Data processing system, method, device, equipment and storage medium

Abstract

This application discloses a data processing system, method, apparatus, device, and storage medium, relating to the field of intelligent driving technology. The system includes: a data integration unit and a sensor unit, a bus data acquisition unit, and a data storage unit connected to the data integration unit; the data integration unit is used to send a start signal to at least one of the sensor unit and the bus data acquisition unit; the sensor unit is used to acquire vehicle environmental information and send the vehicle environmental information to the data integration unit upon receiving the start signal from the data integration unit; the bus data acquisition unit is used to acquire vehicle status information and send the vehicle status information to the data integration unit upon receiving the start signal from the data integration unit; the data integration unit is used to send at least one of the vehicle environmental information and vehicle status information to the data storage unit. This application can improve the management efficiency of data acquisition.

Description

Technical Field

[0001] This application relates to the field of intelligent driving technology, and in particular to a data processing system, method, apparatus, device, and storage medium. Background Technology

[0002] With the improvement of computing power, the maturity of sensor technology, and the development of artificial intelligence algorithms, intelligent driving is gradually moving from theory to market application.

[0003] Data acquisition is a complex and multi-dimensional process aimed at collecting various types of data needed to train, validate, and optimize autonomous driving algorithms, such as raw information from sensors (e.g., cameras, LiDAR, millimeter-wave radar). In related technologies, each sensor module is often developed independently, and the data collected by each sensor module is then fused offline.

[0004] However, while the solutions in related technologies can reduce the initial development difficulty, they affect the efficiency of data collection. Summary of the Invention

[0005] This application provides a data processing system, method, apparatus, device, and storage medium, which not only improves the efficiency of data acquisition but also enhances the management efficiency of various acquired data. The technical solution proposed in this application is as follows:

[0006] According to one aspect of the embodiments of this application, a data processing system is provided, the system comprising: a data integration unit, and a sensor unit, a bus data acquisition unit, and a data storage unit connected to the data integration unit;

[0007] The data integration unit is used to send a start signal to at least one of the sensor unit and the bus data acquisition unit;

[0008] The sensor unit is used to acquire vehicle environment information and send the vehicle environment information to the data integration unit upon receiving the start signal sent by the data integration unit; the vehicle environment information is used to indicate the environment in which the vehicle is located.

[0009] The bus data acquisition unit is used to acquire vehicle status information and send the vehicle status information to the data integration unit when it receives the start signal sent by the data integration unit; the vehicle status information is used to indicate the vehicle's own status.

[0010] The data integration unit is used to send at least one of the vehicle environment information and the vehicle status information to the data storage unit.

[0011] According to one aspect of the embodiments of this application, a data processing method is provided, the method being executed by a data integration unit of a data processing system, the system further comprising a sensor unit, a bus data acquisition unit, and a data storage unit connected to the data integration unit, the method comprising:

[0012] A start signal is sent to at least one of the sensor unit and the bus data acquisition unit, so that the sensor unit, upon receiving the start signal, acquires vehicle environment information and sends the vehicle environment information to the data integration unit; and the bus data acquisition unit, upon receiving the start signal, acquires vehicle status information and sends the vehicle status information to the data integration unit; the vehicle environment information is used to indicate the environment in which the vehicle is located, and the vehicle status information is used to indicate the status of the vehicle itself.

[0013] At least one of the vehicle environment information and the vehicle status information is sent to the data storage unit.

[0014] In some embodiments, sending a start signal to at least one of the sensor unit and the bus data acquisition unit further includes:

[0015] Receive a start command; the start command is used to instruct the start of at least one subunit among the sensor unit and the bus data acquisition unit;

[0016] Based on the startup instruction, a startup list is determined; the startup list contains at least one sub-unit that the startup instruction indicates to be started.

[0017] The start signal is sent to at least one sub-unit in the list to be started.

[0018] In some embodiments, the start command is further used to indicate a specified start condition for at least one subunit of the sensor unit and the bus data acquisition unit; the specified start condition includes at least one of the following: the vehicle's position information meets a specified position condition, or a specified period is reached;

[0019] Sending the start signal to at least one sub-unit in the list to be started includes:

[0020] If the specified startup conditions are met, the startup signal is sent to at least one sub-unit in the list of units to be started.

[0021] In some embodiments, sending at least one of the vehicle environment information and the vehicle status information to the data storage unit includes:

[0022] Perform detection processing on at least one of the vehicle environment information and the vehicle status information;

[0023] If at least one of the vehicle environment information and the vehicle status information is detected to meet the specified detection conditions, at least one of the vehicle environment information and the vehicle status information is sent to the data storage unit.

[0024] In some embodiments, the vehicle environment information includes at least one of the following: image data and point cloud data;

[0025] The vehicle status information includes at least one of the following: vehicle status parameters, distance and relative speed of a distant target, and distance of a nearby target;

[0026] The specified detection conditions include at least one of the following:

[0027] The difference between the timestamps corresponding to the image data and the point cloud data does not exceed a first specified threshold.

[0028] The repetition of objects in the projected point cloud data and the image data meets the first specified requirement;

[0029] The differences between the timestamps corresponding to the vehicle state parameters, the distance and relative speed of the distant measurement target, and the distance of the near measurement target do not exceed a second specified threshold.

[0030] The frame rates corresponding to the vehicle state parameters, the distance and relative speed of the distant measurement target, and the distance of the near measurement target respectively meet the second specified requirement.

[0031] According to one aspect of the embodiments of this application, a data processing apparatus is provided, the apparatus comprising:

[0032] A signal transmitting module is configured to send a start signal to at least one of the sensor unit and the bus data acquisition unit, so that the sensor unit, upon receiving the start signal, acquires vehicle environment information and sends the vehicle environment information to the data integration unit; and the bus data acquisition unit, upon receiving the start signal, acquires vehicle status information and sends the vehicle status information to the data integration unit; the vehicle environment information is used to indicate the environment in which the vehicle is located, and the vehicle status information is used to indicate the status of the vehicle itself.

