一种基于道路网络模型减少车辆轨迹数据量的算法

定位及移动通信的发展使我们可以获取和传输车辆在道路网络上的轨迹信息。除实现定位或导航等基本功能外,从车辆轨迹数据中还可以提取大量的交通信息,成为交通规划和管理的一个重要的信息来源。通过建立轨迹数据与道路网络之间的拓扑关系,提取轨迹数据中能代表主要信息的特征点来代替大量的轨迹数据,以达到减少轨迹数据量的目的。特征点通过一个综合了网络关系、速度币口方向的筛选方法进行提取,该方法也同时有利于建立轨迹数据检索结构和定义查询语言,系统的实验和分析验证了所提出方法的有效性。

Reducing Vehicle Tracking Data Volume through a Network-based Approach

The extended availability of GPS makes it possible to keep track of vehicles'movement for various applications in transportation. An approach is proposed to reduce tracking data volume through representing these data with feature points. Feature points can represent tracking data with much less storage space and without a loss of major characteristics than sample points or raw tracking data. A combination of three criteria, i. e. network, velocity, and direction, is used to select feature points from sample points. Network criterion, a novel concept proposed by this paper, is defined as a change of the locational relationships between vehicles and the underlying road network. Experimental and analytical results demonstrate that the proposed approach outperforms existing ones.