基于速度约束的分段轨迹聚类算法  

Sub-trajectory Clustering Algorithm Based on Speed Restriction

作　　者：韩陈寿[1] 夏士雄[1] 张磊[1] 朱长成[1] 

机构地区：[1]中国矿业大学计算机科学与技术学院,江苏徐州221116

出　　处：《计算机工程》2011年第7期219-221,236,共4页Computer Engineering

基　　金：国家自然科学基金资助项目(50674086);江苏省博士后科学基金资助项目(0701045B);中国矿业大学科技基金资助项目(2007B017)

摘　　要：目前的轨迹数据聚类直接对整条轨迹数据聚类,或先分段再对轨迹段聚类。分段聚类法抛弃轨迹段内部点,丢失轨迹局部特征,没有考虑点的速度影响。针对该问题,提出一种基于速度约束的分段轨迹数据聚类方法。该方法将速度约束和two-pass corner detection应用于轨迹分段,在邻域计算中加入速度约束,采用Discrete Fréchet Distance比较轨迹段距离,保留了轨迹段内部特征。用类似DBSCAN的TraDBSCAN算法对轨迹段进行聚类。实验结果表明,该方法考虑速度因素,可以获得更有效的聚类结果。The current trajectory data clustering algorithms do clustering directly on the whole trajectory,or on sub-trajectory after partitioning.The sub-trajectory clustering algorithms abandon all the points within the sub-trajectory,that is to say,this kind of algorithms loose sub-trajectory＇s internal features,while not considering the speed impact of points.A method for sub-trajectory data clustering taking the speed impact on consideration is proposed.The method uses speed restriction and two-pass corner detection in the segment of trajectories.It adds speed restriction in neighborhood computations and do sub-trajectory distance compared with Discrete Fréchet Distance,which keeps the internal features of sub-trajectory.Besides,TraDBSCAN algorithm that is similar to DBSCAN algorithm is applied for the clustering of sub-trajectory.Experimental results show that the new algorithm is effective and it perfectly considers the speed factor.

关 键 词：轨迹 分段轨迹 离散弗雷歇距离 TraDBSCAN算法 轨迹聚类 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]