A vehicle distribution display method, a storage medium and an electronic device

Abstract

A vehicle distribution display method, a storage medium and an electronic device, the present application relates to the technical field of Internet of Vehicles, solve the problem of low data security and timeliness of the prior art, the present application can be applied to Internet of Vehicles big data analysis business.The display method comprises the following steps: S1, the cloud accesses the vehicle GPS signal, and divides the vehicle into the grid table of the corresponding dimension;S2, the Web end displays the vehicle distribution, then the user selects the vehicle range is transmitted to the cloud;S3, the cloud is filtered according to the vehicle range The grid that meets the condition, draws the grid layer and extracts the boundary point position information, returns to the Web end;S4, the Web end obtains the corresponding range map from the third party map merchant according to the boundary point position information, and the map and the grid layer are fused according to the point position information and are displayed.The present application also provides a storage medium and an electronic device for realizing the above-mentioned vehicle distribution display method.

Description

Technical Field

[0001] This invention relates to the field of vehicle networking technology, specifically to a vehicle distribution display technology. Background Technology

[0002] In current vehicle-to-everything (V2X) operation and management systems, since car manufacturers generally lack map provider qualifications, when vehicle location display is required, the car manufacturer transmits the vehicle coordinate data to a third-party map provider (such as AutoNavi or Baidu Maps), which then implements the mapping. A flowchart illustrating this method is provided below. Figure 1 In summary, this involves sending a large amount of vehicle GPS data to a third-party map provider, who then processes the data and returns it back.

[0003] However, the above implementation method has the following problems:

[0004] 1. In terms of data security, car manufacturers produce a large number of vehicles, and the coordinate data of hundreds of thousands of vehicles is transmitted to third-party mapping providers, which poses a risk of data leakage;

[0005] 2. In terms of performance, the coordinate data of hundreds of thousands of vehicles needs to be retrieved from the server's data storage and then transmitted to the third-party map provider. After the third-party map provider calculates the data, the results are finally returned to the query terminal for display. This not only places high demands on the server's storage and retrieval performance, but also on the network, bandwidth, and terminal interface loading performance. The whole process consumes a lot of resources and can easily affect other services. In addition, the long link is time-consuming.

[0006] 3. Timeliness: Since vehicles are always in motion, if the distribution of all vehicles is to be displayed on the interface in real time, it means that the data of hundreds of thousands of vehicles needs to be transmitted to the third-party map provider regularly. The higher the timeliness requirement, the higher the transmission frequency. It is possible that the previous batch of data has not been processed before the next batch of data needs to be processed. There is a large time delay between the data calculated by the map provider and the current real data of the vehicles.

[0007] 4. Limitations on API calls from map providers: To avoid network attacks, third-party map providers often limit the number of times they can access their provided APIs. The number of requests from the same IP address is limited within a day, which is difficult to meet the needs of car manufacturers. Summary of the Invention

[0008] To address the aforementioned problems in existing technologies, this invention proposes a method for displaying vehicle distribution.

[0009] The technical solution of this invention is as follows:

[0010] A method for displaying vehicle distribution includes the following steps:

[0011] S1. Access vehicle GPS signals via the cloud and classify vehicles into grid tables of corresponding dimensions;

[0012] S2 displays the vehicle distribution on the web interface, and then transmits the vehicle range selected by the user to the cloud.

[0013] S3. The cloud filters grids that meet the conditions based on the vehicle range, draws a grid layer and extracts boundary point information, and returns it to the web client.

[0014] S4. The web client obtains the map of the corresponding range from the third-party map provider based on the boundary point information, and merges and displays the map with the grid layer according to the point information.

[0015] Preferably, the cloud includes a vehicle condition analysis service module, a big data real-time calculation module, a grid data service module, a vehicle location service module, and an image generator; the vehicle condition analysis service module is used to acquire vehicle GPS signals, transmit them to the big data real-time calculation module for processing to obtain grid data and store them in the grid data service module; the vehicle location service module is used to transmit the grid data and the grid layer generated by the image generator to the web terminal.