[0033] The information sending module is used to send at least one of the vehicle environment information and the vehicle status information to the data storage unit.

[0034] In some embodiments, the signal transmitting module is configured to receive a start command; the start command is configured to instruct the start of at least one subunit among the sensor unit and the bus data acquisition unit;

[0035] The signal transmitting module is used to determine a list to be started according to the start command; the list to be started includes at least one sub-unit to be started by the start command;

[0036] The signal sending module is used to send the start signal to at least one sub-unit in the list to be started.

[0037] In some embodiments, the start command is further used to indicate a specified start condition for at least one subunit of the sensor unit and the bus data acquisition unit; the specified start condition includes at least one of the following: the vehicle's position information meets a specified position condition, or a specified period is reached;

[0038] The signal sending module is used to send the start signal to at least one sub-unit in the list to be started when the specified start conditions are met.

[0039] In some embodiments, the information sending module is configured to perform detection processing on at least one of the vehicle environment information and the vehicle status information;

[0040] The information sending module is used to send at least one of the vehicle environment information and the vehicle status information to the data storage unit when at least one of the vehicle environment information and the vehicle status information is detected to meet a specified detection condition.

[0041] In some embodiments, the vehicle environment information includes at least one of the following: image data and point cloud data;

[0042] The vehicle status information includes at least one of the following: vehicle status parameters, distance and relative speed of a distant target, and distance of a nearby target;

[0043] The specified detection conditions include at least one of the following:

[0044] The difference between the timestamps corresponding to the image data and the point cloud data does not exceed a first specified threshold.

[0045] The repetition of objects in the projected point cloud data and the image data meets the first specified requirement;

[0046] The differences between the timestamps corresponding to the vehicle state parameters, the distance and relative speed of the distant measurement target, and the distance of the near measurement target do not exceed a second specified threshold.

[0047] The frame rates corresponding to the vehicle state parameters, the distance and relative speed of the distant measurement target, and the distance of the near measurement target respectively meet the second specified requirement.

[0048] According to one aspect of the embodiments of this application, a computer device is provided, the computer device including a processor and a memory, the memory storing a computer program, the computer program being loaded and executed by the processor to implement the above-described data processing method.

[0049] According to one aspect of the embodiments of this application, a computer-readable storage medium is provided, wherein a computer program is stored in the computer-readable storage medium, the computer program being loaded and executed by a processor to implement the above-described data processing method.

[0050] According to one aspect of the embodiments of this application, a computer program product is provided, the computer program product including a computer program, the computer program being loaded and executed by a processor to implement the above-described data processing method.

[0051] The technical solution provided in this application can bring the following beneficial effects:

[0052] The data integration unit initiates the control of the sensor unit or the data integration unit. Once started, the sensor unit or data integration unit can perform data acquisition tasks and send the acquired vehicle environmental information or vehicle status information to the data integration unit, which then stores the vehicle environmental information or vehicle status information in the data storage unit. The aforementioned data processing system provides a unified data acquisition platform, allowing personnel to drive vehicles equipped with the data processing system and complete the acquisition and storage of vehicle environmental information or vehicle status information through the operation of the data integration unit. This not only improves the efficiency of data acquisition but also enhances the management efficiency of each acquired data point. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a schematic diagram of an implementation environment provided by an exemplary embodiment of this application;

[0055] Figure 2 This is a flowchart of a data acquisition method provided in an exemplary embodiment of this application;

[0056] Figure 3 This is a schematic diagram of a data processing system provided in an exemplary embodiment of this application;

[0057] Figure 4 This is a flowchart of a data processing method provided in an exemplary embodiment of this application;

[0058] Figure 5 This is a schematic diagram of a modular multi-sensor autonomous driving data acquisition system provided in an exemplary embodiment of this application;

[0059] Figure 6 This is a flowchart of a modular multi-sensor autonomous driving data acquisition method provided in an exemplary embodiment of this application;

[0060] Figure 7 This is a block diagram of a data processing apparatus provided in an exemplary embodiment of this application;

[0061] Figure 8 This is a structural block diagram of a computer device provided in one embodiment of this application.

[0062] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. Detailed Implementation

[0063] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0064] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0065] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The singular forms “a,” “the,” and “the” as used in this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0066] In this application embodiment, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of relevant countries and regions.

[0067] It should be understood that although the terms first, second, etc., may be used in this disclosure to describe various information, such information should not be limited to these terms. These terms are used only to distinguish information of the same type from one another. For example, without departing from the scope of this disclosure, a first specified threshold may also be referred to as a second specified threshold, and similarly, a second specified threshold may also be referred to as a first specified threshold. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0068] First, let's introduce and explain several terms used in this application:

[0069] Intelligent driving technology combines advanced technologies such as AI algorithms, sensors, computer vision, radar, monitoring devices, and global positioning systems, enabling vehicles to autonomously complete driving tasks without driver intervention. The core process of autonomous driving technology can be divided into three main parts:

[0070] Environmental perception and positioning: This refers to acquiring information about the vehicle's surroundings through various sensors such as cameras, lidar, millimeter-wave radar, and ultrasonic sensors, and combining this information with high-precision maps and the Global Positioning System (GPS) for accurate positioning. These sensors help vehicles identify road signs, pedestrians, other vehicles, and other obstacles.

[0071] Decision-making and planning: Based on the collected information, the decision-making level needs to make reasonable judgments and plan the best driving route; the decision-making level also needs to consider factors such as safety, comfort and efficiency to ensure that every operation is the optimal solution;

[0072] Execution control: This is the process of translating decisions into actual actions, such as controlling the vehicle's acceleration, deceleration, and steering. This part of the work is done by the drive-by-wire system, which uses electrical signals instead of traditional mechanical connections to achieve more precise and smooth operation.

[0073] Please refer to Figure 1 This diagram illustrates an implementation environment provided by an exemplary embodiment of this application. Figure 1As shown, the implementation environment may include a vehicle 110 and a server 120. The vehicle 110 and the server 120 communicate with each other via a network. Optionally, the vehicle 110 and the server 120 may be directly or indirectly connected via wired or wireless communication; this application does not impose any limitations on this.

