Data processing, data acquisition method and storage medium

Abstract

The application provides a data processing method, a map data acquisition method and a storage medium. The method comprises the following steps: acquiring map data, wherein the map data comprises X trajectory points and at least one trajectory point matched with a standard road segment; segmenting the X trajectory points according to the at least one trajectory point matched with the standard road segment and the collection time of the X trajectory points; generating description information of a trajectory segment according to the collection time of the trajectory points included in the trajectory segment and the matched standard road segment; performing attribute inspection on the trajectory segment by using the corresponding standard road segment data of the matched standard road segment in the standard map data, wherein the attribute inspection comprises topological continuity inspection of the trajectory segment and length inspection of the trajectory segment; and storing the trajectory points, the description information of the trajectory segment corresponding to the trajectory points and the attribute inspection result of the trajectory segment as a data processing result of the map data. The application improves the efficiency of high-precision map production based on data.

Description

Technical Field

[0001] This application relates to high-precision mapping technology, and more particularly to a data processing, data acquisition method, and storage medium. Background Technology

[0002] With technological advancements, electronic maps are evolving from standard maps (also known as high-precision maps) to high-precision maps. High-precision maps require the collection of data. While this data can be collected using specialized data collection vehicles, their high cost and limited availability mean that they typically collect as much data as possible. This results in a large volume of data, reducing the efficiency of creating high-precision maps based on this data. Summary of the Invention

[0003] This application provides a data processing and data acquisition method and a storage medium to improve the stability of data processing.

[0004] In a first aspect, this application provides a data processing method, the method comprising:

[0005] Acquire map data, which includes: X trajectory points, and at least one precise road segment matched by the trajectory points;

[0006] Based on the precise road segment matched by the at least one trajectory point and the acquisition time of the X trajectory points, the X trajectory points are segmented to obtain at least one trajectory segment;

[0007] Based on the acquisition time of the trajectory points included in the trajectory segment and the matched precision road segment, a description of the trajectory segment is generated;

[0008] Using the precise road segment data corresponding to the precise road segment in the precise map data matched by the trajectory segment, the trajectory segment is subjected to attribute checks to obtain the attribute check results of the trajectory segment. The attribute checks include: topological continuity check of the trajectory segment and length check of the trajectory segment.

[0009] The description information of the trajectory point, the trajectory segment corresponding to the trajectory point, and the attribute check result of the trajectory segment are stored as the data processing result of the map data.

[0010] Optionally, the step of segmenting the X trajectory points based on the precise road segment matched by the at least one trajectory point and the acquisition time of the X trajectory points to obtain at least one trajectory segment includes:

[0011] Based on the standard road segment matched by the trajectory points and the acquisition time of the X trajectory points, the trajectory points that match the same standard road segment and have consecutive acquisition times are grouped into the same trajectory segment.

[0012] Optionally, if the X trajectory points include trajectory points that do not match a precise road segment, then for the trajectory points that do not match a precise road segment, the method further includes:

[0013] Based on the collection time of the trajectory points of the road segments that were not matched with the standard precision road segment, a target trajectory segment is searched from the trajectory segments, and the collection time range of the trajectory points of the target trajectory segment covers the collection time of the trajectory points of the road segments that were not matched with the standard precision road segment.

[0014] The trajectory points that did not match the target road segment are assigned to the found target trajectory segment as new trajectory segments.

[0015] Optionally, if the X trajectory points include trajectory points for which no target trajectory segment was found, the method further includes:

[0016] From the new trajectory segment, obtain trajectory points whose segment matching confidence of the standard precision segment is less than the preset confidence threshold;

[0017] The trajectory points with a confidence threshold lower than the preset threshold and the trajectory points for which no target trajectory segment was found are used as trajectory points to be corrected for position coordinate correction.

[0018] Based on the corrected position coordinates of the trajectory point to be corrected, road segment matching is performed in the refined map data to obtain the refined road segment matched by the trajectory point to be corrected.

[0019] For the trajectory points to be corrected that match the standard road segment, and for the trajectory points contained in the new trajectory segment, the trajectory is re-segmented;

[0020] For trajectory points that do not match a precise road segment, the trajectory is segmented according to the time of trajectory point acquisition.

[0021] Optionally, the step of using the refined road segment data corresponding to the refined road segment matched by the trajectory segment in the refined map data to perform attribute checks on the trajectory segment and obtain the attribute check results of the trajectory segment includes:

[0022] If the trajectory segment has a matching precision road segment, then the precision road segment data corresponding to the matching precision road segment in the precision map data is used to perform attribute checks on the trajectory segment to obtain the attribute check results of the trajectory segment.

[0023] Optionally, the step of using the refined road segment data corresponding to the refined road segment matched by the trajectory segment in the refined map data to perform attribute checks on the trajectory segment and obtain the attribute check results of the trajectory segment includes:

[0024] Based on the length of the trajectory segment, and whether the difference between the length of the trajectory segment and the length of the road segment matched by the trajectory segment in the standard map data is less than a preset difference threshold, a first result is obtained to determine whether the length check of the trajectory segment passes.

[0025] Based on whether the trajectory segment is continuous with the time-adjacent trajectory segment in the position on the refined map data, a second result is obtained to determine whether the continuity check of the trajectory segment has passed.

[0026] Based on the first result and the second result of the trajectory segment, the attribute check result of the trajectory segment is obtained.

[0027] Optionally, obtaining the inspection result of the trajectory segment based on the first result and the second result of the trajectory segment includes:

[0028] If the first result indicates that the length check of the trajectory segment fails, then the check result of the trajectory segment is determined to be that the attribute check fails.

[0029] If the first result indicates that the length check of the trajectory segment has passed, and the second result indicates that the continuity check of the trajectory segment has passed, then the check result of the trajectory segment is determined to be that the attribute check has passed;

[0030] If the first result indicates that the length check of the trajectory segment has passed, the second result indicates that the continuity check of the trajectory segment has failed, and there are no trajectory points in the trajectory segment with a road segment matching confidence level less than or equal to the preset confidence threshold, then the check result of the trajectory segment is determined to be that the attribute check has failed.

[0031] If the first result indicates that the length check of the trajectory segment passes, the second result indicates that the continuity check of the trajectory segment fails, and there are trajectory points in the trajectory segment with a segment matching confidence level less than or equal to the preset confidence threshold, then the standard road segment matched by the trajectory point with a segment matching confidence level less than or equal to the preset confidence threshold is replaced with another standard road segment matched by the trajectory point. Based on the standard road segments after the trajectory point replacement, the trajectory points are re-segmented, and the attributes of the new trajectory segments are checked to obtain the attribute check results of the trajectory segments.

[0032] Optionally, the road segment matching confidence is obtained in advance based on the number of precise road segments matched by the trajectory point, and the road segment matching confidence of the trajectory point is negatively correlated with the number of road segments matched by the trajectory point.

[0033] Optionally, the method further includes:

[0034] If the trajectory segment has no matching standard road segment, then based on whether there is a first trajectory segment and a second trajectory segment that are temporally continuous with the trajectory segment and have a matching standard road segment, the attribute check of the trajectory segment is performed to obtain the attribute check result of the trajectory segment; the first trajectory segment is the trajectory segment that is temporally located before the trajectory segment, and the second trajectory segment is the trajectory segment that is temporally located after the trajectory segment.

[0035] Optionally, the step of performing attribute checks on the trajectory segment based on whether there exists a first trajectory segment and a second trajectory segment that are temporally continuous and have matching precision road segments, to obtain the attribute check result of the trajectory segment, includes:

[0036] Determine whether there exist a first trajectory segment and a second trajectory segment that are temporally continuous with the trajectory segment and have matching precision road segments;

[0037] If the first trajectory segment and / or the second trajectory segment do not exist, the check result of the trajectory segment is determined to be attribute check failure;

[0038] If the first trajectory segment and the second trajectory segment exist, and the standard route segments that match the first trajectory segment and the second trajectory segment are the same, then the trajectory segment, the first trajectory segment and the second trajectory segment are merged, and the attribute of the merged trajectory segment is checked.

[0039] If there are inconsistencies in the standard road segments that match the first trajectory segment and the second trajectory segment, and the length checks of the first trajectory segment and the second trajectory segment both pass, then the trajectory points in the trajectory segment are added to the first trajectory segment and the second trajectory segment respectively, and the attributes of the added first trajectory segment and the second trajectory segment are checked.

[0040] If the first trajectory segment and the second trajectory segment, the first trajectory segment and the second trajectory segment match different precision road segments, the length check of the first trajectory segment and / or the second trajectory segment fails, and the road segments matched by the first trajectory segment and the second trajectory segment are not connected in position in the precision map data, then the check result of the trajectory segment is determined to be attribute check failure.

[0041] If the first trajectory segment and the second trajectory segment, the matching precision road segments of the first trajectory segment and the second trajectory segment are inconsistent, the length check of the first trajectory segment and the second trajectory segment fails, and the road segments matched by the first trajectory segment and the second trajectory segment are connected in position in the precision map data, then the first trajectory segment and the second trajectory segment are extended to add trajectory points to the trajectory segment until the length check passes, and the continuity check is performed on the added first trajectory segment and second trajectory segment.

[0042] Secondly, this application provides a method for acquiring data, the method comprising:

[0043] Obtain the road segment identifier for the target road segment;

[0044] Based on the road segment identifier of the target road segment, data for generating high-precision map data of the target road segment is obtained from the data processing results of the map data.

[0045] If a first target trajectory segment is found in the data processing results of the map data based on the road segment identifier of the target road segment, then the data of trajectory points within the collection time range corresponding to the trajectory segment with non-repeating locations are obtained from the first target trajectory segment as the data of the target road segment. The first target trajectory segment contains the road segment identifier of the target road segment and the attribute check result is passed.

[0046] If, based on the segment identifier of the target road segment, a second target trajectory segment is found from the data processing results of the map data, and a third target trajectory segment is found that is topologically continuous with the second target trajectory segment and has no matching precision road segment, then the trajectory points within the collection time range corresponding to the third target trajectory segment are added to the second target trajectory segment one by one until the length check of the second target trajectory segment passes, and the data of the trajectory points within the collection time range corresponding to the second target trajectory segment that has passed the length check is used as the data of the target road segment; wherein, the second target trajectory segment is a trajectory segment that has the identifier of the target road segment, fails the attribute check, and has a matching confidence level greater than or equal to a preset confidence threshold.

