A Segmented Clustering Method Based on Trajectories of Moving Objects in Spatiotemporal Information

Abstract

The invention discloses a clustering method based on mobile object spatiotemporal information trajectory subsections. The clustering method based on mobile object spatiotemporal information trajectory subsections comprises the steps that the three attributes of time, speed and direction are introduced, and a similarity calculation formula of the time, speed and direction is provided for analyzing an internal structure and an external structure of a mobile object trajectory; firstly, according to the space density of the trajectory, the trajectory is divided into a plurality of trajectory subsections, then the similarities of the trajectory subsections are judged by calculating differences of the trajectory subjections on the space, time, speed and direction, finally, trajectory subsections in a non-significant cluster are deleted or are merged into adjacent significant clusters on the basis of a first cluster result, and therefore an overall moving rule is displayed on the clustering spatial form. According to the clustering method based on the mobile object spatiotemporal information trajectory subsections, the clustering result is improved, higher application value is provided, a space quadtree is adopted to conduct indexing on the trajectory subsections, clustering efficiency is greatly improved under the environment of a large-scale trajectory number set, and trajectories can be effectively clustered.

Description

technical field [0001] The invention belongs to the technical field of clustering based on trajectory geographic coordinate values, and in particular relates to a method for segmented clustering of trajectory based on the spatiotemporal information of a moving object. Background technique [0002] The spatio-temporal trajectory is a record sequence of the position and time of a moving object, including basic information such as time, position, and speed. With the rapid development of technologies such as mobile Internet and positioning systems, a large amount of space-time trajectory (Trajectory) data can be collected in time through smart mobile terminals in application fields such as transportation and logistics. As an important spatiotemporal object data type and information source, spatiotemporal trajectory data contains rich knowledge, and its application scope covers many aspects such as human behavior, transportation logistics, emergency evacuation management, animal ...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the embodiments of the present invention is to provide a method for segmented clustering of trajectory based on the space-time information of moving objects, aiming to solve the problem that clustering is performed directly by the geographical coordinates of the trajectory, which leads to the reduction of the clustering effect

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