Map production data quality inspection method and device, electronic equipment and medium

Abstract

The invention provides a map production data quality inspection method and device, electronic equipment, a computer readable storage medium and a computer program product, and relates to the field of computers, in particular to the technical field of high-precision maps and data processing. According to the implementation scheme, map data to be subjected to quality inspection of a target area are acquired; adding corresponding attribute information to the map data with the quality problem in the map data to be subjected to quality inspection, wherein the attribute information is used for representing a traffic scene corresponding to the map data with the quality problem; and performing quality inspection on the map data to be subjected to quality inspection based on the attribute information.

Description

Technical Field

[0001] The present disclosure relates to the field of computers, in particular to the fields of high-precision maps and data processing technology, and specifically to a map production data quality inspection method, device, electronic device, computer-readable storage medium and computer program product. Background Art

[0002] With the development of science and technology, high-precision maps have been widely used. In the production process of high-precision maps, there are often many cases of missing data and maps. This may be due to missing data in the original data collection, or it may be due to abnormalities in the data processing and transmission process. In order to ensure the accuracy of high-precision map data, it is necessary to conduct quality inspection on the high-precision map data.

[0003] The methods described in this section are not necessarily methods that have been previously conceived or employed. Unless otherwise indicated, it should not be assumed that any method described in this section is considered to be prior art simply because it is included in this section. Similarly, unless otherwise indicated, the issues mentioned in this section should not be considered to have been recognized in any prior art. Summary of the invention

[0004] The present disclosure provides a map production data quality inspection method, device, electronic device, computer-readable storage medium and computer program product.

[0005] According to one aspect of the present disclosure, a method for quality inspection of map production data is provided, comprising: acquiring map data to be inspected in a target area; adding corresponding attribute information to map data determined to have quality problems in the map data to be inspected, wherein the attribute information is used to represent a traffic scene corresponding to the map data having quality problems; and performing quality inspection on the map data to be inspected based on the attribute information.

[0006] According to another aspect of the present disclosure, a map production data quality inspection device is provided, comprising: an acquisition unit, configured to acquire map data to be inspected in a target area; a marking unit, configured to add corresponding attribute information to map data determined to have quality problems in the map data to be inspected, wherein the attribute information is used to represent a traffic scene corresponding to the map data having quality problems; and a quality inspection unit, configured to perform quality inspection on the map data to be inspected based on the attribute information.

[0007] According to another aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method described in the present disclosure.

[0008] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided. The computer instructions are used to cause a computer to execute the method described in the present disclosure.

[0009] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, which implements the method described in the present disclosure when executed by a processor.

[0010] According to one or more embodiments of the present disclosure, corresponding attribute information is added to the map data to be inspected that is determined to have quality problems, so as to provide reference to quality inspectors, thereby helping to quickly inspect and locate problems, thereby improving quality inspection efficiency.

[0011] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings exemplarily illustrate the embodiments and constitute a part of the specification, and together with the text description of the specification, are used to explain the exemplary implementation of the embodiments. The embodiments shown are for illustrative purposes only and do not limit the scope of the claims. In all drawings, the same reference numerals refer to similar but not necessarily identical elements.

[0013] Figure 1 A schematic diagram showing an exemplary system in which the various methods described herein may be implemented according to an embodiment of the present disclosure;

[0014] Figure 2 A flowchart of a map production data quality inspection method according to an embodiment of the present disclosure is shown;

[0015] Figure 3 A structural block diagram of a map production data quality inspection device according to an embodiment of the present disclosure is shown; and

[0016] Figure 4 A structural block diagram of an exemplary electronic device that can be used to implement the embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0017] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0018] In the present disclosure, unless otherwise specified, the use of the terms "first", "second", etc. to describe various elements is not intended to limit the positional relationship, timing relationship, or importance relationship of these elements, and such terms are only used to distinguish one element from another element. In some examples, the first element and the second element may refer to the same instance of the element, and in some cases, based on the description of the context, they may also refer to different instances.

