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自主驾驶的人机交互控制
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  • 英文篇名:Survey of human-robot interaction control for autonomous driving
  • 作者:邹启杰 ; 李昊宇 ; 张汝波 ; 裴腾达 ; 刘艳
  • 英文作者:ZOU Qijie;LI Haoyu;ZHANG Rubo;PEI Tengda;LIU Yan;College of Information Engineering, Dalian University;Institute of Unmanned Systems, National University of Defense Technology;College of Mechanical and Electrical Engineering, Dalian Minzu University;
  • 关键词:人机交互 ; 自主驾驶 ; 驾驶员建模 ; 机器学习 ; 协同驾驶
  • 英文关键词:human-robot interaction;;autonomous driving;;driver modeling;;machine learning;;cooperative driving
  • 中文刊名:SDGY
  • 英文刊名:Journal of Shandong University(Engineering Science)
  • 机构:大连大学信息工程学院;国防科技大学无人研究所;大连民族大学机电工程学院;
  • 出版日期:2019-03-22 08:53
  • 出版单位:山东大学学报(工学版)
  • 年:2019
  • 期:v.49;No.234
  • 基金:国家自然科学基金面上资助项目(61673084);; 辽宁省自然科学基金资助项目(201602204)
  • 语种:中文;
  • 页:SDGY201902004
  • 页数:11
  • CN:02
  • ISSN:37-1391/T
  • 分类号:27-37
摘要
本研究对自主驾驶的人机交互中机器学习方法进行综述。通过介绍自主驾驶中人机交互研究的价值和意义,明确了人机交互问题定义以及与机器学习之间的关系,构建了自主驾驶中人机交互团队的架构。围绕提出的人机交互的系统架构和研究方法展开讨论,提出了人机交互问题解决的通用架构。并且,重点针对自主系统和驾驶员两部分介绍了相关机器学习算法,对自主驾驶中人机交互控制的未来研究进行展望,并对本研究进行总结。
        This article summarizes the machine learning methods of human-robot interaction in autonomy vehicles. By introducing the value and significance of human-robot interaction, the relationship between the human-robot interaction problem definition and machine learning were identified, the human-robot interactions team framework was built. The frameworks of human-robot interaction and the research methods of autonomous driving system were reviewed, the general structure for solving human-robot interaction problems was presented. Furthermore, its machine learning algorithm from the two aspects of autonomous control system and driver modeling was introduced. The prospects of the future research direction were summarized.
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