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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, 2021, 39(6): 162-171. doi: 10.3963/j.jssn.1674-4861.2021.06.019
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, 2021, 39(6): 162-171. doi: 10.3963/j.jssn.1674-4861.2021.06.019
CHEN Wei, DU Luyao, KONG Haiyang, FU Shuaizhi, ZHENG Hongjiang. A Cooperative Map Matching Algorithm for Intelligent and Connected Vehicle Positioning[J]. Journal of Transport Information and Safety, 2021, 39(6): 162-171. doi: 10.3963/j.jssn.1674-4861.2021.06.019
Citation: CHEN Wei, DU Luyao, KONG Haiyang, FU Shuaizhi, ZHENG Hongjiang. A Cooperative Map Matching Algorithm for Intelligent and Connected Vehicle Positioning[J]. Journal of Transport Information and Safety, 2021, 39(6): 162-171. doi: 10.3963/j.jssn.1674-4861.2021.06.019

面向智能网联汽车定位的协同地图匹配算法

doi: 10.3963/j.jssn.1674-4861.2021.06.019
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

详细信息
    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

  • 中图分类号: U495

A Cooperative Map Matching Algorithm for 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以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。

     

  • 图  1  典型协同地图匹配场景

    Figure  1.  Typical scenario of the cooperative map

    图  2  网联数据链

    Figure  2.  Datalink of the Internet of Vehicles

    图  3  对目标车辆使用道路约束条件

    Figure  3.  Applying vehicles road constraints to the target vehicle

    图  4  算法执行步骤

    Figure  4.  Steps of the algorithm

    图  5  3种不同算法对应仿真实验结果

    Figure  5.  Simulation results of three different algorithms

    图  6  多车十字路口场景

    Figure  6.  Scene of multi-vehicle intersection

    图  7  水平定位误差与联网车辆数目之间的关系

    Figure  7.  Relationship between horizontal position errors and the number of connected vehicles

    图  8  公共偏差与联网车辆数目之间的关系

    Figure  8.  Relationship between the errors of common deviation and the number of connected vehicles

    图  9  协方差行列式与联网车辆数目之间的关系

    Figure  9.  Relationship between covariance determinant and the number of connected vehicles

    图  10  实车测试场景及设备连接示意图

    Figure  10.  Test scenario and equipment connection

    图  11  水平方向定位误差和协方差行列式

    Figure  11.  Horizontal positioning error and covariance determinant

    图  12  公共偏差估计误差

    Figure  12.  Error estimate of common deviations

    图  13  水平方向定位误差分布

    Figure  13.  Distribution of horizontal positioning errors

    图  14  水平方向定位误差累积分布曲线

    Figure  14.  Cumulative distribution curves of horizontal positioning errors

    表  1  仿真参数设置

    Table  1.   Values of simulation parameters

    参数 数值 参数 数值 单位
    pc1 0.8 Δn 1 s
    pc2 0.6 σax 1 m/s2
    pm1 0.1 σay 1 m/s2
    pm2 0.001 σb 1 m/s2
    β 1 σc 0.1 m/s2
    Ns 6 σd 1 m/s2
    Nv 4 σz 1 m
    n 200
    下载: 导出CSV

    表  2  50次蒙特卡洛实验定位结果均值

    Table  2.   Means of positioning result of 50 Monte Carlo experiments

    项目 参数 粒子数目
    50 100 150 200
    静态粒子滤波 水平误差/m 3.67 3.49 3.35 3.22
    协方差/m2 4.64 4.41 4.53 4.29
    平均耗时/s 46.39 74.86 121.77 136.21
    卡尔曼平滑粒子滤波 水平误差/m 2.44 2.19 2.04 1.93
    协方差/m2 2.28 2.16 2.33 2.24
    平均耗时/s 56.46 77.39 129.68 154.37
    自适应遗传RBPF 水平误差/m 1.46 1.26 1.18 1.08
    协方差/m2 1.59 1.57 1.62 1.56
    平均耗时/s 60.36 94.17 148.59 184.11
    下载: 导出CSV

    表  3  不同联网车辆数目下定位结果

    Table  3.   Positioning results under different numbers of connected vehicles

    定位误差 GNSS 单车地图匹配 联网车辆数目/辆
    2 3 4 5 6 7 8 9 10
    水平误差/m 4.09 2.64 1.79 1.45 1.36 1.17 1.09 1.05 1.03 0.99 0.96
    估计误差/m / 2.07 1.46 1.18 1.06 0.96 0.86 0.73 0.67 0.64 0.62
    协方差/m2 6.62 2.53 2.17 1.91 1.62 1.53 1.50 1.46 1.44 1.39 1.38
    下载: 导出CSV

    表  4  测试环境和参数设置

    Table  4.   Test environment and values of parameters

    参数 设置
    测试地点 湖北省武汉市某高校校园内
    场景描述 天气晴朗的开阔室外
    基准点/m (12 726 565.898 3 547 945.341)
    通信方式 DSRC
    通信频率/Hz 5.9
    通信范围/m ≤1 500
    车辆行驶速度/(km/h) 10~30
    天线增益/dB 50
    数据更新频率/Hz 10
    数据输出频率/Hz 1
    下载: 导出CSV

    表  5  GNSS,单车地图匹配以及协同地图匹配测试结果

    Table  5.   Experimental results of GNSS, single map matching, and cooperative map matching

    东向误差/m 北向误差/m 水平误差/m 协方差行列式/m2 公共偏差估计误差/m CEP/m
    4辆车地图匹配 1.14 1.19 1.67 1.83 1.36 1.06
    单车地图匹配 2.09 2.16 2.94 2.74 2.25 2.13
    原始GNSS定位 2.86 2.78 4.07 3.48 3.58
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-09-19
  • 网络出版日期:  2022-01-12

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