[0047] Thirdly, this application provides a data processing apparatus, the apparatus comprising:

[0048] The acquisition module is used to acquire map data, which includes: X trajectory points and at least one precise road segment matched by the trajectory points;

[0049] The processing module is configured to: segment the X trajectory points according to the at least one trajectory point and the corresponding refined road segment, and the acquisition time of the X trajectory points, to obtain at least one trajectory segment; generate description information for the trajectory segment based on the acquisition time of the trajectory points included in the trajectory segment and the matched refined road segment; perform attribute checks on the trajectory segment using the refined road segment data corresponding to the matched refined road segment in the refined map data, to obtain the attribute check results of the trajectory segment; and store the trajectory points, the description information of the trajectory segment corresponding to the trajectory points, and the attribute check results of the trajectory segment as the data processing results of the map data; the attribute checks include: topological continuity checks of the trajectory segment and length checks of the trajectory segment.

[0050] Fourthly, this application provides a data acquisition device, the device comprising:

[0051] The first acquisition module is used to acquire the road segment identifier of the target road segment;

[0052] The second acquisition module is used to acquire data for generating high-precision map data of the target road segment from the data processing results of the map data, based on the road segment identifier of the target road segment.

[0053] If a first target trajectory segment is found in the data processing results of the map data based on the road segment identifier of the target road segment, then the data of trajectory points within the collection time range corresponding to the trajectory segment with non-repeating locations are obtained from the first target trajectory segment as the data of the target road segment. The first target trajectory segment contains the road segment identifier of the target road segment and the attribute check result is passed.

[0054] If, based on the segment identifier of the target road segment, a second target trajectory segment is found from the data processing results of the map data, and a third target trajectory segment is found that is topologically continuous with the second target trajectory segment and has no matching precision road segment, then the trajectory points within the collection time range corresponding to the third target trajectory segment are added to the second target trajectory segment one by one until the length check of the second target trajectory segment passes, and the data of the trajectory points within the collection time range corresponding to the second target trajectory segment that has passed the length check is used as the data of the target road segment; wherein, the second target trajectory segment is a trajectory segment that has the identifier of the target road segment, fails the attribute check, and has a matching confidence level greater than or equal to a preset confidence threshold.

[0055] Fifthly, this application provides an electronic device, including: a processor and a memory; the processor and the memory are communicatively connected.

[0056] The memory stores computer-executed instructions;

[0057] The processor executes computer execution instructions stored in the memory to implement the method as described in any one of the first and second aspects.

[0058] In a sixth aspect, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the data processing method as described in either the first or second aspect.

[0059] In a seventh aspect, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method described in either the first aspect or the second aspect.

[0060] The data processing, data acquisition method, and storage medium provided in this application segment X trajectory points in map data by using at least one precision road segment matched with trajectory points and the acquisition time of X trajectory points, thus obtaining at least one trajectory segment. Then, using the acquisition time of the trajectory points included in the trajectory segment and the matched precision road segment, descriptive information for the trajectory segment can be generated. By dividing the trajectory points into trajectory segments, the descriptive information of one trajectory segment can describe multiple trajectory points within that segment. Using precision map data, topological continuity checks and length checks are performed on each trajectory segment to obtain attribute check results for each trajectory segment. By performing attribute checks on the trajectory segments, the accuracy of trajectory segment division and trajectory segment descriptive information is ensured. Then, by storing the description information of the trajectory points, the trajectory segments corresponding to the trajectory points, and the attribute check results of the trajectory segments as the data processing results of the map data, the data processing results of the map data include the description information of the trajectory segments where the trajectory points are located and the attribute check results of the trajectory segments. This allows subsequent map data acquisition to be based on the description information and attribute check results of the trajectory segments, rather than processing the data of all road segments as data, thereby improving the efficiency of creating high-precision maps based on this map data. Attached Figure Description

[0061] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0062] Figure 1 This is a schematic diagram of a map data collection scenario;

[0063] Figure 2 This application provides an illustration of an application scenario for a high-precision map processing system.

[0064] Figure 3 This application provides an illustration of another high-precision map processing system.

[0065] Figure 4 A schematic diagram of the hardware structure of an electronic device 10 equipped with a high-precision map processing system;

[0066] Figure 5 A flowchart illustrating a data processing method provided in this application;

[0067] Figure 6 A schematic diagram of a trajectory segment provided for this application;

[0068] Figure 7 A flowchart illustrating a trajectory segment division method for trajectory points where no target trajectory segment was found, provided in this application;

[0069] Figure 8 A schematic diagram of a first trajectory segment and a second trajectory segment provided for this application;

[0070] Figure 9 A flowchart illustrating a method for attribute checking of trajectory segments in unmatched precision road sections provided in this application;

[0071] Figure 10 A flowchart illustrating another data processing method provided in this application;

[0072] Figure 11 A schematic diagram of the structure of a data processing device 30 provided in this application;

[0073] Figure 12 A schematic diagram of the structure of a data acquisition device 40 provided in this application.

[0074] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0075] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0076] Considering the limited resources and high cost of high-definition (HD) map data collection vehicles, each dispatch task for these vehicles will be based on the principle of collecting as much map data as possible. For example, Figure 1 This is a schematic diagram of a map data collection scenario. (For example...) Figure 1 As shown, when the high-precision map acquisition vehicle performs a scheduling task, it will collect map data for all road segments (Links) corresponding to the scheduling task route in order to obtain map data.

[0077] Taking the application of the aforementioned map data to intelligent driving as an example, after acquiring the map data, the high-precision map processing system can process the map data to obtain map data that can be used by intelligent driving.

[0078] However, because the high-precision map acquisition vehicle collects map data for all road segments along a single dispatch route, the aforementioned map data typically includes map data for all road segments along that route. In other words, the high-precision map processing system needs to process map data from all road segments, resulting in a large volume of data and reduced efficiency in creating high-precision maps based on that data.

[0079] Considering that existing map data processing methods suffer from low efficiency due to the need to process map data for all road segments, this application proposes a method based on Standard Definition (SD) map data. This method divides trajectory points in the map data into trajectory segments and adds descriptive information to these segments. The trajectory segments obtained through this method match the SD road segments in the processed map data, thereby improving the efficiency of creating high-precision maps based on the processed map data.

[0080] Optionally, the entity executing this data processing method can be a high-precision map processing system. For example, Figure 2 This application provides an illustration of an application scenario for a high-precision map processing system, such as... Figure 2As shown, in one embodiment, the high-precision map processing system can be entirely deployed in a cloud environment. A cloud environment is an entity that provides cloud services to users using basic resources under a cloud computing model. The cloud environment includes a cloud data center and a cloud service platform. The cloud data center includes a large amount of basic resources (including computing resources, storage resources, and network resources) owned by the cloud service provider. The computing resources included in the cloud data center can be a large number of electronic devices (e.g., servers). For example, taking the computing resources included in the cloud data center as servers running virtual machines, the high-precision map processing system can be deployed independently on servers or virtual machines in the cloud data center. Alternatively, the high-precision map processing system can be distributed and deployed on multiple servers in the cloud data center, or distributed and deployed on multiple virtual machines in the cloud data center, or distributed and deployed on servers and virtual machines in the cloud data center. Figure 2 As shown, the cloud environment can provide data processing services to users by utilizing a high-precision map processing system deployed in a cloud data center.

[0081] Figure 3 This is a schematic diagram illustrating an application scenario for another high-precision map processing system provided in this application. The high-precision map processing system provided in this application has relatively flexible deployment, such as... Figure 3 As shown, in another embodiment, the high-precision map processing system provided in this application can also be distributed and deployed in different environments. The high-precision map processing system provided in this application can be logically divided into multiple parts, each with different functions. Each part of the high-precision map processing system can be deployed in any two or three of the following: terminal electronic devices (located on the user side), edge environments, and cloud environments. Terminal electronic devices located on the user side can include, for example, at least one of the following: terminal servers, smartphones, laptops, tablets, personal desktop computers, etc. The edge environment is an environment including a set of edge electronic devices located close to the terminal electronic devices, including: edge servers, edge stations with computing power, etc. The various parts of the high-precision map processing system deployed in different environments or devices work together to provide users with automatic data processing functions. It should be understood that this application does not restrict the specific environments in which the parts of the high-precision map processing system are deployed. In practical applications, deployment can be adaptively made according to the computing power of the terminal electronic devices, the resource availability of the edge and cloud environments, or specific application requirements. Figure 3 This is a schematic diagram illustrating application scenarios using high-precision map processing systems deployed in edge and cloud environments, respectively.

[0082] High-precision map processing systems can also be deployed independently on an electronic device in any environment (e.g., on an edge server in an edge environment). Figure 4 This is a schematic diagram of the hardware structure of an electronic device 10 equipped with a high-precision map processing system. Figure 4 The illustrated electronic device 10 includes a memory 11, a processor 12, and a communication interface 13. The memory 11, processor 12, and communication interface 13 are communicatively connected to each other. For example, the memory 11, processor 12, and communication interface 13 can be connected via a network. Alternatively, the electronic device 10 may also include a bus 14. The memory 11, processor 12, and communication interface 13 are communicatively connected to each other via the bus 14. Figure 4 It is an electronic device 10 in which the memory 11, processor 12, and communication interface 13 are connected to each other via bus 14.

[0083] The memory 11 can be a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 11 can store programs, and when the program stored in the memory 11 is executed by the processor 12, the processor 12 and the communication interface 13 are used to execute data processing methods.

[0084] The processor 12 may be a general-purpose CPU, microprocessor, application-specific integrated circuit (ASIC), graphics processing unit (GPU), or one or more integrated circuits.

[0085] Processor 12 can also be an integrated circuit chip with signal processing capabilities. In implementation, the functions of the high-precision map processing system of this application can be accomplished through integrated logic circuits in the hardware of processor 12 or through software instructions. The aforementioned processor 12 can also be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the following embodiments of this application. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the following embodiments of this application can be directly implemented by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory 11, and processor 12 reads information from memory 11 and, in conjunction with its hardware, completes the functions of the high-precision map processing system of this application.

[0086] Communication interface 13 uses transceiver modules, such as, but not limited to, transceivers, to enable communication between electronic device 10 and other devices or communication networks. For example, data sets can be acquired through communication interface 13.

[0087] When the aforementioned electronic device 10 includes a bus 14, the bus 14 may include a path for transmitting information between various components of the electronic device 10 (e.g., memory 11, processor 12, communication interface 13).

[0088] The following description continues to use a high-precision map processing system as the execution subject of the data processing method as an example, and provides a detailed explanation of the technical solution of this application in conjunction with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0089] Figure 5 This is a flowchart illustrating a data processing method provided in this application. Figure 5 As shown, the method includes the following steps:

[0090] S101. Obtain map data.

[0091] The aforementioned map data may include: X trajectory points, and at least one precise road segment matched by each trajectory point. For example, the precise road segment matched by a trajectory point may be represented by a road segment identifier. This road segment identifier may be, for example, a road segment identification document (ID). X may be an integer greater than or equal to 2. Of the X trajectory points, some may match a precise road segment, while others may not. Alternatively, each of the X trajectory points may match a precise road segment. Optionally, the map data may be data collected by a map data acquisition device during a single drive of a high-precision map acquisition vehicle on a road.

