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基于眼动特征的疲劳驾驶检测方法

DOI: 10.3969/j.issn.1006-7043.201311044

Keywords: 疲劳驾驶, 眼动特征, 支持向量机, 滑移时窗, 时窗, 检测模型

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Abstract:

为了提高疲劳驾驶检测模型准确率和实时性,基于驾驶模拟实验,利用SmartEye系统提取了驾驶人不同驾驶状态下眼动数据.基于眼动参数协议,提出了眨眼频率、PERCLOS、注视方向和注视时间4个特征参数的计算方法.分析了各特征参数的最优时窗,针对不同特征参数最优时窗差异,提出了滑移时窗的数据融合方法.基于支持向量机,搭建了疲劳驾驶检测模型.实验结果表明,该模型可以有效地进行疲劳状态检测,准确率能够达到83.84%.

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