| [ 1 ] LI Y Y,TOSHIYUKI Y,ZHANG G N.The Effect of
Fatigue Driving on Injury Severity Considering the
Endogeneity[J].Journal of Safety Research,2018,64:
11-19.
[ 2 ] 李都厚,刘群,袁伟,等.疲劳驾驶与交通事故关系[J].
交通运输工程学报,2010,10(2):104-109.
[ 3 ] 胥川,裴赛君,王雪松.基于无侵入测量指标的个体差
异化驾驶疲劳检测[J].中国公路学报,2016,29(10):
118-125.
[ 4 ] 施翔匀.基于心电信号的疲劳驾驶诊断[D].北京:北
方工业大学,2019.
[ 5 ] 王洪涛,殷浩钧,陈创泉,等.基于脑电信号的驾驶疲
劳检测综述[J].华中科技大学学报(自然科学版),
2022,50(11):54-65.
[ 6 ] JEONG I C,DONG H L,PARK S W,et al.Automobile
Driver's Stress Index Provision System that Utilizes
Electrocardiogram[C]//Intelligent Vehicles Symposium.
Piscataway:IEEE,2007:652-656.
[ 7 ] 张磊,方遒,孙彦超.基于毫米波雷达的疲劳驾驶监测
系统[J].机电技术,2022(2):92-95.
[ 8 ] 王侃.基于眼电信号的疲劳驾驶检测技术的研究[D].
吉林:东北电力大学,2022.
[ 9 ] 李鑫,张晖,吴超仲等.基于脉搏波特征融合的驾驶疲
劳检测方法[J].中国公路学报,2020,33(6):168-181.
[10] SAHAYADHAS A,SUNDARAJ K,MURUGAPPAN
M.Detecting Driver Drowsiness Based on Sensors:A Review[J].Sensors,2012,12(12):16937-16953.
[11] 兰振东.基于脑电与车辆运动信息融合疲劳检测研
究[D].大连:大连理工大学,2021.
[12] 张海兵.基于方向盘握力的驾驶员状态识别系统设
计[D].太原:太原理工大学,2020.
[13] 刘志峰.车辆集成式横向安全预警系统及其关键技
术[D].北京:清华大学,2011.
[14] 郭思强,滕靖,郭旭健,等.基于车辆行驶数据的营运车
驾驶员疲劳驾驶监控研究[C]//第九届中国智能交通
年会.北京:中国智能交通协会,2014:89-100.
[15] KNIPLING R R,WIERWILLE W W.Vehicle-based
Drowsy Driver Detection:Current Status and Future
Prospects[R].Washington:United States Department of
Transportation,1994:1-22.
[16] DINGES D F,GRACE R.PERCLOS:A Valid Psychophysiological Measure of Alertness as Assessed by
Psychomotor Vigilance[J].NASA Tech Brief,1998,3:
5-9.
[17] WAHLSTROM E,MASOUD O,PAPANIKOLOPOULOS
N.Vision-based Methods for Driver Monitoring[C]//
2003 Proc IEEE International Conference.Piscataway:
IEEE,2003:382-394.
[18] 赵小平,闵忠兵,薛运强,等.新手驾驶人疲劳状态下的
视觉特性研究[J].重庆理工大学学报(自然科学),
2023,37(1):149-157.
[19] JAGANNATH M,BALASUBRAMANIAN V.Assessment of Early Onset of Driver Fatigue Using Multimodal Fatigue Measures in a Static Simulator[J].
Applied Ergonomics,2014,45(4):1140-1147.
[20] 迟健男,张国胜,刘琳娜.驾驶疲劳监测方法综述[J].
交通节能与环保,2015,11(4):84-89.
[21] MAIOR C,MOURA M,SANTANA J,et al.Real-time
Classification for Autonomous Drowsiness Detection
Using Eye Aspect Ratio[J].Expert Systems with Applications,2020,158:1-12.
[22] YOU F,GONG Y,TU H,et al.A Fatigue Driving Detection Algorithm Based on Facial Motion Information
Entropy[J].Journal of Advanced Transportation,2020
(2):1-17.
[23] CHENG Q,WANG W,JIANG X,et al.Assessment of
Driver Mental Fatigue Using Facial Landmarks[J].
IEEE Access,2019,99:1-10.
[24] 张闯,朱天军,李学民.基于深度学习和面部多特征融
合的驾驶员疲劳检测研究[J].计算机测量与控制,
2022,30(12):42-50.
[25] 陈莉莉.基于视觉特征融合的疲劳驾驶检测方法[D].
上海:上海工程技术大学,2020.
[26] KNAPIK M,CYGANEK B.Driver's Fatigue Recognition Based on Yawn Detection in Thermal Images[J].
Neurocomputing,2019(21):274-292.
[27] KIASHARI S E H,NAHVI A,BAKHODA H.et al.
Evaluation of Driver Drowsiness Using Respiration
Analysis by Thermal Imaging on a Driving Simulator
[J].Multimedia Tools and Applications,2020,79(25/
26):17793-17815. |
