WO2023124470A1

WO2023124470A1 - Region coding method and apparatus, device and storage medium

Info

Publication number: WO2023124470A1
Application number: PCT/CN2022/127510
Authority: WO
Inventors: 徐攀登
Original assignee: 阿里云计算有限公司
Priority date: 2021-12-29
Filing date: 2022-10-26
Publication date: 2023-07-06
Also published as: CN114328788A

Abstract

The present application provides a region coding method and apparatus, a device and a storage medium. The method comprises: acquiring a position range of a region to be coded; determining a plurality of grids covering the position range, the plurality of grids being obtained by means of a first spatial grid coding algorithm, and determining a first code of a lowest common ancestors grid of the plurality of grids; according to boundary coordinates of the plurality of grids, determining, by means of a second spatial grid coding algorithm, a plurality of second codes corresponding to the plurality of grids, wherein the plurality of second codes correspond to the boundary coordinates of the plurality of grids, respectively; and according to the first code and the plurality of second codes, determining a target code of said region. Two spatial grid coding algorithms are combined to participate in coding of a region to be coded, such that the precision of a coding result finally obtained in said region is high, and the final coding result can also tolerate the deviation of boundary positions of said region to a certain extent.

Description

Area coding method, device, equipment and storage medium

This application claims the priority of the Chinese patent application with the application number 202111644026.6 and the title of the invention "region coding method, device, equipment and storage medium" filed with the China Patent Office on December 29, 2021, the entire contents of which are incorporated by reference in In this application.

technical field

The present application relates to the technical field of data processing, and in particular to a region coding method, device, equipment and storage medium.

Background technique

The geospatial grid is a spatial reference system that divides the geospatial region into units of different scales. Grid coding utilizes the structured index expression technology of geospatial position to assign the code to each grid unit of the geospatial grid system to realize the unified identification of the grid position, and the coding result of each grid is used as the spatial index. Commonly used geospatial grid coding algorithms include Geohash algorithm, Google S2 algorithm, and so on.

For example, in the application of supervising vehicles, it is necessary to analyze the vehicle parking area. Assume that a certain vehicle went to a certain loading and unloading point or parking area yesterday. According to the latitude and longitude positioning data and moving speed data of the vehicle at this time, a parking area A (the area where the continuous moving speed is lower than the set threshold) can be determined. ), at this time, it is necessary to perform spatial grid coding on the dwelling area A to obtain the corresponding spatial index of the dwelling area A. In addition, assuming that the vehicle goes to the loading and unloading point or the parking area today, a parking area B can be determined according to the latitude and longitude positioning data and moving speed data of the vehicle at this time. At this time, the parking area B needs to be Perform spatial grid coding to obtain the spatial index corresponding to the residence area B. Since the moving position of the vehicle is different each time, there may be deviations in the resident area each time. For example, the driving route of the vehicle loading and unloading is different yesterday and today, but they are all at the same loading and unloading point. This area is based on its use. Said it should be the same.

Therefore, in order to avoid the final misjudgment of different regions due to differences in regional boundaries, it is necessary to perform spatial grid coding according to the regional boundaries so that the coding results can tolerate a certain range of boundary deviations. The coding result is consistent with the coding result of the parking area B, because they both correspond to the above-mentioned loading and unloading points.

Contents of the invention

Embodiments of the present application provide an area encoding method, device, device, and storage medium, so as to implement spatial encoding of a location area.

In the first aspect, the embodiment of the present application provides a region coding method, including: obtaining the location range of the region to be coded; determining multiple grids covering the location range, and the multiple grids are obtained through the first spatial grid coding algorithm Determining the first encoding of the nearest common ancestor grid of multiple grids; according to the boundary coordinates of multiple grids, a plurality of second encodings corresponding to multiple grids are determined through the second spatial grid encoding algorithm, wherein , the multiple second codes respectively correspond to the boundary coordinates of the multiple grids; according to the first code and the multiple second codes, determine the target code of the area to be coded.

In the second aspect, the embodiment of the present application provides an area encoding device, including: an acquisition module, used to acquire the location range of the area to be encoded; a first encoding module, used to determine multiple grids covering the location range, and determine the The first coding of the nearest common ancestor grid of a grid, the multiple grids are obtained through the first spatial grid coding algorithm; the second coding module is used to pass the second coding according to the boundary coordinates of multiple grids The spatial grid coding algorithm determines multiple second codes corresponding to multiple grids, wherein the multiple second codes correspond to the boundary coordinates of the multiple grids; the determining module is configured to use the first code and the multiple second codes The second code is to determine the target code of the area to be coded.

In a third aspect, the embodiment of the present application provides an electronic device, including: a memory, a processor, and a communication interface; wherein, executable code is stored in the memory, and when the executable code is executed by the processor, the processor can at least Realize the region coding method as in the first aspect.

In a fourth aspect, the embodiment of the present application provides a non-transitory machine-readable storage medium, on which executable code is stored, and when the executable code is executed by a processor of an electronic device, the The processor can at least implement the region coding method in the first aspect.

