https://scholars.lib.ntu.edu.tw/handle/123456789/387203
標題: | Connected vehicle safety science, system, and framework | 作者: | Chen, K.-W. Tsai, H.-M Hsieh, C.-H Lin, S.-D Wang, C.-C Yang, S.-W Chien, S.-Y Lee, C.-H Su, Y.-C Chou, C.-T Lee, Y.-J Pao, H.-K Guo, R.-S Chen, C.-J Yang, M.-H Chen, B.-Y HSIN-MU TSAI SHAO-YI CHIEN BING-YU CHEN RUEY-SHAN GUO SHOU-DE LIN CHUN-TING CHOU YI-PING HUNG |
公開日期: | 2014 | 起(迄)頁: | 235-240 | 來源出版物: | 2014 IEEE World Forum on Internet of Things | 摘要: | In this paper, we propose a framework to develop an M2M-based (machine-to-machine) proactive driver assistance system. Unlike traditional approaches, we take the benefits of M2M in intelligent transportation system (ITS): 1) expansion of sensor coverage, 2) increase of time allowed to react, and 3) mediation of bidding for right of way, to help driver avoiding potential traffic accidents. To develop such a system, we divide it into three main parts: 1) driver behavior modeling and prediction, which collects grand driving data to learn and predict the future behaviors of drivers; 2) M2M-based neighbor map building, which includes sensing, communication, and fusion technologies to build a neighbor map, where neighbor map mentions the locations of all neighboring vehicles; 3) design of passive information visualization and proactive warning mechanism, which researches on how to provide user-needed information and warning signals to drivers without interfering their driving activities. ? 2014 IEEE. |
URI: | http://www.scopus.com/inward/record.url?eid=2-s2.0-84900387159&partnerID=MN8TOARS http://scholars.lib.ntu.edu.tw/handle/123456789/387203 |
DOI: | 10.1109/WF-IoT.2014.6803165 |
顯示於: | 資訊工程學系 |
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