Vehicle track splitting method and device

Abstract

The invention provides a vehicle track splitting method and device. The method comprises the following steps: acquiring a navigation file, a point cloud file and an image file of a target vehicle; splitting the navigation file into a first file corresponding to each track of the target vehicle according to the timestamp, splitting the point cloud file into a second file corresponding to each track, and splitting the image file into a third file corresponding to each track; generating a travel file corresponding to each first file, and converting each second file into a preset data exchange format to obtain a fourth file corresponding to each second file; and merging the travel file corresponding to each track, the third file and the fourth file to obtain a track file corresponding to each track. By adopting the technical means, the problem of low vehicle track splitting efficiency in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a vehicle trajectory splitting method and device. Background Art

[0002] Vehicle trajectory splitting has a wide range of applications in tracking data processing, traffic data analysis, fleet management, and autonomous driving system testing. A vehicle's complete journey may need to be split into multiple sub-trajectories for a variety of reasons, such as analyzing the driving characteristics of a specific road section, identifying abnormal driving behavior, or processing data breakpoints after signal loss. Traditional methods of vehicle trajectory splitting take a long time, generally taking several hours, which means that subsequent data production requires a long wait, and the user experience is very poor. Summary of the invention

[0003] In view of this, embodiments of the present application provide a vehicle trajectory splitting method, device, electronic device and computer-readable storage medium to solve the problem of low efficiency of vehicle trajectory splitting in the prior art.

[0004] In a first aspect of an embodiment of the present application, a vehicle trajectory splitting method is provided, including: obtaining a navigation file, a point cloud file and an image file of a target vehicle; splitting the navigation file into a first file corresponding to each trajectory of the target vehicle according to a timestamp, dividing the point cloud file into a second file corresponding to each trajectory, and dividing the image file into a third file corresponding to each trajectory; generating a travel file corresponding to each first file, converting each second file into a preset data exchange format, and obtaining a fourth file corresponding to each second file; merging the travel file, the third file and the fourth file corresponding to each trajectory to obtain a trajectory file corresponding to each trajectory.

[0005] According to a second aspect of an embodiment of the present application, a vehicle trajectory splitting device is provided, comprising: an acquisition module, configured to acquire a navigation file, a point cloud file and an image file of a target vehicle; a division module, configured to split the navigation file into a first file corresponding to each trajectory of the target vehicle according to a timestamp, split the point cloud file into a second file corresponding to each trajectory, and split the image file into a third file corresponding to each trajectory; a processing module, configured to generate a travel file corresponding to each first file, convert each second file into a preset data exchange format, and obtain a fourth file corresponding to each second file; and a merging module, configured to merge the travel file, the third file and the fourth file corresponding to each trajectory, and obtain a trajectory file corresponding to each trajectory.

[0006] 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.

[0007] 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.

[0008] Compared with the prior art, the embodiments of the present application have the following beneficial effects: obtaining the navigation file, point cloud file and image file of the target vehicle; splitting the navigation file into the first file corresponding to each track of the target vehicle according to the timestamp, splitting the point cloud file into the second file corresponding to each track and splitting the image file into the third file corresponding to each track; generating the travel file corresponding to each first file, converting each second file into a preset data exchange format, and obtaining the fourth file corresponding to each second file; merging the travel file, the third file and the fourth file corresponding to each track, and obtaining the track file corresponding to each track. The above technical means can solve the problem of low efficiency of vehicle track splitting in the prior art, thereby improving the splitting efficiency and user satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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.

[0010] Figure 1 It is a flow chart of a vehicle trajectory splitting method provided in an embodiment of the present application;

[0011] Figure 2 It is a flowchart of another vehicle trajectory splitting method provided in an embodiment of the present application;

[0012] Figure 3 It is a structural schematic diagram of a vehicle track splitting device provided in an embodiment of the present application;

[0013] Figure 4 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0014] 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.

