Data processing method and device, electronic equipment and readable storage medium

Abstract

The invention relates to the technical field of data processing, and provides a data processing method and device, electronic equipment and a readable storage medium. The method comprises the following steps: acquiring vehicle track data and environment data; carrying out data processing on the vehicle trajectory data to obtain all trajectory data sets; determining positioning data of the vehicle, selecting at least one piece of local trajectory data from all the trajectory data sets as target trajectory data, and determining target positioning data from the positioning data by using the target trajectory data; and decomposing the environment data by using the target trajectory data and the target positioning data to obtain local environment data. According to the method and the device, the required local data can be adaptively processed, so that the data processing efficiency and the user experience are improved, and the problems of low efficiency and long time consumption caused by full-amount processing of the vehicle acquisition data in the prior art are solved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a data processing method, device, electronic device and readable storage medium. Background Art

[0002] With the increase in the number of vehicles and the continuous advancement of computer network technology, vehicles are becoming more and more intelligent. In the current vehicle data processing process, the collected vehicle data needs to be processed to generate panoramic image data, CCD image data and laser point cloud data to provide support for subsequent user operations and vehicle execution. However, as more and more laser devices and imaging devices are configured on vehicles, the amount of data collected has also increased dramatically. In particular, the greater the number of kilometers that a vehicle collects data, the more data collected increases. The use of existing data processing methods will inevitably lead to a significant increase in processing time and a significant increase in the consumption of computing resources. Summary of the invention

[0003] In view of this, the embodiments of the present application provide a data processing method, device, electronic device and readable storage medium to solve the technical problems of low efficiency and long time consumption in processing vehicle collected data in the prior art.

[0004] In a first aspect of an embodiment of the present application, a data processing method is provided, the method comprising:

[0005] Acquire vehicle trajectory data and environmental data; perform data processing on the vehicle trajectory data to obtain a complete trajectory data set, wherein the complete trajectory data set includes a plurality of local trajectory data, each of the local trajectory data represents a driving trajectory of the vehicle in a corresponding area; determine the positioning data of the vehicle, select at least one local trajectory data from the complete trajectory data set as target trajectory data, and use the target trajectory data to determine the target positioning data from the positioning data; use the target trajectory data and the target positioning data to decompose the environmental data to obtain local environmental data.

[0006] According to a second aspect of the present application, a data processing device is provided. The method includes:

[0007] The acquisition module is configured to acquire vehicle trajectory data and environmental data; the processing module is configured to perform data processing on the vehicle trajectory data to obtain a complete trajectory data set, wherein the complete trajectory data set includes a plurality of local trajectory data, and each local trajectory data represents a driving trajectory of the vehicle in a corresponding area; the determination module is configured to determine the positioning data of the vehicle, select at least one local trajectory data from the complete trajectory data set as target trajectory data, and determine the target positioning data from the positioning data using the target trajectory data; the decomposition module is configured to decompose the environmental data using the target trajectory data and the target positioning data to obtain local environmental data.

[0008] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0009] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0010] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0011] The method in the embodiment of the present application obtains vehicle trajectory data and environmental data; processes the vehicle trajectory data to obtain a complete trajectory data set, wherein the complete trajectory data set includes multiple local trajectory data, and each local trajectory data represents the driving trajectory of the vehicle in the corresponding area; determines the vehicle's positioning data, selects at least one local trajectory data from the complete trajectory data set as the target trajectory data, and uses the target trajectory data to determine the target positioning data from the positioning data; uses the target trajectory data and the target positioning data to decompose the environmental data to obtain local environmental data. In this way, it is only necessary to determine the complete trajectory data set of the vehicle trajectory data, and then determine the range of the data to be processed from the complete trajectory data set, and at the same time determine the target positioning data corresponding to the selected range, so that the required local data can be processed adaptively, thereby improving data processing efficiency and user experience, and avoiding the problems of low efficiency and long time consumption caused by the full processing of vehicle collection data in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0013] Figure 1 It is a flowchart of a data processing method provided in an embodiment of the present application;

[0014] Figure 2 It is a flowchart of another data processing method provided in an embodiment of the present application;

[0015] Figure 3 is a structural schematic diagram of a data processing device provided in an embodiment of the present application;

[0016] Figure 4 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0018] A data processing method, device, electronic device, and readable storage medium according to an embodiment of the present application will be described in detail below with reference to the accompanying drawings.

