Car driving under distraction: Effects on brain activity and driving performance in young, middle-aged and older drivers

分心驾驶是交通中的一个主要危险因素，并导致相当多的道路交通事故。注意力分散在整个生命周期中会发生变化，在非常年轻和年老的司机中会有所增强。由于未来年轻和老年司机的比例将会增加，因此制定适当的方法来减少司机的分心是很重要的。基于之前的项目“分心驾驶下的汽车驾驶：对年轻、中年和老年司机大脑活动和驾驶表现的影响”，本应用程序旨在研究两种简短的干预措施，使用额外的信息来减少年轻和老年司机在关键驾驶情况下的分心。这是a)一种模拟驾驶员辅助系统的技术相关干预，使用提示作为警告信号；b)一种以人为本的方法，使用个人反馈来告知驾驶员在分心情况下的驾驶表现。在我们提出的实验中，年轻（18-25岁）和年长（65-75岁）的汽车司机在驾驶模拟器中执行驾驶任务，在干预（提示与反馈）之前（前测试）和之后（后测试）。驾驶任务包括车道保持和制动作为对关键事件的响应。参与者必须对偶尔出现的单一干扰作出反应，前提是这些干扰不会发生在关键的驾驶情况下。在这种情况下，干扰因素必须被忽略。为了评估参与者的任务表现并分析潜在的绩效改进的潜在信息过程，将记录行为数据（反应时间和错误率）和神经生理学数据（EEG/ERP）。此外，测试后的数据将揭示，如果性能改善将保持，额外的干预刺激（提示或反馈）何时将被删除。最后，年龄相关的差异和其他可能的调节因素在两种干预措施的有效性将被调查。研究结果将扩展我们对年龄特异性和个体注意力分散和抑制的认识，并可用于开发针对年龄的方法来减少驾驶环境中的注意力分散。

Distracted driving is one major risk factor in traffic and causes a considerable number of road traffic accidents. Distractibility changes across the lifespan and is enhanced in very young and old drivers. Since the percentage of young and old drivers will increase in future, it is important to develop appropriate methods to reduce distraction of drivers. Based on the preceding project “Car driving under distraction: Effects on brain activity and driving performance in young, middle-aged and older drivers” the present application aims to investigate two short interventions, using additional information to reduce the distractibility of young and older drivers in critical driving situations. This is a) a technology-related intervention simulating a driver assistance system, using cues as warning signals, and b) a human-centered approach, using individual feedback to inform the drivers about their driving performance under distraction.In the proposed experiment, young (18-25 years) and older (65-75 years) car drivers perform a driving task in a driving simulator before (pre-test) and after (post-test) an intervention (cues vs. feedback). The driving task consists of lane-keeping and braking as a response to critical events. Participants have to respond to occasionally presented single distractors, provided that these do not occur in critical driving situations. In this case, the distractors had to be ignored. To assess participants’ task performance and analyze the underlying information processes of potential performance improvements, behavioral data (response times and error rates) and neurophysiologic data (EEG/ERP) will be recorded. Moreover, post-test data will reveal, if performance improvements will maintain, when the additional intervention-stimuli (cue or feedback) will be removed. Finally age-related differences and other possible modulating factors in the efficacy of the two interventions will be investigated.The results will expand our knowledge about age-specific and individual distractibility and inhibition and may be utilized to develop age-specific methods to reduce distractibility in driving context.