The time-saving bias, speed choices and driving behavior

When drivers are asked to estimate how much time can be saved by increasing speed, they generally underestimate the time saved when increasing from a relatively low speed and overestimate the time saved when increasing from a relatively high speed. This time-saving bias has been demonstrated to affect drivers’ estimations of driving speed as well as drivers’ personal choice of speed. Specifically, drivers with a high time-saving bias chose unduly high speeds, which sometimes results in speeding, more frequently than drivers with a lower degree of the bias. This study sought to determine whether this relationship would be mediated by individual differences in driving behavior – including drivers’ attitudes, norms and habits regarding speeding behavior as well as their level of aberrant driving behavior (committing aggressive or ordinary violations, errors or lapses in driving, measured by the Driver Behaviour Questionnaire). The results showed that the time-saving bias predicted estimations of required speed better than any of these factors, and also better than drivers’ age, gender, education and income, as well as the number of years they have had a license and their monthly driving kilometrage, their prior speeding violations and crash involvement. In predicting drivers’ personal speed choices, the time-saving bias was second only to the frequency of committing ordinary violations.     

How does emotional intelligence predict driving behaviors among non-commercial drivers?

Dangerous driving behaviors have been found to be a leading contributor to vehicle crashes and fatalities, with more than 2.7 million people injured and 36,560 people killed in the United States in 2018 (NHTSA, 2020). Drivers’ emotions have been found to be among the leading contributors to dangerous driving behaviors. Emotions can be measured and understood through one’s emotional intelligence (EI). Previous research has confirmed the relationship between EI and dangerous driving behaviors among general driving populations in limited scope. This study analyzed dangerous driving behaviors (e.g., aggressive driving) among non-commercial US drivers. 615 US drivers ages 18 to 65 (M = 31.14, SD = 11.15) with valid US driver’s licenses (non-commercial) participated in this study. Participants completed an online survey through Qualtrics that included the Trait Emotional Intelligence Questionnaire (TEIQue-SF) to measure different dimensions of EI and the Dula Dangerous Driving Index (DDDI) and the Driving Behavior Questionnaire (DBQ) to measure dangerous driving behaviors. Furthermore, participants reported their demographic information, including age, sex, and location. Correlation analysis revealed that significant associations exist between dangerous driving behaviors and EI. The emotionality component of EI was found to be the strongest predictor of dangerous driving behaviors. The findings concluded that participants with higher EI scores engaged in less dangerous driving behavior, resulting in fewer crashes and fatalities. Thus, promoting and improving EI may be useful in preventing risky driving among non-commercial drivers. Incorporating emotional intelligence education in driver’s education, workplace training, and licensing procedures can be helpful to develop safer drivers. Further research is needed to investigate commercial drivers’ behaviors in relation to EI.     

Screening out accident-prone Iranian drivers: Are their at-fault accidents related to driving behavior?

To provide a scientific background in road safety domain a better understanding of human risk factor is crucial. The aims of the present study were the following: (1) developing an accident prediction model for estimating the at-fault accidents of drivers (2) controlling for the regression-to-the-mean and screening out the accident-prone drivers (3) identification of significant behavioral predictors in at-fault accident occurrences and delving into the relationship between the aberrant driving behaviors and at-fault accidents of those identified as accident-prone. A questionnaire survey compiling various measures of personality type, aberrant driving behavior, demographic and accident history information of 1762 Iranian drivers was conducted in which 1375 male and 387 female participants were of the average age of 35.6 (S.D. = 11.987). To analyze the obtained data, the generalized linear modeling (GLM) approach was taken resulting in four models with various independent variables. The results indicated that age, gender, education level, years of active driving, and especially exposure had an effect on drivers’ at-fault accidents while there was no discernible effect from income level, personality type and area of residence. In the screening procedure, 715 drivers were identified as accident-prone. Behavioral comparison analyses indicated that the lapses, errors, ordinary and aggressive violations are different for the accident-prone drivers. A comparison between the accident-prone and non-accident-prone drivers revealed that the ordinary violations have considerably higher effect than the others on at-fault accidents. Implications of the results are discussed with regard to insurance policies and education interventions.     

Drivers’ engagement level in Adaptive Cruise Control while distracted or impaired

Adaptive Cruise Control (ACC) is designed for convenience to maintain a set speed and specified distance from a lead vehicle. However, use of ACC may change driving patterns and perceptions over time. Many drivers perceive safety benefits associated with ACC even though the safety implications are not always clear. This study examined the factors that can influence the frequency of ACC use with surveys distributed to ACC owners in Washington State. A cluster analysis was conducted to group drivers based on how often they activated and used ACC under various driving scenarios. Four clusters emerged that showed a range of use from those who rarely used ACC in any situation (low engagement group) to those who used it for almost all situations regardless of whether it is appropriate or not (high engagement group). An ordered logit model was used to predict the likelihood of being in one of the four clusters. Drivers that were less likely to use ACC in distracting or impaired situations tend to be older, were not willing to re-purchase a similar vehicle with ACC, and were generally confused on how to use the cruise speed setting. Drivers who reported higher overall use of ACC also used the system in situations that can be considered distracting or risky, which can negate the overall benefits of ACC.     

直接经验对自主学习意愿的影响：基于计划行为理论的应用

基于计划行为理论,自编直接经验、自主学习意愿等量表,以武汉地区402名中学生为被试,系统分析直接经验对自主学习意愿的影响。结果发现：直接经验的积累可增强学习主体参与自主学习活动的意愿;直接经验对自主学习意愿的积极影响可通过行为态度等核心变量发挥间接效应实现,也可通过直接路径实现;直接经验与自主学习意愿的关系不受行为态度等核心变量调节。这些结果表明,直接经验是自主学习意愿的重要影响因子,对培养和提高学生自主学习意识具有重要价值。     

The impact of smart driving aids on driving performance and driver distraction

In-vehicle information systems (IVIS) have been shown to increase driver workload and cause distraction, both of which are causal factors for accidents. This simulator study evaluates the impact that two prototype ergonomic designs for a smart driving aid have on workload, distraction and driving performance. Scenario complexity was also manipulated as an independent variable. Results showed that real-time delivery of smart driving information did not increase driver workload or adversely affect driver distraction, while also having the positive effect of decreasing mean driving speed in both the simple and complex driving scenarios. Subjective workload was shown to increase with task difficulty, as well as revealing important differences between the two interface designs. The findings are relevant to the development and implementation of smart driving interface designs in the future.     

EPQ信度概化的跨文化比较及其启示

对中国7种主要的心理学杂志,于1998-2008年间发表的与EPQ有关的研究报告或论文做信度概化分析,并与Caruso等人对其他国家的EPQ信度概化分析结果作比较。分析结果表明：中外心理量表使用者都存在严重的“信度引入”的状况;分量表的分数的标准差是信度系数最重要的预测变量;但其他预测变量有所不同。提供的启示是：使用心理量表时一定要报告当前样本的信度系数;不符合心理量表特性要求而增加项目,不一定能提高测验结果的信度。