[0092] For example, the high-precision map processing system can acquire the aforementioned map data by receiving map data reported by the map data acquisition device of the high-precision map acquisition vehicle. In some embodiments, the high-precision map processing system can also receive the map data input by the user through an application programming interface (API) or a graphical user interface (GUI).

[0093] It should be understood that each trajectory point in the aforementioned map data may correspond to specific data. For example, for any trajectory point, the data may include, for instance, visible light images of the road acquired at that trajectory point, laser point cloud data, location information, etc. It should be understood that this application does not limit the content of the data for each of the aforementioned trajectory points.

[0094] S102. Based on the standard road segment matched by at least one trajectory point and the acquisition time of X trajectory points, the X trajectory points are segmented to obtain at least one trajectory segment.

[0095] Optionally, a trajectory segment may include at least one trajectory point. The matching precision road segments for all trajectory points within a trajectory segment can be identical. Between different trajectory segments, the matching precision road segments for the trajectory points within each segment can be the same or different.

[0096] Optionally, the high-precision map processing system can first determine whether each of the aforementioned X trajectory points matches a marked road segment. If each of the X trajectory points matches a marked road segment, the high-precision map processing system can group the trajectory points that match the same marked road segment and whose acquisition time is consecutive into the same trajectory segment. If the aforementioned X trajectory points include trajectory points that do not match a marked road segment, the high-precision map processing system can, optionally, first divide the trajectory points that match marked road segments into trajectory segments, and then determine the trajectory segment containing the trajectory points that do not match a marked road segment based on the trajectory segment division result.

[0097] S103. Generate description information for the trajectory segment based on the acquisition time of the trajectory points included in the trajectory segment and the matched standard road segment.

[0098] For example, the acquisition time of the aforementioned trajectory points can be a timestamp of the trajectory points. Optionally, the timestamp can be a timestamp obtained by the map data acquisition device through satellite time synchronization when determining the location information of the trajectory points through satellite positioning.

[0099] For any trajectory segment, for example, the description information of the trajectory segment may include: the acquisition time range of the trajectory segment, and information such as the benchmark road segments matched by the trajectory segment to describe the trajectory segment. The acquisition time range of the trajectory segment can be the time range between the acquisition time of the earliest acquisition point and the acquisition time of the latest acquisition point in the trajectory segment. The benchmark road segments matched by the trajectory segment can be the same as the benchmark road segments matched by the trajectory points included in the trajectory segment.

[0100] S104. Using the precise road segment data corresponding to the precise road segment in the precise map data matched by the above trajectory segment, perform attribute checks on the trajectory segment to obtain the attribute check results of the trajectory segment.

[0101] The attribute check may include: a topological continuity check of the trajectory segment and a length check of the trajectory segment. For example, the topological continuity check of the trajectory segment may mean determining whether the trajectory segment is geographically continuous with other road segments included in the refined map data. The length check of the trajectory segment may, for example, mean determining whether the error between the length of the trajectory segment and the length of the corresponding refined road segment in the refined map data is within a preset error range.

[0102] For example, the aforementioned high-precision map data may include the location information of all road segments within a region, as well as the road segment identifier for each road segment. Optionally, the high-precision map data may be pre-stored in the high-precision map processing system.

[0103] For example, a high-precision map processing system can use different identifiers to represent different attribute check results. For instance, 1 can be used to indicate a pass result for the attribute check, while 0 can be used to indicate a fail result.

[0104] S105. Store the description information of the above trajectory points and the trajectory segments corresponding to the trajectory points, as well as the attribute check results of the trajectory segments, as the data processing results of the above map data.

[0105] For example, a high-precision map processing system can establish a mapping relationship between the description information and the inspection results of each trajectory segment based on the description information of the trajectory segment corresponding to the trajectory point and the attribute inspection results of the trajectory segment. Then, the high-precision map processing system can store the data processing results of the map data based on the above trajectory points and the mapping relationship.

[0106] It should be understood that this application does not limit the storage location or storage method of the data processing results of the aforementioned map data. For example, a high-precision map processing system may store the data processing results of the map data in the database of the high-precision map processing system.

[0107] In this embodiment, by using at least one precise road segment matched with a trajectory point and the acquisition time of X trajectory points, the X trajectory points in the map data are segmented to obtain at least one trajectory segment. Then, using the acquisition time of the trajectory points included in the trajectory segment and the matched precise road segment, description information of the trajectory segment can be generated. By dividing the trajectory points into trajectory segments, the description information of one trajectory segment can describe multiple trajectory points within that segment. Using the precise map data, the topological continuity and length of each trajectory segment are checked to obtain the attribute check results for each trajectory segment. By performing attribute checks on the trajectory segments, the accuracy of the trajectory segment division and the trajectory segment description information is ensured. Then, by storing the description information of the trajectory points, the trajectory segments corresponding to the trajectory points, and the attribute check results of the trajectory segments as the data processing results of the map data, the data processing results of the map data include the description information of the trajectory segments where the trajectory points are located and the attribute check results of the trajectory segments. This allows subsequent map data acquisition to be based on the description information and attribute check results of the trajectory segments, rather than processing the data of all road segments as data, thereby improving the efficiency of creating high-precision maps based on this map data.

[0108] The following provides a detailed explanation of how a high-precision map processing system, based on the precise road segment matched by at least one trajectory point and the acquisition time of X trajectory points, segments the X trajectory points to obtain at least one trajectory segment:

[0109] As a first possible implementation, the high-precision map processing system can classify the X trajectory points that match the same high-precision road segment and have consecutive collection times into the same trajectory segment based on the high-precision road segment matched by the trajectory points and the collection time of the X trajectory points.

[0110] Taking the example of X trajectory points all matching marked road segments, the high-precision map processing system can first sort the trajectory points according to their acquisition time, resulting in a chronologically ordered list of trajectory points. Then, the high-precision map processing system can group trajectory points acquired at consecutive times and matching the same marked road segments into the same trajectory segment.

[0111] For example, suppose the road segment identifiers of 10 consecutive trajectory points arranged in chronological order are as follows: AAAABBBAAA. Optionally, the high-precision map processing system can divide these 10 trajectory points into 3 trajectory segments. The first 4 consecutive trajectory points with the identifier AAAA constitute trajectory segment 1. The 3 consecutive trajectory points with the identifier BBB constitute trajectory segment 2. The last 3 consecutive trajectory points with the identifier AAA constitute trajectory segment 3.

[0112] Taking the aforementioned X trajectory points, including those without a matched precise road segment as an example, for each trajectory point without a matched precise road segment:

[0113] Optionally, the high-precision map processing system can, for each trajectory point that does not match a specified road segment, obtain the matched specified road segment based on the location information of the trajectory point and the specified map data. Then, the high-precision map processing system can segment the trajectory points in the map data according to the matched specified road segments of each trajectory point to obtain at least one trajectory segment.

[0114] Alternatively, the high-precision map processing system can divide at least one trajectory point that is consecutive in the acquisition time and does not match a standard precision road segment into a trajectory segment. In this implementation, the trajectory segment can be a trajectory segment without a matching standard precision road segment.

[0115] Alternatively, the high-precision map processing system can search for a target trajectory segment from the aforementioned trajectory segments based on the acquisition time of trajectory points that did not match the target road segment. The acquisition time range of the trajectory points in this target trajectory segment covers the acquisition time of the trajectory points that did not match the target road segment. Then, the high-precision map processing system can assign the trajectory points that did not match the target road segment to the found target trajectory segment as a new trajectory segment.

[0116] For example, taking the aforementioned matching of 10 consecutive trajectory points arranged in chronological order as an example: AAAABBBAAA, Figure 6 This is a schematic diagram of a trajectory segment provided in this application. (For example...) Figure 6 As shown, assuming the acquisition time of the trajectory points that did not match the target road segment is time 1, and the acquisition time range of trajectory points in trajectory segment 1 covers the acquisition time of the trajectory points that did not match the target road segment, the high-precision map processing system can determine that trajectory segment 1 is the target trajectory segment. Then, the high-precision map processing system can assign the trajectory points that did not match the target road segment to trajectory segment 1 to obtain a new trajectory segment.

[0117] If the above X trajectory points include trajectory points for which no target trajectory segment was found. Figure 7 This is a flowchart illustrating a trajectory segment division method for trajectory points where no target trajectory segment was found, as provided in this application. Figure 7 As shown, optionally, the high-precision map processing system can perform the following steps:

[0118] S201. From the new trajectory segments mentioned above, obtain the trajectory points whose segment matching confidence of the standard precision segment is less than the preset confidence threshold.

[0119] Optionally, the road segment matching confidence of a trajectory point can be related to the number of accurately matched road segments. In some embodiments, when the number of matched road segments is greater than zero, the road segment matching confidence of a trajectory point is negatively correlated with the number of matched road segments. That is, the fewer the number of matched road segments, the higher the road segment matching confidence of the trajectory point can be. When the number of matched road segments is zero, the road segment matching confidence of the trajectory point can be equal to zero.

[0120] In some embodiments, the aforementioned preset confidence threshold may be a value that the user has pre-stored in the high-precision map processing system.

[0121] Optionally, the road segment matching confidence of a trajectory point can be determined by the high-precision map processing system after acquiring the trajectory point, based on the number of standard road segments matched by the trajectory point. Alternatively, the road segment matching confidence of a trajectory point can also be obtained in advance based on the number of standard road segments matched by the trajectory point. In this implementation, this application does not limit the executing entity used to obtain the road segment matching confidence of the trajectory point. For example, the high-precision map processing system can obtain the road segment matching confidence of the trajectory point in advance based on the number of standard road segments matched by the trajectory point. Alternatively, the high-precision map acquisition vehicle can obtain the road segment matching confidence of the trajectory point in advance based on the number of standard road segments matched by the trajectory point. The high-precision map processing system can obtain the road segment matching confidence of the trajectory point from the high-precision map acquisition vehicle.

[0122] S202. Trajectory points with a lower than the preset confidence threshold and trajectory points for which no target trajectory segment was found are used as trajectory points to be corrected for position coordinate correction.

[0123] It should be understood that this application does not limit how the high-precision map processing system performs position coordinate correction on the trajectory points to be corrected. Optionally, any existing implementation method for trajectory point position coordinate correction can be referred to, which will not be elaborated here.

[0124] S203. Based on the corrected position coordinates of the trajectory points to be corrected, perform road segment matching in the refined map data to obtain the refined road segments that match the trajectory points to be corrected.

[0125] Optionally, the high-precision map processing system can, for example, calculate the distance between the trajectory point to be corrected and each road segment in the preset area included in the high-precision map data, based on the corrected position coordinates of the trajectory point to be corrected. Then, the high-precision map processing system can use road segments whose distance to the trajectory point to be corrected is less than a preset distance threshold as the high-precision road segments matched with the trajectory point to be corrected.