[0019] The terms used in the description of various examples in this disclosure are only for the purpose of describing specific examples and are not intended to be limiting. Unless the context clearly indicates otherwise, if the number of elements is not specifically limited, the element can be one or more. In addition, the term "and / or" used in this disclosure covers any one of the listed items and all possible combinations.

[0020] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0021] Figure 1 FIG. 1 is a schematic diagram of an exemplary system 100 in which various methods and apparatuses described herein may be implemented according to an embodiment of the present disclosure. Figure 1 , the system 100 includes one or more client devices 101, 102, 103, 104, 105, and 106, a server 120, and one or more communication networks 110 coupling the one or more client devices to the server 120. The client devices 101, 102, 103, 104, 105, and 106 may be configured to execute one or more applications.

[0022] In an embodiment of the present disclosure, the server 120 may run one or more services or software applications that enable the method of map production data quality inspection to be performed.

[0023] In some embodiments, server 120 may also provide other services or software applications, which may include non-virtualized environments and virtualized environments. In some embodiments, these services may be provided as web-based services or cloud services, such as provided to users of client devices 101, 102, 103, 104, 105, and / or 106 under a software as a service (SaaS) model.

[0024] exist Figure 1In the configuration shown, the server 120 may include one or more components that implement the functions performed by the server 120. These components may include software components, hardware components, or a combination thereof that can be executed by one or more processors. Users operating client devices 101, 102, 103, 104, 105, and / or 106 may in turn utilize one or more client applications to interact with the server 120 to utilize the services provided by these components. It should be understood that a variety of different system configurations are possible, which may differ from the system 100. Therefore, Figure 1 is one example of a system for implementing the various methods described herein and is not intended to be limiting.

[0025] The user may use client devices 101, 102, 103, 104, 105 and / or 106 to input attribute information to be added, etc. The client device may provide an interface that enables the user of the client device to interact with the client device. The client device may also output information to the user via the interface. Figure 1 Only six client devices are depicted, but one skilled in the art will appreciate that the present disclosure may support any number of client devices.

[0026] Client devices 101, 102, 103, 104, 105 and / or 106 may include various types of computer devices, such as portable handheld devices, general-purpose computers (such as personal computers and laptop computers), workstation computers, wearable devices, smart screen devices, self-service terminal devices, service robots, game systems, thin clients, various messaging devices, sensors or other sensing devices, etc. These computer devices may run various types and versions of software applications and operating systems, such as MICROSOFT Windows, APPLE iOS, UNIX-like operating systems, Linux or Linux-like operating systems (such as GOOGLE Chrome OS); or include various mobile operating systems, such as MICROSOFT Windows Mobile OS, iOS, Windows Phone, Android. Portable handheld devices may include cellular phones, smart phones, tablet computers, personal digital assistants (PDAs), etc. Wearable devices may include head-mounted displays (such as smart glasses) and other devices. Game systems may include various handheld game devices, Internet-enabled game devices, etc. Client devices are capable of executing various different applications, such as various Internet-related applications, communication applications (such as email applications), short message service (SMS) applications, and may use various communication protocols.

[0027] The network 110 may be any type of network known to those skilled in the art that may support data communications using any of a variety of available protocols, including but not limited to TCP / IP, SNA, IPX, etc. By way of example only, the one or more networks 110 may be a local area network (LAN), an Ethernet-based network, a token ring, a wide area network (WAN), the Internet, a virtual network, a virtual private network (VPN), an intranet, an extranet, a blockchain network, a public switched telephone network (PSTN), an infrared network, a wireless network (e.g., Bluetooth, WIFI), and / or any combination of these and / or other networks.

[0028] Server 120 may include one or more general purpose computers, dedicated server computers (e.g., PC (personal computer) servers, UNIX servers, mid-range servers), blade servers, mainframe computers, server clusters, or any other suitable arrangement and / or combination. Server 120 may include one or more virtual machines running virtual operating systems, or other computing architectures involving virtualization (e.g., one or more flexible pools of logical storage devices that may be virtualized to maintain a server's virtual storage device). In various embodiments, server 120 may run one or more services or software applications that provide the functionality described below.

