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智能时代的汽车控制

陈虹 郭露露 宫洵 高炳钊 张琳

陈虹, 郭露露, 宫洵, 高炳钊, 张琳. 智能时代的汽车控制. 自动化学报, 2020, 46(7): 1313−1332 doi: 10.16383/j.aas.c190329
引用本文: 陈虹, 郭露露, 宫洵, 高炳钊, 张琳. 智能时代的汽车控制. 自动化学报, 2020, 46(7): 1313−1332 doi: 10.16383/j.aas.c190329
Chen Hong, Guo Lu-Lu, Gong Xun, Gao Bing-Zhao, Zhang Lin. Automotive control in intelligent era. Acta Automatica Sinica, 2020, 46(7): 1313−1332 doi: 10.16383/j.aas.c190329
Citation: Chen Hong, Guo Lu-Lu, Gong Xun, Gao Bing-Zhao, Zhang Lin. Automotive control in intelligent era. Acta Automatica Sinica, 2020, 46(7): 1313−1332 doi: 10.16383/j.aas.c190329

智能时代的汽车控制

doi: 10.16383/j.aas.c190329
基金项目: 国家自然科学基金(61790564, U1664257, U1864206, 61903152)资助
详细信息
    作者简介:

    陈虹:同济大学特聘教授、吉林大学唐敖庆讲座教授. 1997年获得德国斯图加特大学工学博士学位. 主要研究方向为预测控制, 鲁棒控制, 非线性控制, 汽车控制. E-mail: chenh@jlu.edu.cn

    郭露露:美国佐治亚大学博士后副研究员. 2019年获得吉林大学控制理论与工程博士学位. 主要研究方向为预测控制, 汽车能量管理, 智能网联汽车信息物理安全. E-mail: guoll14@mails.jlu.edu.cn

    宫洵:吉林大学助理教授. 2016年获得吉林大学控制理论与工程博士学位. 美国密歇根大学工学院博士后、联合培养博士. 主要研究方向为智能网联汽车控制与优化, 车辆大数据分析与建模. 本文通信作者. E-mail: gongxun10@hotmail.com

    高炳钊:吉林大学教授. 2009年获得日本横滨国立大学机械工程博士学位、吉林大学控制工程博士学位. 主要研究方向为汽车动力传动系统控制. E-mail: gaobingzhao@hotmail.com

    张琳:同济大学博士后. 2019年获得吉林大学工学博士学位. 主要研究方向为汽车底盘动力学控制, 智能运载测试与评价. E-mail: zhanglin_jlu@foxmail.com

Automotive Control in Intelligent Era

Funds: Supported by National Natural Science Foundation of China (61790564, U1664257, U1864206, 61903152)
  • 摘要: 自动驾驶是汽车产业发展的重要里程碑. 汽车驾驶自动化一直都在进行, 其发展进程是对驾驶人认知感知、决策规划和执行控制等各个重要环节的逐步增强或最终替代. 智能时代下, 大数据分析、泛在计算、泛在传感和人工智能等颠覆性技术为汽车驾驶自动化向着高级别迈进提供了新的机遇. 控制技术是智能时代汽车自动化进程中的基石, 更多的信息在先进控制技术的赋能下将衍生出更多的新功能与新系统, 从而实现汽车安全性、经济性以及舒适性等各个方面的提升. 本文对智能时代的汽车控制进行综述, 首先回顾汽车自动化的发展进程, 然后探讨汽车自动化进程中面临的问题, 最后梳理出一些未来智能汽车控制发展趋势与关键技术.
  • 图  1  汽车自动化分级

    Fig.  1  Levels of automotive automation

    图  2  汽车驾驶控制系统框图

    Fig.  2  Diagram of automated vehicle control system

    图  3  车辆极限工况示意图 (侧向 − 纵向)

    Fig.  3  Schematics of extreme driving condition (lateral-longitudinal)

    图  4  开放道路复杂场景的驾驶自主决策与规划技术

    Fig.  4  The technology of decision-making and planning in open road with complex scenario

    图  5  智能网联环境下的智能节能与减排技术框图

    Fig.  5  Connectivity for improved fuel economy and reduced emission

    图  6  预测安全控制框架示意图

    Fig.  6  Schematics of predictive safety control concept

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出版历程
  • 收稿日期:  2019-04-30
  • 录用日期:  2019-12-08
  • 网络出版日期:  2019-12-30
  • 刊出日期:  2020-07-24

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