Vehicle test data processing method and vehicle

Abstract

The invention provides a vehicle test data processing method and a vehicle, and relates to the technical field of vehicle test. According to the method, the compression mode and the transmission bandwidth of each kind of driving data can be determined according to the importance of each kind of driving data; for each kind of driving data, the driving data is compressed according to the compression mode corresponding to the driving data, and because the transmission bandwidth of each kind of driving data is positively correlated with the corresponding importance, the compression loss corresponding to the data compression mode of each kind of driving data is negatively correlated with the importance of the driving data. And the compression ratio corresponding to the data compression mode of each type of driving data is negatively correlated with the importance of the driving data, so that the more important driving data is allocated with a larger bandwidth, the smaller the compression ratio is, and the lower the compression loss is; the transmission timeliness of important driving data and the quality of the important driving data received by the service platform can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle testing, in particular to a vehicle testing data processing method and a vehicle. BACKGROUND

[0002] Before a vehicle is put into the market far away from the production place, the vehicle needs to be driven on a designated road in a test area selected in the place far away from the production place, so that the vehicle collects testing data while driving and transmits the collected testing data (such as driving data) to a service platform in the production place, so that the staff can analyze whether the driving of the vehicle conforms to the local regulations or whether there is an abnormality according to the collected testing data.

[0003] However, after the testing data is transmitted to the service platform in the production place, the quality of the testing data obtained by the service platform in the production place is low and the latency is high. SUMMARY

[0004] The present application provides a vehicle testing data processing method and a vehicle, which are used to solve the problem that the quality of the testing data obtained by the service platform in the production place is low and the latency is high after the testing data is transmitted to the service platform in the production place.

[0005] In a first aspect, the present application provides a vehicle testing data processing method, comprising: When the vehicle starts driving on a road in a target test area, downloading a driving regulation corresponding to the target test area; Collecting testing data of the road in the target test area by the vehicle, wherein the testing data is a plurality of driving data generated by the vehicle; Determining the importance of each kind of driving data on the driving safety level according to the driving regulation; Determining the compression mode and the transmission bandwidth of each kind of driving data according to the importance of each kind of driving data, wherein the transmission bandwidth of each kind of driving data is positively correlated with the corresponding importance, the compression loss of the data compression mode of each kind of driving data is negatively correlated with the importance of the driving data, and the compression ratio of the data compression mode of each kind of driving data is negatively correlated with the importance of the driving data; According to the compression mode corresponding to each kind of driving data, compressing the driving data; According to the transmission bandwidth corresponding to each kind of driving data, transmitting the compressed plurality of driving data to a service platform far away from the target test area.

[0006] In some embodiments, one kind of driving data in the plurality of driving data is environment data, and the importance of each kind of driving data on the driving safety level is determined according to the preset driving regulation of the target test area, comprising: identifying whether the environmental data represents a marker associated with a violation of the traffic regulations; If so, determining the importance of the marker as the importance of the environmental data.

[0007] In some embodiments, after the environmental data is collected, the method provided by the present application further comprises: detecting whether the environmental data contains privacy data specified in the traffic regulations; If the environmental data contains privacy data, performing desensitization processing on the privacy data in the environmental data.

[0008] In some embodiments, one of the plurality of driving data is vehicle operation data, and the importance of each type of driving data on the traffic safety level is determined according to the traffic regulations of the target test area, including: identifying target vehicle operation data in the vehicle operation data that is prone to violations of the traffic regulations in the target test area; determining the importance of the target vehicle operation data as the importance of the vehicle operation data.

[0009] In some embodiments, the collection frequency and collection resolution of each type of driving data are positively correlated with the importance of the last collected driving data.

[0010] In some embodiments, before transmitting the compressed plurality of driving data to the service platform away from the target test area according to the transmission bandwidth corresponding to each type of driving data, the method provided by the present application further comprises: detecting the signal strength of each different network; selecting the network with the strongest signal strength; transmitting the plurality of driving data to the service platform away from the target test area according to the transmission bandwidth corresponding to each type of driving data, including: transmitting the plurality of driving data to the service platform away from the target test area based on the transmission bandwidth corresponding to each type of driving data in the network with the strongest signal strength.