[0015] A vehicle trajectory splitting method and device according to an embodiment of the present application will be described in detail below with reference to the accompanying drawings.

[0016] Figure 1 It is a flow chart of a vehicle trajectory splitting method provided in an embodiment of the present application. Figure 1 The vehicle trajectory splitting method can be executed by a computer or a server, or software on a computer or a server. Figure 1 As shown, the vehicle trajectory splitting method includes:

[0017] S101, obtaining a navigation file, a point cloud file, and an image file of a target vehicle;

[0018] S102, splitting the navigation file into first files corresponding to each track of the target vehicle according to the timestamp, splitting the point cloud file into second files corresponding to each track, and splitting the image file into third files corresponding to each track;

[0019] S103, generating a trip file corresponding to each first file, converting each second file into a preset data exchange format, and obtaining a fourth file corresponding to each second file;

[0020] S104, merging the travel file, the third file and the fourth file corresponding to each trajectory to obtain a trajectory file corresponding to each trajectory.

[0021] The navigation file includes multiple navigation data, which can be navigation data such as the position, speed, acceleration, and direction of the target vehicle. The image file contains multiple image images, which are mainly derived from the vehicle-mounted camera, which can be a monocular, binocular, or multi-camera system. Image data provides rich visual information, such as color, texture, and motion. The point cloud file contains multiple point cloud data, which usually comes from the lidar system. The lidar system determines the distance of surrounding objects by emitting laser pulses and measuring the time difference of reflected echoes to generate dense three-dimensional point cloud data. Point cloud data provides richer depth information than image files, which helps vehicles make decisions in complex environments, especially when lighting conditions are poor or objects are obscured. Navigation files, point cloud files, and image files all contain information at different times, and information at different times is distinguished by timestamps.

[0022] The navigation file is split into the first file corresponding to the target vehicle in different time periods according to the timestamp, and one time period corresponds to one track. Similarly, the point cloud file is divided into the second file corresponding to each track, and the image file is divided into the third file corresponding to each track. The required information is extracted from the first file to obtain the trip file corresponding to the first file. The information contained in the trip file is less than the information contained in the first file, for example, the trip file only contains the change in the position of the target vehicle in one time period. The preset data exchange format can be LAS format. The second file is usually stored in the form of a point cloud and needs to be converted into a fourth file in LAS (Lidar Data Exchange Format) format. LAS (Lidar Data Exchange Format) is a widely used file format, and files in this format are easy to analyze and process. The trip file, the third file and the fourth file corresponding to a track are merged according to the timestamp to obtain the track file corresponding to the track. The track file includes information at multiple times, and the information at one time includes the position of the target vehicle, point cloud data and image image.

[0023] According to the technical solution provided in the embodiment of the present application, the navigation file, point cloud file and image file of the target vehicle are obtained; the navigation file is split into the first file corresponding to each track of the target vehicle according to the timestamp, the point cloud file is split into the second file corresponding to each track, and the image file is split into the third file corresponding to each track; the travel file corresponding to each first file is generated, and each second file is converted into a preset data exchange format to obtain the fourth file corresponding to each second file; the travel file, the third file and the fourth file corresponding to each track are merged to obtain the track file corresponding to each track. The above technical means can solve the problem of low efficiency of vehicle track splitting in the prior art, thereby improving the splitting efficiency and enhancing user satisfaction.

[0024] Furthermore, after obtaining the navigation file, point cloud file and image file of the target vehicle, the method also includes: creating a first decomposition task, a second decomposition task and a third decomposition task; using the first decomposition task to split the navigation file into first files corresponding to each trajectory according to the timestamp; using the second decomposition task to split the point cloud file into second files corresponding to each trajectory according to the timestamp; using the third decomposition task to split the image file into third files corresponding to each trajectory according to the timestamp.

