4D lane line marking data quality inspection method and device, electronic equipment and storage medium

Abstract

The invention discloses a 4D lane line marking data quality inspection method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring target point cloud data, and determining target 4D lane line marking data according to the target point cloud data; determining a target quality inspection operation result of the target 4D lane line marking data, wherein the target quality inspection operation result is a result obtained after target quality inspection operation is performed on the target 4D lane line marking data; and determining abnormal 4D lane line marking data in the target 4D lane line marking data based on the target quality inspection operation result, wherein the abnormal 4D lane line marking data is target 4D lane line marking data which is represented by the target quality inspection operation result and exceeds the target quality inspection operation. According to the scheme, the target quality inspection operation is executed on the target 4D lane line marking data, and the quality inspection efficiency and accuracy of the target 4D lane line marking data are improved.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving labeling technology, and in particular to a 4D lane line labeling data quality inspection method, device, electronic device and storage medium. Background Art

[0002] With the rapid development of artificial intelligence technology, the application level of autonomous driving in some scenarios is getting higher and higher, and the requirements for the accuracy of perception algorithms in vehicle control are also getting higher and higher. The training of perception algorithms requires a large amount of annotated relevant data as support, and the quality of annotated data plays a key role in the training of perception algorithms.

[0003] At present, the collection of lane marking data is affected by coating materials and weather, and the time dimension is introduced. The multi-frame data captured by the vehicle sensor is fused into one scene to improve the collection effect of lane marking data. However, when the time dimension is introduced to enhance the collection effect of lane marking data, the amount of marked data increases under the large point cloud, and the efficiency and accuracy of manual quality inspection are further reduced. Summary of the invention

[0004] The present invention provides a 4D lane line marking data quality inspection method, device, electronic device and storage medium to solve the problems of low efficiency and poor accuracy in manual quality inspection of 4D lane line marking data.

[0005] According to one aspect of the present invention, a 4D lane line annotation data quality inspection method is provided, the method comprising:

[0006] Obtain target point cloud data, and determine target 4D lane line annotation data based on the target point cloud data, the target point cloud data is the three-dimensional data of the target object in the vehicle driving scene, the target object includes at least a plurality of target lane lines, the target 4D lane line annotation data is the 4D annotation data of the plurality of target lane lines, and the 4D annotation data is obtained by superimposing the three-dimensional data within a preset time range and then adding annotations;

[0007] Determine a target quality inspection operation result of the target 4D lane line annotation data. The target quality inspection operation result is a result obtained after performing a target quality inspection operation on the target 4D lane line annotation data. The target quality inspection operation includes: a jump quality inspection operation, a type quality inspection operation, and a preset quality inspection operation. The jump quality inspection operation is used to check whether the smoothness of each annotated lane line meets a preset smoothness threshold. The annotated lane line is a lane line that represents the target lane line according to the target 4D lane line annotation data. The type quality inspection operation is used to check the annotation type of the target 4D lane line annotation data based on the intersection state between every two annotated lane lines. The preset quality inspection operation is used to check a specified annotation task. The annotation task is a task of performing quality inspection on the target 4D lane line annotation data within the same time range.

[0008] Based on the target quality inspection operation result, abnormal 4D lane line marking data in the target 4D lane line marking data is determined, and the abnormal 4D lane line marking data is the target 4D lane line marking data that exceeds the target quality inspection operation as indicated by the target quality inspection operation result.

[0009] According to another aspect of the present invention, a 4D lane line marking data quality inspection device is provided, the device comprising:

[0010] The first determination module is used to obtain target point cloud data and determine target 4D lane line annotation data according to the target point cloud data. The target point cloud data is three-dimensional data of a target object of a vehicle in a driving scene. The target object includes at least a plurality of target lane lines. The target 4D lane line annotation data is 4D annotation data of a plurality of target lane lines. The 4D annotation data is obtained by superimposing three-dimensional data within a preset time range and then adding annotations.

