Vehicle navigation methods, systems, and vehicles

Abstract

This invention discloses a vehicle navigation method, system, and vehicle, relating to the field of vehicle navigation. The method includes: collecting first road condition data of the current road using a first vehicle, wherein the first vehicle is a vehicle on the current road used to provide interconnection functionality with any electronic device; uploading the first road condition data to a cloud server using the first vehicle, wherein the cloud server processes the first road condition data and second road condition data to obtain target road condition data, and then distributes the target road condition data to a second vehicle, which is any vehicle on the current road; and a third vehicle is any vehicle on the current road other than the first vehicle used to provide interconnection functionality with any electronic device. This invention solves the technical problem of untimely updates to navigation map data.

Description

Technical Field

[0001] This invention relates to the field of vehicle navigation, and more specifically, to a vehicle navigation method, system, and vehicle. Background Technology

[0002] Currently, in related technologies, navigation map software periodically obtains road change information from road management departments, creates incremental navigation maps based on this information, and updates them to the terminal software via the cloud. This method mainly relies on manual, periodic updates of navigation maps, which limits the information obtained and has a production cycle, making it difficult to reflect the latest road information in the navigation map in real time.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This invention provides a vehicle navigation method, system, and vehicle to at least solve the technical problem of untimely updates to navigation map data.

[0005] According to one aspect of the present invention, a vehicle navigation method is provided, comprising: collecting first road condition data of a current road using a first vehicle, wherein the first vehicle is a vehicle on the current road used to provide interconnection functionality with any electronic device; uploading the first road condition data to a cloud server using the first vehicle, wherein the cloud server is used to process the first road condition data and second road condition data to obtain target road condition data, and distributing the target road condition data to a second vehicle, wherein the second road condition data is road condition data of the current road collected by a third vehicle, the second vehicle is any vehicle on the current road, the second vehicle performs navigation based on the target road condition data, and the third vehicle is any vehicle on the current road other than the first vehicle used to provide interconnection functionality with any electronic device.

[0006] Optionally, uploading the first traffic data to the cloud server via the first vehicle includes: classifying the first traffic data using the navigation application of the first vehicle to obtain high-frequency map data and low-frequency map data, wherein the high-frequency map data is map data with a data change frequency greater than a first preset frequency, and the low-frequency map data is map data with a data change frequency less than a second preset frequency; uploading the high-frequency map data to the cloud server based on a first preset period; and uploading the low-frequency map data to the cloud server based on a second preset period.

[0007] Optionally, the cloud server is used to determine whether the first data in the first traffic data and the second data in the second traffic data are the same; in response to the first data and the second data being different, the first data in the first traffic data and the second data in the second traffic data are deleted to obtain the deleted first traffic data and the deleted second traffic data, and the target traffic data is obtained based on the deleted first traffic data and the deleted second traffic data, wherein the first data and the second data are respectively data in the first traffic data and the second traffic data used to represent the same location uploaded at the same time and having the same attributes.

[0008] Optionally, the cloud server is also used to determine whether it receives reported high-frequency map data of the current road within a first preset time. In response to the failure to receive newly reported high-frequency map data within the first preset time, it determines that the historically stored high-frequency map data is invalid, obtains a first invalid result, and updates the target road condition data based on the first invalid result.

[0009] Optionally, the cloud server is also used to determine whether it receives reported low-frequency map data of the current road within a second preset time. In response to the failure to receive newly reported low-frequency map data within the second preset time, it determines that the historically stored low-frequency map data is invalid, obtains a second invalid result, and updates the target road condition data based on the second invalid result.

[0010] Optionally, the method further includes: a cloud server receiving first traffic data uploaded by a first vehicle and second traffic data uploaded by a third vehicle, wherein the first traffic data is traffic data of the current road collected by the first vehicle, the second traffic data is traffic data of the current road collected by the third vehicle, the first vehicle is a vehicle on the current road used to provide interconnection with any electronic device, and the third vehicle is another vehicle on the current road other than the first vehicle used to provide interconnection with any electronic device; the cloud server performs data analysis on the first and second traffic data to obtain target traffic data; the cloud server sends the target traffic data to the second vehicle, wherein the second vehicle performs navigation based on the target traffic data.

