A Calculation Method of Trajectory Similarity

A trajectory similarity and calculation method technology, applied in calculation, computer components, complex mathematical operations, etc., can solve problems such as imperfect calculation accuracy and sensitive sampling frequency

Active Publication Date: 2019-07-12
HOHAI UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, DTW is sensitive to the sampling frequency, and does not use the trajectory shape as an element to calculate the trajectory similarity, resulting in a less than perfect calculation accuracy.

Method used

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  • A Calculation Method of Trajectory Similarity
  • A Calculation Method of Trajectory Similarity
  • A Calculation Method of Trajectory Similarity

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Experimental program
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Embodiment Construction

[0056] The present invention will be further explained below in conjunction with the accompanying drawings and specific embodiments.

[0057] Such as figure 1 Described, the implementation steps of the present invention are as follows:

[0058] Step 1: Collect user spatio-temporal data through the user's hand-held GPS device (mobile phone, PAD, etc.). And take two of the trajectories R and S.

[0059] Step 2: Convert the latitude and longitude coordinates into Universal Transverse Mercator projection coordinates, and use the Kalman filter algorithm to filter the trajectory data.

[0060] Step 3: Combining the point-segment distance and the Euclidean distance between points, calculate the improved spatial distance between each point in R and S.

[0061] Step 4: Calculate the predicted distance between each point in R and S

[0062] Step 5: Using the results of Step 3 and Step 4 and the angular distance between segments, calculate the distance between each segment in R and S...

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Abstract

The present invention disclose a trajectory similarity calculation method. The steps are as follows: 1. Collect user time and space data through the user handheld GPS device, and take two trajectory R and SThe coordinate system, and use the Karman filtering algorithm to filter the trajectory data; 3. Bind the distance between the point and the distance between the point of the point of the two trajectory R and SEach point of each point in R and S is predicted;Follow; 7. Bybonize the results of step 6.The beneficial effect of the present invention is that it can reduce the effect of the trajectory sampling frequency on the accuracy of the algorithm and improve the accuracy of the simultaneous measurement algorithm of the trajectory.

Description

technical field [0001] The invention belongs to the field of computer applications, in particular to a method for calculating trajectory similarity. Background technique [0002] With the development of sensor technology and personal smart devices, GPS devices are widely used to track moving objects (people, vehicles, animals, etc.), and a large amount of trajectory data is continuously generated every day. Trajectory is the spatiotemporal data sequence left by a moving object in space over time. With the promotion of the Internet of Things, urban computing and other fields, the storage and analysis of spatiotemporal data has become a research hotspot in the field of database and machine learning. Through analysis These trajectory data can bring huge impetus to all walks of life, such as planning playground infrastructure construction by analyzing the movement trajectory of playground visitors, analyzing the movement patterns of outstanding football players, and analyzing th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/18G06K9/62
CPCG06F17/18G06F18/22
Inventor 毛莺池钟海士齐海平萍戚荣志李晓芳
Owner HOHAI UNIV
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