In the fifth aspect, the embodiment of the present application provides an area encoding method, including: determining the position range of the area to be encoded according to the position information of the vehicle corresponding to the parking state within a set time period; Grid, multiple grids are obtained through the first spatial grid encoding algorithm; determine the first encoding of the nearest common ancestor grid of multiple grids; according to the boundary coordinates of multiple grids, through the second spatial network The lattice coding algorithm determines multiple second codes corresponding to multiple grids, wherein the multiple second codes correspond to the boundary coordinates of multiple grids respectively; according to the first code and multiple second codes, determine the area to be coded The target code; store the corresponding relationship between the target code and the vehicle identification of the vehicle.

The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present application will be readily apparent by reference to the drawings and the following detailed description.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings that need to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application. For those skilled in the art, other drawings can also be obtained based on these drawings without creative effort.

FIG. 1 is a flow chart of an area coding method provided in an embodiment of the present application;

FIG. 2 is a schematic diagram of a determination result of an S2 grid set covering an area to be encoded provided by an embodiment of the present application;

FIG. 3 is a schematic diagram of a nearest common ancestor grid of a S2 grid set provided in an embodiment of the present application;

Fig. 4 is a schematic diagram of two areas with a boundary position deviation having the same encoding result provided by the embodiment of the present application;

FIG. 5 is a flow chart of an area coding method provided in an embodiment of the present application;

FIG. 6 is a schematic structural diagram of a region coding device provided by an embodiment of the present application; and

FIG. 7 is a schematic structural diagram of an electronic device corresponding to the region encoding device provided in the embodiment shown in FIG. 6 .

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. Under the condition that there is no conflict between the various embodiments, the following embodiments and the features in the embodiments can be combined with each other. In addition, the sequence of steps in the following method embodiments is only an example, rather than a strict limitation.

The region coding method provided in the embodiment of the present application can be executed by an electronic device, which can be a server or a user terminal, and the server can be a physical server or a virtual server (virtual machine) in the cloud.

Two different spatial grid coding algorithms used in the area coding method provided by the embodiment of the present application, for example, the first spatial grid coding algorithm can be the Google S2 algorithm, and the second spatial grid coding algorithm can be the Geohash algorithm, of course , not limited to this, the first spatial grid encoding algorithm can be any spatial grid that can divide the earth space (or map space) into grids of different scales and uniquely encode each grid lattice encoding algorithm.

The Geohash algorithm, invented by Gustavo Niemeyer, is a hierarchical data structure that divides space into a quadrilateral grid. What the Geohash algorithm does is to encode a latitude and longitude coordinate point and map it to a string. Each string represents a rectangular area divided by latitude and longitude. Different latitude and longitude coordinates may be mapped to the same character. string. The length (code length) of the string calculated by the Geohash algorithm can control the size of the grid. There are 12 levels of Geohash encoding, and the side length ranges from 5000km to 3.7cm. Among the 12 levels provided by the algorithm, the change of each level in the middle is relatively large, and sometimes the coverage of the upper level may be too large, while the coverage of the lower level may be too small.

A framework for decomposing a unit sphere into a hierarchy of cells is defined in the Google S2 algorithm. Each grid (Cell) is a quadrilateral bounded by four geodesics. The top layers of the hierarchy are obtained by projecting the six faces of the cube onto the unit sphere, and the lower layers are obtained recursively by subdividing each upper mesh into four sub-meshes (sublayers). The S2 library decomposes the unit sphere into a hierarchical structure called Cell, and encodes all the Cells on the three-dimensional sphere (similar to the earth). The encoding of each unit is uniquely identified by a 64-bit CellId, that is, the cellId of each grid The length of the encoding result is 64bit. The S2 algorithm provides a total of 30 levels of grid coding, ranging from 0.7cm to 85,000,000km in side length. Among the 30 levels provided by the algorithm, the change of each level in the middle is relatively gentle, close to the curve of the 4th power.

The area coding scheme provided by the embodiment of the present application can be applied to the scene of dynamic area coding, wherein the so-called dynamic means that the moving objects such as vehicles are actually in the same "functional area" each time but because of the possible low-speed movement and route of the vehicle Situations where the residency area deviates due to the change.

For example, in the example above: in the same loading and unloading point or parking lot area, the parking area corresponding to the vehicle on the first day is A, and the parking area corresponding to the second day is B, and the parking area A and parking area B are incomplete. The same, the boundary will be deviated, but they are actually in the same functional area - the loading and unloading point or the parking area. In other words, the coding results corresponding to the two resident areas should be the same, because they actually correspond to the same functional area. From another perspective, for one of the resident areas such as resident area A, the final encoding result needs to tolerate a certain range of boundary deviations in the area, that is, the encoding result is slightly different from the boundary of the resident area A. The same applies for the dwell area B of the deviation. To put it simply, assuming that the range covered by the final encoding result is called range X, then both the resident area A and the resident area B should be included in the range X, but the range X should not be larger than the resident area A. 1. The location range of the dwelling area B is too large, because the encoding precision will be too low.

The implementation process of the region coding scheme provided by the embodiment of the present application will be described below.

FIG. 1 is a flow chart of an area coding method 100 provided by an embodiment of the present application. As shown in FIG. 1 , the method 100 includes the following steps 101 to 104 .

In step 101, the location range of the region to be coded is obtained.

In one embodiment, obtaining the location range of the area to be coded can be achieved by: obtaining the location information continuously sent by the vehicle; if it is determined according to the location information that the vehicle is moving at a low speed within a set The received location information determines the location range of the area to be coded.

Wherein, the low-speed moving state includes a stop state and a moving state whose speed is lower than a set threshold.

