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面向智能网联汽车定位的协同地图匹配算法

陈伟 杜路遥 孔海洋 傅率智 郑洪江

陈伟, 杜路遥, 孔海洋, 傅率智, 郑洪江. 面向智能网联汽车定位的协同地图匹配算法[J]. 交通信息与安全.
引用本文: 陈伟, 杜路遥, 孔海洋, 傅率智, 郑洪江. 面向智能网联汽车定位的协同地图匹配算法[J]. 交通信息与安全.
CHEN Wei, DU Luyao, KONG Haiyang, FU Shuaizhi, ZHENG Hongjiang. A Cooperative Map Matching Algorithm Applied in Intelligent and Connected Vehicle Positioning[J]. Journal of Transport Information and Safety.
Citation: CHEN Wei, DU Luyao, KONG Haiyang, FU Shuaizhi, ZHENG Hongjiang. A Cooperative Map Matching Algorithm Applied in Intelligent and Connected Vehicle Positioning[J]. Journal of Transport Information and Safety.

面向智能网联汽车定位的协同地图匹配算法

基金项目: 

国家重点研发计划项目(2018YFB0105205)、湖北省技术创新专项重大项目(2019AAA025)、武汉理工大学双一流项目资助

详细信息
    作者简介:

    陈伟(1963-),博士,教授.研究方向:交通信息工程及控制.E-mail:greatchen@whut.edu.cn

    通讯作者:

    陈伟(1963-),博士,教授.研究方向:交通信息工程及控制.E-mail:greatchen@whut.edu.cn

A Cooperative Map Matching Algorithm Applied in Intelligent and Connected Vehicle Positioning

  • 摘要: 为实现智能网联环境下低成本、高精度的车辆定位,研究了基于自适应遗传Rao-Blackwellized粒子滤波的协同地图匹配算法。利用联网车辆的定位信息和道路约束条件消除公共偏差,提高车辆定位精度。将自适应遗传算法引入到粒子滤波的重采样过程中,增加粒子的多样性,解决传统粒子滤波算法中容易出现的“粒子退化”和“粒子耗尽”问题。通过仿真实验与传统粒子滤波及卡尔曼平滑粒子滤波下的定位结果进行了对比,同时分析了不同联网车辆数目对定位精度的影响。通过实际测试验证了算法在实际应用中的定位效果。实测结果表明:以典型十字路口为例,在联网车辆数目为4的情况下,协同地图匹配算法的定位误差范围为1.67 m,分别为原始GNSS定位以及单车地图匹配定位结果的41.03%和56.80%。同时,该算法的统计定位精度(CEP)达到1.06 m,比GNSS原始定位精度提高了2.52 m,具有较好的定位效果。

     

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  • 网络出版日期:  2021-12-14

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