[0126] S204. For the trajectory points to be corrected that match the standard road segment, and the trajectory points contained in the new trajectory segment, re-segment the trajectory.

[0127] Optionally, the specific implementation of re-segmenting the trajectory can refer to the method described in any embodiment of this application, and will not be repeated here.

[0128] S205. For trajectory points to be corrected that do not match a standard road segment, segment the trajectory according to the time of trajectory point acquisition.

[0129] For example, the high-precision map processing system can also divide the trajectory points to be corrected, where the trajectory points are collected in consecutive time and do not match any standard road segments, into a trajectory segment. In this implementation, the trajectory segment can be a trajectory segment without a matching standard road segment.

[0130] It should be understood that this application does not limit the order in which the high-precision map processing system performs the above steps S204 and S205. Optionally, the high-precision map processing system may also perform steps S204 and S205 simultaneously.

[0131] In this embodiment, the high-precision map processing system can calibrate the position coordinates of trajectory points with low road segment matching confidence in the trajectory segment, and re-segment the trajectory based on the corrected position coordinates. This makes the trajectory segment division result determined based on the calibrated trajectory points, thereby improving the accuracy of trajectory segment division and thus improving the accuracy of the data processing results obtained from the above-mentioned map data.

[0132] Taking the example of trajectory points among the aforementioned X trajectory points where no target trajectory segment was found, optionally, for these trajectory points where no target trajectory segment was found, the high-precision map processing system can, for example, divide at least one trajectory point with a continuous acquisition time into a trajectory segment according to the acquisition time of the trajectory point where no target trajectory segment was found. In this implementation, the trajectory segment can be a non-matching precision road segment. Optionally, the high-precision map processing system can, for example, indicate that the trajectory segment is a non-matching precision road segment by not adding a road segment identifier, or by adding an identifier to the trajectory point to indicate that the trajectory segment has no matching precision road segment. For example, assuming that the acquisition times of at least one trajectory point with a continuous acquisition time where no target trajectory segment was found are all within the range of... Figure 6 In the time range 1 shown, the high-precision map processing system can take at least one trajectory point in the continuous acquisition time that has not found the target trajectory segment as a trajectory segment.

[0133] Regarding how to segment the X trajectory points based on the at least one matched road segment and the acquisition time of X trajectory points to obtain at least one trajectory segment, as a second possible implementation, the high-precision map processing system can also determine the segment matching confidence of each trajectory point among the at least one trajectory point based on the number of matched road segments. Then, the high-precision map processing system can perform position coordinate correction on trajectory points whose segment matching confidence is less than a preset confidence threshold. Finally, the high-precision map processing system can use the corrected position coordinates of the trajectory points to perform road segment matching in the refined map data to obtain the matched road segment after the trajectory point correction.

[0134] Then, the high-precision map processing system can segment the X trajectory points based on the matched precision road segments after trajectory point correction and the acquisition time of the X trajectory points, to obtain at least one trajectory segment. Optionally, the method by which the high-precision map processing system segments the X trajectory points based on the matched precision road segments after trajectory point correction and the acquisition time of the X trajectory points can refer to the first possible implementation of "segmenting the X trajectory points based on the matched precision road segments of at least one trajectory point and the acquisition time of the X trajectory points to obtain at least one trajectory segment" described in the foregoing embodiment, which will not be elaborated here.

[0135] The following is a detailed explanation of the road segment matching confidence of the above trajectory points:

[0136] As mentioned above, the road segment matching confidence score can be obtained in advance based on the number of standardized road segments matched by the trajectory points. The following example illustrates the road segment matching confidence score of trajectory points using the map data acquisition device of the high-precision map acquisition vehicle, obtained based on the number of standardized road segments matched by the trajectory points:

[0137] As one possible implementation, the map data acquisition device can, during the map data acquisition process, use refined map data to obtain refined road segments matching the acquired M trajectory points. Here, M is an integer, and M is less than or equal to the aforementioned X.

[0138] Optionally, the refined map data can be pre-stored by the user in the map data acquisition device. This refined map data may include, for example, the location information and segment identifier for each road segment.

[0139] Optionally, during the map data acquisition process, for any one of the M trajectory points, the map data acquisition device can, for example, calculate the distance between the trajectory point and each road segment included in the refined map data using the location information of the trajectory point and the location information of each road segment. Then, the map data acquisition device can use road segments whose distance from the trajectory point is less than a preset distance threshold as the refined road segments matched with the trajectory point.

[0140] After acquiring the precise road segments matching the M collected trajectory points, the map data acquisition device can obtain the matching confidence score for each trajectory point based on the number of precise road segments matching each trajectory point. Optionally, the road segment matching confidence score of the trajectory point can be negatively correlated with the number of road segments matching the trajectory point.

[0141] For example, the map data acquisition device may pre-store a mapping relationship between the number of matched precise road segments and the matching confidence level. For any trajectory point among M trajectory points, the map acquisition device can determine the matching confidence level of the trajectory point based on the number of matched precise road segments and the mapping relationship. For example, if the number of matched precise road segments of the trajectory point is 1, that is, the trajectory point can match one and only one precise road segment, then the matching confidence level of the trajectory point can be high. If the number of matched precise road segments of the trajectory point is greater than or equal to 2, it indicates that the accuracy of the trajectory point's location may be poor, then the matching confidence level of the trajectory point can be low. If the number of matched precise road segments of the trajectory point is 0, it indicates that the location of the trajectory point may be incorrect, then the matching confidence level of the trajectory point can be 0. For example, with Figure 1 Taking the road segment shown as an example, the precise road segment for trajectory point matching and the road segment matching confidence can be shown in Table 1 below:

[0142] Table 1

[0143] High-precision road segments for trajectory point matching Road segment matching confidence of trajectory points Section 1 or Section 2 2 Section 1 and Section 2 1 none 0

[0144] In this embodiment, the map data acquisition device can acquire M precise road segments with matching trajectories and road segment matching confidence scores, instead of acquiring X precise road segments with matching trajectories and matching confidence scores. This reduces the amount of data that the map data acquisition device needs to process and improves the efficiency of the map data acquisition device in data processing.

[0145] As mentioned above, in some embodiments, the trajectory segment may have a matching precision road segment, for example, the precision road segment matched by the trajectory segment may be a precision road segment matched by the trajectory points included in the trajectory segment. In some embodiments, the trajectory segment may also have no matching precision road segment.

[0146] Therefore, the following section will take two cases as examples: trajectory segments with matching high-precision road segments and trajectory segments without matching high-precision road segments, to explain in detail how the high-precision map processing system performs attribute checks on each trajectory segment and obtains the attribute check results for each trajectory segment.

[0147] If a trajectory segment has a matching precision road segment, as a possible implementation, the high-precision map processing system can use the precision road segment data corresponding to the matching precision road segment in the precision map data to perform attribute checks on the trajectory segment and obtain the attribute check results of the trajectory segment.

[0148] As mentioned above, the attribute check may include a topological continuity check of the trajectory segment and a length check of the trajectory segment. It should be understood that this application does not limit the order in which the high-precision map processing system performs continuity and length checks on the trajectory segment. The following example, where the high-precision map processing system performs a length check on the trajectory segment first, followed by a topological continuity check, will be used to illustrate the attribute check in detail:

[0149] Regarding the length check of a trajectory segment, optionally, the high-precision map processing system can determine whether the length check of the trajectory segment passes based on whether the difference between the length of the trajectory segment and the length of the road segment matching the trajectory segment in the high-precision map data is less than a preset difference threshold. If the difference between the length of the trajectory segment and the length of the road segment matching the trajectory segment in the high-precision map data is less than the preset difference threshold, it indicates that the data collection for that road segment in the map data is complete, and the high-precision map processing system can determine that the first result is that the length check of the trajectory segment passes. If the difference between the length of the trajectory segment and the length of the road segment matching the trajectory segment in the high-precision map data is greater than or equal to the preset difference threshold, it indicates that the data collection for that road segment in the map data is incomplete, and the high-precision map processing system can determine that the first result is that the length check of the trajectory segment fails. For example, the high-precision map processing system can use identifier 3 to indicate that the first result is that the length check of the trajectory segment passes, and identifier 4 to indicate that the first result is that the length check of the trajectory segment fails.

[0150] For example, the aforementioned preset difference threshold can be pre-stored by the user in the high-precision map processing system. It should be understood that this application does not limit how the high-precision map processing system calculates the length of a trajectory segment. For example, the high-precision map processing system can first fit the trajectory points included in the trajectory segment to obtain a line segment. Then, the high-precision map processing system can calculate the length of this line segment as the length of the trajectory segment.

[0151] For the continuity check of trajectory segments, optionally, the high-precision map processing system can obtain a second result regarding whether the continuity check of the trajectory segment passes based on whether the trajectory segment is continuous with the time-adjacent trajectory segment in the high-precision map data. If the trajectory segment is continuous with the time-adjacent trajectory segment in the high-precision map data, the high-precision map processing system can determine that the second result indicates the continuity check of the trajectory segment passes. If the trajectory segment is not continuous with the time-adjacent trajectory segment in the high-precision map data, the high-precision map processing system can determine that the second result indicates the continuity check of the trajectory segment fails. For example, the high-precision map processing system can use identifier 1 to indicate that the second result indicates the continuity check of the trajectory segment passes, and identifier 2 to indicate that the second result indicates the continuity check of the trajectory segment fails.

[0152] For example, a high-precision map processing system can determine that a trajectory segment is continuous with its temporally adjacent trajectory segment in the high-precision map data when the distance between the end of the trajectory segment and the end of a time-adjacent trajectory segment is less than or equal to a preset continuity check distance threshold. Conversely, a high-precision map processing system can determine that a trajectory segment is discontinuous with its temporally adjacent trajectory segment in the high-precision map data when the distance between the end of the trajectory segment and the end of a time-adjacent trajectory segment is greater than the preset continuity check distance threshold. For example, the preset continuity check distance threshold can be pre-stored by the user in the high-precision map processing system.

[0153] After obtaining the second and first results of the trajectory segment, the high-precision map processing system can obtain the attribute check results of the trajectory segment based on the second and first results of the trajectory segment.

[0154] The following section provides a detailed explanation of how a high-precision map processing system obtains the attribute check results of a trajectory segment based on the second result and the first result of the trajectory segment:

[0155] As a first possible implementation, the high-precision map processing system can determine that the attribute check of a trajectory segment has passed when the second result of the trajectory segment indicates that the continuity check of the trajectory segment has passed, and the first result of the trajectory segment indicates that the length check of the trajectory segment has passed. If the second result indicates that the continuity check of the trajectory segment has failed, or the first result indicates that the length check of the trajectory segment has failed, or the second result indicates that the continuity check of the trajectory segment has failed and the first result also indicates that the length check of the trajectory segment has failed, then the high-precision map processing system can determine that the attribute check of the trajectory segment has failed.