[0011] In some embodiments, before transmitting the plurality of driving data to the service platform away from the target test area according to the transmission bandwidth corresponding to each type of driving data, the method provided by the present application further comprises: inputting the recorded network fluctuation data of the previous plurality of time periods into a pre-trained network fluctuation model to determine the network fluctuation data of the next time period, wherein the network fluctuation model is obtained by inputting a plurality of training samples into a network to be trained, and each training sample includes historical network fluctuation data of a plurality of previous time periods and network fluctuation data of the next time period in history; In the case that the network fluctuation data of the next time period represents network instability, the plurality of driving data is buffered.

[0012] In some embodiments, the compressed plurality of driving data is transmitted to the service platform away from the target test area according to the transmission bandwidth corresponding to each type of driving data, including: For each type of driving data, the compressed driving data is segmented into a plurality of data packets. According to the transmission bandwidth corresponding to the driving data, the plurality of data packets of the compressed driving data is transmitted to the service platform away from the target test area in a way of resuming transmission at a breakpoint.

[0013] In some embodiments, the plurality of data packets of the compressed driving data is transmitted to the service platform away from the target test area in a way of resuming transmission at a breakpoint, including: At each transmission of a data packet, a first hash value is generated based on the data packet, and the data packet carrying the first hash value is transmitted to the service platform away from the target test area. In the case that a second hash value generated by the service platform according to the received data packet is inconsistent with the first hash value, the data packet is retransmitted to the service platform away from the target test area in response to a retransmission request of the service platform.

[0014] In a second aspect, the present application further provides a vehicle, including a memory, an on-board controller, and a computer program stored in the memory and executable on the on-board controller, wherein the on-board controller executes the computer program to enable the vehicle to perform the method provided in the first aspect.

[0015] In a third aspect, the present application further provides a computer readable storage medium, which stores a computer program, wherein the computer program is executed by a processor to enable a computer to perform the method provided in the first aspect.

[0016] In a fourth aspect, the present application further provides a computer program product, which includes a computer program, wherein the computer program is executed to enable a computer to perform the method provided in the first aspect.

[0017] This application provides a method for processing vehicle test data and a vehicle. Based on driving regulations, the importance of each type of driving data in terms of driving safety is determined. Based on the importance of each type of driving data, a compression method and transmission bandwidth are determined. For each type of driving data, the data is compressed according to the corresponding compression method. Based on the transmission bandwidth corresponding to each type of driving data, the compressed driving data is transmitted to a service platform far from the target testing area. It is understood that since the transmission bandwidth of each type of driving data is positively correlated with its importance, the compression loss corresponding to each compression method is negatively correlated with the importance of the driving data, and the compression ratio corresponding to each compression method is negatively correlated with the importance of the driving data, more important driving data can be allocated a larger bandwidth, a smaller compression ratio, and lower compression loss. This improves the timeliness of the transmission of important driving data and the quality of important driving data received by the service platform far from the target testing area, helping to improve the reliability of the analysis results subsequently analyzed by personnel based on the received test data. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic diagram illustrating the interaction between a vehicle and a service platform provided in an embodiment of this application; Figure 2 A flowchart illustrating the vehicle test data processing method provided in this application embodiment; Figure 3 This is a functional unit diagram of the vehicle test data processing device provided in an embodiment of this application. Detailed Implementation

[0020] Embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0021] The accompanying drawings illustrate various structural schematics according to embodiments of the present disclosure. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0022] In the context of this disclosure, when a layer / element is referred to as being "above" another layer / element, the layer / element may be directly above the other layer / element, or there may be an intermediate layer / element between them. Additionally, if a layer / element is "above" another layer / element in one orientation, then when the orientation is reversed, the layer / element may be "below" the other layer / element.

[0023] The technical solutions of this application and how they solve the aforementioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0024] This application provides a method for processing test data of a vehicle, applied to vehicle 101. For example... Figure 1 As shown, vehicle 101 is communicatively connected to service platform 102. Figure 2 As shown, the method provided in this application embodiment includes: S201: When vehicle 101 begins to travel on the road in the target test area, download the driving regulations corresponding to the target test area.

