Fear and avoidance of driving among drivers involved in a road traffic crash. The role of traumatic fear and driving cognitions

Fear and avoidance of driving are possible consequences of involvement in road traffic crashes (RTCs). Few studies have assessed the factors associated with fear and avoidance of driving after an RTC. The aim of this present study is to investigate the relations among trauma appraisals of fear, negative driving cognitions, fear and avoidance of driving in a sample of people who experienced vehicle crashes. Further, the mediating role of negative driving cognitions in the relation between trauma appraisals, fear of driving and avoidance of driving was assessed. The sample was comprised of 116 drivers who had been involved in an RTC in the past two years. Negative driving cognitions positively predicted fear of driving and avoidance of driving. Moreover, negative driving cognitions mediated the relation among trauma appraisals of fear with fear of driving and avoidance of driving. The theoretical and practical implications of these results are discussed.     

The prevalence of cognitive disengagement in automobile crashes

The current study analysed crashes identified in a large-scale naturalistic driving database to assess the prevalence of cognitive disengagement (i.e., purely cognitive distraction and mind wandering/microsleep) or episodes wherein the driver did not look away from the roadway during secondary task completion or wherein another clearly observable contributing crash factor was not present, and the driver's reaction to the crash showed symptoms of cognitive disengagement. The study found that <1% (95% CI [0.45, 1.66]) of higher severity crashes had a potential contributing crash factor of mind wandering/microsleep; ~1.5% (95% CI [0.83, 2.32]) had a potential contributing factor of purely cognitive distraction. The results suggest a relatively low prevalence of cognitive disengagement among automotive crashes compared with visual/manual secondary tasks. However, the current methodology is limited in that it does not account for instances where cognitive disengagement, in combination with other factors, may have led to crashes, potentially leading to conservative estimates.     

When Parsimony Subdues Distinctiveness: Simplified Public Perceptions of Politicians' Personality

Voters develop uniquely simplified perceptions of political candidates' personalities during election campaigns. In an earlier study, voters described their own personalities, and also those of celebrities, using the same five factors typical of the Big Five model of personality. In contrast, the appraisal of political candidates' personalities by voters in both Italy and the United States was reduced to only a few factors. The present research extends that exploration of the relationship between personality and politics to the public's perception of politicians' personalities across a wider variety of politicians and across a long time span after an election campaign. Two studies conducted in Italy, with more than 3,000 voters, replicated the earlier results: The factors of Energy and Agreeableness are primary anchors for evaluating politicians' personalities both during campaigns and for several years thereafter. Also uncovered were congruences between the ways that voters tend to present themselves (self-schemata) and the schemata they use to evaluate candidates representing their political preference.     

音乐对驾驶警觉的影响及其理论模型

驾车时听音乐非常普遍。唤醒理论认为, 音乐可以使驾驶员处于最佳唤醒水平, 有利于驾驶警觉的维持。但是, 根据中枢容量有限理论, 音乐也会使驾驶员分心, 危害道路安全。动态模型在已有研究的基础上提出, 音乐对驾驶警觉起到唤醒抑或分心影响, 取决于音乐复杂性、驾驶情境要求及驾驶员个体差异等诸多因素的动态调节。最新的补偿控制理论则强调, 驾驶员自我调控是恢复动态平衡的关键。而未来的研究应关注驾驶员心理负荷的测量、智能车载音乐系统的开发以及驾驶员培训等领域。     

How to define the accident risk level of car drivers by combining objective and subjective measures of driving style

