一种基于约束的最短路径低频浮动车数据地图匹配算法

Flowing Car Data Map-Matching Based on Constrained Shortest Path Algorithm

  • 摘要: 针对精度差、频率低的浮动车数据特点,给出了空间和拓扑约束下的最短路径浮动车数据地图匹配算法,基于不同采样频率的匹配结果证明算法准确度高。基于武汉市浮动车数据的匹配结果表明,算法具有高可靠性,可以用于浮动车数据的交通信息提取与特征挖掘。

     

    Abstract: As the floating car data is often with a low precision and frequency,this paper proposes a shortest path based map-matching algorithm for floating car data under spatial and topological constraints,the experimental results on different sampling frequencies data show the algorithm have a promising accuracy.Moreover,the experimental result on floating car data from Wuhan city demonstrate that the algorithm has high reliability which can be used for traffic state extraction and feature analysis.

     

/

返回文章
返回