[0025] For example, download the corresponding driving regulations from the regulatory management server associated with the target test area.

[0026] S202: Vehicle 101 collects test data of the road in the target test area, wherein the test data consists of various driving data generated by vehicle 101.

[0027] For example, the test data includes, but is not limited to, environmental data of the environment in which vehicle 101 is located and operational data of vehicle 101.

[0028] For example, vehicle 101 is equipped with an environmental perception sensor array, which may include, but is not limited to, multiple cameras, multiple millimeter-wave radars, lidar, and positioning sensors. This array can collect environmental data (such as image data and point cloud data) about the environment surrounding vehicle 101. Multiple cameras are respectively mounted on the windshield, rearview mirrors, and rear of vehicle 101; millimeter-wave radars are mounted on the front and rear bumpers and side skirts of vehicle 101; and lidar is mounted on the roof of vehicle 101. For instance, the cameras can collect image data of the surrounding environment of vehicle 101, which is used to identify traffic signs, lane lines, obstacles, etc.; the millimeter-wave radar is used to sense the distance and relative speed between vehicle 101 and the vehicle in front; and the lidar is used to collect point cloud data of the environment surrounding vehicle 101.

[0029] It should be noted that the time deviation of each data point can be controlled within ±2ms by fusing the collected data through extended Kalman filtering and performing time alignment.

[0030] For example, the vehicle 101 is equipped with an operating data sensing sensor assembly, which may include, but is not limited to, an engine speed sensor (for collecting engine speed), a vehicle speed sensor (for collecting vehicle speed), a pedal sensor (for collecting pedal position), an exhaust volume sensor (for collecting exhaust flow), and an acceleration sensor (for collecting the acceleration of the vehicle 101).

[0031] It should be noted that the system can detect whether the environmental data contains privacy data as stipulated in driving regulations (such as facial images and license plate numbers); if the environmental data contains privacy data, the privacy data in the environmental data will be anonymized (e.g., masked).

[0032] Specifically, the collection frequency and resolution of each type of driving data can be positively correlated with the importance of the previously collected type of driving data. For example, if the environmental data contains markers associated with violations stipulated in traffic regulations, the collection frequency and resolution of the driving data can be increased; similarly, if the environmental data indicates that vehicle 101 is located in an area with frequent traffic congestion, the collection frequency and resolution of the driving data can be increased. In this way, the richness of the collected high-importance driving data can be improved.

[0033] S203: Determine the importance of each type of driving data in terms of driving safety, in accordance with driving regulations.

[0034] S203 can be implemented in two ways, including but not limited to: The first approach is to identify whether the environmental data represents a marker associated with a violation as defined in traffic regulations. If so, the importance of the marker is determined as the importance of the environmental data.

[0035] For example, traffic regulations may specify traffic lights (running a red light is a violation), speed limit signs (speeding is a violation), and lane markings (crossing solid lines is a violation).

[0036] Traffic lights are rated 9 points for importance, speed limit signs are rated 8 points for importance, and lane markings are rated 7 points for importance. A score greater than 6 points indicates high importance, and the higher the score, the more important it is.

[0037] The second type: One type of driving data is vehicle 101 operation data. Identify the target vehicle 101 operation data that is prone to violating traffic regulations in the target test area; determine the importance of the target vehicle 101 operation data by associating its importance with the traffic regulations.

[0038] For example, the operating data of the target vehicle 101 that is prone to illegal behavior can be vehicle speed (speeding is illegal), exhaust emission flow (excessive emissions are illegal), and acceleration (the greater the acceleration, the more likely it is to cause illegal behavior). The importance of vehicle speed is 8 points, the importance of exhaust emission flow is 7 points, the importance of acceleration is 7 points, and a score greater than 6 points indicates high importance, and the higher the score, the more important it is.

[0039] S204: Determine the compression method and transmission bandwidth for each type of driving data based on its importance.

