GNSS高采样率路径增量地图匹配方法  

Matching the high sampled trajectory with road networks based on path increment

作　　者：王浩岩 刘远刚[1] 李少华[1] 梁博 何宗宜 WANG Haoyan;LIU Yuangang;LI Shaohua;LIANG Bo;HE Zongyi(School of Geosciences,Yangtze University,Wuhan 430100,China;School of Resource and Environmental Sciences,Wuhan University,Wuhan 430079,China)

机构地区：[1]长江大学地球科学学院,湖北武汉430100 [2]武汉大学资源与环境科学学院,湖北武汉430079

出　　处：《测绘学报》2023年第2期329-340,共12页Acta Geodaetica et Cartographica Sinica

基　　金：国家自然科学基金(42172172,41701537);地理信息工程国家重点实验室开放基(SKLGIE2016-Z-4-1,SKLGIE2017-M-4-6)。

摘　　要：针对高采样率GNSS轨迹数据在复杂城市路网中的匹配问题,本文提出一种基于路径增量的匹配方法。该方法分为组合过滤及增量匹配两个部分,首先通过组合过滤进行路网简化,然后以路径为增量进行匹配计算,在路口点处的匹配中采用综合距离因子与弯曲度的相似度评价方案。为验证其有效性,选取多条复杂程度各异的高采样率轨迹数据进行试验,并与曲率积分约束的地图匹配算法和隐马尔科夫模型两种现有匹配方法进行对比。结果表明,本文算法在高采样率匹配试验中的匹配准确率和效率均表现最优,且能够较好地处理各类复杂路段的匹配,能够满足在复杂城市路网中的高采样率轨迹匹配的需求。Aiming at matching the high sampled GNSS trajectory data with complex urban road networks,a matching method based on path increment is proposed.The method consists of two parts:combined filtering and incremental matching.Firstly,the road network is simplified through combined filtering,and then the matching process is carried out with the road paths as the increments.During the matching process at the intersection point,the similarity evaluation scheme integrating distance factor and curvature is adopted.In order to verify the effectiveness of the method,several high sampled trajectory data with different complexity are selected for experiments.The method is compared with two existing matching methods,including the curvedness feature constrained map matching method and hidden Markov model(HMM).The results show that the proposed method not only performs better in accuracy and efficiency,but also can suppress the occurrence of matching errors in various complex sections.

关 键 词：地图匹配 GNSS轨迹 高采样率 复杂路网 增量 

分 类 号：P208[天文地球—地图制图学与地理信息工程]