The effects of situational factors and impulsiveness on drivers' intentions to violate traffic rules: Difference of driving experience

Task and Resting-State Functional Connectivity Predict Driving Violations

Aberrant driving behaviors cause accidents; however, there is a lack of understanding of the neural mechanisms underlying these behaviors. To address this issue, a task and resting-state functional connectivity was used to predict aberrant driving behavior and associated personality traits. The study included 29 right-handed participants with driving licenses issued for more than 1 year. During the functional magnetic resonance imaging experiment, participants first recorded their resting state and then watched a driving video while continuously rating the risk and speed on each block. Functional connectome-based predictive modeling was employed for whole brain tasks and resting-state functional connectivity to predict driving behavior (violation, error, and lapses), sensation-seeking, and impulsivity. Resting state and task-based functional connectivity were found to significantly predict driving violations, with resting state significantly predicting lapses and task-based functional connectivity showing a tendency to predict errors. Conversely, neither impulsivity nor sensation-seeking was associated with functional connectivity. The results suggest a significant association between aberrant driving behavior, but a nonsignificant association between impulsivity and sensation-seeking, and task-based or resting state functional connectivity. This could provide a deeper understanding of the neural processing underlying reckless driving that may ultimately be used to prevent accidents.

The association between the Big Five personality traits and driving behaviors: A systematic review and meta-analysis

Although a large number of studies have examined the relationship between the Big Five personality traits and driving behaviors, consistent evidence for their relationships is still lacking. The main purpose of this study was to systematically review the relationships between the Big Five personality traits and various driving behaviors with different intentions (including risky, aggressive, and positive driving behaviors) through a meta-analysis. A total of 34 articles met the inclusion criteria for the meta-analysis. The results showed that risky and aggressive driving behaviors were negatively associated with conscientiousness (r = -0.21; r = -0.26), agreeableness (r = -0.23; r = -0.37), and openness (r = -0.08; r = -0.07), positively associated with neuroticism (r = 0.11; r = 0.26), and nonsignificantly associated with extraversion (r = 0.06; r = -0.06). Positive driving behaviors were positively associated with conscientiousness (r = 0.30), agreeableness (r = 0.32) and openness (r = 0.20) but nonsignificantly associated with extraversion (r = 0.08) and neuroticism (r = -0.10). In addition, the association between the Big Five personality traits and driving behaviors could be moderated by age, gender and type of personality measure. In conclusion, this study contributes to the literature by quantitatively synthesizing existing findings and reconciling previous debates on the relationship between the Big Five personality traits and driving behaviors. From a practical perspective, our findings provide valuable insights into driver selection and screening, policy development, and safety intervention design.

Does Mindfulness Mediate the Relation between Impulsiveness and Job Stressfulness Perception of Professional Drivers?

(1) Background: Professional driving is a stressful occupation that requires high levels of attention and decision-making, often leading to job stress. Impulsiveness, a personality trait characterized by a tendency to act without forethought, has been associated with negative outcomes such as anxiety, stress, and risky behaviors. Mindfulness has been proposed as a potential strategy for reducing job stress in various occupational settings. However, little is known about the relationship between these variables. This study aimed to investigate the mediating role of mindfulness in the relationship between impulsiveness and job stressfulness perception among professional drivers. (2) Methods: A total of 258 professional drivers from Poland, Lithuania, and Slovakia, have completed self-report questionnaires: Impulsiveness-Venturesomeness-Empathy; Subjective Assessment of Work; Five Facet Mindfulness. (3) Results: Results indicated a positive correlation between impulsiveness and job stressfulness perception, and a negative correlation with mindfulness. Mindfulness partially mediated the relationship between impulsiveness and job stressfulness perception. Additionally, variations were identified in the perceived work environment factors and mindfulness among drivers based on their country of origin. (4) Conclusions: The findings suggest that mindfulness could be a useful approach for reducing job stressfulness perception among professional drivers with high levels of impulsiveness. Given the implications of job stressfulness for professional drivers' health and safety, developing mindfulness interventions tailored to their specific needs could be a promising direction for future research and intervention development.

An exploration of the role of driving experience on self-reported and real-world aberrant driving behaviors

A significant proportion of global road crashes are attributed to unsafe driving behaviors. The current study aimed to explore potential differences in driving behaviors across experienced and novice drivers using two separate approaches; a questionnaire study and an instrumented vehicle study (IVS). The analysis of 260 questionnaires and 1,372 traffic interactions within the IVS revelated that driving experience affects driving performance for different driving tasks. Factor analysis of the questionnaire data revealed the impact of driving errors, lapses, violations, and aggressive violations on the behavior of novice and experienced drivers. Behavioral models of novice and experienced drivers encountering other road users were determined using binary logistic regression. The results showed that novice drivers were more likely to engage in driving violations while experienced drivers were more likely to engage in aggressive violations. Unauthorized speeding, zigzag movements, using a mobile phone while driving, and unauthorized overtaking on roads were the most frequent driving violations by novice drivers. The most frequent aggressive violations by experienced drivers were tempting other drivers to create a race and chasing other drivers. These findings may be used as a framework to facilitate safer driving behaviors by reducing errors, lapses, violations and aggressive violations, and facilitating safety-promoting attitudes.

Impact of experience on visual behavior and driving performance of high-speed train drivers

This study investigated the impact of experience on the visual behavior and driving performance of high-speed train drivers, and explored the correlation between visual behavior and driving performance. Through a simulated driving task, eye movement data and operating data of novice drivers, trainee drivers, and experienced drivers in the traction stage, normal operation process stage, and braking stage were collected. Variance and linear regression were used to analyze the difference and correlation between indicators. The results show that experience could change the driver’s information collection method from long fixation to multi-frequency. Experience also increased the consistency of group operations and reduced the likelihood of hazard occurrences. Therefore, driving performance can be improved by reducing the average fixation duration of information through interface optimization.