[0029] The computing units in the server 120 may run one or more operating systems including any of the above operating systems and any commercially available server operating systems. The server 120 may also run any of a variety of additional server applications and / or middle-tier applications, including HTTP servers, FTP servers, CGI servers, JAVA servers, database servers, etc.

[0030] In some implementations, server 120 may include one or more applications to analyze and consolidate data feeds and / or event updates received from users of client devices 101, 102, 103, 104, 105, and 106. Server 120 may also include one or more applications to display data feeds and / or real-time events via one or more display devices of client devices 101, 102, 103, 104, 105, and 106.

[0031] In some embodiments, the server 120 may be a server of a distributed system, or a server combined with a blockchain. The server 120 may also be a cloud server, or an intelligent cloud computing server or intelligent cloud host with artificial intelligence technology. A cloud server is a host product in a cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and virtual private servers (VPS) services.

[0032] The system 100 may also include one or more databases 130. In some embodiments, these databases may be used to store data and other information. For example, one or more of the databases 130 may be used to store information such as map production data. The databases 130 may reside in various locations. For example, the database used by the server 120 may be local to the server 120, or may be remote from the server 120 and may communicate with the server 120 via a network-based or dedicated connection. The databases 130 may be of different types. In some embodiments, the database used by the server 120 may be, for example, a relational database. One or more of these databases may store, update, and retrieve data to and from the database in response to commands.

[0033] In some embodiments, one or more of the databases 130 may also be used by applications to store application data. The databases used by the applications may be different types of databases, such as a key-value store, an object store, or a conventional store backed by a file system.

[0034] Figure 1 The system 100 may be configured and operated in various ways to enable the application of various methods and apparatuses described in the present disclosure.

[0035] In the production process of high-precision maps, there are often many cases of missing data and drawings. This may be due to missing data in the original data collection, or it may be due to abnormalities in the data processing and transmission process. The data processing program will automatically add and delete various types of data and track points, such as deleting duplicate tracks or splitting different tracks by batches. This automatic processing operation is not transparent in traditional data processing, and only the results of program processing can be seen during manual quality inspection. When encountering problems such as missing maps due to deletion errors, you can only contact R&D personnel to manually trace the problem and confirm whether it is an abnormal deletion. This method is not only time-consuming, but also cumbersome.

[0036] Therefore, according to an embodiment of the present disclosure, a method for quality inspection of map production data is provided. Figure 2 A flowchart of a map production data quality inspection method according to an embodiment of the present disclosure is shown. Figure 2 As shown, method 200 includes: acquiring map data to be inspected in a target area (step 210); adding corresponding attribute information to the map data determined to have quality problems in the map data to be inspected, wherein the attribute information is used to represent the traffic scene corresponding to the map data with quality problems (step 220); and performing quality inspection on the map data to be inspected based on the attribute information (step 230).

[0037] High-precision map production data quality inspection is a crucial part of the high-precision map production process, which ensures the accuracy, completeness and reliability of map data. In the continuous automatic circulation and processing of map data, there may be problems with the original data or occasional accuracy problems caused by the program. In addition, any operation involving program deletion of track points may result in the loss of tracks and data.

[0038] According to the embodiments of the present disclosure, corresponding attribute information is added to the map data to be inspected that is determined to have quality problems, so as to provide reference to quality inspectors, thereby helping to quickly inspect and locate problems, thereby improving quality inspection efficiency.

[0039] According to some embodiments, the map data to be inspected includes a plurality of image data of the target area and a plurality of track data collected by vehicles passing through the target area, wherein each of the plurality of track data includes a plurality of track points collected during the driving process of the corresponding vehicle. Adding corresponding attribute information to the map data with quality problems determined in the map data to be inspected includes: adding a first attribute to the identified track points with quality problems in the plurality of track data, wherein the first attribute identifies the first scene information corresponding to the track points with quality problems; and adding a second attribute to the image data with quality problems included in the plurality of image data, wherein the second attribute identifies the second scene information corresponding to the image data with quality problems. Performing quality inspection on the map data to be inspected based on the attribute information includes: performing quality inspection on the map data to be inspected based on the first attribute and the second attribute.

