Crash risk evaluation of aggressive driving on motorways: Microscopic traffic simulation approach

This paper provides quantitative evaluation of safety implications of aggressive driving (speeding, following closely and weaving through traffic) by using microscopic traffic simulation approach. Combination of VISSIM and Surrogate Safety Assessment Model (SSAM) were used to model motorway and assess safety of the simulated vehicle. The use of vehicle conflicts was validated by correlating it to historic crashes. Crash risk, severity levels and the magnitude of the perceived benefits of aggressive driving were quantified relative to normal drivers under two scenarios: (1) congested, and (2) non-congested traffic conditions. Involvement in vehicle conflicts is used to determine crash-risk while reductions in Post Encroachment Time (PET) and travel time were used to determine the severity levels of the expected crashes and the magnitude of the perceived benefits. The results indicated that the crash risk of aggressive drivers was found to be in the range 3.10–5.8 depending on traffic conditions and type of road aggression. PET of the conflicts involving aggressive drivers reduced by 7–61% indicating high severity levels of the expected crashes. Moreover, the magnitude of the perceived benefit in terms of reduction in travel time was found to be as little as 1–2%. The study concluded that aggressive driving is entailed with a massive risk while its benefits are actually very little.     

Lessons learned from pedestrian-driver communication and yielding patterns

Understanding the hidden patterns of tacit communication between drivers and pedestrians is crucial for improving pedestrian safety. However, this type of communication is a result of the psychological processes of both pedestrians and drivers, which are very difficult to understand thoroughly. This study utilizes a naturalistic field study dataset and explores the hidden patterns from successful and failed communication events using a pattern recognition method known as Taxicab Correspondence Analysis (TCA). The successful communication scenarios indicate the combinations of variable attributes such as eye contact, facial expression, the assertion of crossing, and effective traffic control devices are strongly associated with successful scenarios. The patterns for failed scenarios are most likely to be on the roadway with a relatively higher speed limit (e.g., 35 mph) and a relatively lower speed limit (e.g., 15 mph) under different conditions. On roadways with a higher speed limit, the failed scenarios are highly associated with passive and undecisive pedestrians, pedestrians far away from the crosswalk, regardless of pedestrian-driver eye contact and facial expression of the pedestrians. Instead of waiting for pedestrians to making a crossing decision, overspeeding drivers are more likely to speed up and pass the crosswalk. On roadways with a lower speed limit, the failed scenarios are often associated with distracted pedestrians, vehicles having the right of way, and the absence of effective traffic control devices. These findings could help transportation agencies identify appropriate countermeasures to reduce pedestrian crashes. The findings on driver-pedestrian communication patterns could provide scopes for improvement in computer vision-based algorithms designed for autonomous vehicle industries.     

Étude des liens entre conduite automobile agressive et transgressive et impulsivité : compréhension empirique et clinique à l’aide du modèle UPPS de l’impulsivité

The aim of this study is to clarify the relationship between impulsiveness and aggressive and transgressive driving using the UPPS Impulsive Behavior Scale. A total of 353 participants (laypersons) filled the Aggressive Driving Behavior Scale (ADBS) and the UPPS. Main results indicate: positive correlations between the four facets of impulsiveness and aggressive and transgressive driving and urgency and sensation-seeking are significant predictors of aggressive driving and its dimensions. These results highlight the need to develop treatment based on an in-depth clinical evaluation of prime behaviours.     

The different effects of personality on prosocial and aggressive driving behaviour in a Chinese sample

Dangerous driving behaviours, as a direct cause of accidents and death, are the focus of considerable research attention. However, unlike unsafe driving behaviours, few studies have explored safe driving behaviours and their effects on road traffic. This study aims to verify the Chinese version of the Prosocial and Aggressive Driving Inventory (PADI) and then investigate the relationship between personality and aggressive/prosocial driving behaviours. A total of 303 licensed drivers were recruited, and they voluntarily and anonymously completed the PADI, the Driving Behaviours Questionnaire (DBQ), and personality scales (anger, sensation-seeking and altruism). The results of this research confirmed the reliability and validity of the Chinese PADI. Most importantly, it was found that different relationships between different personalities and aggressive/prosocial driving behaviours. Specifically, individuals with high altruism exhibited more prosocial driving behaviours, while individuals with high sensation seeking presented more aggressive driving behaviours. The importance of these findings lies in two main potential implications: developing an effective measurement of prosocial driving behaviours in China and providing favourable evidence to guide drivers toward more prosocial driving behaviours.     

