Assessing the potential impacts of connected vehicle systems on Driver’s situation awareness and driving performance

Vehicles equipped with connected vehicle technologies are able to communicate with each other and with infrastructures. Compared to Advanced Driving Assistance Systems (ADAS) using camera systems and sensor technologies, the Connected Vehicle Systems (CVS) leverage the wireless communication networks to detect hazards with a greater range, alert drivers of hazards much earlier, and therefore enhance driving safety. However, drivers’ reliance on the CVS to detect critical situations could negatively affect them maintaining situation awareness (SA) in noncritical situations when no warning is issued by the CVS. The present study conducted a driving simulator experiment with 40 participants to investigate the effect of connected vehicle systems on driver SA in normal, noncritical driving scenarios after they were exposed to the CVS with different designs of collision warning lead time (3 s, 6 s, and no warnings). After drivers experienced the CVS-supported warnings with the assigned design of lead time in critical situations, driver SA was measured in normal driving conditions using the freeze probe technique. Results revealed that drivers who experienced the CVS with early warnings (6 s) showed lower SA for normal driving events compared to those who experienced the CVS with late warnings (3 s) or no warnings. Although early warnings of CVS brought more safety benefits to drivers in critical situations, the degraded driver SA due to drivers’ reliance on such warning systems could endanger drivers when a system failure occurred. These findings highlight the importance of balancing the effects of warning lead time on driver SA and driving performance in designing connected vehicle systems.     

时间感知在跨期决策中的作用——时间决策模型的新探索

“时间”是跨期决策的“必需品”, 人们感知到的延迟时间决定跨期决策的结果。近年来, 研究者发现“时间长度感知”、“时间资源感知”和“时间框架感知”是时间感知作用于跨期决策的主要方式。时间感知的神经作用机制包含微观层面和宏观层面两种。“对数/指数时间折扣模型”、“感知时间基础模型”及“多模态漂移扩散模型”解释了时间感知的作用方式。然而, 现有理论模型还存在诸多局限, 主要包括“长短时距预测偏差”和“实际决策与预期决策偏差”两个方面。因此, 深入探讨时间感知影响跨期决策的基本方式, 分析现有理论模型的局限性并提出整合的机制框架具有十分重要的意义。未来研究亟需进一步整合时间感知的理论模型, 开展脑机制与应用方面的研究, 从深层揭露时间感知的作用本质, 帮助个人与社会更理性地决策。     

青少年时间态度与学业拖延的关系：成就动机的中介作用

采用青少年时间态度量表、成就动机量表和学业拖延问卷,对 733名中学生进行调查,旨在探究时间态度与学业拖延的关系,揭示成就动机在时间态度与学业拖延之间的中介作用机制。结果发现（1）过去消极、现在消极和未来消极与学业拖延呈显著正相关,过去积极、现在积极和未来积极与学业拖延呈显著负相关。（2）过去消极、现在消极和未来消极与成就动机呈显著负相关,过去积极、现在积极和未来积极与成就动机呈显著正相关;成就动机与学业拖延呈显著负相关。（3）成就动机在现在消极与学业拖延之间起部分中介作用,在未来积极、未来消极与学业拖延之间起完全中介作用。     

Distributional learning has immediate and long-lasting effects

Evidence of distributional learning, a statistical learning mechanism centered on relative frequency of exposure to different tokens, has mainly come from short-term learning and therefore does not ostensibly address the development of important learning processes. The present longitudinal study examines both short- and long-term effects of distributional learning of phonetic categories on non-native sound discrimination over a 12-month period. Two groups of listeners were exposed to a two-minute distribution of auditory stimuli in which the most frequently presented tokens either approximated or exaggerated the natural production of the speech sounds, whereas a control group listened to a piece of classical music for the same length of time. Discrimination by listeners in the two distribution groups improved immediately after the short exposure, replicating previous results. Crucially, this improvement was maintained after six and 12 months, demonstrating that distributional learning has long-lasting effects.