The vehicle can report its own vehicle status data at short set time intervals, including the current position, moving speed, etc. Assuming that the above-mentioned set time is 10 minutes, if the vehicle is within 10 consecutive minutes, the reported speed is low When the threshold is set, it can be considered that the vehicle is in a parked state. At this time, the location coordinates (latitude and longitude coordinates) received within the 10 minutes can be combined to determine the location range defined by these latitude and longitude coordinates as the area to be encoded. The location range of , that is, the location range of the residence area. For example, calculate the maximum longitude and latitude and minimum longitude and latitude, that is, the positions of the southeast and northwest corners of the rectangle, and the rectangle drawn in this way is the resident area, that is, the area to be coded. 10 minutes is just an example, and the value of the set duration can be set according to actual needs.

The way to determine the area to be coded is not limited to the rectangular area determined by the above-mentioned maximum latitude and longitude and minimum longitude and latitude, other methods for determining the minimum circumscribed polygonal area surrounding each position coordinate within the above 10 minutes can be used.

In addition, in the above example, the parking state of the vehicle is determined based on the moving speed. In fact, whether the vehicle is in the parking state can also be determined in the following way: According to the position coordinates reported by the vehicle within 10 consecutive minutes, determine the 10 The moving distance of the vehicle in minutes, if the moving distance is less than the set threshold (such as 200 meters), it is considered that the vehicle is in the parking state within these 10 minutes, and the position range of the area to be encoded is calculated according to the position coordinates reported within these 10 minutes .

For a special situation, assuming that the reported position of the vehicle is the same within 10 consecutive minutes, that is, the vehicle is completely stopped, at this time, it can be determined that the area to be encoded is a circle with the position coordinate as the center and the preset length as the radius area, the preset length is, for example, 200 meters.

In step 102, a plurality of grids covering the location range of the area to be encoded is determined, and a first encoding of the nearest common ancestor grid of the plurality of grids is determined, and the plurality of grids are obtained through a first spatial grid encoding algorithm.

In one embodiment, taking the first spatial grid coding algorithm as the Google S2 algorithm as an example, the S2 library provides a function for obtaining a grid covering a certain area, which is called a grid screening algorithm here, and for a certain For an area x, set the parameters such as the maximum number of cells (MaxCells), the maximum accuracy level of the grid (MaxLevel), and the minimum accuracy level of the grid (MinLevel), that is, the grid screening algorithm can be used to solve the problem that covers the area The grid collection of x.

Based on this, in this embodiment, determining a plurality of grids covering the location range of the area to be encoded can be implemented as: determining from a variety of different grid precision levels provided by the first spatial grid encoding algorithm and the grid area to be encoded A target grid accuracy level for location range matching; input the target grid accuracy level and the number of grids into a preset grid screening algorithm, so as to output a plurality of second grids through the grid screening algorithm.

It should be noted that, on the basis of obtaining several grids of different scales (that is, different precision levels) corresponding to the earth space through the first spatial grid coding algorithm in advance, in fact, not only the Encoding, and the coverage location range of each grid is also known, and the coverage location range can be represented by the four boundary coordinates of the grid. In addition, the input of the above-mentioned grid screening algorithm also includes the location range of the area to be encoded, so that the grid screening algorithm can screen out a plurality of grids that match the location range of the area to be encoded from several known grids . The mesh screening algorithm can find the plurality of meshes by using a greedy algorithm.

In addition, the target grid accuracy level matching the location range of the area to be encoded is determined from a variety of different grid accuracy levels provided by the first spatial grid encoding algorithm. In one embodiment, it can be based on the area of the area to be encoded As well as the coverage area of each level of grid, determine the target grid accuracy level that matches the area of the area to be coded. Or, in one embodiment, the target grid accuracy level can also be set to a default level, such as level=13, which covers a side length of about 1000 meters, because the side length of most functional areas in practical applications Generally within the range of 1000 meters.

It can be known from the above description that in this embodiment, the parameters can be set as follows: MaxLevel=MinLevel=13, MaxCells=1.

Wherein, the setting of MaxLevel=MinLevel makes the determined multiple grids have the same precision level, so that the multiple grids are actually adjacent grids. MaxCells=1 does not mean that the number of determined grids is only one, but if a grid with a precision level that can surround the area to be encoded cannot be found and meets the MaxLevel=MinLevel constraint, it will further search for the minimum number The precision level that can enclose the area to be coded is a plurality of grids conforming to the constraint of MaxLevel=MinLevel, and the minimum number, that is, the number of multiple grids is generally greater than or equal to 2.

Of course, if in practical applications, through the above-mentioned grid screening algorithm, based on the input parameter values, a grid that can enclose the area to be encoded with a precision level that meets the constraint of MaxLevel=MinLevel is directly found, then the grid’s encoding That is, it can be used as the final target encoding corresponding to the area to be encoded, and the encoding process can be ended.

It should be noted that, in fact, MaxLevel can also be different from MinLevel. For example, MinLevel is set to a certain grid precision level whose coverage area is equal to or smaller than the area corresponding to the area to be coded, and MaxLevell is set to cover an area larger than the area corresponding to the area to be coded. A certain grid precision level for the area. MaxCells can also be set to a value greater than 1.

