A Novel Driver Fatigue Assessment in Uncertain Traffic Condition

摘要：

　　In order to assess the driver fatigue in the dynamic,noisy and uncertain traffic conditions,this paper proposes a driver fatigue assessment system with a Bayesian network(BN).The multiple source feature data,such as percent eye closure and other behaviors that characterize a drivers level of fatigue,sampled from driving subsystems,are processed into training and testing data sets.Using the training data,the assessment BN is modeled,and then testing features data sets presented to the assessment BN model to detect the onset of driver fatigue.By existing BN inference algorithms,and the inference result for driver fatigue assessment is provided.The presented approach achieves the assessment with not only complete evidences but also incomplete ones.Experimental results show that the proposed approach is more effective and robust in bringing out the driver fatigue classification than the traditional Radius basis function neural network method.

关键词： Situation assessment fatigue behaviors Bayesian network inference

作者: GUO Wenqiang XIAO Qinkun HOU Yongyan ZHANG Baorong PENG Cheng

作者单位: College of Electrical & Information Engineering,Shaanxi University of Science & Technology,Xian,710 College of Electronics & Information,Xian Technological University,Xian,710032,China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 4777-4781

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）