CN111966767B - Track thermodynamic diagram generation method, device, electronic equipment and storage medium - Google Patents

Track thermodynamic diagram generation method, device, electronic equipment and storage medium Download PDF

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CN111966767B
CN111966767B CN202010594681.4A CN202010594681A CN111966767B CN 111966767 B CN111966767 B CN 111966767B CN 202010594681 A CN202010594681 A CN 202010594681A CN 111966767 B CN111966767 B CN 111966767B
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coordinate
distance threshold
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万江燕
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Beijing Baidu Netcom Science and Technology Co Ltd
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Abstract

The application discloses a track thermodynamic diagram generation method and device, and relates to the fields of intelligent transportation, cloud computing and big data. The specific implementation scheme is as follows: converting the geographic coordinates of the target track points to be processed currently to generate plane coordinates of the target track points; determining whether the coordinate difference value between the center point coordinate and the plane coordinate of each of the N clusters currently established is larger than a preset distance threshold value; if the coordinate difference value between the center point coordinate and the plane coordinate of the M-th cluster in the N clusters is smaller than or equal to a preset distance threshold value, adding the target track point into the M-th cluster; if the coordinate difference value between the central point coordinate and the plane coordinate of each of the N clusters is larger than a preset distance threshold value, a new cluster taking the plane coordinate as the central point coordinate is established; traversing all target track points to be processed, and generating a corresponding track thermodynamic diagram according to the track points contained in each cluster in all the established clusters.

Description

Track thermodynamic diagram generation method, device, electronic equipment and storage medium
Technical Field
Embodiments of the present application relate generally to the field of data processing technology, and more particularly, to the field of intelligent transportation, cloud computing, and big data.
Background
The space-time track is a record sequence of the position and time of the moving object, and comprises basic information such as time, position, speed and the like. With the rapid development of technologies such as mobile internet and positioning system, a large amount of space-time Trajectory (trajectry) data can be collected in time through the intelligent mobile terminal in the application fields such as traffic, logistics and the like. As an important space-time object data type and information source, the space-time track data contains rich knowledge, and the application range of the space-time track data covers various aspects of human behaviors, traffic logistics, emergency evacuation management, animal habit, marketing and the like.
For each vehicle terminal in the vehicle network, a ten-thousand magnitude space-time track may be reported, and the space-time track may contain a large number of track points, so that in order to facilitate the user to know the distribution condition of the track points reported by each vehicle terminal, a track thermodynamic diagram may be provided for the user. Therefore, how to generate a trajectory thermodynamic diagram based on the reported trajectory points has become a problem to be solved.
Disclosure of Invention
The application provides a track thermodynamic diagram generation method, a track thermodynamic diagram generation device, electronic equipment and a storage medium.
According to a first aspect, there is provided a method of generating a trajectory thermodynamic diagram, comprising:
converting the geographic coordinates of the target track points to be processed currently to generate plane coordinates of the target track points;
determining whether a coordinate difference value between a center point coordinate and the plane coordinate of each of N currently established clusters is larger than a preset distance threshold value, wherein N is larger than or equal to 1;
if the coordinate difference value between the central point coordinate of the M th cluster in the N clusters and the plane coordinate is smaller than or equal to a preset distance threshold value, adding the target track point into the M th cluster;
if the coordinate difference value between the central point coordinate of each cluster in the N clusters and the plane coordinate is larger than a preset distance threshold value, a new cluster taking the plane coordinate as the central point coordinate is established;
traversing all target track points to be processed, and generating a corresponding track thermodynamic diagram according to the track points contained in each cluster in all the established clusters.
According to a second aspect, there is provided a trajectory thermodynamic diagram generation device comprising:
The plane coordinate generation module is used for converting the geographic coordinates of the target track point to be processed currently to generate the plane coordinates of the target track point;
the first determining module is used for determining whether a coordinate difference value between a central point coordinate and the plane coordinate of each of N currently established clusters is larger than a preset distance threshold value, wherein N is larger than or equal to 1;
the adding module is used for adding the target track point to the M th cluster when the coordinate difference value between the central point coordinate of the M th cluster and the plane coordinate in the N clusters is smaller than or equal to a preset distance threshold value;
the establishing module is used for establishing a new cluster taking the plane coordinate as the center point coordinate when the coordinate difference value between the center point coordinate of each cluster in the N clusters and the plane coordinate is larger than a preset distance threshold value;
the track thermodynamic diagram generating module is used for traversing all target track points to be processed and generating a corresponding track thermodynamic diagram according to the track points contained in each cluster in all the established clusters.
According to a third aspect, there is provided an electronic device comprising:
at least one processor; and
A memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of generating a thermodynamic diagram of a trajectory as described above with respect to the embodiments of the first aspect.
According to a fourth aspect, there is provided a non-transitory computer readable storage medium storing computer instructions for causing a computer to execute the method of generating a thermodynamic diagram of a trajectory according to the embodiment of the first aspect described above.
