Volume 39 Issue 6
Dec.  2021
Turn off MathJax
Article Contents
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

A Cooperative Map Matching Algorithm for Intelligent and Connected Vehicle Positioning

doi: 10.3963/j.jssn.1674-4861.2021.06.019
  • Received Date: 2021-09-19
    Available Online: 2022-01-12
  • A cooperative map-matching algorithm based on adaptive genetic Rao-Blackwellized particle filter is studied for low-cost and high-precision vehicle positioning in the intelligent and connected vehicle environment.The accuracy of vehicle positioning is improved using the real-time location data and road constraints of other connected vehicles. The adaptive genetic algorithm is introduced into the re-sampling process of the particle filter, increasing the diversity of particles to solve the problems of"particle degradation"and"particle exhaustion"in traditional particle filters algorithms. The model of the algorithm is established and simulated. The positioning results under the traditional particle filter and Kalman particle filter are compared, with the influences of different connected vehicle numbers on the positioning accuracy analyzed. The experiment is completed in the real scene, and the performance of the algorithm is verified. The results show that taking a typical intersection with four connected vehicles as a case study, the range of position error of cooperative map matching is 1.67 m. It is only 41.03% and56.80% of the traditional GNSS and the single map matching positioning results, respectively. The circular error probable(CEP)of this algorithm is 1.06 m, which is 2.52 m higher than the raw GNSS positioning result.

     

  • loading
  • [1]
    MOHSEN R, DENIS G, DOMINIQUE G. A novel approach for improved vehicular positioning using cooperative map matching and dynamic base station DGPS concept[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(1): 230-239. doi: 10.1109/TITS.2015.2465141
    [2]
    KARAM N, CHAUSSE F, AUFRERE R, et al. Localization of a group of communicating vehicles by state exchange[C]. 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China: IEEE, 2006.
    [3]
    YAO Jun, BALAEI A T, HASSAN M, et al. Improving cooperative positioning for vehicular Networks[J]. IEEE Transactions on Vehicular Technology, 2011, 60(6): 2810-2823. doi: 10.1109/TVT.2011.2158616
    [4]
    罗文慧, 董宝田, 王泽胜. 基于车路协同的车辆定位算法研究[J]. 西南交通大学学报, 2018, 53(5): 1072-1077. doi: 10.3969/j.issn.0258-2724.2018.05.026

    LUO Wenhui, DONG Baotian, WANG Zesheng. Algorithm based on cooperative vehicle infrastructure systems[J]. Journal of Southwest Jiaotong University, 2018, 53(5): 1072-1077. (in Chinese). doi: 10.3969/j.issn.0258-2724.2018.05.026
    [5]
    徐宏宇, 王浩, 王尔申. 基于扩展卡尔曼滤波的GPS定位数据处理方法研究[J]. 科学技术与工程, 2012, (31): 8137-8142. doi: 10.3969/j.issn.1671-1815.2012.31.002