[0011] The second determination module is used to determine the target quality inspection operation result of the target 4D lane line annotation data. The target quality inspection operation result is the result obtained after performing the target quality inspection operation on the target 4D lane line annotation data. The target quality inspection operation includes: a jump quality inspection operation, a type quality inspection operation and a preset quality inspection operation. The jump quality inspection operation is used to check whether the smoothness of each annotated lane line meets the preset smoothness threshold. The annotated lane line is a lane line that represents the target lane line according to the target 4D lane line annotation data. The type quality inspection operation is used to check the annotation type of the target 4D lane line annotation data based on the intersection state between every two annotated lane lines. The preset quality inspection operation is used to check the specified annotation task. The annotation task is a task of performing quality inspection on the target 4D lane line annotation data within the same time range;

[0012] The third determination module is used to determine abnormal 4D lane line marking data in the target 4D lane line marking data based on the target quality inspection operation result, where the abnormal 4D lane line marking data is the target 4D lane line marking data that exceeds the target quality inspection operation as indicated by the target quality inspection operation result.

[0013] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the 4D lane line marking data quality inspection method of any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions, and the computer instructions are used to implement the 4D lane line marking data quality inspection method of any embodiment of the present invention when executed by a processor.

[0018] The technical solution of the embodiment of the present invention obtains target point cloud data and determines target 4D lane line annotation data based on the target point cloud data. The target point cloud data is the three-dimensional data of the target object of the vehicle in the driving scene. The target object includes at least a plurality of target lane lines. The target 4D lane line annotation data is the 4D annotation data of the plurality of target lane lines. The 4D annotation data is obtained by superimposing the three-dimensional data within a preset time range and then adding annotations, thereby realizing the acquisition of the target 4D lane line annotation data and providing actual data support for the subsequent quality inspection process; determining the target quality inspection operation result of the target 4D lane line annotation data. The target quality inspection operation result is the result obtained after performing the target quality inspection operation on the target 4D lane line annotation data. The target quality inspection operation includes: a jump quality inspection operation, a type quality inspection operation and a preset quality inspection operation. The jump quality inspection operation is used to check whether the smoothness of each annotated lane line meets the preset smoothness threshold. The annotated lane line is based on The target 4D lane line annotation data represents the lane line of the target lane line. The type quality inspection operation is used to inspect the annotation type of the target 4D lane line annotation data based on the intersection state between every two annotated lane lines. The preset quality inspection operation is used to inspect the specified annotation task. The annotation task is a task to perform quality inspection on the target 4D lane line annotation data belonging to the same time range. The target quality inspection operation is performed on the target 4D lane line annotation data, which improves the efficiency and accuracy of quality inspection on the target 4D lane line annotation data and reduces labor costs. The abnormal 4D lane line annotation data in the target 4D lane line annotation data is determined based on the target quality inspection operation result. The abnormal 4D lane line annotation data is the target 4D lane line annotation data that exceeds the target quality inspection operation represented by the target quality inspection operation result. The abnormal 4D lane line annotation data with annotation errors is determined according to the target quality inspection operation result, so as to facilitate secondary quality inspection of the abnormal 4D lane line annotation data.

[0019] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 A flowchart of a 4D lane line marking data quality inspection method provided in Example 1 of the present invention;

[0022] Figure 2 A flowchart of a 4D lane line marking data quality inspection method provided in Embodiment 2 of the present invention;

[0023] Figure 3 A flowchart of a 4D lane line marking data quality inspection method provided in Embodiment 3 of the present invention;

[0024] Figure 4 A schematic diagram of lane marking provided in Embodiment 3 of the present invention;

[0025] Figure 5 A schematic diagram of the structure of a 4D lane marking data quality inspection device provided in Embodiment 4 of the present invention;

[0026] Figure 6 A schematic diagram of the structure of an electronic device for implementing a 4D lane line marking data quality inspection method provided in Embodiment 5 of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] It is understandable that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and relevant provisions.

