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  • 标题:Design of the optimal motions of autonomous vehicles in intersections through neural networks
  • 本地全文:下载
  • 作者:Balázs Németh ; Péter Gáspár ; Dávid Szőcs
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:9
  • 页码:19-24
  • DOI:10.1016/j.ifacol.2018.07.004
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe handling of vehicle interactions is a challenge in the research into the traveling of autonomous vehicles. This paper focuses on collision-free motion design of autonomous vehicles to guarantee their minimum traveling time in intersections. First, a decision logic of the order of the vehicles in intersections is proposed. Based on the decision logic a constrained nonlinear optimization method is also proposed, with which the minimum traveling time of the vehicles without their collision is guaranteed. Since the on-line solution of the nonlinear optimization task can be numerically complex, a neural network based approximation of the optimal solution is developed. The efficiency of the method with various intersection scenarios is shown in the CarSim simulation environment.
  • 关键词:Keywordsautonomous vehiclesneural networksintersectionsconstrained nonlinear optimization
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