Analysis of speed reductions and crash risk of aggressive drivers during emergent pre-crash scenarios at unsignalized intersections

Aggressive driver behavior (ADB) is often linked with road crashes, especially during crash imminent situations. Previous studies demonstrated that ADB was positively correlated with collision risk; however, this relationship has not quantified evidently. This study aimed to analyze drivers' collision risk and speed reduction behavior during an emergent pre-crash scenario (such as a conflict encroaching into an unsignalized intersection at different critical time gaps) using a driving simulator. The effect of ADB on crash risk is investigated using the time to collision (TTC). Further, drivers' collision evasive behavior is analyzed using speed reduction time (SRT) survival probabilities. Fifty-eight Indian drivers are identified as aggressive, moderately aggressive, and, non-aggressive based on aggressive indicators such as vehicle kinematics (percentage of the time spent in speeding and rapid accelerations, maximum brake pressure, etc.). Two separate models are built to analyze ADB effects on TTC and SRT using a Generalized Linear Mixed Model (GLMM) and a Weibull Accelerated Failure Time (AFT) model, respectively. From the results, it can be observed that aggressive drivers' TTC and SRT are reduced by 82% and 38%, respectively. Compared to a 7 sec conflict approaching time gap, TTC is reduced by 18%, 39%, 51%, and 58% for 6 sec, 5 sec, 4 sec, and 3 sec conflict approaching time gaps, respectively. The estimated SRT survival probabilities for aggressive, moderately aggressive and non-aggressive drivers are 0%, 3% and 68% at 3 sec of conflict approaching time gap, respectively. SRT survival probability increased by 25% for matured drivers and decreased by 48% for drivers who tend to engage in frequent speeding. Important implications of the study findings are discussed.

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.

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.

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.

Assessing safety critical driving patterns of heavy passenger vehicle drivers using instrumented vehicle data - An unsupervised approach

Assessing the individual's driving profile and identifying the at-fault behaviors contributes to road safety, riding comfort, and driver assistance systems. This study proposes a framework to identify aggressive driving patterns in longitudinal control using real-time driving profiles of heavy passenger vehicle (HPV) drivers. The main objective is to detect and quantify the instantaneous driving decisions and classify the identified maneuvers (acceleration, braking) using unsupervised machine learning techniques without any prior-ground truth. To this end, total 8295 acceleration events, and 7151 braking events, were extracted from 142 driving profiles collected using high-resolution (10 Hz) GPS instrumentation. The principal component analysis was conducted on a multi-dimensional feature set, followed by a two-stage k-means clustering on the reduced feature subspace. The results showed that 86.5% of accelerations and 65.3% of braking maneuvers were characterized as non-aggressive, indicating safe or base-line driving behavior. However, 13.5% of accelerations and 34.7% of braking maneuvers were featured to be aggressive, indicative of the actual risky behaviors. Further analysis demonstrated the heterogeneity in drivers' trip-level frequency of aggressive maneuvers and highlighted the need for a continuous driving assessment. The study also revealed that the thresholds derived from the obtained clusters featuring the aggressive accelerations (+0.3 to +0.48 g) and aggressive braking (-0.42 to -0.27 g) maneuvers were beyond the acceptable limits of passenger safety and comfort. The insights from the study aids in developing driver assistance systems for personalized feedback provision and improve driver behavior.

Retaliatory aggressive driving: A justice perspective

Driving anger and roadway aggression have previously been conceptualized using attributional theory, the theory of planned behavior, and the general aggression model (GAM) framework. The current study builds on these findings, testing the applicability of the attribution-of-blame model of perceptions of injustice and expanding existing models of retaliatory driving aggression to include unjust world beliefs and sensitivity to injustice. A sample of 269 participants from a large urban Canadian university viewed five animated driving scenarios (i.e., a queuing violation, a dangerous turn in front of oncoming traffic, selfish parking behavior, misuse of a high occupancy vehicle lane, and a driver failing to stop at a red light). Prior to viewing each scenario, a brief written description of the scenario was provided to each participant and read aloud by the experimenter. After viewing each scenario, participants completed a questionnaire regarding their attributions, emotions, and anticipated behavior in response to the animated scenario. After viewing all animated videos, participants completed a second questionnaire that assessed individual differences and demographic variables. Consistent with the GAM, structural equation and mediation analyses identified a significant path from individual differences (i.e., belief in an unjust world and driving injustice sensitivity), through internal states (i.e., perceptions of injustice and anger), to retaliatory aggressive driving. Results of this study found consistent paths between factors which were significant across all five scenarios and may therefore be generalizable to other driving situations. Other pathways were found to influence only a selection of the five scenarios, suggesting that they may be situation specific. Results provide support for possible intervention strategies that can be employed by driver education programs to reduce aggressive driving.