According to the technical scheme of the embodiment of the application, before all the track points are clustered, geographic coordinates of the track points are uniformly converted into plane coordinates, and for each track point, the coordinates are converted only once, so that the time complexity is greatly reduced; in addition, the embodiment of the application firstly calculates the coordinate difference value between two points, and then compares the coordinate difference value with the distance threshold value, so as to judge whether the two points are classified into the same cluster or not according to the comparison result of the size. Therefore, compared with the traditional distance operation, the method optimizes the distance operation, can greatly reduce the calculation of a large number of floating points, reduces the use of calculation resources and improves the calculation performance.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The drawings are for better understanding of the present solution and do not constitute a limitation of the present application. Wherein:
FIG. 1 is a flow chart of a method of generating a trace thermodynamic diagram provided in accordance with an embodiment of the present application;
FIG. 2 is a flow chart of another method of generating a trace thermodynamic diagram provided in accordance with an embodiment of the present application;
FIG. 3 is a flow chart of yet another method of generating a trace thermodynamic diagram provided in accordance with an embodiment of the present application;
FIG. 4 is a flow chart of another method of generating a trace thermodynamic diagram provided in accordance with an embodiment of the present application;
FIG. 5 is a flow chart of yet another method of generating a trace thermodynamic diagram provided in accordance with an embodiment of the present application;
FIG. 6 is a block diagram of a track thermodynamic diagram generation device according to an embodiment of the present application;
FIG. 7 is a block diagram of another trace thermodynamic diagram generation device according to an embodiment of the present application;
fig. 8 is a block diagram of an electronic device for implementing a track thermodynamic diagram generation method of an embodiment of the present application.
Detailed Description
Exemplary embodiments of the present application are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
FIG. 1 is a flow chart of a method of generating a trace thermodynamic diagram in accordance with one embodiment of the present application. The track thermodynamic diagram generating method according to the embodiment of the present application may be applied to the track thermodynamic diagram generating device according to the embodiment of the present application, and the track thermodynamic diagram generating device may be configured in an electronic apparatus. Wherein the electronic device may be a server. As an example, the steps included in the track thermodynamic diagram generating method of the embodiment of the present application may be executed at the cloud server, so that the cloud server generates the track thermodynamic diagram through the cloud computing function.
As shown in fig. 1, the track thermodynamic diagram generating method may include:
and step 101, converting the geographic coordinates of the target track point to be processed currently to generate the plane coordinates of the target track point.
It should be noted that, the target track point to be processed currently may be a track point reported by the terminal device. In some embodiments of the present application, geographic coordinates of a plurality of target track points reported by a terminal device are obtained, and conversion processing is performed on the geographic coordinates of the target track points to be processed currently according to a mercator coordinate transformation model, so as to generate plane coordinates of the target track points. As a possible implementation, the terminal device may be a vehicle terminal device in a vehicle network. The vehicle terminal equipment can report the track points recorded by the self navigation system to the cloud server, so that the cloud server processes all the track points reported by the vehicle terminal equipment by utilizing cloud computing and big data processing technology to generate a track thermodynamic diagram.
In this embodiment of the present application, after obtaining the geographic coordinates of multiple target track points reported by the terminal device, the geographic coordinates of the target track points to be processed currently may be obtained, where the geographic coordinates may be longitude and latitude coordinates. And then, the coordinate transformation can be carried out on the longitude and latitude coordinates of the target track point to be processed currently by using the ink card support coordinate transformation model so as to obtain the plane coordinates of the target track point. Wherein, in the embodiment of the application, the mercator coordinate transformation model can be expressed as follows:
Wherein x is the abscissa in the plane coordinates, y is the ordinate in the plane coordinates, longitude is the longitude coordinate of the target track point, and latitude is the latitude coordinate of the target track point.
That is, the latitude and longitude coordinates of the target track point to be currently processed can be transformed by using the above formula (1), so that the plane coordinates (x, y) of the target track point can be obtained.
Step 102, determining whether a coordinate difference value between a center point coordinate and a plane coordinate of each of the N currently established clusters is greater than a preset distance threshold, wherein N is greater than or equal to 1.
It should be noted that, in the present application, after obtaining the geographic coordinates of a plurality of target track points reported by the terminal device, when clustering the track points to be processed currently, the geographic coordinates of the track points to be processed currently are converted into plane coordinates, so that the coordinates of the central point of the cluster in the currently established cluster are plane coordinates, but not geographic coordinates. That is, the coordinates of the points in each of the N clusters currently established are plane coordinates, and the coordinates of the center point of each cluster are also plane coordinates, so that only one coordinate transformation is required for the geographic coordinates of the currently categorized target track points, the number of times of coordinate transformation of the track points can be greatly reduced, and only one transformation is required for the coordinates of each point, so that the time complexity of the coordinate transformation stage is controlled within O (N), where N is the total number of target track points. In the conventional track point distance clustering, the geographic coordinates of the target track points to be processed are generally converted into plane coordinates, the geographic coordinates of the center points of the current clusters are converted into plane coordinates, and then the distance between the target track points to be processed and the center points of the current clusters is calculated, so that the classification of the target track points to be processed is realized. Therefore, before all the track points are clustered, the geographical coordinates of the track points are uniformly converted into plane coordinates, and the coordinates of each track point are converted once, so that the time complexity is greatly reduced.
In step S102, a coordinate difference between the center point coordinate of each of the N clusters currently established and the plane coordinate of the target track point to be processed is calculated, and then the coordinate difference between the center point coordinate of each cluster and the plane coordinate of the target track point to be processed and a preset distance threshold may be compared. For example, assuming that there are L clusters currently established, at this time, a coordinate difference between the center point coordinate of each of the L clusters and the plane coordinate of the target track point to be processed currently may be calculated, and then, based on the coordinate difference and a preset distance threshold, it is determined whether the target track point to be processed currently is added to one of the L clusters or a new cluster with the target track point as the center point needs to be established.
It can be appreciated that the conventional clustering algorithm utilizes the euclidean DISTANCE between two points to implement clustering, for example, the euclidean DISTANCE between two points is calculated, the euclidean DISTANCE between the two points is compared with a preset DISTANCE threshold, if the euclidean DISTANCE is less than or equal to the DISTANCE threshold value DISTANCE, the two points are clustered into one class, and if the euclidean DISTANCE is greater than the DISTANCE threshold value, the two points are considered not to belong to the same class. However, compared with the traditional clustering algorithm, the DISTANCE judgment is performed by adopting the same DISTANCE threshold value DISTANCE, but the coordinate difference value between two points is calculated, the coordinate difference value is compared with the DISTANCE threshold value, and whether the two points are classified into the same cluster or not is judged according to the size comparison result. Therefore, compared with the traditional distance operation, the method optimizes the distance operation, can greatly reduce the calculation of a large number of floating points, reduces the use of calculation resources and improves the calculation performance. The specific implementation of the optimized distance operation can be seen from the description of the following embodiments.
