title: Online Detection of Driver Fatigue Using Steering Wheel Angles for Real Driving Conditions.
abstract: This paper presents a drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles (SWA) collected from sensors mounted on the steering lever. The proposed system ﬁrstly extracts approximate entropy (ApEn)featuresfromﬁxedslidingwindowsonreal-timesteeringwheelanglestimeseries. Afterthat, this system linearizes the ApEn features series through an adaptive piecewise linear ﬁtting using a given deviation. Then, the detection system calculates the warping distance between the linear features series of the sample data. Finally, this system uses the warping distance to determine the drowsiness state of the driver according to a designed binary decision classiﬁer. The experimental data were collected from 14.68 h driving under real road conditions, including two fatigue levels: "wake" and "drowsy". The results show that the proposed system is capable of working online with an average 78.01% accuracy, 29.35% false detections of the "awake" state, and 15.15% false detections of the "drowsy" state. The results also conﬁrm that the proposed method based on SWA signal is valuable for applications in preventing trafﬁc accidents caused by driver fatigue.
authors.affiliation: College of Electrical and Information Engineering, Chongqing University of Science and Technology, Chongqing 401331, China. cqustlzj@sina.cn.
authors.forename: Zuojin
authors.initials: Z
authors.lastname: Li
authors.affiliation: State Key Lab of Automotive Safety and Energy, Department of Automotive Engineering, Tsinghua University, Beijing 100084, China. lisb04@gmail.com.
authors.forename: Shengbo Eben
authors.initials: SE
authors.lastname: Li
authors.affiliation: State Key Lab of Automotive Safety and Energy, Department of Automotive Engineering, Tsinghua University, Beijing 100084, China. lirenaxe@gmail.com.
authors.forename: Renjie
authors.initials: R
authors.lastname: Li
authors.affiliation: State Key Lab of Automotive Safety and Energy, Department of Automotive Engineering, Tsinghua University, Beijing 100084, China. chengbo@tsinghua.edu.cn.
authors.forename: Bo
authors.initials: B
authors.lastname: Cheng
authors.affiliation: College of Electrical and Information Engineering, Chongqing University of Science and Technology, Chongqing 401331, China. sjl@126.com.
authors.forename: Jinliang
authors.initials: J
authors.lastname: Shi
keywords: approximate entropy (ApEn); fatigue detection; steering wheel angles (SWA); warping distance