How does emotional intelligence predict driving behaviors among non-commercial drivers?

Dangerous driving behaviors have been found to be a leading contributor to vehicle crashes and fatalities, with more than 2.7 million people injured and 36,560 people killed in the United States in 2018 (NHTSA, 2020). Drivers’ emotions have been found to be among the leading contributors to dangerous driving behaviors. Emotions can be measured and understood through one’s emotional intelligence (EI). Previous research has confirmed the relationship between EI and dangerous driving behaviors among general driving populations in limited scope. This study analyzed dangerous driving behaviors (e.g., aggressive driving) among non-commercial US drivers. 615 US drivers ages 18 to 65 (M = 31.14, SD = 11.15) with valid US driver’s licenses (non-commercial) participated in this study. Participants completed an online survey through Qualtrics that included the Trait Emotional Intelligence Questionnaire (TEIQue-SF) to measure different dimensions of EI and the Dula Dangerous Driving Index (DDDI) and the Driving Behavior Questionnaire (DBQ) to measure dangerous driving behaviors. Furthermore, participants reported their demographic information, including age, sex, and location. Correlation analysis revealed that significant associations exist between dangerous driving behaviors and EI. The emotionality component of EI was found to be the strongest predictor of dangerous driving behaviors. The findings concluded that participants with higher EI scores engaged in less dangerous driving behavior, resulting in fewer crashes and fatalities. Thus, promoting and improving EI may be useful in preventing risky driving among non-commercial drivers. Incorporating emotional intelligence education in driver’s education, workplace training, and licensing procedures can be helpful to develop safer drivers. Further research is needed to investigate commercial drivers’ behaviors in relation to EI.     

Young drivers’ perception of hazards: Variation with experience and day versus night

Young novice drivers have a relatively high crash risk for several years following initial licensing, and while all drivers are at greater risk at night, the night-time increase is greater for inexperienced drivers. Poor hazard perception has been identified as an important contributor to inexperienced drivers’ risk, but research on day-night differences in hazard perception for drivers varying in experience is lacking. This exploratory study investigated the nature of hazards reported by young inexperienced drivers versus more experienced and slightly older drivers. Hazards were not pre-identified by researchers; participants were simply provided with a general definition of ‘hazard’. Analysis focused on how experience level affected qualitative differences in the kinds of hazards reported, with particular focus on day-night differences.The 53 participants ranged in driving experience from learners through to 5+years post licensing, and in age from 16 to 30 years. They viewed 14 day- and night-time video clips of a diverse range of driving situations, pausing the video whenever they identified a hazard and then explaining why they had paused it at that point. Their responses were recorded. Content analysis of responses showed that more experienced drivers reported visibility-related hazards significantly more often than inexperienced ones, and significantly more so at night. They also commented significantly more on hazards related to tight bends in the road and significantly less on hazards concerning compliance with rules. Comments tended to be fewer with higher vehicle speeds, particularly for the least experienced drivers.Results are discussed in terms of how experience-related differences in drivers’ cognitive schemata and mental models are likely to affect hazard perception and crash risk, particularly at night. Some implications for driver training and license testing are suggested.     

Capturing the effects of texting on young drivers behaviour based on copula and Gaussian Mixture Models

This research effort aims to investigate the impact of texting on young drivers' behavior and safety based on data from driving simulator experiments, for different driving contexts, like motorways, urban and rural roads, during daytime and night, and for alternative weather conditions (‘clear sky’ and rain). The study offers a complete and comprehensive investigation of the effects of texting on driving behavior, able to provide evidence on policy-making. For the purposes of this study, a driving simulator experiment was carried out where 34 young participants drove predefined driving scenarios. Initially, multivariate copula analysis was used in order to explore statistical inferences among variables, especially since it retains a parametric specification for bivariate dependencies and allows testing of several parametric structures to characterize them. Secondly, alternative copula configurations were tested, which showed that texting and other road and environmental characteristics affect young drivers behavior and in particular more than one outcome can occur at the same time. Finally, Gaussian Mixture Modeling (GMM) was employed, demonstrating that the variables' pairs that presented the strongest correlations were lane departure and speed, as well as speed and reaction time. GMMs application showed that drivers using mobile phones who were involved in a collision presented a different driving behavior compared to the drivers who were occupied but were not involved in a collision.     