[0074] Vehicle 110 is equipped with various sensors and communication devices, enabling it to record and transmit important data such as road conditions, traffic flow, and weather conditions in real time. For example, to achieve remote monitoring and support subsequent data analysis, vehicle 110 can transmit important data such as road conditions, traffic flow, and weather conditions to server 120 via a network.

[0075] Optionally, vehicle 110 may be equipped with different types of sensors as needed, such as cameras, lidar, millimeter-wave radar, ultrasonic sensors, etc., and other types of sensors may also be installed; this application does not limit this. The sensors of vehicle 110 will be used to monitor dynamic changes around the vehicle, including the position of other vehicles, pedestrian activity, and the presence of obstacles. For example, vehicle 110 may use a CAN bus or other forms of internal network protocols to ensure stable communication between the various sensors and with the central processing unit, achieving efficient data exchange.

[0076] For example, vehicle 110 is a data collection vehicle (DCV).

[0077] Server 120 is used to provide backend services for vehicles 110. Optionally, server 120 is a single server, a server cluster or distributed system consisting of multiple servers, a cloud computing service center, or a cloud server, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, or content delivery network (CDN) that provides cloud computing services. Optionally, server 120 can provide backend services for multiple vehicles 110 simultaneously.

[0078] One data acquisition method involves developing each sensor module separately and then fusing the acquired data offline. Specifically, different data processing schemes are typically used for different models of LiDAR and millimeter-wave radar; for different camera models, the raw data is processed by an Image Signal Processor (ISP) and then converted to JPEG or NV12 format before acquisition. However, this data acquisition method results in low correlation between the modules.

[0079] Based on this, subsequent embodiments of this application provide a new data acquisition method, which is executed by the data integration unit of a data processing system installed in a vehicle. The data processing system also includes a sensor unit, a bus data acquisition unit, and a data storage unit connected to the data integration unit.

[0080] like Figure 2 As shown, upon receiving a start command, the data integration unit sends a start signal to at least one of the sensor unit and the bus data acquisition unit; wherein, the start command may be triggered by a person inside the vehicle through the data integration unit; or, it may be sent to the vehicle by the server through the network.

[0081] Accordingly, upon receiving the start signal, the sensor unit acquires vehicle environmental information and sends it to the data integration unit. The vehicle environmental information is used to indicate the environment in which the vehicle is located, such as image information and point cloud information.

[0082] Accordingly, upon receiving a start signal, the bus data acquisition unit acquires vehicle status information and sends the vehicle status information to the data integration unit. The vehicle status information is used to indicate the vehicle's own status, such as vehicle status parameters, distance and relative speed of the distant measurement target, and distance of the distant measurement target.

[0083] Subsequently, upon receiving vehicle environment information from the sensor unit and vehicle status information from the data integration unit, the data integration unit sends at least one of the vehicle environment information and vehicle status information to the data storage unit.

[0084] Please refer to Figure 3 This illustration shows a schematic diagram of a data processing system provided in an exemplary embodiment of this application. Optionally, the data processing system can be installed in a vehicle, for example, the vehicle is... Figure 1 Vehicle 110 in the system shown. (e.g.) Figure 3 As shown, the system may include a data integration unit 310, and a sensor unit 320, a bus data acquisition unit 330, and a data storage unit 340 connected to the data integration unit 310.

[0085] For example, sensor unit 320 can be connected to data integration unit 310 via Ethernet (ETH), bus data acquisition unit 330 can be connected to data integration unit 310 via Peripheral Component Interconnect Fast Standard (PCIE), and data storage unit 340 can be connected to data integration unit 310 via USB or ETH.

[0086] The data integration unit 310 is used to send a start signal to at least one of the sensor unit 320 and the bus data acquisition unit 330.

[0087] The data integration unit 310 is the core control node of the entire data processing system. When a data acquisition cycle needs to be started, the data integration unit 310 sends a start signal to at least one of the sensor unit 320 and the bus data acquisition unit 330.

[0088] For example, the aforementioned start signal can be a simple trigger pulse or a set of commands containing detailed parameter settings, such as sampling frequency, continuous monitoring within a specific time period, etc.

[0089] Optionally, the data integration unit 310 can be an industrial control computer (such as an IPC) installed with the vehicle's data acquisition system. An operator inside the vehicle can trigger a start command on the industrial control computer, which can instruct the sending of a start signal to at least one of the sensor unit 320 and the bus data acquisition unit 330.

[0090] Optionally, the server can send a remote start command to the data integration unit 310 via a network, which can instruct the sending of a start signal to at least one of the sensor unit 320 and the bus data acquisition unit 330.

[0091] The sensor unit 320 is used to acquire vehicle environment information and send the vehicle environment information to the data integration unit 310 when it receives a start signal sent by the data integration unit 310; the vehicle environment information is used to indicate the environment in which the vehicle is located.

[0092] Upon receiving the start signal from the data integration unit 310, the sensor unit 320 begins operation, using its built-in sensing devices (such as cameras and lidar) to collect information about the vehicle's surrounding environment. Once data acquisition is complete, the sensor unit 320 can package the collected vehicle environment information and send it back to the data integration unit 310 through an appropriate communication interface.

[0093] For example, sensor unit 320 includes at least one of the following: a camera subunit, a lidar subunit, and a Precise Time Protocol (PTP) subunit, and may also include other subunits, which are not limited in this application. Accordingly, the above-mentioned vehicle environment information may include at least one of the following: image information acquired by the camera subunit and point cloud information acquired by the lidar subunit. PTP is a time synchronization device that aligns the timestamps of the image data and the point cloud data.

[0094] The camera subunit includes a camera mounted on the vehicle to capture visual information. Optionally, the camera can be a monocular, binocular, or tri-lens camera, or even a surround-view camera. The main function of the camera subunit is to identify road signs, lane lines, pedestrians, and other obstacles using image processing algorithms.

