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无人驾驶车辆局部路径规划的时间一致性与鲁棒性研究

姜岩 王琦 龚建伟 陈慧岩

姜岩, 王琦, 龚建伟, 陈慧岩. 无人驾驶车辆局部路径规划的时间一致性与鲁棒性研究. 自动化学报, 2015, 41(3): 518-527. doi: 10.16383/j.aas.2015.c140341
引用本文: 姜岩, 王琦, 龚建伟, 陈慧岩. 无人驾驶车辆局部路径规划的时间一致性与鲁棒性研究. 自动化学报, 2015, 41(3): 518-527. doi: 10.16383/j.aas.2015.c140341
JIANG Yan, WANG Qi, GONG Jian-Wei, CHEN Hui-Yan. Research on Temporal Consistency and Robustness in Local Planning of Intelligent Vehicles. ACTA AUTOMATICA SINICA, 2015, 41(3): 518-527. doi: 10.16383/j.aas.2015.c140341
Citation: JIANG Yan, WANG Qi, GONG Jian-Wei, CHEN Hui-Yan. Research on Temporal Consistency and Robustness in Local Planning of Intelligent Vehicles. ACTA AUTOMATICA SINICA, 2015, 41(3): 518-527. doi: 10.16383/j.aas.2015.c140341

无人驾驶车辆局部路径规划的时间一致性与鲁棒性研究

doi: 10.16383/j.aas.2015.c140341
基金项目: 

国家自然科学基金(61304194, 51275041)资助

详细信息
    作者简介:

    王琦 北京理工大学智能车辆研究所博士后.主要研究方向为智能车机器人的路径规划及环境感知. E-mail: wangqi.dream@gmail.com

    通讯作者:

    姜岩 北京理工大学智能车辆研究所讲师.2010年获北京航空航天大学车辆工程系博士学位.主要研究方向为无人驾驶车辆感知, 规划和控制技术.本文通信作者.E-mail: piuzuzu@gmail.com

Research on Temporal Consistency and Robustness in Local Planning of Intelligent Vehicles

Funds: 

Supported by National Natural Science Foundation of China (61304194, 51275041)

  • 摘要: 在无人驾驶系统中,局部规划在跟踪全局路径的同时完成避障,提高了规划系统在动态未知环境中的工作能力.避障分析的有效性是局部规划最重要的功能之一.然而在仿真和实车测试中发现,广泛使用的基于优化求解的局部规划算法无法在不依赖全局精确定位时保证规划结果满足时间一致性要求.时间不一致将导致车辆的实际行驶路线偏离初始规划结果,造成避障分析失效.本文设计了基于前向预测的局部路径规划算法,在不依赖全局精确定位的前提下保证规划结果的时间一致性.除了时间一致性问题外,跟踪控制误差也是导致规划结果避障分析失效的主要原因之一.现有研究大多通过膨胀障碍物体现误差的影响,然而这种方法无法避免车辆驶入膨胀危险区域而停车.本算法在路径生成过程中增加误差影响,用通行区域代替原有不具有宽度的规划路径进行避障分析,既可以解决误差导致的避障失效,又避免出现膨胀障碍物带来的问题.通过V-Rep软件与实车规划程序进行联合仿真,在能够体现时间一致性影响的典型场景中对本算法与基于最优化曲线生成的局部路径规划算法进行比较, 验证了该算法具有更好的安全分析有效性.应用本算法的北京理工大学无人驾驶平台参加了2013年智能车未来挑战赛,在无人干预的情况下顺利完成 18公里城郊赛段和5公里城市赛段行驶,展现了良好的避障能力.
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出版历程
  • 收稿日期:  2014-05-13
  • 修回日期:  2014-10-12
  • 刊出日期:  2015-03-20

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