And 103, if the coordinate difference value between the central point coordinate and the plane coordinate of the M-th cluster in the N clusters is smaller than or equal to a preset distance threshold value, adding the target track point into the M-th cluster.
And 104, if the coordinate difference value between the central point coordinate and the plane coordinate of each of the N clusters is larger than a preset distance threshold value, establishing a new cluster taking the plane coordinate of the target track point as the central point coordinate.
Step 105, traversing all target track points to be processed, and generating a corresponding track thermodynamic diagram according to the track points contained in each cluster in all the established clusters.
Optionally, after traversing all the target track points to be processed, all the target track points to be processed are put into clusters at this time, the number of track points contained in each cluster in all the current clusters can be counted at this time, and a track thermodynamic diagram is generated according to the number of track points contained in each cluster in all the current clusters. Therefore, the target track points reported by the vehicle terminals are processed, so that track points reported by all the vehicle terminals are formed into a thermodynamic diagram, and the thermodynamic diagram is provided for a user, so that the user can know the distribution condition of the track points of all the vehicle terminals, and the user can conveniently analyze the track of the vehicle terminals according to the thermodynamic diagram, and support data analysis is provided for intelligent traffic.
According to the track thermodynamic diagram generating method, before all track points are clustered, geographic coordinates of the track points are uniformly converted into plane coordinates, and for each track point, the coordinates are converted only once, so that time complexity is greatly reduced; in addition, the embodiment of the application firstly calculates the coordinate difference value between two points, and then compares the coordinate difference value with the distance threshold value, so as to judge whether the two points are classified into the same cluster or not according to the comparison result of the size. Therefore, compared with the traditional distance operation, the method optimizes the distance operation, can greatly reduce the calculation of a large number of floating points, reduces the use of calculation resources and improves the calculation performance.
It should be noted that, the optimization of the distance operation according to the embodiment of the present application may be as follows:
the conventional clustering algorithm utilizes euclidean DISTANCE between two points to realize clustering, for example, the euclidean DISTANCE between two points is calculated, the euclidean DISTANCE between the two points is compared with a preset DISTANCE threshold value, if the euclidean DISTANCE is smaller than or equal to the DISTANCE threshold value DISTANCE, the two points are clustered into one class, and if the euclidean DISTANCE is larger than the DISTANCE threshold value, the two points are considered not to belong to the same class. Wherein the Euclidean distance between two points is Wherein Δx is a horizontal coordinate difference value between two points, Δy is a vertical coordinate difference value between two points, and the DISTANCE threshold value of the clustering (i.e., the preset DISTANCE threshold value) is DISTANCE. According to the method, the distance calculation can be greatly reduced through algebraic operation optimization, and the complex operation of floating point numbers can be avoided under the following conditions:
case 1:due to presence->If Deltax>DISTANCE deduces->It can be seen that as long as there is Δx>DISTANCE is inevitably->The method is also applicable, so that the distance calculation can be optimized from Euclidean distance calculation to horizontal coordinate difference calculation, and the distance calculation can be reduced;
case 2: ,due to presence->If Deltay>DISTANCE deduces->It can be seen that as long as there is deltay>DISTANCE is inevitably->The method is also applicable, so that the distance calculation can be optimized from Euclidean distance calculation to longitudinal coordinate difference calculation, and the distance calculation can be reduced;
case 3:due to presence->If Deltax+Deltay<DISTANCE can deduce->It can be seen that as long as there is Δx+Δy<DISTANCE is inevitably->The method is also applicable, so that the distance calculation can be optimized from Euclidean distance calculation to difference sum calculation of a horizontal coordinate difference value and a vertical coordinate difference value, and the distance calculation can be reduced;
case 4:due to the existence of If it isIt can deduce->It can be seen that there is only +.>Then inevitably->The same holds true, so optimizing the distance calculation from the euclidean distance calculation to the difference sum calculation of the horizontal coordinate difference value and the vertical coordinate difference value can reduce the distance calculation.
Therefore, through the optimization, the complex floating point number operation is converted into simple operation, and the complex floating point number operation can be reduced by 99% by practice. Because the distance calculation is optimized from the traditional Euclidean distance calculation to the coordinate difference calculation, the adopted distance comparison mode is also optimized when judging whether the current target track point to be processed can be added into the current existing cluster. The following will describe cases 1, 2, 3 and 4 described above, respectively.
In some embodiments of the present application, as shown in fig. 2, the specific implementation process for determining whether the coordinate difference between the center point coordinate and the plane coordinate of each of the N currently established clusters is greater than the preset distance threshold may include:
step 201, obtaining a horizontal coordinate difference value between a center point coordinate and a plane coordinate of a current cluster to be processed;
for example, after the plane coordinates of the target track point to be processed currently are obtained, the distance between the target track point and the center point of the mth cluster in the current N clusters may be calculated, so as to calculate the horizontal coordinate difference Δx between the plane coordinates of the target track point and the center point coordinates of the mth cluster.
Step 202, comparing the horizontal coordinate difference value with a preset first distance threshold value;
optionally, a difference Δx between the plane coordinates of the target track point and the coordinates of the center point of the mth cluster is compared with a preset first DISTANCE threshold value DISTANCE.
In step 203, if the horizontal coordinate difference is greater than the first distance threshold, it is determined that the coordinate difference is greater than a preset distance threshold.
