基于生理信号分析的不同风格驾驶人疲劳特性
Fatigue characteristics of drivers with different styles based on physiological signal analysis
为了研究不同驾驶人疲劳驾驶的差异性，从生理角度出发，探究不同驾驶风格驾驶人的疲劳特性。通过 k-均值聚类将 20 名被测试人分为 3 种驾驶风格（激进型、平稳型和谨慎型），采集驾驶人的心电信号（ECG ）、肌电信号（EMG ）数据，获取其特征指标并进行单因素方差分析，最终选取ECG高频功率（high-frequency, HF）作为疲劳驾驶的表征指标，并基于HF分析结合主观询问、支持向量机（support vector machine, SVM）确定不同风格驾驶人的最优驾驶时间。研究结果表明：在0~80 min 内，激进型驾驶人疲劳积累速度最快，谨慎型驾驶人最慢；80~120 min 内，谨慎型驾驶人疲劳积累速度最快。实验结果验证了采用 HF 作为驾驶疲劳表征指标的有效性，可为不同驾驶风格类型驾驶人选择安全驾驶时间提供依据，具备一定的理论指导意义和实际应用价值。
公路运输工程生理学自动化技术、自动化技术设备
疲劳驾驶积累驾驶人风格模拟驾驶实验
马有才,莫振龙,龚俊,万平,赵小平.基于生理信号分析的不同风格驾驶人疲劳特性[EB/OL].(2022-09-27)[2025-11-05].http://www.paper.edu.cn/releasepaper/content/202209-25.点此复制
In order to study the differences of drivers in fatigue state, this paper explores the fatigue characteristics of drivers with different driving styles from the physiological point of view. Twenty subjects were divided into three driving styles by k-means clustering method, including aggressive driving style, smooth driving style and cautious driving style. The data of ECG and EMG were collected to obtain the characteristic indexes, and the one-way ANOVA was performed. Finally, ECG high-frequency (HF) power is selected as the characterization index of fatigue driving, and the optimal driving time of different styles of drivers is determined based on HF analysis combined with subjective inquiry and support vector machine (SVM). The study shows that : within 0-80 min, the fatigue accumulation speed of aggressive drivers is the fastest, and that of cautious drivers is the slowest; within 80-120 minutes, the fatigue accumulation speed of cautious drivers is the fastest. The experimental results verify the effectiveness of using HF as a driving fatigue characterization index, which can provide a basis for drivers with different driving styles to choose safe driving time, and have a certain theoretical significance and practical ap-plication value.
fatigue driving accumulationdriver stylesimulated driving test
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