[0040] In the present disclosure, the trajectory data is collected during the driving process of the vehicle, wherein a plurality of trajectory data may be derived from a plurality of vehicles, and the plurality of trajectory data may be collected during multiple driving processes of the vehicle.

[0041] In the present disclosure, the map data with quality problems includes map data that has been determined to have quality problems and map data that may have quality problems.

[0042] In the present disclosure, the multiple image data of the target area may include any type of image data used for map production, including but not limited to pictures, point cloud images, satellite images, etc.

[0043] In some examples, map collection vehicles are often equipped with a variety of high-precision sensors and devices to ensure that high-quality image data can be obtained. For example, high-resolution cameras are used to capture detailed images of the road and the environment on both sides of it. These cameras may have multiple lenses to capture images from different angles and fields of view; laser radar (LiDAR) emits lasers and receives reflected light signals to measure the distance and shape of the vehicle's surroundings, thereby generating high-precision three-dimensional point cloud data. These data, combined with image data, can provide richer geographic information.

[0044] According to some embodiments, the first attribute includes at least one of the following items: a reversing scene, and a repeated collection scene. The reversing scene indicates that the corresponding track point is a track point collected in a reversing scene; the repeated collection scene indicates that the corresponding track point is a repeated track point obtained by repeatedly collecting the same lane.

[0045] In the map production process, stitching the top view is a key step, which involves merging image data from multiple perspectives or regions into a coherent panoramic view. For example, after using drones, satellites, ground cameras or vehicle-mounted cameras to collect image data of the target area, the collected images are pre-processed by denoising, correcting distortion, adjusting colors, etc., and image fusion or stitching technology is used to obtain a stitched top view of the target area.

[0046] In some examples, due to actual scene limitations or other human factors, the vehicle may be reversed during the collection process, resulting in abnormal top view effects. Usually at the end of a small road, there are multiple vehicle tracks and the track points are relatively disordered. This problem can be solved by deleting the reversing track points and only using normal collection tracks to process the data. According to the timestamp of the collected data, the tracks with later times will be deleted first. By adding the first attribute information related to the reversing scene to the corresponding track points for marking, it can be provided to subsequent quality inspectors as a reference to help achieve rapid quality inspection and improve quality inspection efficiency.

[0047] In some examples, in order to ensure that multi-lane road data can be accurately produced, there are rigid requirements for the number of times the collection vehicle collects on multiple lanes and the lanes covered by the track. In the standard three-lane scenario, the collection vehicle is required to collect at least one trip in the middle lane, that is, the splicing of the top view can ensure the data accuracy of the lane covered by the collection track and the left and right lanes, a total of three lanes. Beyond the three-lane range, it cannot be guaranteed. In the standard three-lane scenario, if the collection vehicle has gone two or more times, the collection track will participate in the data processing. Once there is an accuracy deviation in the two tracks, it will cause great interference to the final result data. The track accuracy is affected by many factors. The track of the same location collected by the same vehicle for multiple times may have unavoidable accuracy deviations. Therefore, such problems can be solved by deleting one of the tracks that has a large deviation from the actual one. In the above embodiment, the first attribute information related to the repeated collection scene is added to the corresponding track point to achieve marking, so as to provide it to subsequent quality inspectors as a reference, help to achieve rapid quality inspection, and improve quality inspection efficiency.

[0048] According to some embodiments, the trajectory point includes position information of the corresponding vehicle at the trajectory point, wherein the first attribute includes an elevated scene, and the elevated scene indicates that the corresponding trajectory point is a trajectory point within a preset horizontal range and has a height difference.

