and included three equal roadway portions representing Levels of Service (LOS) A, C, and E as defined in the 2000 Highway Capacity Manual. Participants also completed questionnaires documenting demographics and driving history. Both safety and traffic flow related driving outcomes were considered. A Repeated Measures Multivariate Analysis of Variance was employed to analyze continuous outcome variables and a Generalized Estimate Equation (GEE) Poisson model was used to analyze count variables. Results revealed that, in general more lane deviations and crashes occurred during texting. Distraction (in most cases, text messaging) had a significantly negative impact on traffic flow, such that participants exhibited greater fluctuation in speed, changed lanes significantly fewer times, and took longer to complete the scenario. In turn, more simulated vehicles passed the participant drivers while they were texting or talking on a cell phone than while undistracted. The results indicate that distracted driving, particularly texting, may lead to reduced safety and traffic flow, thus having a negative impact on traffic operations. No significant differences were detected between age groups, suggesting that all drivers, regardless of age, may drive in a manner that impacts safety and traffic flow negatively when distracted.     

Longitudinal jerk and celeration as measures of safety in bus rapid transit drivers in Tehran

Abstract

Traditionally, analysis of individual differences in road traffic crash risk has relied on after the fact crash data. Nowadays with the help of technologies like GPS, new measures are developed to assess driving risk, inferred from naturalistic driving behaviour of drivers. In this study, two main ways of modelling driver behaviour in naturalistic driving research were discussed and compared to each other. For this purpose, 176 Bus Rapid Transit (BRT) drivers were investigated during their normal driving on Tehran BRT routes. Their speed was continuously recorded by a smart phone app from which was derived deceleration, jerk and celeration measures. Analysis showed that all of the proposed measures had positive correlations with culpable crashes and that one of the jerk variables yielded the highest correlation. Measurements of speed derivatives like jerk and celeration can help to identify dangerous driving styles in public transportation and reduce the number of crashes. Although the results of this study are encouraging, further studies for longer periods are needed to improve the reliability of the measures.     

Prevalence of texting while driving and other risky driving behaviors among young people in Ontario,Canada: Evidence from 2012 and 2014

This paper reports on the prevalence of texting while driving and other risky driving behaviors by age and gender in two large samples of youth aged 16–19 years in Ontario, Canada. In Study 1 (N = 6133), we found that males reported more frequent texting while driving and speeding than females and, in terms of age, sixteen year olds reported frequent texting while driving than older participants. In Study 2 (N = 4450), which was conducted two years later, males again reported more frequent texting while driving, however there was no difference in the rate of talking on the phone while driving among males and females. Participants also reported on experiences that led to a significant reduction in their texting while driving. The most common reasons were the perceived danger of texting while driving, laws and fines against texting while driving, and observing close-calls and accidents experienced by other people. The results of both studies suggest that driving-related risk-taking behaviors co-occur and that young passengers in vehicles, including 14 and 15 year olds, are bystanders to texting while driving. Finally, there was a substantial decline in the prevalence of texting while driving across the studies. In Study 1, 27% of participants reported “sometimes” to “almost always” texting while driving compared to 6% of participants in Study 2. Limitations and implications for public campaigns targeted youth distracted driving are discussed.     

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

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18–26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 s in time headway when a driver is engaged in hands-free phone conversation and a 0.75 s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.     