[0095] The lidar subunit includes a lidar radar (LiDAR) mounted on the vehicle. LiDAR is a radar system that uses a laser beam to detect characteristics such as the target's position and velocity. Its working principle involves emitting a detection signal (laser beam) towards the target, receiving the signal reflected back from the target, comparing the two, and processing the data to obtain relevant target information. LiDAR features high resolution and accuracy, enabling it to generate precise 3D point cloud maps in complex environments, which is crucial for constructing detailed environmental models.

[0096] The Precision Time Protocol (PTP) subunit provides precise time synchronization services over the network. This helps eliminate time discrepancies caused by differences in the internal clocks of individual sensors, thereby improving the reliability and accuracy of the entire system.

[0097] The bus data acquisition unit 330 is used to acquire vehicle status information and send the vehicle status information to the data integration unit 310 when it receives a start signal sent by the data integration unit 310; the vehicle status information is used to indicate the vehicle's own status.

[0098] Upon receiving the start signal from the data integration unit 310, the bus data acquisition unit 330 begins operation, capturing information related to the vehicle's own operating status by reading status reports from various electronic control units (ECUs) connected to the vehicle network. Once data acquisition is complete, the bus data acquisition unit 330 can package the acquired vehicle status information and send it back to the data integration unit 310 through an appropriate communication interface.

[0099] For example, the bus data acquisition unit 330 includes at least one of the following: a body CAN subunit, a millimeter-wave radar subunit, and an ultrasonic sensor subunit, and may also include other subunits, which are not limited in this application. Accordingly, the above-mentioned vehicle status information may include at least one of the following: vehicle status parameters acquired by the body CAN subunit, the distance and relative speed of the long-range measurement target acquired by the millimeter-wave radar subunit, and the distance of the short-range measurement target acquired by the ultrasonic sensor subunit. Among them, the vehicle status parameters include engine performance indicators, vehicle speed, throttle opening, brake pressure, etc., and the long-range measurement target and the short-range measurement target refer to obstacles (such as other vehicles) encountered by the vehicle during driving.

[0100] Among them, the body CAN subunit uses a serial communication protocol to connect various electronic control units (ECUs) inside the vehicle, enabling them to exchange information efficiently.

[0101] The millimeter-wave radar subunit includes a millimeter-wave radar installed on the vehicle. Millimeter-wave radar uses high-frequency signals within the radio wave band for distance measurement and velocity estimation. Compared to lidar, millimeter-wave radar has better penetration in adverse weather conditions (such as rain, snow, and fog), making it ideal as an all-weather sensor.

[0102] The ultrasonic sensor subunit includes ultrasonic sensors installed on the vehicle. Ultrasonic sensors are primarily used for short-range detection tasks, such as reversing radar in parking assistance systems. When a vehicle approaches an obstacle, the ultrasonic sensor emits sound waves and waits for the echo to return, thereby calculating the relative distance between the two.

[0103] The data integration unit 310 is used to send at least one of vehicle environment information and vehicle status information to the data storage unit 340.

[0104] For example, after receiving vehicle environment information from sensor unit 320 and vehicle status information from bus data acquisition unit 330, data integration unit 310 can perform preliminary cleaning, conversion, and format standardization processing on the vehicle environment information and vehicle status information to eliminate inconsistencies between data. The processed environment information and / or vehicle status information will be further packaged into a format suitable for long-term storage and sent to a dedicated dataset storage unit 340 for storage.

[0105] Optionally, the data storage unit 340 includes at least one of the following: a solid-state drive (SSD) subunit, a network-attached storage (NAS) subunit, and may also include other subunits, which are not limited in this application. Accordingly, the data integration unit 310 can send at least one of vehicle environmental information and vehicle status information to the SSD subunit of the data storage unit 340 via USB; the data integration unit 310 can also send at least one of vehicle environmental information and vehicle status information to the NAS subunit of the data storage unit 340 via Ethernet.

[0106] For example, during the process of sending at least one of vehicle environment information and vehicle status information to the data storage unit 340, the data integration unit 310 may carry a scene tag during the transmission. This scene tag refers to the data scene in which the vehicle environment information and vehicle status information are currently being collected. For example, the scene tag could be sunny, rainy, highway, etc. Optionally, the scene tag can be added manually or automatically by the data integration unit 310. Specifically, for example, the data integration unit 310 can use an image recognition algorithm to obtain the scene tag of the vehicle environment information and the vehicle status information within the same time period as the vehicle environment information based on the image information in the vehicle environment information.

[0107] In summary, the technical solution provided in this application embodiment starts the sensor unit or data integration unit through the data integration unit. After starting, the sensor unit or data integration unit can perform data acquisition tasks and send the acquired vehicle environment information or vehicle status information to the data integration unit, which then stores the vehicle environment information or vehicle status information in the data storage unit. The above-mentioned data processing system provides a unified data acquisition platform. The acquisition personnel can drive vehicles equipped with the data processing system and complete the acquisition and storage of vehicle environment information or vehicle status information through the operation of the data integration unit. This not only improves the efficiency of data acquisition but also improves the management efficiency of each acquired data.

[0108] Based on the above Figure 3 In one possible implementation of the scheme in the illustrated embodiment, the data integration unit 310 is used to receive a start command; the start command is used to instruct the start of at least one sub-unit among the sensor unit 320 and the bus data acquisition unit 330.

[0109] The data integration unit 310 is used to determine a list to be started based on the startup instruction; the list to be started includes at least one sub-unit to be started as indicated by the startup instruction.

[0110] The data integration unit 310 is used to send a start signal to at least one sub-unit in the list to be started.

[0111] The aforementioned start command includes at least one of the following: a remote command from the server, a trigger command from inside the vehicle, and may also include other types of commands, which are not limited in this application.

[0112] Once a start command is received, the data integration unit 310 can parse the start command through its internal logic module to extract key parameters, such as the identifier of the sub-unit and the expected operating mode. Then, based on the parsing results, the data integration unit 310 can determine a list of sub-units to be started, which lists all sub-units that need to respond to this start command.

