Method for determining station position, method for determining, device and electronic equipment

Abstract

This application provides a method, a judgment method, an apparatus, and an electronic device for determining a site location. The method for determining the site location may include: determining a candidate region based on acquired trajectory points; ensuring all trajectory points are located within the candidate region; dividing the candidate region into multiple grids; using information from the trajectory points within each grid, expanding the candidate grid set containing the specified grid to obtain a target grid set; and determining the site location based on the target grid set. Through this process, the determination and judgment of the site location can be achieved simply by referring to the relevant information of the acquired trajectory points.

Description

Technical Field

[0001] This application relates to the field of intelligent transportation technology, and in particular to a method, judgment method, device and electronic equipment for determining station location. Background Technology

[0002] Public transportation is a common way to travel in the green way. Users often check information such as bus stops and routes on electronic maps when they travel, so it is very important to keep the location of bus stops on electronic maps accurate.

[0003] The related technologies involve clustering user trajectory points near a site. However, clustering methods are highly sensitive to parameters, requiring the specification of trajectory point density and cluster radius. The density of trajectory points around different sites varies greatly, making it difficult to determine a suitable, universal density and cluster radius. This results in high complexity and low accuracy in determining the accuracy of site identification based on user trajectories. Summary of the Invention

[0004] This application provides a method, judgment method, device, electronic device and storage medium for determining the location of a station. The determination and judgment of the location of a station can be achieved by using the relevant information of the obtained trajectory points.

[0005] In a first aspect, embodiments of this application provide a method for determining a site location, which may include:

[0006] Based on the obtained trajectory points, candidate regions are determined; all trajectory points are located within the candidate regions.

[0007] The candidate region is divided into multiple grids.

[0008] By using the information of trajectory points within the grid, the candidate grid set containing the specified grid is expanded to obtain the target grid set;

[0009] The location of the site is determined based on the target grid set.

[0010] Secondly, embodiments of this application provide a method for determining a site location, which may include:

[0011] The location of the site is determined using the method corresponding to the first aspect.

[0012] By utilizing the location of the site, the accuracy of the existing site location is determined, and the determination result is obtained.

[0013] Thirdly, embodiments of this application provide a device for determining a site location, which may include:

[0014] The candidate region determination module is used to determine candidate regions based on the acquired trajectory points; all trajectory points are located within the candidate regions.

[0015] The grid generation module is used to divide the candidate region into multiple grids;

[0016] The target grid set determination module is used to expand the candidate grid set containing the specified grid by utilizing the information of trajectory points within the grid, thereby obtaining the target grid set;

[0017] The site location determination module is used to determine the location of a site based on a target grid set.

[0018] Fourthly, embodiments of this application provide a device for determining the location of a site, which may include:

[0019] The site location determination module is used to determine the location of the site; the location of the site is determined using the method corresponding to the first embodiment.

[0020] The accuracy assessment module is used to assess the accuracy of existing site locations using the site's location information and obtain the assessment result.

[0021] Fifthly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor implements any of the methods described above when executing the computer program.

[0022] Sixthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements any of the methods described above.

[0023] Compared with the prior art, this application has the following advantages:

[0024] Determining stations can be achieved by referring only to information from trajectory points, requiring only a few parameters. Furthermore, since this information is determined based on trajectory points, which are often dynamic—meaning the trajectory points near each station to be determined are different—the above embodiment can determine stations based on dynamic data, improving accuracy while simplifying complexity.

[0025] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application, it can be implemented according to the contents of the specification. In order to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0026] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the various drawings denote the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings depict only some embodiments according to this application and should not be construed as limiting the scope of this application.

[0027] Figure 1 A schematic diagram illustrating the scenario of determining the site location provided in this application;

[0028] Figure 2 This is a flowchart illustrating a method for determining a site location according to an embodiment of this application;

[0029] Figure 3 This is one of the schematic diagrams illustrating the expansion of a mesh according to an embodiment of this application;

[0030] Figure 4 This is a second schematic diagram illustrating the expansion of a mesh according to an embodiment of this application;

[0031] Figure 5 This is a schematic diagram illustrating the scenario where the results of the determination by the relevant technical sites are presented.