[0030] Embodiment 1

[0031] Figure 1 The flowchart of a 4D lane line marking data quality inspection method provided in the first embodiment of the present invention. The embodiment of the present invention can be applied to the situation of quality inspection of 4D lane line marking data. The method can be executed by a 4D lane line marking data quality inspection device. The device can be implemented in the form of hardware and / or software and can be configured in an electronic device that implements the 4D lane line marking data quality inspection method. Figure 1 As shown, the method includes:

[0032] S101. Acquire target point cloud data, and determine target 4D lane line annotation data based on the target point cloud data. The target point cloud data is three-dimensional data of a target object of a vehicle in a driving scene. The target object includes at least a plurality of target lane lines. The target 4D lane line annotation data is 4D annotation data of the plurality of target lane lines. The 4D annotation data is obtained by superimposing three-dimensional data within a preset time range and then adding annotations.

[0033] In the embodiment of the present invention, the driving scene may refer to various situations or environments encountered by the vehicle during automatic driving. The target object may refer to several objects in the driving scene, such as the road on which the vehicle is located, nearby pedestrians, signs or buildings, etc. The target lane line may refer to the lane line of the road on which the vehicle is located in the driving scene, which is used to divide the road, guide traffic flow, indicate driving direction and lane boundaries, etc. Exemplarily, when the vehicle is driving on a road with only one lane, the several target lane lines may be lane lines on both sides of the lane; when the vehicle is driving on a road with multiple lanes, the several target lane lines may be multiple lane lines that divide the road.

[0034] The target point cloud data may refer to the three-dimensional data of the target object in the driving scene. By using the statistical filtering method on the target point cloud data, discrete points can be removed to improve the accuracy of subsequent processing. When the amount of target point cloud data exceeds the preset threshold, the voxel grid filtering method can be combined to reduce the amount of target point cloud data and improve system performance. 4D annotated data may refer to the data annotated by introducing the time dimension in the three-dimensional space, which is obtained by superimposing multiple frames of three-dimensional data within a preset time range and then adding annotations.

[0035] Specifically, when a vehicle is traveling in a driving scene, three-dimensional data of a target object in the driving scene can be obtained as target point cloud data, and the target point cloud data at least includes three-dimensional data of several target lane lines. Furthermore, by superimposing the three-dimensional data of several target lane lines within a preset time range and adding annotations, 4D annotation data of several target lane lines can be obtained as target 4D lane line annotation data.

[0036] For example, the target point cloud data of the target lane line can be collected at a time interval of 0.1s by the sensor configured by the vehicle, and the 3D data of several target lane lines can be screened out from the target point cloud data. Furthermore, when the preset time range is 1s, 10 frames of 3D data can be obtained within the preset time range, and the 4D annotation data of the target lane line can be obtained by superimposing the 10 3D annotation data frames and adding annotations using a semantic recognition algorithm or manual annotation.

[0037] S102. Determine a target quality inspection operation result for the target 4D lane line annotation data. The target quality inspection operation result is a result obtained after performing a target quality inspection operation on the target 4D lane line annotation data. The target quality inspection operation includes: a jump quality inspection operation, a type quality inspection operation, and a preset quality inspection operation. The jump quality inspection operation is used to check whether the smoothness of each annotated lane line meets a preset smoothness threshold. The annotated lane line is a lane line that represents the target lane line according to the target 4D lane line annotation data. The type quality inspection operation is used to check the annotation type of the target 4D lane line annotation data based on the intersection state between every two annotated lane lines. The preset quality inspection operation is used to check a specified annotation task. The annotation task is a task that performs quality inspection on the target 4D lane line annotation data within the same time range.

[0038] In an embodiment of the present invention, a marked lane line may refer to a lane line that represents a target lane line after connecting each node in the target 4D lane line marking data in sequence according to the marked target lane line. Accordingly, the number of marked lane lines is the same as the number of target lane lines. A jump quality inspection operation may refer to checking whether a lane line jump occurs in a marked lane line. When the smoothness of a marked lane line exceeds a preset smoothness threshold, it can be considered that a lane line jump occurs in the marked lane line. The three dimensions in the target 4D lane line marking data may be the X-axis, the Y-axis, and the Z-axis, respectively, and accordingly, a lane line jump may include an X-axis lane line jump, a Y-axis lane line jump, and a Z-axis lane line jump.