[0156] As a second possible implementation, if the first result indicates that the length check of the trajectory segment fails, it means that the data collection for that road segment in the map data is incomplete. Therefore, the high-precision map processing system can also directly determine that the trajectory segment's check result is an attribute check failure, thereby improving the accuracy of the map data processing results. When the first result indicates that the length check of the trajectory segment passes, and the second result indicates that the continuity check of the trajectory segment (it should be understood that the continuity checks mentioned throughout this application refer to topological continuity checks) passes, the high-precision map processing system can determine that the trajectory segment's check result is an attribute check success.

[0157] In this implementation, optionally, considering that there may be trajectory points with low road segment matching confidence in the trajectory segment, since trajectory points with low road segment matching confidence can match multiple high-precision road segments, the high-precision map processing system can further determine the attribute check result of the trajectory segment based on the road segment matching confidence when the length check of the trajectory segment represented by the first result passes and the continuity check of the trajectory segment represented by the second result fails.

[0158] Optionally, if the first result represents the trajectory segment length check passing, and the second result represents the trajectory segment continuity check failing, and there are no trajectory points in the trajectory segment with a road segment matching confidence level less than or equal to a preset confidence threshold, it indicates that the trajectory segment does not have low-confidence trajectory points. In other words, other matching, high-precision road segments without trajectory points can make the attribute check of the trajectory segment pass. Therefore, the high-precision map processing system can determine that the trajectory segment's check result is an attribute check failure, thereby improving the accuracy of the map data processing results.

[0159] If the first result, representing the length check of the trajectory segment, passes, and the second result, representing the continuity check of the trajectory segment, fails, and there are trajectory points in the trajectory segment with a road segment matching confidence level less than or equal to a preset confidence threshold, it indicates that the trajectory segment contains trajectory points with low road segment confidence, meaning that there are trajectory points with replaceable standard road segments. The high-precision map processing system can then replace the standard road segments matched by the trajectory points with road segment matching confidence levels less than or equal to the preset confidence threshold with other standard road segments matched by that trajectory point. Then, based on the replaced standard road segments, the high-precision map processing system can re-segment the trajectory for each trajectory point and perform attribute checks on the new trajectory segments to obtain the attribute check results for the trajectory segments.

[0160] When a high-precision map processing system replaces a road segment matched by a trajectory point with a confidence level less than or equal to a preset confidence threshold with another road segment matched by that trajectory point, it may optionally, for example, update the road segments matched by each low-confidence trajectory point in the trajectory segment to obtain the updated road segments for each trajectory point.

[0161] Alternatively, in some embodiments, the high-precision map processing system can also determine the trajectory points of the standard precision road segment to be replaced based on the trajectory points that cause the continuity check of the trajectory segment to fail. For example, taking three temporally consecutive trajectory points in a trajectory segment as an example, assuming that these three temporally consecutive trajectory points are all low-confidence trajectory points, and the standard precision road segments that each trajectory point can match are shown in Table 2 below:

[0162] Table 2

[0163] trajectory points Trajectory point 1 Trajectory point 2 Trajectory point 3 The first standard segment matched A A A The second standard road segment matched B B C

[0164] Optionally, as mentioned above, the high-precision map processing system can obtain a second result regarding whether the continuity check of a trajectory segment passes based on whether the trajectory segment and its temporally adjacent trajectory segments are continuous in position on the high-precision map data. Here, the temporally adjacent trajectory segments can be those preceding or following the trajectory segment. Taking Table 2 as an example, assume that the road segment identifiers when trajectory points 1-3 constitute this trajectory segment are AAA.

[0165] In this implementation, optionally, the high-precision map processing system can, when the continuity check of the trajectory segment with "time adjacent trajectory segments before this trajectory segment" fails, replace the road segment identifier of trajectory point 1 and trajectory point 2 with B, obtaining the replaced high-precision road segment corresponding to Update 1 as shown in Table 3 below. The high-precision map processing system can, when the continuity check of the trajectory segment with "time adjacent trajectory segments after this trajectory segment" fails, replace the road segment identifier of trajectory point 3 with C, obtaining the replaced high-precision road segment corresponding to Update 2 as shown in Table 3 below. The high-precision map processing system can, when the continuity check of the trajectory segment with "time adjacent trajectory segments after this trajectory segment" fails, and the continuity check with "time adjacent trajectory segments before this trajectory segment" also fails, replace the road segment identifiers of trajectory point 1, trajectory point 2, and trajectory point 3 with BBC respectively, obtaining the replaced high-precision road segment corresponding to Update 3 as shown in Table 3 below.

[0166] Table 3

[0167] trajectory points Trajectory point 1 Trajectory point 2 Trajectory point 3 Before the update A A A Update 1 B B A Update 2 A A C Update 3 B B C

[0168] After obtaining the matched high-precision road segments after replacing each trajectory point, the high-precision map processing system can re-segment all trajectory points to obtain new trajectory segment division results. Then, the high-precision map processing system can perform attribute checks on the new trajectory segments to obtain the check results. Optionally, the method by which the high-precision map processing system performs attribute checks on the above-mentioned new trajectory segments can refer to the method described in the foregoing embodiments, and will not be repeated here.

[0169] If no matching high-precision road segment exists for a trajectory segment, as a possible implementation, the high-precision map processing system can perform attribute checks on the trajectory segment based on whether there exists a first trajectory segment and a second trajectory segment that are temporally continuous and have matching high-precision road segments, thus obtaining the attribute check result for the trajectory segment. Here, the first trajectory segment is the one that precedes the current trajectory segment in time, and the second trajectory segment is the one that follows the current trajectory segment in time. For example, Figure 8 A schematic diagram of a first trajectory segment and a second trajectory segment provided in this application.

[0170] In this implementation, Figure 9 This is a flowchart illustrating a method for attribute checking of trajectory segments in unmatched precision road sections, as provided in this application. Figure 9 As shown, as one possible implementation, the method may include the following steps:

[0171] S301. The high-precision map processing system can first determine whether there exists a first trajectory segment and a second trajectory segment that are temporally continuous with the trajectory segment and have matching precision road segments. For example, the high-precision map processing system can determine whether there exists a first trajectory segment and a second trajectory segment that are temporally continuous with the trajectory segment by considering the acquisition time range of each trajectory segment.

[0172] In some embodiments, for the trajectory segment, if there is no first trajectory segment or no second trajectory segment, or if there is neither a first trajectory segment nor a second trajectory segment, the high-precision map processing system can execute step S302 to determine that the inspection result of the trajectory segment is that the attribute inspection fails.

[0173] S302. The result of the inspection of the trajectory segment is determined to be that the attribute check failed.

[0174] Because map data acquisition devices typically record the acquisition time accurately during map data collection, if no other trajectory segment is temporally adjacent to a given trajectory segment, it indicates that the segment may not belong to any road segment within the area. Therefore, by determining that the attribute check result for this trajectory segment is "failed," the high-precision map processing system improves the accuracy of attribute checks on trajectory segments, thereby enhancing the accuracy of the data processing results generated from the map data based on these attribute check results.

[0175] For the trajectory segment, if there is a first trajectory segment and a second trajectory segment, the high-precision map processing system may optionally execute step S303 to further check the attributes of the trajectory segment based on whether the matching precision road segments of the first trajectory segment and the second trajectory segment are consistent.

[0176] S303. Determine whether the standard road segments that match the first trajectory segment and the second trajectory segment are consistent.

[0177] Optionally, if a first trajectory segment and a second trajectory segment exist, and the matching precision road segment for the first trajectory segment and the second trajectory segment is the same, that is, the first trajectory segment and the second trajectory segment belong to the same road segment. The lack of a matching precision road segment for this trajectory segment may be due to a malfunction in the map data acquisition device during operation on that road segment, or a weak signal causing errors in the location information acquisition of that trajectory segment. Therefore, the high-precision map processing system can execute step S304.

[0178] S304. Merge the trajectory segment, the first trajectory segment, and the second trajectory segment, and perform an attribute check on the merged trajectory segment.

[0179] Optionally, the high-precision map processing system can perform attribute checks on the merged trajectory segment in the same way as described in the aforementioned embodiments, and will not be repeated here.

[0180] In this implementation, trajectory segments belonging to the same road segment, the first trajectory segment, and the second trajectory segment are merged to obtain a merged trajectory segment, which improves the accuracy of obtaining trajectory segments and the accuracy of data processing results for generating map data based on the attribute check results of trajectory segments.

[0181] If a first trajectory segment and a second trajectory segment exist, and the matching precision road segments of the first trajectory segment and the second trajectory segment are inconsistent, the high-precision map processing system may optionally further determine whether the length check of the first trajectory segment and the second trajectory segment has passed.

[0182] S305. Determine whether the length checks of the first and second trajectory segments are passed.

[0183] If there are discrepancies between the first trajectory segment and the second trajectory segment, the matching road segments in the high-precision map data are inconsistent, and the length checks of both the first and second trajectory segments pass, it indicates that the difference between the length of the first trajectory segment and the length of the road segment it matches in the high-precision map data is less than a preset difference threshold, and the difference between the length of the second trajectory segment and the length of the road segment it matches in the high-precision map data is also less than a preset difference threshold. In this implementation, the high-precision map processing system can execute step S306.

[0184] S306. Add the trajectory points in the trajectory segment to the first trajectory segment and the second trajectory segment respectively, and perform attribute checks on the added first trajectory segment and the second trajectory segment.

[0185] Optionally, the high-precision map processing system can, for example, add the trajectory points in the first trajectory segment one by one according to the order of the acquisition time interval between the endpoint trajectory point and the endpoint trajectory point of the first trajectory segment in ascending order, and add the trajectory points in the second trajectory segment one by one according to the order of the acquisition time interval between the endpoint trajectory point and the starting trajectory point of the second trajectory segment in ascending order. For example, Figure 8 As shown, the high-precision map processing system can add the trajectory points in this trajectory segment to the first trajectory segment and the second trajectory segment.

[0186] It should be understood that this application does not limit the number of trajectory points in the trajectory segment that the high-precision map processing system adds to the first and second trajectory segments. Optionally, taking the addition of trajectory points to the first trajectory segment as an example, the high-precision map processing system may, for example, perform an attribute check on the first trajectory segment after each trajectory point is added, during the process of adding trajectory points from the trajectory segment to the first trajectory segment one by one, until an added first trajectory segment with the longest length and satisfying the attribute check is obtained.

[0187] In this implementation, since the length checks of the first and second trajectory segments are performed within a certain error range—meaning the lengths of both segments can vary within a certain range while still meeting the length check requirements—adding trajectory points from the first and second segments reduces the number of trajectory points without matching precise road segments, thus improving the utilization rate of the map data acquisition device. Furthermore, by performing attribute checks on the added first and second trajectory segments, the length checks of these segments are ensured to still meet the requirements, improving the accuracy of trajectory segment determination.

