Influence of personal mobile phone ringing and usual intention to answer on driver error

Given evidence of effects of mobile phone use on driving, and also legislation, many careful drivers refrain from answering their phones when driving. However, the distracting influence of a call on driving, even in the context of not answering, has not been examined. Furthermore, given that not answering may be contrary to an individual's normal habits, this study examined whether distraction caused by the ignored call varies according to normal intention to answer whilst driving. That is, determining whether the effect is more than a simple matter of noise distraction. Participants were 27 young drivers (18–29 years), all regular mobile users. A Theory of Planned Behaviour questionnaire examined predictors of intention to refrain from answering calls whilst driving. Participants provided their mobile phone number and were instructed not to answer their phone if it were to ring during a driving simulation. The simulation scenario had seven hazards (e.g. car pulling out, pedestrian crossing) with three being immediately preceded by a call. Infractions (e.g. pedestrian collisions, vehicle collisions, speed exceedances) were significantly greater when distracted by call tones than with no distraction. Lower intention to ignore calls whilst driving correlated with a larger effect of distraction, as was feeling unable to control whether one answered whilst driving (Perceived Behavioural Control). The study suggests that even an ignored call can cause significantly increased infractions in simulator driving, with pedestrian collisions and speed exceedances being striking examples. Results are discussed in relation to cognitive demands of inhibiting normal behaviour and to drivers being advised to switch phones off whilst driving.     

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.     

To call or not to call—That is the question (while driving)

We studied whether decisions to engage in cell phone conversation while driving and the consequences of such decisions are related to the driver's age, to the road conditions (demands of the driving task), and to the driver's role in initiating the phone call (i.e. the driver as caller vs. as receiver). Two experiments were performed in a driving simulator in which driver age, road conditions and phone conversation, as a secondary task, were manipulated. Engagement in cell phone conversations, performance in the driving and the conversation tasks, and subjective effort assessment were recorded. In general, drivers were more willing to accept incoming calls than to initiate calls. In addition, older and younger drivers were more susceptible to the deleterious effects of phone conversations while driving than middle aged/experienced drivers. While older drivers were aware of this susceptibility by showing sensitivity to road conditions before deciding whether to engage in a call or not, young drivers showed no such sensitivity. The results can guide the development of young driver training programs and point at the need to develop context-aware management systems of in-vehicle cell phone conversations.     

Why drivers use cell phones and support legislation to restrict this practice

The use of cell phones while driving is ubiquitous, particularly in countries where the practice is legal. However, surveys indicate that most drivers favor legislation to limit the use of mobile devices during the operation of a vehicle. A study was conducted to understand this inconsistency between what drivers do and what they advocate for others. Participants completed a survey about their driving attitudes, abilities, and behaviors. Following previous research, drivers reported using cell phones for benefits such as getting work done. The hypocrisy of using cell phones while advocating restrictions appears to stem from differences in the perceived safety risks of self vs. others’ use of cell phones. Many if not most drivers believe they can drive safely while using mobile devices. However, they lack confidence in others’ ability to drive safely while distracted and believe that others’ use of cell phones is dangerous. The threat to public safety of others’ usage of mobile devices was one of the strongest independent predictors of support for legislation to restrict cell phone use.     

Driving while conversing: Cell phones that distract and passengers who react

The research systematically compared the driving performance and conversational patterns of drivers speaking with in-car passengers, hands-free cell phones, and remote passengers who could see the driver's current driving situation (via a window into a driving simulator). Driving performance suffered during cell phone and remote passenger conversations as compared with in-car passenger conversations and no-conversation controls in terms of their approach speeds, reaction times, and avoidance of road and traffic hazards. Of particular interest was the phenomenon of conversation suppression, the tendency for passengers to slow their rates of conversation as the driver approached a hazard. On some occasions these passengers also offered alerting comments, warning the driver of an approaching hazard. Neither conversation suppression nor alerting comments were present during cell phone conversations. Remote passengers displayed low levels of alerting comments and conversation suppression, but not enough to avoid negative effects on driving performance. The data suggested that conversation modulation was a key factor in maintaining driving performance and that seeing the road and traffic was not sufficient to produce it. A second experiment investigated whether a cell phone modified to emit warning tones could alleviate some of the adverse effects typically associated with cell phone conversations. The modified cell phone produced discourse patterns that were similar to passenger conversations and driving performance nearly as good as that of drivers who were not conversing. This latter finding supported the argument that conversation modulation is a key ingredient in avoiding adverse effects of conversations with drivers, rather than the physical presence of an in-car passenger.     