[0049] In the present disclosure, an elevated scene in a three-dimensional map or geographic information system generally refers to a special terrain or road structure, which is characterized by the fact that the trajectory points are not only within a preset horizontal range, but also have significant height differences. In some examples, the trajectory data can be collected through satellite positioning systems such as GPS and Beidou, or can be obtained through built-in positioning modules such as mobile phones and vehicle-mounted equipment. The elevation data of the surface is obtained through remote sensing technology (such as satellite remote sensing, drone mapping, etc.), and the height difference between different locations is calculated. In a three-dimensional map, the height difference information is used to construct a three-dimensional model of the terrain, making the map more realistic and three-dimensional.

[0050] The trajectory points in the elevated scene are usually within a preset horizontal range, but there is a height difference. In some examples, such data will be split according to the height difference, and the upper and lower layers will be split into different batches for processing. The production of map data in such scenarios is strongly dependent on trajectory accuracy and height difference information, and problems occur frequently. Therefore, it can be marked for subsequent quality inspection and verification. In the above embodiment, marking is achieved by adding the first attribute information related to the repeated acquisition scene to the corresponding trajectory point, which can be provided to subsequent quality inspectors as a reference to help achieve rapid quality inspection and improve quality inspection efficiency.

[0051] It is understandable that in addition to the above scenarios, the trajectory can be deleted and the corresponding first attribute information can be marked according to the scenario and given conditions to achieve the purpose of eliminating abnormal data from participating in production. In actual scenarios, especially complex collection scenarios such as viaducts and tunnels, the program cannot guarantee 100% accuracy of deletion due to the limitations of the scenario and signal. Therefore, for example, in the manual quality inspection link, the operator will review the top view drawing effect. When there are abnormalities caused by the above scenarios, the attribute information corresponding to the corresponding trajectory point will be marked for review.

[0052] According to some embodiments, the second attribute includes at least one of the following items: a lane line scene, and an intersection scene. The lane line scene represents a lane line portion with quality problems in the target area formed by splicing the multiple image data; the intersection scene represents an intersection portion in the target area formed by splicing the multiple image data.

[0053] In map production or intelligent transportation systems, the accuracy of lane lines and intersections is crucial. The lane line scene refers to the scene in which the lane line part of the image is specifically analyzed and represented after multiple image data (which may come from different times, angles or shooting devices) are stitched together into a complete map or target area image. In this process, the system will identify the location, direction, type (such as solid line, dashed line, double yellow line, etc.) of the lane line and whether there are quality problems (such as wear, blur, missing, wrong marking, etc.). The intersection scene refers to the scene in which the intersection part is specifically analyzed and represented in the stitched image. The intersection is a key point where traffic flows meet, and its accurate representation is crucial for navigation, traffic monitoring and planning. In the intersection scene, the system will identify the geometry of the intersection (such as crossroads, T-junction, Y-junction, etc.), the location and status of traffic lights, lane allocation (such as left turn lane, through lane, right turn lane, etc.) and pedestrian crossing facilities (such as zebra crossings, crosswalk lights, etc.). Since abnormal problems are most likely to occur at intersections, in order to prevent the program from missing any processing, all intersection points will be marked as features for manual review.

[0054] By marking the image data in lane line scenes and intersection scenes, it can serve as a reminder for subsequent quality inspectors to use as a reference, helping to achieve rapid quality inspection and improve quality inspection efficiency.

[0055] According to some embodiments, the lane line scenario includes at least one of the following items: a lane line continuous occlusion scenario, a lateral error scenario, and a longitudinal error scenario. The lane line continuous occlusion scenario indicates that the lane line portion with quality problems is an occluded lane line portion; the lateral error scenario indicates that the corresponding lane line is staggered left and right in the direction extending along the corresponding trajectory; and the longitudinal error scenario indicates that the corresponding lane line is a zebra crossing and the zebra crossing is staggered.

[0056] In some examples, it is difficult to avoid the presence of other vehicles around, hard barriers in the road, etc. during the scene collection process, resulting in long-distance lane line occlusion in the collected data, affecting data usage. The second attribute information is marked based on the range of lane line occlusion identified near the vehicle trajectory, that is, the continuous lane line occlusion scene is identified to remind subsequent quality inspection personnel to determine whether the quality standard is met based on the occlusion situation.