[0188] If there is a first trajectory segment and a second trajectory segment, the matching precision road segments of the first trajectory segment and the second trajectory segment are inconsistent, or the length check of the first trajectory segment and / or the second trajectory segment fails, optionally, the high-precision map processing system can further execute step S307 to perform an attribute check on the trajectory segment based on whether the road segments matched by the first trajectory segment and the road segments matched by the second trajectory segment in the precision map data are connected in position.

[0189] S307. Determine whether the road segments matched by the first trajectory segment and the road segments matched by the second trajectory segment in the high-precision map data are connected in location.

[0190] Optionally, if there are inconsistencies between the first trajectory segment and the second trajectory segment, the matching road segments of the first trajectory segment and the second trajectory segment, the length check of the first trajectory segment and / or the second trajectory segment fails, and the road segments matched by the first trajectory segment and the second trajectory segment in the high-precision map data are not adjacent in position, it indicates that the road segment to which the trajectory segment belongs is not between the road segments to which the first trajectory segment belongs and the road segments to which the second trajectory segment belongs. In this case, the high-precision map processing system can execute step S308 to determine that the check result of the trajectory segment is that the attribute check fails.

[0191] If there are discrepancies between the first and second trajectory segments, the matching road segments of the first and second trajectory segments, or the length check of the first and second trajectory segments fails, and the road segments matched by the first and second trajectory segments in the high-precision map data are adjacent in position, it indicates that the trajectory segment corresponds to the connection point of the first and second trajectory segments. Therefore, the high-precision map processing system can execute step S308.

[0192] S309. Extend the first trajectory segment and the second trajectory segment to add trajectory points to the trajectory segment until the length check of the first trajectory segment and the second trajectory segment passes, and perform a continuity check on the added first trajectory segment and the second trajectory segment.

[0193] Optionally, the high-precision map processing system can extend the first trajectory segment and the second trajectory segment to add trajectory points to the trajectory segment until the length check of the first trajectory segment and the second trajectory segment passes. The specific implementation method can refer to the method described in the foregoing embodiments, and will not be repeated here.

[0194] In this implementation, the trajectory segment is used as the trajectory segment corresponding to the connection between the first trajectory segment and the second trajectory segment, and the length and continuity of the added first and second trajectory segments are checked to ensure the accuracy of the first and second trajectory segments.

[0195] In this embodiment, for cases where there are no matching precision road segments in a trajectory segment, the gaps in the trajectory segment are filled by using the first and second trajectory segments that are temporally continuous and have matching precision road segments. Furthermore, by performing attribute checks on the trajectory segment, the first trajectory segment, and the second trajectory segment, the accuracy and matching rate of the trajectory matching precision road network are improved.

[0196] In some embodiments, after storing the description information of the trajectory points and the corresponding trajectory segments, as well as the attribute check results of the trajectory segments, as the data processing results of the map data, the high-precision map processing system can also obtain the data corresponding to the target road segment from the data processing results of the map data based on the road segment identifier of the target road segment. As one possible implementation, the high-precision map processing system can first obtain the identifier of the target road segment.

[0197] For example, a high-precision map processing system can receive the identifier of a target road segment input by the user via an API or a GUI. Alternatively, the high-precision map processing system can also receive map data of a target area input by the user. This map data of the target area may include the identifiers of all road segments within that target area. The high-precision map processing system can then use all the identifiers of road segments within the target area included in the map data of that target area as the identifier of the target road segment. Alternatively, the high-precision map processing system can also receive the identifier of the target area input by the user, and then determine the identifier of the target road segment corresponding to that target area based on the identifier of the target area and the mapping relationship between area identifiers and road segment identifiers.

[0198] Then, the high-precision map processing system can obtain the data used to generate high-precision map data for the target road segment from the data processing results of the map data, based on the road segment identifier of the target road segment. The data processing results of this map data are obtained based on any of the aforementioned embodiments.

[0199] If the high-precision map processing system finds at least one first target trajectory segment (a trajectory segment with the identifier of the target road segment and whose attribute check result passes) from the data processing results of the aforementioned map data based on the road segment identifier of the target road segment, it indicates that the map data acquisition device has acquired map data for the target road segment. Then, the high-precision map processing system can obtain data on trajectory points within the acquisition time range corresponding to the at least one first target trajectory segment with non-repeating locations as the data for the target road segment.

[0200] Optionally, the high-precision map processing system can also store the data corresponding to the remaining trajectory segments as backup data for the target road segment. It should be understood that this application does not limit how the high-precision map processing system stores the backup data for the target road segment. For example, the high-precision map processing system can store the backup data for the target road segment in its database.

[0201] In this implementation, the high-precision map processing system can obtain the first target trajectory segment corresponding to the target road segment from the data processing results of the map data based on the target road segment's identifier. Because this first target trajectory segment has passed attribute checks, the completeness and accuracy of the first target trajectory segment obtained by the high-precision map processing system are ensured. By using the data of trajectory points within the collection time range corresponding to non-repeating trajectory segments as the target road segment's data, the amount of data for the target road segment is further reduced, thereby further improving the efficiency of the high-precision map processing system in processing the target road segment's data. By storing the data corresponding to the remaining trajectory segments as backup data for the target road segment, this backup data can be used for subsequent data processing, avoiding the need for the map data acquisition device to collect map data from the target road segment again, thus improving the efficiency of data acquisition and further improving the efficiency of data processing.

[0202] If the high-precision map processing system does not find the first target trajectory segment in the data processing results of the map data, it indicates that the map data acquisition device may not have collected map data for the target road segment.

[0203] In some embodiments, if the high-precision map processing system finds a second target trajectory segment (which is a trajectory segment with the aforementioned target road segment identifier, which fails the attribute check, and whose road segment matching confidence is greater than or equal to a preset confidence threshold) and a third target trajectory segment that is topologically continuous with the second target trajectory segment and has no matching high-precision road segment in the data processing results of the map data, it indicates that the map data acquisition device has not failed to collect map data of the target road segment, but rather that the attribute check result failed. In other words, the map data acquisition device may have partially collected map data of the target road segment.

[0204] Therefore, the high-precision map processing system can add the trajectory points within the collection time range corresponding to the third target trajectory segment to the second target trajectory segment one by one until the length of the second target trajectory segment passes the length check, and use the data of the trajectory points within the collection time range corresponding to the second target trajectory segment that has passed the length check as the data of the target road segment.

[0205] In this implementation, by adding the trajectory points of the third target trajectory segment to the second target trajectory segment one by one, the length of the second target trajectory segment is extended, so that the target road segment can correspond to more trajectory points, thereby reducing the probability of missing trajectory points of the target road segment and improving the accuracy of obtaining data on the target road segment.

[0206] In some embodiments, after acquiring data of a target road segment, the high-precision map processing system can use this data to generate high-precision map data. It should be understood that this application does not limit how the high-precision map processing system uses the data of the target road segment to generate high-precision map data. Optionally, the specific implementation method for generating high-precision map data using the data of the target road segment can refer to any existing implementation method, which will not be elaborated upon here.

[0207] In some embodiments, if the high-precision map processing system does not find the first target trajectory segment in the data processing results of the map data, finds a second target trajectory segment, and does not find a third target trajectory segment, optionally, the high-precision map processing system may output a prompt message indicating that the map data used to represent the target road segment was partially collected. If the high-precision map processing system does not find the first target trajectory segment in the data processing results of the map data, and does not find a second target trajectory segment, optionally, the high-precision map processing system may output a prompt message indicating that the map data used to represent the target road segment was not collected.

[0208] In this embodiment, the high-precision map processing system can obtain the corresponding trajectory segment of the target road segment based on its identifier, and obtain the target road segment's data based on the data of the trajectory points in the corresponding trajectory segment. Then, the high-precision map processing system can generate high-precision map data based on the target road segment's data. Compared to the prior art method of processing map data from all road segments in a region to obtain high-precision map data, this application reduces the amount of data required to generate high-precision map data, thus improving the efficiency of creating high-precision maps based on this map data.

[0209] Optionally, the high-precision map processing system can, for example, determine that the high-precision map data is missing when it fails to generate high-precision map data using data from the target road segment. Alternatively, the high-precision map processing system can also determine that the high-precision map data is missing in response to a user-triggered instruction indicating that the high-precision map data is missing.

[0210] If the high-precision map processing system determines that high-precision map data is missing, it may optionally output a data supplementation prompt. For example, the high-precision map processing system can output this prompt via a user terminal (e.g., a mobile phone, computer). Alternatively, in some embodiments, the high-precision map processing system can also output the data supplementation prompt to a map data acquisition device, so that the map data acquisition device responds to the prompt and performs data supplementation operations promptly. For example, the data supplementation prompt may include information such as the target road segment's identifier.

[0211] In this embodiment, when high-precision map data is missing, the high-precision map processing system can output a prompt message for data supplementation, enabling the map data acquisition device to promptly supplement map data for the target road segment, further improving the efficiency of acquiring high-precision map data.

[0212] Figure 10 A flowchart illustrating another data processing method provided in this application. Figure 10 As shown, the data processing method may include the following steps:

[0213] Step 1: The map data acquisition device binds the road segment identifier (also known as linkID) of the first trajectory point to multiple road segments (SD road network) in the high-precision map data, and determines the matching confidence.

[0214] In some embodiments, because the map data acquisition device can bind the road segment identifier of the first trajectory point in real time, the first trajectory point can also be referred to as a real-time trajectory point. Optionally, for real-time trajectory points not bound to a linkID, a null identifier can be added to the real-time trajectory point to indicate that the real-time trajectory point has no matching linkID. For example, the rules for the map data acquisition device to determine the matching confidence of the first trajectory point can be as follows:

[0215] If a link object in the SD road network can be matched (that is, a unique road segment identifier is matched), the matching confidence is 2; if multiple link objects in the SD road network can be matched (that is, multiple road segment identifiers are matched), the matching confidence is 1; if no link object in the SD road network can be matched, the matching confidence is 0.

[0216] Step 2: The high-precision map processing system determines the linkID and matching confidence of the trajectory points other than the first trajectory point (which can be called the second trajectory points).

[0217] Optionally, the high-precision map processing system can sort the first trajectory points by time and divide the trajectory into segments according to the linkID of each first trajectory point to obtain initial trajectory segments. Then, the high-precision map processing system can add second trajectory points to the initial trajectory segments according to the acquisition time range of the trajectory segments to obtain at least one trajectory segment.

[0218] Step 3: The high-precision map processing system re-binds the linkIDs of the trajectory points after position correction and re-binds the new results, and then re-divides the trajectory segments.

[0219] Optionally, the high-precision map processing system can rebind the SD road network linkIDs of trajectory points with matching confidence levels of 1 and 0 according to their geometric location information, and assign matching confidence levels to the trajectory points based on the number of bound linkIDs.