Using topic modeling to develop multi-level descriptions of naturalistic driving data from drivers with and without sleep apnea

One challenge in using naturalistic driving data is producing a holistic analysis of these highly variable datasets. Typical analyses focus on isolated events, such as large g-force accelerations indicating a possible near-crash. Examining isolated events is ill-suited for identifying patterns in continuous activities such as maintaining vehicle control. We present an alternative approach that converts driving data into a text representation and uses topic modeling to identify patterns across the dataset. This approach enables the discovery of non-linear patterns, reduces the dimensionality of the data, and captures subtle variations in driver behavior. In this study topic models were used to concisely described patterns in trips from drivers with and without untreated obstructive sleep apnea (OSA). The analysis included 5000 trips (50 trips from 100 drivers; 66 drivers with OSA; 34 comparison drivers). Trips were treated as documents, and speed and acceleration data from the trips were converted to “driving words.” The identified patterns, called topics, were determined based on regularities in the co-occurrence of the driving words within the trips. This representation was used in random forest models to predict the driver condition (i.e., OSA or comparison) for each trip. Models with 10, 15 and 20 topics had better accuracy in predicting the driver condition, with a maximum AUC of 0.73 for a model with 20 topics. Trips from drivers with OSA were more likely to be defined by topics for smaller lateral accelerations at low speeds. The results demonstrate topic modeling as a useful tool for extracting meaningful information from naturalistic driving datasets.     

Relations between a laboratory-based sustained attention task and traffic violations in an Iranian sample of drivers

The role of cognitive abilities regarding driver behavior is crucially important in the occurrence of traffic violations and preventing tragic motor vehicle collisions. Sustained attention is one cognitive ability that may contribute to safe driving behavior. The present study investigated the relation between sustained attention and traffic violations. One hundred and one Iranian male drivers (age: M = 37.17, SD = 8.37) with at least 2 years driving experience voluntarily participated in the study. Participants were categorized into two groups based on the number of driving rule violations they committed over the last 2 years (n = 48 clean record, n = 53 violators). Sustained attention was measured by performance on the Conjunctive Continuous Performance Task (CCPT). Four CCPT performance measures were computed: (1) Mean reaction time for correct responses (M-RT); (2) standard deviation of reaction times for correct responses (SD-RT); (3) percent of omission errors (failure to respond to target stimulus); (4) percent of commission errors (identification of a non-target stimulus as target). Results showed after controlling for age and education, there was a significant group difference on M-RT, indicating that individuals with no traffic violations had faster reaction times as compared to those who had 1 or more traffic violations. No effect of group on any of the other outcomes was present after correcting for alpha inflation. When assessing the effect of age and education, education was significantly related to average reaction time and percent of omission errors. No significant effect of age was apparent. Findings suggest cognitive function, specifically sustained attention measured with a laboratory-based measure, may be associated with safe driving behavior.     

Take-over requests in highly automated driving: A crowdsourcing survey on auditory,vibrotactile, and visual displays

An important research question in the domain of highly automated driving is how to aid drivers in transitions between manual and automated control. Until highly automated cars are available, knowledge on this topic has to be obtained via simulators and self-report questionnaires. Using crowdsourcing, we surveyed 1692 people on auditory, visual, and vibrotactile take-over requests (TORs) in highly automated driving. The survey presented recordings of auditory messages and illustrations of visual and vibrational messages in traffic scenarios of various urgency levels. Multimodal TORs were the most preferred option in high-urgency scenarios. Auditory TORs were the most preferred option in low-urgency scenarios and as a confirmation message that the system is ready to switch from manual to automated mode. For low-urgency scenarios, visual-only TORs were more preferred than vibration-only TORs. Beeps with shorter interpulse intervals were perceived as more urgent, with Stevens’ power law yielding an accurate fit to the data. Spoken messages were more accepted than abstract sounds, and the female voice was more preferred than the male voice. Preferences and perceived urgency ratings were similar in middle- and high-income countries. In summary, this international survey showed that people’s preferences for TOR types in highly automated driving depend on the urgency of the situation.     

