Abstract:
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.
Key words:
trajectory,
sub-trajectory,
discrete Freshet distance,
TraDBSCAN algorithm,
trajectory clustering
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。
关键词:
轨迹,
分段轨迹,
离散弗雷歇距离,
TraDBSCAN算法,
轨迹聚类
CLC Number:
HAN Chen-Shou, JIA Shi-Xiong, ZHANG Lei, SHU Chang-Cheng. Sub-trajectory Clustering Algorithm Based on Speed Restriction[J]. Computer Engineering, 2011, 37(7): 219-221,236.
韩陈寿, 夏士雄, 张磊, 朱长成. 基于速度约束的分段轨迹聚类算法[J]. 计算机工程, 2011, 37(7): 219-221,236.