Psychometric properties of the Mexican version of the Driver's Angry Thoughts Questionnaire and analysis of invariance with the Romanian and Spanish versions

Research has shown the relevance of three axes in the study of violent behaviour: the emotional axis (anger), the behavioural axis (aggression), and the cognitive axis (hostility or aggressive thinking). In the field of driving, the first two axes have received a lot of attention, whereas the third one has been less studied. The current research aimed to analyse the psychometric properties of the Driver's Angry Thoughts Questionnaire (DATQ) in a Mexican sample. Besides, the structural invariance of this instruments was analysed with respect to both the Spanish and the Romanian versions. A sample of 294 participants taken from the general Mexican drivers population completed a set of measures including the DATQ and the Driving Survey, as a measure of risky driving, aggressive driving, and crash-related events. The results showed that the Mexican version of the DATQ replied the original five-factor structure, maintaining the 65 items likewise in both the Spanish and Romanian versions. Analyses of the invariance suggested the equivalence among the three versions, especially in the case of Mexican-Spanish. Moreover, the five factors were positive and mostly significantly related to each other, and with both risky driving and aggressive driving. Some significant relationships were attained also with crash-related events, especially in the case of those which happened in the last three months (short-termed). Finally, males showed higher scores than females in the five ways of aggressive thinking. Limitations of the study, practical implications and future research are discussed.

Analysis of factors influencing aggressive driver behavior and crash involvement

OBJECTIVE

Aggressive driver behavior is one of the major contributing factors to road crashes. However, the relationship between aggressive driver behavior and crash risk is scarcely explored. The present study focused on quantifying the effect of aggressive driver behavior on crash probability.

METHOD AND DATA SOURCES

A sample of 405 Indian drivers were analyzed to model the aggressive driver behavior using self-reported measures. Generalized linear models were developed to quantify the effects of independent variables such as age, gender, personality traits (e.g., driving anger, physical aggression, hostility), and individual predilections to commit violations (e.g., excessive speeding and frequent risky overtaking) on aggressive driver behavior and crash probabilities.

RESULTS

K-means clustering technique was applied to the Aggressive Driving Scale (ADS) scores to cluster the drivers into three groups (aggressive, normal, and cautious). Gender was significantly correlated with aggressive driver behavior. Compared to female drivers, male drivers were 2.57 times more likely to engage in aggressive driving. Driver's age was negatively correlated with aggressive driving. With one-year increment in driver's age, the tendency of a driver to engage in aggressive driving was reduced by 26%. In addition, the likelihood of being engaged in aggressive driving was increased by 2.98 times and 2.15 times for the drivers who engage in excessive speeding and frequent risky overtaking, respectively. Driver's personality traits were significantly correlated with aggressive drivers. The crash involvement model showed that aggressive drivers were 2.79 times more likely to be involved in road crashes than cautious drivers. Further, married drivers were 2.17 times less likely to be involved in crashes, whereas for professional drivers the crash involvement probability was increased by 75%.

CONCLUSIONS

The results revealed that in addition to age and gender personality traits were significant predictors of driving aggression. Further, the driver's marital status was negatively correlated with the crash involvement and professional drivers were more likely to be involved in crashes than nonprofessional drivers. The study findings can be used in identifying specific risk-prone drivers to provide safety measures via in-vehicle Advanced Driver Assistance Systems (ADAS).

Regulating Road Rage

Road rage has been a problem since the advent of cars. Given the ubiquity of road rage, and its potentially devastating consequences, understanding road rage and developing interventions to curb it are important priorities. Emerging theoretical and empirical advances in the study of emotion and emotion regulation have provided new insights into why people develop road rage and how it can be prevented and treated. In the current article, we suggest an integrative conceptual framework for understanding road rage, based upon a psychological analysis of emotion and emotion regulation. We begin by defining road rage and other key constructs. We then consider the interplay between road rage generation and road rage regulation. Using an emotion regulation framework, we describe key points at which emotion-regulation difficulties can lead to road rage, followed by strategies that may alleviate these difficulties. We suggest that this framework usefully organizes existing research on road rage, while exposing key directions for future research.

Predicting Risky and Aggressive Driving Behavior among Taxi Drivers: Do Spatio-Temporal Attributes Matter?

Risky and aggressive driving maneuvers are considered a significant indicator for traffic accident occurrence as well as they aggravate their severity. Traffic violations caused by such uncivilized driving behavior is a global issue. Studies in existing literature have used statistical analysis methods to explore key contributing factors toward aggressive driving and traffic violations. However, such methods are unable to capture latent correlations among predictor variables, and they also suffer from low prediction accuracies. This study aimed to comprehensively investigate different traffic violations using spatial analysis and machine learning methods in the city of Luzhou, China. Violations committed by taxi drivers are the focus of the current study since they constitute a significant proportion of total violations reported in the city. Georeferenced violation data for the year 2016 was obtained from the traffic police department. Detailed descriptive analysis is presented to summarize key statistics about various violation types. Results revealed that over-speeding was the most prevalent violation type observed in the study area. Frequency-based nearest neighborhood cluster methods in Arc map Geographic Information System (GIS) were used to develop hotspot maps for different violation types that are vital for prioritizing and conducting treatment alternatives efficiently. Finally, different machine learning (ML) methods, including decision tree, AdaBoost with a base estimator decision tree, and stack model, were employed to predict and classify each violation type. The proposed methods were compared based on different evaluation metrics like accuracy, F-1 measure, specificity, and log loss. Prediction results demonstrated the adequacy and robustness of proposed machine learning (ML) methods. However, a detailed comparative analysis showed that the stack model outperformed other models in terms of proposed evaluation metrics.