[0032] Figure 6 This is a flowchart of a method for determining the location of a site according to an embodiment of this application;

[0033] Figure 7 This is a structural block diagram of a site location determination device according to an embodiment of this application;

[0034] Figure 8 This is a structural block diagram of a site location determination device according to an embodiment of this application; and

[0035] Figure 9 This is a block diagram of an electronic device used to implement embodiments of this application. Detailed Implementation

[0036] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the concept or scope of this application. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0037] To facilitate understanding of the technical solutions of the embodiments of this application, the relevant technologies of the embodiments of this application are described below. The following relevant technologies are optional solutions and can be combined with the technical solutions of the embodiments of this application in any way, and all of them fall within the protection scope of the embodiments of this application.

[0038] Figure 1This is a schematic diagram illustrating an application scenario for implementing the method of this application embodiment. When using navigation software, users typically input their navigation destination and then proceed to that destination according to the planned path displayed by the software. With user authorization, the user's trajectory points can be collected. The area near the navigation destination can be designated as a specific region, and the trajectory points of different users within that region can be used as a reference to determine unknown navigation destinations or correct known destinations. For example, the navigation destination can be a station or a specific location, such as the main entrance of a point of interest or a newsstand. In determining a station, the designated area can be divided into multiple grids, and a certain number of grids are selected for determining the station based on the density of trajectory points within each grid. Furthermore, the designated grids can be expanded based on the density of trajectory points within each grid. For example, the surrounding grids of the designated grid can also be selected as grids for determining the station. The expansion can be done by first determining the expansion direction, such as southeast, northeast, southwest, northwest, etc. By comparing the expansion directions, a suitable expansion direction is selected based on the density of trajectory points in each expansion direction. Figure 1 The diagram shows a schematic of the trajectory points in the expanded grid set, which is located within an approximately square with sides of about 0.05 kilometers. Ultimately, this can be expanded into a grid set composed of multiple grids. Based on the positions of the trajectory points contained within the grid set, the centroid, center, etc., of the grid set can be calculated. The calculation results can then be used as station locations to determine their positions.

[0039] The expansion direction is selected by utilizing the density of trajectory points, ensuring that the expansion direction is strongly correlated with the density of trajectory points within the grid. Furthermore, during the expansion process, the shape of the grid set must be approximately circular or square; that is, the shape of the expanded grid set is the same as or approximately the same as the shape of the original grid set. This avoids long tails in the grid set shape, resulting in more accurate station determinations. Based on this, the accuracy of existing station locations can be determined, and the locations of unknown stations can also be identified.

[0040] The acquisition of trajectory point data involved in this application is all data authorized by the user or fully authorized by all parties. The collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0041] This application provides a method for determining a site location, such as... Figure 2 The diagram shown is a flowchart of a method for determining the location of a site according to an embodiment of this application. Corresponding to the first embodiment, it may include:

[0042] Step S201: Determine the candidate region based on the obtained trajectory points; all trajectory points are located within the candidate region.

[0043] Track points can be obtained by collecting the location data of a user's smart device with the user's consent. For example, when a user uses a navigation application installed on their smart device and enters a navigation destination (such as a website), the user's track points are obtained through the location data of their smart device. Furthermore, the navigation destination can be associated with the obtained track points. For instance, a valid area can be defined with the navigation destination as the center and a specified distance as the radius. Then, only track points within the valid area can be counted.

[0044] For trajectory points within the valid region, the boundaries of candidate regions can be determined using extreme coordinates or clustering. For example, the coordinates of trajectory points within the valid region can be traversed to determine the extreme coordinates in the four cardinal directions (north, south, east, and west); the region enclosed by these extreme coordinates can then be considered a candidate region. Alternatively, the trajectory points within the valid region can be clustered, and the boundaries of candidate regions can be determined based on the clustering results.