[0220] Step 4: The high-precision map processing system uses the high-precision map data to perform attribute checks on each trajectory segment and obtains the check results to determine whether the attribute checks of each trajectory segment have passed.

[0221] ① When the trajectory segment has a matching, precisely defined route segment:

[0222] I. Continuity Check of Trajectory Segments: For consecutive trajectory segments across two time periods, the high-precision map processing system checks whether the corresponding road segments are continuous in location on the high-precision map data. If continuous, the continuity check status is set to 1, indicating that the continuity check has passed. Otherwise, the continuity check status is set to 0, indicating that the continuity check has failed.

[0223] II. Trajectory Segment Length Check: The length of the trajectory segment is compared with the length of the road segment matched in the refined map data. If the length deviation is within 5%, the length check result is marked as 1, indicating that the length check has passed. Otherwise, the length check result is marked as 0, indicating that the length check has failed.

[0224] III. For trajectory segments that fail the continuity check or length check, the inspection result of the trajectory segment is determined based on the matching confidence of the trajectory segment (the matching confidence mentioned anywhere in this application refers to the road segment matching confidence). If the first result indicates that the continuity check of the trajectory segment fails, and the matching confidence of the trajectory segment is greater than or equal to a preset confidence threshold, it means that there are no low-confidence trajectory points in the trajectory segment, and the high-precision map processing system can determine that the inspection result of the trajectory segment is that the attribute check fails. If the first result indicates that the continuity check of the trajectory segment fails, and the matching confidence of the trajectory segment is less than a preset confidence threshold, the high-precision map processing system can re-segment the trajectory points according to the updated road segment identifiers of each trajectory point in the trajectory segment, and perform attribute checks on the new trajectory segments to obtain the inspection result of the trajectory segment.

[0225] ② The specific implementation method when there is no matching precise road segment for the trajectory segment can be as follows: Figure 9 The method and process shown will not be repeated here.

[0226] Step 5: The high-precision map processing system performs demand matching.

[0227] ① Regarding the identification of target road segments issued in response to requirements, if at least one first target trajectory segment is found in the data processing results of map data, it is marked as if the map data for that road segment has been collected. Optionally, the high-precision map processing system can also store the map data corresponding to the at least one first target trajectory segment as a field in a preset format, such as a JSON field (a storage field format in a programming language).

[0228] ② If map data for the target road segment is not collected: The high-precision map processing system can search for track segments that fail the length check or continuity check to see if there is a track segment with high matching confidence that matches the target road segment. If so, the target road segment is marked as partially collected.

[0229] ③ The high-precision map processing system did not find the first target trajectory segment in the data processing results of the map data, but found a second target trajectory segment and a third target trajectory segment. The second target trajectory segment is one that has the identifier of the aforementioned target road segment, fails the attribute check, and has a matching confidence level greater than or equal to a preset confidence threshold. The third target trajectory segment is a continuous trajectory segment with no matching high-precision road segment. The high-precision map processing system adds the trajectory points of the third target trajectory segment one by one to the aforementioned second target trajectory segment until the length check of the second target trajectory segment passes, and then uses the second target trajectory segment that passes the length check as the data for the target road segment.

[0230] Step 6: The high-precision map processing system obtains the data of the target road segment.

[0231] For the target road segments, filter and process the data:

[0232] ① If at least one first target trajectory segment is found in the data processing results of the map data, that is, the map data of the segment has been collected: the high-precision map processing system can use the data corresponding to the non-repeating trajectory segments in the at least one first target trajectory segment as the data of the target segment, and store the data corresponding to the remaining trajectory segments as backup map data of the target segment (when there is a problem with the data of the target segment, the high-precision map processing system can prioritize data retrieval from the backup map data).

[0233] ② For trajectory segments without matching road segment identifiers: The high-precision map processing system can mark these trajectory segments as unprocessed map data. When high-precision map data is missing, the high-precision map processing system can prioritize retrieving data from this unprocessed map data. If the high-precision map processing system cannot retrieve the missing data, it can optionally output a prompt message for data supplementation. Through the above method, the integrity of the road segments corresponding to trajectory segments without matching road segment identifiers is ensured.

[0234] In this embodiment, given the limited and costly map data acquisition devices, which necessitate acquiring as much data as possible in a single scheduling process, a scheduling scheme for target road segment data is achieved by filtering the target road segment data based on the target road segment identifier. This achieves redundancy filtering of the originally acquired map data, reducing the volume of target road segment data from the source and improving data processing efficiency. It also lowers the machine costs and manual processing costs of the high-precision map processing system. Furthermore, based on the temporal continuity of trajectory segments and the connectivity and length characteristics of road segments in the high-precision map data, the accuracy of matching trajectory segments with road segments is improved, thereby enhancing the accuracy of obtaining target road segment data based on the trajectory segments.

[0235] Figure 11 This is a schematic diagram of the structure of a data processing device 30 provided in this application. Figure 11 As shown, the data processing device 30 includes: an acquisition module 31 and a processing module 32. Wherein,

[0236] The acquisition module 31 is used to acquire map data. The map data includes: X trajectory points, and at least one precisely defined road segment matching each trajectory point.

[0237] Processing module 32 is configured to segment the X trajectory points according to the at least one trajectory point and the corresponding refined road segment, and the acquisition time of the X trajectory points, to obtain at least one trajectory segment; generate description information for the trajectory segment based on the acquisition time of the trajectory points included in the trajectory segment and the matched refined road segment; perform attribute checks on the trajectory segment using the refined road segment data corresponding to the matched refined road segment in the refined map data, obtain the attribute check results of the trajectory segment, and store the trajectory point, the description information of the trajectory segment corresponding to the trajectory point, and the attribute check results of the trajectory segment as the data processing results of the map data. The attribute checks include: topological continuity checks of the trajectory segment and length checks of the trajectory segment.

[0238] Optionally, the processing module 32 is specifically used to classify the trajectory points that match the same standard road segment and have consecutive collection times into the same trajectory segment based on the standard road segment matched by the trajectory points and the collection time of the X trajectory points.

[0239] Optionally, processing module 32 is specifically configured to, when the X trajectory points include trajectory points for which no precise road segment is matched, search for a target trajectory segment from the trajectory segments according to the acquisition time of the trajectory points for which no precise road segment is matched, and assign the trajectory points for which no precise road segment is matched to the found target trajectory segment as new trajectory segments. The acquisition time range of the trajectory points in the target trajectory segment covers the acquisition time of the trajectory points for which no precise road segment is matched.

[0240] Optionally, the processing module 32 is further configured to include, among the X trajectory points: when no trajectory point for the target trajectory segment is found, trajectory points from the new trajectory segment whose road segment matching confidence of the standard precision road segment is less than a preset confidence threshold; use the trajectory points less than the preset confidence threshold and the trajectory points for which no target trajectory segment is found as trajectory points to be corrected for position coordinate correction; perform road segment matching in the standard precision map data based on the corrected position coordinates of the trajectory points to be corrected to obtain the standard precision road segment matched by the trajectory points to be corrected; re-segment the trajectory points to be corrected that match the standard precision road segment, as well as the trajectory points contained in the new trajectory segment; and segment the trajectory points to be corrected that do not match the standard precision road segment according to the trajectory point acquisition time.

[0241] Optionally, the road segment matching confidence is obtained in advance based on the number of precise road segments matched by the trajectory point, and the road segment matching confidence of the trajectory point is negatively correlated with the number of road segments matched by the trajectory point.

[0242] Optionally, the processing module 32 is specifically used to perform attribute checks on the trajectory segment when the trajectory segment has a matching precision road segment, using the precision road segment data corresponding to the matching precision road segment in the precision map data, to obtain the attribute check result of the trajectory segment.

[0243] Optionally, the processing module 32 is specifically used to obtain a first result of whether the length check of the trajectory segment passes, based on whether the difference between the length of the trajectory segment and the length of the road segment matched by the trajectory segment in the refined map data is less than a preset difference threshold; to obtain a second result of whether the continuity check of the trajectory segment passes, based on whether the trajectory segment and the time-adjacent trajectory segment are continuous in position on the refined map data; and to obtain an attribute check result of the trajectory segment based on the first result and the second result of the trajectory segment.

[0244] Optionally, the processing module 32 is specifically configured to: determine that the trajectory segment's inspection result is attribute check failure when the first result indicates that the trajectory segment's length check fails; determine that the trajectory segment's inspection result is attribute check success when the first result indicates that the trajectory segment's length check passes and the second result indicates that the trajectory segment's continuity check passes; and determine that the trajectory segment's inspection result is attribute check success when the first result indicates that the trajectory segment's length check passes, the second result indicates that the trajectory segment's continuity check fails, and there are no trajectory points in the trajectory segment with a road segment matching confidence level less than or equal to the preset confidence threshold. If the inspection result of the trajectory segment is that the attribute check fails; if the first result indicates that the length check of the trajectory segment passes, the second result indicates that the continuity check of the trajectory segment fails, and there are trajectory points in the trajectory segment with a road segment matching confidence level less than or equal to the preset confidence threshold, the standard road segment matched by the trajectory point with a road segment matching confidence level less than or equal to the preset confidence threshold is replaced with other standard road segments matched by the trajectory point. Based on the standard road segments after the trajectory point replacement, the trajectory points are re-segmented, and the attribute check is performed on the new trajectory segments to obtain the attribute check result of the trajectory segment.

[0245] Optionally, the processing module 32 is further configured to, when the trajectory segment has no matching precision road segment, perform an attribute check on the trajectory segment based on whether there is a first trajectory segment and a second trajectory segment that are temporally continuous with the trajectory segment and have a matching precision road segment, to obtain the attribute check result of the trajectory segment. Wherein, the first trajectory segment is the trajectory segment that precedes the current trajectory segment in time, and the second trajectory segment is the trajectory segment that follows the current trajectory segment in time.

[0246] Optionally, the processing module 32 is specifically used to determine whether there are first trajectory segments and second trajectory segments that are temporally continuous with the trajectory segment and have matching precision road segments; when there are no first trajectory segments and / or second trajectory segments, determine that the check result of the trajectory segment is that the attribute check fails; when there are first trajectory segments and second trajectory segments, and the precision road segments matching the first trajectory segment and the second trajectory segment are consistent, merge the trajectory segment, the first trajectory segment, and the second trajectory segment, and perform attribute checks on the merged trajectory segment; when there are first trajectory segments and second trajectory segments, the precision road segments matching the first trajectory segment and the second trajectory segment are inconsistent, and the length checks of the first trajectory segment and the second trajectory segment both pass, add the trajectory points in the trajectory segment to the first trajectory segment and the second trajectory segment respectively, and perform attribute checks on the added first trajectory segment and the second trajectory segment; If the first trajectory segment and the second trajectory segment, the matching precision road segments of the first trajectory segment and the second trajectory segment are inconsistent, the length check of the first trajectory segment and / or the second trajectory segment fails, and the road segments matched by the first trajectory segment and the second trajectory segment in the precision map data are not connected in position, the check result of the trajectory segment is determined to be an attribute check failure. If the first trajectory segment and the second trajectory segment, the matching precision road segments of the first trajectory segment and the second trajectory segment are inconsistent, the length check of the first trajectory segment and the second trajectory segment fails, and the road segments matched by the first trajectory segment and the second trajectory segment in the precision map data are connected in position, the first trajectory segment and the second trajectory segment are extended to add trajectory points to the trajectory segment until the length check passes, and the continuity check is performed on the added first trajectory segment and second trajectory segment.

