利用地图栅格化的海量浮动车数据道路匹配快速算法

李宇光; 李清泉

doi:10.13203/j.whugis20140071

利用地图栅格化的海量浮动车数据道路匹配快速算法

李宇光¹,
李清泉^2,1

¹ 武汉大学测绘遥感信息工程国家重点实验室,湖北武汉,430079;² 深圳大学空间信息智能感知与服务深圳市重点实验室,广东深圳,518060

基金项目: 深圳市科技研发资金资助项目 (ZDSY20121019111146499)；深圳市战略性新兴产业发展专项资金资助项目(JCYJ20121019111128765)；国家863计划资助项目(2012AA101701)

详细信息

作者简介:
李宇光,副教授。主要从事交通地理信息系统的理论与方法研究。

中图分类号: P208
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出版历程
- 收稿日期: 2014-01-19
- 修回日期: 2014-06-04
- 发布日期: 2014-06-04

A Fast Algorithm for Huge Volume Floating Car Data Map-Matching:A Vector to Raster Map Conversion Approach

LI Yuguang¹,
LI Qingquan^2,1

¹State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China;²Shenzhen Key Laboratory of Spatial Smart Sensing and Services,Shenzhen University,Shenzhen 518060,China

Funds: Shenzhen Scientific Research and Development Funding Program,No.ZDSY20121019111146499;Shenzhen Dedica-ted Funding of Strategic Emerging Industry Development Program,No.JCYJ20121019111128765;The National 863Program of China,No.2012AA101701.

More Information

Author Bio:
LI Yuguang,associate professor,specializes in the theories and methods of Geography Information System-Transportation.

摘要

摘要: 目的提出了在大城市路网环境下快速确定海量浮动车数据匹配路段的方法。首先构建路网道路缓冲区,再对道路缓冲区地图进行栅格化处理,并构建空间位置与道路ID的索引,然后基于每个浮动车数据中的地理位置信息依据索引找出浮动车数据可能的匹配道路,最后对这些道路进行匹配度计算,确定浮动车数据的匹配道路。实验表明,该方法能显著减少每个浮动车数据需要计算匹配度道路的数量,成倍地提高海量浮动车数据道路匹配算法的效率。
- 海量浮动车数据 /
- 道路匹配 /
- 地图栅格化 /
- 空间索引
Abstract: Objective We propose a fast algorithm for matching huge volume floating car data(FCD)with maps ofurban areas.Firstly,a road buffer is constructed.Secondly,all links buffer are conversed to rastermaps and a spatial index map between the geographical coordinate and link IDs is built.Then,thecandidate links are selected based on the coordinates of FCD and the spatial index.Finally,the map-matching degree is calculated between the FCD and the candidate links.The map-matching links are i-dentified in the results.Experiments show that the proposed method reduces the number of links thatneed be calculated for every FCD,thus resulting in efficiency improvement of the proposed map-matc-hing algorithm.
- huge volume floating car data /
- map-matching /
- raster map conversion /
- spatial index