[0019] Figure 1 is a flow chart of a data processing method provided in an embodiment of the present application. Figure 1 As shown, the method includes:

[0020] S101, obtaining vehicle trajectory data and environment data;

[0021] S102, performing data processing on the vehicle trajectory data to obtain a complete trajectory data set, wherein the complete trajectory data set includes a plurality of local trajectory data, each of which represents a driving trajectory of the vehicle in a corresponding area;

[0022] S103, determining the positioning data of the vehicle, selecting at least one local trajectory data from the entire trajectory data set as target trajectory data, and determining target positioning data from the positioning data using the target trajectory data;

[0023] S104, decomposing the environmental data using the target trajectory data and the target positioning data to obtain local environmental data.

[0024] It can be understood that the above-mentioned data processing method provided in this example is applied to the data processing system of vehicles, and the above-mentioned vehicles include vehicles with automatic driving or intelligent driving (including vehicles with manned functions (such as cars, buses, large buses, minibuses, etc.), vehicles with cargo functions (such as ordinary trucks, vans, trailers, closed trucks, tank trucks, flatbed trucks, container trucks, dump trucks, trucks with special structures), special vehicles (such as logistics distribution vehicles, automatic guided transport vehicles AGV, patrol cars, cranes, cranes, excavators, bulldozers, forklifts, rollers, loaders, off-road engineering vehicles, armored engineering vehicles, sewage treatment vehicles, sanitation vehicles, vacuum trucks, floor washing vehicles, sprinkler trucks, sweeping robots, food delivery robots, shopping guide robots, lawn mowers, golf carts, etc.), vehicles with entertainment functions (such as entertainment vehicles, amusement park automatic driving devices, balance cars, etc.), rescue vehicles (such as fire trucks, ambulances, power repair vehicles, engineering rescue vehicles, etc.)), etc.

[0025] Among them, the above-mentioned vehicle trajectory data and environmental data are the initial collection data of the vehicle, which are collected by the vehicle in real time. Exemplarily, the vehicle trajectory data and environmental data collected by the vehicle are stored in the storage medium in the vehicle. The files storing the vehicle trajectory data include but are not limited to Project (engineering information), Para (camera parameters), and Sync (synchronizer information), etc., and the files storing the environmental data include but are not limited to Image (CCD image data), Laser (point cloud data) and Panorama (panoramic image data), etc.

[0026] It can be understood that the entire trajectory data set is obtained by processing the vehicle trajectory data. Following the above example, after obtaining the vehicle trajectory data, the Para (camera parameter) file in the vehicle trajectory data can be queried, and the data in the file can be used to generate the entire trajectory data set, wherein the entire trajectory data set includes multiple local trajectory data, each local trajectory data represents the driving trajectory of the vehicle in the corresponding area, and the driving trajectory specifically includes the trajectory point information of each time period, including file name, year, month, day, hour, minute, second, millisecond, number of satellites, etc. And the file name storing the entire trajectory data set is Project.IDX.

[0027] In some examples, after obtaining all trajectory data sets, this example further determines the vehicle's positioning data, which is the positioning and attitude results of the vehicle, stored in ASCII format, and the file name storing the positioning data is Project.NAV, where the positioning data is mainly used for the vehicle's geographic reference, including but not limited to latitude and longitude, elevation, pitch angle, heading angle, roll angle, easting mean error, northing mean error, elevation mean error and other information.