Older driver distraction: A naturalistic study of behaviour at intersections

This study examined older driver engagement in distracting behaviours (secondary activities) at intersections using naturalistic driving data from a larger study based in Melbourne, Australia. Of interest was whether engagement in secondary activities at intersections was influenced by factors such as driver gender and situational variables, in particular, those relating to the complexity of the driving environment. Specifically we expected that when making left/right turns, older drivers would reduce the proportion of time engaged in secondary behaviours at intersections which required gap judgements (partly controlled or uncontrolled) compared with intersections that were fully controlled by traffic signals. Consideration was given to engagement in secondary activity with hands off the wheel and when the vehicle was moving versus stationary. Older drivers aged between 65 and 83 years drove an instrumented vehicle (IV) on their regular trips for approximately two weeks. The IV was equipped with a video camera system, enabling recording of the road environment and driver and a data acquisition unit, enabling recording of trip distance, vehicle speed, braking, accelerating, steering and indicator use. Driving experience and demographics were collected and functional abilities were assessed using the Useful Field of View (UFOV), Trail Making Test B, Mini Mental Status Examination (MMSE), visual acuity and contrast sensitivity. The study yielded a total of 371 trips with 4493 km (99.8 h) of naturalistic driving data including 1396 left and right turns. Trips were randomly selected from the dataset and in-depth analysis was conducted on 200 intersection manoeuvres (approximately 50% left turns, 50% right turns). The most frequently observed secondary activities were scratching/grooming (42.5%), talking/singing (30.2%) and manipulating the vehicle control panel (12.2%). Glances “off road” 2 s or longer were associated with reading, reaching and manipulation of the vehicle control panel. Hands off the wheel was associated with reading. Key parameters associated with the percent of intersection time that drivers engaged in secondary activities were intersection complexity, vehicle status (moving vs. stationary) and traffic density. In conclusion, older drivers appeared to engage selectively in secondary activities according to roadway/driving situations, supporting the notion that drivers self-regulate by engaging in secondary tasks less frequently when the driving task is more challenging compared with less challenging manoeuvres.     

A parametric duration model of the reaction times of drivers distracted by mobile phone conversations

The use of mobile phones while driving is more prevalent among young drivers—a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q advanced driving simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver's peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21–26 years old and split evenly by gender. Drivers’ reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver's age, license type (provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted presents a significant and measurable safety concern that will undoubtedly persist unless mitigated.     

A meta-analysis of the effects of cell phones on driver performance

The empirical basis for legislation to limit cell phones while driving is addressed. A comprehensive meta-analysis of the effects of cell phones on driving performance was performed. A total of 33 studies collected through 2007 that met inclusion criteria yielded 94 effect size estimates, with a total sample size of approximately 2000 participants. The dependent variables of reaction time, lateral vehicle control, headway and speed and the moderating variables of research setting (i.e., laboratory, simulator, on-road), conversation target (passenger, cell phone) and conversation type (cognitive task, naturalistic) were coded. Reaction time (RT) to events and stimuli while talking produced the largest performance decrements. Handheld and hands-free phones produced similar RT decrements. Overall, a mean increase in RT of .25s was found to all types of phone-related tasks. Observed performance decrements probably underestimate the true behavior of drivers with mobile phones in their own vehicles. In addition, drivers using either phone type do not appreciably compensate by giving greater headway or reducing speed. Tests for moderator effects on RT and speed found no statistically significant effect size differences across laboratory, driving simulation and on-road research settings. The implications of the results for legislation and future research are considered.     

Effect of North Carolina's restriction on teenage driver cell phone use two years after implementation

A majority of states now restrict teenagers from using a mobile communication device while driving. The effect of these restrictions is largely unknown. In a previous study, we found North Carolina's teenage driver cell phone restriction had little influence on young driver behavior four months after the law took effect (Foss et al., 2009). The goal of the present study was to examine the longer-term effect of North Carolina's cell phone restriction. It was expected that compliance with the restriction would increase, as awareness of the restriction grew over time. Teenagers were observed at high schools in North Carolina approximately two years after the law was implemented. Observations were also conducted in South Carolina, which did not have a cell phone restriction. In both states, there was a broad decrease in cell phone use. A logistic regression analysis showed the decrease in cell phone use did not significantly differ between the two states. Although hand-held cell phone use decreased, there was an increase in the likelihood that drivers in North Carolina were observed physically manipulating a phone. Finally, a mail survey of teenagers in North Carolina showed awareness for the cell phone restriction now stands at 78% among licensed teens. Overall, the findings suggest North Carolina's cell phone restriction has had no long-term effect on the behavior of teenage drivers. Moreover, it appears many teenage drivers may be shifting from talking on a phone to texting.     