Sleep loss and change detection in driving scenes

Driver sleepiness is a significant road safety problem. Sleep-related crashes occur on both urban and rural roads, yet to date driver-sleepiness research has focused on understanding impairment in rural and motorway driving. The ability to detect changes is an attention and awareness skill vital for everyday safe driving. Previous research has demonstrated that person states, such as age or motivation, influence susceptibility to change blindness (i.e., failure or delay in detecting changes). The current work considers whether sleepiness increases the likelihood of change blindness within urban and rural driving contexts. Twenty fully-licenced drivers completed a change detection ‘flicker’ task twice in a counterbalanced design: once following a normal night of sleep (7–8 h) and once following sleep restriction (5 h). Change detection accuracy and response time were recorded while eye movements were continuously tracked. Accuracy was not significantly affected by sleep loss; however, following sleep loss there was some evidence of slowed change detection responses to urban images, but faster responses for rural images. Visual scanning across the images remained consistent between sleep conditions, resulting in no difference in the probability of fixating on the change target. Overall, the results suggest that sleep loss has minimal impact on change detection accuracy and visual scanning for changes in driving scenes. However, a subtle difference in response time to change detection between urban and rural images indicates that change blindness may have implications for sleep-related crashes in more visually complex urban environments. Further research is needed to confirm this finding.     

Factors influencing intentions to text while driving among Polish drivers

Previous research has found that using a mobile phone while driving has a detrimental effect on driver safety and performance. The present study used the Theory of Planned Behaviour (TPB) to examine a number of factors thought to be related to intentions to send or read text messages while driving. A total of 298 Polish drivers completed a survey that included measures of the TPB components related to intentions to send or read text messages in four different scenarios. The scenarios differed according to whether or not the drivers were waiting at traffic lights or travelling at 100 km/h and according to whether or not they were under time pressure. The research found that Attitudes and Perceived Behavioural Control were positive predictors of general intentions to use a mobile phone while driving. Similarly, Attitudes consistently predicted intentions to send and read text messages across the four scenarios. The findings of this study could be utilised for developing an educational campaign aimed at promoting more positive attitudes toward road safety and at reducing intentions to use mobile phones while driving.     

Peer passenger identity and passenger pressure on young drivers’ speeding intentions

Young drivers, aged 17-24 years, have the highest fatality rate in Australia. It is believed that part of this risk is due to pressure from peer passengers to engage in speeding; which may be active (i.e., verbal encouragement) or passive (i.e., perceived pressure on the part of the driver). The Theory of Planned Behaviour (TPB) was used to investigate this impact of peer passengers on young drivers, particularly the influence of the type of peer pressure and a driver’s level of identification with their passengers. A scenario-based questionnaire was constructed, informed by focus groups and pilot studies, and distributed to university students (N = 398). The questionnaire measured participants’ intentions and the TPB constructs, including two components of perceived behaviour control, within a baseline scenario as well as an experimental scenario in which the variables of type of pressure and identification were manipulated. Consistent with the hypotheses, the study found that attitudes and self-efficacy significantly predicted intentions over and above the variance explained by the sociodemographic variables of age, gender, self-esteem, sensation seeking, as well as past behaviour and exposure. Across the scenarios, attitudes explained between 4.3% and 14.5%, while self-efficacy to refrain from speeding explained between 4.9% and 17.1%, of the unique variance in intentions to speed. However, contrary to expectations, intentions to speed were found to be higher in the “no passenger” than “passenger present” conditions, although this finding is not completely inconsistent with recent literature. A high level of identification with passengers led to higher intentions to speed than low identification as expected, but, inconsistent with expectations, different types of pressure (i.e., active versus passive) did not influence intentions to speed.     

Implementation of automatic speed enforcement: Covariation with young drivers’ reported speeding behaviour and motivations

IntroductionSpeeding represents one of the main causes of road crashes worldwide, particularly among young drivers who are over-represented in road-crash statistics. For promoting road safety in France, an automatic speed enforcement (ASE) system was introduced late 2002.ObjectiveIn order to examine its efficiency on speeding and its motivations, we compared young drivers’ intentions and beliefs about speeding between the introduction of ASE (T1) and its completion in 2005 (T2) via a large survey based on the extended Theory of Planned Behaviour (TPB). We assumed the introduction of the ASE would covariate with a reduction in intention to speeding between T1 and T2 and a change in the extended TPB factors according to gender and driving experience.MethodOne thousand one hundred and ninety-two young participants (49.7% men) divided into novice, beginner, and more-experienced drivers filled in a questionnaire based on the extended TPB about their driving behaviour and history at T1 and 24 months later (T2).ResultsMen, beginner and more-experienced drivers expressed more intention to speeding within the next 12 months at T1 and showed a higher decrease in intention between T1 and T2 as compared to women and novice drivers. The extended TPB accounted for 59% of the variance in the decrease of the intention to speeding. Its main predictors were: lower perceived behavioural control over speeding, less social pressure, lower perceived similarity with the prototypical deviant driver, and higher comparative optimism. Secondly, slightly more positive behavioural beliefs and more negative outcome evaluations predicted this decrease.ConclusionPractical implications of the findings for road safety are discussed.     