[0028] Further, to determine the positioning data, this example can use the entire trajectory data set to select at least one local trajectory data as the target trajectory data, the target trajectory data represents the trajectory range of the data to be processed, and the target trajectory data can be obtained based on at least one local trajectory data selected by the user. For example, the user can select the trajectory range to be processed by box selection and dragging, and then the system uses the local trajectory data corresponding to the trajectory range as the target trajectory data. In addition, the vehicle system can also select at least one local trajectory data from the entire trajectory data set as the target trajectory data to reduce the low processing efficiency and computing resource occupation caused by full processing. At the same time, the target trajectory data is used to determine the target positioning data from the positioning data, so that the range of the target positioning data corresponds to the selected target trajectory data. Finally, the target trajectory data and the target positioning data are used to decompose the environmental data to obtain the local environmental data, avoiding the time waste caused by the full processing of the entire trajectory data set in the prior art, thereby improving the data processing efficiency and further improving the user experience.

[0029] In addition, when the existing method fails to process vehicle collection data, due to the large amount of data and the long processing time span, it also takes a lot of time to investigate the cause of the failure. According to the method of this embodiment, at least one local trajectory data is selected from the entire trajectory data set as the target trajectory data for investigation, which can greatly shorten the time for locating the problem.

[0030] According to the technical solution provided by the implementation of this application, vehicle trajectory data and environmental data are obtained; data processing is performed on the vehicle trajectory data to obtain a complete trajectory data set, wherein the complete trajectory data set includes multiple local trajectory data, and each local trajectory data represents the driving trajectory of the vehicle in the corresponding area; the positioning data of the vehicle is determined, and at least one local trajectory data is selected from the complete trajectory data set as the target trajectory data, and the target positioning data is used to determine the target positioning data from the positioning data; the environmental data is decomposed using the target trajectory data and the target positioning data to obtain local environmental data. In this way, it is only necessary to determine the complete trajectory data set of the vehicle trajectory data, and then determine the range of the data to be processed from the complete trajectory data set, and at the same time determine the target positioning data corresponding to the selected range, so that the required local data can be processed adaptively, thereby improving data processing efficiency and user experience, and avoiding the problems of low efficiency and long time consumption caused by the full processing of vehicle collection data in the prior art.

[0031] In some embodiments, determining the positioning data of a vehicle includes: obtaining a collection configuration file corresponding to the vehicle trajectory data, and converting the format of the data in the collection configuration file to obtain first format data; determining multiple file paths for generating target format files; and obtaining positioning data based on the file data in each file path and the first format data.

[0032] Specifically, this example first obtains the acquisition configuration file corresponding to the vehicle trajectory data, converts the data in the acquisition configuration file to obtain the first format data, and exemplarily queries the .cnb format file (acquisition configuration file) under the Project directory and the Base file path, which includes engineering information and inertial navigation data, and then converts the data in the .cnb format file to obtain the .o format file data (first format data), thereby achieving the unification and standardization of the data format. It can be understood that the Project stores engineering file information, including the start time, end time, reference station information, etc. of the project.

[0033] Further, multiple file paths for generating target format files are determined. Exemplarily, the multiple file paths include the directory address of the initial collected data, the .240 format file address under the Project directory, the Base directory address, the Project.imu file address and the Para folder address. After obtaining the above-mentioned multiple file paths for generating target format files, the file data contained in the above-mentioned multiple paths are combined with the first format data obtained by format conversion to generate positioning data as the vehicle's geographic reference information.

[0034] According to the technical solution provided in the embodiment of the present application, determining the positioning data of the vehicle includes: obtaining a collection configuration file corresponding to the vehicle trajectory data, and converting the format of the data in the collection configuration file to obtain first format data; determining multiple file paths for generating target format files; and obtaining positioning data based on the file data in each file path and the first format data. In this way, the format unification and standardization of multiple data can be completed, and finally the obtained positioning data is used as the geographic reference information of the vehicle to provide a reasonable basis for the subsequent data processing process.

[0035] In some embodiments, positioning data is obtained based on the file data and the first format data in each file path, including: performing inertial measurement unit (IMU) data processing on multiple file data and the first format data to obtain IMU file data; performing global positioning system (GPS) positioning processing on the IMU file data to obtain positioning data.