[0011] Optionally, the cloud server processes the first traffic data and the second traffic data to obtain target traffic data, including: the cloud server determining whether the first data in the first traffic data and the second data in the second traffic data are the same; in response to the first data and the second data being different, the cloud server deleting the first data in the first traffic data and the second data in the second traffic data to obtain deleted first traffic data and deleted second traffic data; the cloud server processing the deleted first traffic data and deleted second traffic data to obtain target traffic data, wherein the first data and the second data are respectively data in the first traffic data and the second traffic data used to represent data uploaded at the same time and at the same location with the same attributes.

[0012] According to another aspect of the present invention, a vehicle navigation system is also provided, comprising: a first vehicle for collecting first road condition data of the current road, wherein the first vehicle is a vehicle on the current road used to provide interconnection functionality with any electronic device; a third vehicle for collecting second road condition data of the current road, wherein the third vehicle is another vehicle on the current road other than the first vehicle used to provide interconnection functionality with any electronic device; a cloud server for processing the first road condition data and the second road condition data to obtain target road condition data; a second vehicle for navigating based on the target road condition data, wherein the second vehicle is any vehicle on the current road; and a controller for controlling the first vehicle to upload the first road condition data to the cloud server and controlling the cloud server to send the target road condition data to the second vehicle.

[0013] Optionally, the controller is also used to control the navigation application of the first vehicle to classify the first road condition data to obtain high-frequency map data and low-frequency map data. The high-frequency map data is map data with a data change frequency greater than a first preset frequency, and the low-frequency map data is map data with a data change frequency less than a second preset frequency. The controller is also used to upload the high-frequency map data to the cloud server based on a first preset period and to upload the low-frequency map data to the cloud server based on a second preset period.

[0014] According to another aspect of the present invention, a vehicle is also provided, comprising: one or more processors; a storage device for storing one or more programs; and a vehicle navigation method wherein the one or more programs are executed by the one or more processors, causing the one or more processors to perform any of the above-described methods.

[0015] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is running, it controls the device where the computer-readable storage medium is located to execute the above-described information push method.

[0016] According to another aspect of the present invention, a processor is also provided, which is used to run a program, wherein the program executes the above-described information push method during runtime.

[0017] In this embodiment of the invention, a first vehicle collects first road condition data of the current road and uploads it to a cloud server. The cloud server processes the first and second road condition data to obtain target road condition data, which is then sent to a second vehicle. The second road condition data is the road condition data of the current road collected by a third vehicle. It is worth noting that the first vehicle is a vehicle on the current road that provides connectivity with any electronic device, the second vehicle is any vehicle on the current road that navigates based on the target road condition data, and the third vehicle is any other vehicle on the current road that provides connectivity with any electronic device. The cloud server comprehensively processes the road condition data collected by the first and third vehicles and sends it to the second vehicle. This achieves the goal of the cloud server being able to comprehensively process road condition data collected by any vehicle on the current road that provides connectivity with any electronic device and send it to any vehicle on the current road, thereby achieving the technical effect of timely updating navigation data on the current road and solving the technical problem of untimely updates to navigation map data. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0019] Figure 1 This is a flowchart of a vehicle navigation method according to an embodiment of the present invention;

[0020] Figure 2 This is a flowchart illustrating data classification and uploading according to an embodiment of the present invention;

[0021] Figure 3 This is a flowchart of a data update according to an embodiment of the present invention;

[0022] Figure 4 This is a schematic diagram of a vehicle navigation process according to an embodiment of the present invention;

[0023] Figure 5 This is a schematic diagram of a navigation device according to an embodiment of the present invention;

[0024] Figure 6 This is a flowchart of a data reporting method according to an embodiment of the present invention;

[0025] Figure 7This is a schematic diagram of a vehicle navigation device according to an embodiment of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] First, the technical terms used in this embodiment are explained as follows:

[0029] Vehicle-to-X (V2X) wireless communication technology: V2X refers to the exchange of information between a vehicle and the outside world. By integrating GPS navigation technology, vehicle-to-vehicle communication technology, wireless communication, and remote sensing technology, the Internet of Vehicles (IoV) has laid the foundation for a new direction in automotive technology development, achieving compatibility between manual and autonomous driving. Vehicles equipped with V2X, in autonomous driving mode, can automatically select the best route based on real-time traffic information, thereby significantly alleviating traffic congestion.

[0030] Example 1

[0031] According to an embodiment of the present invention, a method embodiment for a vehicle navigation method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0032] Figure 1 This is a flowchart of a vehicle navigation method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0033] Step S102: Collect the first road condition data of the current road through the first vehicle.

[0034] The first vehicle is a vehicle currently on the road that provides connectivity with any electronic device.