Aggressive thinking on the road. The mediation effect of aggressive thinking in the relationship between driving anger and aggression in Romanian drivers

Anger and aggression on the road have been pointed out as two of the main predictors of road accidents. However, while the emotional (anger) and behavioral (aggression) components of hostility have been deeply studied, the cognitive part has not received the same attention in this specific context. Thus, it is important to provide psychometric tools for assessing aggressive thoughts during driving, as the literature showed that cognitions play an important role in aggressive behavior. To this end, we asked Romanian drivers to answer three questionnaires: Driving Anger Thought Questionnaire (DATQ), the Driving Anger Scale (DAS) and the Driving Anger Expression Inventory (DAX), obtaining a total sample of 2133 answers. First, the psychometric properties of the DATQ were tested through a Confirmatory Factor Analysis, showing that the original 5-factor structure was maintained (Judgmental/Disbelieving Thinking, α = .93 both in men and women; Pejorative Labeling/Verbally Aggressive Thinking, α = .90 both in men and women; Physically Aggressive Thinking, α = .89 in men and α = .86 in women; Revenge/Retaliatory Thinking, α = .84 in men and α = .81 in women, and Adaptive/Constructive Expression, α = .84 in men and α = .82 in women). Then, we analyzed the mediation effect of angry thoughts between anger and aggression on the road, concluding that angry thoughts mediate this relationship. The main implications of the results are discussed.     

Accident involvement among Iranian lorry drivers: Direct and indirect effects of background variables and aberrant driving behaviour

Road accident rates among Iranian lorry drivers are considerably high and, according to empirical evidence, aberrant driving behaviours, summed to certain demographic, psycho-social and work-related factors, may explain their accident involvement. Consequently, the main aim of the study was to examine the direct and indirect effects of background variables (i.e. annual mileage, lorry driving experience, demographic and socioeconomic factors) on accident involvement mediated through aberrant driving behaviour among Iranian lorry drivers. A cross-sectional questionnaire survey was conducted in 2012 among 914 lorry drivers in 10 selected provinces in Iran. The 27-item Driver Behaviour Questionnaire (DBQ) was used to measure aberrant driving behaviour. Results from valid observations (n = 785) confirmed a four-factor solution (including ordinary violations, aggressive violations, errors, and lapses) of the DBQ. Errors, ordinary violations and aggressive violations were positively associated with accident involvement. However, lapses were not significantly associated with accident involvement. The results of structural equation modeling (SEM) further showed that, in addition to direct effects of background variables on accident involvement, several variables had indirect effects mediated by three-DBQ factors; ordinary violations, aggressive violations, and errors. Higher age, having more lorry driving experience, having higher educational attainment, and married drivers were indirectly related to less accident involvement. Annual driving mileage and the resting rate of drivers was both directly and indirectly related to accident involvement. Higher income and car ownership were directly related to fewer accidents. Interventions could aim to decrease ordinary violations, aggressive violations and errors among younger, less educated and single lorry drivers. Initiatives targeted to increase the scheduled resting frequency of lorry drivers may also hold promise.     

Associations between self-reported mindfulness,driving anger and aggressive driving

Anger and aggression on the roads is associated with how drivers evaluate the driving situation and the behaviour of other drivers. Consequently, both can be exacerbated when these evaluations are made superficially and/or when drivers have pre-existing negative schemas regarding certain types of road situations or users. Mindfulness is likely to have negative associations with anger and aggression because it promotes opposing appraisals. That is, it encourages emotion-regulation and involves acceptance of, but not reaction to, the current situation. To examine these associations, a total of 309 drivers responded to an online questionnaire assessing mindfulness, driving anger and aggressive driving. The results showed that mindfulness shared negative relationships with driving anger and self-reported aggressive driving. However, when these relationships were examined simultaneously using Structural Equation Modelling, mindfulness was found to relate only to anger and this, in turn, predicted aggressive driving. Further analysis showed that driving anger mediates the relationship between mindfulness and aggressive driving. These results suggest that mindfulness training may provide a promising intervention for drivers prone to driving anger and subsequent aggression.