[0045] Step S202: Divide the candidate region into grids to obtain multiple grids.

[0046] Since the candidate region may be a large area, it can be further divided into multiple grids. For example, the candidate region can be divided into multiple square grids. Generally, the candidate region is rectangular in shape. Therefore, one edge of the candidate region can be selected as a reference for grid division. For example, one edge of the candidate region can be divided into 10 equal segments, or 20 equal segments, etc. The specific number of segments can be adjusted according to the actual situation, and the specific value is not limited here.

[0047] Since candidate regions are typically rectangular, when generating meshes within them, the meshes at the edges tend to be rectangular rather than square. When this occurs, the size of the candidate region can be adjusted. For example, the candidate region can be expanded to change the shape of the meshes at its edges from rectangular to square. Alternatively, the candidate region can be shrunk to remove non-square meshes at its edges.

[0048] Step S203: Using the information of trajectory points within the grid, expand the candidate grid set containing the specified grid to obtain the target grid set.

[0049] For each grid cell, trajectory point information can be obtained based on the occurrence of trajectory points within the grid. This information can include the number of trajectory points, their location, etc. Based on the number of trajectory points and the grid size, the density of trajectory points in each grid cell can be determined. Based on the distribution of trajectory point locations, it can be determined whether the trajectory points in each grid cell are clustered or dispersed. Therefore, the number, density, location, and degree of clustering of trajectory points can all be used as trajectory point information. For example, several grid cells with high trajectory point density can be selected as designated grid cells, such as the top five grid cells with the highest trajectory point density. This designated grid cell can then be expanded to obtain a candidate grid cell set. This expansion can involve combining the candidate grid cells with a certain number of neighboring grid cells to form a grid set. For example, if there are five designated grid cells, expanding each of the five designated grid cells will yield five candidate grid cell sets. By comparing these five candidate grid cell sets, the target grid cell set can be selected. The comparison can be based on factors such as the density of trajectory points within the candidate grid cell set and the degree of clustering of trajectory points within the candidate grid cell set.

[0050] Step S204: Determine the location of the station based on the target grid set.

[0051] Based on the positions of the trajectory points contained in the grid set, the centroid, center, etc., of the grid set can be calculated, and the calculation result can be used as the station location. For example, the representative position of the target grid set can be determined by using the average position of trajectory points in the target grid set, or by using a weighted average position of trajectory points. This representative position is then determined as the station location. The above-described embodiments of this application can be used to judge the accuracy of existing station locations or to further correct them. For example, after determining the location corresponding to station A using the above method, if this location differs from the existing location corresponding to station A in navigation software or map software, the difference can be reported or corrected based on the location difference.

[0052] Through the above process, station determination can be achieved by referring only to trajectory point information, using only a few parameters. Furthermore, since this information is determined based on trajectory points, which are often dynamic—that is, the trajectory points near each station to be determined are different—the above embodiment can determine stations based on dynamic data, improving accuracy while simplifying complexity.

[0053] In one implementation, step S203, which involves expanding the grid set containing the specified grid using information about trajectory points within the grid to obtain the target grid set, may include:

[0054] Step S2031: Determine multiple candidate expansion directions for the candidate mesh set; the candidate mesh set includes the specified mesh, or multiple meshes obtained by expanding the specified mesh.

[0055] The candidate mesh set can be a single mesh or a set of multiple meshes. For example, if this is the first time the candidate mesh set has been determined, it can be a set of single meshes. That is, if this is the first time the candidate mesh set has been determined, it will only include the specified meshes. If this is not the first time the candidate mesh set has been determined, it may be a set of multiple meshes. The process of determining the candidate mesh set will be described in detail later. The candidate expansion direction can be the northwest, northeast, southeast, or southwest direction of the candidate mesh set.

[0056] Step S2032: Using the information of the trajectory points in the grid in the candidate expansion direction, determine the target expansion direction among multiple candidate expansion directions.