That is, when the horizontal coordinate difference Δx between the plane coordinate of the target track point and the center point coordinate of the mth cluster is greater than the first DISTANCE threshold value dis, it may be determined that the coordinate difference between the plane coordinate of the target track point and the center point coordinate of the mth cluster is greater than the preset DISTANCE threshold value dis, that is, the preset DISTANCE threshold value at this time and the first DISTANCE threshold value dis are the same numerical value, at this time, the target track point may not be considered to be added into the mth cluster, at this time, the center point coordinate of the (m+1) th cluster in the current N clusters may be obtained, and the horizontal coordinate difference Δx between the plane coordinate of the target track point and the center point coordinate of the (m+1) th cluster may be calculated, and the horizontal coordinate difference Δx may be compared with the preset first DISTANCE threshold value, and if the horizontal coordinate difference Δx is greater than the preset DISTANCE threshold value dis, it may be determined that the coordinate difference between the plane coordinate of the target track point and the center point coordinate of the mth+1 cluster is greater than the preset DISTANCE threshold value dis, and the horizontal coordinate difference between the plane coordinate of the target track point and the current n+1 cluster is still established from the current coordinate point of the current N and the current coordinate point of the current n+1 cluster until the horizontal coordinate of the target track point is equal to the horizontal coordinate between the current coordinate point and the current coordinate of the point of the m+1 cluster is greater than the current coordinate value.
It can be seen that, by optimizing the above case 1, the distance calculation is optimized from the euclidean distance calculation to the abscissa difference calculation, and by determining that the abscissa distance between the plane coordinates of the target track point and the coordinates of the center points of all the current clusters is greater than the first distance threshold, the target track point is considered to be an isolated point with respect to all the current clusters, and a new cluster can be established with the target track point as the center point, so that the distance calculation is optimized from the euclidean distance calculation to the abscissa difference calculation, and the calculation between most of the two points is filtered by determining the abscissa distance between the two points in advance, thereby greatly reducing the floating point number calculation.
In some embodiments of the present application, as shown in fig. 3, the specific implementation process for determining that the coordinate difference between the center point coordinate and the plane coordinate of each of the N currently established clusters is greater than the preset distance threshold may include:
step 301, obtaining a difference value of a vertical coordinate between a center point coordinate and a plane coordinate of a current cluster to be processed;
for example, after the plane coordinates of the target track point to be processed currently are obtained, the distance between the target track point and the center point of the mth cluster in the current N clusters may be calculated, so as to calculate the vertical coordinate difference Δy between the plane coordinates of the target track point and the center point coordinates of the mth cluster.
Step 302, comparing the difference value of the vertical coordinate with a preset first distance threshold value;
optionally, a difference Δy between the plane coordinates of the target track point and the coordinates of the center point of the mth cluster is compared with a preset first DISTANCE threshold value DISTANCE.
In step 303, if the difference value of the vertical coordinate is greater than the first distance threshold value, it is determined that the difference value of the vertical coordinate is greater than the preset distance threshold value.
That is, when the difference Δy between the plane coordinates of the target track point and the coordinates of the center point of the mth cluster is greater than the first DISTANCE threshold value, it may be determined that the difference Δy between the plane coordinates of the target track point and the coordinates of the center point of the mth cluster is greater than the preset DISTANCE threshold value, that is, the preset DISTANCE threshold value and the coordinates of the center point of the mth cluster at this time are the same value, at this time, the target track point may not be considered to be added into the mth cluster, at this time, the coordinates of the center point of the (m+1) th cluster in the current N clusters may be obtained, the difference Δy between the plane coordinates of the target track point and the coordinates of the center point of the (m+1) th cluster may be calculated, and the difference Δy between the vertical coordinate of the plane coordinates of the target track point and the coordinates of the center point of the (m+1) th cluster may be compared with the preset first DISTANCE threshold value, and if the difference Δy is greater than the preset DISTANCE threshold value, it may be determined that the difference Δy between the plane coordinates of the target track point and the coordinates of the center point of the mth+1 cluster is greater than the preset DISTANCE threshold value, and the difference Δy between the current coordinate point of the current n+2 between the target track point and the current coordinate point of the current N cluster and the center point of the current cluster may be calculated.
Therefore, the distance calculation can be optimized from the Euclidean distance calculation to the longitudinal coordinate difference calculation through the optimization of the condition 2, and the target track point can be considered to be an isolated point relative to all the current clusters through the fact that the longitudinal coordinate difference value between the plane coordinates of the target track point and the central point coordinates of all the current clusters is larger than the first distance threshold value, and a new cluster can be established by taking the target track point as the central point at the moment.
In some embodiments of the present application, as shown in fig. 4, the specific implementation process for determining that the coordinate difference between the center point coordinate and the plane coordinate of each of the N currently established clusters is less than or equal to the preset distance threshold may include:
step 401, acquiring a horizontal coordinate difference value and a vertical coordinate difference value between a center point coordinate and a plane coordinate of a current cluster to be processed;
for example, after the plane coordinates of the target track point to be processed currently are obtained, the distance between the target track point and the center point of the mth cluster in the current N clusters may be calculated, so that the horizontal coordinate difference Δx and the vertical coordinate difference Δy between the plane coordinates of the target track point and the center point coordinates of the mth cluster may be calculated.
Step 402, adding the horizontal coordinate difference value and the vertical coordinate difference value to obtain a difference sum, and comparing the difference sum with a preset first distance threshold;
optionally, a difference Δx between the plane coordinates of the target track point and the coordinates of the center point of the mth cluster and a difference Δy between the plane coordinates and the coordinates of the center point of the mth cluster are summed to obtain a sum Δx+Δy of differences, and the sum Δx+Δy of differences is compared with a first DISTANCE threshold value DISTANCE.