[0016] Preferably, the grid data obtained by the big data real-time computing module includes the vehicle distribution in the grid and the vehicle count in the grid. It calculates the grid where the vehicle is located based on the reported GPS signal, queries the grid where the vehicle was previously located, and updates the grid where the vehicle is located if the grid changes. It also updates the vehicle count in the previous grid and the new grid simultaneously to obtain real-time grid data.

[0017] Preferably, the web client includes a layer linkage control and display module, a vehicle distribution data query module, and a map plugin module. The vehicle distribution data query module is used to receive the grid layer transmitted from the cloud. The map plugin module is used to obtain map information provided by a third-party map provider. The layer linkage control and display module is used to integrate and display the map information and the grid layer according to point information.

[0018] Preferably, the grid table includes 360*180 cells divided by latitude and longitude, and each cell is named according to "latitude_longitude" to record the number of vehicles in each cell, where 180° east longitude is recorded as E179; 180° west longitude is recorded as W179; 90° south latitude is recorded as S89; and 90° north latitude is recorded as N89.

[0019] Preferably, the web interface is displayed as a rectangle, and the four corners of the rectangle are respectively N89_E179, N89_W179, S89_E179 and S89_W179 by default.

[0020] Preferably, step S2 further includes:

[0021] S21. When the web interface is initialized, all grid vehicles are retrieved by default, and the search criteria are sent to the cloud.

[0022] S22. The cloud retrieves the grid according to the retrieval request, obtains the grid count, and draws the grid image based on the grid count and the relative position of the grid.

[0023] S23. The cloud extracts the center point coordinates of the four corner grids of the rectangle and returns the grid image and the center point coordinates of the four corners to the web client.

[0024] S24. The web client obtains map information from a third-party map provider using the coordinates of the four corner center points, and integrates the map with the grid image using the points corresponding to the four corner center points in the map to form a complete vehicle distribution map.

[0025] S25. When a web user selects a vehicle range, the size of the grid image is adjusted, and the information of the four corners of the adjusted grid image is selected and sent to the cloud.

[0026] The present invention also provides a computer-readable storage medium for storing a computer program that executes the vehicle distribution display method described above.

[0027] The present invention also provides an electronic device, including a processor and a memory, wherein the processor and the memory communicate with each other through a communication bus; the memory is used to store computer programs; and the processor is used to execute the computer programs stored in the memory to implement the vehicle distribution display method described above.

[0028] Compared with the prior art, the specific beneficial effects of the present invention are as follows:

[0029] 1. This invention provides real-time vehicle location services within the cloud-based vehicle manufacturing platform of a car manufacturer through big data computing technology, which offers significant improvements in data security, performance, real-time performance, and access restrictions compared to existing third-party map provider solutions.

[0030] 2. This invention divides vehicles into pre-defined grids based on GPS latitude and longitude using real-time calculations. The corresponding grids are extracted based on vehicle selection on the web page, with the center coordinates of the edge grids as the representative. Vehicle data does not need to be transmitted to third-party map providers; only map information is obtained from them. Vehicle location updates and map display are processed separately and do not interfere with each other. This significantly reduces the amount of data requests, greatly improves efficiency, and meets the needs of car manufacturers. Attached Figure Description

[0031] Figure 1This is a flowchart illustrating existing vehicle distribution display methods in the background technology;

[0032] Figure 2 A flowchart illustrating the vehicle distribution display method provided by the present invention;

[0033] Figure 3 This is a schematic diagram illustrating the process of merging and displaying a grid layer with a map on the web interface as described in Example 1.

[0034] Figure 4 This is a schematic diagram of the workflow of the real-time big data computing module described in Example 3;

[0035] Figure 5 This is a schematic diagram of the method described in Example 7. Detailed Implementation

[0036] To make the technical solutions of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. It should be noted that the following embodiments are only used to better understand the technical solutions of the present invention and should not be construed as limiting the present invention.

[0037] Example 1.

[0038] This embodiment provides a method for displaying vehicle distribution. A flowchart of the method can be found here. Figure 2 Specifically, it includes the following steps:

[0039] S1. Access vehicle GPS signals via the cloud and classify vehicles into grid tables of corresponding dimensions;

[0040] S2 displays the vehicle distribution on the web interface, and then transmits the vehicle range selected by the user to the cloud.