[0039] In an embodiment of the present invention, the type quality inspection operation may refer to inspecting the type of the corresponding target 4D lane line annotation data when two marked lane lines intersect among a plurality of marked lane lines. Exemplarily, when two marked lane lines intersect, the types of the corresponding target 4D lane line annotation data are not allowed to be the same type. The preset quality inspection operation may refer to a customized inspection operation for a specified annotation task to achieve flexible automatic quality inspection.

[0040] Specifically, the jump quality inspection operation, type quality inspection operation and preset quality inspection operation performed on the target 4D lane line annotation data can be used as the target quality inspection operation performed on the target 4D lane line annotation data. Correspondingly, the jump quality inspection operation result, type quality inspection operation result and preset quality inspection operation result obtained after the jump quality inspection operation, type quality inspection operation and preset quality inspection operation are performed on the target 4D lane line annotation data can be used as the target quality inspection operation result.

[0041] As an option, determining the target quality inspection operation result of the target 4D lane line annotation data includes the following steps A1-A2:

[0042] Step A1: determining the intersection state between every two marked lane lines among a plurality of marked lane lines.

[0043] Step A2: determining the type quality inspection result of the target 4D lane line marking data according to the intersection state.

[0044] Specifically, each marked lane line can be discretized to obtain a discrete point sequence for each marked lane line, so that the discrete point sequences of each marked lane line can be judged to be intersecting. If there is an intersection between the discrete point sequences, the corresponding two marked lane lines are considered to be in an intersecting state. Furthermore, if it is detected that there are two intersecting marked lane lines among several marked lane lines, the type inspection result of the target 4D lane line annotation data corresponding to the two intersecting marked lane lines is used as the type quality inspection operation result.

[0045] As an option, determining the target quality inspection operation result of the target 4D lane line annotation data includes the following steps B1-B3:

[0046] Step B1: determine the target quality inspection object in the labeling task, where the target quality inspection object is the object for quality inspection of the target 4D lane line labeling data.

[0047] Step B2: Determine the reference configuration operation of the target quality inspection object, the reference configuration operation includes: target configuration, action configuration, condition configuration and logical relationship configuration.

[0048] Step B3: Determine a preset quality inspection operation result of the target 4D lane line marking data according to the target quality inspection object and the reference configuration operation.

[0049] In an embodiment of the present invention, the target quality inspection object may refer to an object that is preset when inspecting the target 4D lane line annotation data, such as a global annotation or a three-dimensional point cloud lane line. The target configuration may refer to a preset quality inspection operation performed when inspecting the target quality inspection object, such as inspecting the lane line type or inspecting the lane line jump. The action configuration may include equal to, not equal to, greater than, less than, empty or illegal. The condition configuration may refer to a preset specific detection value when inspecting the target quality inspection object. The logical relationship configuration may include and and or.

[0050] Specifically, the verification operation of the target quality inspection object can be generated by performing target configuration, action configuration and condition configuration on the target quality inspection object in the labeling task, and the reference configuration operation of the target quality inspection object can be generated after logical relationship configuration of multiple verification operations. Furthermore, the target 4D lane line annotation data is compared and verified with the reference configuration operation of the target quality inspection object to obtain the preset quality inspection operation result of the target 4D lane line annotation data. Exemplarily, the target quality inspection object can be specified as a three-dimensional point cloud lane line, the target configuration is to check lane line jumps, the action configuration is greater than, and the condition configuration is to set the jump detection threshold to 0.9, so that the operation verification operation of the three-dimensional point cloud lane line is to check lane line jumps greater than the jump detection threshold of 0.9.

[0051] S103. Determine abnormal 4D lane line marking data in the target 4D lane line marking data based on the target quality inspection operation result, where the abnormal 4D lane line marking data is the target 4D lane line marking data that exceeds the target quality inspection operation as indicated by the target quality inspection operation result.

[0052] Specifically, the target quality inspection operation result can be used to determine abnormal 4D lane line marking data with errors in the target 4D lane line marking data, so as to perform a secondary quality inspection on the abnormal 4D lane line marking data, thereby ensuring the accuracy of the lane line marking data.