[0025] In order to improve the processing effect, the first decomposition task, the second decomposition task and the third decomposition task can be created to decompose the navigation file, the point cloud file and the image file respectively. The first decomposition task, the second decomposition task and the third decomposition task can be executed in parallel to decompose the navigation file, the point cloud file and the image file at the same time, thereby speeding up the processing speed.

[0026] Figure 2 FIG. 1 is a flow chart of another vehicle track splitting method provided in an embodiment of the present application. Figure 2 As shown, the method includes:

[0027] Execute the following loop:

[0028] S201, determining whether i is greater than N, where i is the sequence number of each track and N is the total number of all tracks;

[0029] S202, when i is greater than N, generating an index layer and a vehicle position and heading layer based on the trajectory files corresponding to each trajectory;

[0030] S203, displaying each track of the target vehicle according to the index layer and the vehicle position and heading layer, and ending the loop;

[0031] S204, when i is less than or equal to N, split the first file corresponding to the i-th track from the navigation file according to the timestamp, split the second file corresponding to the i-th track from the point cloud file, and split the third file corresponding to the i-th track from the image file;

[0032] S205, generating a travel file corresponding to the ith trajectory based on the first file corresponding to the ith trajectory;

[0033] S206, converting the second file corresponding to the ith track into a preset data exchange format to obtain a fourth file corresponding to the ith track;

[0034] S207, merging the travel file, the third file and the fourth file corresponding to the i-th trajectory to obtain the trajectory file corresponding to the i-th trajectory, and updating i with the value of i plus 1.

[0035] When i is greater than N, in fact, when i is equal to N+1, it is confirmed that the trajectory files of all trajectories have been generated. Based on the trajectory files corresponding to all trajectories, the index layer and the vehicle position and heading layer are generated. The index layer is used to locate each trajectory, and the vehicle position and heading layer is used to display the detailed information of each trajectory. The trajectories of the target vehicle are displayed according to the index layer and the vehicle position and heading layer.

[0036] When i is less than or equal to N, it means that the trajectory files of all trajectories have not been generated. The ith trajectory corresponds to the ith time period. The first file of the ith time period is split from the navigation file, the second file of the ith time period is split from the point cloud file, and the third file of the ith time period is split from the image file. Extract the required information from the first file corresponding to the ith trajectory to obtain the itinerary file corresponding to the ith trajectory. Convert the second file corresponding to the ith trajectory into the preset data exchange format to obtain the fourth file corresponding to the ith trajectory. After merging the itinerary file, the third file, and the fourth file corresponding to the ith trajectory to obtain the trajectory file corresponding to the ith trajectory, update i with the value of i plus 1.

[0037] Furthermore, after merging the travel file, the third file and the fourth file corresponding to each trajectory to obtain the trajectory file corresponding to each trajectory, the method also includes: generating an index layer and a vehicle position and heading layer based on the trajectory file corresponding to each trajectory; displaying each trajectory of the target vehicle according to the index layer and the vehicle position and heading layer; wherein the index layer is used to locate each trajectory, and the vehicle position and heading layer is used to display detailed information of each trajectory.

[0038] The index layer is created based on the information (such as timestamp) in the trajectory file corresponding to each trajectory. The index layer can quickly locate each trajectory. The vehicle position and heading layer is obtained based on the detailed information in the trajectory file corresponding to each trajectory. The vehicle position and heading layer can display the detailed information of each trajectory (such as the location of the target vehicle, point cloud data and image).

[0039] Furthermore, before generating a travel file corresponding to each first file and converting each second file into a preset data exchange format and obtaining a fourth file corresponding to each second file, the method also includes: respectively determining the splitting points of the navigation file, the splitting points of the point cloud file and the splitting points of the image file; determining the endpoints of each trajectory based on the splitting points of the navigation file, the splitting points of the point cloud file and the splitting points of the image file; splitting the navigation file into the first files corresponding to each trajectory, splitting the point cloud file into the second files corresponding to each trajectory and splitting the image file into the third files corresponding to each trajectory according to the endpoints of each trajectory.

