基于路网的移动对象轨迹压缩

传统上采用（x,y,t）点的序列表达移动对象轨迹信息,这种表达方式有两个问题：第一,由于误差导致的精度问题,GPS接收器经常产生偏离道路的位置;第二,大量的采样导致的空间复杂性数据。本文采用基于路网的移动对象轨迹模型,讨论了路网中轨迹数据压缩问题,提出了一个非线性的压缩算法。试验结果表明,该算法更好地利用了移动对象在路网上的运动规律,提高了轨迹的精度,得到了更高的压缩比。

Compression of Moving Objects Trajectory Based on Road Net

The traditional way of representing moving object trajectory is a sequence of(x,y,t) points.There are two problems with this representation of motion.First,because of the imprecision due to errors,GPS receivers often produce off-the-road locations,and secondly a large number of samplings produces data of space complexity.This paper adopts a trajectory model based on road net,discusses trajectory compression,and proposes a non-linear compression method.The testing result shows that the non-linear method can take advantage of moving rules better and can get higher precision and compression rate.