[0247] The data processing device 30 provided in this application is used to execute the data processing method embodiment executed by the aforementioned high-precision map processing system. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0248] Figure 12 This is a schematic diagram of the structure of a data acquisition device 40 provided in this application. Figure 12 As shown, the data acquisition device 40 includes: a first acquisition module 41 and a second acquisition module 42. Wherein,

[0249] The first acquisition module 41 is used to acquire the road segment identifier of the target road segment.

[0250] The second acquisition module 42 is used to acquire data for generating high-precision map data of the target road segment from the data processing results of the map data based on the road segment identifier of the target road segment.

[0251] The second acquisition module 42 is specifically used to: when searching for a first target trajectory segment from the data processing results of the map data based on the road segment identifier of the target road segment, acquire data of trajectory points within the collection time range corresponding to the trajectory segments with non-repeating locations from the first target trajectory segment as the data of the target road segment; when searching for a second target trajectory segment and a third target trajectory segment that is topologically continuous with the second target trajectory segment and has no matching precision road segments from the data processing results of the map data based on the road segment identifier of the target road segment, add the trajectory points within the collection time range corresponding to the third target trajectory segment one by one to the second target trajectory segment until the length check of the second target trajectory segment passes, and use the data of trajectory points within the collection time range corresponding to the second target trajectory segment that has passed the length check as the data of the target road segment. The first target trajectory segment contains the road segment identifier of the target road segment and the attribute check result is passed; the second target trajectory segment is a trajectory segment that has the identifier of the target road segment, the attribute check result is not passed, and the road segment matching confidence is greater than or equal to a preset confidence threshold.

[0252] The data acquisition device 40 provided in this application is used to execute the data acquisition method embodiment executed by the aforementioned high-precision map processing system. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0253] This application also provides a method such as Figure 4 The electronic device 10 shown has a processor 12 that reads a set of computer instructions stored in the memory 11 to execute the aforementioned data processing method and data acquisition method.

[0254] This application also provides a computer-readable storage medium, which may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. Specifically, the computer-readable storage medium stores program instructions, which are used in the methods described in the above embodiments.

[0255] This application also provides a program product including executable instructions stored in a readable storage medium. At least one processor of an electronic device can read the executable instructions from the readable storage medium, and the at least one processor executes the executable instructions to cause the electronic device to implement the data processing method and data acquisition method provided in the various embodiments described above.

[0256] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A data processing method, characterized in that, The method includes: Acquire map data, which includes: X trajectory points, and at least one precise road segment matched by the trajectory points; Based on the precise road segment matched by the at least one trajectory point and the acquisition time of the X trajectory points, the X trajectory points are segmented to obtain at least one trajectory segment; Based on the acquisition time of the trajectory points included in the trajectory segment and the matched precision road segment, a description of the trajectory segment is generated; In response to the trajectory segment having a matching precision road segment, based on the length of the trajectory segment and whether the difference between the length of the trajectory segment and the length of the matching road segment in the precision map data is less than a preset difference threshold, a first result is obtained as to whether the length check of the trajectory segment passes. Based on whether the trajectory segment is continuous with the time-adjacent trajectory segment in the position on the refined map data, a second result is obtained to determine whether the continuity check of the trajectory segment has passed. Based on the first result and the second result of the trajectory segment, the attribute check result of the trajectory segment is obtained; The description information of the trajectory point, the trajectory segment corresponding to the trajectory point, and the attribute check result of the trajectory segment are stored as the data processing result of the map data.

2. The method according to claim 1, characterized in that, The step of segmenting the X trajectory points based on the precise road segment matched by the at least one trajectory point, and the acquisition time of the X trajectory points, to obtain at least one trajectory segment, includes: Based on the standard road segment matched by the trajectory points and the acquisition time of the X trajectory points, the trajectory points that match the same standard road segment and have consecutive acquisition times are grouped into the same trajectory segment.

3. The method according to claim 2, characterized in that, If the X trajectory points include trajectory points that do not match a precise road segment, then for the trajectory points that do not match a precise road segment, the method further includes: Based on the collection time of the trajectory points of the road segments that were not matched with the standard precision road segment, a target trajectory segment is searched from the trajectory segments, and the collection time range of the trajectory points of the target trajectory segment covers the collection time of the trajectory points of the road segments that were not matched with the standard precision road segment. The trajectory points that did not match the target road segment are assigned to the found target trajectory segment as new trajectory segments.

4. The method according to claim 3, characterized in that, If the X trajectory points include trajectory points for which no target trajectory segment was found, then the method further includes: From the new trajectory segment, obtain trajectory points whose segment matching confidence of the standard precision segment is less than the preset confidence threshold; The trajectory points with a confidence threshold lower than the preset threshold and the trajectory points for which no target trajectory segment was found are used as trajectory points to be corrected for position coordinate correction. Based on the corrected position coordinates of the trajectory point to be corrected, road segment matching is performed in the refined map data to obtain the refined road segment matched by the trajectory point to be corrected. For the trajectory points to be corrected that match the standard road segment, and for the trajectory points contained in the new trajectory segment, the trajectory is re-segmented; For trajectory points that do not match a precise road segment, the trajectory is segmented according to the time of trajectory point acquisition.

5. The method according to any one of claims 1-4, characterized in that, The step of obtaining the attribute check result of the trajectory segment based on the first result and the second result of the trajectory segment includes: If the first result indicates that the length check of the trajectory segment fails, then the check result of the trajectory segment is determined to be that the attribute check fails. If the first result indicates that the length check of the trajectory segment has passed, and the second result indicates that the continuity check of the trajectory segment has passed, then the check result of the trajectory segment is determined to be that the attribute check has passed; If the first result indicates that the length check of the trajectory segment passes, the second result indicates that the continuity check of the trajectory segment fails, and there are no trajectory points in the trajectory segment with a road segment matching confidence level less than or equal to a preset confidence threshold, then the check result of the trajectory segment is determined to be an attribute check failure. If the first result indicates that the length check of the trajectory segment passes, the second result indicates that the continuity check of the trajectory segment fails, and there are trajectory points in the trajectory segment with a segment matching confidence level less than or equal to the preset confidence threshold, then the standard road segment matched by the trajectory point with a segment matching confidence level less than or equal to the preset confidence threshold is replaced with another standard road segment matched by the trajectory point. Based on the standard road segments after the trajectory point replacement, the trajectory points are re-segmented, and the attributes of the new trajectory segments are checked to obtain the attribute check results of the trajectory segments.

6. The method according to claim 5, characterized in that, The road segment matching confidence is obtained in advance based on the number of precise road segments matched by the trajectory point, and the road segment matching confidence of the trajectory point is negatively correlated with the number of road segments matched by the trajectory point.

7. The method according to any one of claims 1-4, characterized in that, The method further includes: If the trajectory segment has no matching standard road segment, then based on whether there is a first trajectory segment and a second trajectory segment that are temporally continuous with the trajectory segment and have a matching standard road segment, the attribute check of the trajectory segment is performed to obtain the attribute check result of the trajectory segment; the first trajectory segment is the trajectory segment that is temporally located before the trajectory segment, and the second trajectory segment is the trajectory segment that is temporally located after the trajectory segment.

8. The method according to claim 7, characterized in that, The step of performing attribute checks on the trajectory segment based on whether there exists a first trajectory segment and a second trajectory segment that are temporally continuous and have matching precision road segments, and obtaining the attribute check result of the trajectory segment, includes: Determine whether there exist a first trajectory segment and a second trajectory segment that are temporally continuous with the trajectory segment and have matching precision road segments; If the first trajectory segment and / or the second trajectory segment do not exist, the check result of the trajectory segment is determined to be attribute check failure; If the first trajectory segment and the second trajectory segment exist, and the standard route segments that match the first trajectory segment and the second trajectory segment are the same, then the trajectory segment, the first trajectory segment and the second trajectory segment are merged, and the attribute of the merged trajectory segment is checked. If there are inconsistencies in the standard road segments that match the first trajectory segment and the second trajectory segment, and the length checks of the first trajectory segment and the second trajectory segment both pass, then the trajectory points in the trajectory segment are added to the first trajectory segment and the second trajectory segment respectively, and the attributes of the added first trajectory segment and the second trajectory segment are checked. If the first trajectory segment and the second trajectory segment, the first trajectory segment and the second trajectory segment match different precision road segments, the length check of the first trajectory segment and / or the second trajectory segment fails, and the road segments matched by the first trajectory segment and the second trajectory segment are not connected in position in the precision map data, then the check result of the trajectory segment is determined to be attribute check failure. If the first trajectory segment and the second trajectory segment, the matching precision road segments of the first trajectory segment and the second trajectory segment are inconsistent, the length check of the first trajectory segment and the second trajectory segment fails, and the road segments matched by the first trajectory segment and the second trajectory segment are connected in position in the precision map data, then the first trajectory segment and the second trajectory segment are extended to add trajectory points to the trajectory segment until the length check passes, and the continuity check is performed on the added first trajectory segment and second trajectory segment.

9. A method for acquiring data, characterized in that, The method includes: Obtain the road segment identifier for the target road segment; Based on the road segment identifier of the target road segment, data for generating high-precision map data of the target road segment is obtained from the data processing results of the map data. If a first target trajectory segment is found in the data processing results of the map data based on the road segment identifier of the target road segment, then the data of trajectory points within the collection time range corresponding to the trajectory segment with non-repeating locations are obtained from the first target trajectory segment as the data of the target road segment. The first target trajectory segment contains the road segment identifier of the target road segment and the attribute check result is passed. If, based on the segment identifier of the target road segment, a second target trajectory segment is found from the data processing results of the map data, and a third target trajectory segment is found that is topologically continuous with the second target trajectory segment and has no matching precision road segment, then the trajectory points within the collection time range corresponding to the third target trajectory segment are added to the second target trajectory segment one by one until the length check of the second target trajectory segment passes, and the data of the trajectory points within the collection time range corresponding to the second target trajectory segment that has passed the length check is used as the data of the target road segment; wherein, the second target trajectory segment is a trajectory segment that has the identifier of the target road segment, fails the attribute check, and has a road segment matching confidence greater than or equal to a preset confidence threshold.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 9.

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