[0040] Furthermore, the splitting points of the navigation file, the cutting points of the point cloud file and the cutting points of the image file are determined respectively, including: determining the splitting points of the navigation file according to the correlation relationship between each navigation data in the navigation file; determining the cutting points of the point cloud file according to the correlation relationship between each point cloud data in the point cloud file; determining the cutting points of the image file according to the correlation relationship between each image image in the image file.

[0041] Determine the split point of the navigation file according to the association relationship of each navigation data in the navigation file, that is, use the unique navigation data in the navigation file as the split point. If a navigation data has a large change with the previous navigation data, the navigation data is considered to be unique. For example, in the navigation file, there are three consecutive navigation data ABC. The speed of the target vehicle in A and B does not change much, but the speed of the target vehicle in B and C changes greatly (the change can be determined by the set threshold), then C can be used as a split point.

[0042] Determining the segmentation points of point cloud files and determining the segmentation points of image files is similar to determining the splitting points of navigation files. For point cloud files, if a point cloud data has a large change from the previous point cloud data (the more points that are different between two adjacent point cloud data, the greater the change between the two point cloud data), the point cloud data is considered unique. For image files, if an image image has a large change from the previous image image (the more visual features that are different between two adjacent image images, the greater the change between the two image images), the image image is considered unique.

[0043] A split point of the navigation file, a split point of the point cloud file, and a split point of the image file correspond to a time. A new time is determined by weighted summation of the three times, and the new time is used as an endpoint. For example, the second split point of the navigation file, the second split point of the point cloud file, and the second split point of the image file correspond to the times of 9:32:50, 9:33:40, and 9:32:30, respectively. The maximum interval between the three times is 70 seconds. 9:32:50 is the middle value of the three times. The weight 4 is assigned to the time. The interval between 9:32:30 and 9:32:50 is close, and the interval between 9:33:40 and 9:32:50 is far. The weight 2 is assigned to 9:32:30, and the weight 1 is assigned to 9:33:40. Starting from 9:32:00, 9:32:50 can be expressed as 50, 9:33:40 can be expressed as 100, and 9:32:30 can be expressed as 30, (50*4+100+30*2) / 7=51. So 9:32:51 is taken as an endpoint.

[0044] Furthermore, before obtaining the navigation file of the target vehicle, the method also includes: collecting different types of data through various on-board sensors arranged on the target vehicle; and using a combined navigation algorithm to fuse different types of data according to timestamps to obtain a navigation file.

[0045] On-board sensors include GPS receivers, inertial measurement units, wheel speed sensors, etc., which are used to collect information such as position, speed, acceleration, direction, etc. The combined navigation algorithm integrates different types of data into multiple data according to timestamps, and each data includes information such as position, speed, acceleration, direction, etc.

[0046] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described one by one here.

[0047] 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.

[0048] Figure 3 Schematic diagram of a vehicle track splitting device provided in an embodiment of the present application. Figure 3 As shown, the vehicle track splitting device comprises:

[0049] An acquisition module 301 is configured to acquire a navigation file, a point cloud file and an image file of a target vehicle;

[0050] A division module 302 is configured to divide the navigation file into first files corresponding to each track of the target vehicle according to the timestamp, divide the point cloud file into second files corresponding to each track, and divide the image file into third files corresponding to each track;

[0051] The processing module 303 is configured to generate a trip file corresponding to each first file, convert each second file into a preset data exchange format, and obtain a fourth file corresponding to each second file;

[0052] The merging module 304 is configured to merge the travel file, the third file and the fourth file corresponding to each trajectory to obtain a trajectory file corresponding to each trajectory.

