基于交通路网的移动对象数据模型

结合城市交通路网中移动对象沿道路运行的特点,提出了一种基于交通路网的移动对象定时更新模型及其位置更新策略.该模型实现了高频采样时在保证精度的前提下对数据进行筛选以实现数据压缩,低频采样时根据路网拓扑结构和对象运行轨迹对数据进行补偿以提高教据精度.同时,它能够支持历史查询,当前查询和预测查询,并对中断信息进行处理.与传统模型相比,该模型保存的轨迹信息更接近于实际运行轨迹.

Moving Objects Data Model Based on Road Network

Considering that moving users often move on the road network, a new moving objects' timing updating model based on road network and its corresponding location update policies were proposed. Under high frequency sampling, this model makes the data compressed on the premise of high precise by selecting the timing-sampling data. And under low frequency sampling, it makes the data compensate according to the topology of the road network and the object's trajectory in order to increase the precise. In addition, this model can support three types of queries, the history, the current and the future. Even more, it takes some measures against the lost information, making this model much stronger. Compared with the traditional model, trajectory in this model is much more close to the real one.