[0113] Optionally, the list of sub-units to be started not only specifies which sub-units should be started, but may also include additional configuration options, such as sampling rate, duty cycle, and other settings.

[0114] Once the list of units to be activated is determined, the next task of the data integration unit 310 is to send activation signals to each sub-unit listed on the list. For example, if the list includes the camera sub-unit in the sensor unit 320, this means that the camera sub-unit will begin environmental photography.

[0115] In this embodiment, the data integration unit can send a start signal to at least one subunit among the sensor unit to be started and the bus data acquisition unit according to the received start command; that is, this application can specify the subunit to be started through the start command, thereby realizing the switching of acquisition mode, improving the flexibility of data acquisition and reducing operating costs.

[0116] Based on the solutions in the above embodiments of this application, in one possible implementation, the start command is further used to indicate a specified start condition for at least one subunit of the sensor unit 320 and the bus data acquisition unit 330; the specified start condition includes at least one of the following: the vehicle's position information meets the specified position condition, or a specified period is reached.

[0117] The data integration unit 310 is used to send a start signal to at least one sub-unit in the list to be started when specified start conditions are met.

[0118] In other words, in addition to identifying the sub-unit to be started, the above startup instructions can also carry additional information, namely, specifying the startup conditions.

[0119] The aforementioned vehicle location information meeting the specified location conditions refers to the vehicle traveling to a specified location. For example, the vehicle location information meeting the specified location conditions could be when the vehicle enters a preset geofence area; or when it is near a specific location (such as a parking lot entrance or a highway toll station).

[0120] Optionally, the data integration unit 310 can utilize vehicle CAN data, such as vehicle speed and distance traveled, in conjunction with positioning equipment and algorithms to complete high-precision vehicle positioning in order to obtain the aforementioned vehicle location information.

[0121] The aforementioned arrival time period can be a fixed time interval, such as once per hour; or a specific date, such as the first day of each month; or an event-driven time point, such as 5 minutes after the engine starts.

[0122] In this embodiment, the data integration unit can send a start signal to at least one subunit among the sensor unit and bus data acquisition unit to be started, based on the received start command and under specified start conditions. In other words, this application can specify the start conditions of the subunit to be started through the start command, such as the vehicle arriving at a specified location or reaching a specified period, thereby enabling the pre-setting of the acquisition mode, improving the flexibility of data acquisition, and reducing operating costs.

[0123] Based on the solutions in the above embodiments of this application, in one possible implementation, the data integration unit 310 is used to perform detection processing on at least one of vehicle environment information and vehicle status information.

[0124] The data integration unit 310 is used to send at least one of the vehicle environment information and vehicle status information to the data storage unit 340 when at least one of the vehicle environment information and vehicle status information is detected to meet the specified detection conditions.

[0125] The data integration unit 310 can create a database table or file structure to store at least one corresponding detection item from vehicle environment information and vehicle status information, as well as the specified detection conditions for each detection item.

[0126] Accordingly, upon receiving at least one of vehicle environment information and vehicle status information, the data integration unit 310 can perform detection processing on at least one of the vehicle environment information and vehicle status information according to the corresponding detection items in the database table or file structure; and send the vehicle environment information and vehicle status information that meet the specified detection conditions to the data storage unit 340.

[0127] This application embodiment shows that before sending data to the data storage unit, the data integration unit first detects the received data, and then sends the data that meets the detection conditions to the data storage unit; that is, the above-mentioned data processing system can collect vehicle environment information and vehicle status information that meet the quality conditions required by the autonomous driving system, avoid sending and storing unnecessary data, and thus improve the accuracy and availability of data collection.

[0128] Based on the solutions in the above embodiments of this application, in one possible implementation, the vehicle environment information includes at least one of the following: image data and point cloud data;

[0129] Vehicle status information includes at least one of the following: vehicle status parameters, distance and relative speed of the distant target, and distance of the distant target;

[0130] The specified detection conditions include at least one of the following:

[0131] The difference between the timestamps corresponding to the image data and the point cloud data shall not exceed a first specified threshold.

[0132] The redundancy between the projected point cloud data and the objects in the image data meets the first specified requirement;

[0133] The difference between the timestamps corresponding to the vehicle status parameters, the distance and relative speed of the distant target, and the distance of the nearby target does not exceed a second specified threshold.

[0134] The frame rates corresponding to the vehicle status parameters, the distance and relative speed of the distant target, and the distance of the nearby target respectively meet the second specified requirement.

[0135] The image data mentioned above is captured by the camera subunit and can provide rich visual information to help identify other vehicles, pedestrians, traffic signs, etc. on the road; the point cloud data mentioned above comes from the LiDAR subunit and is used to build a three-dimensional environment model to accurately describe the position and shape of surrounding objects.

[0136] The vehicle status parameters mentioned above are derived from the vehicle's CAN subunit and may include vehicle speed, acceleration, steering angle, etc. The distance and relative speed of long-range targets are measured by millimeter-wave radar, while the distance of short-range targets is measured by ultrasonic sensors.

[0137] The first specified threshold, the first specified requirement, the second specified threshold, and the second specified requirement are preset in the data integration unit 310.

[0138] Specifically, the difference between the timestamps corresponding to the image data and the point cloud data shall not exceed a first specified threshold. This means that when image data and the corresponding point cloud data are acquired simultaneously, the time difference between them should be very small. For example, this first specified threshold is in milliseconds; specifically, the difference between the timestamps corresponding to the image data and the point cloud data shall not exceed 100ms. This requirement ensures that the two different types of data can reflect the same environmental state at almost the same time, thereby improving the quality of the acquired data.

[0139] Among these methods, detecting the redundancy between the projected point cloud data and the objects in the image data verifies whether the point cloud data, after being projected onto the two-dimensional image plane, can form a good match with the objects in the image. If the redundancy between the projected point cloud data and the objects in the image data meets the first specified requirement, each point in the point cloud should have a corresponding pixel location, and the distribution of these points on the image should match the actual object contour, which helps to confirm the consistency of multi-sensor data.

