Modeling social rejection,physiological arousal,and peer influence on risky driving among adolescents and young adults

Peer passengers are a significant risk factor for young drivers to experience adverse driving outcomes. However, few studies have manipulated social evaluation contexts and individual susceptibilities to peer influence, such as physiological arousal, to measure effects on driving. The current study explored whether social evaluation affects driving outcomes and if the type of evaluation affects perception of peer norms. Young drivers (N = 75) were randomized to control, social acceptance, or social rejection conditions and observed risky or risk-averse driving norms. Results indicated that peer passengers and peer driving norms, regardless of the social-evaluative context, affected variability in driving outcomes, particularly in intersections. Physiological arousal and perceptions of social acceptance also predicted more variability in driving outcomes. These findings suggest that passengers increase irregular driving patterns, perhaps due to passengers distracting young drivers from road conditions. Further, social acceptance increases the strength of the relationship between the presence of peer passengers and inconsistent driving patterns, indicating that social rewards may precede risky behavior more often than social threats do.     

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.     

Psychological consequences of motor vehicle accidents: A systematic review

People involved in motor vehicle accidents (MVA) are at increased risk for psychological problems. Although the existing literature states that MVAs cause substantial negative mental health effects, summarizing and comparing these effects to understand their consequences could be more explored. This systematic literature review provides an overview of the literature surrounding the psychological consequences of MVAs to summarize and quantify their effects on mental health. The studies published in an English-language journal in the last 20 years (2001–2021) that present psychological consequences of MVAs were included. Web of Science, Scopus, and PubMed databases were used for the literature search. The systematic literature search found 23 eligible studies. After identifying all relevant studies on the topic, we synthesized the applied psychological assessment methods and the psychological consequences of MVAs. Current gaps in the reviewed papers and what future research are needed are also discussed. Results indicated that negative psychological consequences following an MVA are substantial, with all studies pointing to negative consequences in at least one psychopathology. Trauma-related MVA injuries are associated with elevated psychological distress, and MVA-related psychological consequences could have long-term effects if left untreated.     

The dynamics of purchasing an electric vehicle – A prospective longitudinal study of the decision-making process

This paper presents the results of a longitudinal prospective study which followed 113 people interested in the purchase of an electric vehicle for a period of two months. Based on an adapted stage model of self-regulated behavioral change (Bamberg, 2013b), a short online questionnaire with a stage diagnostic and the measurement of central model constructs was administered to the participants every second day. The analysis shows that 85% of transitions between the stages occur along the paths of the stage model. Stage transitions are preceded by increases in goal intentions and implementation intentions during the week before the transition. Intentions are predicted by most of the expected model constructs, but the effects were different on the between-person and the within-person level. The average stage durations are between two and three weeks. Implications of the study for research on stage models and practice are discussed.     

How does glance behavior influence crash and injury risk? A ‘what-if’ counterfactual simulation using crashes and near-crashes from SHRP2

As naturalistic driving data become increasingly available, new analyses are revealing the significance of drivers’ glance behavior in traffic crashes. Due to the rarity of crashes, even in the largest naturalistic datasets, near-crashes are often included in the analyses and used as surrogates for crashes. However, to date we lack a method to assess the extent to which driver glance behavior influences crash and injury risk across both crashes and near-crashes. This paper presents a novel method for estimating crash and injury risk from off-road glance behavior for crashes and near-crashes alike; this method can also be used to evaluate the safety impact of secondary tasks (such as tuning the radio). We apply a ‘what-if’ (counterfactual) simulation to 37 lead-vehicle crashes and 186 lead-vehicle near-crashes from lead-vehicle scenarios identified in the SHRP2 naturalistic driving data. The simulation combines the kinematics of the two conflicting vehicles with a model of driver glance behavior to estimate two probabilities: (1) that each event becomes a crash, and (2) that each event causes a specific level of injury. The usefulness of the method is demonstrated by comparing the crash and injury risk of normal driving with the risks of driving while performing one of three secondary tasks: the Rockwell radio-tuning task and two hypothetical tasks. Alternative applications of the method and its metrics are also discussed. The method presented in this paper can guide the design of safer driver–vehicle interfaces by showing the best tradeoff between the percent of glances that are on-road, the distribution of off-road glances, and the total task time for different tasks.     

Peer pressure and risk taking in young drivers’ speeding behavior

Although many countermeasures have been implemented in Europe, young drivers continue to have a high rate of involvement in car crashes. Their crash rate is higher in presence of peer passengers than when driving alone. Peer presence could contribute toward explaining this involvement, especially regarding speeding. Peers are known to often influence young drivers’ risky behaviors through proximal (direct and indirect active pressures) and distal (passive pressure) forms of intervention (Allen & Brown, 2008). This present study examined the effect of peer pressure and peer risk taking on the estimated speeding behavior of a scenario driver (ESBSD) as well as on the estimated speeding intention of a scenario driver (ESISD). The scenario driver was the main character in an online-scenario based questionnaire regarding speeding. The main character is a fictional young male depicted driving with his best friends in all the experimental scenarios in which the variables type of pressure and peer risk taking were manipulated. One hundred and eighty young French drivers (18–25 years, 50% men) took part in the study. The key findings were that (1) only direct and indirect active pressure, but not passive pressure, increased the ESBSD and that (2) high (vs. low) peer risk taking lead to a higher ESISD. However, no interaction between the pressure type and peer risk taking on ESBSD and ESISD was found. Implications of the findings are discussed.     

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.     

Unmanned Aircraft Systems Selection Practices: Current Research and Future Directions

This review examines evolving personnel selection practices for unmanned aircraft systems/remotely piloted aircraft (UAS/RPA) across the U.S. Air Force, U.S. Naval Services, and U.S. Army. Findings across services revealed several themes, including strengths (e.g., strong predictive validities, consistency in operator profiles), weaknesses (e.g., small number of predictive validation studies, small sample sizes), and gaps (e.g., need for further investigation of noncognitive predictors). Ongoing and proposed research, including development and implementation of new instruments and methodologies, are discussed, followed by suggestions to facilitate enhanced UAS/RPA selection practices across the services.