面向多采样间隔大规模GPS浮动车的并行地图匹配方法研究

项目名称： 面向多采样间隔大规模GPS浮动车的并行地图匹配方法研究

项目编号： No.41201467

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 地理学

项目作者： 张弘弢

作者单位： 中国科学院深圳先进技术研究院

项目金额： 25万元

中文摘要： 本研究以大规模GPS浮动车的实时地图匹配为目标，针对当前地图匹配方法难以确保多采样间隔、大样本数据集环境下浮动车匹配的准确性和现势性问题，采用全局匹配与局部匹配并举的原则和分布式并行计算技术，开展多采样间隔大规模GPS浮动车的并行地图匹配方法研究。通过构建增量轨迹形状相似性测度，结合道路网数据的分层分级组织，实现短采样间隔浮动车的快速地图匹配；综合考虑路段实时的时间（速度）特征和浮动车历史轨迹信息，借助全局寻优思路和其他浮动车的交通行为特征，建立长采样间隔浮动车的群体地图匹配方法；在此基础上，通过对浮动车数据的合理拆分，并利用普通多核PC并行机群，研究面向大规模浮动车地图匹配的并行计算方法，以达到与分布式共享存储并行计算模型的高度耦合；提出面向路段基于线性参照坐标的匹配结果压缩存储方案。为后继基于浮动车技术的实时路况发布、交通预测、动态导航及紧急事故响应等实时动态交通信息服务奠定重要基础。

中文关键词： 地图匹配；浮动车技术；并行处理；数据挖掘；

英文摘要： The existing map matching methods of floating car are primarily targeted at high-sampling-rate, by which methods it is difficult to simultaneously guarantee the accuracy and instantaneity for the map matching of large-scale floating car. Therefore, with the objective of real-time matching large-scale floating car, this project launches a study on developing a parallel map matching approach for multi-sampling-rate and large-scale GPS-based floating car by employing the matching strategy combining the global matching and the local matching as well as the distributed parallel computing technology. First of all, the rapid map matching of high-sampling-rate floating car is implemented by establishing the incremental trajectory shape similarity measure that is integrated with the hierarchy organization of the road network data. Secondly, a colony map matching method of low-sampling-rate floating car taking both of the real-time time/speed characteristics of the road sections and the floating car historical tracking information into account is exploited by means of the global optimization belief for the shortest path search. More importantly, a functional granularity partition and parallelization method for the map matching of large-scale floating car is thoroughly investigated in this project, which has been coupled w

英文关键词： map matching；floating car technology；parallel processing；data mining；