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  • 标题:Game Theoretical Decision Making Approach for a Cooperative Lane Change
  • 本地全文:下载
  • 作者:Mark Hruszczak ; Brian Tewanima Lowe ; Frank Schrodel
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:15247-15252
  • DOI:10.1016/j.ifacol.2020.12.2312
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractRecent advances in communications technology make it possible for vehicles to interact with each other and their environment. This allows for superior maneuvers, which open up a wide range of possibilities, which conventional vehicles without communication lack. To that end, this paper examines a decision making approach for an automated and cooperative lane change maneuver, which is based on the fundamentals of game theory. The decision making algorithm is realized with intuitive benefit functions, which are modelled similar to the semantic of human driving behavior. The used benefit functions can be classified into two sub-games: player against a single player and player against the totality of all players. By mapping four distinct driving maneuvers to their respective benefits, the problem of selecting the optimal maneuver can be solved using game theory methods. After the optimal driving maneuver has been identified, the cooperative lane change can be performed. The approach has been validated in a simulated highway scenario. Simulations have shown that a cooperative lane change does not have a significant negative effect on the traffic flow.
  • 关键词:Keywordsautomated guided vehiclesautonomous vehiclesautomobile industrycooperative lane changedecision makinggame theorytraffic flow
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