CN118227966A

CN118227966A - Vehicle line extraction method and device, electronic equipment and storage medium

Info

Publication number: CN118227966A
Application number: CN202410335156.9A
Authority: CN
Inventors: 王佳; 刘喜; 胡浩文; 任彼德
Original assignee: Changsha Qianmo Transportation Planning And Design Co ltd; Changsha University of Science and Technology
Current assignee: Changsha Qianmo Transportation Planning And Design Co ltd; Changsha University of Science and Technology
Priority date: 2024-03-22
Filing date: 2024-03-22
Publication date: 2024-06-21

Abstract

The application relates to a vehicle line extraction method, a device, electronic equipment and a storage medium, wherein the vehicle line extraction method comprises the following steps: acquiring a vehicle track point set according to vehicle positioning data; preprocessing a vehicle track point set through thinning and duplication removing operation to obtain an initial representative point set; obtaining a result representative point set according to the initial representative point set and the vehicle track points within the preset radius range of each initial representative point; and connecting each result representative point according to the result representative point set and a preset rule, and extracting to obtain a vehicle line. The application can effectively avoid the interference of abnormal values, thereby rapidly extracting the circuit with more reliability and accuracy under the connection rule.

Description

Vehicle line extraction method and device, electronic equipment and storage medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a vehicle line extraction method, a device, an electronic device, and a storage medium.

Background

With the development of urban traffic informatization, GPS positioning data is favored and used in more and more fields and application programs due to the advantages of low cost, real data, wide coverage range, strong temporal characteristics and the like, so that convenience and service quality of private travel are improved. The GPS data of the vehicle is processed and analyzed, and the specific track of the vehicle line is accurately extracted from the GPS data, so that the GPS data has important theoretical significance and application value for urban traffic planning and management, traffic flow state prediction, intelligent traffic control facility construction and the like. The traditional vehicle route extraction method mainly directly obtains the route track of the vehicle according to a certain running track or a plurality of running tracks of the vehicle, the method is simple and easy to implement, and the route track of the vehicle can be basically fitted in most cases, but because GPS data has more abnormal values in many cases, position information deviating from the route is easy to generate, so that the accuracy of extracting the route is affected.

Accordingly, the inventor provides a vehicle route extraction method, a device, an electronic apparatus, and a storage medium.

Disclosure of Invention

(1) Technical problem to be solved

The application provides a vehicle line extraction method, a device, electronic equipment and a storage medium, which aims to solve the technical problems that: since the GPS data has many abnormal values in many cases, positional information of the deviated line is easily generated, and thus accuracy of extracting the line is affected.

(2) Technical proposal

In a first aspect, the present application provides a vehicle route extraction method, including:

acquiring a vehicle track point set according to vehicle positioning data;

Preprocessing a vehicle track point set through thinning and duplication removing operation to obtain an initial representative point set;

Obtaining a result representative point set according to the initial representative point set and the vehicle track points within the preset radius range of each initial representative point;

and connecting each result representative point according to the result representative point set and a preset rule, and extracting to obtain a vehicle line.

Further, the preprocessing of the vehicle track point set through the thinning and weight removing operation to obtain an initial representative point set includes:

Dividing coordinate values of all vehicle track points by a preset bandwidth value, and rounding and removing weights to obtain a thinning point;

Multiplying each sparse point by the preset bandwidth value to obtain the coordinate value of each initial representative point, thereby obtaining an initial representative point set.

Further, the obtaining a result representative point set according to the initial representative point set and the vehicle track points within the preset radius range of each initial representative point includes:

respectively moving each initial representative point to the average value of coordinate values of the vehicle track points in the respective preset radius range;

Removing the weight of the initial representative points after the movement, and removing the initial representative points of which the number of the vehicle track points in the preset radius range is smaller than or equal to a preset number threshold value;

repeatedly moving each initial representative point to the preset times at the average value of the coordinate values of the vehicle track points in the respective preset radius range to obtain a result representative point set.