Texting while driving: Is speech-based text entry less risky than handheld text entry?

Research indicates that using a cell phone to talk or text while maneuvering a vehicle impairs driving performance. However, few published studies directly compare the distracting effects of texting using a hands-free (i.e., speech-based interface) versus handheld cell phone, which is an important issue for legislation, automotive interface design and driving safety training. This study compared the effect of speech-based versus handheld text entries on simulated driving performance by asking participants to perform a car following task while controlling the duration of a secondary text-entry task. Results showed that both speech-based and handheld text entries impaired driving performance relative to the drive-only condition by causing more variation in speed and lane position. Handheld text entry also increased the brake response time and increased variation in headway distance. Text entry using a speech-based cell phone was less detrimental to driving performance than handheld text entry. Nevertheless, the speech-based text entry task still significantly impaired driving compared to the drive-only condition. These results suggest that speech-based text entry disrupts driving, but reduces the level of performance interference compared to text entry with a handheld device. In addition, the difference in the distraction effect caused by speech-based and handheld text entry is not simply due to the difference in task duration.     

An analysis of driving and working hour on commercial motor vehicle driver safety using naturalistic data collection

Current hours-of-service (HOS) regulations prescribe limits to commercial motor vehicle (CMV) drivers’ operating hours. By using naturalistic-data-collection, researchers were able to assess activities performed in the 14-h workday and the relationship between safety-critical events (SCEs) and driving hours, work hours, and breaks. The data used in the analyses were collected in the Naturalistic Truck Driving Study and included 97 drivers and about 735,000 miles of continuous driving data. An assessment of the drivers’ workday determined that, on average, drivers spent 66% of their shift driving, 23% in non-driving work, and 11% resting. Analyses evaluating the relationship between driving hours (i.e., driving only) and SCE risk found a time-on-task effect across hours, with no significant difference in safety outcomes between 11th driving hour and driving hours 8, 9 or 10. Analyses on work hours (i.e., driving in addition to non-driving work) found that risk of being involved in an SCE generally increased as work hours increased. This suggests that time-on-task effects may not be related to driving hours alone, but implies an interaction between driving hours and work hours: if a driver begins the day with several hours of non-driving work, followed by driving that goes deep into the 14-h workday, SCE risk was found to increase. Breaks from driving were found to be beneficial in reducing SCEs (during 1-h window after a break) and were effective in counteracting the negative effects of time-on-task.     

Effects of practice, age, and task demands, on interference from a phone task while driving

Experimental research on the effects of cellular phone conversations on driving indicates that the phone task interferes with many driving-related functions, especially with older drivers. Unfortunately in past research (1) the dual task conditions were not repeated in order to test for learning, (2) the 'phone tasks' were not representative of real conversations, and (3) most often both the driving and the phone tasks were experimenter-paced. In real driving drivers learn to time-share various tasks, they can pace their driving to accommodate the demands of a phone conversation, and they can even partially pace the phone conversation to accommodate the driving demands. The present study was designed to better simulate real driving conditions by providing a simulated driving environment with repeated experiences of driving while carrying two different hands-free 'phone' tasks with different proximities to real conversations. In the course of five sessions of driving and using the phone, there was a learning effect on most of the driving measures. In addition, the interference from the phone task on many of the driving tasks diminished over time as expected. Finally, the interference effects were greater when the phone task was the often-used artificial math operations task than when it was an emotionally involving conversation, when the driving demands were greater, and when the drivers were older. Thus, the deleterious effects of conversing on the phone are very real initially, but may not be as severe with continued practice at the dual task, especially for drivers who are not old.     