[0140] The data integration unit 310 also needs to consider the synchronization between vehicle state parameters and other sensor data. The differences between the timestamps corresponding to the aforementioned vehicle state parameters, the distance and relative speed of the distant target, and the distance of the nearby target do not exceed a second specified threshold. This ensures that the timestamp differences of all relevant data streams remain within a small range, thus avoiding erroneous judgments due to time deviations.

[0141] To maintain stable perception performance, the data integration unit 310 monitors the update frequency (i.e., frame rate) of vehicle state parameters, distance and relative speed of distant targets, and distance of nearby targets. If the frame rate of a subunit's output data is too low, information loss may occur; conversely, if the frame rate is too high, it may increase the computational burden. Therefore, ensuring that the frame rates corresponding to the aforementioned vehicle state parameters, distance and relative speed of distant targets, and distance of nearby targets meet the second specified requirement guarantees the efficient operation of the data processing system.

[0142] This application embodiment illustrates the specific information of the aforementioned vehicle environment information and vehicle status information, and clarifies the detection content for detecting the aforementioned vehicle environment information and vehicle status information, such as time synchronization, to further improve the accuracy and availability of data collection.

[0143] Please refer to Figure 4 The diagram illustrates a flowchart of a data processing method provided in an exemplary embodiment of this application. The method is executed by a data integration unit of a data processing system; optionally, the data processing system may be... Figure 3 The data processing system shown. (For example...) Figure 4 As shown, the method may include steps 410 to 420.

[0144] Step 410: Send a start signal to at least one of the sensor unit and the bus data acquisition unit, so that the sensor unit can acquire vehicle environment information and send the vehicle environment information to the data integration unit upon receiving the start signal; and the bus data acquisition unit can acquire vehicle status information and send the vehicle status information to the data integration unit upon receiving the start signal; the vehicle environment information is used to indicate the environment in which the vehicle is located, and the vehicle status information is used to indicate the status of the vehicle itself.

[0145] Step 420: Send at least one of the vehicle environment information and vehicle status information to the data storage unit.

[0146] It should be noted that the above Figure 4 The method provided in the embodiments is the same as that described above. Figure 3 The systems provided in the embodiments belong to the same concept, and their specific implementation process can be found in the system embodiments, which will not be repeated here.

[0147] Based on the solutions shown in the above embodiments, this application proposes a multi-sensor modular autonomous driving data acquisition system, including low-level data access from multiple sensors, coupling between different modules, and integration and expansion of the entire system, aiming to solve the following problems:

[0148] The data acquisition solutions for different models of lidar and millimeter-wave radar vary greatly, lack platformization, and are difficult to expand and manage.

[0149] Mainstream camera data formats require a large amount of space, and acquisition solutions have high resource requirements, such as storage space and computing power.

[0150] The positioning accuracy of ordinary GPS systems is not high, which makes it difficult to meet the high-precision positioning requirements of autonomous driving, and at the same time, it does not provide an effective means of determining positioning accuracy.

[0151] The entire autonomous driving data acquisition system was not tightly coupled, and the time synchronization of each module could not be effectively confirmed, thus failing to leverage the complementary advantages of multiple modules.

[0152] Please refer to Figure 5 This illustrates a schematic diagram of a modular multi-sensor autonomous driving data acquisition system provided in an exemplary embodiment of this application. Figure 5 As shown, the multi-sensor modular autonomous driving data acquisition system includes four modules: a sensor module, a CAN module, an industrial personal computer (IPC) module, and a data storage module.

[0153] The camera is connected to the Electronic Control Unit (ECU) via a Gigabit Multimedia Serial Link (GMSL). Sensors and camera data encoding modules such as LiDAR, ECU, and Precision Time Protocol (PTP) are connected to the switch via Ethernet (ETH), and then to the IPC module via ETH. Modules such as millimeter-wave radar, vehicle CAN, and ultrasonic sensor (USS) are connected to the CAN hardware connector via the Controller Area Network (CAN) interface, and then to the IPC module via Peripheral Component Interconnect Express (PCIE).

[0154] The data storage modules include solid-state drives (SSDs) and network-attached storage (NAS).

[0155] The IPC module deploys the data acquisition system, integrates sensor data, and monitors the operating status of each module.

[0156] Sensor data processing, such as image compression and timestamp conversion, can be deployed on the IPC side. Simultaneously, it monitors whether the data meets requirements, such as camera image quality and timestamp alignment. A unified data acquisition program can also be deployed on the IPC side, receiving user commands to start, pause / resume, and stop acquisition, and writing the required data to the storage module. For example, the IPC module's user interface (UI) displays trigger controls for Start, Pause / Resume, Stop, Camera Monitor, Lidar Monitor, and Time Sync Monitor.

[0157] Users can select the required sensors, such as LiDAR and millimeter-wave radar, in the IPC module's UI based on their autonomous driving data needs, and connect them to the IPC module via Ethernet or CAN interface. The IPC module can store data to an SSD via Universal Serial Bus (USB) or to a NAS via Ethereum. The data storage module can parse the collected data and provide it to the algorithm module for data analysis, model training, and other purposes.

[0158] Please refer to Figure 6 This illustrates a flowchart of a modular multi-sensor autonomous driving data acquisition method provided in an exemplary embodiment of this application. Figure 6 As shown, the above-mentioned modular multi-sensor autonomous driving data acquisition method includes the following steps:

[0159] Step 601, Mount the NAS server:

[0160] In this process, users click the "Mount NAS" button on the front end of the data acquisition system, and the background calls the mounting service to complete the storage module configuration.

[0161] Step 602, Start the background service:

[0162] In this system, when a user clicks the "Start Service" button on the front end of the data acquisition system, a script is called in the background to start all sensor services.

[0163] Step 603: Establish connection between front-end and back-end:

[0164] The front-end and back-end communicate using the WebSocket protocol.