In conjunction with Fig. 2, the determination results of the above-mentioned multiple grids covering the region to be coded are exemplified. The multiple grids in the area to be coded are composed of grid g1 and grid g2, where it is assumed that the precision levels corresponding to grid g1 and grid g2 are both 13.

That is to say, what is illustrated in FIG. 2 is a situation where the region to be encoded spans different grids. In fact, grid g1 and grid g2 may have a brother relationship or a cousin relationship. If it is a sibling relationship, both will have a common parent grid. In the case of a cousin relationship, there is a brother or cousin relationship between its parent grids. However, no matter what kind of adjacent relationship between grid g1 and grid g2 is, when the area to be coded can only be covered by multiple grids, it is impossible to directly use the coding of grid g1 and grid g2 to code the area to be coded uniquely coded.

Therefore, next, it is necessary to determine the nearest common ancestor grid of the plurality of grids, and the encoding of the nearest common ancestor grid is called the first encoding.

Before introducing the determination process of the first encoding of the nearest common ancestor grids of the above-mentioned multiple grids, the nearest common ancestor grids of grid g1 and grid g2 are illustrated with reference to FIG. 3 .

As shown in Figure 3, first, it is necessary to find the respective parent grids of grid g1 and grid g2, assuming that they are grid parent_g1 and grid parent_g2 respectively, and it is found that grid parent_g1 and grid parent_g2 are still two neighboring grids. different grids, and then continue to find the parent grids of grid parent_g1 and grid parent_g2, which are assumed to be grid parent_parent_g1 and grid parent_parent_g2 respectively. It is found that the grid parent_parent_g1 and the grid parent_parent_g2 are still two different grids adjacent to each other, continue to find the parent grids of the grid parent_parent_g1 and the grid parent_parent_g2, and so on, assuming that a grid G is finally found, that is, the grid The parent grid of grid parent_parent_g1 and grid parent_parent_g2 is the same grid G, and at this time, grid G is the nearest common ancestor grid of grid g1 and grid g2.

In the Google S2 algorithm, each grid code (CellID) is composed of 64 bits. The first 3 bits represent one of the 6 faces of the cube, and the value range is [0,5]. 3 bits can represent the value 0-7, but 6, 7 are invalid values. The last bit of 64 bits is 1, which is reserved on purpose. Used to quickly find how many bits are in the middle. Search forward from the last digit at the end to find the first position that is not 0, that is, to find the first 1, and the previous digit of this digit to the 4th digit at the beginning (because the first 3 digits are occupied) are all available number. Meshes with level > 0 have a common ancestor.

Based on the grid coded data structure, in fact, the problem of finding the nearest common ancestor grid can be transformed into the problem of finding the longest common sequence in multiple grid coded binary strings from left to right, and the longest one is from The root node (encoding of the grid with level=1) starts with the furthest common ancestor, which is the nearest common ancestor grid.

In one embodiment, the nearest common ancestor grid of multiple grids can be determined in the following manner: Exclusive OR processing is performed on the codes of multiple grids to obtain an exclusive OR result; The common sequence length of the coding of grids; according to the common sequence length, determine the first coding of the nearest common ancestor grid of multiple grids.

Due to the 64-bit length process, for the convenience of examples, only a shorter length of 24 is used as an example here: suppose the code of the grid g1 is: 111111111100000000000000. Suppose the code of grid g2 is: 111111121100000000000000.

The XOR result of the coding of the above two grids is: 000000010000000000000000, that is, 10000000000000000, and the length is 17. Note that the multi-bit 0s in front of the XOR are meaningless, so ignore them.

Based on this, the common sequence length of the coding of the two grids is: 24-17=7 bits, which means that the first 7 bits of the coding of the two grids are the same, so, from the coding of the two grids Intercept the first 7 codes, and set the remaining 17 codes to 0 to get the code of the nearest common ancestor grid of the two grids: 111111100000000000000000.

In step 103, according to the boundary coordinates of the plurality of grids, a plurality of second codes corresponding to the plurality of grids are determined through the second spatial grid encoding algorithm, wherein the plurality of second codes correspond to the plurality of grids respectively Coordinates of each boundary.

In step 104, according to the first code and multiple second codes, the target code of the region to be coded is determined.

Wherein, the common prefix codes of multiple second codes may be determined first, and then, according to the first codes and the common prefix codes, the target codes of the regions to be coded are determined.

In the embodiment of the present application, the area defined by the position coordinates corresponding to the vehicle in the parking state for a period of time can be used as the area to be encoded. The position range of the area to be encoded is determined by the minimum and maximum latitude and longitude coordinates. After the location range of the area to be encoded is obtained, spatial grid encoding is performed on the area to be encoded to determine its corresponding target encoding. Specifically, first, among the known grids obtained by the first spatial grid encoding algorithm (such as Google S2 algorithm), determine multiple grids covering the area to be encoded, and then determine the nearest common grid of multiple grids. The ancestral grid, that is, the encoding that determines the nearest common ancestor grid (referred to as the first encoding). Secondly, according to the boundary coordinates of multiple grids, a plurality of second codes corresponding to multiple grids are determined through a second spatial grid coding algorithm (such as Geohash algorithm), wherein the multiple second codes correspond to multiple The coordinates of each boundary of the grid. Finally, according to the first code and multiple second codes, the target code of the region to be coded is determined.

