Links between observed and self-reported driving anger, observed and self-reported aggressive driving, and personality traits

Detecting event-related driving anger with facial features captured by smartphones

Driving anger is a serious global issue that poses risks to road safety, thus necessitating the development of effective detection and intervention methods. This study investigated the feasibility of using smartphones to capture facial expressions to detect event-related driving anger. Sixty drivers completed the driving tasks in scenarios with and without multi-stage road events and were induced to angry and neutral states, respectively. Their physiological signals, facial expressions, and subjective data were collected. Four feature combinations and six machine learning algorithms were used to construct driving anger detection models. The model combining facial features and the XGBoost algorithm outperformed models using physiological features or other algorithms, achieving an accuracy of 87.04% and an F1-score of 85.06%. Eyes, mouth, and brows were identified as anger-sensitive facial areas. Additionally, incorporating individual characteristics into models further improved classification performance. This study provides a contactless and highly accessible approach for event-related driving anger detection.Practitioner Summary: This study proposed a cost-effective and contactless approach for event-related and real-time driving anger detection and could potentially provide insights into the design of emotional interactions in intelligent vehicles.

Influence of emotions on the aggressive driving behavior of online -car-hailing drivers based on association rule mining

Emotion is an important factor that can lead to the occurrence of aggressive driving. This paper proposes an association rule mining-based method for analysing contributing factors associated with aggressive driving behaviour among online car-hailing drivers. We collected drivers' emotion data in real time in a natural driving setting. The findings show that 29 of the top 50 association rules for aggressive driving are related to emotions, revealing a strong relationship between driver emotions and aggressive driving behaviour. The emotions of anger, surprised, happy and disgusted are frequently associated with aggressive driving behaviour. Negative emotions combined with other factors (for example, driving at high speeds and high acceleration rates and with no passengers in the vehicle) are more likely to lead to aggressive driving behaviour than negative emotions alone. The results of this study provide practical implications for the supervision and training of car-hailing drivers.

The role of anger rumination as a mediator in the relationship between driver moral disengagement and driving angry

Background

Road rage is a common phenomenon during driving, which not only affects the psychological health of drivers but also may increase the risk of traffic accidents. This article explores the impact of moral disengagement and anger rumination on road rage through two studies.

Method

This research combined experimental studies with survey questionnaires. Study one used a driving simulator to investigate whether moral disengagement and anger rumination are psychological triggers of road rage in real-time driving, and whether there are differences in the main psychological triggers of road rage under different road scenarios. Building on the first study, study two employed a survey questionnaire to analyze the relationship between moral disengagement, anger rumination, and road rage. Participants in both studies were drivers with certain driving ages and experience. Data were processed and analyzed using descriptive statistics, factor analysis, reliability and validity tests, and multiple regression analysis.

Results

The findings indicated: (1) There were significant differences in the anger induction rate across different road scenarios, χ2 = 35.73, p < 0.01, effect size = 0.29. Significant differences in average anger levels were observed in scenarios involving oncoming vehicles, lane-cutting, sudden stops by the vehicle ahead, pedestrians crossing the road, and traffic congestion (F = 20.41, p < 0.01, ηp2 = 0.36), with anger rumination playing a major role in the formation of road rage; (2) Moral disengagement significantly predicted road rage (β = 0.25, t = 3.85, p < 0.01). The predictive effect of moral disengagement on anger rumination was significant (β = 0.39, t = 6.17, p < 0.01), as was the predictive effect of anger rumination on road rage (β = 0.43, t = 6.3, p < 0.01). The direct effect of moral disengagement on road rage included 0 in the bootstrap 95% confidence interval, while the mediating effect of anger rumination did not include 0 in the bootstrap 95% confidence interval, indicating that anger rumination fully mediated the relationship between moral disengagement and road rage.

Better understanding female and male driving offenders' behavior: Psychological resources and vulnerabilities matter!

Although driving risk taking appears to be mainly male, an increase in driving violations has been observed in recent years among French female drivers. The main objective of the present study was to explore the driving behaviors, psychological resources, and vulnerabilities of female and male driving offenders participating in a French driver rehabilitation program. The second aim was to examine to what extent females' and males' resources and vulnerabilities predicted their violations, engagement in distracting activities while driving, and prosocial driving behaviors. In the course of 110 rehabilitation programs, 1686 driving offenders (22.4% females) completed a paper-and-pencil questionnaire. Compared to male offenders, females were more likely to have received a higher education, be divorced, or separated, and drive fewer annual kilometers. They also had had fewer demerit points than males in the last three years. They were more empathetic but also more impulsive than their male counterparts and less self-compassionate and mindful. Regression and moderation analyses revealed that, across genders, certain psychological resources such as mindfulness can be considered as protective factors for driving offenders as they tend to decrease dangerous behaviors and increase prosocial ones, while vulnerabilities such as aggressive driving anger expression seem to have the opposite effect. Our results provide a better understanding of driving offenders' behavior and the influence of personal dispositions. They also open new interesting research avenues in the prevention of dangerous behaviors among this high-risk population.

