Method and device for analyzing advancing mode of object

Abstract

The invention provides a method and device for analyzing the advancing mode of an object, and the method comprises the steps: selecting a certain amount of trajectory data from a trajectory information base of a to-be-analyzed object according to a target position range and a target time period of the to-be-analyzed object; according to the similarity degree of the positions of the analysis objects and the staying duration, aggregating the trajectory data with the similar positions into the same set, obtaining a plurality of space-time analysis subsets, calculating the average deviation amount of each space-time analysis subset, and selecting the space-time analysis subset with the maximum average deviation amount as a sampling space-time set; deleting the points of which the average deviation is greater than zero and the staying duration is greater than a preset value to obtain a filtered sampling time-space set, and then calculating the average deviation of the filtered sampling time-space set; and judging the advancing mode of the to-be-analyzed object according to the average deviation of the filtered sampling time-space set. Interference data are effectively filtered, and the analysis efficiency and accuracy of the object advancing mode are greatly improved.

Description

technical field [0001] The present invention relates to the technical field of traveling track analysis, in particular to a method and device for analyzing the traveling mode of an object. Background technique [0002] As the society enters the era of big data, big data systems around the world are connected to a large amount of trajectory data, which stores a large amount of latitude and longitude information, and identifies the real activity of each object. The analysis of the object's travel mode is the key to confirm the investigation direction in case investigation. An important basis for judgment, how to quickly analyze the travel mode of the object has become the key to expanding the results of the battle. However, objects travel in many ways, such as airplanes, motor vehicles, automobiles, bicycles, walking, etc., and the rules are not obvious. Traditional analysis methods can only be manually viewed and analyzed piece by piece of data after the incident occurs, and ...

AI Technical Summary

Problems solved by technology

[0005] 1) The scope of the analysis of the travel mode is small. Due to the low efficiency of the manual method, it can only analyze the travel direction within a small time range, and cannot automatically correlate and analyze the results of similar time periods, and then obtain the rules and characteristics of the travel mode of the object, resulting in many Potentially valuable leads cannot be automatically mined;

[0006] 2) The timeliness of the analysis of the travel mode is poor. The traditional method can only rely on manual methods for analysis after the incident occurs. The analysis results lag behind, which affects the value of big data service business work

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