In the embodiment of the present application, two different spatial grid encoding algorithms are jointly used to uniquely encode the area to be encoded, wherein, the grids of different levels obtained based on the first spatial grid encoding algorithm are determined to be After calculating the multiple grids corresponding to the region, and calculating the nearest common ancestor grids of these multiple grids, since the range that the nearest common ancestor grid can cover may be much larger than the range of the area to be encoded, the nearest common ancestor is directly used If the first code corresponding to the grid is used as the unique coding identifier of the region to be coded, there will be a large positional deviation. Therefore, in order to reduce the deviation, the second space grid coding algorithm is combined to participate in the coding of the area to be coded. In the recent public In the case that the ancestral grid will cause a large error, the error can be reduced through the second encoding results corresponding to the above-mentioned multiple grids in the second spatial grid encoding algorithm, so that the accuracy of the encoding result finally obtained in the area to be encoded higher. In addition, the combination of the first encoding of the above-mentioned common ancestor grid and the above-mentioned multiple second encodings to determine the grid encoding result of the area to be encoded can tolerate a certain degree of deviation of the boundary of the area to be encoded, that is, for example, two boundary coordinates For different but mostly overlapping areas to be encoded, the encoding method provided by the embodiment of the present application can often make the two areas to be encoded have the same encoding result.

For the case where the region to be encoded is covered by multiple grids, the encoding of the nearest common ancestor grid of multiple grids is calculated, because the accuracy level corresponding to the nearest common ancestor grid may differ from the accuracy level of the above MinLevel grid Larger, it will cause the side length of the nearest common ancestor grid to be larger than the maximum side length deviation of the region to be encoded. As shown in Figure 3, assuming that grid g1 and grid g2 have level=15, the side length is about 306 meters, the maximum side length of the region to be coded is about 600 meters, and the nearest common ancestor grid of grid g1 and grid g2 The level=11, the side length is about 5000 meters, and the deviation is large.

In order to reduce the error, this embodiment combines the second spatial grid encoding algorithm such as the geohash algorithm to participate in the spatial encoding process of the area to be encoded. The length of the geohash grid encoding is similar to the grid precision level of the first spatial grid encoding algorithm above. Different encoding lengths correspond to different coverage areas. In the case that the encoding of the nearest common ancestor grid of the above multiple grids has a large error, the error can be reduced by the longest common prefix of the geohash encoding corresponding to the multiple grids.

In one embodiment, firstly, according to the boundary coordinates of the multiple grids, multiple second codes corresponding to the multiple grids are determined through a second spatial grid coding algorithm such as the geohash algorithm. As above, the four boundary coordinates of each grid are known, and the encoding result corresponding to each boundary coordinate can be obtained based on the geohash algorithm.

In addition, as above, the geohash algorithm can output codes of different lengths, each length corresponding to a different coverage. In practical applications, a default target code length, such as 9 bits, can be set according to the actual situation. In this way, each boundary coordinate will be coded into a code whose length is the target code length. Alternatively, the target coding length can also be determined in the following manner: obtain the coverages corresponding to different coding lengths under the second spatial grid coding algorithm; The location range of the coded region matches the target code length. Wherein, the matching may be: the side length corresponding to the target encoding length is less than or equal to the longest side length of the region to be encoded.

After obtaining the second code corresponding to each boundary coordinate of each grid of the plurality of grids, determine the common prefix code of all the obtained multiple second codes.

In one embodiment, assuming that multiple second codes include: abcdefg, abcdefd, abcdefe, abcdefb, the longest common prefix code of these codes is: abcdef.

The target code of the area to be coded can be determined as: the splicing result of the first code of the above-mentioned nearest common ancestor grid and the common prefix codes of multiple second codes: first code_common prefix code.

However, in practical applications, there may be some special cases, such as the coverage area corresponding to the common prefix code is larger than the coverage area corresponding to the first code. At this time, the target code of the area to be coded can use the first code.

That is to say, if the coverage corresponding to the common prefix code is smaller than the coverage corresponding to the first code, it is determined that the target code of the area to be coded is the splicing result of the first code and the public prefix code; if the coverage corresponding to the public prefix code is larger than For the coverage area corresponding to the first code, it is determined that the target code of the area to be coded is the first code.

The splicing result of the first code and the public prefix code can be understood as follows: within a large range defined by the first code, multiple small sub-regions are further divided, and the code of one of the sub-regions is the common prefix code , the encoding of this sub-area is the encoding result of the area to be encoded. Therefore, the use of geohash common prefix encoding to reduce the error caused by the grid encoding of the nearest s2 common ancestor.

Based on the above introduction, it can be seen that the coverage corresponding to the finally determined target code depends on the coverage corresponding to the above-mentioned first code and the common prefix code, and this coverage is generally larger than the location range of the area to be coded, so , so that all the regions to be coded that fall within the coverage corresponding to the target code will eventually get the same target code through the coding method provided by the embodiment of the present application, that is, the target code can tolerate the area boundary of the region to be coded to have A certain degree of deviation, with good credibility and stability. For example, as shown in Figure 4, most of the area to be encoded Q1 and the area to be encoded Q2 shown in the figure overlap, but the boundary position is slightly different. Based on the above encoding scheme, the final area Q1 to be encoded and the area to be encoded Q2 corresponds to the same target encoding, and two different encoding results will not be caused due to a slight boundary deviation between the two regions to be encoded.