[0057] Combination Figure 3 As shown, exemplarily, Figure 3 Grid 34 in the table can be used as the designated grid, that is, the initial candidate grid set. The determination method can be to sort the trajectory points within each grid in the candidate region from highest to lowest density, thereby selecting a certain number of grids at the top of the sorted list as the designated grids. As mentioned earlier, during the initial expansion, the candidate grid set can be a set consisting of a single grid. That is, during the initial expansion, the candidate grid set includes only one designated grid.

[0058] Taking a candidate grid set consisting of a single grid as an example, the expansion process is illustrated. Expanding northwest yields a first grid set composed of grids 23, 24, 33, and 34. Expanding northeast yields a second grid set composed of grids 24, 25, 34, and 35. Expanding southeast yields a third grid set composed of grids 34, 35, 44, and 45. Expanding southwest yields a fourth grid set composed of grids 33, 34, 43, and 44.

[0059] After expansion, the target expansion direction can be determined by comparing the information of trajectory points in the candidate mesh sets obtained after expansion along each candidate direction. For example, the target expansion direction can be determined by comparing the density of trajectory points in the candidate mesh sets. Alternatively, the target expansion direction can be determined by comparing the degree of aggregation or dispersion of trajectory points in the candidate mesh sets.

[0060] Step S2033: Expand the candidate mesh set along the target expansion direction to obtain the target mesh set.

[0061] After expanding the candidate mesh along the target expansion direction, the target mesh set can be obtained.

[0062] In one implementation, the information of trajectory points within the grid includes the density of trajectory points within the grid. In this case, step S2032, which involves using the information of trajectory points within the grid along candidate expansion directions to determine the target expansion direction from multiple candidate expansion directions, may specifically include:

[0063] Compare the density of trajectory points within the grid along the candidate expansion direction, and determine the candidate expansion direction corresponding to the grid with the highest density of trajectory points as the target expansion direction.

[0064] By comparing the density of trajectory points in each candidate grid set, the scalability of each candidate expansion direction can be determined, thereby identifying the target expansion direction. Figure 3 For example, after expanding along each candidate expansion direction, four candidate mesh sets are obtained. Since each candidate mesh set contains a corresponding specified mesh 34, the density in each candidate mesh set is determined by the density of trajectory points within the meshes along the candidate expansion direction. For example, if the corresponding Figure 3 As the trajectory extends from the center to the northwest, the density of trajectory points in grids 23, 24, and 33 can be statistically analyzed and represented as ρ. 西北 Similarly, if the corresponding Figure 3 As the trajectory extends from the center to the northeast, the density of trajectory points in grids 24, 25, and 35 can be statistically analyzed and represented as ρ. 东北 Correspondingly, we can also obtain the density of trajectory points if the trajectory extends southwest and southeast, respectively, denoted as ρ. 西南 ρ 东南 Finally, by comparing ρ 西南 ρ 东南 ρ 西北 ρ 东北 The size of the grid is used to select the candidate expansion direction with the highest trajectory point density. Therefore, the candidate expansion direction corresponding to the grid with the highest trajectory point density is determined as the target expansion direction. That is, corresponding to... Figure 3 In the example shown, the density of trajectory points in grids 35, 44, and 45 is the highest, so the southeast direction is determined as the target expansion direction.

[0065] In one implementation, expanding the candidate mesh set along the target expansion direction may specifically include:

[0066] The candidate mesh set is combined with a specified number of meshes in the target expansion direction to form the target mesh set, and the difference between the shape of the target mesh set and the shape of the candidate mesh set is within a specified range.

