title: Reliable Identiﬁcation of Vehicle-Boarding Actions Based on Fuzzy Inference Syste.
abstract: Existing smartphone-based solutions to prevent distracted driving suffer from inadequate system designs that only recognize simple and clean vehicle-boarding actions, thereby failing to meet the required level of accuracy in real-life environments. In this paper, exploiting unique sensory features consistently monitored from a broad range of complicated vehicle-boarding actions, we propose a reliable and accurate system based on fuzzy inference to classify the sides of vehicle entrancebyleveragingbuilt-insmartphonesensorsonly. Theresultsofourcomprehensiveevaluation on three vehicle types with four participants demonstrate that the proposed system achieves 91.1%∼94.0% accuracy, outperforming other methods by 26.9%∼38.4% and maintains at least 87.8 %accuracy regardless of smartphone positions and vehicle types.
authors.affiliation: Department of Information and Communication Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), 333 Techno jungang-daero, Hyeonpung-myeon, Dalseong-gun, Daegu 42988, Korea. daehan@dgist.ac.kr.
authors.forename: DaeHan
authors.initials: D
authors.lastname: Ahn
authors.affiliation: Research Institute of Engineering & Technology, Hanyang University, 55 Hanyangdaehak-ro, Ansan, Gyeonggi-do 15588, Korea. hominpark@gmail.com.
authors.forename: Homin
authors.initials: H
authors.lastname: Park
authors.affiliation: Department of Interdisciplinary Engineering System, Hanyang University, 55 Hanyangdaehak-ro, Ansan, Gyeonggi-do 15588, Korea. hsh2438@naver.com.
authors.forename: Seokhyun
authors.initials: S
authors.lastname: Hwang
authors.affiliation: Department of Robotics Engineering, Hanyang University, 55 Hanyangdaehak-ro, Ansan, Gyeonggi-do 15588, Korea. taejoon@hanyang.ac.kr.
authors.forename: Taejoon
authors.initials: T
authors.lastname: Park
keywords: driver identiﬁcation; driving while distracted; fuzzy inference system; inertial sensors; vehicle-boarding actions