[0035] The first vehicle mentioned above can be a vehicle using vehicle-to-X (V2X) wireless communication technology.

[0036] The aforementioned electronic devices may include, but are not limited to, roadside units, cameras, vehicles, and terminal devices.

[0037] The aforementioned first road condition data refers to the current road condition data collected by the first vehicle, including but not limited to: road event information, sign information, congestion information, traffic light information, map information, real-time identified obstacle information, information on distant emergency vehicles, and information on abnormal or malfunctioning vehicles.

[0038] In one optional embodiment, the first road condition data of the current road can be collected by image acquisition devices such as cameras or cameras installed on the vehicle. The road condition data of the current road can be collected automatically when the speed of the first vehicle slows down significantly, without the need for user operation.

[0039] Step S104: The first vehicle uploads the first road condition data to the cloud server.

[0040] The cloud server processes the first and second road condition data to obtain the target road condition data, and then sends the target road condition data to the second vehicle. The target road condition data refers to the road condition data of the current road obtained by comprehensively processing the road condition data collected by the V2X vehicle. The second road condition data is the road condition data of the current road collected by the third vehicle. The second vehicle is any vehicle on the current road. The second vehicle performs navigation based on the target road condition data. The third vehicle is any vehicle on the current road other than the first vehicle that provides the function of interconnection with any electronic device.

[0041] The aforementioned cloud server is a simple, efficient, secure, reliable computing service with elastically scalable processing capabilities. It can be used to comprehensively process road condition data collected by V2X vehicles and distribute it to other vehicles.

[0042] The aforementioned second road condition data is the current road condition data collected by the third vehicle, including but not limited to: road event information, sign information, congestion information, traffic light information, map information, real-time obstacle identification information, information on distant emergency vehicles, and information on abnormal or malfunctioning vehicles. The second road condition data and the first road condition data are road condition data collected by different vehicles. By comprehensively processing the first road condition data and the second road condition data, the current road condition information can be obtained more accurately and comprehensively.

[0043] In one alternative embodiment, secondary road condition data of the current road can be collected using image acquisition devices such as cameras or video cameras.

[0044] The aforementioned third vehicle refers to any vehicle on the current road other than the first vehicle, which provides connectivity with any electronic device. When the speed of the third vehicle slows down significantly, it can automatically collect road condition data without user intervention. After successful collection, it uploads the second road condition data. The first and third vehicles exist simultaneously on the current road. By comprehensively processing the road condition information collected by multiple vehicles existing on the current road, the road condition information can be made more accurate and comprehensive.

[0045] The second vehicle mentioned above is any vehicle currently on the road. Unlike the first and third vehicles, the second vehicle can be a vehicle that can provide the function of interconnecting with any electronic device, or it can be a vehicle that does not provide the function of interconnecting with any electronic device.

[0046] Optionally, the above-mentioned uploading of the first traffic data to the cloud server via the first vehicle includes: classifying the first traffic data using the navigation application of the first vehicle to obtain high-frequency map data and low-frequency map data, wherein the high-frequency map data is map data with a data change frequency greater than a first preset frequency, and the low-frequency map data is map data with a data change frequency less than a second preset frequency; uploading the high-frequency map data to the cloud server based on a first preset period; and uploading the low-frequency map data to the cloud server based on a second preset period.

[0047] High-frequency map data can be dynamic data, i.e., data that changes frequently in the map, such as traffic light information. Low-frequency map data can be static data, i.e., data that changes less frequently in the map, such as signage information and map information. The first preset frequency and the second preset frequency can be pre-set. The first preset frequency represents the frequency of dynamic data, and the second preset frequency represents the frequency of static data. The first preset frequency is greater than the second preset frequency. The first preset period is a shorter period, such as 1000ms. For data that changes frequently, a shorter period can be used to upload the data, ensuring the real-time accuracy of the data in the cloud server. The second preset period is a longer period, such as 10000ms. For data that changes infrequently, a longer period can be used to upload the data, reducing resource consumption. Table 1 is an illustration of an optional database according to an embodiment of the present invention, as shown in the table below:

[0048] Table 1 Database illustration

[0049]

[0050] In one alternative embodiment, high-frequency map data and low-frequency map data can be uploaded to a cloud server via a navigation application.