[0067] As mentioned above Figure 3 For example, if the target expansion direction is determined to be southeast, the candidate grid set consisting of a single specified grid 34 can be expanded southeastward to obtain an expanded grid set consisting of grids 34, 35, 44, and 45. Each expansion can determine the specified number of grids in the expansion direction based on the number of grids in the current grid set. For example, if the current grid set contains 1 grid, the specified number could be 3. That is, expanding from a single grid to a grid set consisting of 4 grids. The above example can be translated to expanding from grid 34 southeastward to obtain a grid set consisting of grids 34, 35, 44, and 45. Thus, the grid set consisting of a single grid, which is a square before expansion, becomes a grid set consisting of 4 squares after expansion; the grid set itself remains a square.

[0068] For example, if the current candidate mesh set already consists of 4 meshes, then the specified quantity can be 5. That is, the candidate mesh set of 4 meshes is expanded to a mesh set of 9 meshes. Combined with... Figure 4 As shown, if the current candidate grid set is composed of grids 34, 35, 44, and 45, the expansion can be performed following the steps described above. For example, expanding northwest results in a fifth grid set consisting of grids 23 to 25, 33 to 35, and 43 to 45. Expanding northeast results in a sixth grid set consisting of grids 24 to 26, 34 to 36, and 44 to 46. Expanding southeast results in a seventh grid set consisting of grids 34 to 36, 44 to 46, and 54 to 56. Expanding southwest results in an eighth grid set consisting of grids 33 to 35, 43 to 45, and 53 to 55. Finally, the target expansion direction is determined using the information of the trajectory points within the grids along the candidate expansion direction. Thus, the grid set consisting of four grids is square before expansion. After expansion, it becomes a grid set consisting of 9 squares, and the grid set itself remains square. (Corresponding...) Figure 4 In the example above, the target expansion direction determined during the second expansion is still southeast. The candidate grid set consisting of 4 grids is expanded southeastward to obtain a grid set consisting of 9 grids.

[0069] For example, if the current candidate mesh set is already a mesh set consisting of 9 meshes, then the specified number can be 7. That is, the mesh set consisting of 9 meshes is expanded to a mesh set consisting of 16 meshes. The specific expansion process is the same as described above and will not be detailed further.

[0070] In the current implementation, the example is described where the shape of the expanded target mesh set is the same as the shape of the candidate mesh set before expansion. In actual expansion, expansion can also be performed based on shape similarity. For example, a similarity threshold can be set to ensure that the similarity between the expanded shape and the original shape is not lower than this threshold. For instance, the original candidate mesh set might be a square. If the expanded target mesh set is a rectangle, the difference between the long and short sides of the rectangle must be within a specified range to ensure that the similarity between the rectangle and the square is not lower than the similarity threshold. The specific values ​​for the specified difference range of the long and short sides, the similarity threshold, etc., can be set according to the actual scenario; this application does not limit the specific values.

[0071] Furthermore, considering the possibility of multiple candidate mesh sets, each candidate mesh set can be expanded into a corresponding target mesh set. Therefore, by comparing the density of trajectory points in multiple target mesh sets, the target mesh set with the highest density can be selected as the final result. It's easy to understand that if there are overlapping areas among multiple target mesh sets, the overlapping areas need to be included in the calculation multiple times when comparing the density of trajectory points. For example, if the first target mesh set contains mesh 34, and the second target mesh set also contains mesh 34, then when calculating the density, mesh 34 needs to participate in the calculation of the density of trajectory points in both the first and second target mesh sets.

[0072] In one implementation, after expanding the candidate mesh set along the target expansion direction, it may further include:

[0073] If at least one of the following conditions is met: the position of the grid in the candidate region in the direction to be expanded, the information of the trajectory points within the grid in the direction to be expanded, and the already expanded distance, then the expansion stops.

[0074] For example, a specified condition could be whether the expansion has reached the boundary of the candidate region. That is, if the boundary of the candidate region has been reached after the current expansion, then it can be determined to stop the expansion.

[0075] For example, the specified condition could be whether the number of trajectory points in the grid along the expansion direction of the target to be detected is low or whether the density of trajectory points is low. That is, if after the current expansion, the number of trajectory points in the grid along the expansion direction of the target to be detected is lower than the corresponding number threshold, or the density of trajectory points is lower than the corresponding density threshold, it can be determined to stop the expansion.

