脑电在交通驾驶行为中的应用研究综述

Review on the Application of EEG in Traffic Driving Behavior Study

驾驶人是交通系统中的自驱动因素,其感知特性与交通驾驶行为密切相关,通过脑电定量分析驾驶人在驾驶过程中的大脑活动规律,是获知驾驶人感知特性的有效途径.本文主要从疲劳驾驶、分心驾驶、睡眠剥夺驾驶和其他特定场景驾驶4个方面,对脑电研究涉及的关键科学问题、实验环境、脑电信号处理方法、数据分析方法等进行归纳总结.总结发现:相关研究的本质可归结为不同驾驶状态与脑电波间的定性和定量关系研究;研究方法则主要借助真人驾驶模拟实验收集脑电等相关数据,再利用功率谱分析等信号处理技术处理脑电信号,再通过方差分析等方法对脑电信号数据进行统计分析.最后,给出了脑电研究在交通驾驶行为中的研究展望.

Drivers are ＂self-driven particle＂ factors of a traffic system, and its perception characteristics have close relationship with traffic driving behavior. It is an effective way to detect the drivers＇ perception characteristics by using electroencephalography （EEG） to analyze their brain signals quantitatively. This paper presents the key scientific problems of EEG researches, experimental environment, EEG signal processing methods and data analysis methods from four aspects which are fatigued driving, distracted driving, sleep-deprived driving and driving under some other specific conditions. It is founded that the research essence is to study the qualitative and quantitative relationship between various driving states and EEG; the common study approaches including using simulation driving experiments to collect various data, such as EEG data; and then some signal processing methods, such as power spectrum analysis, are adopted to process EEG signals; after that, statistical methods, such as variance analysis, are used to analyze the data. In the end, the potential future directions of EEG research in traffic research fields are also proposed.