情绪效价可预测性对时间捆绑效应的影响

时间捆绑效应指的是主观上主动动作和动作结果的时间点相互靠近的现象。其中, 时间捆绑效应可分为动作捆绑和结果捆绑, 分别对应主动动作和动作结果的时间点变化。本研究通过一个混合设计实验考察了情绪效价可预测性对时间捆绑效应的影响。情绪效价可预测性(可预测、不可预测)为被试内因素, 刺激模态(听觉刺激、视觉刺激)为被试间因素。结果发现, 情绪效价为可预测时, 结果捆绑在主动按键后产生听觉刺激或视觉刺激都出现了增强, 而动作捆绑仅在产生视觉刺激时才出现增强。结果表明, 情绪效价为可预测时会增强时间捆绑效应, 但该作用在动作捆绑和结果捆绑中存在差异。由于时间捆绑效应是反映主动控制感的主要指标, 本研究结果对先进驾驶辅助系统的交互设计具有一定的参考意义。     

Modality-general benefit of eye-closure on the retrieval of intentionally learned information

The beneficial effect of eye-closure during retrieval was demonstrated in many studies addressing eyewitness memory or memory of episodic events. Fewer studies examined the effect concerning the intentional learning of verbal information. Furthermore, the question of whether the eye-closure effect is modality-specific, boosting visual memory only, or modality-general, boosting also other forms of memory (e.g., auditory memory), is still open. These issues were addressed in the present study. Participants (N = 129) were asked to study aurally and visually presented lists of unrelated nouns (within-subjects). During free recall, participants either kept their eyes open or closed their eyes (between-subjects). Eye-closure resulted in better free recall than keeping the eyes open. Importantly, this effect emerged for both visually and aurally presented word lists, suggesting that the effect of closing the eyes is rather modality-general. The results are discussed with respect to limitations of previous studies and practical implications.     

The self-reported driving behaviour of young drivers in Lithuania: An application of the behaviour of young novice drivers scale – Lithuania (BYNDS-Li)

BackgroundWith just one year left in the Decade of Action for Road Safety, it is timely nations reflect on their progress in the realm of improving road safety more generally, and in young driver road safety specifically given the pernicious problem that is young driver risky driving behaviour and road crashes. Effective intervention requires a fundamental foundation of understanding the nature of the problem. Therefore the current study explored the self-reported risky driving behaviour of young drivers in Lithuania, a nation classified as a developed country as recently as 2015.MethodThe self-report Behaviour of Young Novice Drivers Scale (BYNDS, 1) was applied in a sample of 457 Lithuanian young drivers aged 18–24 years, after a rigorous forward-backward translation process.ResultsSeven factors (risky exposure, transient rule violations, driver misjudgements, driver mood, vehicle overcrowding, personal seatbelt use, substance consumption) explained 65.2% of the variance in self-reported risky driving behaviour as measured by the BYNDS-Li. The most common risky driving behaviours included driving in excess of posted speed limits, and driving at high risk times such as at night and on weekends.Discussion and implicationsThe seven-factor structure of the BYNDS-Li supports arguments that culturally-valid measures should be operationalised in jurisdictions other than those in which they were developed (in the case of the BYNDS, Queensland, Australia). Moreover, systems thinking argues that interventions and efforts must be multi-sectoral and collaborative interventions. In the case of young driver road safety, these should be framed within the 4E’s of education, engineering, enforcement, and engagement.     

How drivers adapt their behaviour to changes in task complexity: The role of secondary task demands and road environment factors

The present study investigates the impact of different sources of task complexity such as driving demands and secondary task demands on driver behaviour. Although much research has been dedicated to understanding the impact of secondary task demands or specific road traffic environments on driving performance, there is little information on how drivers adapt their behaviour to their combined presence. This paper aims to describe driver behaviour while negotiating different sources of task complexity, including mobile phone use while driving (i.e., calling and texting) and different road environments (i.e., straight segments, curves, hills, tunnels, and curves on hills). A driving simulator experiment was conducted to explore the effects of different road scenarios and different types of distraction while driving. The collected data was used to estimate driving behaviour through a Generalized Linear Mixed Model (GLMM) with repeated measures. The analysis was divided into two phases. Phase one aimed to evaluate driver performance under the presence and absence of pedestrians and oncoming traffic, different lanes width and different types of distraction. The second phase analysed driver behaviour when driving through different road geometries and lane widths and under different types of distraction. The results of the experiment indicated that drivers are likely to overcorrect position in the vehicle lane in the presence of pedestrians and oncoming traffic. The effect of road geometry on driver behaviour was found to be greater than the effect of mobile phone distraction. Curved roads and hills were found to influence preferred speeds and lateral position the most. The results of this investigation also show that drivers under visual-manual distraction had a higher standard deviation of speed and lateral position compared to the cognitive distraction and the non-distraction condition.     