[0040] Among them, the transmission bandwidth of each type of driving data is positively correlated with its importance (e.g., bandwidth A is allocated to driving data of high importance, and bandwidth B is allocated to driving data of low importance (e.g., entertainment data generated on vehicle 101), and bandwidth A is greater than bandwidth B). The compression loss corresponding to the data compression method of each type of driving data is negatively correlated with the importance of the driving data (e.g., lossless compression is used for driving data of high importance, and lossy compression is used for driving data of low importance). Furthermore, the compression ratio corresponding to the data compression method of each type of driving data is negatively correlated with the importance of the driving data (e.g., the compression ratio of driving data of high importance is C, and the compression ratio of driving data of low importance is D, and compression ratio C is less than compression ratio D).

[0041] S205: For each type of driving data, compress the driving data according to the corresponding compression method.

[0042] It should be noted that the compressed driving data can be packaged into JSON format.

[0043] S206: Based on the transmission bandwidth corresponding to each type of driving data, transmit the compressed driving data to the service platform 102, which is far from the target test area.

[0044] Specifically, for each type of driving data, the compressed driving data of that type is divided into multiple data packets; based on the transmission bandwidth corresponding to the type of driving data, the multiple data packets of the compressed driving data of that type are transmitted to the service platform 102 far away from the target test area using a breakpoint resume method (e.g., transmitting one data packet every 10ms).

[0045] For example, when transmitting each data packet, a first hash value is generated based on the data packet, and the data packet carrying the first hash value is transmitted to the service platform 102 located away from the target test area. If the second hash value generated by the service platform 102 based on the received data packet is inconsistent with the first hash value, the data packet is retransmitted to the service platform 102 located away from the target test area in response to the retransmission request of the service platform 102. In this way, the reliability of various driving data received by the service platform 102 can be further improved. In addition, forward error correction coding (Reed-Solomon) can be used to automatically recover lost data packets.

[0046] In summary, the vehicle test data processing method provided in this application can determine the importance of each type of driving data in terms of driving safety according to driving regulations; determine the compression method and transmission bandwidth of each type of driving data based on its importance; compress each type of driving data according to its corresponding compression method; and transmit the compressed driving data to a service platform 102 located far from the target test area according to the transmission bandwidth corresponding to each type of driving data. It is understandable that since the transmission bandwidth of each type of driving data is positively correlated with its corresponding importance, the compression loss corresponding to each data compression method is negatively correlated with the importance of the driving data, and the compression ratio corresponding to each data compression method is negatively correlated with the importance of the driving data, more important driving data can be allocated a larger bandwidth, a smaller compression ratio, and lower compression loss. This improves the timeliness of the transmission of important driving data and the quality of the important driving data received by the service platform 102, helping to improve the reliability of the analysis results subsequently analyzed by staff based on the received test data.

[0047] In addition, prior to S206, the method provided in this application embodiment further includes: detecting the signal strength of each different network; selecting the network with the strongest signal strength; in this way, S206 can be implemented to transmit multiple types of driving data to the service platform 102 far away from the target test area based on the transmission bandwidth corresponding to each type of driving data on the network with the strongest signal strength, thereby improving the timeliness and reliability of multiple types of driving data transmission.

[0048] For example, in Africa, one can choose the satellite communication network with the strongest signal strength from among 4G / 5G networks, satellite communication networks, and Wi-Fi networks; similarly, in Europe, one can choose the 4G / 5G network with the strongest signal strength from among 4G / 5G networks, satellite communication networks, and Wi-Fi networks.

[0049] Furthermore, prior to S206, the method provided in this application embodiment further includes: inputting recorded network fluctuation data from multiple previous time periods into a pre-trained network fluctuation model to determine network fluctuation data for the next time period. The network fluctuation model is trained by inputting multiple training samples into the network to be trained, each training sample including historical network fluctuation data from multiple previous time periods and historical network fluctuation data for the next time period. When the network fluctuation data for the next time period indicates network instability, multiple types of driving data are cached. This avoids data loss during transmission of multiple types of driving data. Transmission of multiple types of driving data only continues when the network stabilizes.