Analysis of driver characteristics, self-reported psychology measures and driving performance measures associated with aggressive driving

Whereas aggressive driving mainly causes speed-related crashes, aggressive driving may be reduced to improve road safety by identifying aggressive driving behaviour, aggressive drivers' characteristics, and their underlying motivational and psychological processes. Previous studies show that both driving performance and self-reported measures of aggressive driving are effective means to identify aggressive drivers. However, these studies assessed aggressive driving patterns across only a limited number of events, did not relate driver characteristics to aggressive driving in each event, and used chiefly vehicle kinematics variables (e.g., mean speed), but not vehicle dynamics variables (e.g., brake pedal force) which better capture driver reaction and decision-making. To address these limitations, this study assessed driver characteristics, self-reported psychological measures, and driving performance measures associated with aggressive driving among 55 drivers' behaviours in 9driving events using a driving simulator and survey responses. The results of structural equation models showed that unique aggressive driving patterns and driver characteristics related to aggressive driving vary among different driving events. As such, we recommend road safety policies to reduce aggressive driving based on the findings in this study.

The relationship between aggressive driving and driver performance: A systematic review with meta-analysis

Traffic crashes remain a leading cause of accidental human death where aggressive driving is a significant contributing factor. To review the driver's performance presented in aggressive driving, this systematic review screens 2412 pieces of relevant literature, selects and synthesizes 31 reports with 34 primary studies that investigated the driver's control performance among the general driver population in four-wheeled passenger vehicles and published with full text in English. These 34 selected studies involved 1731 participants in total. By examining the selected 34 studies, the measures relating to vehicle speed (e.g., mean speed, n = 22), lateral control (e.g., lane deviation, n = 17) and driving errors (e.g., violation of traffic rules, n = 12) were reported most frequently with a significant difference observed between aggressive driving and driving in the control group. The result of the meta-analysis indicates that the aggressive driving behaviour would have 1) a significantly faster speed than the behaviour in the control group with an increase of 5.32 km/h (95% confidence interval, [3.27, 7.37] km/h) based on 8 studies with 639 participants in total; 2) 2.51 times more driving errors (95% confidence interval, [1.32, 3.71] times) than the behaviour in the control group, based on 5 studies with 136 participants in total. This finding can be used to support the identification and quantification of aggressive driving behaviour, which could form the basis of an in-vehicle aggressive driving monitoring system.

Preliminary evidence of the efficacy of the Reducing Aggressive Driving (RAD) program

INTRODUCTION

Aggressive driving contributes to crashes, which often result in serious or fatal injuries. Efforts to reduce road trauma need to include strategies to reduce emotional and aggressive driving. Thus far, solutions have not comprehensively addressed the reasons why drivers become aggressive. This study provides preliminary evidence of the effectiveness of the Reduce Aggressive driving (RAD) program in improving driver behavior. The RAD is based on group discussion, feedback, and goal setting to encourage more positive responses to triggers for aggressive driving. The aim of this study was to evaluate the delivery of the RAD and its impact on driver anger and aggression.

METHOD

A total of 94 drivers, ranging in age from 18 to 74 years (Mean = 38; SD = 15; 56% males) attended one two-hour online RAD session during which they identified triggers for their aggression and developed individual strategies to avoid aggressive driving. Most (87%) participants agreed that the RAD helped them generate realistic strategies to avoid aggressive driving. A subset of 67 participants provided self-reported anger and aggressive driving tendencies one month, and four months after the RAD.

RESULTS

When these were compared to baseline measures taken before participation in the RAD, decreases across all measures were observed. Thus, anger and aggressive driving significantly decreased one month after the RAD, and these decreases were maintained at the four month follow up; providing evidence of the effectiveness of the RAD in reducing these dangerous behaviors. Further research is needed to objectively measure changes in behavior to and support broader roll-out of the RAD program.

Simulating the effect of different lighting conditions on left-turn driving behavior using a scenario-based anger method

Anger is a key factor affecting drivers' subjective judgment and driving skills. The influence of anger on driving behavior has been widely studied, but there is a lack of comparative research under different lighting conditions. Through a driving simulation experiment, this paper studies the influence of anger on left-turn driving behavior under two light conditions day and night. In the experiment, 32 licensed participants were divided into two groups, one in emotional neutrality and the other in anger. Among them, the emotional state of anger is induced by a traffic-related video. The results showed that compared with daytime participants, participants at night had higher anger intensity, shorter gap acceptance, and post encroachment time (PET) when left-turn driving. In addition, compared with neutral emotion participants, angry participants tended to accept shorter gap acceptance and PET when turning left. This indicates that participants failed to respond correctly to left-turn driving behavior in a state of anger. However, the response of gender differences to situational driving anger was not affected by light conditions. The anger intensity of male participants during the day and night was higher than that of female participants, and the gap between acceptance and PETs during left-turn was shorter than that of female participants. This shows that male participants are more likely to produce high-intensity anger and are more likely to make dangerous driving decisions in a state of anger. This paper puts forward some suggestions on identifying anger and preventing angry driving.

