基于增量聚类的道路网络中移动对象聚集模式检测算法设计

Design of Clustering Pattern Detection Algorithm for Moving Objects in Road Network Based on Incremental Clustering

随着位置获取技术的发展,人们采集了大量的移动对象轨迹数据,为了使交通管理精细化,利用这些数据来精确提取道路网中的拥堵或热点区域就变得越来越重要。提出一种基于增量聚类的移动对象聚集模式检测算法,以精确提取道路网络中的拥堵或热点区域。算法通过初始聚类和增量聚类更新聚类特征,并利用聚类特征计算聚类半径进行热点检测,通过实测数据和合成数据验证了算法有效性。结果表明,该算法能有效检测聚集模式并计算其生命周期,为道路网络拥堵和热点区域检测提供新方法。

With the development of location acquisition technology,a large amount of moving object trajectory data has been collected.In order to conduct fine-grained traffic management,it becomes increasingly important to use these data to accurately extract congested or hotspot areas in the road network.This paper presents a clustering pattern detection algorithm for moving objects based on incremental clustering,aiming to accurately extract congested or hotspot areas in the road network.The algorithm updates the clustering features through initial clustering and incremental clustering and uses the clustering features to calculate the clustering radius for hotspot detection.The effectiveness of the algorithm is verified by measured data and synthetic data.The results show that the algorithm can effectively detect the clustering patterns and calculate their lifecycles,providing a new approach for detecting congested and hotspot areas in road networks.