| 基于多通道信息融合的疲劳驾驶行为分析研究 |
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| 引用本文： | 秦洪懋,刘志强,汪澎.基于多通道信息融合的疲劳驾驶行为分析研究[J].中国安全科学学报,2011,21(2). |
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| 作者姓名： | 秦洪懋 刘志强 汪澎 |
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| 作者单位： | 江苏大学,汽车与交通工程学院,江苏,镇江,212013 |
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| 摘 要： | 为了克服单一通道信息在驾驶疲劳行为判定中的局限性,提出了综合运用多通道信息融合共同判定驾驶疲劳行为的方法。该方法在充分考虑各信息源相关性和互补性的基础上,优化采用驾驶人疲劳特征ECD、车道偏离程度SAAE、方向盘转动程度SWA等疲劳判别指标,运用MVAR进行多维特征向量提取,以有向无环支持向量机为融合算法,建立了基于多分类支持向量机的驾驶疲劳行为判定模型。结果表明,运用DAG-SVM进行多通道信息决策提高了疲劳驾驶行为检测的准确性和可靠性。
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| 关 键 词： | 交通运输安全工程 驾驶辅助系统 疲劳驾驶 支持向量机(SVM) 信息融合 |
Research on Drowsy Driving Behavior Based on Multi-channel Information Fusion |
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| QIN Hong-mao,LIU Zhi-qiang,WANG Peng.Research on Drowsy Driving Behavior Based on Multi-channel Information Fusion[J].China Safety Science Journal,2011,21(2). |
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| Authors: | QIN Hong-mao LIU Zhi-qiang WANG Peng |
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| Institution: | QIN Hong-mao LIU Zhi-qiang WANG Peng(School of Automobile & Traffic Engineering,Jiangsu University,Zhenjiang Jiangsu 212013,China) |
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| Abstract: | In order to overcome the limitations of single-channel information in the determination of drowsy driving behavior,a method was proposed based on multi-channel information fusion.According to the correlation and complementarities analysis,some parameters such as ECD(Eye Closure Degree) of driver fatigue characteristics,SAAE(Symmetry Axis Angle of EDF) of lane deviation,and SWA(Steering Wheel Angle)of steering wheel rotation degree were developed,multivariate autoregressive(MVAR) model was studied to extract... |
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| Keywords: | traffic and transportation safety engineering driver assist system driving fatigue support vector machine(SVM) information fusion |
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