[0051] Figure 2 This is a flowchart illustrating data classification and uploading according to an embodiment of the present invention, such as... Figure 2 As shown, the data classification and uploading steps are as follows: The V2X vehicle receives traffic data and then sends it to the vehicle's navigation application. The V2X vehicle's navigation application splits the traffic data into static and dynamic data, uploading the static data at a period of 10,000 ms and the dynamic data at a period of 1,000 ms. By uploading different types of data in different ways through these steps, resource consumption can be reduced.

[0052] Optionally, the cloud server in the above steps is used to determine whether the first data in the first traffic data and the second data in the second traffic data are the same; in response to the first data and the second data being different, the first data in the first traffic data and the second data in the second traffic data are deleted to obtain the deleted first traffic data and the deleted second traffic data, and the target traffic data is obtained based on the deleted first traffic data and the deleted second traffic data.

[0053] The first data and the second data are respectively data from the first traffic condition data and the second traffic condition data that represent data uploaded at the same time, location, and with the same attributes, such as speed limit information for a specific lane on a specific day, month, and year. If the first data and the second data are different, it means that one of the data is inaccurate. All data with the same attribute are deleted, i.e., data cleaning is performed. Then, the target traffic condition data is obtained based on the deleted traffic condition data, which can improve the accuracy of the target traffic condition data.

[0054] In an alternative embodiment, the first and second data can be deleted using a delete statement in the database.

[0055] Optionally, the cloud server in the above steps is also used to determine whether it receives the reported high-frequency map data of the current road within a first preset time. In response to not receiving the newly reported high-frequency map data within the first preset time, it determines that the historically stored high-frequency map data is invalid, obtains a first invalid result, and updates the target road condition data based on the first invalid result.

[0056] The first preset time is a user-defined period for the validity of high-frequency map data. Since the reporting cycle for high-frequency map data is short, this validity period can be set to a short duration, such as 60 seconds. The first invalid result refers to the determination that the high-frequency map data is invalid. Based on the first invalid result, the target traffic data is updated. This can involve deleting the invalid high-frequency map data and uploading the valid high-frequency map data to update the target traffic data. Deleting map data that has not been uploaded for a long time ensures data real-time performance.

[0057] Optionally, the cloud server is also used to determine whether it receives reported low-frequency map data of the current road within a second preset time. In response to the failure to receive newly reported low-frequency map data within the second preset time, it determines that the historically stored low-frequency map data is invalid, obtains a second invalid result, and updates the target road condition data based on the second invalid result.

[0058] The second preset time is a user-defined period for the validity of low-frequency map data. Since the reporting cycle for low-frequency map data is relatively long, this validity period can be set to a longer duration, such as 60 minutes. The second invalid result refers to the determination that the high-frequency map data is invalid. Based on the second invalid result, the target traffic data is updated. This can involve deleting the determined invalid low-frequency map data and uploading the valid low-frequency map data to update the target traffic data. Deleting map data that has not been uploaded for a long time ensures data real-time performance.

[0059] Figure 3This is a flowchart of a data update according to an embodiment of the present invention, such as... Figure 3 As shown, the data update process specifically includes: after cloud data analysis and processing, data cleaning is performed, and then the data is classified into static data and dynamic data. If no static data is reported within 60 minutes, the static data is considered invalid. If no dynamic data is reported within 60 seconds, the dynamic data is considered invalid. Then, valid data is used to update the map and road traffic events, and the data is distributed to the terminal navigation application. The navigation application issues warnings based on the vehicle data and map data.

[0060] Optionally, the above method further includes: a cloud server receiving first traffic data uploaded by a first vehicle and second traffic data uploaded by a third vehicle. The first traffic data is the traffic data of the current road collected by the first vehicle, and the second traffic data is the traffic data of the current road collected by the third vehicle. The first vehicle is a vehicle on the current road used to provide interconnection functionality with any electronic device, and the third vehicle is any other vehicle on the current road other than the first vehicle used to provide interconnection functionality with any electronic device. The cloud server performs data analysis on the first and second traffic data to obtain target traffic data. The cloud server then sends the target traffic data to the second vehicle, whereby the second vehicle performs navigation based on the target traffic data.

[0061] The aforementioned first and second road condition data include, but are not limited to: road event information, sign information, congestion information, traffic light information, map information, real-time obstacle identification information, information on distant emergency vehicles, and information on abnormal or malfunctioning vehicles. The second and first road condition data are road condition data collected by different vehicles. By comprehensively processing the first and second road condition data, we can obtain more accurate and comprehensive road condition information on the current road.

