論文

査読有り
2019年6月

A new risk estimation model of bayesian network for adapting to driving environment changing

ICIC Express Letters, Part B: Applications
  • Zhong Zhang
  • ,
  • Taira Furuichi
  • ,
  • Takuma Ueda
  • ,
  • Takuma Akiduki
  • ,
  • Tomoaki Mashimo

10
6
開始ページ
515
終了ページ
521
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.24507/icicelb.10.06.515

© 2019, ICIC International. All rights reserved. In recent years, research on automated driving of automobiles is being promoted, and accidents caused by human error by driving support systems are also expected to decrease. However, most of the accidents occur because the risk that the driver feels subjectively is too small. Therefore, to reduce the number of traffic accidents, it is necessary to raise danger perception while driving. There are two kinds of risk in the driving environment: the subjective risk felt by the driver and the objective risk existing in the driving environment. In this research, we construct a model to estimate each risk value by using two pieces of information: traffic environment information obtained from the front image of the vehicle and driving operation information of the driver. Furthermore, by combining them the risk of adapting to the driving environment is determined, and acts to raise drivers’ perception of danger.

リンク情報
DOI
https://doi.org/10.24507/icicelb.10.06.515
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85068884164&origin=inward
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85068884164&origin=inward
ID情報
  • DOI : 10.24507/icicelb.10.06.515
  • ISSN : 2185-2766
  • SCOPUS ID : 85068884164

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