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文章基本信息

  • 标题:Automotive User Profiling Using Vehicle Data Considering Different Driving Scenarios
  • 本地全文:下载
  • 作者:Bharat S. Dangra ; Mangesh V. Bedekar ; Suja S. Panicker
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2014
  • 卷号:5
  • 期号:6
  • 页码:7346-7349
  • 出版社:TechScience Publications
  • 摘要:The central idea of the paper is to find the various attributes of driver and their importance while driving so that these attributes can be used to create user profile of the drivers driving the vehicle. In this paper first we describe the architecture responsible for the generation of this attribute data and then we describe how this data can be collected and from where. Then we assigned preference to the attributes based on the seriousness of attribute, its number of occurrence and their dependencies on one another. After assigning preference we classify attributes into Primary, Secondary and Tertiary for user profile creation. Then we have described how these attributes can again be divided into Static and Dynamic for runtime comparison of driver attributes with the profiles already created. After that we consider various driving scenarios which also play crucial role in drivers driving activity.
  • 关键词:User Profiling; Driver Parameters; Vehicle Data;Driving Scenarios
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