[0036] Specifically, multiple file data and first format data (i.e., .o format file data) are processed, and the focus is first on the precise analysis and integration of inertial measurement unit (IMU) data. As a key component of vehicle trajectory data, IMU includes but is not limited to key motion information such as vehicle acceleration and angular velocity, which is crucial for subsequent positioning and trajectory reconstruction.

[0037] Continuing with the above example, read the .240 format file in the Project directory, which usually contains the original IMU data records during vehicle driving, such as timestamps, accelerometer readings, gyroscope readings, etc. Then, combined with the calibration parameters in the Base directory), calibrate the IMU data to eliminate hardware bias and system noise and improve data accuracy. After completing the calibration of the IMU data, the system fuses these processed data with other relevant information in the first format data (.o format file data) (such as engineering information, inertial navigation data overview, etc.). Ensure that the IMU data is connected to the overall background information of the vehicle's driving to provide a basis for subsequent processing.

[0038] Further, the fusion stage of GPS data processing is entered. By reading the GPS configuration file that may exist in the Para folder or directly obtaining GPS data from an external data source, the system synchronizes the IMU data with the GPS data in time and aligns it in space. The high-precision position information provided by GPS is used to correct the accumulated errors in the GPS data.

[0039] According to the technical solution provided in the embodiment of the present application, IMU data processing is performed on multiple file data and the first format data to obtain IMU file data; GPS positioning processing is performed on the IMU file data to obtain positioning data. In this way, IMU data processing can remove noise and deviation in the data, while GPS positioning processing can correct signal errors and environmental interference to ensure the accuracy of positioning.

[0040] In some embodiments, after the vehicle trajectory data is processed to obtain the entire trajectory data set, it also includes: parsing the entire trajectory data set to obtain the coordinates of all trajectory points; based on the coordinates of all trajectory points, obtaining the vehicle's trajectory line, and displaying the trajectory line through a visual interface.

[0041] Specifically, after generating all trajectory data sets, the configuration files corresponding to all trajectory data sets can be further processed and parsed, and these configuration information can be used to enhance the practicality and intuitiveness of the trajectory data. That is, by reading the configuration files corresponding to all trajectory data sets, these configuration files contain key metadata of the trajectory data, such as sampling rate, coordinate system, map projection method, etc. The system parses these configuration files, extracts the necessary parameter settings, and obtains the coordinates of all trajectory points for constructing the vehicle driving trajectory line.

[0042] Furthermore, based on the coordinates of all the multiple trajectory points obtained by analysis, the trajectory line of the vehicle can be obtained. Specifically, the trajectory line of the vehicle can be generated by methods such as linear interpolation and curve fitting, which are not specifically limited in this embodiment. The above algorithm can smoothly process the transition between trajectory points and reduce the jump phenomenon caused by sampling frequency or positioning error, thereby more realistically restoring the driving path of the vehicle. At the same time, the directionality of the trajectory line can also be considered to ensure that the drawing of the trajectory line is consistent with the actual driving direction of the vehicle.

[0043] It can be understood that after obtaining an accurate trajectory line, it can be displayed through a visualization interface (such as the vehicle's onboard screen or the user's mobile terminal). The user can use the visualization interface to select at least one local trajectory data as the target trajectory data for subsequent processing. It should be noted that the visualization interface can support basic two-dimensional display, and can also switch to a three-dimensional view according to user needs to present the vehicle's driving trajectory in a more three-dimensional manner. In addition, the visualization interface also provides interactive functions such as zooming, panning, and rotating the map to select specific trajectory segments for highlighting or data analysis.

[0044] According to the technical solution provided in the embodiment of the present application, all trajectory data sets are parsed to obtain the coordinates of all trajectory points; based on the coordinates of all trajectory points, the vehicle's trajectory line is obtained, and the trajectory line is displayed through a visual interface. Through further data processing and visual display, not only the accurate reconstruction and efficient management of vehicle trajectory data are achieved, but also an intuitive and convenient data analysis and display tool can be provided for users.