[0053] According to the technical solution provided in the embodiment of the present application, the navigation file, point cloud file and image file of the target vehicle are obtained; the navigation file is split into the first file corresponding to each track of the target vehicle according to the timestamp, the point cloud file is split into the second file corresponding to each track, and the image file is split into the third file corresponding to each track; the travel file corresponding to each first file is generated, and each second file is converted into a preset data exchange format to obtain the fourth file corresponding to each second file; the travel file, the third file and the fourth file corresponding to each track are merged to obtain the track file corresponding to each track. The above technical means can solve the problem of low efficiency of vehicle track splitting in the prior art, thereby improving the splitting efficiency and enhancing user satisfaction.

[0054] In some embodiments, the division module 302 is also configured to create a first decomposition task, a second decomposition task and a third decomposition task; use the first decomposition task to split the navigation file into first files corresponding to each trajectory according to the timestamp; use the second decomposition task to split the point cloud file into second files corresponding to each trajectory according to the timestamp; use the third decomposition task to split the image file into third files corresponding to each trajectory according to the timestamp.

[0055] In order to improve the processing effect, the first decomposition task, the second decomposition task and the third decomposition task can be created to decompose the navigation file, the point cloud file and the image file respectively. The first decomposition task, the second decomposition task and the third decomposition task can be executed in parallel to decompose the navigation file, the point cloud file and the image file at the same time, thereby speeding up the processing speed.

[0056] In some embodiments, the merging module 304 is also configured to execute the following loop: determine whether i is greater than N, where i is the serial number of each trajectory and N is the total number of all trajectories; when i is greater than N, generate an index layer and a vehicle position and heading layer based on the trajectory files corresponding to each trajectory; display each trajectory of the target vehicle according to the index layer and the vehicle position and heading layer, and end the loop; when i is less than or equal to N, split the first file corresponding to the i-th trajectory from the navigation file according to the timestamp, split the second file corresponding to the i-th trajectory from the point cloud file, and split the third file corresponding to the i-th trajectory from the image file; based on the first file corresponding to the i-th trajectory, generate a travel file corresponding to the i-th trajectory; convert the second file corresponding to the i-th trajectory into a preset data exchange format to obtain a fourth file corresponding to the i-th trajectory; merge the travel file, the third file and the fourth file corresponding to the i-th trajectory to obtain the trajectory file corresponding to the i-th trajectory, and update i with the value of i plus 1.

[0057] When i is greater than N, in fact, when i is equal to N+1, it is confirmed that the trajectory files of all trajectories have been generated. Based on the trajectory files corresponding to all trajectories, the index layer and the vehicle position and heading layer are generated. The index layer is used to locate each trajectory, and the vehicle position and heading layer is used to display the detailed information of each trajectory. The trajectories of the target vehicle are displayed according to the index layer and the vehicle position and heading layer.

[0058] When i is less than or equal to N, it means that the trajectory files of all trajectories have not been generated. The ith trajectory corresponds to the ith time period. The first file of the ith time period is split from the navigation file, the second file of the ith time period is split from the point cloud file, and the third file of the ith time period is split from the image file. Extract the required information from the first file corresponding to the ith trajectory to obtain the itinerary file corresponding to the ith trajectory. Convert the second file corresponding to the ith trajectory into the preset data exchange format to obtain the fourth file corresponding to the ith trajectory. After merging the itinerary file, the third file, and the fourth file corresponding to the ith trajectory to obtain the trajectory file corresponding to the ith trajectory, update i with the value of i plus 1.

[0059] In some embodiments, the merging module 304 is also configured to generate an index layer and a vehicle position and heading layer based on the trajectory files corresponding to each trajectory; and display each trajectory of the target vehicle according to the index layer and the vehicle position and heading layer; wherein the index layer is used to locate each trajectory, and the vehicle position and heading layer is used to display detailed information of each trajectory.

[0060] The index layer is created based on the information (such as timestamp) in the trajectory file corresponding to each trajectory. The index layer can quickly locate each trajectory. The vehicle position and heading layer is obtained based on the detailed information in the trajectory file corresponding to each trajectory. The vehicle position and heading layer can display the detailed information of each trajectory (such as the location of the target vehicle, point cloud data and image).