Stuck in the 70s: The role of social norms in distracted driving

Successful campaigns to end distracted driving must understand prevailing social norms for behaviors such as texting and phoning while driving. The current work examined this issue by asking younger drivers to read car crash scenarios and rate the responsibility of the driver for the crash, and to levy fines and assign jail time, as a function of whether the driver was attentive, had been drinking, or was distracted by phoning or texting. In the first experiment, ratings were performed in the absence of injunctive norm information (laws against drunk and distracted driving). In the second experiment, injunctive norm information was included. Impaired drivers were viewed as more responsible in both experiments, with texting drivers viewed as the most responsible. However, drunk drivers received the most fines and jail time. When compared to data from the 1970s, the results show that anti-drunk driving campaigns have changed how younger drivers view drunk driving, but that norms have not yet changed for distracted driving, despite consistent results showing they know the risk of driving distracted. Implications for social norm distracted driving campaigns are discussed.     

Concealing their communication: Exploring psychosocial predictors of young drivers’ intentions and engagement in concealed texting

Making a conscious effort to hide the fact that you are texting while driving (i.e., concealed texting) is a deliberate and risky behaviour involving attention diverted away from the road. As the most frequent users of text messaging services and mobile phones while driving, young people appear at heightened risk of crashing from engaging in this behaviour. This study investigated the phenomenon of concealed texting while driving, and utilised an extended Theory of Planned Behaviour (TPB) including the additional predictors of moral norm, mobile phone involvement, and anticipated regret to predict young drivers’ intentions and subsequent behaviour. Participants (n = 171) were aged 17–25 years, owned a mobile phone, and had a current driver's licence. Participants completed a questionnaire measuring their intention to conceal texting while driving, and a follow-up questionnaire a week later to report their behavioural engagement. The results of hierarchical multiple regression analyses showed overall support for the predictive utility of the TPB with the standard constructs accounting for 69% of variance in drivers’ intentions, and the extended predictors contributing an additional 6% of variance in intentions over and above the standard constructs. Attitude, subjective norm, PBC, moral norm, and mobile phone involvement emerged as significant predictors of intentions; and intention was the only significant predictor of drivers’ self-reported behaviour. These constructs can provide insight into key focal points for countermeasures including advertising and other public education strategies aimed at influencing young drivers to reconsider their engagement in this risky behaviour.     

Gender differences in psychosocial predictors of texting while driving

A sample of 158 male and 357 female college students at a midwestern university participated in an on-line study of psychosocial motives for texting while driving. Men and women did not differ in self-reported ratings of how often they texted while driving. However, more women sent texts of less than a sentence while more men sent texts of 1–5 sentences. More women than men said they would quit texting while driving due to police warnings, receiving information about texting dangers, being shown graphic pictures of texting accidents, and being in a car accident. A hierarchical regression for men’s data revealed that lower levels of feeling distracted by texting while driving (20% of the variance), higher levels of cell phone dependence (11.5% of the variance), risky behavioral tendencies (6.5% of the variance) and impulsivity (2.3%) of the variance) were significantly associated with more texting while driving (total model variance = 42%). A separate regression for women revealed that higher levels of cell phone dependence (10.4% of the variance), risky behavioral tendencies (9.9% of the variance), texting distractibility (6.2%), crash risk estimates (2.2% of the variance) and driving confidence (1.3% of the variance) were significantly associated with more texting while driving (total model variance = 31%.) Friendship potential and need for intimacy were not related to men’s or women’s texting while driving. Implications of the results for gender-specific prevention strategies are discussed.     

Pedestrian injuries due to mobile phone use in public places

Research shows that pedestrians, similar to drivers, experience reduced situation awareness, distracted attention and unsafe behavior when talking or texting on their mobile phones. The present study centered on injuries related to mobile phone use among pedestrians. It used data from the US Consumer Product Safety Commission on injuries in hospital emergency rooms from 2004 through 2010. It found that mobile-phone related injuries among pedestrians increased relative to total pedestrian injuries, and paralleled the increase in injuries for drivers, and in 2010 exceeded those for drivers. Pedestrian injuries related to mobile-phone use were higher for males and for people under 31 years old. Using a mobile phone while walking puts pedestrians at risk of accident, injury or death.