[0045] In some embodiments, the environmental data includes point cloud data, and the environmental data is decomposed using target trajectory data and target positioning data to obtain local environmental data, including: if it is determined that there is a point cloud file corresponding to the point cloud data, then the target point cloud data is obtained from the point cloud file, and the target configuration data corresponding to the target point cloud data is determined; the target point cloud data and the target configuration data are decomposed using the target trajectory data and the target positioning data to obtain local point cloud data.

[0046] Specifically, in complex environmental data processing scenarios, point cloud data, as a direct representation of the surface shape and position information of objects in three-dimensional space, is crucial for accurate modeling and analysis of the vehicle driving environment. When confirming the existence of point cloud data associated with the current analysis task, this example further retrieves the corresponding point cloud file and configuration file from the storage medium. Exemplarily, if a Laser folder is included, the target point cloud data in the formats of .rxp, .pcap, .bari, .hsr, .zfs, .ko, etc. under the Laser folder and the data of the DeviceConfig.xml configuration file under the Project directory (target configuration data) are obtained, wherein the DeviceConfig.xml configuration file is an XML format file used to store device configuration information, such as calibration parameters, scanning modes, resolutions, etc. of point cloud devices, as well as for interpreting and processing point cloud data.

[0047] Furthermore, using the target trajectory data and the target positioning data as a guide, the target point cloud data and the target configuration data corresponding to the target point cloud data are decomposed to ensure that the decomposed point cloud data range matches the selected target trajectory data, thereby extracting local point cloud data closely related to at least one local trajectory data of interest to the user. Exemplarily, the local point cloud data is a point cloud data file in .las format, which is an open standard binary file format, mainly used to store point cloud data obtained by laser radar scanning, and supports recording multiple attributes such as three-dimensional coordinates of laser points, multiple echo information, intensity information, scanning angles, and classification information.

[0048] It should be noted that this process involves simple data screening. At the same time, it can also be combined with the vehicle's precise position, posture and trajectory information to ensure accurate extraction of local point cloud data.

[0049] According to the technical solution provided by the embodiment of the present application, if it is determined that there is a point cloud file corresponding to the point cloud data, the target point cloud data is obtained from the point cloud file, and the target configuration data corresponding to the target point cloud data is determined; the target point cloud data and the target configuration data are decomposed using the target trajectory data and the target positioning data to obtain local point cloud data. By decomposing the target point cloud data and the target configuration data using the target trajectory data selected by the user and the target positioning data corresponding to the target trajectory data range to obtain local point cloud data, only the data within the user selected range can be processed, thereby improving the pertinence and efficiency of data processing, and thus improving the user experience.

[0050] In some embodiments, the environmental data includes panoramic image data, and the environmental data is decomposed using target trajectory data and target positioning data to obtain local environmental data, including: acquiring target panoramic image data in a panoramic image file; decomposing the target panoramic image data using target trajectory data and target positioning data to obtain local panoramic image data.

[0051] Specifically, panoramic image data, as another important data in the vehicle, provides a comprehensive perspective of the vehicle's surrounding environment, which helps users to more intuitively understand the changes in the external environment during the vehicle's driving. In this example, when the environmental data includes panoramic image data, the target panoramic image data stored in the panoramic image file is first obtained, and illustratively, the .pgr file in the Panorama folder is obtained.

[0052] Furthermore, the target trajectory data and the target positioning data are used as a guide to decompose the target panoramic image data and filter out the local panoramic image data corresponding to the target trajectory data range. It should be noted that this process can match the panoramic image file with the vehicle's driving trajectory based on the target positioning data, thereby determining the image segment corresponding to the target trajectory data range.

[0053] According to the technical solution provided in the embodiment of the present application, target panoramic image data in a panoramic image file is obtained; the target panoramic image data is decomposed using target trajectory data and target positioning data to obtain local panoramic image data, which not only improves the targeted data processing, but also greatly reduces the loading and processing time of non-essential data, allowing users to more quickly obtain panoramic image information of specific areas they are concerned about, thereby improving the user experience.