[0062] The aforementioned third vehicle refers to any vehicle on the current road other than the first vehicle, which provides connectivity with any electronic device. When the speed of the third vehicle slows down significantly, it can automatically collect road condition data without user intervention. After successful collection, it uploads the second road condition data. The first and third vehicles exist simultaneously on the current road. By comprehensively processing the road condition information collected by multiple vehicles existing on the current road, the road condition information can be made more accurate and comprehensive.

[0063] The second vehicle mentioned above is any vehicle currently on the road. Unlike the first and third vehicles, the second vehicle can be a vehicle that can provide the function of interconnecting with any electronic device, or it can be a vehicle that does not provide the function of interconnecting with any electronic device.

[0064] The cloud server sends the target road condition data to the second vehicle, which then uses the target road condition data for navigation. This allows the user of the second vehicle to obtain the current road condition data in a timely manner, resulting in more accurate navigation route planning.

[0065] Figure 4 This is a schematic diagram of a vehicle navigation method according to an embodiment of the present invention, such as... Figure 4 As shown, V2X vehicles upload the road condition data they collect through roadside units to the map cloud, and then the map cloud distributes the map data to other vehicles for navigation.

[0066] Optionally, the cloud server processes the first traffic data and the second traffic data to obtain target traffic data, including: the cloud server determining whether the first data in the first traffic data and the second data in the second traffic data are the same; in response to the first data and the second data being different, the cloud server deleting the first data in the first traffic data and the second data in the second traffic data to obtain deleted first traffic data and deleted second traffic data; and the cloud server processing the deleted first traffic data and deleted second traffic data to obtain target traffic data.

[0067] The first data and the second data are respectively data from the first traffic condition data and the second traffic condition data that represent data uploaded at the same time, location, and with the same attributes, such as speed limit information for a specific lane on a specific day, month, and year. If the first data and the second data are different, it means that one of the data is inaccurate. All data with the same attribute are deleted, i.e., data cleaning is performed. Then, the target traffic condition data is obtained based on the deleted traffic condition data, which can improve the accuracy of the target traffic condition data.

[0068] In an alternative embodiment, the first and second data can be deleted using a delete statement in the database.

[0069] Figure 5 This is a schematic diagram of a navigation device according to an embodiment of the present invention, such as... Figure 5As shown, the device includes: a data receiving module for receiving data from V2X vehicles; a data cleaning module for collecting all data over a period of time, removing abnormal data whose values ​​are outside the reasonable range, removing data with low consistency ratios, and retaining data with high consistency ratios in the database; a data processing module for merging data with the same attribute and whose data values ​​do not conflict, and classifying all data into two categories: static data and dynamic data; a data sending module for sending data when data changes or according to different attribute data sending cycles; a timer module for timing the data update cycle, for example, the update cycle for static data is 60 minutes, and the update cycle for dynamic data is 60 seconds; and a vehicle-side application module for updating the map and providing navigation route warnings after the navigation application receives the data.

[0070] Through the above steps, the first vehicle collects the first road condition data of the current road and uploads it to the cloud server. The cloud server processes the first and second road condition data to obtain the target road condition data, which is then sent to the second vehicle. The second road condition data is the road condition data of the current road collected by the third vehicle. It is worth noting that the first vehicle is a vehicle on the current road that provides connectivity with any electronic device, the second vehicle is any vehicle on the current road that navigates based on the target road condition data, and the third vehicle is any other vehicle on the current road that provides connectivity with any electronic device. The cloud server integrates the road condition data collected by the first and third vehicles and sends it to the second vehicle. This achieves the goal of the cloud server being able to integrate and process road condition data collected by any vehicle on the current road that provides connectivity with any electronic device and send it to any vehicle on the current road, thereby achieving the technical effect of timely updating the navigation data on the current road and solving the technical problem of untimely updates to navigation map data.

[0071] Example 2

[0072] According to another aspect of the present invention, a vehicle navigation system is also provided, which can execute the vehicle navigation method in Embodiment 1 above. The specific implementation scheme and application scenario in this embodiment are the same as those in Embodiment 1 above, and will not be repeated here.

[0073] The system includes: a first vehicle for collecting first road condition data of the current road, wherein the first vehicle is a vehicle on the current road used to provide interconnection functionality with any electronic device; a third vehicle for collecting second road condition data of the current road, wherein the third vehicle is any vehicle on the current road other than the first vehicle used to provide interconnection functionality with any electronic device; a cloud server for processing the first road condition data and the second road condition data to obtain target road condition data; a second vehicle for navigation based on the target road condition data, wherein the second vehicle is any vehicle on the current road; and a controller for controlling the first vehicle to upload the first road condition data to the cloud server and controlling the cloud server to send the target road condition data to the second vehicle.