Identification of aggressive driving from naturalistic data in car-following situations

INTRODUCTION

Aggressive driving has been associated as one of the causes for crashes, sometimes with very serious consequences. The objective of this study is to investigate the possibility of identifying aggressive driving in car-following situations on motorways by simple jerk metrics derived from naturalistic data.

METHOD

We investigate two jerk metrics, one for large positive jerk and the other for large negative jerk, when drivers are operating the gas and brake pedal, respectively.

RESULTS

The results obtained from naturalistic data from five countries in Europe show that the drivers from different countries have a significantly different number of large positive and large negative jerks. Male drivers operate the vehicle with significantly larger number of negative jerks compared to female drivers. The validation of the jerk metrics in identifying aggressive driving is performed by tailgating (following a leading vehicle in a close proximity) and by a violator/non-violator categorization derived from self-reported questionnaires. Our study shows that the identification of aggressive driving could be reinforced by the number of large negative jerks, given that the drivers are tailgating, or by the number of large positive jerks, given that the drivers are categorized as violators. Practical applications: The possibility of understanding, classifying, and quantifying aggressive driving behavior and driving styles with higher risk for accidents can be used for the development of driver support and coaching programs that promote driver safety and are enabled by the vast collection of driving data from modern in-vehicle monitoring and smartphone technology.

Self-Reported Anger: Vulnerability for Risky Behaviors in Two-Wheeler Riding Young Men

OBJECTIVES

Aggressive driving and road accidents are major concerns in the public health sector. This study aimed to explore risk to aggressive and risky behaviors on the road in two-wheeler riding young men.

METHODS

The study comprised 433 young male two-wheeler riders from an urban city of India. A two-wheeler riding survey that captured subjective perception of difficulty in managing anger in general, easy provocability to anger, and aggressive and risky behaviors on the road, and Negative Mood Regulation (NMR) scale were administered.

RESULTS

Of the 433 participants, 83 (19%) reported experiencing problematic anger in general, whereas 175 (40.42%) did not endorse experiencing problematic anger. Based on this, two groups were formed, namely, problematic anger-present group and problematic anger-absent group. The problematic anger-present group reported high score on easy provocability to anger, difficulty in controlling anger, specific motives related to riding fast than usual, and severity of aggressive responses to frustrating situations while riding, and low score on NMR scale. Statistical analysis revealed a significant difference between the groups.

CONCLUSION

This study highlights the relevance of assessing subjective perception of problematic anger in two-wheeler riding young men. This has implications for designing interventions for enhancing road safety.

The influence of impulsivity and the Dark Triad on self-reported aggressive driving behaviours

The present study tested the role of Dark Triad traits (DT; narcissism, psychopathy, and Machiavellianism) as potential contributors to self-reported aggressive driving alongside driving anger, general aggression, impulsiveness, and attributions of malign driving intent. Members of the general community (N = 168) completed an online survey battery measuring these characteristics, and a proxy measure of aggressive driving. Regression analyses revealed that psychopathy, a history of physical aggression towards others, and the "progress impeded" aspect of driving anger, accounted for 50.8% of the variance in self-reported aggressive driving behaviours. The remaining variables were not significant. A structural equation model found all measures fitted into a single model in which impulsivity and the DT predicted general aggression, general aggression fully mediated the effect of the DT on driving anger, and general aggression and progress impedance predicted self-reported aggressive driving (GFI = 0.925). These results indicate tendencies toward expressing aggression physically, frustration at goals being impeded, and a callous, impulsive nature can predispose an individual to aggressive driving behaviours. Implications of these findings and recommendations for research are discussed.

Road anger expression-Changes over time and attributed reasons

Based on the results from three independent surveys conducted in Denmark in 2005, 2008 and 2016, this paper provides an overview of the development of road anger expression in general and in demographic sub-groups of road users. In addition, it investigates how people explain own and other people's road anger expression and if attributed reasons are related to demographic factors and level of anger expression measured based on the short form of the driving anger expression inventory (DAX-short). From 2005 to 2016 the percentage of people involved in anger expression incidents increased particularly in the densely populated Capital Region of Denmark. The increase was most pronounced for "yelling" and "threatening". Men were more often involved than women both as aggressor and as victim, but the gender difference decreased from 2008 to 2016. Generally, own anger expression was more often explained with getting frightened (non-hostile attribution), while anger expression by other road users was more often explained by not being able to control own anger or by wanting to show that one made a mistake (hostile attribution). However, people scoring high in aggressive anger expression often explained own anger expression by "not being able to control anger", thereby indicating self-reflection and a potential for behavioural change. Behavioural reactions to being frightened are to some extend mistakenly interpreted as expressions of anger by other road users. Results indicate that cognitive and behavioural interventions, possibly as part of the driver education, are relevant to reduce aggressive anger expression in traffic.