[0054] In some embodiments, the environmental data includes charge-coupled device (CCD) image data, and the environmental data is decomposed using target trajectory data and target positioning data to obtain local environmental data, including: acquiring target CCD image data in a CCD image file; decomposing the target CCD image data using target trajectory data and target positioning data to obtain local CCD image data.

[0055] Specifically, CCD image data has high resolution and excellent color reproduction capability, which can provide support for image acquisition and analysis during vehicle driving. In this embodiment, when the environmental data includes CCD image data, the target CCD image data stored in the CCD image file is first obtained, and exemplarily, the .nscn file in the Image folder is obtained.

[0056] Furthermore, the target trajectory data and target positioning data are used as guidance to decompose the target CCD image data, and the local CCD image data corresponding to the target trajectory data range is screened out. In addition, due to the high-resolution characteristics of CCD image data, the image quality needs to be maintained during decomposition to avoid image distortion caused by scaling or cropping operations. Therefore, when extracting local CCD image data, more complex image processing algorithms can be used, such as content-based image scaling, edge detection and retention, etc., to ensure that the final local image data meets user needs and maintains good visual quality.

[0057] According to the technical solution provided in the embodiment of the present application, the target CCD image data in the CCD image file is obtained; the target CCD image data is decomposed using the target trajectory data and the target positioning data to obtain local CCD image data, which not only improves the targeted data processing, but also greatly reduces the loading and processing time of non-essential data, allowing users to more quickly obtain panoramic image information of specific areas they are concerned about, thereby improving the user experience.

[0058] Figure 2 is a flow chart of another data processing method provided in an embodiment of the present application, such as Figure 2 As shown, the method includes:

[0059] S201, acquiring vehicle trajectory data and environmental data, wherein the environmental data includes point cloud data, panoramic image data and CCD image data;

[0060] S202, performing data processing on the vehicle trajectory data to obtain a complete trajectory data set;

[0061] S203, parsing all trajectory data sets to obtain coordinates of all trajectory points, obtaining a trajectory line of the vehicle based on the coordinates of all trajectory points, and displaying the trajectory line through a visualization interface;

[0062] S204, determining the positioning data of the vehicle, selecting at least one local trajectory data from the entire trajectory data set as target trajectory data, and determining target positioning data from the positioning data using the target trajectory data;

[0063] S205, using the target trajectory data and the target positioning data to respectively process the point cloud data, the panoramic image data, and the CCD image data to obtain local point cloud data, local panoramic image data, and local CCD image data.

[0064] It can be understood that the environmental data includes point cloud data collected by point cloud devices (such as laser radar), panoramic image data and CCD image data obtained by camera devices (such as cameras configured on vehicles). After obtaining the vehicle trajectory data, the Para (camera parameter) file in the vehicle trajectory data can be queried, and the data in the file can be used to generate the entire trajectory data set (the file name is Project.IDX), and then the entire trajectory data set is parsed to obtain the coordinates of all trajectory points, and the coordinates of all trajectory points are connected to obtain the vehicle's trajectory line, and the trajectory line is displayed through a visual interface. The user can select the trajectory range to be processed based on the visual interface, and then determine the target trajectory data from the entire trajectory data set based on the trajectory range selected by the user.

[0065] Furthermore, the acquisition configuration file corresponding to the vehicle trajectory data is obtained, and the data in the acquisition configuration file is converted into a format to obtain first format data; multiple file paths for generating target format files are determined; based on the file data in each file path and the first format data, positioning data (file name is Project.NAV) is obtained as the geographic reference information of the vehicle. Then, the target trajectory data is used to determine the target positioning data corresponding to the target trajectory data from the positioning data, and the data is streamlined to reduce data redundancy. Finally, the target trajectory data and the target positioning data are used to perform point cloud data, panoramic image data, and CCD image data, respectively, to obtain local point cloud data, local panoramic image data, and local CCD image data. In this way, the required local data can be processed adaptively, thereby improving data processing efficiency and user experience, and avoiding the low efficiency and long time consumption caused by the full processing of vehicle acquisition data in the prior art.

