Estimation of Driver's Fatigue Based on Steering Wheel Angle

被引:0
作者
He, Qichang [1 ]
Li, Wei [1 ]
Fan, Xiumin [1 ]
机构
[1] Shanghai Jiao Tong Univ, Shanghai Key Lab Adv Mfg Environm, Sch Mech Engn, Shanghai 200030, Peoples R China
来源
ENGINEERING PSYCHOLOGY AND COGNITIVE ERGONOMICS | 2011年 / 6781卷
关键词
Driver fatigue; Steering wheel angle; Lane deviation; Bayesian Network model;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Driver's fatigue has been verified as a major factor in many traffic accidents. The estimation of driver's vigilance by steering wheel angle is good way because it is a non-invasive method compared with EEG. An adaptive vigilance estimation methodology based on steering wheel angle information is proposed. The sample data classification index is built from EEG and PVT information of ten driver's virtual driving experiment on driving simulator. According to the geometry information of road centerline and the location of the automobile center, a new algorithm is proposed to compute the lane deviation. The correlation coefficient between steering wheel angle and lane deviation are computed, and the results show that their correlation level is 0.05. Based on the steering wheel angle, the driver fatigue evaluation model is established by the Bayesian Network (BN). The structure and parameters for BN model are determined after adaptive training. The experiment results verified that this model is effective to identify driver's fatigue level.
引用
收藏
页码:145 / 155
页数:11
相关论文
共 16 条
[1]  
[Anonymous], INVESTIGATION LOW LE
[2]  
[Anonymous], TECHNICAL REPORT
[3]   Real-time system for monitoring driver vigilance [J].
Bergasa, LM ;
Nuevo, J ;
Sotelo, MA ;
Barea, R ;
Lopez, ME .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2006, 7 (01) :63-77
[4]   Electroencephalographic study of drowsiness in simulated driving with sleep deprivation [J].
Eoh, HJ ;
Chung, MK ;
Kim, SH .
INTERNATIONAL JOURNAL OF INDUSTRIAL ERGONOMICS, 2005, 35 (04) :307-320
[5]  
Eskandarian A, 2007, 2007 IEEE INTELLIGENT VEHICLES SYMPOSIUM, VOLS 1-3, P1284
[6]  
Gu HS, 2002, SIXTH IEEE WORKSHOP ON APPLICATIONS OF COMPUTER VISION, PROCEEDINGS, P137, DOI 10.1109/ACV.2002.1182171
[7]  
Heckerman D., 1998, Learning in Graphical Models
[8]  
Hong J.E., INT J IND ERG, V35, P307
[9]   Using EEG spectral components to assess algorithms for detecting fatigue [J].
Jap, Budi Thomas ;
Lal, Sara ;
Fischer, Peter ;
Bekiaris, Evangelos .
EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (02) :2352-2359
[10]   A critical review of the psychophysiology of driver fatigue [J].
Lal, SKL ;
Craig, A .
BIOLOGICAL PSYCHOLOGY, 2001, 55 (03) :173-194