A qualitative exploration of driving stress and driving discourtesy

BACKGROUND

Driving courtesy, and conversely driving discourtesy, recently has been of great interest in the public domain. In addition, there has been increasing recognition of the negative impact of stress upon the individual's health and wellbeing, with a plethora of interventions aimed at minimising stress more generally. The research literature regarding driving dis/courtesy, in comparison, is scant, with a handful of studies examining the dis/courteous driving behaviour of road users, and the relationship between driving discourtesy and driving stress.

AIM

To examine courteous and discourteous driving experiences, and to explore the impact of stress associated with such driving experiences.

METHOD

Thirty-eight drivers (20 females) from the Sunshine Coast region volunteered to participate in one of four 1-1.5 h focus groups. Content analysis used the verbatim utterances captured via an Mp3 device.

RESULTS

Three themes pertaining to stressful and discourteous interactions were identified. Theme one pertained to the driving context: road infrastructure (eg, roundabouts, roadwork), vehicles (eg, features), location (eg, country vs city, unfamiliar areas), and temporal aspects (eg, holidays). Theme two pertained to other road users: their behaviour (eg, tailgating, merging), and unknown factors (eg, illicit and licit drug use). Theme three pertained to the self as road user: their own behaviours (eg, deliberate intimidation), and their emotions (eg, angry reaction to other drivers, being in control).

DISCUSSION AND CONCLUSIONS

Driving dis/courtesy and driving stress is a complex phenomenon, suggesting complex intervention efforts are required. Driving discourtesy was reported as being highly stressful, therefore intervention efforts which encourage driving courtesy and which foster emotional capacity to cope with stressful circumstances appear warranted.

The impact of police presence on angry and aggressive driving

An extensive body of research has found that angry and aggressive driving are both significantly related to crash involvement. There has also been a large body of research investigating the situational factors related to angry and aggressive driving, but one interesting question that has not yet been answered is whether the enforcement of traffic laws causes or reduces angry and aggressive driving. The independent region of Northern Kosovo represents a unique opportunity to investigate the impact of a lack of traffic enforcement on driving behaviour. Therefore, the present study set out to investigate whether the presence of traffic enforcement has a significant impact on the level of driver anger and aggressive driving. Registered owners of motor vehicles in Northern Kosovo and Serbia were both sent a questionnaire which contained the 28-item Dula Dangerous Driving Index (DDDI) and the 21-item UK Driving Anger Scale (UKDAS). This found that anger was higher in two of the four driving anger factors (direct hostility and progress impeded) and two of the three DDDI factors (risky driving & aggressive driving). Furthermore, the present study found that the lack of police enforcement was a significant predictor of both aggressive and risky driving, even after the driving anger and demographic variables had been partialled out. Therefore, it appears that introducing or increasing traffic enforcement may be one method of reducing aggressive and risky driving behaviour.

Anger expression among Danish cyclists and drivers: A comparison based on mode specific anger expression inventories

Based on the short form of the driving anger expression inventory (DAX-short, 15-item), the present study developed an adapted version of the DAX for cyclists (CAX, 14 items). The data basis was an online survey of 2000 inhabitants of Denmark. A principle component analysis on the translated DAX-short confirmed the 4-factor solution of the original study differentiating between (1) personal physical aggressive expression, (2) use of a vehicle to express anger, (3) verbal aggressive expression and (4) adaptive/constructive expression. In case of cycling, the factor "use of a vehicle to express anger" only included one item and was left out. Based on the results, reliable subscales were developed. Drivers scored higher in verbal aggressive expression than cyclists, while there was no significant difference in constructive expression. The subscales for drivers and cyclists showed significant relations to age, gender, self-reported aggressive behaviours and traffic fines: Women scored for instance lower in physical expression, while older people scored higher in constructive expression. The effect of age and gender on anger expression among drivers and cyclists remained significant when controlling for exposure and other factors in linear regression analyses. These analyses also showed a relationship between a positive attitude towards driving and higher levels of anger expression among drivers, while this was not the case for cyclists.