Further, the connecting each result representative point according to the result representative point set and a preset rule, extracting to obtain a vehicle line, including:

determining a starting point according to the result representative point set;

Determining a second point nearest to the starting point and a third point nearest to the second point according to the first preset distance threshold and the second preset distance threshold;

if the included angle between the first vector formed by the starting point and the second point and the included angle between the second vector formed by the second point and the third point are smaller than a preset included angle threshold value, connecting the starting point, the second point and the third point;

and repeatedly determining and connecting the starting point, the second point and the third point until all the result representative points are connected, and extracting to obtain the vehicle line.

Further, the determining, according to the first preset distance threshold and the second preset distance threshold, the second point nearest to the starting point and the third point nearest to the second point includes:

If the distance between the result representative point closest to the starting point and the starting point is larger than or equal to a first preset distance threshold value and smaller than or equal to a second preset distance threshold value, determining the result representative point closest to the starting point as a second point;

And if the distance between the result representative point closest to the second point and the second point is larger than or equal to the first preset distance threshold value and smaller than or equal to the second preset distance threshold value, determining the result representative point closest to the second point as a third point.

Further, the determining, according to the first preset distance threshold and the second preset distance threshold, the second point nearest to the starting point, and the third point nearest to the second point further includes:

If the distance between the result representative point closest to the starting point and the starting point is smaller than a first preset distance threshold, merging the result representative point closest to the starting point with the starting point;

If the distance between the result representative point closest to the starting point and the starting point is larger than a second preset distance threshold value, determining the starting point again according to the result representative point set.

Further, if the included angle between the first vector formed by the start point and the second vector formed by the second point and the third point is smaller than the preset included angle threshold, after connecting the start point, the second point and the third point, the method further includes:

If the included angle between the first vector formed by the starting point and the second point and the included angle between the second vector formed by the second point and the third point are larger than or equal to a preset included angle threshold value, the second point is redetermined.

In a second aspect, the present application provides a vehicle course extraction device, comprising:

the data acquisition module is used for acquiring a vehicle track point set according to the vehicle positioning data;

the initial representing module is used for preprocessing the vehicle track point set through thinning and de-duplication operation to obtain an initial representing point set;

The result representing module is used for obtaining a result representing point set according to the initial representing point set and the vehicle track points within the preset radius range of each initial representing point;

and the line extraction module is used for connecting each result representative point according to the result representative point set and a preset rule, and extracting and obtaining a vehicle line.

In a third aspect, the present application provides an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the vehicle course extraction method as described above when executing the computer program.

In a fourth aspect, the present application provides a computer readable storage medium storing a computer program which when executed by a processor implements a vehicle route extraction method as described above.

(3) Advantageous effects

The technical scheme of the application has the following advantages:

According to the vehicle line extraction method provided by the first aspect of the application, the vehicle track point set is preprocessed through the thinning and deduplication operation to obtain the initial representative point set, the result representative point set is obtained according to the initial representative point set and the vehicle track points in the preset radius range of each initial representative point, each result representative point is connected according to the result representative point set and the preset rule, the vehicle line is extracted, the interference of abnormal values can be effectively avoided, and therefore the line with higher reliability and accuracy can be rapidly extracted under the connection rule.

It will be appreciated that the advantages of the second, third and fourth aspects may be found in the relevant description of the first aspect and are not repeated here.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic flow chart of a vehicle route extraction method provided by the application;

FIG. 2 is a graph of extracted line results provided by the present application;

FIG. 3 is a partial view of an extracted curve of the line provided by the present application;

FIG. 4 is a graph of robustness effects of the vehicle route extraction method provided by the application;

Fig. 5 is a schematic structural diagram of a vehicle route extraction device provided by the application;

Fig. 6 is a schematic structural diagram of an electronic device provided by the present application.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

Furthermore, the terms "first," "second," "third," and the like in the description of the present specification and in the appended claims, are used for distinguishing between descriptions and not necessarily for indicating or implying a relative importance.

Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise. "plurality" means "two or more".

With the steady development of social economy, by the end of 9 months in 2023, the national automobiles keep 3.3 hundred million, and new energy automobiles reach 1821 ten thousand, so that the situation of high-speed growth is presented; the automobile is a transportation tool which can fully adapt to personal personalized travel will, and information of different dimensions is hidden in daily travel journey, such as path selection habit of a user when the user travels is depicted, and in addition, the characteristics of urban road structure, road network layout and the like can be displayed. The GPS data of the vehicle is processed and analyzed, and the specific track of the vehicle line is accurately extracted from the GPS data, so that the GPS data has important theoretical significance and application value for urban traffic planning and management, traffic flow state prediction, intelligent traffic control facility construction and the like.

With the development of urban traffic informatization, GPS positioning data is favored and used in more and more fields and application programs due to the advantages of low cost, real data, wide coverage range, strong temporal characteristics and the like, so that convenience and service quality of private travel are improved. However, the current GPS sensor is affected by external objective environmental conditions, and the phenomenon of offset between GPS positioning data and actual trajectory is still present. Therefore, when the GPS data is preprocessed, a proper screening method is adopted to filter discrete and offset abnormal GPS data values, and then a reliable and accurate vehicle line track is restored.

The traditional vehicle route extraction method mainly directly obtains the route track of the vehicle according to a certain running track or a plurality of running tracks of the vehicle, the method is simple and easy to implement, and the route track of the vehicle can be basically fitted in most cases, but because GPS data has more abnormal values in many cases, position information deviating from the route is easy to generate, so that the accuracy of extracting the route is affected.

In view of the above, the present application provides a vehicle route extraction method, apparatus, electronic device, and storage medium, which can solve the above problems.

The following describes in further detail the embodiments of the present application with reference to the drawings and examples. The following examples are illustrative of the application and are not intended to limit the scope of the application.

As shown in fig. 1, the vehicle route extraction method provided in this embodiment includes:

s100, acquiring a vehicle track point set according to vehicle positioning data.

S200, preprocessing the vehicle track point set through thinning and de-duplication operation to obtain an initial representative point set.

In some embodiments, the preprocessing the vehicle track point set through the thinning and deduplication operation to obtain an initial representative point set includes: dividing coordinate values of all vehicle track points by a preset bandwidth value, and rounding and removing weights to obtain a thinning point; multiplying each sparse point by the preset bandwidth value to obtain the coordinate value of each initial representative point, thereby obtaining an initial representative point set.

In an application, the vehicle positioning data may be vehicle GPS data, and the vehicle GPS data may be preprocessed by a thinning and deduplication operation to obtain the initial representative point. In processing vehicle GPS data, further data processing is inconvenient due to repeated data. If more storage space is wasted, the displayed graph is not smooth or has larger error. Therefore, the number of data points is reduced to the maximum extent under the condition of ensuring the basic shape characteristic reflecting the original graph or curve through a certain rule, and the process is called thinning.

The coordinate value of the vehicle track point can be longitude and latitude, the application divides the longitude and latitude of all original track points by a set bandwidth value BW (thinning factor) and obtains the thinning point (similar to grid division) after rounding and de-duplication, and then the thinning point is multiplied by the bandwidth value BW to obtain the longitude and latitude of the initial representative point. Position information of initial representative point: x=int [ O/BW ] ×bw, where O represents the original GPS trajectory point coordinates and X represents the initial representative point coordinates. The bandwidth value influences the distance between the acquired initial representative points, the larger the bandwidth value is, the farther the distance is, the smaller the number of the initial representative points is, the smaller the bandwidth value is, the closer the distance is, and the number of the initial representative points is larger.