Perceived risk can be defined as the expectation of being involved in a traffic accident. Traffic risk perception is often subjectively evaluated being risk perception as highly individual, and depending on experiences with accidents. For this reason, a subjective measure of risk level can be useful. On the other hand, accident risk level can be measured also through objective measures, consisting in kinematic parameters defining the driving style. At this aim, it is very important to analyse instantaneous and geo-referenced travelling kinematic parameters of the vehicle recorded by real tests on the road.The aim of this paper is to identify the accident risk level of each driver based on a methodology combining both subjective and objective parameters. Specifically, by using the proposed methodology the risk can be measured immediately by using only the kinematic parameters adopted when driving; we defined three levels of risk of being involved in a road accident (low, medium, and high risk). We retain that our research can give a contribution in terms of improvement of road safety, because the distorted perception of risk level is one of the main causes of road accidents. Very often, drivers are not aware of the risk taking; therefore, it is necessary to raise the awareness of drivers to have safer driving. The proposed method can be useful for informing the driver on the level of risk he/she assumes, so that he/she can take the necessary precautions next time that will cover that stretch of road.     

Reward versus punishment: Reinforcement sensitivity theory,young novice drivers’ perceived risk,and risky driving

One reason that young novice drivers remain statistically over-represented in road deaths is their rate of engagement in risky driving. Prominent contributing factors include driver’s age, sex, personality, risk perception, and their driving experience. This study applied reinforcement sensitivity theory (RST, specifically reward sensitivity and punishment sensitivity) to predict young novice drivers’ perceived risk and self-reported risky driving engagement, while accounting for potential influences of age, sex, and driving experience. Drivers (N = 643, 490 females, 17–25 years, M = 20.02, SD = 2.32) who held an Australian driver’s license (P1, P2, or Open) anonymously completed an online survey containing the Behaviour of Young Novice Drivers Scale, the Sensitivity to Punishment and Sensitivity to Reward Questionnaire, and a measure of perceived risk of driving-related behaviours. A path analytic model derived from RST showed that perceived risk had the strongest negative association with reported risky driving engagement, followed by reward sensitivity (positive association). Respondent’s age and reward sensitivity were associated with perceived risk. Age, reward sensitivity, and perceived risk were associated with reported engagement in risky driving behaviours. Driver sex only had direct paths with RST variables, and through reward sensitivity, indirect paths to perceived risk, and reported risky driving. Neither punishment sensitivity nor driving experience contributed significantly to the model. Implications and applications of the model, and the unique set of variables examined, are discussed in relation to road safety interventions and driver training.     

Identifying effects of driving and secondary task demands,passenger presence,and driver characteristics on driving errors and traffic violations – Using naturalistic driving data segments preceding both safety critical events and matched baselines

Researchers have identified various factors that likely affect aberrant driving behaviors and therefore crash risk. However, it remains unclear which of these factors poses the greatest risk for committing either errors or violations under naturalistic driving conditions. This study investigated important variables contributing to driving errors and traffic violations based on naturalistic driving data from the second Strategic Highway Research Program (SHRP 2). The analyzed driving segments preceded both safety critical events and matched baselines. Results showed that intersection influence, high-risk visually distracting secondary tasks, and the severities of the safety critical events were the main factors associated with driving errors. The primary factors linked to violations were intersection influence, persistent individual differences in driver behavior, and the severities of the safety critical events. Furthermore, the number of aberrant driving behaviors in trip segments preceding crashes was higher than in the matched segments unrelated to safety critical events. However, the most common aberrant driving behavior types in the respective segment groups appeared to resemble each other. This suggests that crashes became more likely due to drivers committing more violations and errors overall as opposed to drivers making one certain type of error or violation.     

Safe driving communication: A regulatory focus perspective

This research article examines the effects of self‐regulation on adolescents' aggressive driving tendencies and their attitudes toward safe driving communication. Two experimental studies demonstrate that an individual's regulatory orientation is a good predictor of aggressive driving tendencies and that self‐regulation plays a moderating role on the effects of safe driving messages on recipients' attitudes. Specifically, the findings reveal that promotion‐oriented (vs. prevention‐oriented) individuals are more likely to demonstrate aggressive driving tendencies. In addition, promotion‐oriented individuals show more favorable attitudes toward gain‐framed safe driving messages than loss‐framed messages. Prevention‐oriented individuals show the opposite pattern. Implications for theory and practice are discussed.     

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.