Angry thoughts in Spanish drivers and their relationship with crash-related events. The mediation effect of aggressive and risky driving

Several studies have related aggressive and risky driving behaviours to accidents. However, the cognitive processes associated with driving aggression have received very little attention in the scientific literature. With the aim of shedding light on this topic, the present research was carried out on a sample of 414 participants in order to validate the Driver's Angry Thoughts Questionnaire (DATQ) with a sample of Spanish drivers and to test the hypothesis of the mediation effect of aggressive and risky driving on the relationship between drivers' angry thoughts and crash-related events. The results showed a good fit with the five-factor model of the questionnaire (Judgmental and Disbelieving Thinking, Pejorative Labelling and Verbally Aggressive Thinking, Revenge and Retaliatory Thinking, Physically Aggressive Thinking, and Coping Self-Instruction). Moreover, slight gender differences were observed in drivers' angry thoughts, with women scoring higher than men (η²=0.03). However, younger drivers had higher scores than older drivers in general (η²=0.06). Finally, several mediation effects of aggressive driving and risky driving on the relationship between aggressive thinking and the crash-related events were found. Implications of the results for research in traffic psychology and clinical assessment of aggressive drivers as well as limitations of the study are discussed.

Can vehicle longitudinal jerk be used to identify aggressive drivers? An examination using naturalistic driving data

This paper investigated the characteristics of vehicle longitudinal jerk (change rate of acceleration with respect to time) by using vehicle sensor data from an existing naturalistic driving study. The main objective was to examine whether vehicle jerk contains useful information that could be potentially used to identify aggressive drivers. Initial investigation showed that there are unique characteristics of vehicle jerk in drivers' gas and brake pedal operations. Thus two jerk-based metrics were examined: (1) driver's frequency of using large positive jerk when pressing the gas pedal, and (2) driver's frequency of using large negative jerk when pressing the brake pedal. To validate the performance of the two metrics, drivers were firstly divided into an aggressive group and a normal group using three classification methods (1) traveling at excessive speed (speeding), (2) following too closely to a front vehicle (tailgating), and (3) their association with crashes or near-crashes in the dataset. The results show that those aggressive drivers defined using any of the three methods above were associated with significantly higher values of the two jerk-based metrics. Between the two metrics the frequency of using large negative jerk seems to have better performance in identifying aggressive drivers. A sensitivity analysis shows the findings were largely consistent with varying parameters in the analysis. The potential applications of this work include developing quantitative surrogate safety measures to identify aggressive drivers and aggressive driving, which could be potentially used to, for example, provide real-time or post-ride performance feedback to the drivers, or warn the surrounding drivers or vehicles using the connected vehicle technologies.

Effect of personality traits, age and sex on aggressive driving: Psychometric adaptation of the Driver Aggression Indicators Scale in China

This study aimed to assess the reliability and validity of the Chinese version of the Driver Aggression Indicators Scale (DAIS), which measures aggressive driving behaviors. Besides, demographic variables (sex and age) and the big five personality traits were examined as potential impact factors of aggressive driving. A total of 422 participants completed the DAIS, Big Five Personality Inventory (BFPI), and the socio-demographic scale. First, psychometric results confirmed that the DAIS had a stable two-factor structure and acceptable internal consistency. Then, agreeableness and conscientiousness were negatively correlated with hostile aggression and revenge committed by the drivers themselves, while neuroticism was positively correlated with aggressive driving committed by the drivers themselves. Meanwhile, more agreeable drivers may perceive less hostile aggression and revenge. More neurotic drivers may perceive more aggressive warning. Finally, the effects of age and sex on aggressive driving were not same as most studies. We found that older age group perceived and committed more hostile acts of aggression and revenge than younger age groups. Female drivers of 49-60 years perceived more aggressive warnings committed by other drivers.

The dangers of rumination on the road: Predictors of risky driving

Past studies found many different types of factors can influence dangerous driving behaviors. Driver inattention, such as driving under the influence or using a cell phone while driving, was found to contribute to risky driving behaviors. Rumination is a cognitive process that may also contribute to risky driving behaviors due to its influence on attention and limited executive processes. The present study explores the potential role of rumination in dangerous driving behavior endorsement. It was hypothesized that trait rumination would be significantly related to dangerous driving behaviors and that this relationship would be conditional to the sex of the participant. Six-hundred and fifty-three Southeastern university students were recruited to participate and asked to complete multiple questionnaires measuring anger rumination, thought content, driving anger, and dangerous driving behaviors. It was demonstrated that self-reported risky driving behaviors significantly predicted dangerous driving behavior endorsement on the Dula Dangerous Driving Index. Trait rumination scores were found to predict self-reported dangerous driving, aggressive driving, and risky driving behaviors as well as trait driving anger scores. However, no conditional effects based on the sex of the participant were found. It appeared males and females were equally likely to report dangerous driving behaviors, driving anger thoughts, and trait anger rumination. Findings from the current study may assist in understanding how cognitive processes influence different driving behaviors and help develop methods to re-direct attention to safe driving behaviors, and conversely away from ruminative thoughts that increase the likelihood of dangerous driving.