[0053] The technical solution of the embodiment of the present invention obtains target point cloud data and determines target 4D lane line annotation data based on the target point cloud data. The target point cloud data is the three-dimensional data of the target object of the vehicle in the driving scene. The target object includes at least a plurality of target lane lines. The target 4D lane line annotation data is the 4D annotation data of the plurality of target lane lines. The 4D annotation data is obtained by superimposing the three-dimensional data within a preset time range and then adding annotations, thereby realizing the acquisition of the target 4D lane line annotation data and providing actual data support for the subsequent quality inspection process; determining the target quality inspection operation result of the target 4D lane line annotation data. The target quality inspection operation result is the result obtained after performing the target quality inspection operation on the target 4D lane line annotation data. The target quality inspection operation includes: a jump quality inspection operation, a type quality inspection operation and a preset quality inspection operation. The jump quality inspection operation is used to check whether the smoothness of each annotated lane line meets the preset smoothness threshold. The annotated lane line is based on The target 4D lane line annotation data represents the lane line of the target lane line. The type quality inspection operation is used to inspect the annotation type of the target 4D lane line annotation data based on the intersection state between every two annotated lane lines. The preset quality inspection operation is used to inspect the specified annotation task. The annotation task is a task to perform quality inspection on the target 4D lane line annotation data belonging to the same time range. The target quality inspection operation is performed on the target 4D lane line annotation data, which improves the efficiency and accuracy of quality inspection on the target 4D lane line annotation data and reduces labor costs. The abnormal 4D lane line annotation data in the target 4D lane line annotation data is determined based on the target quality inspection operation result. The abnormal 4D lane line annotation data is the target 4D lane line annotation data that exceeds the target quality inspection operation represented by the target quality inspection operation result. The abnormal 4D lane line annotation data with annotation errors is determined according to the target quality inspection operation result, so as to facilitate secondary quality inspection of the abnormal 4D lane line annotation data.

[0054] Embodiment 2

[0055] Figure 2 A flowchart of a 4D lane line marking data quality inspection method provided in the second embodiment of the present invention. The technical solution of this embodiment further optimizes the target quality inspection operation result of determining the target 4D lane line marking data of the above embodiment on the basis of the technical solution of the above embodiment. The solutions not described in detail in this embodiment can be found in the above embodiment. This embodiment can be combined with various optional solutions in one or more of the above embodiments. Figure 2 As shown, the method includes:

[0056] S201. Acquire target point cloud data, and determine target 4D lane line annotation data based on the target point cloud data. The target point cloud data is three-dimensional data of a target object of a vehicle in a driving scene. The target object includes at least a plurality of target lane lines. The target 4D lane line annotation data is 4D annotation data of the plurality of target lane lines. The 4D annotation data is obtained by superimposing three-dimensional data within a preset time range and then adding annotations.

[0057] S202: Determine a target surface equation of the target 4D lane line marking data, where the target surface equation is used to fit a drivable vehicle trajectory corresponding to the target 4D lane line marking data.

[0058] Specifically, the target surface equation can be obtained by performing surface fitting on the vehicle drivable trajectory corresponding to the target 4D lane line annotation data, wherein the vehicle drivable trajectory may refer to the road on which the vehicle travels in the driving scene represented by the target 4D lane line annotation data.

[0059] As an optional method, determining the target surface equation of the target 4D lane line annotation data includes the following steps C1-C4:

[0060] Step C1: determining the vehicle drivable trajectory corresponding to the target 4D lane line marking data according to the target point cloud data.

[0061] Step C2: segment the vehicle's drivable trajectory according to the preset segmentation distance.

[0062] Step C3: determine the target plane equation corresponding to each segment of the vehicle's drivable trajectory.

[0063] Step C4: performing weighted summation on the target plane equation of each segment of the vehicle's drivable trajectory to obtain the target surface equation.