And adopting the bandwidth BW as a thinning factor to carry out thinning and weight removing preprocessing on the GPS data of the vehicle, and then multiplying the data by the bandwidth to restore the data to an initial representative point. Therefore, the number of GPS coordinates is effectively reduced, the workload of subsequent data processing is greatly reduced, and the reliability of the track after thinning is further improved.

S300, obtaining a result representative point set according to the initial representative point set and the vehicle track points in the preset radius range of each initial representative point.

In some embodiments, the obtaining a result representative point set according to the initial representative point set and the vehicle track points within the preset radius range of each initial representative point includes: respectively moving each initial representative point to the average value of coordinate values of the vehicle track points in the respective preset radius range; removing the weight of the initial representative points after the movement, and removing the initial representative points of which the number of the vehicle track points in the preset radius range is smaller than or equal to a preset number threshold value; repeatedly moving each initial representative point to the preset times at the average value of the coordinate values of the vehicle track points in the respective preset radius range to obtain a result representative point set.

In application, a result representative point set can be obtained from the initial representative points through N times of mean shift (enabling sample points to be gathered to the area with the greatest density) within a proper radius, and the result representative points with less number of covered original track points are eliminated.

Specifically, a number of movements N, a suitable radius of coverage R, and a threshold V of the number of original track points within the radius of coverage R may be set. The primary moving step comprises the following steps: firstly, acquiring longitude and latitude coordinates of all track points in an initial representative point coverage radius R range, moving all initial representative points to a coordinate mean value of all track points in the coverage radius range, simultaneously recording the number of the track points in the initial representative point coverage radius range, performing de-duplication operation on the moved representative points, and finally removing the result representative points with the GPS point number less than or equal to V in the coverage radius R according to a threshold V. The above is considered as one movement. And repeating the steps for N times to obtain a result representative point set. The result represents the position information of the point:

wherein Y represents the resulting representative point coordinates, O represents the original trajectory point coordinates, and v represents the number of original trajectory points within the original representative point coverage radius R.

The N-time mean shift method ensures that the sample points are gathered towards the area with the maximum density, and can reduce the influence of abnormal data points, so that the engineering practicability is high and the application value is high.

And S400, connecting the result representative points according to the result representative point set and a preset rule, and extracting to obtain a vehicle line.

In some embodiments, the connecting each result representative point according to the result representative point set and a preset rule, and extracting a vehicle line, includes: determining a starting point according to the result representative point set; determining a second point nearest to the starting point and a third point nearest to the second point according to the first preset distance threshold and the second preset distance threshold; if the included angle between the first vector formed by the starting point and the second point and the included angle between the second vector formed by the second point and the third point are smaller than a preset included angle threshold value, connecting the starting point, the second point and the third point; and repeatedly determining and connecting the starting point, the second point and the third point until all the result representative points are connected, and extracting to obtain the vehicle line.

In some embodiments, the determining the second point nearest to the starting point and the third point nearest to the second point according to the first preset distance threshold and the second preset distance threshold includes: if the distance between the result representative point closest to the starting point and the starting point is larger than or equal to a first preset distance threshold value and smaller than or equal to a second preset distance threshold value, determining the result representative point closest to the starting point as a second point; and if the distance between the result representative point closest to the second point and the second point is larger than or equal to the first preset distance threshold value and smaller than or equal to the second preset distance threshold value, determining the result representative point closest to the second point as a third point.

In some embodiments, the determining the second point nearest to the starting point and the third point nearest to the second point according to the first preset distance threshold and the second preset distance threshold further includes: if the distance between the result representative point closest to the starting point and the starting point is smaller than a first preset distance threshold, merging the result representative point closest to the starting point with the starting point; if the distance between the result representative point closest to the starting point and the starting point is larger than a second preset distance threshold value, determining the starting point again according to the result representative point set.