[0061] In some embodiments, the division module 302 is also configured to respectively determine the splitting points of the navigation file, the splitting points of the point cloud file, and the splitting points of the image file; determine the endpoints of each trajectory based on the splitting points of the navigation file, the splitting points of the point cloud file, and the splitting points of the image file; split the navigation file into first files corresponding to each trajectory according to the endpoints of each trajectory, split the point cloud file into second files corresponding to each trajectory, and split the image file into third files corresponding to each trajectory.

[0062] In some embodiments, the division module 302 is also configured to determine the splitting points of the navigation file according to the association relationship between each navigation data in the navigation file; determine the cutting points of the point cloud file according to the association relationship between each point cloud data in the point cloud file; and determine the segmentation points of the image file according to the association relationship between each image image in the image file.

[0063] Determine the split point of the navigation file according to the association relationship of each navigation data in the navigation file, that is, use the unique navigation data in the navigation file as the split point. If a navigation data has a large change with the previous navigation data, the navigation data is considered to be unique. For example, in the navigation file, there are three consecutive navigation data ABC. The speed of the target vehicle in A and B does not change much, but the speed of the target vehicle in B and C changes greatly (the change can be determined by the set threshold), then C can be used as a split point.

[0064] Determining the segmentation points of point cloud files and determining the segmentation points of image files is similar to determining the splitting points of navigation files. For point cloud files, if a point cloud data has a large change from the previous point cloud data (the more points that are different between two adjacent point cloud data, the greater the change between the two point cloud data), the point cloud data is considered unique. For image files, if an image image has a large change from the previous image image (the more visual features that are different between two adjacent image images, the greater the change between the two image images), the image image is considered unique.

[0065] A split point of the navigation file, a split point of the point cloud file, and a split point of the image file correspond to a time. A new time is determined by weighted summation of the three times, and the new time is used as an endpoint. For example, the second split point of the navigation file, the second split point of the point cloud file, and the second split point of the image file correspond to the times of 9:32:50, 9:33:40, and 9:32:30, respectively. The maximum interval between the three times is 70 seconds. 9:32:50 is the middle value of the three times. The weight 4 is assigned to the time. The interval between 9:32:30 and 9:32:50 is close, and the interval between 9:33:40 and 9:32:50 is far. The weight 2 is assigned to 9:32:30, and the weight 1 is assigned to 9:33:40. Starting from 9:32:00, 9:32:50 can be expressed as 50, 9:33:40 can be expressed as 100, and 9:32:30 can be expressed as 30, (50*4+100+30*2) / 7=51. So 9:32:51 is taken as an endpoint.

[0066] In some embodiments, the acquisition module 301 is further configured to collect different types of data through various on-board sensors installed on the target vehicle; and use a combined navigation algorithm to fuse different types of data according to timestamps to obtain a navigation file.

[0067] On-board sensors include GPS receivers, inertial measurement units, wheel speed sensors, etc., which are used to collect information such as position, speed, acceleration, direction, etc. The combined navigation algorithm integrates different types of data into multiple data according to timestamps, and each data includes information such as position, speed, acceleration, direction, etc.

[0068] 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 implementation process of the embodiments of the present application.

[0069] 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.

[0070] 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.

[0071] 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.

[0072] 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.

[0073] 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.

[0074] 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 computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes 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 computer-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, and the computer program code may be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

[0075] 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 vehicle trajectory splitting method, characterized in that: include: Obtain navigation files, point cloud files and image files of the target vehicle; Splitting the navigation file into first files corresponding to each track of the target vehicle according to the timestamp, splitting the point cloud file into second files corresponding to each track, and splitting the image file into third files corresponding to each track; Generate a trip file corresponding to each first file, convert each second file into a preset data exchange format, and obtain a fourth file corresponding to each second file; The travel file, the third file and the fourth file corresponding to each trajectory are merged to obtain a trajectory file corresponding to each trajectory.

