Track similarity judgment method and system and computer medium

A trajectory similarity and similarity technology, which is applied to computer parts, calculations, special data processing applications, etc., can solve problems such as large amount of calculation, low efficiency, and low accuracy

Pending Publication Date: 2021-05-14
BEIJING TRANWISEWAY INFORMATION TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention proposes a trajectory similarity judgment method, system and computer medium, aiming to solve the problems of large amount of calculation, low efficiency and low accuracy in the evaluation or judgment process of the existing line trajectory

Method used

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  • Track similarity judgment method and system and computer medium
  • Track similarity judgment method and system and computer medium
  • Track similarity judgment method and system and computer medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0047] figure 1 A schematic diagram of steps of a method for judging trajectory similarity according to an embodiment of the present application is shown in .

[0048] Such as figure 1 As shown, the trajectory similarity judgment method in the embodiment of the present application specifically includes the following steps:

[0049] S101: Obtain at least two routes, where the routes include multiple track points.

[0050] S102: Scaling the at least two routes into a target rectangle of the same size to obtain new coordinates of multiple track points on the at least two routes.

[0051] Specifically, the target rectangle is a square, and correspondingly, the two-dimensional matrix constructed with the square in the subsequent steps is a two-dimensional matrix with the same number of rows and columns.

[0052] figure 2 is a schematic diagram of a circumscribed rectangle of a route in a method for judging trajectory similarity according to an embodiment of the present applica...

Embodiment 2

[0085] This embodiment provides a trajectory similarity judging system. For details not disclosed in the trajectory similarity judging system in this embodiment, please refer to the specific implementation content of the trajectory similarity judging method in other embodiments.

[0086] Figure 5 A schematic structural diagram of a trajectory similarity judging system according to an embodiment of the present application is shown in .

[0087] Such as Figure 5 As shown, the trajectory similarity judging system in the embodiment of the present application specifically includes a route acquisition module 10 , a route scaling module 20 , a two-dimensional matrix module 30 and a similarity module 40 .

[0088] specific,

[0089] Route acquiring module 10: for acquiring at least two routes, the routes including multiple track points.

[0090] Route zooming module 20: for scaling the at least two routes into a target rectangle of the same size to obtain new coordinates of multi...

Embodiment 3

[0123] This embodiment provides a trajectory similarity judging device. For details not disclosed in the trajectory similarity judging device in this embodiment, please refer to the specific implementation content of the trajectory similarity judging method or system in other embodiments.

[0124] Figure 6 A schematic structural diagram of a trajectory similarity judging device 400 according to an embodiment of the present application is shown in .

[0125] Such as Figure 6 As shown, the trajectory similarity judging device 400 includes:

[0126] Memory 402: for storing executable instructions; and

[0127] Processor 401: used to connect with memory 402 to execute executable instructions so as to complete the motion vector prediction method.

[0128] Those skilled in the art can understand that the Figure 6 It is only an example of the trajectory similarity judging device 400, and does not constitute a limitation to the trajectory similarity judging device 400. It may i...

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PUM

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Abstract

The invention provides a track similarity judgment method and system and a computer medium. The method comprises the steps of: obtaining at least two routes which comprise a plurality of track points; zooming the at least two routes into target rectangles with the same size according to the same proportion to obtain new coordinates of a plurality of track points on the at least two routes; constructing a two-dimensional initial matrix of which the initial value is zero by using the target rectangles, traversing a plurality of track points on each route, and converting two-dimensional matrix values corresponding to the new coordinates of the plurality of track points on the routes into 1 to obtain at least two two-dimensional matrixes, one route corresponding to one two-dimensional matrix; and comparing the positions of the two to-be-compared routes with the value of 1 in the corresponding two-dimensional matrixes, under the condition that the positions are the same, determining that the two routes are coincident points, and obtaining the similarity of the two o-be-compared routes according to the number of the coincident points. According to the method, the to-be-compared routes are converted into the matrixes with the same size, and then the matrixes are compared, so that the judgment accuracy of the line similarity is improved.

Description

technical field [0001] The present application belongs to the technical field of artificial intelligence, and in particular relates to a method, system and computer medium for judging trajectory similarity. Background technique [0002] In the prior art, in terms of analyzing vehicle driving behavior based on trajectory data, the vehicle behavior can be analyzed according to the similarity of the trajectory, or the basis for intelligent driving can be provided according to the similarity of the trajectory. For example, by judging the similarity of routes, establishing the relationship between APP users and trucks, and then analyzing user behavior. [0003] At present, there are many methods for judging the similarity of two trajectories, such as point-based LCSS algorithm and DTW algorithm, etc., as well as shape-based Frechet algorithm and Hausdorff algorithm, and segmentation-based methods. [0004] Most of the existing technologies need to calculate the route coincidence...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9537G06K9/62
CPCG06F16/9537G06F18/22
Inventor 陈卓杨晓明夏曙东孙智彬张志平
Owner BEIJING TRANWISEWAY INFORMATION TECH
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