[0041] S3. The cloud filters grids that meet the conditions based on the vehicle range, draws a grid layer and extracts boundary point information, and returns it to the web client.

[0042] S4. The web client obtains the map of the corresponding range from the third-party map provider based on the boundary point information, and merges and displays the map with the grid layer according to the point information.

[0043] This embodiment divides vehicles into pre-defined grids through real-time calculation. The corresponding grids are extracted based on vehicle selection on the web page, using boundary point information as a representative. Vehicle data does not need to be transmitted to third-party map providers; only map information is obtained from them. A schematic diagram illustrating the process of merging the grid layer with the map on the web interface is shown below. Figure 3 As can be seen, vehicle location updates and map display are processed separately and do not interfere with each other. Therefore, the amount of data requests can be greatly reduced, the timeliness can be greatly improved, and the needs of car manufacturers can be met.

[0044] Example 2.

[0045] This embodiment is a further example of Embodiment 1. The cloud includes a vehicle condition analysis service module, a big data real-time calculation module, a grid data service module, a vehicle location service module, and an image generator. The vehicle condition analysis service module is used to acquire vehicle GPS signals, transmit them to the big data real-time calculation module for processing to obtain grid data, and store them in the grid data service module. The vehicle location service module is used to transmit the grid data and the grid layer generated by the image generator to the Web terminal.

[0046] This embodiment provides real-time vehicle location services within the cloud of the vehicle manufacturer's vehicle networking platform through big data computing technology, which can significantly improve data security, performance, real-time performance, and access restrictions compared to existing third-party map provider solutions.

[0047] Example 3.

[0048] This embodiment is a further example of embodiment 2. The grid data obtained by the big data real-time computing module includes the distribution of vehicles in the grid and the vehicle count in the grid. It calculates the grid where the vehicle is located based on the reported GPS signal, and queries the grid where the vehicle was previously located. If the grid changes, it updates the grid where the vehicle is located and synchronously updates the vehicle count in the previous grid and the new grid to obtain real-time grid data.

[0049] This invention uses a big data real-time computing module to divide vehicles into grids pre-defined according to business needs based on GPS latitude and longitude, realizing real-time updates of vehicle location and corresponding grids, and providing a foundation for subsequent fusion with corresponding map information.

[0050] Example 4.

[0051] This embodiment is a further example of embodiment 1. The web terminal includes a layer linkage control and display module, a vehicle distribution data query module, and a map plugin module. The vehicle distribution data query module is used to receive the grid layer transmitted from the cloud. The map plugin module is used to obtain map information provided by a third-party map provider. The layer linkage control and display module is used to merge and display the map information and the grid layer according to the point information.

[0052] Example 5.

[0053] This embodiment is a further example of Embodiment 1. The grid table includes 360*180 cells divided by latitude and longitude, and each cell is named according to "latitude_longitude". The number of vehicles in each cell is recorded, where 180° east longitude is recorded as E179; 180° west longitude is recorded as W179; 90° south latitude is recorded as S89; and 90° north latitude is recorded as N89.

[0054] This embodiment divides geographical locations according to latitude and longitude, which can obtain cells for all locations. The division method is reasonable and reliable, providing users with comprehensive and accurate information.

[0055] Example 6.

[0056] This embodiment is a further example of embodiment 1. The web interface is displayed as a rectangle, and the four corners of the rectangle are N89_E179, N89_W179, S89_E179 and S89_W179 by default.

[0057] This embodiment is the initial setup for the web interface display, which can display all vehicles in the grid for easy selection.

[0058] Example 7.

[0059] This embodiment is a further illustrative example of Embodiment 1, and step S2 further includes:

[0060] S21. When the web interface is initialized, all grid vehicles are retrieved by default, and the search criteria are sent to the cloud.

[0061] S22. The cloud retrieves the grid according to the retrieval request, obtains the grid count, and draws the grid image based on the grid count and the relative position of the grid.

[0062] S23. The cloud extracts the center point coordinates of the four corner grids of the rectangle and returns the grid image and the center point coordinates of the four corners to the web client.