    XU Hongyu, WANG Hao, WANG Ershen. Research of GPS positioning data processing based on extended Kalman Filtering[J]. Science Technology and Engineering, 2012(31): 8137-8142. (in Chinese). doi: 10.3969/j.issn.1671-1815.2012.31.002
    [6]
    SCHUBERT R, MATTERN N, OBST M. cooperative localization and map matching for urban road applications[C]. 18th ITS World Congress, Orlando, USA: Intelligent Transportation Society, 2011.
    [7]
    KHAOULA L, PHILIPPE B, ISABLLE F. Cooperative localization with reliable confidence domains between vehicles sharing GNSS pseudoranges errors with no base station[J]. IEEE Intelligent Transportation Systems Magazine, 2017, 9(1): 22-34. doi: 10.1109/MITS.2016.2630586
    [8]
    EFATMANESHNIK M, ALAM N, KEALY A, et al. A fast multidimensional scaling filter for vehicular cooperative positioning(Article)[J]. Journal of Navigation, 2012, 65(2): 223-243. doi: 10.1017/S0373463311000610
    [9]
    ALAM N, BALAEI A T, DEMPSTER A. Relative positioning enhancement in VANETs: A tight integration approach[J]. IEEE Transactions on Intelligent Transportation Systems, 2013, 14(1): 47-55. doi: 10.1109/TITS.2012.2205381
    [10]
    MOHSEN R, DENIS G, DOMINIQUE G. Dynamic base station DGPS for cooperative vehicle localization[C]. 2014International Conference on Connected Vehicles and Expo(ICCVE), Vienna, Austria, IEEE, 2014.
    [11]
    LIU Kai, LIM H B, FRAZZOLI E, et al. Improving positioning accuracy using GPS pseudorange measurements for cooperative vehicular localization[J]. IEEE Transactions on Vehicular Technology, 2014, 63(6): 2544-2556. doi: 10.1109/TVT.2013.2296071
    [12]
    MOHSEN R, DENIS G, DOMINIQUE G, et al. A new decentralized bayesian approach for cooperative vehicle localization based on fusion of GPS and VANET based Inter-vehicle distance measurement[J]. IEEE Intelligent Transportation Systems Magazine, 2015, 7(2): 85-95. doi: 10.1109/MITS.2015.2408171
    [13]
    殷鹏, 何玉庆, 韩建达, 等. 基于多分辨率粒子滤波的全局协同定位方法[J]. 中国科学(技术科学), 2019, 49(1): 87-96. https://www.cnki.com.cn/Article/CJFDTOTAL-JEXK201901009.htm

    YIN Peng, HE Yuqing, HAN Jianda, et al. Multi-resolution and particle filter based global cooperated localization method[J]. Science China(Technical Science), 2019, 49(1): 87-96. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JEXK201901009.htm
    [14]
    SHEN Macheng, SUN Jing, ZHAO Ding. Optimization of vehicle connections in V2V-based cooperative localization[C]. 2017 IEEE 20th International Conference on Intelligent Transportation Systems(ITSC), Yokohama, Japan: IEEE, 2017.
    [15]
    SHEN Macheng, SUN Jing, ZHAO Ding, et al. Improving localization accuracy in connected vehicle networks using Rao-Blackwellized particle filters: Theory, simulations, and experiments[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 20(6): 2255-2266. http://www.researchgate.net/profile/Ding_Zhao6/publication/313857307_Improving_Localization_Accuracy_in_Connected_Vehicle_Networks_Using_Rao-Blackwellized_Particle_Filters_Theory_Simulations_and_Experiments/links/58ad9985aca2725b540dcfd2/Improving-Localization-Accuracy-in-Connected-Vehicle-Networks-Using-Rao-Blackwellized-Particle-Filters-Theory-Simulations-and-Experiments.pdf
    [16]
    董永祥. 千寻位置CORS-RTK在建筑基坑放样中的应用[J]. 全球定位系统, 2018, 43(6): 92-97. https://www.cnki.com.cn/Article/CJFDTOTAL-QUDW201806017.htm

    DONG Yongxiang. Application of the Qianxun SI CORS-RTK in the foundation pit staking[J]. GNSS World of China, 2018, 43(6): 92-97. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-QUDW201806017.htm
    [17]
    黄飞. 基于车路协同的车辆换道辅助系统设计与实现[D]. 西安: 长安大学, 2018.

    HUANG Fei. The design and implementation of lane-changing dring assistance system based on CVIS[D]. Xi'an: Chang'an Univesity, 2018. (in Chinese).
    [18]
    VUKADINOVIC V, BAKOWSKI K, MAR-SCH P, et al. 3GPP C-V2X and IEEE 802.11p for vehicle-to-vehicle communications in highway platooning scenarios[J]. Ad Hoc Networks, 2018, 15(74): 17-29.
    [19]
    孙家兵, 何雪, 张立功. 联合多台GPS观测值计算动态定位GPS高程的改进方法[J]. 测绘通报, 2018, 16(5): 90-92. https://www.cnki.com.cn/Article/CJFDTOTAL-CHTB201805019.htm

    SUN Jiabin, HE Xue, ZHANG Ligong. The method to improve the accuracy of dynamic GPS elevation by combining multiple GPS observation[J]. Bulletin of Surveying and Mapping, 2018, 16(5): 90-92. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-CHTB201805019.htm
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(14)  / Tables(5)

    Article Metrics

    Article views (926) PDF downloads(30) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return