[0074] The first road condition data refers to the current road condition data collected by the first vehicle, including but not limited to: road event information, sign information, congestion information, traffic light information, map information, real-time obstacle identification information, remote emergency vehicle information, abnormal or malfunctioning vehicle information, etc. Any electronic device may include but is not limited to: roadside units, cameras, etc. The second road condition data refers to the current road condition data collected by the third vehicle, including but not limited to: road event information, sign information, congestion information, traffic light information, map information, real-time obstacle identification information, remote emergency vehicle information, abnormal or malfunctioning vehicle information, etc. The target road condition data refers to the current road condition data obtained by comprehensively processing the road condition data collected by the V2X vehicle.

[0075] The second vehicle navigates based on target road condition data, enabling its user to obtain current road condition data in a timely manner and resulting in more accurate navigation route planning. The controller controls the first vehicle to upload the first road condition data to the cloud server, and controls the cloud server to distribute the target road condition data to the second vehicle. This allows both V2X and non-V2X vehicles to utilize V2X data for navigation planning without requiring modifications to road test equipment. This solution has low real-time costs, requiring only upgrades to the navigation application map and cloud infrastructure to achieve V2X-enhanced map navigation.

[0076] Optionally, the controller is further configured to control the navigation application of the first vehicle to classify the first road condition data to obtain high-frequency map data and low-frequency map data, wherein the high-frequency map data is map data with a data change frequency greater than a first preset frequency, and the low-frequency map data is map data with a data change frequency less than a second preset frequency. The controller is further configured to upload the high-frequency map data to the cloud server based on a first preset period and the low-frequency map data to the cloud server based on a second preset period.

[0077] High-frequency map data can be dynamic data, meaning data that changes frequently on the map, such as traffic light changes. Low-frequency map data can be static data, meaning data that changes less frequently on the map, such as signage and map information. The first and second preset frequencies can be pre-set. The first preset frequency represents the frequency of dynamic data, and the second preset frequency represents the frequency of static data. The first preset frequency is greater than the second preset frequency. The first preset period is a shorter period, such as 1000ms, for frequently changing data, allowing for uploads with a shorter period to ensure the real-time accuracy of the data on the cloud server. The second preset period is a longer period, such as 10000ms, for infrequently changing data, allowing for uploads with a longer period to reduce resource consumption.

[0078] The above-mentioned uploading of high-frequency map data to the cloud server based on the first preset period and uploading of low-frequency map data to the cloud server based on the second preset period classifies data with high and low change rates, which not only ensures data integrity but also improves the real-time performance of data fusion.

[0079] Figure 6 This is a flowchart of a data reporting method according to an embodiment of the present invention, such as... Figure 6 As shown, the data reporting process includes: based on the road condition information marked on the map, it can be determined whether the V2X vehicle has entered the V2X communication area based on the distance. If the V2X vehicle has entered the V2X communication area, it is determined whether there is road condition data to be received. If so, the road condition data is reported. If the vehicle does not receive a V2X message until it leaves the V2X area, it is considered that no road condition data is received, and the cloud is notified that there is no road condition data to be reported at this location.

[0080] Example 3

[0081] According to another aspect of the present invention, a vehicle navigation device is also provided, which can execute the vehicle navigation method in Embodiment 1 above. The specific implementation scheme and application scenario in this embodiment are the same as those in Embodiment 1 above, and will not be repeated here.

[0082] Figure 7 This is a schematic diagram of a vehicle navigation device according to an embodiment of the present invention, such as... Figure 7As shown, the device includes: a data acquisition module 702, used to acquire first road condition data of the current road through a first vehicle, wherein the first vehicle is a vehicle on the current road that provides interconnection functionality with any electronic device; and a data upload module 704, used to upload the first road condition data to a cloud server through the first vehicle, wherein the cloud server processes the first road condition data and the second road condition data to obtain target road condition data, and sends the target road condition data to a second vehicle, wherein the second road condition data is the road condition data of the current road acquired by a third vehicle, the second vehicle is any vehicle on the current road, the second vehicle performs navigation based on the target road condition data, and the third vehicle is any vehicle on the current road other than the first vehicle that provides interconnection functionality with any electronic device.