Gender Roles and the Expression of Driving Anger Among Ukrainian Drivers

The current study investigated the validity of the revised (25-item) version of the driving anger expression inventory (DAX) on a novel sample of 385 drivers from Ukraine. The roles of sex and gender in relation to self-reported aggressive tendencies were also examined. Confirmatory factor analysis supported the four-factor structure of the DAX (adaptive/constructive expression; use of the vehicle to express anger; verbal aggressive expression; and personal physical aggressive expression), and the three aggressive factors were found to have positive relationships with trait anger and driving anger, while adaptive/constructive expression was negatively related to trait and driving anger. Drivers who reported recent near-misses or loss of concentration scored higher on verbal aggressive expression. Those who had recently received a traffic ticket also reported higher levels of all three types of aggressive anger expression. Further, the presence of feminine traits, but not sex, predicted more adaptive/constructive behaviors and lower scores for verbal aggressive expression, personal physical aggressive expression, and total aggressive expression. However, masculine traits did not predict any of these factors. This research concludes that the revised DAX is a valid tool to measure the expression of driving anger and that the endorsement of feminine traits is related to less aggressive expression of driving anger.

The association between driving anger and driving outcomes: A meta-analysis of evidence from the past twenty years

Through the use of meta-analysis, this study investigated the relationships between driving anger and five types of driving outcomes (aggressive driving, risky driving, driving errors, near misses and accidents). The moderating effects of three variables (age, study publication year, and participants' country of origin) on these relationships were also examined. A total of 51 studies published over the past two decades met the inclusion criteria for the meta-analysis. The results showed that driving anger significantly predicted all three types of aberrant driving, with zero-order correlations of 0.312, 0.243, and 0.179 with aggressive driving, risky driving and driving errors, respectively. The correlations between driving anger and accident-related conditions, though at relatively weaker levels, were still statistically significant. Tests for effects of the moderating variables suggested that driving anger was a stronger predictor of risky driving among young drivers than among old drivers. Also, the anger-aggression association was found to decrease over time and vary across countries. The implications of the results and the directions for future research are discussed.

Effect of exposure to aggressive stimuli on aggressive driving behavior at pedestrian crossings at unmarked roadways

BACKGROUND

Aggressive driving, influenced by the proneness of driving aggression, angry state and provoking situation, is adversely affecting traffic safety especially in developing countries where pedestrians frequently cross an unmarked crosswalk. Exposure to aggressive stimuli causes driving anger and aggressive driving behaviors, but the exposure effect on higher and lower aggression drivers and their cumulative changes under successive exposures need more investigation.

OBJECTIVES

An experiment was conducted to examine (1) driving behaviors of individuals with higher and lower aggressive driving traits when approaching pedestrian crossings at unmarked roadways with and without aggressive provocation; and (2) cumulative changes of driving performance under repeated provocations.

METHOD

We conducted a driving simulator study with 50 participants. Trait of aggressive driving served as a between-subjects variable: participants with an Aggressive Driving Scale (ADS) total score of 30 or more (for men) or 23 or more (for women) were regarded as higher aggressive drivers; lower aggressive drivers were those individuals whose ADS total scores were 21 or less (for men) or 13 or less (for women). Exposure to aggressive stimuli (provoked vs. non-provoked condition) served as a within-subjects variable. Several aspects of the participants' minimum driving speed, lateral distance from a simulated pedestrian, lateral deviation, and subjective measures were collected.

RESULTS

We found that drivers with higher aggressive driving traits were more likely to feel irritated and fail to give way for pedestrians and drove closer to pedestrians when exposed to sustained honking and improper passing compared to the non-provoked condition. This trait×state interaction only occurred when pedestrians crossed the street from the right roadway edge line. In addition, we observed an accumulation effect of exposure to aggressive stimuli on driver's aggressive behaviors at pedestrian crossings.

CONCLUSIONS

Environmental design, law enforcement, and educational campaign may have practical value for reducing pedestrian and driver conflicts at unmarked roadways.

Car driver attitudes, perceptions of social norms and aggressive driving behaviour towards cyclists

The interaction of car drivers and cyclists is one of the main causes of cycle incidents. The role of attitudes and social norms in shaping car drivers' aggressive behaviour towards cyclists, is not well understood and merits investigation. A sample of 276 drivers completed an online questionnaire concerning their attitudes towards cyclists, attitudes towards risky driving, perception of social norms concerning aggressive driving towards cyclists, and the frequency with which they engage in such aggressive driving behaviours. The results showed that attitudes towards cyclists, as well as social norm perceptions concerning aggressive driving towards cyclists, were associated with aggressive driving towards cyclists. Negative attitudes towards cyclists were more pronounced in non-cyclists than cyclists and their association with aggressive driving behaviour was stronger in cyclists than non-cyclists. The perception of social norms concerning aggressive driving towards cyclists had a stronger association with aggressive driving in non-cyclists than cyclists. Attitudes towards risk taking did not affect aggressive driving towards cyclists. These findings can inform campaigns that aim to improve cyclist and car driver interaction on the roads, making them safer to use for cyclists.