The effects of perception of risk and importance of answering and initiating a cellular phone call while driving

Recent data suggest that laws banning cellular phone use while driving may not change use patterns, especially among young drivers with high rates of mobile phone adoption. We examined reasons younger drivers choose or do not choose to talk on a phone while driving among a sample of young drivers (n = 276) with very high ownership of cellular phones (over 99%) and a very high use of cellular phones while driving (100% for those that were primary operators of an automobile). Respondents were surveyed for patterns of use, types of call, perceived risk, and motivations for use. The data were analyzed using structural equation modeling (SEM) to explore the relationships between perceived risk of the behavior, emotionality of the call, perceived importance of the call, and how often calls were initiated versus answered. The model suggests that even though people believe that talking on a cellular phone while driving is dangerous, they will tend to initiate a cellular conversation if they believe that the call is important.     

Decisions and actions of distracted drivers at the onset of yellow lights

Driving on an approach to a signalized intersection while distracted is relatively risky, as potential vehicular conflicts and resulting angle collisions tend to be relatively more severe compared to other locations. Given the prevalence and importance of this particular scenario, the objective of this study was to examine the decisions and actions of distracted drivers during the onset of yellow lights. Driving simulator data were obtained from a sample of 69 drivers under baseline and handheld cell phone conditions at the University of Iowa – National Advanced Driving Simulator. Explanatory variables included age, gender, cell phone use, distance to stop-line, and speed. Although there is extensive research on drivers’ responses to yellow traffic signals, the examinations have been conducted from a traditional regression-based approach, which do not necessary provide the underlying relations and patterns among the sampled data. In this paper, we exploit the benefits of both classical statistical inference and data mining techniques to identify the a priori relationships among main effects, non-linearities, and interaction effects. Results suggest that the probability of yellow light running increases with the increase in driving speed at the onset of yellow. Both young (18–25 years) and middle-aged (30–45 years) drivers reveal reduced propensity for yellow light running whilst distracted across the entire speed range, exhibiting possible risk compensation during this critical driving situation. The propensity for yellow light running for both distracted male and female older (50–60 years) drivers is significantly higher. Driver experience captured by age interacts with distraction, resulting in their combined effect having slower physiological response and being distracted particularly risky.     

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.     

Extent and variations in mobile phone use among drivers of heavy vehicles in Denmark

A substantial body of research has shown that use of mobile phones while driving can impair driving performance and increase the risk of being involved in accidents. Similarly, mobile phone use seems to be an increasing activity thus representing a relevant traffic safety issue. This paper investigates the extent and variations in mobile phone use among drivers of heavy vehicles in Denmark. The data was collected through written questionnaires and had a response rate of 58%. It was found that more than 99% of the drivers used mobile phones while driving. Despite a prohibition of hand-held mobile phone use while driving 31% of the drivers reported to do so. Analysis of the variations in usage found a positive significant relationship between driving hours and phone use. A negative linear effect was found between age and phone use. Similarly, a positive significant association was found between the number of stops and the amount of phone use. 0.5% reported that their use of mobile phones had contributed to an accident, while 6% had experienced their mobile phone use causing a dangerous situation. However, 66% reported experiencing dangerous situations because of others road users' mobile phone use. Various implications of the findings are discussed particularly in relation to the drivers with high exposure.     

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.     

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.     

Self-report measures of distractibility as correlates of simulated driving performance

The present study investigated the relationship between self-reported measures pertaining to attention difficulties and simulated driving performance while distracted. Thirty-six licensed drivers participated in a simulator driving task while engaged in a cell phone conversation. The participants completed questionnaires assessing their tendency toward boredom, cognitive failures, and behaviors associated with attention deficit and hyperactivity. Scores on these measures were significantly correlated with various driving outcomes (e.g., speed, lane maintenance, reaction time). Significant relationships were also found between one aspect of boredom proneness (i.e., inability to generate interest or concentrate) and self-reports of past driving behavior (moving violations). The current study may aid in the understanding of how individual differences in driver distractibility may contribute to unsafe driving behaviors and accident involvement. Additionally, such measures may assist in the identification of individuals at risk for committing driving errors due to being easily distracted. The benefits and limitations of conducting and interpreting simulation research 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.     