[0063] S24. The web client obtains map information from a third-party map provider using the coordinates of the four corner center points, and integrates the map with the grid image using the points corresponding to the four corner center points in the map to form a complete vehicle distribution map.

[0064] S25. When a web user selects a vehicle range, the size of the grid image is adjusted, and the information of the four corners of the adjusted grid image is selected and sent to the cloud.

[0065] Example 8.

[0066] A computer-readable storage medium for storing a computer program that executes the vehicle distribution display method as described in any one of Examples 1-7.

[0067] Example 9.

[0068] An electronic device includes a processor and a memory, wherein the processor and the memory communicate with each other via a communication bus; the memory is used to store computer programs; and the processor, when executing the computer programs stored in the memory, implements the vehicle distribution display method as described in any one of Embodiments 1-7.

Claims

1. A method of distributing a vehicle, characterized by, The method comprises the following steps: S1, the cloud accesses the vehicle GPS signal, and divides the vehicle into a grid table corresponding to the dimension; S2, the Web end displays the vehicle distribution, and then transmits the vehicle range selected by the user to the cloud; S3, the cloud filters the grid meeting the condition according to the vehicle range, draws a grid layer and extracts the boundary point information, and returns to the Web end; S4, the Web end obtains the map corresponding to the range from the third-party map provider according to the boundary point information, and fuses and displays the map and the grid layer according to the point information. The step S2 further comprises: S21, when the Web end interface is initialized, the default is to obtain all grid vehicles, and the search condition is sent to the cloud; S22, the cloud searches the grid according to the search request, obtains the grid count, and draws a grid picture according to the grid count and the relative position of the grid; S23, the cloud extracts the center point coordinates of the four corner grids respectively, and returns the grid picture and the four corner center point coordinates to the Web end; S24, the Web end obtains the map information from the third-party map provider by using the four corner center point coordinates, fuses and displays the map and the grid picture by using the point corresponding to the four corner center point in the map, and forms a complete vehicle distribution map; S25, when the Web end user selects the vehicle range, the size of the grid picture is adjusted, and the four corner information of the adjusted grid picture is selected and sent to the cloud; The cloud comprises a vehicle condition analysis service module, a big data real-time calculation module, a grid data service module, a vehicle position service module and a picture generator; the vehicle condition analysis service module is used for obtaining the vehicle GPS signal, transmitting to the big data real-time calculation module to obtain the grid data and storing to the grid data service module, and the vehicle position service module is used for transmitting the grid data and the grid layer generated by the picture generator to the Web end; The grid data obtained by the big data real-time calculation module comprises the vehicle distribution in the grid and the grid vehicle count, the vehicle position in the grid is calculated according to the reported GPS signal, the grid in which the vehicle is located before is inquired, if the grid changes, the vehicle position in the grid is updated, and the vehicle count of the previous grid and the new grid is synchronously updated, so as to obtain the real-time grid data; The Web end comprises a layer linkage control display module, a vehicle distribution data query module and a map plug-in module; the vehicle distribution data query module is used for receiving the grid layer transmitted by the cloud, the map plug-in module is used for obtaining the map information provided by the third-party map provider, and the layer linkage control display module is used for fusing and displaying the map information and the grid layer according to the point information.

2. The vehicle distribution presentation method according to claim 1, characterized by, The grid table comprises 360*180 unit cells divided according to the latitude and longitude, and each unit cell is named according to "latitude_longitude", and the vehicle number of each unit cell is recorded, wherein the east longitude 180° is counted into E179; the west longitude 180° is counted into W179; the south latitude 90° is counted into S89; and the north latitude 90° is counted into N89.

3. The vehicle distribution presentation method according to claim 1, characterized by, The web interface is displayed as a rectangle, and the four corners of the rectangle are respectively defaulted as N89_E179, N89_W179, S89_E179 and S89_W179.

4. A computer-readable storage medium, characterized in that, The computer readable storage medium is used to store a computer program, and the computer program executes the vehicle distribution display method according to any one of claims 1-3.

5. An electronic device, comprising: The computer readable storage medium is used to store a computer program, and the computer program executes the vehicle distribution display method according to any one of claims 1-3.

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