2. The method according to claim 1, characterized in that After obtaining the navigation file, point cloud file and image file of the target vehicle, the method further includes: Creating a first decomposed task, a second decomposed task, and a third decomposed task; Using the first decomposition task to split the navigation file into first files corresponding to each track according to the timestamp; Using the second decomposition task, the point cloud file is divided into second files corresponding to each track according to the timestamp; The image file is divided into third files corresponding to each track according to the timestamp by using the third decomposition task.

3. The method according to claim 1, characterized in that The method further comprises: Execute the following loop: Determine whether i is greater than N, where i is the sequence number of each trajectory and N is the total number of all trajectories; When i is greater than N, an index layer and a vehicle position and heading layer are generated based on the trajectory files corresponding to each trajectory; Displaying each track of the target vehicle according to the index layer and the vehicle position and heading layer, and ending the loop; When i is less than or equal to N, a first file corresponding to the i-th track is split from the navigation file according to the timestamp, a second file corresponding to the i-th track is split from the point cloud file, and a third file corresponding to the i-th track is split from the image file; Based on the first file corresponding to the ith track, generate a travel file corresponding to the ith track; Converting the second file corresponding to the ith track into the preset data exchange format to obtain a fourth file corresponding to the ith track; Merge the travel file, the third file, and the fourth file corresponding to the i-th trajectory to obtain the trajectory file corresponding to the i-th trajectory, and update i with the value of i plus 1.

4. The method according to claim 1, characterized in that: After merging the travel file, the third file and the fourth file corresponding to each trajectory to obtain the trajectory file corresponding to each trajectory, the method further includes: Generate index layer and vehicle position and heading layer based on the trajectory files corresponding to each trajectory; Displaying each track of the target vehicle according to the index layer and the vehicle position and heading layer; The index layer is used to locate each track, and the vehicle position and heading layer is used to display detailed information of each track.

5. The method according to claim 1, characterized in that Before generating a trip file corresponding to each first file, converting each second file into a preset data exchange format, and obtaining a fourth file corresponding to each second file, the method further includes: Respectively determining the splitting points of the navigation file, the segmentation points of the point cloud file and the segmentation points of the image file; Determine the endpoints of each track according to the splitting points of the navigation file, the segmentation points of the point cloud file and the segmentation points of the image file; The navigation file is split into first files corresponding to each trajectory according to the endpoints of each trajectory, the point cloud file is split into second files corresponding to each trajectory, and the image file is split into third files corresponding to each trajectory.

6. The method according to claim 5, characterized in that Respectively determining the splitting points of the navigation file, the segmentation points of the point cloud file, and the segmentation points of the image file, including: Determining the splitting point of the navigation file according to the association relationship between the navigation data in the navigation file; Determine the splitting points of the point cloud file according to the association relationship between each point cloud data in the point cloud file; The segmentation points of the image file are determined according to the association relationship between the image images in the image file.

7. The method according to claim 1, characterized in that Before obtaining the navigation file of the target vehicle, the method further includes: Collecting different types of data through various on-board sensors arranged on the target vehicle; The navigation file is obtained by fusing different types of data according to timestamps using a combined navigation algorithm.

8. A vehicle track splitting device, characterized in that: include: An acquisition module, configured to acquire a navigation file, a point cloud file, and an image file of a target vehicle; a partitioning module configured to partition the navigation file into first files corresponding to each track of the target vehicle according to timestamps, partition the point cloud file into second files corresponding to each track, and partition the image file into third files corresponding to each track; A processing module is configured to generate a trip file corresponding to each first file, convert each second file into a preset data exchange format, and obtain a fourth file corresponding to each second file; The merging module is configured to merge the travel file, the third file and the fourth file corresponding to each trajectory to obtain a trajectory file corresponding to each trajectory.

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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