Trait Predictors of Aggression and Crash-Related Behaviors Across Drivers from the United Kingdom and the Irish Republic

Aggressive driving is acknowledged as a contributor to motor vehicle crashes. This study explored a theoretical model of aggressive expression and crash-related outcomes using self-report data collected, using an online questionnaire, from drivers in the United Kingdom and the Republic of Ireland. The proposed model tested whether the personality traits of boredom proneness, sensation seeking, and impulsivity, coupled with trait driving anger, predicted aggressive driving; and whether aggressive driving predicted crash-related outcomes (loss of concentration and control, near misses, and moving violations). The structural model was confirmed, with aggressive expressions of anger being found to mediate the relationships driving anger and impulsivity had with the crash-related outcomes. Multigroup invariance analysis showed that the model remained invariant across drivers from the United Kingdom and Ireland, suggesting that the contributing factors for aggressive expression and crash involvement are similar across both countries. When self-reported crash-related conditions were compared between drivers in the United Kingdom and Ireland, drivers in the United Kingdom reported more aggressive driving, more minor crashes, more incidents of road rage, and more frequent losses of concentration and vehicle control.

The impact of childhood symptoms of conduct disorder on driver aggression in adulthood

BACKGROUND

Despite limited empirical investigation, existing scientific literature suggests that individuals with a history or current diagnosis of conduct disorder (CD) may be more likely to demonstrate reckless and aggressive driving. Much of the limited research in this field examines the impact of childhood CD on driver behaviour and collision risk in young adults. Few if any, studies assess the impact of this disorder on driver behaviour beyond age 21 years. The current research is a population-based study of the impact of CD symptoms during childhood on the risk of engaging in driver aggression during adulthood.

METHODS

Data are based on telephone interviews with 5230 respondents who reported having driven in the past year. Data are derived from the 2011-2013 cycles of the CAMH Monitor, an ongoing cross-sectional survey of adults in Ontario, Canada aged 18 years and older. A binary logistic regression analysis of self-reported driver aggression in the previous 12 months was conducted, consisting of measures of demographic characteristics, driving exposure, problem substance use, alcohol- and drug-impaired driving, symptoms of attention deficit hyperactivity disorder, and childhood (before age 15) symptoms of CD.

RESULTS

When entered with demographic characteristics, driving exposure, and other potential confounders, childhood symptoms of CD increased the odds of reporting driver aggression more than two-fold (adjusted OR=2.12). Exploratory analyses of the interaction between childhood symptoms of CD and age was not a significant predictor of driver aggression.

CONCLUSIONS

Results suggest that symptoms of CD during childhood are associated with significantly increased odds of self-reported driver aggression during adulthood. Limitations and future directions of the research are discussed.

Modeling anger and aggressive driving behavior in a dynamic choice-latent variable model

This paper develops a hybrid choice-latent variable model combined with a Hidden Markov model in order to analyze the causes of aggressive driving and forecast its manifestations accordingly. The model is grounded in the state-trait anger theory; it treats trait driving anger as a latent variable that is expressed as a function of individual characteristics, or as an agent effect, and state anger as a dynamic latent variable that evolves over time and affects driving behavior, and that is expressed as a function of trait anger, frustrating events, and contextual variables (e.g., geometric roadway features, flow conditions, etc.). This model may be used in order to test measures aimed at reducing aggressive driving behavior and improving road safety, and can be incorporated into micro-simulation packages to represent aggressive driving. The paper also presents an application of this model to data obtained from a driving simulator experiment performed at the American University of Beirut. The results derived from this application indicate that state anger at a specific time period is significantly affected by the occurrence of frustrating events, trait anger, and the anger experienced at the previous time period. The proposed model exhibited a better goodness of fit compared to a similar simple joint model where driving behavior and decisions are expressed as a function of the experienced events explicitly and not the dynamic latent variable.

The impact of aggressive driving-related injuries in Ohio, 2004-2009

OBJECTIVE

This study describes the medical and financial impact (hospital charges) of aggressive driving-related injuries in Ohio.

METHODS

Statewide crash and hospital databases were probabilistically linked for 2004 through 2009. Descriptive analyses and multivariate regression modeling of multiply-imputed data on motor vehicle occupants involved in aggressive driving-related crashes were performed.

RESULTS

There were 821,136 motor vehicle occupants involved in aggressive driving-related crashes in Ohio from 2004 through 2009; injuries were sustained by 15.0%. The rate of aggressive driving-related crashes was highest among drivers ages 16 to 19 years (3787.1 crashes per 100,000 licensed drivers). Aggressive driving-related inpatients accrued more than $250.8 million in hospital charges and 28,366 inpatient days of treatment in 2004 through 2009. Occupants ages 16 to 19 years had higher odds of sustaining injury when involved in aggressive driving-related crashes (OR = 1.10; 95% CI = 1.07, 1.12; p < 0.001), but lower odds of death, inpatient admission, ISS ≥ 16, and rehabilitation.

DISCUSSION

Aggressive driving-related injuries have a substantial medical and financial impact in Ohio.

PRACTICAL APPLICATIONS

Compared with other highway safety issues, prevention efforts aimed specifically at aggressive driving are lacking. Targeted enforcement and public awareness campaigns are needed.