[0057] In some examples, the lane lines in the stitched top view should theoretically be consistent with the displayed world, but due to factors such as the trajectory accuracy of the acquisition process and the acquisition equipment, there may be deviations in the lane line stitching. When the lane lines appear jagged and staggered left and right, it is defined as a lateral error. In some examples, when the zebra crossing appears staggered up and down, it is defined as a longitudinal error. There are many reasons for lateral deviations and longitudinal errors. By marking the corresponding second attribute information to identify lateral error scenarios and longitudinal error scenarios, subsequent quality inspectors can be reminded as a reference to help achieve rapid quality inspection and improve quality inspection efficiency.

[0058] It is understandable that in addition to the above scenarios, the corresponding second attribute information can also be marked according to the scenario and given conditions to achieve the purpose of reminder. For example, in actual scenarios, there are small roads without zebra crossings, single-track roads with less than three lanes, no obvious identification features, data production is strongly dependent on track accuracy, and the frequency of problems is high, so such scenes can be marked for manual inspection.

[0059] According to some embodiments, the attribute information is displayed according to corresponding visual attributes, wherein the visual attributes are determined based on the traffic scene.

[0060] In some examples, identify whether the data has accuracy problems that do not meet the requirements, and there may be nodes where data is invalidated or tracks are deleted. For example, the deleted and invalidated data is labeled differently according to the reasons and links for deletion, and finally displayed in different interactive colors on the top view quality inspection client for reference by quality inspectors. In this way, quality inspectors can intuitively view the status of all track points, such as whether they have been deleted, at which link they were deleted, and why they were deleted. In this way, quality inspectors can directly judge whether this deletion is normal based on standards and scenarios, quickly locate problems, reduce troubleshooting time, and improve quality inspection efficiency.

[0061] According to the embodiments of the present disclosure, Figure 3 As shown, a map production data quality inspection device 300 is also provided, including: an acquisition unit 310, configured to acquire map data to be inspected in a target area; a marking unit 320, configured to add corresponding attribute information to the map data with quality problems determined in the map data to be inspected, wherein the attribute information is used to represent the traffic scene corresponding to the map data with quality problems; and a quality inspection unit 330, configured to perform quality inspection on the map data to be inspected based on the attribute information.

[0062] According to some embodiments, the map data to be inspected includes multiple picture data of the target area taken and multiple trajectory data collected by vehicles passing through the target area, wherein each of the multiple trajectory data includes multiple trajectory points collected during the driving process of the corresponding vehicle.

[0063] The marking unit includes: a first marking unit configured to add a first attribute to the track points with quality problems that have been identified in the plurality of track data, wherein the first attribute identifies the first scene information corresponding to the track points with quality problems; and a second marking unit configured to add a second attribute to the picture data including the identified picture data with quality problems in the plurality of picture data, wherein the second attribute identifies the second scene information corresponding to the picture data with quality problems. The quality inspection unit includes: a unit for performing quality inspection on the map data to be inspected based on the first attribute and the second attribute.

[0064] According to some embodiments, the first attribute includes at least one of the following items: a reversing scene, and a repeated collection scene. The reversing scene indicates that the corresponding track point is a track point collected in a reversing scene; the repeated collection scene indicates that the corresponding track point is a repeated track point obtained by repeatedly collecting the same lane.

[0065] According to some embodiments, the trajectory point includes position information of the corresponding vehicle at the trajectory point, wherein the first attribute includes an elevated scene, and the elevated scene indicates that the corresponding trajectory point is a trajectory point within a preset horizontal range and has a height difference.

[0066] According to some embodiments, the second attribute includes at least one of the following items: a lane line scene, and an intersection scene. The lane line scene represents a lane line portion with quality problems in the target area formed by splicing the multiple image data; the intersection scene represents an intersection portion in the target area formed by splicing the multiple image data.

