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  • 标题:Car-following method based on inverse reinforcement learning for autonomous vehicle decision-making
  • 本地全文:下载
  • 作者:Hongbo Gao ; Guanya Shi ; Guotao Xie
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2018
  • 卷号:15
  • 期号:6
  • DOI:10.1177/1729881418817162
  • 出版社:SAGE Publications
  • 摘要:There are still some problems need to be solved though there are a lot of achievements in the fields of automatic driving. One of those problems is the difficulty of designing a car-following decision-making system for complex traffic conditions. In recent years, reinforcement learning shows the potential in solving sequential decision optimization problems. In this article, we establish the reward function R of each driver data based on the inverse reinforcement learning algorithm, and r visualization is carried out, and then driving characteristics and following strategies are analyzed. At last, we show the efficiency of the proposed method by simulation in a highway environment.
  • 关键词:Car-following ; inverse reinforcement learning (IRL) ; autonomous vehicle ; decision-making ; automatic driving
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