[0165] Step 604, System Status and Image Detection Display:

[0166] When a user clicks the monitoring button on the front end of the data acquisition system, a system status display window pops up to show the system status in real time, and a camera image display window pops up to show the camera images in real time.

[0167] Step 605, check the validity of the data:

[0168] In this process, the user clicks the detection button on the front end of the data acquisition system, and the background collects sensor data to generate detection data and calls the detection program to determine whether the data meets the requirements.

[0169] Step 606, Start / Pause Data Collection:

[0170] In this process, the user clicks the "Start Data Acquisition" button on the front end of the data acquisition system, and the background program starts the data acquisition process to write the sensor data to the storage unit.

[0171] In this system, users can click the start / pause button on the front end of the data acquisition system and then close the data disk storage service in the background.

[0172] Step 607: Stop data collection and exit:

[0173] In this system, users can click the "Stop Data Acquisition" button in the foreground of the data acquisition system to close the data acquisition program and data disk storage service in the background.

[0174] In this process, the user stops the background service of the data collection system to complete the data collection process.

[0175] In summary, the above system generates data using sensors such as cameras and radar, completes data acquisition and interaction through software deployment on IPC devices, and stores data using NAS or SSD devices. The system divides autonomous driving sensors into different modules and provides a unified integrated management platform based on QT, which can flexibly adjust the data acquisition scheme and monitor data quality according to actual needs.

[0176] On the one hand, it provides a unified data acquisition platform that can not only collect sensor data of different specifications and meeting quality requirements from cameras, LiDAR, and Radar sensors needed for autonomous driving systems, but also achieve tight coupling between various sensor modules, improving data availability through time synchronization and dynamic / static data projection. On the other hand, it can also provide scene labels for the data during the data acquisition process, thereby ensuring high efficiency in data mining training of algorithm modules. Therefore, this application can improve system stability and scalability, providing data acquisition flexibility through sensor adjustment and acquisition mode switching, and reducing operating costs.

[0177] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0178] Please refer to Figure 7 This diagram illustrates a block diagram of a data processing apparatus provided in an exemplary embodiment of this application. The apparatus has the functions to implement the above examples, which can be implemented in hardware or by hardware executing corresponding software. Figure 7 As shown, the device may include a signal transmission module 701 and an information transmission module 702.

[0179] The signal transmitting module 701 is used to send a start signal to at least one of the sensor unit and the bus data acquisition unit, so that the sensor unit can acquire vehicle environment information and send the vehicle environment information to the data integration unit when it receives the start signal; and the bus data acquisition unit can acquire vehicle status information and send the vehicle status information to the data integration unit when it receives the start signal; the vehicle environment information is used to indicate the environment in which the vehicle is located, and the vehicle status information is used to indicate the status of the vehicle itself.

[0180] The information sending module 702 is used to send at least one of vehicle environmental information and vehicle status information to the data storage unit.

[0181] In some embodiments, the signal transmitting module 701 is configured to receive a start command; the start command is configured to instruct the start of at least one subunit among the sensor unit and the bus data acquisition unit.

[0182] The signal transmitting module 701 is used to determine a list to be started according to the start command; the list to be started contains at least one sub-unit to be started by the start command;

[0183] The signal sending module 701 is used to send a start signal to at least one sub-unit in the list to be started.

[0184] In some embodiments, the start command is further used to indicate a specified start condition for at least one subunit among the sensor unit and the bus data acquisition unit; the specified start condition includes at least one of the following: the vehicle's position information meets a specified position condition, or a specified period is reached;

[0185] The signal sending module 701 is used to send a start signal to at least one sub-unit in the list to be started when specified start conditions are met.

[0186] In some embodiments, the information sending module 702 is used to perform detection processing on at least one of vehicle environment information and vehicle status information;

[0187] The information sending module 702 is used to send at least one of the vehicle environment information and vehicle status information to the data storage unit when at least one of the vehicle environment information and vehicle status information is detected to meet the specified detection conditions.

[0188] In some embodiments, vehicle environmental information includes at least one of the following: image data and point cloud data;

[0189] Vehicle status information includes at least one of the following: vehicle status parameters, distance and relative speed of distant targets, and distance of nearby targets;

[0190] The specified detection conditions include at least one of the following:

[0191] The difference between the timestamps corresponding to the image data and the point cloud data shall not exceed a first specified threshold.

[0192] The redundancy between the projected point cloud data and the objects in the image data meets the first specified requirement;

[0193] The difference between the timestamps corresponding to the vehicle status parameters, the distance and relative speed of the distant target, and the distance of the nearby target does not exceed a second specified threshold.

[0194] The frame rates corresponding to the vehicle status parameters, the distance and relative speed of the distant target, and the distance of the nearby target respectively meet the second specified requirement.

[0195] It should be noted that the apparatus provided in the above embodiments is only illustrated by the division of the above functional modules when implementing its functions. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the content structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0196] Please refer to Figure 8 This diagram illustrates a structural block diagram of a computer device according to an embodiment of this application. The computer device 800 can be any electronic device capable of data computation, processing, and storage. The computer device 800 can be used to implement the data processing methods provided in the above embodiments.

[0197] Typically, computer device 800 includes a processor 801 and a memory 802.

[0198] Processor 801 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 801 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field Programmable Gate Array), and PLA (Programmable Logic Array). Processor 801 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 801 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 801 may also include an Artificial Intelligence (AI) processor, which is used to handle computational operations related to machine learning.

[0199] The memory 802 may include one or more computer-readable storage media, which may be non-transitory. The memory 802 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 802 are used to store a computer program configured to be executed by one or more processors to implement the data processing method described above.

[0200] Those skilled in the art will understand that Figure 8 The structure shown does not constitute a limitation on the computer device 800, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0201] In an exemplary embodiment, a computer-readable storage medium is also provided, wherein a computer program is stored in the storage medium, and the computer program, when executed by a processor, implements the above-described data processing method. Optionally, the computer-readable storage medium may include: ROM (Read-Only Memory), RAM (Random Access Memory), SSD (Solid State Drives), or optical disc, etc. The random access memory may include ReRAM (Resistance Random Access Memory) and DRAM (Dynamic Random Access Memory).