Factors influencing the use of cellular (mobile) phone during driving and hazards while using it

This study addressed the strategic decisions on not using a mobile phone at all while driving, and phone-related driving hazards among those drivers who do use one, reflecting tactical and operational level processes. A representative sample of 834 licensed drivers who own a mobile phone were interviewed on their phone use and hazards, background factors, and self-image as a driver. Logistic regression models indicated that older age, female gender, smaller amount of driving, and occupation promoted not using a phone at all while driving. Additionally, low skill level and high safety motivation contributed to this decision. Among those who used a phone while driving, exposure to risk in terms of higher mileage and more extensive phone use increased phone-related hazards, as also did young age, leading occupational position, and low safety motivation. Neither gender nor driving skill level had any effect on such self-reported hazards. This study clearly indicates that potential risks of mobile phones are being controlled at many levels, by strategic as well as tactical decisions and, consequently, phone-related accidents have not increased in line with the use of the mobile phones.     

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.     

Psychological predictors of college students’ cell phone use while driving

Despite the known risk, many people talk on a phone while driving. This study explored psychological predictors of cell phone use while driving. College students (final N = 69) completed a survey and predicted their driving performance both with and without a simultaneous phone conversation. Their actual performance on a driving simulator was then assessed. Cell phone use reduced performance on the simulation task. Further, perceiving oneself as good at compensating for driving distractions, overestimating one's performance on the driving simulator, and high illusory control predicted more frequent cell phone use while driving in everyday life. Finally, those who talked more frequently on a phone while driving had poorer real-world driving records. These findings suggest illusory control and positive illusions partly explain driver's decisions of whether to use cell phones 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.     

Mobile phone use-effects of handheld and handsfree phones on driving performance

The study was concerned with effects of handsfree and handheld mobile phone dialling and conversation in simulated driving. In the main experiment dealing with conversation, 48 participants drove a distance of about 70 km on a route which led through urban and rural environments. In the dialling experiment, the participants drove a distance of 15 km on a rural two-lane road. The experimental design was mixed with phone mode as a between-subjects factor and phone use (yes/no) as a within-subjects factor. Performance on a peripheral detection task (PDT) while driving was impaired by dialling and conversation for both phone modes, interpreted as an increase in mental workload. Driving performance was impaired by dialling--lateral position deviation increased in a similar way for both phone modes. Conversation had, however, opposite effects--lateral position deviation decreased in a similar way for both phone modes. Driving speed decreased as an effect of dialling with the greatest effect for handsfree phone mode. Conversation also caused reduced speed, but only for handheld phone mode. The effects on speed can be interpreted as a compensatory effort for the increased mental workload. In spite of the compensatory behaviour, mental workload was still markedly increased by phone use. Subjective effects of dialling and conversation were also analysed. Most participants reported a speed decrease but no effect on lateral position deviation as an effect of dialling or conversation. In the conversation experiment, driving performance was rated better for handsfree than for handheld mode. In the dialling experiment, no difference between the two phone modes appeared.     

Shifting attention across near and far spaces: Implications for the use of hands-free cell phones while driving

In three experiments, participants performed two tasks concurrently during driving. In the peripheral detection task, they responded manually to visual stimuli delivered through a LED placed on the internal rear mirror; in the conversation task, they were engaged in a conversation with a passenger, or through earphone-operated, loudspeaker-operated, or hand-held cell phones. Results showed that drivers were slower at responding to the visual stimuli when conversing through a hand-held cell phone or an earphone-operated cell phone than when conversing through a loudspeaker-operated cell phone or with a passenger. These results suggest that due to the brain coding the space into multiple representations, devices that make phone conversations taking place in the near, personal space make drivers slower at responding to visual stimuli, compared to devices that make the conversation occurring in a far space.