In step 403, if the sum of the differences is less than or equal to the first distance threshold, it is determined that the coordinate difference is less than or equal to the preset distance threshold.
That is, when the sum Δx+Δy of the differences between the plane coordinates of the target track point and the coordinates of the center point of the mth cluster is less than or equal to the first DISTANCE threshold value DISTANCE, it may be determined that the coordinate difference between the plane coordinates of the target track point and the coordinates of the center point of the mth cluster is less than or equal to the preset DISTANCE threshold value DISTANCE, where the target track point may be considered to satisfy the clustering condition, the target track point and the points in the mth cluster belong to the same class, and where the target track point may be added to the mth cluster.
It will be appreciated that if the sum Δx+Δy of the differences between the plane coordinates of the target track point and the center point coordinates of the mth cluster is greater than the first DISTANCE threshold value DISTANCE, the center point coordinates of the mth+1th cluster in the N clusters may be obtained, the sum of differences between the plane coordinates of the target track point and the center point coordinates of the mth+1th cluster may be calculated, the sum of differences may be compared with the first DISTANCE threshold value, if the sum of differences is less than or equal to the first DISTANCE threshold value DISTANCE, the target track point may be added to the mth+1th cluster, otherwise, the center point coordinates of the next cluster may be obtained from the N clusters, and the DISTANCE between the target track point and the center point of the next cluster may be calculated.
From this, it can be seen that, by optimizing the above case 3, the distance calculation is optimized from the euclidean distance calculation to the sum of differences calculation, and by the sum of differences between the plane coordinates of the target track point and the coordinates of the center point of the current cluster being smaller than the first distance threshold, the target track point and the points in the current cluster can be considered to belong to the same class, and at this time, the target track point is added to the current cluster to complete the classification of the target track point. Therefore, the distance calculation is optimized from Euclidean distance calculation to difference sum calculation, and most of the two-point distance calculation is filtered by judging the difference sum between the two points in advance, so that floating point number calculation is greatly reduced.
In some embodiments of the present application, as shown in fig. 5, the specific implementation process for determining whether the coordinate difference between the center point coordinate and the plane coordinate of each of the N currently established clusters is greater than the preset distance threshold may include:
step 501, obtaining a horizontal coordinate difference value and a vertical coordinate difference value between a center point coordinate and a plane coordinate of a current cluster to be processed;
for example, after the plane coordinates of the target track point to be processed currently are obtained, the distance between the target track point and the center point of the mth cluster in the current N clusters may be calculated, so that the horizontal coordinate difference Δx and the vertical coordinate difference Δy between the plane coordinates of the target track point and the center point coordinates of the mth cluster may be calculated.
Step 502, adding the horizontal coordinate difference value and the vertical coordinate difference value to obtain a difference sum, and comparing the difference sum with a preset second distance threshold; wherein the second distance threshold is less than the first distance threshold;
optionally, summing a horizontal coordinate difference Δx and a vertical coordinate difference Δy between the plane coordinate of the target track point and the center point coordinate of the mth cluster to obtain a difference sum Δx+Δy, and comparing the difference sum Δx+Δy with a second distance threshold. Wherein the second distance threshold may be
In step 503, if the sum of the differences is greater than the second distance threshold, it is determined that the coordinate difference is greater than the preset distance threshold.
That is, when the sum Δx+Δy of the differences between the plane coordinates of the target track point and the center point coordinates of the M-th cluster is greater than the second distance thresholdThen it can be determined between the plane coordinates of the target track point and the center point coordinates of the mth clusterThe coordinate difference is greater than a preset DISTANCE threshold value DISTANCE, at this time, the target track point can not be considered to be added into the mth cluster, at this time, the center point coordinate of the mth+1th cluster in the current N clusters can be obtained, the sum of differences Δx+Δy between the plane coordinate of the target track point and the center point coordinate of the mth+1th cluster is calculated, the sum of differences Δx+Δy is compared with a preset second DISTANCE threshold value, if the sum of differences Δx+Δy is greater than the second DISTANCE threshold value, it can be determined that the coordinate difference between the plane coordinate of the target track point and the center point coordinate of the mth+1th cluster is greater than the preset DISTANCE threshold value, at this time, the center point coordinate of the mth+2th cluster still continues to be obtained from the current N clusters until the DISTANCE calculation is performed between the target track point and the center point of the current all clusters, and the sum of differences Δx+Δy between the plane coordinate of the target track point and the center point of the current all clusters is greater than the second DISTANCE threshold value, and a new cluster taking the plane coordinate of the target track point as the center point is established.
It can be seen that, by optimizing the above case 4, the distance calculation is optimized from the euclidean distance calculation to the difference sum calculation, and by determining that the difference sum between the plane coordinates of the target track point and the coordinates of the center points of all the current clusters is greater than the second distance threshold, the target track point is considered to be an isolated point with respect to all the current clusters, and a new cluster can be established with the target track point as the center point, thereby, by optimizing the distance calculation from the euclidean distance calculation to the difference sum calculation, and by determining the difference sum between the two points in advance, the floating point number calculation is filtered, and the floating point number calculation is greatly reduced.
In some embodiments of the present application, if the abscissa difference value is less than or equal to the first distance threshold, the ordinate difference value is less than or equal to the first distance threshold, the sum of differences is greater than the first distance threshold, and the sum of differences is less than or equal to the second distance threshold, then calculating an euclidean distance value between a center point coordinate and the plane coordinate of the cluster to be currently processed according to the abscissa difference value and the ordinate difference value; and determining the Euclidean distance value as a coordinate difference value between the center point coordinate of the cluster to be processed currently and the plane coordinate.
