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Evans Leaders Fund","award":["23090"],"award-info":[{"award-number":["23090"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2018,1,8]]},"abstract":"<jats:p>Distracted driving causes a large number of fatalities every year and is now becoming an important issue in the traffic safety study. In this paper, we present SafeDrive, a driving safety system that leverages wearable wrist sensing techniques to detect and analyze driver distracted behaviors. Existing wrist-worn sensing approaches, however, do not address challenges under real driving environments, such as less distinguishable gesture patterns due to in-vehicle physical constraints, various gesture hallmarks produced by different drivers and significant noise introduced by various driving conditions. In response, SafeDrive adopts a semi-supervised machine learning model for in-vehicle distracting activity detection. To improve the detection accuracy, we provide online updated classifiers by collecting real-time gesture data, while at the same time utilize smartphone sensing to generate soft hints filtering out anomalies and non-distracted hand movements. In the evaluation, we conduct extensive real-road experiments involving 20 participants (10 males and 10 females) and 5 vehicles (a sedan, a minivan and three SUVs). Our approach can achieve an average classification accuracy of over 90% with a error rate of a few percent, which demonstrate that SafeDrive is robust to real driving environments, and has great potential to help drivers shape safe driving habits.<\/jats:p>","DOI":"10.1145\/3161179","type":"journal-article","created":{"date-parts":[[2018,1,9]],"date-time":"2018-01-09T13:26:11Z","timestamp":1515504371000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":33,"title":["SafeDrive"],"prefix":"10.1145","volume":"1","author":[{"given":"Landu","family":"Jiang","sequence":"first","affiliation":[{"name":"McGill University, Montreal, QC, Canada"}]},{"given":"Xinye","family":"Lin","sequence":"additional","affiliation":[{"name":"McGill University, Montreal, QC, Canada"}]},{"given":"Xue","family":"Liu","sequence":"additional","affiliation":[{"name":"McGill University, Montreal, QC, Canada"}]},{"given":"Chongguang","family":"Bi","sequence":"additional","affiliation":[{"name":"Michigan State University, Department of Computer Science and Engineering, East Lansing, MI, USA"}]},{"given":"Guoliang","family":"Xing","sequence":"additional","affiliation":[{"name":"Michigan State University, Department of Computer Science and Engineering, East Lansing, MI, USA"}]}],"member":"320","published-online":{"date-parts":[[2018,1,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2486001.2486039"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSIPA.2009.5478674"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1080\/03610927408827101"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2742647.2742659"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3054977.3054979"},{"key":"e_1_2_1_6_1","volume-title":"Communication Systems and Networks (COMSNETS), 2014 Sixth International Conference on. 1--8.","author":"Chu Hon","year":"1991","unstructured":"Hon Chu , Vasumathi Raman , Jianbing Shen , Apoorv Kansal , Victor Bahl , and Romit Roy Choudhury . 1991 . 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