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Titlebook: HCI in Mobility, Transport, and Automotive Systems. Driving Behavior, Urban and Smart Mobility; Second International Heidi Kr?mker Conferen

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書目名稱HCI in Mobility, Transport, and Automotive Systems. Driving Behavior, Urban and Smart Mobility
副標題Second International
編輯Heidi Kr?mker
視頻videohttp://file.papertrans.cn/421/420167/420167.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: HCI in Mobility, Transport, and Automotive Systems. Driving Behavior, Urban and Smart Mobility; Second International Heidi Kr?mker Conferen
描述.This two-volume set LNCS 12212 and 12213 constitutes the refereed proceedings of the Second International Conference on HCI in Mobility, Transport, and Automotive Systems, MobiTAS 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020, in Copenhagen, Denmark, in July, 2020.* .A total of 1439 full papers and 238 posters have been carefully reviewed and accepted for publication in HCII 2020. The papers cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. .MobiTAS 2020 includes a total of 59 papers and they are organized in the following topical sections: .Part I, Automated Driving and In-Vehicle Experience Design: UX topics in automated driving, and designing in-vehicle experiences..Part II, Driving Behavior, Urban and Smart Mobility: studies on driving behavior, and urban and smart mobility.. .*The conference was held virtually due to the COVID-19 pandemic..
出版日期Conference proceedings 2020
關鍵詞artificial intelligence; communication systems; computer hardware; computer networks; computer security;
版次1
doihttps://doi.org/10.1007/978-3-030-50537-0
isbn_softcover978-3-030-50536-3
isbn_ebook978-3-030-50537-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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es that infrared thermography might represent a complementary method for unbiasedly track the driver’s fatigue levels, without interfering with his/her comfort or task performance, and without compromising safety.
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The Elusive Trail to the Standard Model,between two drivers occurred, it would take longer to change lanes than in the estimation-success case. Furthermore, the lateral swaying of the cars was worse in the estimation-failure case than in the estimation-success case because the two drivers allocated much cognitive resources and time to mon
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https://doi.org/10.1057/9780230117518river’s alert level. And this index was highly related to the time to initiate driver’s steering operation after the RtI presentation. We have developed a prototype of the driver monitoring system that detects drivers’ eyelid movements. The findings obtained from a test course experiment and a publi
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