计算机科学 ›› 2016, Vol. 43 ›› Issue (8): 207-211.doi: 10.11896/j.issn.1002-137X.2016.08.042
高法钦
GAO Fa-qin
摘要： 研究了路网空间内的路径预测与查询技术,设计了基于统计信息和概率论的最优路径预测算法。实际应用中,路网错综复杂。提出可能路径集合的概念,并设计算法来提取当前路径预测涉及到的路网子网,减小路网规模和路径预测的复杂度。在空间网络环境下,现有移动对象位置预测技术主要针对短期预测,不能预测下一路口的交通情况。为了弥补这一缺陷,降低用户端的位置更新率,设计了路网移动模型来简洁描述提取自大量历史移动路径的移动统计特征,捕捉路口处转向模式。基于移动模型,提出了具有较高精度的交通预测模型来预测对象的运动路径。
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