[0066] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the process of the embodiments of the present application.

[0067] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described in detail here.

[0068] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0069] Figure 3 Schematic diagram of a data processing device provided in an embodiment of the present application. Figure 3 As shown, the device comprises:

[0070] An acquisition module 301 is configured to acquire vehicle trajectory data and environment data;

[0071] The processing module 302 is configured to perform data processing on the vehicle trajectory data to obtain a complete trajectory data set, wherein the complete trajectory data set includes a plurality of local trajectory data, each of which represents a driving trajectory of the vehicle in a corresponding area;

[0072] The determination module 303 is configured to determine the positioning data of the vehicle, select at least one local trajectory data from the entire trajectory data set as the target trajectory data, and determine the target positioning data from the positioning data using the target trajectory data;

[0073] The decomposition module 304 is configured to decompose the environmental data using the target trajectory data and the target positioning data to obtain local environmental data.

[0074] In some embodiments, the determination module 303 is also configured to obtain a collection configuration file corresponding to the vehicle trajectory data, and convert the format of the data in the collection configuration file to obtain first format data; determine multiple file paths for generating target format files; and obtain positioning data based on the file data and the first format data in each file path.

[0075] In some embodiments, the determination module 303 is also configured to perform inertial measurement unit (IMU) data processing on multiple file data and first format data to obtain IMU file data; and perform global positioning system (GPS) positioning processing on the IMU file data to obtain positioning data.

[0076] In some embodiments, the processing module 302 is further configured to parse all trajectory data sets to obtain coordinates of all trajectory points; based on the coordinates of all trajectory points, obtain the trajectory line of the vehicle, and display the trajectory line through a visual interface.

[0077] In some embodiments, the decomposition module 304 is also configured to obtain target point cloud data from the point cloud file and determine target configuration data corresponding to the target point cloud data if it is determined that there is a point cloud file corresponding to the point cloud data; and use the target trajectory data and the target positioning data to decompose the target point cloud data and the target configuration data to obtain local point cloud data.

[0078] In some embodiments, the decomposition module 304 is further configured to obtain target panoramic image data in the panoramic image file; decompose the target panoramic image data using the target trajectory data and the target positioning data to obtain local panoramic image data.

[0079] In some embodiments, the decomposition module 304 is further configured to obtain target CCD image data in the CCD image file; decompose the target CCD image data using the target trajectory data and the target positioning data to obtain local CCD image data.

[0080] The data processing device provided in this embodiment obtains vehicle trajectory data and environmental data; processes the vehicle trajectory data to obtain a complete trajectory data set, wherein the complete trajectory data set includes multiple local trajectory data, and each local trajectory data represents the driving trajectory of the vehicle in the corresponding area; determines the vehicle's positioning data, selects at least one local trajectory data from the complete trajectory data set as the target trajectory data, and uses the target trajectory data to determine the target positioning data from the positioning data; uses the target trajectory data and the target positioning data to decompose the environmental data to obtain local environmental data. In this way, it is only necessary to determine the complete trajectory data set of the vehicle trajectory data, and then determine the range of the data to be processed from the complete trajectory data set, and at the same time determine the target positioning data corresponding to the selected range, so that the required local data can be processed adaptively, thereby improving data processing efficiency and user experience, and avoiding the problems of low efficiency and long time consumption caused by the existing technology of fully processing vehicle collection data.

[0081] Figure 4 Schematic diagram of an electronic device 4 provided in an embodiment of the present application. Figure 4 As shown, the electronic device 4 of this embodiment includes: a processor 401, a memory 402, and a computer program 403 stored in the memory 402 and executable on the processor 401. When the processor 401 executes the computer program 403, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor 401 executes the computer program 403, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0082] The electronic device 4 may be a desktop computer, a notebook, a PDA, a cloud server, or other electronic device. The electronic device 4 may include, but is not limited to, a processor 401 and a memory 402. Those skilled in the art will appreciate that Figure 4 The electronic device 4 is merely an example and does not limit the electronic device 4 , and may include more or less components than those shown in the figure, or different components.