[0067] According to some embodiments, the lane line scenario includes at least one of the following items: a lane line continuous occlusion scenario, a lateral error scenario, and a longitudinal error scenario. The lane line continuous occlusion scenario indicates that the lane line portion with quality problems is an occluded lane line portion; the lateral error scenario indicates that the corresponding lane line is staggered left and right in the direction extending along the corresponding trajectory; and the longitudinal error scenario indicates that the corresponding lane line is a zebra crossing and the zebra crossing is staggered.

[0068] According to some embodiments, the attribute information is displayed according to corresponding visual attributes, wherein the visual attributes are determined based on the traffic scene.

[0069] Here, the operations of the above-mentioned units 310-330 of the map production data quality inspection device 300 are similar to the operations of the steps 210-230 described above, and will not be repeated here.

[0070] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0071] According to an embodiment of the present disclosure, an electronic device, a readable storage medium and a computer program product are also provided.

[0072] refer to Figure 4 , a block diagram of an electronic device 400 that can be used as a server or client of the present disclosure will now be described, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0073] like Figure 4As shown, the electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0074] Multiple components in the electronic device 400 are connected to the I / O interface 405, including: an input unit 406, an output unit 407, a storage unit 408, and a communication unit 409. The input unit 406 can be any type of device that can input information to the electronic device 400. The input unit 406 can receive input digital or character information and generate key signal input related to user settings and / or function control of the electronic device, and can include but is not limited to a mouse, a keyboard, a touch screen, a track pad, a track ball, a joystick, a microphone, and / or a remote controller. The output unit 407 can be any type of device that can present information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 408 can include but is not limited to a disk, an optical disk. The communication unit 409 allows the electronic device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and can include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth device, an 802.11 device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0075] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 401 performs the various methods and processes described above, such as method 200. For example, in some embodiments, the method 200 may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the method 200 described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the method 200 in any other appropriate manner (e.g., by means of firmware).

[0076] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0077] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0078] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0079] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0080] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0081] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0082] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0083] Although the embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it should be understood that the above-mentioned methods, systems and devices are merely exemplary embodiments or examples, and the scope of the present invention is not limited by these embodiments or examples, but only by the claims after authorization and their equivalent scope. Various elements in the embodiments or examples can be omitted or replaced by their equivalent elements. In addition, each step can be performed in an order different from that described in the present disclosure. Further, the various elements in the embodiments or examples can be combined in various ways. It is important that with the evolution of technology, many elements described herein can be replaced by equivalent elements that appear after the present disclosure.

Claims

1. A map production data quality inspection method, comprising: Obtain the map data to be inspected in the target area; Adding corresponding attribute information to the map data determined to have quality problems in the map data to be inspected, wherein the attribute information is used to represent the traffic scene corresponding to the map data having quality problems; as well as The map data to be inspected is quality inspected based on the attribute information.

2. The method of claim 1, wherein: The map data to be inspected includes a plurality of image data of the target area taken and a plurality of track data collected by vehicles passing through the target area, wherein each of the plurality of track data includes a plurality of track points collected during the driving process of the corresponding vehicle, wherein: Adding corresponding attribute information to the map data determined to have quality problems in the map data to be inspected includes: Adding a first attribute to the identified track points with quality problems in the plurality of track data, wherein the first attribute identifies first scene information corresponding to the track points with quality problems; and Adding a second attribute to the picture data including the identified picture data with quality problems among the multiple picture data, wherein the second attribute identifies second scene information corresponding to the picture data with quality problems; Performing quality inspection on the map data to be inspected based on the attribute information includes: The map data to be quality inspected is quality inspected based on the first attribute and the second attribute.

3. The method of claim 2, wherein: The first attribute includes at least one of the following items: a reversing scene, a repeated acquisition scene, wherein, The reversing scene indicates that the corresponding track points are track points collected in the reversing scene; The repeated collection scenario indicates that the corresponding trajectory points are repeated trajectory points obtained by repeatedly collecting data on the same lane.

