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한국자동차공학회

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20권 3호 455-463 2019 [IJAT]

제목 MODELLING THE INTRUSIVE FEELINGS OF ADVANCED DRIVER ASSISTANCE SYSTEMS BASED ON VEHICLE ACTIVITY LOG DATA: CASE STUDY FOR THE LANE KEEPING ASSISTANCE SYSTEM
분야 Connected Automated Vehicles and ITS
언어 English
저자 Kyudong Park(Pohang University of Science and Technology), Jiyoung Kwahk(Pohang University of Science and Technology), Sung H. Han(Pohang University of Science and Technology), Minseok Song(Pohang University of Science and Technology), Dong Gu Choi(Pohang University of Science and Technology), Hyeji Jang(Pohang University of Science and Technology), Dohyeon Kim(Pohang University of Science and Technology), Young Deok Won(Hyundai Motor Company), In Sub Jeong(Hyundai Motor Company)
Key Words ADAS, LKAS, Vehicle activity log data, Intrusive feeling, Affective design
초록 Although the automotive industry has been among the sectors that best-understands the importance of drivers’ affect, the focus of design and research in the automotive field has long emphasized the visceral aspects of exterior and interior design. With the adoption of Advanced Driver Assistance Systems (ADAS), endowing ‘semi-autonomy’ to the vehicles, however, the scope of affective design should be expanded to include the behavioural aspects of the vehicle. In such a ‘sharedcontrol’ system wherein the vehicle can intervene in the human driver’s operations, a certain degree of ‘intrusive feelings’ are unavoidable. For example, when the Lane Keeping Assistance System (LKAS), one of the most popular examples of ADAS, operates the steering wheel in a dangerous situation, the driver may feel interrupted or surprised because of the abrupt torque generated by LKAS. This kind of unpleasant experience can lead to prolonged negative feelings such as irritation, anxiety, and distrust of the system. Therefore, there are increasing needs of investigating the driver’s affective responses towards the vehicle’s dynamic behaviour. In this study, four types of intrusive feelings caused by LKAS were identified to be proposed as a quantitative performance indicator in designing the affectively satisfactory behaviour of LKAS. A metric as well as a statistical data analysis method to quantitatively measure the intrusive feelings through the vehicle sensor log data.
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