In addition, the coverage area corresponding to the target code obtained through the above solution is not significantly larger than the location range of the area to be coded, so the accuracy of the coded result is guaranteed.

In one implementation manner, performing spatial grid coding on the area to be coded has many practical significances. For example, the corresponding relationship between the target code and the resident information of the vehicle may be recorded, wherein the resident information includes the identification of the vehicle and the number of resident times of the vehicle. The vehicle refers to the vehicle in the above-mentioned area to be encoded determined according to the vehicle state data such as its position and moving speed. For example, the geographic area corresponding to the target code is actually a parking lot area. A certain vehicle often parks in this parking lot area, and then every time it goes to this parking lot area to park, it can determine an area to be encoded. However, the final target codes corresponding to each determined area to be coded are the same, and the corresponding relationship between the target codes and the number of parking times of the vehicle can be recorded.

For another example, it can also be used to analyze the traffic situation of users. For example, if a user often travels between places X and Y, then every time he drives to place X, he can determine a region to be coded, and determine the target code corresponding to each region to be coded through the above scheme Both are A. Similarly, every time you drive to the location Y, you can determine a region to be coded. Through the above scheme, it is determined that the target code corresponding to each region to be coded is B. Then, combined with the target code The number of parking times of the vehicle associated with records on A and target code B, and the regularity between the time when the above target code A and target code B are determined each time, it can be analyzed that the user is often in the two target codes. Analysis results to and from geographic regions.

The following is an exemplary description of the optional specific implementation of the two calculation processes involved in the above. One of the calculation processes is: determining the first code of the nearest common ancestor grid of multiple grids, and the other calculation process is : Determine the common prefix encoding of multiple second encodings.

Regarding the first code for determining the nearest common ancestor grid of the plurality of grids, in fact, the number of the plurality of grids may be more than two, such as may be three, four, and so on. To determine the first code of the nearest common ancestor grid of multiple grids, XOR calculation can be directly performed on the codes of these multiple grids, and the first code of the nearest common ancestor grid can be determined according to the XOR result. Or, based on the computing power of the electronic equipment that implements the regional coding scheme, it is also possible to perform XOR with the coding of two grids, and finally determine the nearest common ancestor network according to the target XOR result with the longest median of the obtained multiple XOR results The first code of the grid. For example, assuming that multiple grids are composed of grid 1, grid 2 and grid 3, the bit length of the XOR result of grid 1 and grid 2 is n1, and the XOR result of grid 1 and grid 3 The length of bits is n2, the length of bits of the XOR result of grid 2 and grid 3 is n3, and assuming that n1 is greater than n2, and n1 is greater than n3, that is, the number of bits of the XOR result of grid 1 and grid 2 n1 is the longest, and the total length of the coding of the grid is 64 in addition, then it can be determined that the common sequence length of the coding of the three grids is: 64-n1=m bits, which means that the coding of the three grids is The first m bits are the same, so the codes of the nearest common ancestor grid of the three grids can be obtained by cutting out the first m bit codes from the codes of the three grids, and setting the remaining n1 bit codes to 0.

For determining the common prefix code of multiple second codes, assuming that the lengths of multiple second codes are equal and the length is k, then the middle position of the total length can be taken first: (1+k)/2=p, more If the first p bits of the second codes are equal, it is determined that the first p bits of the multiple second codes are the same, and at this time, the traversal range is updated to the remaining bits after the p bits, and the middle position of the remaining bits is calculated , repeat the above process; and if the first p bits of multiple second codes are not equal, it means that the common prefix codes of multiple second codes are located within the first p bits and will not be located after p bits. , update the traversal range to the first p bits, calculate the middle position of the first p bits, and repeat the above judgment process. In this way, by traversing layer by layer, the longest common prefix part of multiple second codes can be found.

FIG. 5 is a flow chart of an area coding method 500 provided by an embodiment of the present application. As shown in FIG. 5 , the method 500 may include steps 501 to 504 as follows.

In step 501, the location range of the area to be coded is determined according to the location information of the vehicle corresponding to the parking state continuously within a set time period.

For the implementation of this step, reference may be made to relevant descriptions in the foregoing embodiments, and details are not repeated here.

In step 502, a plurality of grids covering a location range are determined, and a first encoding of a nearest common ancestor grid of the plurality of grids is determined, the plurality of grids are obtained through a first spatial grid encoding algorithm.

In step 503, according to the boundary coordinates of the multiple grids, a plurality of second codes corresponding to the multiple grids are determined through the second space grid coding algorithm, wherein the multiple second codes correspond to the multiple grids respectively Coordinates of each boundary.

In step 504, according to the first code and multiple second codes, the target code of the area to be coded is determined, and the corresponding relationship between the target code and the vehicle identification of the vehicle is stored.

In an embodiment, the area coding method further includes: according to the storage result, determining the number of times the vehicle stays in the location area corresponding to the target code. Wherein, the location area corresponding to the target code refers to the location area where all coding results are the target code, including but not limited to the above-mentioned to-be-coded area.