[0076] For example, the specified condition could be whether the extended distance is long enough. That is, if after the current extension, the distance between the grid in the target extension direction and the original grid has reached or exceeded a predetermined extension distance threshold, it can be determined to stop the extension.

[0077] Conversely, if the current expansion does not reach the boundary of the subsequent region, and the number of trajectory points within the grid in the target expansion direction is not less than the corresponding quantity threshold or not less than the corresponding density threshold, and the expansion distance threshold has not been reached, then expansion can continue. The method for continuing expansion is the same as the aforementioned steps, and will not be repeated here.

[0078] In one implementation, the step S204 involving determining the location of the station based on the target grid set may include:

[0079] Step S2041: Determine the representative position of the target grid set by using the positions of the trajectory points within the target grid set; the positions of the trajectory points are obtained by using the positions of the trajectory points within the grid in the trajectory point information.

[0080] The representative location of the target grid can be either the average coordinates of the trajectory points within the target grid, or a weighted average coordinate of the trajectory points within the target grid. The weighted average coordinate can be determined by assigning weights to the trajectory points based on their position within the target grid. For example, the center point of the target grid can be determined first, and the weight of each trajectory point can be set based on its distance from the center point. The weight can be inversely proportional to the distance from the center point; that is, the smaller the distance, the greater the weight. Alternatively, the weights can be determined according to the distribution of the trajectory points: in areas where the trajectory points are relatively densely distributed, the weights are higher; in areas where the trajectory points are relatively sparsely distributed, the weights are lower.

[0081] Step S2042: Determine the representative location of the target grid set as the site location.

[0082] Once the representative location of the target grid is determined, this location can be designated as the station location. Therefore, the station location can be determined based on the trajectory points. Generally, the area with the highest density of trajectory points is often the final destination chosen by most users. Based on this, the determined station location can be more closely approximated to the actual situation.

[0083] Figure 6This is a flowchart of a method for determining a site location according to another embodiment of this application. Corresponding to the second embodiment, it may include:

[0084] Step S601: Determine the location of the site; the location of the site is determined using the method corresponding to the first embodiment.

[0085] The location of a station can be determined based on the method for determining the location of a station involved in the first embodiment. The location of a station can be represented by the coordinates of the station on a map.

[0086] Step S602: Use the location of the site to determine the accuracy of the existing site location and obtain the determination result.

[0087] The existing station location can be a location already present in map or navigation software. The existing station and the previously determined station are the same station in the real world. The corresponding existing station location can be represented as the station's coordinates on a map. Based on this, the accuracy of the existing station location can be judged by comparing the determined location with the existing location, thus obtaining a judgment result.

[0088] For example, a location difference threshold can be set. If the difference between the determined location and an existing location exceeds the location difference threshold, it can be interpreted as the existing site location being inaccurate.

[0089] Furthermore, the results of the assessment can be used to calibrate the locations of existing stations. For example, if the location of an existing station is inaccurate, it can be adjusted based on the determined location, thereby achieving calibration of the existing station location.

[0090] Corresponding to the application scenarios and methods provided in the embodiments of this application, the embodiments of this application also provide a site determination device. For example... Figure 7 The diagram shown is a structural block diagram of a site determination device according to an embodiment of this application. The site determination device may include:

[0091] The candidate region determination module 701 is used to determine the candidate region based on the acquired trajectory points; all trajectory points are located within the candidate region.

[0092] The grid division module 702 is used to divide the candidate region into multiple grids.

[0093] The target grid set determination module 703 is used to expand the candidate grid set containing the specified grid by utilizing the information of trajectory points within the grid to obtain the target grid set;

[0094] The site location determination module 704 is used to determine the location of the site based on the target grid set.