In some embodiments, if the included angle between the first vector formed by the start point and the second vector formed by the second point and the third point is smaller than the preset included angle threshold, after connecting the start point, the second point and the third point, the method further includes: if the included angle between the first vector formed by the starting point and the second point and the included angle between the second vector formed by the second point and the third point are larger than or equal to a preset included angle threshold value, the second point is redetermined.

In application, the lines may be extracted from the result representative point set by a nearest neighbor algorithm and a given connection rule. The nearest neighbor algorithm is measured by euclidean distance, which is the distance between two points calculated using the length of the straight line between the two points. Assuming that the longitude and latitude of the point a is (λ1, ψ1) and the longitude and latitude of the point B is (λ2, ψ2), the calculation formula between the two points is as follows:

the line is then obtained according to the following rules:

Setting an included angle threshold A, a distance threshold D _min and a distance threshold D _max, and selecting a starting point as a first point (the starting point can be the result representative point of the most edge on the line); finding the result representative point nearest to the current first point as a second point, weighting the center points based on the number of the covered track points if the distance between the two points is smaller than a distance threshold D _min for merging (the first point does not participate in merging), and taking another section (re-selecting the starting point in the reserved result representative points) if the distance between the two points is larger than a distance threshold D _max.

If the two points are at a suitable distance (D _min≤d_i,i+1≤D_max), searching for a third result representative point closest to the current second point; the third point and the second point are judged in the same way, if the distance between the third point and the second point is proper, the included angle between the first point and the second point and between the second point and the third point is calculated, and if the included angle between the vectors is larger than or equal to the included angle threshold A, the second point is removed and the second point closest to the first point is found again; if the vector included angle is smaller than the included angle threshold A, the first point is connected with the second point, the second point is set as the current first point, the vehicle line can be obtained by repeating the steps, and all the selected result representative points are sequentially connected.

The nearest neighbor algorithm and the connection rule ensure that the connection of the data points accords with the time sequence and the influence of other vehicle tracks can be effectively removed.

The following description will be given by way of specific examples. The vehicle GPS data is shown in table 1 below for a total of 64263 coordinate point data. The bandwidth value bw=2.5e-4 was set, and 499 pieces of initial representative point data were calculated by the above method, as shown in table 2 below.

TABLE 1

TABLE 2

The number of movements n=2, the radius of coverage r=1e-4, the threshold number v=40 in the range of the radius of coverage R. The above method was carried out 2 times to obtain 273 representative points of the results, as shown in Table 3. Removing the result representative points with the number of coordinates within the coverage radius less than or equal to 40 gives the following table 4, and 268 result representative points in total.

TABLE 3 Table 3

TABLE 4 Table 4

And selecting a result representative point with the minimum latitude as a starting point, wherein the longitude and latitude coordinates of the result representative point are [111.72036,29.02007]. The minimum distance threshold is set to be 1e-4, and the maximum distance threshold is set to be 0.02, namely, the distance between two points is between [1e-4,0.02] and is proper. The included angle threshold is set to 120 degrees. The circuit result finally extracted by the circulation is shown in the following fig. 2, the curve partial diagram is shown in the following fig. 3, and the robustness effect on outliers is shown in the following fig. 4.

According to the vehicle line extraction method provided by the embodiment of the application, the factor of inaccurate positioning offset caused by the influence of external objective environmental conditions on the GPS signal of the vehicle is fully considered, and the reliable and accurate vehicle line track can be restored. Under the condition that the position information (longitude and latitude) given by the GPS has offset, the method shows that the thinning and mean shift operation can effectively avoid the interference of abnormal values, so that a line with higher reliability and accuracy can be rapidly extracted under the connection rule.

Corresponding to the vehicle course extraction method described in the above embodiments, as shown in fig. 5, the present embodiment provides a vehicle course extraction device 500 including:

A data acquisition module 501, configured to acquire a vehicle track point set according to vehicle positioning data;

the initial representing module 502 is configured to pre-process the vehicle track point set through thinning and deduplication operations to obtain an initial representing point set;

A result representing module 503, configured to obtain a result representing point set according to the initial representing point set and the vehicle track points within the preset radius range of each initial representing point;

The circuit extracting module 504 is configured to connect each result representative point according to the result representative point set and a preset rule, and extract a vehicle circuit.

