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文章基本信息

  • 标题:Reverse deduction of vehicle group situation based on dynamic Bayesian network
  • 作者:Xiaoyuan Wang ; Jianqiang Wang ; Yaqi Liu
  • 期刊名称:Advances in Mechanical Engineering
  • 印刷版ISSN:1687-8140
  • 电子版ISSN:1687-8140
  • 出版年度:2018
  • 卷号:10
  • 期号:3
  • DOI:10.1177/1687814017747708
  • 语种:English
  • 出版社:Sage Publications Ltd.
  • 摘要:Vehicle group is the basic unit of microscopic traffic flow, and also a concept that often involved in the research of active vehicle security. It is of great significance to identify vehicle group situation accurately for the research of traffic flow theory and the intelligent vehicle driving system. Three-lane condition was taken as an example and the privacy protection of driver (only the data of travel time were used) was a premise in this article. Poisson’s distribution was used to identify vehicle group situation which was constituted by target vehicle and its neighboring vehicles when the target vehicle arrived at the end of study area. And the dynamic Bayesian network was used to build the reverse deduction model of vehicle group situation. The model was verified through actual and virtual driving experiments. Verification results showed that the model established in this article was reasonable and feasible.
  • 关键词:Vehicle group situation; reverse deduction; privacy protection; Poisson’s distribution; dynamic Bayesian network
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