Following slower drivers: Lead driver status moderates driver’s anger and behavioural responses and exonerates culpability

Two experiments investigated the effects of lead-driver status on the anger-experienced and aggression-expressed in traffic scenarios in which the lead drivers’ actions were determined by an event obviously beyond, or within, their control. Experiment I contrasted reactions to lead-cars bearing Learner driver markings (Low Status) or similar unmarked cars (Control), while Experiment II contrasted reactions to Ambulances (High Status) or otherwise identical generic work vans (Control). Reported anger, heart-rate and behaviour were measured while drivers drove. When the lead vehicle slowed or changed course because of the actions of another road user, drivers were reliably more angered when slowed by a learner driver than an unmarked sedan. Drivers reported less anger when slowed by an Ambulance, than by a work van, when there was no apparent cause for the lead-vehicle slowing. Driver behaviour also differed according to lead-vehicle status. Drivers allowed greater headway between themselves and a slower ambulance, but drove closer to the work-van, and followed Learner drivers at a dangerously close distance, leaving greater headway behind a similar, unmarked car. Reliable differences in subjective anger ratings and behaviour suggest that anger experienced and expressed depends not just on the actions of the perpetrator but on the perceived status of that perpetrator. Higher status vehicles appear to be forgiven their indiscretions more readily even when there are no extenuating circumstances, whilst lower status drivers are likely to be blamed more readily for circumstances beyond their control.     

Driving construals: Personal Construct Theory in a reckless driving context

With research revealing low road safety campaign efficacy and links between reckless driving behaviors and crash frequency, further investigation into the foundations and composition of driver education and training is required. Through two studies, the current research aimed to develop a measure that utilized the principles of Kelly’s (1955) Personal Construct Theory to (a) elicit constructs, or construals, specific to selected elements of reckless driving behaviors, (b) pilot a method in which the elicited constructs could be measured by asking participants to choose those they deemed most important, (c) group participants based on their constructs, and (d) assess between-group differences in self-reported reckless driving behavior. Results suggest that drivers can be categorized based on the constructs they use, and that rates of self-reported past engagement in reckless driving behavior, and willingness to do so in the future, vary systematically between these construal-based driver categories. Continuing research is required to develop and test applications of these findings.     

基于认知机制的有条件自动驾驶接管中的人因问题

自动驾驶能在很大程度上缓解现代交通问题并提升驾驶舒适度。有条件自动驾驶下, 驾驶员可执行非驾驶相关任务但需要在系统无法处理的状况下接管车辆。在这一关键过程中, 驾驶员需要进行注意转换并获得情境意识以成功接管。已有研究表明, 接管请求、非驾驶相关任务、驾驶情景及驾驶员因素是影响接管过程重要因素。未来可从认知机制角度研究各因素对接管过程产生的影响, 以及探究接管过程中各因素之间可能存在的交互作用。     

Traffic Offences: Planned or Habitual? Using the Theory of Planned Behaviour and habit strength to explain frequency and magnitude of speeding and driving under the influence of alcohol

This study addresses the socio‐cognitive determinants of traffic offences, in particular of speeding and drinking and driving. It has two aims: (1) to test the hypothesis of a direct effect of habits on offences (i.e., independent of intentions) by employing a specific measure of habits (i.e., the SRIH) and (2) to analyse the offences by taking account of three distinct parameters: Frequency, usual magnitude (i.e., the most frequent deviation from the law) and maximal magnitude (i.e., the greatest deviation occasionally adopted) in order to represent more accurately the variability of the offending behaviours. A total of 642 drivers replied to a questionnaire. The results corroborate the idea that intention and habit are distinct and direct determinants of offences. The use of the SRIH dismisses the criticisms made with regard to the measure of past behaviour. The distinction between the three behavioural parameters proves to be relevant, as their determinants are not exactly similar. Finally, attitude and subjective norm had direct effects on the maximal magnitude and/or on the frequency of the offence. The discussion concerns the contribution of this study to the analysis of offences as well as its limitations and addresses the theoretical plausibility of the direct effects of attitude and the subjective norm.     

Motorcycle riders’ self-reported aggression when riding compared with car driving

Aggressive driving has been shown to be related to increased crash risk for car driving. However, less is known about aggressive behaviour and motorcycle riding and whether there are differences in on-road aggression as a function of vehicle type. If such differences exist, these could relate to differences in perceptions of relative vulnerability associated with characteristics of the type of vehicle such as level of protection and performance. Specifically, the relative lack of protection offered by motorcycles may cause riders to feel more vulnerable and therefore to be less aggressive when they are riding compared to when they are driving. This study examined differences in self-reported aggression as a function of two vehicle types: passenger cars and motorcycles. Respondents (n = 247) were all motorcyclists who also drove a car. Results were that scores for the composite driving aggression scale were significantly higher than on the composite riding aggression scale. Regression analyses identified different patterns of predictors for driving aggression from those for riding aggression. Safety attitudes followed by thrill seeking tendencies were the strongest predictors for driving aggression, with more positive safety attitudes being protective whilst greater thrill seeking was associated with greater self-reported aggressive driving behaviour. For riding aggression, thrill seeking was the strongest predictor (positive relationship), followed by self-rated skill, such that higher self-rated skill was protective against riding aggression. Participants who scored at the 85th percentile or above for the aggressive driving and aggressive riding indices had significantly higher scores on thrill seeking, greater intentions to engage in future risk taking, and lower safety attitude scores than other participants. In addition participants with the highest aggressive driving scores also had higher levels of self-reported past traffic offences than other participants. Collectively, these findings suggest that people are less likely to act aggressively when riding a motorcycle than when driving a car, and that those who are the most aggressive drivers are different from those who are the most aggressive riders. However, aggressive riders and drivers appear to present a risk to themselves and others on road. Importantly, the underlying influences for aggressive riding or driving that were identified in this study may be amenable to education and training interventions.     