[0083] The data upload module 704 includes: a data classification unit, used to classify the first traffic data through the navigation application of the first vehicle to obtain high-frequency map data and low-frequency map data, wherein the high-frequency map data is map data with a data change frequency greater than a first preset frequency, and the low-frequency map data is map data with a data change frequency less than a second preset frequency; a first upload unit, used to upload the high-frequency map data to the cloud server based on a first preset period; a second upload unit, used to upload the low-frequency map data to the cloud server based on a second preset period; a first judgment unit, used to judge whether the first data in the first traffic data and the second data in the second traffic data are the same; a first deletion unit, used to delete the first data in the first traffic data and the second data in the second traffic data in response to the first data and the second data being different, to obtain the deleted first traffic data and the deleted second traffic data; and a first acquisition unit, used to obtain the deleted first traffic data and the deleted second traffic data based on the deleted first traffic data and the deleted second traffic data. The target traffic data is obtained from the second traffic data, wherein the first data and the second data are respectively data from the first traffic data and the second traffic data used to represent the same location and the same attributes uploaded at the same time; the second judgment unit is used to judge whether the reported high-frequency map data of the current road is received within a first preset time; the second acquisition unit is used to determine that the historically stored high-frequency map data is invalid and obtain a first invalid result in response to the fact that no new reported high-frequency map data is received within the first preset time; the first update unit is used to update the target traffic data based on the first invalid result; the third judgment unit is used to judge whether the reported low-frequency map data of the current road is received within a second preset time; the third acquisition unit is used to determine that the historically stored low-frequency map data is invalid and obtain a second invalid result in response to the fact that no new reported low-frequency map data is received within the second preset time; the second update unit is used to update the target traffic data based on the second invalid result.

[0084] The aforementioned device further includes: a data receiving module, used by the cloud server to receive first road condition data uploaded by a first vehicle and second road condition data uploaded by a third vehicle, wherein the first road condition data is the road condition data of the current road collected by the first vehicle, the second road condition data is the road condition data of the current road collected by the third vehicle, the first vehicle is a vehicle on the current road used to provide interconnection with any electronic device, and the third vehicle is another vehicle on the current road other than the first vehicle used to provide interconnection with any electronic device; a data analysis module, used by the cloud server to perform data analysis on the first road condition data and the second road condition data to obtain target road condition data; and a data distribution module, used by the cloud server to distribute the target road condition data to the second vehicle, wherein the second vehicle performs navigation based on the target road condition data.

[0085] The data analysis module includes: a fourth judgment unit, used by the cloud server to determine whether the first data in the first traffic data and the second data in the second traffic data are the same; a second deletion unit, used by the cloud server to delete the first data in the first traffic data and the second data in the second traffic data in response to the first data and the second data being different, to obtain the deleted first traffic data and the deleted second traffic data; and a fourth acquisition unit, used by the cloud server to process the deleted first traffic data and the deleted second traffic data to obtain target traffic data, wherein the first data and the second data are respectively data in the first traffic data and the second traffic data used to represent data uploaded at the same time and at the same location with the same attributes.

[0086] Example 4

[0087] According to another aspect of the present invention, a vehicle is also provided, comprising: one or more processors; a storage device for storing one or more programs; and a vehicle navigation method wherein the one or more programs are executed by the one or more processors, causing the one or more processors to perform any of the above-described methods.

[0088] Example 5

[0089] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the above-described vehicle navigation method.

[0090] Example 6

[0091] According to another aspect of the present invention, a processor is also provided, which is used to run a program, wherein the program executes the above-described vehicle navigation method when it runs.

[0092] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0093] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0094] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0095] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0096] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0097] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0098] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A navigation method of a vehicle, characterized by, include: First road condition data of the current road is collected by a first vehicle, wherein the first vehicle is a vehicle on the current road used to provide interconnection with any electronic device; The first vehicle uploads the first traffic data to a cloud server, wherein the cloud server processes the first and second traffic data to obtain target traffic data, and then sends the target traffic data to the second vehicle. The second traffic data is the traffic data of the current road collected by the third vehicle, and the second vehicle is any vehicle on the current road. The second vehicle performs navigation based on the target traffic data, and the third vehicle is any vehicle on the current road other than the first vehicle that provides interconnection functionality with any electronic device. The process of uploading the first road condition data to the cloud server via the first vehicle includes: The navigation application of the first vehicle classifies the first road condition data to obtain high-frequency map data and low-frequency map data. The high-frequency map data is map data with a data change frequency greater than a first preset frequency, and the low-frequency map data is map data with a data change frequency less than a second preset frequency. The high-frequency map data is uploaded to the cloud server based on a first preset cycle. The low-frequency map data is uploaded to the cloud server based on the second preset cycle.

