摘要
基于实际道路条件下的车辆行驶实验数据,通过分析驾驶人在疲劳状态下的方向盘操作特征,提出了双时间窗指标提取方法,采用该方法提取了最大零速百分比和最大角度标准差两个疲劳判别指标。以此为基础建立了Fisher线性判别算法,同时为减少对非常疲劳状态的误判,加入驾驶人疲劳状态时变判别准则,最终形成了驾驶人疲劳状态实时检测模型。使用实路数据对模型进行验证,结果表明模型对疲劳驾驶的识别率达到82%。
On-the-road driving experiments were conducted to collect data for different levels of drowsiness.An analysis of the steering wheel data was used to identify two measures,the maximum non-steering percentage and the maximum standard deviation of the steering wheel angle,calculated using the double-window method,found to be significantly different for different drowsiness levels.These were introduced into a linear drowsiness prediction model that also takes into account the drowsiness level history.Validation tests show that the method which is solely based on the driver＇s steering performance has a successful drowsiness detection of about 82%.
出处
《清华大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2010年第7期1072-1076,1081,共6页
Journal of Tsinghua University(Science and Technology)
基金
国家“八六三”高技术项目(2006AA11Z213)
关键词
疲劳驾驶
疲劳检测
方向盘操作
drowsy driving
drowsiness detection
steering performance