[0095] In one implementation, the target mesh set determination module 703 may include:

[0096] The candidate expansion direction determination submodule is used to determine multiple candidate expansion directions for a candidate mesh set; the candidate mesh set includes a specified mesh, or includes multiple meshes obtained by expanding a specified mesh;

[0097] The target expansion direction determination submodule is used to determine the target expansion direction from multiple candidate expansion directions by utilizing the information of trajectory points in the grid on the candidate expansion directions.

[0098] The extended execution submodule is used to expand the candidate mesh set along the target expansion direction to obtain the target mesh set.

[0099] In one implementation, the information of trajectory points within the grid includes the density of trajectory points within the grid. Based on this, the target expansion direction determination submodule can specifically be used for:

[0100] Compare the density of trajectory points within the grid along the candidate expansion direction, and determine the candidate expansion direction corresponding to the grid with the highest density of trajectory points as the target expansion direction.

[0101] In one implementation, the extended execution submodule can be specifically used to: combine the candidate mesh set with a specified number of meshes in the target extension direction to form a target mesh set, wherein the difference between the shape of the target mesh set and the shape of the candidate mesh set is within a specified range.

[0102] In one embodiment, it may further include a determination module, which may be used to: stop expansion if at least one of the following conditions is met: the position of the grid in the candidate region in the direction to be expanded, the information of the trajectory points in the grid in the direction to be expanded, and the expanded distance.

[0103] In one implementation, the site location determination module 704 may include:

[0104] The representative position determination unit is used to determine the representative position of the target grid set by utilizing the positions of trajectory points within the target grid set; the positions of the trajectory points are obtained from the positions of the trajectory points within the grid in the trajectory point information.

[0105] The site determination unit is used to determine the representative location of the target grid set as the site location.

[0106] Corresponding to the application scenarios and methods provided in the embodiments of this application, the embodiments of this application also provide a device for determining the location of a site. For example... Figure 8 The diagram shown is a structural block diagram of a site location determination device according to an embodiment of this application. The site location determination device may include:

[0107] The site location determination module 801 is used to determine the location of the site; the location of the site is determined using the method corresponding to the first embodiment.

[0108] The accuracy judgment module 802 is used to judge the accuracy of the location of an existing site by using the location of the site, and obtain the judgment result.

[0109] The functions of each module in each device in the embodiments of this application can be found in the corresponding description in the above method, and they have corresponding beneficial effects, which will not be repeated here.

[0110] Figure 9 This is a block diagram of an electronic device used to implement embodiments of this application. For example... Figure 9 As shown, the electronic device includes a memory 910 and a processor 920. The memory 910 stores a computer program that can run on the processor 920. When the processor 920 executes the computer program, it implements the method described in the above embodiments. The number of memories 910 and processors 920 can be one or more.

[0111] The electronic device also includes:

[0112] The communication interface 930 is used to communicate with external devices and exchange and transmit data.

[0113] If the memory 910, processor 920, and communication interface 930 are implemented independently, they can be interconnected via a bus to communicate with each other. This bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 9 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0114] Optionally, in a specific implementation, if the memory 910, processor 920, and communication interface 930 are integrated on a single chip, then the memory 910, processor 920, and communication interface 930 can communicate with each other through an internal interface.

[0115] This application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method provided in this application.

[0116] This application also provides a chip including a processor for calling and executing instructions stored in a memory, causing a communication device with the chip installed to perform the method provided in this application.

[0117] This application also provides a chip, including: an input interface, an output interface, a processor, and a memory. The input interface, output interface, processor, and memory are connected through an internal connection path. The processor is used to execute code in the memory. When the code is executed, the processor is used to execute the method provided in the application embodiment.

[0118] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. General-purpose processors can be microprocessors or any conventional processor. It is worth noting that the processor can be a processor supporting Advanced Reduced Instruction Set Machines (ARM) architecture.

[0119] Further, optionally, the aforementioned memory may include read-only memory and random access memory. The memory may be volatile memory or non-volatile memory, or may include both. Non-volatile memory may include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may include random access memory (RAM), which serves as an external cache. By way of example, but not limitation, many forms of RAM are available. Examples include Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DR RAM).