[0202] In an exemplary embodiment, a computer program product is also provided, the computer program product including a computer program stored in a computer-readable storage medium. A processor of a computer device reads the computer program from the computer-readable storage medium, and the processor executes the computer program, causing the computer device to perform the data processing method described above.

[0203] It should be understood that "multiple" as used herein refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. Furthermore, the step numbers described herein are merely illustrative of one possible execution order. In some other embodiments, the steps may not be executed in numerical order, such as two steps with different numbers being executed simultaneously, or two steps with different numbers being executed in the reverse order of the illustration. This application does not limit this.

[0204] The above description is merely an exemplary embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A data processing system, characterized in that, The system includes: a data integration unit, and a sensor unit, a bus data acquisition unit, and a data storage unit connected to the data integration unit; The data integration unit is used to send a start signal to at least one of the sensor unit and the bus data acquisition unit; The sensor unit is configured to acquire vehicle environment information and send the vehicle environment information to the data integration unit upon receiving the start signal from the data integration unit; the vehicle environment information includes at least one of the following: image data and point cloud data. The bus data acquisition unit is used to acquire vehicle status information and send the vehicle status information to the data integration unit when it receives the start signal sent by the data integration unit; the vehicle status information includes at least one of the following: vehicle status parameters, distance and relative speed of a distant target, and distance of a nearby target; The data integration unit is configured to send at least one of the vehicle environment information and the vehicle status information to the data storage unit when at least one of the vehicle environment information and the vehicle status information meets a specified detection condition; the specified detection condition includes at least one of the following: The difference between the timestamps corresponding to the image data and the point cloud data does not exceed a first specified threshold. The repetition of objects in the projected point cloud data and the image data meets the first specified requirement; The differences between the timestamps corresponding to the vehicle state parameters, the distance and relative speed of the distant measurement target, and the distance of the near measurement target do not exceed a second specified threshold. The frame rates corresponding to the vehicle state parameters, the distance and relative speed of the distant measurement target, and the distance of the near measurement target respectively meet the second specified requirement.

2. The system according to claim 1, characterized in that, The data integration unit is used to receive a start command; the start command is used to instruct at least one subunit of the sensor unit and the bus data acquisition unit to start. The data integration unit is configured to determine a list of units to be started based on the startup instruction; the list of units to be started includes at least one sub-unit to be started as indicated by the startup instruction. The data integration unit is used to send the start signal to at least one sub-unit in the list to be started.

3. The system according to claim 2, characterized in that, The start command is also used to indicate a specified start condition for at least one subunit of the sensor unit and the bus data acquisition unit; the specified start condition includes at least one of the following: the vehicle's position information meets a specified position condition, or a specified period is reached; The data integration unit is used to send the start signal to at least one sub-unit in the list to be started when the specified start conditions are met.

4. A data processing method, characterized in that, The method is executed by a data integration unit of a data processing system, which further includes a sensor unit, a bus data acquisition unit, and a data storage unit connected to the data integration unit. The method includes: A start signal is sent to at least one of the sensor unit and the bus data acquisition unit, so that the sensor unit, upon receiving the start signal, acquires vehicle environment information and sends the vehicle environment information to the data integration unit; and the bus data acquisition unit, upon receiving the start signal, acquires vehicle status information and sends the vehicle status information to the data integration unit; the vehicle environment information includes at least one of the following: image data and point cloud data, and the vehicle status information includes at least one of the following: vehicle status parameters, distance and relative speed of a distant target, and distance of a nearby target; If at least one of the vehicle environment information and the vehicle status information meets a specified detection condition, at least one of the vehicle environment information and the vehicle status information is sent to the data storage unit; the specified detection condition includes at least one of the following: The difference between the timestamps corresponding to the image data and the point cloud data does not exceed a first specified threshold. The repetition of objects in the projected point cloud data and the image data meets the first specified requirement; The differences between the timestamps corresponding to the vehicle state parameters, the distance and relative speed of the distant measurement target, and the distance of the near measurement target do not exceed a second specified threshold. The frame rates corresponding to the vehicle state parameters, the distance and relative speed of the distant measurement target, and the distance of the near measurement target respectively meet the second specified requirement.

5. A data processing apparatus, characterized in that, The device includes: A signal transmitting module is configured to send a start signal to at least one of a sensor unit and a bus data acquisition unit, so that the sensor unit, upon receiving the start signal, acquires vehicle environmental information and sends the vehicle environmental information to a data integration unit; and the bus data acquisition unit, upon receiving the start signal, acquires vehicle status information and sends the vehicle status information to the data integration unit; the vehicle environmental information includes at least one of the following: image data and point cloud data; the vehicle status information includes at least one of the following: vehicle status parameters, distance and relative speed of a distant target, and distance of a nearby target; The information sending module is configured to send at least one of the vehicle environment information and the vehicle status information to the data storage unit when at least one of the vehicle environment information and the vehicle status information meets a specified detection condition; the specified detection condition includes at least one of the following: The difference between the timestamps corresponding to the image data and the point cloud data does not exceed a first specified threshold. The repetition of objects in the projected point cloud data and the image data meets the first specified requirement; The differences between the timestamps corresponding to the vehicle state parameters, the distance and relative speed of the distant measurement target, and the distance of the near measurement target do not exceed a second specified threshold. The frame rates corresponding to the vehicle state parameters, the distance and relative speed of the distant measurement target, and the distance of the near measurement target respectively meet the second specified requirement.

6. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing a computer program, which is loaded and executed by the processor to implement the data processing method as described in claim 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which is loaded and executed by a processor to implement the data processing method as described in claim 4.

8. A computer program product, characterized in that, The computer program product includes a computer program stored in a computer-readable storage medium, and a processor reads from and executes the computer program to implement the data processing method as described in claim 4.

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