It should be noted that, because the content of information interaction and execution process between the modules/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.

The embodiment of the present application further provides an electronic device 600, as shown in fig. 6, including a memory 601, a processor 602, and a computer program 606 stored in the memory 601 and executable on the processor 602, where the processor 602 implements the steps of the vehicle route extraction method provided in the first aspect when executing the computer program 606.

In application, the electronic device may include, but is not limited to, a processor and a memory, fig. 6 is merely an example of an electronic device and does not constitute limitation of an electronic device, and may include more or less components than illustrated, or combine certain components, or different components, such as an input-output device, a network access device, etc. The input output devices may include cameras, audio acquisition/playback devices, display screens, and the like. The network access device may include a network module for wireless networking with an external device.

In an Application, the Processor may be a central processing unit (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

In applications, the memory may in some embodiments be an internal storage unit of the electronic device, such as a hard disk or a memory of the electronic device. The memory may also be an external storage device of the electronic device in other embodiments, such as a plug-in hard disk provided on the electronic device, a smart memory card (SMART MEDIA CARD, SMC), a secure digital (SecureDigital, SD) card, a flash memory card (FLASH CARD), or the like. The memory may also include both internal storage units and external storage devices of the electronic device. The memory is used to store an operating system, application programs, boot Loader (Boot Loader), data, and other programs, etc., such as program code for a computer program, etc. The memory may also be used to temporarily store data that has been output or is to be output.

The embodiments of the present application also provide a computer readable storage medium storing a computer program, which when executed by a processor, implements the steps of the above-described method embodiments.

The present application may be implemented in whole or in part by a computer program which, when executed by a processor, performs the steps of the method embodiments described above, and which may be embodied in a computer readable storage medium. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to an electronic device, a recording medium, computer Memory, read-Only Memory (ROM), random access Memory (RAM, random Access Memory), electrical carrier signals, telecommunications signals, and software distribution media. Such as a U-disk, removable hard disk, magnetic or optical disk, etc.

Those of ordinary skill in the art will appreciate that the various illustrative apparatus and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the embodiments of the apparatus described above are illustrative only, and the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, the apparatus may be indirectly coupled or in communication connection, whether in electrical, mechanical or other form.

The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims

1. A vehicle course extraction method, characterized by comprising:

acquiring a vehicle track point set according to vehicle positioning data;

2. The vehicle route extraction method according to claim 1, wherein the preprocessing of the vehicle track point set by thinning and deduplication operation to obtain an initial representative point set includes:

3. The vehicle route extraction method according to claim 1, wherein the obtaining a result representative point set according to the initial representative point set and the vehicle track points within the preset radius range of each initial representative point includes:

4. The vehicle route extraction method according to claim 1, wherein the connecting each result representative point according to the result representative point set and a preset rule, and extracting the vehicle route, comprises:

determining a starting point according to the result representative point set;

5. The vehicle course extraction method of claim 4, wherein determining a second point nearest to the start point and a third point nearest to the second point based on the first preset distance threshold and the second preset distance threshold comprises:

6. The vehicle course extraction method of claim 4, wherein the determining a second point nearest to the start point and a third point nearest to the second point based on the first preset distance threshold and the second preset distance threshold further comprises:

7. The vehicle route extraction method according to claim 4, wherein if an included angle between a first vector formed by the start point and the second point and an included angle between a second vector formed by the second point and the third point are smaller than a preset included angle threshold, connecting the start point, the second point and the third point further comprises:

8. A vehicle course extraction device characterized by comprising:

9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the vehicle route extraction method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the vehicle course extraction method according to any one of claims 1 to 7.