Driver's Visual Attention Characteristics and Their Emotional Influencing Mechanism under Different Cognitive Tasks

The visual attention system is the gateway to the human information processing system, and emotion is an important part of the human perceptual system. In this paper, the driver's visual attention characteristics and the influences of typical driving emotions on those were explored through analyzing driver's fixation time and identification accuracy to different visual cognitive tasks during driving. The results showed that: the increasing complexity of the cognitive object led to the improvement of visual identification speed. The memory and recall process increased drivers' fixation time to cognitive objects, and the recall accuracy decreased with the increase in time interval. The increase in the number of cognitive objects resulted in the driver improving the visual identification speed for the cognitive object at the end of the sequence consciously. The results also showed that: the visual cognitive efficiency was improved in the emotional states of anger and contempt, and was decreased in the emotional states of surprise, fear, anxiety, helplessness and pleasure, and the emotional state of relief had no significant effect on the visual cognitive efficiency. The findings reveal the driver's visual information processing mechanism to a certain extent, which are of great significance to understand the inner micro-psychology of driver's cognition.

Powerful Stress Relieving Medicinal Plants for Anger, Anxiety, Depression, and Stress During Global Pandemic

Consideration and improvement for anxiety and depression are important during a global pandemic. Appropriate healthcare can be obtained by paying more attention to traditional medicinal sciences. The adverse effects of stress with various symptoms can be managed by introducing plants that boost mental health. The most relevant psychological reactions in the general population related to the global pandemic are pervasive anxiety, frustration and boredom, specific and uncontrolled fear, disabling loneliness, significant lifestyle changes, and psychiatric conditions. Ginseng, chamomile, passionflower, herbal tea, lavender, saffron, kava, rose, cardamom, Chinese date, and some chief formula like yokukansan, Dan-zhi-xiao-yao-san, so-ochim-tang-gamiband, and saikokaryukotsuboreito are notable herbal treatments for mental health problems. The most common medicinal plants that have been used in Iran for the cure of stress and anxiety are Viper's-buglosses, Dracocephalum, valerian, chamomile, common hop, hawthorns, and lavender. Medicinal plants and herbs can be used for the treatment and alleviation of the negative effects of stress, anger, and depression during the global pandemic.

Typology of aggressive and transgressive drivers

The present study investigates the pattern in which transgressive and aggressive driving motives and aggressive driving were ordered in different clusters of drivers. To establish the difference between profiles, anger disorders, state-trait anger, and motives for transgression and respect for traffic rules were studied and compared between clusters. A total of 383 participants (laypersons), of all age and gender, filled out self-report measures evaluating aggressive driving, state-trait anger, anger disorders, aggressive driving motives, and motives for transgression and respect for traffic rules. Results show the emergence of four profiles of drivers: Respectful, Aggressive-Avenger, Aggressive-Dominant, and Aggressive-Situational. The difference between these clusters has been confirmed by the high tendency of anger disorders for Aggressive-Dominant, low tendency of aggressive driving for Respectful, high tendency for motives for aggressive driving as altruistic protection for Aggressive-Avenger, and high tendency of speeding for Aggressive-Situational. Our findings strongly support the importance of creating programs adapted to each driver's profile.

The Moderating Effects of Emotions on the Relationship Between Self-Reported Individual Traits and Actual Risky Driving Behaviors

Purpose

Researches addressing driving behaviors have not fully revealed how emotions affect risky driving behaviors and tend to focus on the effects of some negative emotions rather than those of more specific emotions. This study aimed to test the potential moderating effects of eight common driving emotions on the relationship between self-reported individual traits (sensation seeking and driving style) and actual risky driving behaviors, sequentially providing some implications for the risky driving behavior prevention.

Participants and Methods

A total of 78 licensed drivers were recruited from undergraduate students, company employees and taxi drivers in China. The participants’ data on self-reported driving style (SDBS) and self-reported sensation seeking (SSSS) were obtained through questionnaires. The participants’ data on actual risky driving behaviors (ARD) in eight driving emotional activation states were obtained through a series of emotion induction experiments and driving experiments. The Structural Equation Modeling (SEM) and moderating effect tests were employed to investigate the relationships of driving emotions, SDBS, SSSS and ARD.

Results

Results showed that anger and pleasure affected risky driving behaviors positively by enhancing the relationship between SDBS and ARD, while surprise and fear were negatively related to risky driving behaviors by weakening this relationship. Anxiety positively affected risky driving behaviors by synchronously enhancing the relationship between SDBS and ARD and the relationship between SSSS and ARD, while helplessness and relief affected risky driving behaviors negatively by weakening the two relationships. Contempt affected risky driving behaviors positively by enhancing the relation between SSSS and ARD.

Conclusion

The results illustrated the effects of different emotions on risky driving behaviors, and also partly explained the reasons for these effects. This research provided a source of reference for reducing traffic accidents caused by risky driving behaviors.