For example, if the difference between the plane coordinate of the target track point and the center point coordinate of a certain cluster in the current N clusters is smaller than or equal to the first distance threshold, the distance determination screening may be performed by using the difference, for example, if the difference between the plane coordinate of the target track point and the center point coordinate of a certain cluster in the current N clusters is smaller than or equal to the first distance threshold, the distance determination screening may be performed by using the difference sum, for example, if the difference between the plane coordinate of the target track point and the center point coordinate of all clusters in the current N clusters is larger than the first distance threshold, the distance determination screening may be performed by using the difference sum and the second distance threshold, for example, if the difference between the plane coordinate of the target track point and the center point coordinate of a certain cluster in the current N clusters is smaller than or equal to the second distance threshold, the target track point may not be classified by the optimization of the distance calculation, and the target track point may be classified by using the euclidean distance determination condition, for calculating the euclidean distance between the target track point and the center point to be processed If the Euclidean distance value is +.>Determining the coordinate difference value between the coordinates of the central point of the current cluster to be processed and the plane coordinates of the target track point, if the Euclidean distance value +.>If the DISTANCE value is smaller than or equal to the DISTANCE threshold value, adding the target track point into the current cluster to be processed, and if the Euclidean DISTANCE value is +.>And if the DISTANCE is greater than the DISTANCE threshold value DISTANCE, a new cluster taking the plane coordinate of the target track point as the center point coordinate is established. Therefore, the application filters most of the calculation between two points by judging the abscissa distance, the ordinate distance and the like between the two points in advance, and if the filtering condition is not met, the calculation of the Euclidean distance value between the two points is still carried out. Therefore, the distance operation is optimized by adding the filtering and screening conditions, the complex floating point number operation is converted into simple operation, a large number of floating point number calculations are greatly reduced, and the use of calculation resources is reduced, so that the calculation performance is improved.
In order to implement the above embodiment, the present application further provides a track thermodynamic diagram generating device.
Fig. 6 is a block diagram of a track thermodynamic diagram generating device according to an embodiment of the present application. As shown in fig. 6, the trajectory thermodynamic diagram generating device 600 may include: a planar coordinate generation module 601, a first determination module 602, an addition module 603, an establishment module 604, and a trajectory thermodynamic diagram generation module 605.
Specifically, the plane coordinate generating module 601 is configured to perform conversion processing on the geographic coordinates of the target track point to be processed currently, and generate the plane coordinates of the target track point. In some embodiments of the present application, the plane coordinate generating module 601 obtains geographic coordinates of a plurality of target track points reported by a terminal device, and performs conversion processing on the geographic coordinates of the target track points to be processed currently according to a mercator coordinate conversion model, so as to generate plane coordinates of the target track points.
The first determining module 602 is configured to determine whether a coordinate difference between a center point coordinate and a plane coordinate of each of N currently established clusters is greater than a preset distance threshold, where N is greater than or equal to 1.
The adding module 603 is configured to add the target track point to the mth cluster when a coordinate difference between the center point coordinate and the plane coordinate of the mth cluster in the N clusters is less than or equal to a preset distance threshold.
The establishing module 604 is configured to establish a new cluster with the plane coordinate as the center point coordinate when the coordinate difference between the center point coordinate and the plane coordinate of each of the N clusters is greater than a preset distance threshold.
The track thermodynamic diagram generating module 605 is configured to traverse all target track points to be processed, and generate a corresponding track thermodynamic diagram according to the track points included in each cluster in all the established clusters.
In some embodiments of the present application, the first determining module 602 is specifically configured to: acquiring a horizontal coordinate difference value between a center point coordinate and a plane coordinate of a current cluster to be processed; comparing the horizontal coordinate difference value with a preset first distance threshold value; and if the horizontal coordinate difference value is larger than the first distance threshold value, determining that the coordinate difference value is larger than a preset distance threshold value.
In some embodiments of the present application, the first determining module 602 is specifically configured to: acquiring a longitudinal coordinate difference value between a center point coordinate and a plane coordinate of a current cluster to be processed; comparing the difference value of the vertical coordinates with a preset first distance threshold value; and if the difference value of the vertical coordinates is larger than the first distance threshold value, determining that the difference value of the coordinates is larger than a preset distance threshold value.
In some embodiments of the present application, the first determining module 602 is specifically configured to: acquiring a horizontal coordinate difference value and a vertical coordinate difference value between a center point coordinate and a plane coordinate of a current cluster to be processed; adding the horizontal coordinate difference value and the vertical coordinate difference value to obtain a difference sum, and comparing the difference sum with a preset first distance threshold; and if the sum of the differences is smaller than or equal to the first distance threshold value, determining that the coordinate difference is smaller than or equal to a preset distance threshold value.
In some embodiments of the present application, the first determining module 602 is specifically configured to: acquiring a horizontal coordinate difference value and a vertical coordinate difference value between a center point coordinate and a plane coordinate of a current cluster to be processed; adding the horizontal coordinate difference value and the vertical coordinate difference value to obtain a difference sum, and comparing the difference sum with a preset second distance threshold; wherein the second distance threshold is less than the first distance threshold; if the sum of the differences is greater than the second distance threshold, it is determined that the coordinate difference is greater than a preset distance threshold.
In some embodiments of the present application, as shown in fig. 7, the track thermodynamic diagram generating device 600 may further include: a calculation module 606 and a second determination module 607. The calculating module 606 is configured to calculate, when the horizontal coordinate difference value is less than or equal to a first distance threshold, the vertical coordinate difference value is less than or equal to the first distance threshold, the sum of differences is greater than the first distance threshold, and the sum of differences is less than or equal to a second distance threshold, an euclidean distance value between a center point coordinate and a plane coordinate of a current cluster to be processed according to the horizontal coordinate difference value and the vertical coordinate difference value; the second determining module 607 is configured to determine the euclidean distance value as a coordinate difference between the center point coordinate and the plane coordinate of the cluster to be currently processed.