[0120] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions according to this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another.

[0121] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0122] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0123] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process. Furthermore, the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functionality involved.

[0124] The logic and / or steps described in the flowchart or otherwise herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus or device (such as a computer-based system, a processor-included system or other system that can fetch and execute instructions from, an instruction execution system, apparatus or device).

[0125] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. All or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware, the program being stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiments.

[0126] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. This storage medium can be a read-only memory, a disk, or an optical disk, etc.

[0127] The above are merely exemplary embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various variations or substitutions within the technical scope described in this application, and these should all be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for determining the location of a station, characterized in that, include: Based on the obtained trajectory points, determine the candidate region; All trajectory points are located within the candidate region; The candidate region is divided into multiple grids. Determine multiple candidate expansion directions for the candidate mesh set; Using the information of the trajectory points within the grid along the candidate expansion directions, the target expansion direction is determined from the plurality of candidate expansion directions; The candidate mesh set containing the specified mesh is expanded along the target expansion direction to obtain the target mesh set; wherein, the candidate mesh set includes the specified mesh, or includes multiple meshes obtained by expanding the specified mesh; The location of the station is determined based on the target grid set.

2. The method according to claim 1, characterized in that, The information of the trajectory points within the grid includes the density of the trajectory points within the grid. The step of determining the target expansion direction from the plurality of candidate expansion directions using the information of the trajectory points within the grid along the candidate expansion directions includes: Compare the density of trajectory points within the grid along the candidate expansion direction, and determine the candidate expansion direction corresponding to the grid with the highest density of trajectory points as the target expansion direction.

3. The method according to claim 1, characterized in that, Expanding the candidate mesh set along the target expansion direction includes: The candidate mesh set is combined with a specified number of meshes in the target expansion direction to form a target mesh set, wherein the shape of the target mesh set differs from the shape of the candidate mesh set within a specified range.

4. The method according to claim 1, characterized in that, After expanding the candidate mesh set along the target expansion direction, the method further includes: If at least one of the following conditions is met: the position of the grid in the candidate region along the direction to be expanded, the information of the trajectory points within the grid along the direction to be expanded, and the already expanded distance, then the expansion is stopped.

5. The method according to claim 1, characterized in that, Determining the location of a station based on the target grid set includes: The representative position of the target grid set is determined by using the positions of the trajectory points within the target grid set; the positions of the trajectory points are obtained from the positions of the trajectory points within the grid in the trajectory point information. The representative location of the target grid set is determined as the site location.

6. A method for determining the location of a station, characterized in that, include: Determine the location of the target site; The location of the target site is determined using any one of claims 1 to 5; Using the location of the target site, the accuracy of the existing location of the target site is judged, and a judgment result is obtained.

7. A device for determining the location of a station, characterized in that, include: The candidate region determination module is used to determine candidate regions based on the acquired trajectory points; All trajectory points are located within the candidate region; The grid division module is used to divide the candidate region into multiple grids. A target mesh set determination module is used to determine multiple candidate expansion directions of a candidate mesh set; using information about trajectory points within the meshes along the candidate expansion directions, a target expansion direction is determined from the multiple candidate expansion directions; the candidate mesh set containing the specified mesh is expanded along the target expansion direction to obtain a target mesh set; wherein, the candidate mesh set includes the specified mesh, or includes multiple meshes obtained by expanding the specified mesh; A site location determination module is used to determine the location of a site within the target grid set.

8. A device for determining the location of a station, characterized in that, include: A site location determination module is used to determine the location of a site; the location of the site is determined using any one of claims 1 to 5; The judgment module is used to judge the accuracy of the location of the existing site using the location of the site, and obtain the judgment result.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory, wherein the processor, when executing the computer program, implements the method of any one of claims 1-6.

10. A computer-readable storage medium storing a computer program that, when executed by a processor, implements the method of any one of claims 1-6.

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