In one embodiment, for example, there may be a need to analyze where the user often goes. In the face of this need, it is assumed that the user travels by car and needs to stop after arriving at a certain place. During the parking process, the moving speed of the vehicle is Relatively low, it is considered to be continuously in the resident state (the state where the speed is lower than the set threshold), so that the above-mentioned area to be encoded can be formed based on the movement track generated during the parking process, and the area to be encoded is encoded to obtain the above-mentioned target code (determination of the target code For the process, refer to the related descriptions in other aforementioned embodiments), so as to record the corresponding relationship between the target code and the vehicle identification in turn, indicating that the user drives to the location area corresponding to the target code once. Every time the user drives to the location area, an area to be encoded will be formed based on the parking trajectory at that time, and the target codes corresponding to the area to be encoded each time are consistent, so the user's position corresponding to the target code can be calculated The number of stops in the area, and the time of each arrival. Provide a basis for subsequent targeted service pushes for users based on the location statistics.

In another embodiment, the method further includes: acquiring the area function information corresponding to the target code; determining whether the vehicle has the authority to park in the location area corresponding to the target code according to the area function information; if the vehicle does not have the authority, generating a vehicle violation record.

In one embodiment, according to the location and range of the location area corresponding to the target code, the corresponding area function information, such as parking lot, passenger station, and so on, can be obtained. The area function information may be pre-marked by the traffic management agency.

For example, assume that the function of the location area corresponding to the target code is: passenger station. However, if the vehicle of the user entering the area does not have an operating permit, it means that the vehicle does not have the authority to enter the location area and park. The parking record includes information such as vehicle identification, target code, and entry time. Wherein, it may be determined by querying the license issuing database whether the user's vehicle has the authority to park at the passenger station.

The area coding device of one or more embodiments of the present application will be described in detail below. Those skilled in the art can understand that these devices can be configured by using commercially available hardware components through the steps taught in this solution.

FIG. 6 is a schematic structural diagram of a region coding device provided by an embodiment of the present application. As shown in FIG.

The obtaining module 11 is used to obtain the location range of the region to be coded.

The first encoding module 12 is configured to determine a plurality of grids covering a location range, and determine a first encoding of a nearest common ancestor grid of the plurality of grids, and the plurality of grids are obtained through a first spatial grid encoding algorithm.

The second coding module 13 is used to determine multiple second codes corresponding to multiple grids through the second spatial grid coding algorithm according to the boundary coordinates of multiple grids, and determine the common prefix codes of multiple second codes, wherein , the plurality of second codes respectively correspond to the boundary coordinates of the plurality of grids.

The determination module 14 is configured to determine the target code of the area to be coded according to the first code and the common prefix code.

In one embodiment, the first encoding module 12 is specifically configured to: perform XOR processing on the codes of multiple grids to obtain an XOR result; determine the common value of the codes of multiple grids according to the bit length of the XOR results. Sequence length; according to the common sequence length, determine the first encoding of the nearest common ancestor grid of the plurality of grids.

In one embodiment, the encoding lengths of multiple second encodings are the target encoding lengths, and the target encoding lengths are preset values, or the target encoding lengths are determined according to the following method: obtaining the different encoding lengths under the second space grid encoding algorithm The coverage corresponding to the length; according to the location range of the region to be encoded and the coverage corresponding to different encoding lengths, determine the target encoding length matching the location range of the area to be encoded.

In one embodiment, the first encoding module 12 is specifically configured to: determine a target grid accuracy level that matches the location range of the area to be encoded from a variety of different grid accuracy levels provided by the first spatial grid encoding algorithm; Input the target grid accuracy level and the number of grids into the preset grid screening algorithm, so as to output a plurality of second grids through the grid screening algorithm.

In one embodiment, the determining module 14 is specifically configured to: if the coverage area corresponding to the common prefix code is smaller than the coverage area corresponding to the first code, determine that the target code of the area to be coded is the splicing result of the first code and the public prefix code ; If the coverage area corresponding to the common prefix code is larger than the coverage area corresponding to the first code, determine that the target code of the area to be coded is the first code.

In one embodiment, the acquiring module 11 is specifically used to: acquire the location information continuously sent by the vehicle; The information determines the location range of the region to be coded.

In one embodiment, the area coding device further includes: a statistics module, configured to record the correspondence between the target code and the parking information of the vehicle, where the parking information includes the identification of the vehicle and the number of parking times of the vehicle.

The device shown in FIG. 6 can execute the steps provided in the foregoing embodiments. For the detailed execution process and technical effects, refer to the descriptions in the foregoing embodiments, and details are not repeated here.

In a possible design, the structure of the region encoding device shown in FIG. 6 above can be implemented as an electronic device. As shown in FIG. 7 , the electronic device may include: a processor 21 , a memory 22 , and a communication interface 23 . Wherein, executable codes are stored in the memory 22, and when the executable codes are executed by the processor 21, the processor 21 can at least implement the region encoding method provided in the foregoing embodiments.

In addition, the embodiment of the present application provides a non-transitory machine-readable storage medium, the non-transitory machine-readable storage medium stores executable code, when the executable code is executed by the processor of the electronic device , so that the processor can at least implement the region coding method provided in the foregoing embodiments.

The device embodiments described above are only illustrative, and the network elements described as separate components may or may not be physically separated. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. It can be understood and implemented by those skilled in the art without any creative efforts.

Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of a general hardware platform plus necessary, and of course can also be implemented by a combination of hardware and software. Based on such an understanding, the above-mentioned technical solution can be embodied in the form of a computer product in essence or the part that contributes to the related technology, and this application can adopt one or more computer-usable storage media containing computer-usable program codes. (including but not limited to disk storage, CD-ROM, optical storage, etc.) in the form of a computer program product.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, rather than limiting them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still Modifications are made to the technical solutions described in the foregoing embodiments, or equivalent replacements are made to some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims

A region coding method, comprising:

Obtain the location range of the area to be encoded;

determining a plurality of grids covering the range of locations, the plurality of grids obtained by a first spatial grid coding algorithm;

determining a first encoding of a nearest common ancestor mesh of the plurality of meshes;

According to the boundary coordinates of the plurality of grids, a plurality of second codes corresponding to the plurality of grids are determined through a second spatial grid encoding algorithm, wherein the plurality of second codes correspond to the plurality of grids respectively. The boundary coordinates of each grid;

Determine a target code of the region to be coded according to the first code and the plurality of second codes.
The method according to claim 1, wherein said determining the target code of the region to be coded according to the first code and the plurality of second codes comprises:

determining a common prefix code of the plurality of second codes;

Determine the target code of the region to be coded according to the first code and the common prefix code.
The method according to claim 1, wherein said determining the first encoding of the nearest common ancestor grid of said plurality of grids comprises:

Exclusive OR processing is performed on the codes of the plurality of grids to obtain an exclusive OR result;

determining the common sequence length of the coding of the plurality of grids according to the bit length of the XOR result;

A first encoding of a nearest common ancestor grid of the plurality of grids is determined based on the common sequence length.
The method according to claim 1, wherein the code lengths of the plurality of second codes are target code lengths, and the target code length is a preset value, or the target code length is determined according to the following manner:

Acquiring coverages corresponding to different coding lengths under the second spatial grid coding algorithm;

According to the location range of the region to be coded and the coverage ranges corresponding to the different code lengths, determine a target code length matching the location range of the region to be coded.
The method of claim 1, wherein said determining a plurality of grids covering said range of locations comprises:

determining a target grid precision level that matches the location range of the region to be encoded from a plurality of different grid precision levels provided by the first spatial grid coding algorithm;

The target mesh accuracy level and the number of meshes are input into a preset mesh screening algorithm, so as to output the plurality of second meshes through the mesh screening algorithm.
The method according to claim 2, wherein said determining the target code of the region to be coded according to the first code and the common prefix code comprises:

If the coverage corresponding to the common prefix code is smaller than the coverage corresponding to the first code, then determine that the target code of the area to be coded is the splicing result of the first code and the public prefix code;

If the coverage corresponding to the common prefix code is larger than the coverage corresponding to the first code, determine that the target code of the area to be coded is the first code.
The method according to any one of claims 1 to 6, wherein said obtaining the location range of the region to be coded comprises:

Obtain the location information continuously sent by the vehicle;

If it is determined according to the position information that the vehicle is moving at a low speed within a set time period, the position range of the area to be encoded is determined according to the position information received within the set time period.
The method according to claim 7, wherein the method further comprises:

Recording the correspondence between the target code and the resident information of the vehicle, where the resident information includes the identification of the vehicle and the resident times of the vehicle.
A region coding device, comprising:

An acquisition module, configured to acquire the location range of the area to be encoded;

A first encoding module, configured to determine a plurality of grids covering the location range, determine a first encoding of a nearest common ancestor grid of the plurality of grids, the plurality of grids are passed through the first spatial grid obtained by the encoding algorithm;

The second encoding module is configured to determine a plurality of second encodings corresponding to the plurality of grids through a second spatial grid encoding algorithm according to the boundary coordinates of the plurality of grids, and determine the plurality of second encodings A public prefix code, wherein the plurality of second codes correspond to the boundary coordinates of the plurality of grids;

A determining module, configured to determine a target code of the region to be coded according to the first code and the plurality of second codes.
An electronic device, comprising: a memory, a processor, and a communication interface; wherein, executable code is stored on the memory, and when the executable code is executed by the processor, the processor is made to execute the The area coding method described in any one of 1 to 8.
A non-transitory machine-readable storage medium, wherein executable code is stored on the non-transitory machine-readable storage medium, and when the executable code is executed by a processor of an electronic device, the processor Executing the region coding method as described in any one of claims 1 to 8.
A region coding method, comprising:

Determine the location range of the area to be encoded according to the location information of the vehicle that continuously corresponds to the parking state within the set duration;

determining a plurality of grids covering the range of locations, the plurality of grids obtained by a first spatial grid coding algorithm;

determining a first encoding of a nearest common ancestor mesh of the plurality of meshes;

According to the boundary coordinates of the plurality of grids, a plurality of second codes corresponding to the plurality of grids are determined through a second spatial grid encoding algorithm, wherein the plurality of second codes correspond to the plurality of grids respectively. The boundary coordinates of each grid;

determining a target code of the region to be coded according to the first code and the plurality of second codes;

The corresponding relationship between the target code and the vehicle identification of the vehicle is stored.
The method according to claim 12, wherein said method further comprises:

According to the storage result, determine the number of stays of the vehicle in the location area corresponding to the target code.
The method according to claim 12, wherein said method further comprises:

Acquiring regional function information corresponding to the target code;

According to the area function information, determine whether the vehicle has the authority to park in the location area corresponding to the target code;

If the vehicle does not have the authority, a parking violation record of the vehicle is generated.