【摘要】 为解决典型草原公路交叉口交通标志组合设置现存问题，针对性优化交叉口交通工程设施组合设置。通过模拟试验，采集40名驾驶员的脑电信号，聚类为5种(MS1—MS5)微状态地形图，并对驾驶员的反应时间和微状态的持续时间、覆盖率、出现频率、转换概率进行统计分析。试验结果表明，在草原公路交叉口交通设施组合的认知过程中，驾驶员脑电微状态中的默认网络和背侧注意网络发挥主要作用；MS4的持续时间和MS1—MS3的转换概率随交通设施增多呈上升趋势，可以作为评估驾驶员认知负荷的直接指标；微状态指标和反应时趋势分析发现在信息量等级C,即4种交通工程设施组合时驾驶员大脑状态具有最佳表现，认知能力最强，负荷较小且反应最快。更多还原

【Abstract】 In order to solve the existing problem of the combination of traffic signs at typical grassland highway intersections, the combination setting of intersection traffic engineering facilities was optimized. Through simulation experiments, the electroencephalogram(EEG) signals of 40 drivers were collected, clustered into 5(MS1—MS5) microstate topographic maps, and the reaction time and duration, coverage, frequency of occurrence and conversion probability of the drivers were statistically analyzed. The experimental results showed that the default network and the dorsal attention network in the driver’s EEG microstate played a major role in the cognitive process of the combination of traffic facilities at the grassland highway intersection. The duration of MS4 and the conversion probability of MS1—MS3 increased with the increase of transportation facilities, which can be used as direct indicators to evaluate driver’s cognitive load. Microstate indicators and reaction time trend analysis found that at the information level C, that was, the combination of four traffic engineering facilities, the driver’s brain state had the best performance, the strongest cognitive ability, the smaller load and the fastest response.更多还原