Trajectory clustering method and device, and storage medium

Abstract

A trajectory clustering method comprises the steps of acquiring a target trajectory set, and the target trajectory set comprises a plurality of trajectories; dividing the tracks in the target track set according to the position data of each track in the target track set to obtain a plurality of target track subsets; respectively calculating the similarity between different tracks in each target track subset; and according to the similarity between different trajectories in each target trajectory subset and a preset similarity threshold, clustering the trajectories in each target trajectory subset to obtain a clustering result. According to the method, the tracks in the target track set are divided into the corresponding different target track subsets according to the position data of the tracks in the target track set. When trajectory clustering is carried out on different target trajectory subsets, other trajectories except the target trajectory subsets do not need to be considered, the trajectory similarity can be quickly calculated, and the discovery overhead of similar trajectories is reduced, so that the overall calculation overhead of trajectory clustering is reduced.

Description

technical field [0001] The present application relates to the field of data processing, and in particular to a method, device and storage medium for trajectory clustering. Background technique [0002] A position sensor is a sensor that can locate movable individuals such as pedestrians and vehicles. At present, a global positioning system (global positioning system, GPS) device is the most typical and commonly used position sensor. In addition, surveillance cameras, wireless Internet access (wifi) probes, mobile phone base stations and other individual identification devices with fixed positions can also be regarded as position sensors, because they can also provide individual position information through monitoring. For the needs of urban intelligent management, security, etc., the use of position sensors to collect time-space displacement data of various entities (such as pedestrians, vehicles, etc.), and the technology of data mining and analysis of these time-space dis...

AI Technical Summary

Problems solved by technology

Most of the trajectories used in the existing methods are generated by GPS devices, and the trajectory points may be at any position, which leads to the need to enumerate the spatial distance of each pair of trajectory points in the two trajectories when calculating the trajectory similarity relationship, and the time difference relationship in time, so the calculation is more difficult

In the existing trajectory clustering methods, when performing trajectory clustering, it is necessary to perform trajectory similarity calculations on a large number of trajectories, so as to find similar trajectories among these trajectories, so the number of trajectories that need to be calculated for similarity is often very large , the discovery of similar trajectories is too expensive, which leads to too much computational overhead of trajectory clustering, and the clustering efficiency is low

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