[0050] Please see Figure 3 This application provides a vehicle test data processing device. It should be noted that the basic principle and technical effects of the vehicle test data processing device provided in this application are the same as those in the above embodiments. For the sake of brevity, any parts not mentioned in this application can be referred to the corresponding content in the above embodiments. The device provided in this application includes a data download unit, a data acquisition unit, an importance determination unit, a transmission parameter determination unit, a data compression unit, and a data transmission unit. The data download unit is used to download the driving regulations corresponding to the target test area when driving on the road in the target test area begins. The data acquisition unit is used to collect test data of the road in the target test area, including various driving data generated by vehicle 101. The importance determination unit is used to determine the importance of each type of driving data in terms of driving safety, based on driving regulations. The transmission parameter determination unit is used to determine the compression method and transmission bandwidth of each type of driving data according to the importance of each type of driving data. The transmission bandwidth of each type of driving data is positively correlated with its corresponding importance, the compression loss corresponding to the data compression method of each type of driving data is negatively correlated with the importance of the driving data, and the compression ratio corresponding to the data compression method of each type of driving data is negatively correlated with the importance of the driving data. The data compression unit is used to compress the driving data according to the compression method corresponding to each type of driving data. The data transmission unit is used to transmit compressed driving data to the service platform 102, which is far from the target test area, according to the transmission bandwidth corresponding to each type of driving data.

[0051] In some implementations, one of the driving data types is environmental data. The importance determination unit is used to identify whether the environmental data represents a marker associated with a violation as specified in the driving regulations. If so, the importance of the marker is determined as the importance of the environmental data.

[0052] In some embodiments, the apparatus provided in this application further includes: a desensitization processing unit, used to detect whether the environmental data contains privacy data as specified in the driving regulations; if the environmental data contains privacy data, then the privacy data in the environmental data is desensitized.

[0053] In some implementations, one type of driving data is vehicle 101 operation data. The importance determination unit is used to identify target vehicle 101 operation data that is prone to violating traffic regulations in the target test area; and to determine the importance of the target vehicle 101 operation data as the importance of the vehicle 101 operation data.

[0054] In some implementations, the frequency and resolution of each type of driving data acquisition are positively correlated with the importance of the previously acquired driving data.

[0055] In some embodiments, the apparatus provided in this application further includes: a network selection unit for detecting the signal strength of different networks and selecting the network with the strongest signal strength.

[0056] The data transmission unit is specifically used to transmit various types of driving data to the service platform 102, which is far from the target test area, based on the transmission bandwidth corresponding to each type of driving data, in the network with the strongest signal strength.

[0057] In some embodiments, the apparatus provided in this application further includes: a data caching unit, used to input recorded network fluctuation data from multiple previous time periods into a pre-trained network fluctuation model to determine network fluctuation data for the next time period, wherein the network fluctuation model is trained by inputting multiple training samples into a network to be trained, and each training sample includes historical network fluctuation data from multiple previous time periods and historical network fluctuation data for the next time period; when the network fluctuation data for the next time period indicates network instability, multiple types of driving data are cached.

[0058] In some implementations, the data transmission unit is specifically used to divide the compressed type of driving data into multiple data packets for each type of driving data; and to transmit the multiple data packets of compressed driving data to the service platform 102 far away from the target test area using a breakpoint resume method according to the transmission bandwidth corresponding to the type of driving data.

[0059] In some implementations, the data retransmission unit is configured to generate a first hash value based on the data packet when transmitting each data packet, and transmit the data packet carrying the first hash value to the service platform 102 located away from the target test area; if the second hash value generated by the service platform 102 based on the received data packet is inconsistent with the first hash value, the data packet is retransmitted to the service platform 102 located away from the target test area in response to the retransmission request of the service platform 102.

[0060] In addition, this application also provides a vehicle, including a memory, an on-board controller, and a computer program stored in the memory and executable on the on-board controller. When the on-board controller executes the computer program, it causes the vehicle to perform the method provided in the above embodiments of this application.

[0061] In addition, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the computer to perform the method provided in the above embodiments of this application.

[0062] In addition, this application also provides a computer program product, including a computer program that, when run, causes a computer to perform the method provided in the above embodiments of this application.

[0063] The above description does not provide detailed technical specifications regarding the structure of each layer. However, those skilled in the art should understand that layers and regions of desired shapes can be formed using various technical means. Furthermore, to form the same structure, those skilled in the art can also design methods that are not entirely identical to those described above. Additionally, although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be advantageously combined.

