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  • 标题:Automated driving recognition technologies for adverse weather conditions
  • 本地全文:下载
  • 作者:Keisuke Yoneda ; Naoki Suganuma ; Ryo Yanase
  • 期刊名称:IATSS Research
  • 印刷版ISSN:0386-1112
  • 出版年度:2019
  • 卷号:43
  • 期号:4
  • 页码:1-10
  • DOI:10.1016/j.iatssr.2019.11.005
  • 出版社:Elsevier
  • 摘要:During automated driving in urban areas, decisions must be made while recognizing the surrounding environment using sensors such as camera, Light Detection and Ranging (LiDAR), millimeter-wave radar (MWR), and the global navigation satellite system (GNSS). The ability to drive under various environmental conditions is an important issue for automated driving on any road. In order to introduce the automated vehicles into the markets, the ability to evaluate various traffic conditions and navigate safely presents serious challenges. Another important challenge is the development of a robust recognition system can account for adverse weather conditions. Sun glare, rain, fog, and snow are adverse weather conditions that can occur in the driving environment. This paper summarizes research focused on automated driving technologies and discuss challenges to identifying adverse weather and other situations that make driving difficult, thus complicating the introduction of automated vehicles to the market.
  • 关键词:Automated vehicle ; Self-localization ; Surrounding recognition ; Path planning ; Adverse condition
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