The extended theory of planned behavior considering heterogeneity under a connected vehicle environment: A case of uncontrolled non-signalized intersections

With the emergence of connected vehicle (CV) technology, there is a doubt whether CVs can improve driver intentions and behaviors, and thus protect them from accidents with the provision of real-time information. In order to understand the possible impacts of the real-time information provided by CV technology on drivers, this paper aims to develop a model which considers the heterogeneity between drivers with the aid of the extended theory of planned behavior. At the uncontrolled non-signalized intersections, a stated preference (SP) questionnaire survey was conducted to build the dataset consisting of 1001 drivers. Based on the collected dataset, the proposed model examines the relationships between subjective norms, attitudes, risk perceptions, perceived behavioral control and driving intentions, and studies how such driving intentions are simultaneously related to driver characteristics and experiences in the CV environment. Furthermore, driver groups which are homogenous with respect to personality traits are formed, and then are employed to analyze the heterogeneity in responses to driving intentions. Four key findings are obtained when analyzing driver responses to the real-time information provided by CV technology: 1) the proposed H-ETPB model is verified with a good fitness measure; 2) irrespective to driver personality traits, attitudes and perceived behavioral control have a direct and indirect association with driving intentions to accelerate; 3) driving intentions of high-neurotic drivers to accelerate are significantly related to subjective norms, while that of low-neurotic drivers are not; 4) elder high-neurotic drivers, and low-neurotic drivers who have unstable salaries or ever joined in online car hailing service have a strong intention in accelerating. The findings of this study could provide the theoretical framework to optimize traffic performance and information design, as well as provide in-vehicle personalized information service in the CV and CAV environments and assist traffic authorities to design the most acceptable traffic rules for different drivers at an uncontrolled non-signalized intersection.

Statistical Evaluation of BIS-11 and DAQ Tools in the Field of Traffic Psychology

This paper focuses on the statistical evaluation of two independent research tools in the field of traffic psychology. Our research focuses on young drivers in the Slovak Republic and conducts an international comparison. At present, these young drivers make up only about 7% of the total number of drivers, but they cause about 20% of accidents. The paper analyzes the traffic accident rate of young as well as inexperienced drivers. All drivers in the survey had a short period of driving experience. The traffic-psychological survey obtained detailed data via two independent tools. We aimed to find relations between the factors and subfactors of the tools used, namely the BIS-11 (Barratt Impulsiveness Scale) and DAQ (Driver Attitude Questionnaire). The researchers also used these tools in other countries, so it was possible to compare the results obtained. The results from these tools should reveal the psychological causes of as many traffic accidents as possible. Our paper shows the possibilities for the evaluation of the tools used with correlation analysis. The results of our research are shown in symmetrical matrixes of correlation coefficients. Our study also compares its values with the results of foreign authors. Such research has revealed some facts about young drivers’ violations connected with drunk driving, speeding, and other traffic offenses. Our aim was to find connections between the driver’s history (skills, traffic accidents, age, etc.) and psychological characteristics, and we have answered several research questions. In conclusion, we have highlighted the most significant relationships between the factors of driver psychology.

Frustration at congested railway level crossings: How long before extended closures result in risky behaviours?

Drivers' non-compliance with rules is a prominent factor in collisions with trains at railway level crossings. Road user impatience and frustration has been identified as an underlying factor in non-compliance and can be characterised as a specific risk factor. However, research on non-compliance related to waiting times and driver inconvenience lacks in the literature. This paper, therefore, seeks to enhance the currently limited understanding of the relationship between waiting times and risky driver behaviour. An Advanced Driving Simulator was used to obtain objective measures of level crossing non-compliance. Subjective measures on driver frustration and decision-making processes were also collected. Sixty participants completed six driving tasks each, with the tasks varying in terms of traffic conditions, number of trains and associated waiting times. This study shows that increased waiting times result in higher levels of frustration and an increased likelihood of risky driving behaviour, particularly for waiting times longer than 3 min. Non-compliance included entering the activated crossing before boom gates are down, entering the crossing after the train passage but before signals are deactivated, stopping/reversing on the crossing. Subjective data revealed that participants did not comply with level crossing rules due to factors including time pressure, impatience/frustration and low perceived risk. The results suggest that, where possible, waiting times should be standardised at values lower than 3 min to reduce the likelihood of risky road user behaviour.

The association between sensation seeking and driving outcomes: A systematic review and meta-analysis

The purpose of this study was to evaluate the association between sensation seeking (SS) and driving outcomes (including four aberrant driving behaviors, accident involvement and tickets received) through a systematic review and meta-analysis. Forty-four eligible studies, representing 48 individual trials, were identified from a systematic literature search of four electronic databases, and included in the meta-analysis. Overall, the meta-analysis results showed that SS yielded significant positive correlations with risky driving (pooled r = 0.24, p < 0.001), aggressive driving (pooled r = 0.23, p = 0.019), and errors (pooled r = 0.22, p = 0.016). SS was also positively correlated with accident involvement (pooled r = 0.08, p < 0.001) and tickets received (pooled r = 0.19, p < 0.001), though at weaker levels. The correlations could also be moderated by a number of study and sample characteristics, such as country of origin, publication year, age, gender, driving experience and type of SS measure. The findings help facilitate our understanding of the role of SS in aberrant driving behaviors and accident risk, and provide new insight into the design of evidence-based driving education and accident prevention interventions.