[0064] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0065] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for processing test data of a vehicle, characterized in that, The method includes: When the vehicle begins to drive on the road in the target test area, the driving regulations corresponding to the target test area are downloaded. The vehicle collects test data of the road in the target test area, wherein the test data is a variety of driving data generated by the vehicle; Based on the aforementioned driving regulations, determine the importance of each type of driving data in terms of driving safety; Based on the importance of each type of driving data, the compression method and transmission bandwidth of each type of driving data are determined. The transmission bandwidth of each type of driving data is positively correlated with its corresponding importance, the compression loss corresponding to the data compression method of each type of driving data is negatively correlated with the importance of the driving data, and the compression ratio corresponding to the data compression method of each type of driving data is negatively correlated with the importance of the driving data. For each type of driving data, the driving data is compressed according to the compression method corresponding to the driving data; Based on the transmission bandwidth corresponding to each type of driving data, the compressed driving data is transmitted to a service platform located far from the target test area.

2. The method according to claim 1, characterized in that, One type of driving data among the various driving data is environmental data. Based on the driving regulations of the preset target test area, the importance of each type of driving data in terms of driving safety is determined, including: Identify whether the environmental data represents any markers associated with violations as defined in the driving regulations; If it exists, the importance corresponding to the marker is determined as the importance of the environmental data.

3. The method according to claim 2, characterized in that, After collecting the environmental data, the method further includes: The system detects whether the environmental data contains privacy data as specified in the driving regulations. If the environmental data contains private data, then the private data in the environmental data will be anonymized.

4. The method according to claim 1, characterized in that, One type of driving data is vehicle operation data. Based on the driving regulations of the preset target test area, the importance of each type of driving data in terms of driving safety is determined, including: Identify target vehicle operation data from the vehicle operation data that are prone to violating traffic regulations in the target test area; The importance of associating the target vehicle's operating data with that importance is determined as the importance of the vehicle's operating data.

5. The method according to claim 1, characterized in that, The acquisition frequency and resolution of each type of driving data are positively correlated with the importance of the previously acquired driving data.

6. The method according to claim 1, characterized in that, Before transmitting the compressed driving data to a service platform located away from the target test area according to the transmission bandwidth corresponding to each type of driving data, the method further includes: Detect the signal strength of various different networks; Choose the network with the strongest signal; The step of transmitting the various types of driving data to a service platform located far from the target test area based on the transmission bandwidth corresponding to each type of driving data includes: transmitting the various types of driving data to a service platform located far from the target test area on the network with the strongest signal strength, based on the transmission bandwidth corresponding to each type of driving data.

7. The method according to claim 1, characterized in that, Before transmitting the various types of driving data to a service platform located far from the target test area according to the transmission bandwidth corresponding to each type of driving data, the method further includes: The network fluctuation data recorded from multiple previous time periods are input into a pre-trained network fluctuation model to determine the network fluctuation data for the next time period. The network fluctuation model is trained by inputting multiple training samples into the network to be trained. Each training sample includes historical network fluctuation data from multiple previous time periods and historical network fluctuation data for the next time period. In the event that the network fluctuation data in the next time period indicates network instability, the various types of driving data are cached.

8. The method according to claim 1, characterized in that, The step of transmitting compressed driving data to a service platform located far from the target test area, based on the transmission bandwidth corresponding to each type of driving data, includes: For each type of driving data, the compressed driving data is divided into multiple data packets; Based on the transmission bandwidth corresponding to the driving data, multiple data packets of compressed driving data are transmitted to a service platform far from the target test area using a breakpoint resume method.

9. The method according to claim 8, characterized in that, The method of transmitting multiple data packets of compressed driving data to a service platform far from the target test area using a breakpoint resume transmission technique includes: When transmitting each data packet, a first hash value is generated based on the data packet, and the data packet carrying the first hash value is transmitted to the service platform. If the second hash value generated by the service platform based on the received data packet is inconsistent with the first hash value, the service platform shall retransmit the data packet in response to the retransmission request of the service platform.

10. A vehicle, characterized in that, The system includes a memory, an onboard controller, and a computer program stored in the memory and executable on the onboard controller, characterized in that, when the onboard controller executes the computer program, it causes the vehicle to perform the method as described in any one of claims 1 to 7.

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