According to the track thermodynamic diagram generating device, before all track points are clustered, geographic coordinates of the track points are uniformly converted into plane coordinates, and for each track point, the coordinates are converted only once, so that time complexity is greatly reduced; in addition, the embodiment of the application firstly calculates the coordinate difference value between two points, and then compares the coordinate difference value with the distance threshold value, so as to judge whether the two points are classified into the same cluster or not according to the comparison result of the size. Therefore, compared with the traditional distance operation, the method optimizes the distance operation, can greatly reduce the calculation of a large number of floating points, reduces the use of calculation resources and improves the calculation performance.
According to embodiments of the present application, an electronic device and a readable storage medium are also provided.
Fig. 8 is a block diagram of an electronic device for implementing a track thermodynamic diagram generating method according to an embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the application described and/or claimed herein.
As shown in fig. 8, the electronic device includes: one or more processors 801, memory 802, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the electronic device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In other embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple electronic devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 801 is illustrated in fig. 8.
Memory 802 is a non-transitory computer-readable storage medium provided herein. Wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the trace thermodynamic diagram generation method provided herein. The non-transitory computer readable storage medium of the present application stores computer instructions for causing a computer to perform the trajectory thermodynamic diagram generation method provided by the present application.
The memory 802 is used as a non-transitory computer readable storage medium, and may be used to store a non-transitory software program, a non-transitory computer executable program, and modules, such as program instructions/modules corresponding to the track thermodynamic diagram generating method in the embodiments of the present application (e.g., the plane coordinate generating module 601, the first determining module 602, the adding module 603, the establishing module 604, and the track thermodynamic diagram generating module 605 shown in fig. 6). The processor 801 executes various functional applications of the server and data processing, i.e., implements the track thermodynamic diagram generation method in the above-described method embodiments by running non-transitory software programs, instructions, and modules stored in the memory 802.
Memory 802 may include a storage program area that may store an operating system, at least one application program required for functionality, and a storage data area; the storage data area may store data created according to the use of the electronic device to implement the track thermodynamic diagram generation method, or the like. In addition, memory 802 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory 802 may optionally include memory remotely located with respect to processor 801, which may be connected via a network to an electronic device for implementing the track thermodynamic diagram generation method. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device for implementing the track thermodynamic diagram generating method may further include: an input device 803 and an output device 804. The processor 801, memory 802, input devices 803, and output devices 804 may be connected by a bus or other means, for example in fig. 8.
The input device 803 may receive input numeric or character information and generate key signal inputs related to user settings and function controls of the electronic device used to implement the track thermodynamic diagram generation method, such as input devices for a touch screen, a keypad, a mouse, a trackpad, a touch pad, a pointer stick, one or more mouse buttons, a trackball, a joystick, and the like. The output device 804 may include a display apparatus, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibration motors), among others. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device may be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASIC (application specific integrated circuit), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
These computing programs (also referred to as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present application may be performed in parallel, sequentially, or in a different order, provided that the desired results of the technical solutions disclosed in the present application can be achieved, and are not limited herein.
The above embodiments do not limit the scope of the application. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application are intended to be included within the scope of the present application.

Claims (13)

1. A method of generating a trace thermodynamic diagram, comprising:
converting the geographic coordinates of the target track points to be processed currently to generate plane coordinates of the target track points;
determining whether a coordinate difference value between a center point coordinate and the plane coordinate of each of N currently established clusters is larger than a preset distance threshold value, wherein N is larger than or equal to 1;
if the coordinate difference value between the central point coordinate of the M th cluster in the N clusters and the plane coordinate is smaller than or equal to a preset distance threshold value, adding the target track point into the M th cluster;
if the coordinate difference value between the central point coordinate of each cluster in the N clusters and the plane coordinate is larger than a preset distance threshold value, a new cluster taking the plane coordinate as the central point coordinate is established;
Traversing all target track points to be processed, and generating a corresponding track thermodynamic diagram according to track points contained in each cluster in all the established clusters;
the determining that the coordinate difference between the center point coordinate and the plane coordinate of each of the N currently established clusters is greater than a preset distance threshold comprises:
acquiring a horizontal coordinate difference value between the center point coordinate of the cluster to be processed currently and the plane coordinate;
comparing the horizontal coordinate difference value with a preset first distance threshold value;
if the horizontal coordinate difference value is larger than the first distance threshold value, determining that the coordinate difference value is larger than a preset distance threshold value;
the determining that the coordinate difference value between the center point coordinate and the plane coordinate of each of the N currently established clusters is smaller than or equal to a preset distance threshold value comprises the following steps:
acquiring a horizontal coordinate difference value and a vertical coordinate difference value between the center point coordinates of the current cluster to be processed and the plane coordinates;
adding the horizontal coordinate difference value and the vertical coordinate difference value to obtain a difference sum, and comparing the difference sum with a preset first distance threshold;
and if the sum of the differences is smaller than or equal to the first distance threshold, determining that the coordinate difference is smaller than or equal to a preset distance threshold.
2. The track thermodynamic diagram generating method according to claim 1, wherein the converting the geographic coordinates of the target track point to be processed currently to generate the plane coordinates of the target track point includes:
obtaining geographic coordinates of a plurality of target track points reported by terminal equipment;
and converting the geographic coordinates of the target track point to be processed currently according to the mercator coordinate conversion model, and generating the plane coordinates of the target track point.