Human factors of transitions in automated driving: A general framework and literature survey

The topic of transitions in automated driving is becoming important now that cars are automated to ever greater extents. This paper proposes a theoretical framework to support and align human factors research on transitions in automated driving. Driving states are defined based on the allocation of primary driving tasks (i.e., lateral control, longitudinal control, and monitoring) between the driver and the automation. A transition in automated driving is defined as the process during which the human-automation system changes from one driving state to another, with transitions of monitoring activity and transitions of control being among the possibilities. Based on ‘Is the transition required?’, ‘Who initiates the transition?’, and ‘Who is in control after the transition?’, we define six types of control transitions between the driver and automation: (1) Optional Driver-Initiated Driver-in-Control, (2) Mandatory Driver-Initiated Driver-in-Control, (3) Optional Driver-Initiated Automation-in-Control, (4) Mandatory Driver-Initiated Automation-in-Control, (5) Automation-Initiated Driver-in-Control, and (6) Automation-Initiated Automation-in-Control. Use cases per transition type are introduced. Finally, we interpret previous experimental studies on transitions using our framework and identify areas for future research. We conclude that our framework of driving states and transitions is an important complement to the levels of automation proposed by transportation agencies, because it describes what the driver and automation are doing, rather than should be doing, at a moment of time.     

Characteristics of college students who text while driving: Do their perceptions of a significant other influence their decisions?

IntroductionTexting while driving is a significant risk factor for automobile collisions. The use of cell phones is prevalent among young people and commonly reported when they drive.MethodA web-based survey of 861 college student drivers determined how texting was associated with other forms of risky driving, perceptions of risk, and their driving and texting interactions with a significant other.ResultsTexting drivers were more likely to engage in other risky driving behaviors, perceived less risk in texting and driving, felt more immune to traffic risks, and had friends who text and drive. Logistic regression analyses showed that even after adjusting for risky driving behaviors and perceived risk, texting drivers were significantly more likely to do so if they saw their significant other text and drive.ConclusionsTraffic safety campaigns need to address important social influences on this behavior.     

材料模式与认知负荷对小学生类比学习的影响

探讨学习材料不同模式和学习过程不同的认知负荷对小学生类比推理学习迁移的影响.包括两个分实验.实验1探讨学习材料的不同组织模式对小学生类比推理学习迁移的影响,两组小学生分别学习模式化与非模式化的材料,然后完成迁移程度远近不同的四类测题.结果表明,非模式化条件下完成远迁移题目的成绩显著优于模式化条件下的成绩.实验2探讨小学生在不同认知负荷条件下类比推理学习的迁移效果,两组小学生分别在高认知负荷与低认知负荷情况下学习类比推理的材料,然后完成上述四类测题.结果表明,高认知负荷条件下完成远迁移题目的成绩显著优于低认知负荷条件下的成绩.本实验结果表明,对于小学生类比推理的学习来说,非模式化、高负荷的学习更有利于促进迁移,支持了积极反应理论.     

Traffic congestion,driver stress,and driver aggression

Drivers were interviewed over cellular telephones in high‐ and low‐congestion conditions during a single commute. During each interview, state measures of driver stress and driver behaviors were obtained. Behavior responses were subdivided into six categories: aggressive, information seeking, planning, minor self‐destructive, distraction, and relaxation techniques. Both state driver stress and aggression were greater in high‐ than in low‐congestion conditions. No other behavior category differed between low and high congestion. Multiple regressions were calculated to determine the predictors of state driver stress. In low congestion, time urgency predicted state driver stress, while aggression predicted driver stress in high congestion. In both conditions, a trait susceptibility toward viewing driving as generally stressful was predictive of state driver stress levels, which further strengthens the use of the Driving Behaviour Inventory—General as a predictor of “trait” driver stress. Females and males did not differentiate on state stress or any behavior category. Aggr. Behav. 25:409–423, 1999. © 1999 Wiley‐Liss, Inc.     

Identifying the main factors contributing to driving errors and traffic violations – Results from naturalistic driving data

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 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). In addition, this study identified factors determining the drivers’ willingness to perform common secondary tasks while driving, which have been associated with different degrees of crash risk. Results showed that anger, passenger presence, and persistent individual differences in driver behavior were the main factors associated with committed violations; surprise, high-risk visually distracting secondary tasks, and the driving task demand passing through an interchange were the main factors associated with errors. The willingness to engage in risky secondary tasks while driving appeared to be related to an overall tendency to engage in risky driving behaviors. However, drivers considered the driving context particularly when engaging in visually distracting secondary tasks. This study’s comprehensive approach should be a step towards generating a complete model of the variables that contribute to, or mitigate dangers in traffic.