[0083] The processor 401 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0084] The memory 402 may be an internal storage unit of the electronic device 4, for example, a hard disk or memory of the electronic device 4. The memory 402 may also be an external storage device of the electronic device 4, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 4. The memory 402 may also include both an internal storage unit and an external storage device of the electronic device 4. The memory 402 is used to store computer programs and other programs and data required by the electronic device.

[0085] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.

[0086] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the present application implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, which may be in source code form, object code form, executable file or some intermediate form. The readable storage medium may include: any entity or device that can carry computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0087] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A data processing method, characterized in that: include: Obtain vehicle trajectory data and environmental data; Processing the vehicle trajectory data to obtain a complete trajectory data set, wherein the complete trajectory data set includes a plurality of local trajectory data, each of which represents a driving trajectory of the vehicle in a corresponding area; Determine the positioning data of the vehicle, select at least one local trajectory data from the entire trajectory data set as target trajectory data, and determine target positioning data from the positioning data using the target trajectory data; The target trajectory data and the target positioning data are used to decompose the environmental data to obtain local environmental data.

2. The method according to claim 1, characterized in that The determining the positioning data of the vehicle comprises: Acquire a collection configuration file corresponding to the vehicle trajectory data, and perform format conversion on the data in the collection configuration file to obtain data in a first format; Determining a plurality of file paths for generating the target format file; The positioning data is obtained based on the file data in each of the file paths and the first format data.

3. The method according to claim 2, characterized in that The obtaining the positioning data based on the file data in each of the file paths and the first format data includes: Performing inertial measurement unit (IMU) data processing on the plurality of file data and the first format data to obtain IMU file data; The IMU file data is subjected to global positioning system (GPS) positioning processing to obtain the positioning data.

4. The method according to claim 1, characterized in that: After the vehicle trajectory data is processed to obtain the entire trajectory data set, the method further includes: Parsing all the trajectory data sets to obtain coordinates of all trajectory points; Based on the coordinates of all trajectory points, the trajectory line of the vehicle is obtained, and the trajectory line is displayed through a visual interface.

5. The method according to claim 1, characterized in that The environmental data includes point cloud data, and the environmental data is decomposed by using the target trajectory data and the target positioning data to obtain local environmental data, including: If it is determined that there is a point cloud file corresponding to the point cloud data, then obtaining target point cloud data from the point cloud file, and determining target configuration data corresponding to the target point cloud data; The target point cloud data and the target configuration data are decomposed using the target trajectory data and the target positioning data to obtain local point cloud data.

6. The method according to claim 1, characterized in that The environmental data includes panoramic image data, and the environmental data is decomposed using the target trajectory data and the target positioning data to obtain local environmental data, including: Obtain target panoramic image data in the panoramic image file; The target panoramic image data is decomposed using the target trajectory data and the target positioning data to obtain local panoramic image data.

7. The method according to claim 1, characterized in that The environmental data includes charge-coupled device (CCD) image data, and the environmental data is decomposed using the target trajectory data and the target positioning data to obtain local environmental data, including: Get the target CCD image data in the CCD image file; The target CCD image data is decomposed using the target trajectory data and the target positioning data to obtain local CCD image data.

8. A data processing device, characterized in that: include: An acquisition module, configured to acquire vehicle trajectory data and environment data; A processing module is configured to perform data processing on the vehicle trajectory data to obtain a complete trajectory data set, wherein the complete trajectory data set includes a plurality of local trajectory data, each of which represents a driving trajectory of the vehicle in a corresponding area; a determination module configured to determine the positioning data of the vehicle, select at least one local trajectory data from the entire trajectory data set as target trajectory data, and determine target positioning data from the positioning data using the target trajectory data; The decomposition module is configured to decompose the environmental data using the target trajectory data and the target positioning data to obtain local environmental data.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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