4. The method according to claim 2 or 3, wherein: The trajectory point includes position information of the corresponding vehicle at the trajectory point, wherein the first attribute includes an elevated scene, and the elevated scene indicates that the corresponding trajectory point is a trajectory point within a preset horizontal range and has a height difference.

5. The method according to any one of claims 2 to 4, wherein: The second attribute includes at least one of the following items: lane line scene, intersection scene, wherein, The lane line scene represents a lane line portion with quality problems in the target area formed by splicing the multiple image data; The intersection scene represents the intersection portion in the target area formed by splicing the multiple image data.

6. The method of claim 5, wherein: The lane line scenario includes at least one of the following items: a lane line continuous occlusion scenario, a lateral error scenario, and a longitudinal error scenario, wherein: The lane line continuous occlusion scenario indicates that the lane line portion with quality problems is the occluded lane line portion; The lateral error scenario indicates that the corresponding lane line is staggered left and right in the direction extending along the corresponding trajectory; and The longitudinal error scenario indicates that the corresponding lane line is a zebra crossing and the zebra crossing is staggered.

7. The method according to claim 1 or 2, wherein: The attribute information is displayed according to corresponding visual attributes, wherein the visual attributes are determined based on the traffic scene.

8. A map production data quality inspection device, comprising: An acquisition unit configured to acquire map data to be inspected in a target area; a marking unit configured to add corresponding attribute information to the map data determined to have quality problems in the map data to be inspected, wherein the attribute information is used to indicate the traffic scene corresponding to the map data having quality problems; as well as The quality inspection unit is configured to perform quality inspection on the map data to be inspected based on the attribute information.

9. The device of claim 8, wherein: The map data to be inspected includes a plurality of image data of the target area taken and a plurality of track data collected by vehicles passing through the target area, wherein each of the plurality of track data includes a plurality of track points collected during the driving process of the corresponding vehicle, wherein: The marking unit comprises: A first marking unit, configured to add a first attribute to the identified track points with quality problems in the plurality of track data, wherein the first attribute identifies first scene information corresponding to the track points with quality problems; and A second marking unit is configured to add a second attribute to the picture data including the identified picture data with quality problems among the multiple picture data, wherein the second attribute identifies second scene information corresponding to the picture data with quality problems; The quality inspection unit comprises: A unit for performing quality inspection on the map data to be quality inspected based on the first attribute and the second attribute.

10. The device of claim 9, wherein: The first attribute includes at least one of the following items: a reversing scene, a repeated acquisition scene, wherein, The reversing scene indicates that the corresponding track points are track points collected in the reversing scene; The repeated collection scenario indicates that the corresponding trajectory points are repeated trajectory points obtained by repeatedly collecting data on the same lane.

11. The device according to claim 9 or 10, wherein: The trajectory point includes position information of the corresponding vehicle at the trajectory point, wherein the first attribute includes an elevated scene, and the elevated scene indicates that the corresponding trajectory point is a trajectory point within a preset horizontal range and has a height difference.

12. The device according to any one of claims 9 to 11, wherein: The second attribute includes at least one of the following items: lane line scene, intersection scene, wherein, The lane line scene represents a lane line portion with quality problems in the target area formed by splicing the multiple image data; The intersection scene represents the intersection portion in the target area formed by splicing the multiple image data.

13. The device of claim 12, wherein: The lane line scenario includes at least one of the following items: a lane line continuous occlusion scenario, a lateral error scenario, and a longitudinal error scenario, wherein: The lane line continuous occlusion scenario indicates that the lane line portion with quality problems is the occluded lane line portion; The lateral error scenario indicates that the corresponding lane line is staggered left and right in the direction extending along the corresponding trajectory; and The longitudinal error scenario indicates that the corresponding lane line is a zebra crossing and the zebra crossing is staggered.

14. The device according to claim 8 or 9, wherein: The attribute information is displayed according to corresponding visual attributes, wherein the visual attributes are determined based on the traffic scene.

15. An electronic device, comprising: at least one processor; as well as a memory communicatively coupled to the at least one processor; in The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

16. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

17. A computer program product comprising a computer program, wherein: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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