Behavioural Change Techniques used in road safety interventions for young people

IntroductionDeath and injury from road traffic is a public health problem worldwide and accordingly there is substantial interest and investment in developing interventions to change road user behaviour. Alongside this, there is growing awareness of the need to evaluate interventions and to identify the most effective mechanisms by which behaviour can be changed. Progress has been hindered due to lack of a common taxonomy with which to define specific techniques used in attempts to change behaviour.ObjectiveBehavioural Change Techniques (BCTs) have been successfully deployed to change a range of different health behaviours. This paper defines a series of BCTs that can be applied in the road safety setting and asks which ones are found in road safety interventions for young road users?MethodAbraham and Michie (2008) identified twenty-six techniques used in behavioural change interventions. These BCTs, plus one other adapted from forensic psychology, are classified into nine groupings. Six educational road safety interventions commonly used in the UK with pre-drivers and young, novice drivers are characterised in terms of the BCTs they employ.ResultsOnly a small subset of BCTs are employed in most of the interventions. They concentrate primarily on increasing awareness of the risks associated with a particular behaviour, and the severity of the potential adverse consequences.ConclusionRecommendations are given for improving the effectiveness of road safety interventions for young people including young, novice drivers by increasing the range of BCTs deployed.     

Anger,aggression, and risky behavior: a comparison of high and low anger drivers

This research tested hypotheses from state-trait anger theory applied to anger while driving. High and low anger drivers drove equally often and as many miles, but high anger drivers reported more frequent and intense anger and more aggression and risky behavior in daily driving, greater anger in frequently occurring situations, more frequent close calls and moving violations, and greater use of hostile/aggressive and less adaptive/constructive ways of expressing anger. In low impedance simulations, groups did not differ on state anger or aggression; however, high anger drivers reported greater state anger and verbal and physical aggression in high impedance simulations. High anger drivers drove at higher speeds in low impedance simulations and had shorter times and distances to collision and were twice as likely to crash in high impedance simulations. Additionally, high anger drivers were more generally angry. Hypotheses were generally supported, and few gender differences were noted for anger and aggression.     

Electrocortical signs of arousal in response to darkness and the assessment of type A behavior in professional drivers with and without cardiovascular disease

Background and Aims  In night driving, the fatal accident rate is about four times that in daytime. There is a lack of published studies of the effect of darkness on electrocortical responses in professional drivers (PD). Aim: Assessing relations between electroencephalographic (EEG) reactions to enforced darkness reminiscent of night driving, and untoward behavioral response patterns, notably Type A behavior. Methods  PD: 13 with ischemic heart disease, 12 hypertensives (HTN), 10 borderline hypertensives and 34 normotensives, and 23 non-PD controls. Five minutes of electroencephalographic recording with eyes closed, and subsequently 3 minutes exposure to darkness. EEG parameters were: alpha abundance, amplitude and frequent. Type A behavior (TAB) was assessed by observation and by questionnaire. Results  Alpha abundance diminished significantly for darkness compared to spontaneous recording for all groups. No between-group differences were found for EEG. There were no significant differences in EEG between drivers with IHD or HTN taking versus not taking centrally active β-blockers. Drivers with IHD were the only group to show significant increase in dominant α frequency at darkness. The IHD group also had the highest TAB questionnaire scores and the heaviest exposure to professional driving. Type A scores were significantly correlated with dominantt alpha frequency during darkness. Low availability of attachment and special driving hazards best predicted TAB scores in driven. There was a significance between group difference with respect to Symbolic Aversiveness at the work place comparing each driver group with the non-PD control group. Conclusions  Exposure to darkness reminiscent of night driving can elicit central arousal, in conflict with circadian rhythm, and in combination with other driving hazards which contribute to symbolic aversiveness, the essence of driving. And low availability of social attachment could contribute to sustained, and in turn to the development of Type A behavior in professional drivers.