文章基本信息

标题：Synthesizing voluntary lane-change policy using control improvisation
本地全文：下载
作者：Jin I. Ge ; Richard M. Murray
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2019
卷号：51
期号：34
页码：396-399
DOI：10.1016/j.ifacol.2019.01.007
语种：English
出版社：Elsevier
摘要：AbstractIn this work, we propose control improvisation to synthesize voluntary lane-change policy that meets human preferences under given traffic environments. We first train Markov models to describe the lane-change environment for an automated vehicle under assumed traffic patterns. Parameters in the environment model are trained using traffic data and calibrated using control improvisation. Then, based on human lane-change behavior, we train a voluntary lane-change policy using explicit-duration Markov decision process. Parameters in the lane-change policy are calibrated through control improvisation to allow an automated car to voluntarily change lanes while avoiding overly frequent lane-change maneuvers under various traffic environments.
关键词：Keywordsvoluntary lane-changingcontrol improvisationhuman car-following behavior