2. The vehicle navigation method according to claim 1, characterized in that, The cloud server is used to determine whether the first data in the first traffic data and the second data in the second traffic data are the same; in response to the first data and the second data being different, the first data in the first traffic data and the second data in the second traffic data are deleted to obtain the deleted first traffic data and the deleted second traffic data, and the target traffic data is obtained based on the deleted first traffic data and the deleted second traffic data, wherein the first data and the second data are respectively data in the first traffic data and the second traffic data used to represent the same location uploaded at the same time and having the same attributes.

3. The vehicle navigation method according to claim 1, characterized in that, The cloud server is also used to determine whether the high-frequency map data of the current road is received within a first preset time. In response to the fact that no new high-frequency map data is received within the first preset time, the server determines that the historically stored high-frequency map data is invalid, obtains a first invalid result, and updates the target road condition data based on the first invalid result.

4. The vehicle navigation method according to claim 1, characterized in that, The cloud server is also used to determine whether the reported low-frequency map data of the current road is received within a second preset time. In response to the fact that no new reported low-frequency map data is received within the second preset time, the historically stored low-frequency map data is determined to be invalid, a second invalid result is obtained, and the target road condition data is updated based on the second invalid result.

5. A vehicle navigation method, characterized in that, include: The cloud server receives first road condition data uploaded by a first vehicle and second road condition data uploaded by a third vehicle. The first road condition data is the road condition data of the current road collected by the first vehicle, and the second road condition data is the road condition data of the current road collected by the third vehicle. The first vehicle is a vehicle on the current road that provides the function of interconnection with any electronic device, and the third vehicle is any other vehicle on the current road that provides the function of interconnection with any electronic device, excluding the first vehicle. The cloud server performs data analysis on the first traffic data and the second traffic data to obtain the target traffic data; The cloud server sends the target traffic data to the second vehicle, wherein the second vehicle performs navigation based on the target traffic data; The cloud server receives the first traffic data uploaded by the first vehicle, including: The cloud server receives high-frequency map data uploaded by the first vehicle based on a first preset period; The cloud server receives low-frequency map data uploaded by the first vehicle based on a second preset period; The high-frequency map data and the low-frequency map data are obtained by classifying the first road condition data through the navigation application of the first vehicle. The high-frequency map data is map data with a data change frequency greater than a first preset frequency, and the low-frequency map data is map data with a data change frequency less than a second preset frequency.

6. The vehicle navigation method according to claim 5, characterized in that, The cloud server processes the first traffic data and the second traffic data to obtain target traffic data, including: The cloud server determines whether the first data in the first traffic data and the second data in the second traffic data are the same; In response to the fact that the first data and the second data are different, the cloud server deletes the first data from the first traffic data and the second data from the second traffic data to obtain the deleted first traffic data and the deleted second traffic data. The cloud server processes the deleted first traffic data and the deleted second traffic data to obtain the target traffic data, wherein the first data and the second data are respectively data from the first traffic data and the second traffic data used to represent data uploaded at the same time, the same location, and with the same attributes.

7. A vehicle navigation system, characterized in that, include: The first vehicle is used to collect the first road condition data of the current road, wherein the first vehicle is a vehicle on the current road used to provide interconnection functions with any electronic device; A third vehicle is used to collect second road condition data of the current road, wherein the third vehicle is any vehicle on the current road other than the first vehicle that is used to provide interconnection functionality with any electronic device; A cloud server is used to process the first and second traffic data to obtain the target traffic data. A second vehicle is used for navigation based on the target road condition data, wherein the second vehicle is any vehicle on the current road; The controller is used to control the first vehicle to upload the first road condition data to the cloud server, and to control the cloud server to send the target road condition data to the second vehicle; The controller is further configured to control the navigation application of the first vehicle to classify the first road condition data to obtain high-frequency map data and low-frequency map data. The high-frequency map data is map data with a data change frequency greater than a first preset frequency, and the low-frequency map data is map data with a data change frequency less than a second preset frequency. The controller is further configured to upload the high-frequency map data to the cloud server based on a first preset period and the low-frequency map data to the cloud server based on a second preset period.

8. A vehicle, characterized in that, include: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors perform the vehicle navigation method according to any one of claims 1 to 6.

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