面向路网的不确定移动范围查询技术

Uncertain Moving Range Query Techniques in Road Networks

随着移动定位技术和物联网技术的不断发展,时空查询技术受到了广泛关注.在实际的应用中,对象的移动方向和轨迹常受到空间网络限制并且位置信息往往带有不确定性.在以一般性的概率分布函数形式表示位置的不确定性的基础上,提出一种基于分割区间的概率查询增量处理模型和查询优化方法.考虑采用概率分布近似中心作为目标对象的估计位置,近似地解决普遍位置不确定性的问题,以较小的精度损失换取效率上的极大提高.最后,采用真实的路网数据集和模拟的对象分布,验证了模型和算法在效率和准确性方面均表现突出.

With the continuous development of the mobile positioning technology and the Internet, spatio-temporal query processing has drawn more and more attention. In the real situation, the directions and trajectories of mobile objects are usually restricted by an underlying spatial network, and the position information is usually uncertain. Based on the general probability distribution function （PDF） used to represent the uncertainty of the positions, incremental processing model and optimization methods for probabilistic query based on split intervals are proposed. By taking the probability distribution approximate center as the estimated position of the target objects, the general position uncertainty problem is solved and the efficiency is improved with a minor cost of accuracy. Finally, based on the real-life road network dataset and synthetic object distribution, the accuracy and efficiency of the proposed models and algorithms are verified.