The prosocial and aggressive driving inventory (PADI): a self-report measure of safe and unsafe driving behaviors

Surveys of 1217 undergraduate students supported the reliability (inter-item and test-retest) and validity of the Prosocial and Aggressive Driving Inventory (PADI). Principal component analyses on the PADI items yielded two scales: Prosocial Driving (17 items) and Aggressive Driving (12 items). Prosocial Driving was associated with fewer reported traffic accidents and violations, with participants who were older and female, and with lower Boredom Susceptibility and Hostility scores, and higher scores on Agreeableness, Conscientiousness, Openness, and Neuroticism. Aggressive Driving was associated with more frequent traffic violations, with female participants, and with higher scores on Competitiveness, Sensation Seeking, Hostility, and Extraversion, and lower scores on Conscientiousness, Agreeableness, and Openness. The theoretical and practical implications of the PADI's dual focus on safe and unsafe driving are discussed.

Development of a short form of the driving anger expression inventory

The present study developed a revised version of the driving anger expression inventory (25-items) and a short (15-item) version using data from 551 drivers. Split half factor analyses on both versions confirmed the original four factors; personal physical aggressive expression, use of a vehicle to express anger, verbal aggressive expression and adaptive/constructive expression. The two DAX versions were strongly correlated, demonstrating the suitability of both forms of the scale and the aggressive forms of expression were higher for drivers who reported initiating road rage interactions. Total aggressive expression was also higher for drivers who reported recent crash-related conditions, such as: loss of concentration, losing control of their vehicle, moving violations, near-misses and major crashes. The revised DAX and DAX-short provide shorter versions of the 49-item DAX that can more easily be combined with other questionnaires and require smaller sample sizes to analyse. Further research is required to validate these tools among different samples and populations.

Driving anger in Malaysia

The present study examined the types of situations that cause Malaysian drivers to become angry. The 33-item version of the driver anger scale (Deffenbacher et al., 1994) was used to investigate driver anger amongst a sample of 339 drivers. Confirmatory factor analysis showed that the fit of the original six-factor model (discourtesy, traffic obstructions, hostile gestures, slow driving, illegal driving and police presence), after removing one item and allowing three error pairs to covary, was satisfactory. Female drivers reported more anger, than males, caused by traffic obstruction and hostile gestures. Age was also negatively related to five (discourtesy, traffic obstructions, hostile gestures, slow driving and police presence) of the six factors and also to the total DAS score. Furthermore, although they were not directly related to crash involvement, several of the six forms of driving anger were significantly related to the crash-related conditions of: near misses, loss of concentration, having lost control of a vehicle and being ticketed. Overall the pattern of findings made in the present research were broadly similar to those from Western countries, indicating that the DAS is a valid measure of driving anger even among non-European based cultures.

Forgivingness, anger, and hostility in aggressive driving

This study was aimed at investigating the relationship between trait forgivingness, general anger, hostility, driving anger, and self-reported aggressive driving committed by the driver him/herself ("self" scale) and perceiving him/herself as an object of other drivers' aggressive acts ("other" scale). The Slovak version of questionnaires was administrated to a sample of 612 Slovak and Czech drivers. First, the factor structure of the Driver Anger Indicators Scale (DAIS) was investigated. Factor analyses of the self and other parts of the DAIS resulted in two factors, which were named as aggressive warnings and hostile aggression and revenge. Next, the results showed that from all dependent variables (scales of the DAIS), self-reported aggressive warnings (self) on the road were predicted best by chosen person-related factors. The path model for aggressive warnings (self) suggested that trait forgivingness and general anger were fully mediated by driving anger whereas hostility proved to be a unique predictor of aggressive behavior in traffic. Driving anger was found to be the best predictor of perceptions that other drivers behave aggressively.

The theory of planned behavior, materialism, and aggressive driving

PURPOSE

Aggressive driving is a growing problem worldwide. Previous research has provided us with some insights into the characteristics of drivers prone to aggressiveness on the road and into the external conditions triggering such behavior. Little is known, however, about the personality traits of aggressive drivers. The present study proposes planned behavior and materialism as predictors of aggressive driving behavior.

DESIGN/METHODOLOGY

Data was gathered using a questionnaire-based survey of 220 individuals from twelve large industrial organizations in Israel. Our hypotheses were tested using structural equation modeling.

FINDINGS

Our results indicate that while planned behavior is a good predictor of the intention to behave aggressively, it has no impact on the tendency to behave aggressively. Materialism, however, was found to be a significant indicator of aggressive driving behavior.

RESEARCH LIMITATIONS

Our study is based on a self-reported survey, therefore might suffer from several issues concerning the willingness to answer truthfully. Furthermore, the sampling group might be seen as somewhat biased due to the relatively high income/education levels of the respondents.

ORIGINALITY/VALUE

While both issues, aggressive driving and the theory of planned behavior, have been studied previously, the linkage between the two as well as the ability of materialism to predict aggressive behavior received little attention previously. The present study encompasses these constructs providing new insights into the linkage between them.