3. The trajectory thermodynamic diagram generation method of claim 1, wherein determining that a coordinate difference between a center point coordinate of each of the N currently established clusters and the plane coordinate is greater than a preset distance threshold comprises:
acquiring a longitudinal coordinate difference value between the center point coordinate of the cluster to be processed currently and the plane coordinate;
comparing the longitudinal coordinate difference value with a preset first distance threshold value;
and if the vertical coordinate difference value is larger than the first distance threshold value, determining that the coordinate difference value is larger than a preset distance threshold value.
4. The trajectory thermodynamic diagram generation method of claim 1, wherein determining that a coordinate difference between a center point coordinate of each of the N currently established clusters and the plane coordinate is greater than a preset distance threshold comprises:
Acquiring a horizontal coordinate difference value and a vertical coordinate difference value between the center point coordinates of the current cluster to be processed and the plane coordinates;
adding the horizontal coordinate difference value and the vertical coordinate difference value to obtain a difference sum, and comparing the difference sum with a preset second distance threshold; wherein the second distance threshold is less than the first distance threshold;
and if the difference sum is larger than the second distance threshold, determining that the coordinate difference is larger than a preset distance threshold.
5. The trajectory thermodynamic diagram generation method of any one of claims 1 to 4, further comprising:
if the difference value of the horizontal coordinates is smaller than or equal to the first distance threshold, the difference value of the vertical coordinates is smaller than or equal to the first distance threshold, the sum of the differences is larger than the first distance threshold, and the sum of the differences is smaller than or equal to the second distance threshold, calculating Euclidean distance values between the coordinates of the central points of the current to-be-processed clusters and the plane coordinates according to the difference value of the horizontal coordinates and the difference value of the vertical coordinates;
and determining the Euclidean distance value as a coordinate difference value between the center point coordinate of the cluster to be processed currently and the plane coordinate.
6. A trajectory thermodynamic diagram generation device, comprising:
the plane coordinate generation module is used for converting the geographic coordinates of the target track point to be processed currently to generate the plane coordinates of the target track point;
the first determining module is used for determining whether a coordinate difference value between a central point coordinate and the plane coordinate of each of N currently established clusters is larger than a preset distance threshold value, wherein N is larger than or equal to 1;
the adding module is used for adding the target track point to the M th cluster when the coordinate difference value between the central point coordinate of the M th cluster and the plane coordinate in the N clusters is smaller than or equal to a preset distance threshold value;
the establishing module is used for establishing a new cluster taking the plane coordinate as the center point coordinate when the coordinate difference value between the center point coordinate of each cluster in the N clusters and the plane coordinate is larger than a preset distance threshold value;
the track thermodynamic diagram generation module is used for traversing all target track points to be processed and generating a corresponding track thermodynamic diagram according to the track points contained in each cluster in all the established clusters;
the first determining module is specifically configured to:
Acquiring a horizontal coordinate difference value between the center point coordinate of the cluster to be processed currently and the plane coordinate;
comparing the horizontal coordinate difference value with a preset first distance threshold value;
if the horizontal coordinate difference value is larger than the first distance threshold value, determining that the coordinate difference value is larger than a preset distance threshold value;
the first determining module is specifically configured to:
acquiring a horizontal coordinate difference value and a vertical coordinate difference value between the center point coordinates of the current cluster to be processed and the plane coordinates;
adding the horizontal coordinate difference value and the vertical coordinate difference value to obtain a difference sum, and comparing the difference sum with a preset first distance threshold;
and if the sum of the differences is smaller than or equal to the first distance threshold, determining that the coordinate difference is smaller than or equal to a preset distance threshold.
7. The apparatus for generating a thermodynamic diagram of a trajectory as claimed in claim 6, wherein said planar coordinate generating module is specifically configured to:
obtaining geographic coordinates of a plurality of target track points reported by terminal equipment;
and converting the geographic coordinates of the target track point to be processed currently according to the mercator coordinate conversion model, and generating the plane coordinates of the target track point.
8. The apparatus for generating a thermodynamic diagram of a trajectory as claimed in claim 6, wherein said first determining module is specifically configured to:
acquiring a longitudinal coordinate difference value between the center point coordinate of the cluster to be processed currently and the plane coordinate;
comparing the longitudinal coordinate difference value with a preset first distance threshold value;
and if the vertical coordinate difference value is larger than the first distance threshold value, determining that the coordinate difference value is larger than a preset distance threshold value.
9. The apparatus for generating a thermodynamic diagram of a trajectory as claimed in claim 6, wherein said first determining module is specifically configured to:
acquiring a horizontal coordinate difference value and a vertical coordinate difference value between the center point coordinates of the current cluster to be processed and the plane coordinates;
adding the horizontal coordinate difference value and the vertical coordinate difference value to obtain a difference sum, and comparing the difference sum with a preset second distance threshold; wherein the second distance threshold is less than the first distance threshold;
and if the difference sum is larger than the second distance threshold, determining that the coordinate difference is larger than a preset distance threshold.
10. The trajectory thermodynamic diagram generation device of any one of claims 6 to 9, further comprising:
the calculation module is used for calculating Euclidean distance values between the center point coordinates and the plane coordinates of the current to-be-processed cluster according to the horizontal coordinate difference value and the vertical coordinate difference value when the horizontal coordinate difference value is smaller than or equal to the first distance threshold value, the vertical coordinate difference value is smaller than or equal to the first distance threshold value, the difference sum is larger than the first distance threshold value, and the difference sum is smaller than or equal to the second distance threshold value;
And the second determining module is used for determining the Euclidean distance value as a coordinate difference value between the center point coordinate and the plane coordinate of the cluster to be processed currently.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of generating a trace thermodynamic diagram of any one of claims 1 to 5.
12. A non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the trajectory thermodynamic diagram generation method of any one of claims 1 to 5.
13. A computer program product comprising a computer program which, when executed by a processor, implements a method of generating a thermodynamic diagram of a trajectory according to any one of claims 1 to 5.
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