Assessing the driving distraction effect of vehicle HMI displays using data mining techniques

With the rapid development of human–machine interface (HMI) systems in vehicles, driving distraction caused by HMI displays affects road safety. This study presents a data mining technique to model the four driving distraction indicators: speed deviation, lane departure standard deviation, dwell time, and mean glance time. Driving distraction data was collected on a real-car driving simulator. 3 secondary tasks in 13 mass produced cars were tested by 24 drivers. The random forest algorithm outperformed linear regression, extreme gradient boosting, and multi-layer perceptron as the best model, demonstrating good regression performance as well as good interpretability. The result of random forest showed that the importance of target speed is large for all driving distraction indicators. Among the variables of interaction and user interface design, less step and less on-screen distance of finger movement are efficient for lowering lane departure standard deviation and dwell time. The position of right point is another important variable, and should be between 37 and 47 degrees on a typical sample in this study. A larger angle leads to bigger lane departure, while a smaller angle leads to bigger mean glance time. Most variables of HMI display positioning themselves are not important. This study provides one driving distraction assessment method with a variable impact trend analysis for HMI secondary tasks in an early phase of product development.     

中国古代心理学思想中的注意问题

本文根据古代思想家的有关言论,探讨了他们的注意心理思想,即注意的慨念。特征,分心与分散,分配与集中,注意与感知、记忆、思维的关系,注意在学习中的作用。     

“I would have lost the respect of my friends and family if they knew I had bent the road rules”: Parents,peers, and the perilous behaviour of young drivers

Young novice drivers are at considerable risk of injury on the road. Their behaviour appears vulnerable to the social influence of their parents and friends. The nature and mechanisms of parent and peer influence on young novice driver (16–25 years) behaviour was explored via small group interviews (n = 21) and two surveys (n1 = 1170, n2 = 390) to inform more effective young driver countermeasures. Parental and peer influence occurred in pre-Licence, Learner, and Provisional (intermediate) periods. Pre-Licence and unsupervised Learner drivers reported their parents were less likely to punish risky driving (e.g., speeding). These drivers were more likely to imitate their parents and reported their parents were also risky drivers. Young novice drivers who experienced or expected social punishments from peers, including ‘being told off’ for risky driving, reported less riskiness. Conversely drivers who experienced or expected social rewards such as being ‘cheered on’ by friends – who were also more risky drivers – reported more risky driving including crashes and offences. Interventions enhancing positive influence and curtailing negative influence may improve road safety outcomes not only for young novice drivers, but for all persons who share the road with them. Parent-specific interventions warrant further development and evaluation including: modelling safe driving behaviour by parents; active monitoring of driving during novice licensure; and sharing the family vehicle during the intermediate phase. Peer-targeted interventions including modelling of safe driving behaviour and attitudes; minimisation of social reinforcement and promotion of social sanctions for risky driving also need further development and evaluation.     

A comprehensive analysis of factors leading to speeding offenses among large-truck drivers

Much research has demonstrated that speeding is the most common offense among car drivers. However, few studies have focused on this offense among drivers of large trucks. This paper investigates the factors that lead to speeding offenses for drivers of large trucks in Taiwan. The study sample consisted of information for 2101 male large-truck drivers from a national survey in 2012. The results revealed that drivers’ daily working hours ranged from 2 to 15 h with a mean of 9.67 h, and that they worked for approximately 25.23 days – and rested only 4.77 days – per month. Among these observed drivers, 11.6% reported having at least one speeding offense over a one-year period. The results of a logistic regression model presented that the factors that influenced speeding offense were not related to job experience. Rather, the driver’s demographics (age and education), mental condition (sleep quality), and driving status (yearly distance driven and driving late at night) were significantly linked to speeding offenses.