摘要
针对低频采样时地图匹配算法易出错、稳定性差等问题,提出了一种基于动态距离权重因子的隐马尔可夫模型地图匹配算法。引入动态距离权重因子优化路段检索区域,计算定位点与候选道路间的匹配度M,其数值较大的候选路段所对应的为最终确定的候选路段。研究结果表明:本文提出的匹配算法的单点匹配时间约为5.20 ms,匹配准确率可以达到90%以上,优于其他3种对比算法。
In order to solve the problem that map matching algorithm was prone to error and had poor stability for low frequency sampling,a hidden Markov model(HMM)map matching algorithm based on dynamic distance weighting factor was proposed.Segment search area was optimized,and dynamic distance weighting factor was introduced.The matching degree M was calculated between the anchor point and the candidate road.The candidate road segment with larger value was corresponding to the finally determined candidate road segment.The results show that the single-point matching time of the matching algorithm proposed in this paper is about 5.20 ms.The matching accuracy rate reaches to more than 90%,and is better than the other three comparison algorithms.
作者
滕志军
李昊天
张宇
何义昌
TENG Zhijun;LI Haotian;ZHANG Yu;HE Yichang(Key Laboratory of Modern Power System Simulation&Control&Renewable Energy Technology,Ministry of Education,Northeast Electric Power University,Jilin 132012,China;School of Electrical Engineering,Northeast Electric Power University,Jilin 132012,China;Heze Branch,China United Network Telecommunications Corporation,Heze 274000,China)
出处
《河南科技大学学报（自然科学版）》
CAS
北大核心
2020年第4期40-45,M0004,M0005,共8页
Journal of Henan University of Science And Technology:Natural Science
基金
国家自然科学青年基金项目(61501107)
吉林省教育厅“十三五”科学研究规划基金项目(JJKH20180439KJ)。