[0064] Specifically, according to the vehicle motion characteristics, the vehicle drivable trajectory can be segmented from the target point cloud data, and the vehicle drivable trajectory can be divided into i segments according to the preset segmentation distance d. After plane fitting for each segment of the vehicle drivable trajectory, the corresponding target plane equation can be obtained. Furthermore, based on the vehicle drivable trajectory, the weighted summation of each target plane equation can be obtained to obtain the target surface equation.

[0065] For example, the PANSAC algorithm can be used to perform plane fitting on each segment of the vehicle's drivable trajectory. i , and from l i Randomly select three non-collinear points to fit the vehicle's drivable trajectory to obtain the fitting plane equation f i (x, y, z) = a i x+b i y+c i z+di = 0. Calculate l i The distance from other points in the plane to the fitted plane equation is compared with the preset distance threshold. Points less than the preset distance threshold are regarded as inliers, and the proportion of inliers is calculated. Among them, n inlier represents the number of internal points, n total Indicates l i The above process is repeated until the increase in p is less than the preset increase threshold, and the final fitting plane equation is used as the target plane equation. Then, the target surface equation can be obtained by weighted summation of each target plane equation. Among them, w i represents the weight of each target plane equation and is determined based on the inlier ratio p.

[0066] S203, determining the Z-axis jitter tolerance value of the target 4D lane line annotation data, where the three dimensions of the target 4D lane line annotation data are the X-axis, the Y-axis, and the Z-axis, and the Z-axis jitter tolerance value is used to check whether the smoothness of each annotated lane line on the Z-axis meets a preset smoothness threshold.

[0067] Specifically, the jitter error value allowed for the Z-axis value of each node coordinate in the target 4D lane line annotation data can be preset as the Z-axis jitter tolerance value. If the Z-axis value of each node coordinate in the target 4D lane line annotation data meets the Z-axis jitter tolerance value, it can be considered that the smoothness of the annotated lane line corresponding to the target 4D lane line annotation data on the Z-axis meets the preset smoothness threshold.

[0068] S204: Determine a jump quality inspection operation result of the target 4D lane line marking data based on the target surface equation and the Z-axis jitter tolerance value.

[0069] Specifically, the coordinates of each node in the target 4D lane line annotation data can be substituted into the target surface equation to obtain the Z-axis jitter value of each node coordinate relative to the target surface equation. Furthermore, the absolute value of the Z-axis jitter value of each node coordinate relative to the target surface equation can be compared with the Z-axis jitter tolerance value. If the absolute value of the Z-axis jitter value of the node exists is greater than the Z-axis jitter tolerance value, it is considered that the marked lane line represented by the target 4D lane line annotation data has a Z-axis lane line jump, and the node is marked. If the absolute value of the Z-axis jitter value of the node does not exist is greater than the Z-axis jitter tolerance value, it is considered that the marked lane line represented by the target 4D lane line annotation data does not have a Z-axis lane line jump. Finally, whether the marked lane line represented by the target 4D lane line annotation data has a Z-axis lane line jump can be used as the jump quality inspection operation result.

[0070] S205. Determine abnormal 4D lane line marking data in the target 4D lane line marking data based on the target quality inspection operation result, where the abnormal 4D lane line marking data is the target 4D lane line marking data that exceeds the target quality inspection operation as indicated by the target quality inspection operation result.

[0071] The technical solution of the embodiment of the present invention obtains target point cloud data and determines target 4D lane line annotation data according to the target point cloud data. The target point cloud data is three-dimensional data of the target object of the vehicle in the driving scene. The target object includes at least several target lane lines. The target 4D lane line annotation data is 4D annotation data of several target lane lines. The 4D annotation data is obtained by superimposing the three-dimensional data within a preset time range and then adding annotations, thereby realizing the acquisition of the target 4D lane line annotation data and providing actual data support for the subsequent quality inspection process; determining the target surface equation of the target 4D lane line annotation data, and the target surface equation is used to fit the vehicle drivable trajectory corresponding to the target 4D lane line annotation data; determining the Z-axis jitter tolerance value of the target 4D lane line annotation data, the three dimensions of the target 4D lane line annotation data are respectively the X-axis, the Y-axis and the Z-axis, and the Z-axis jitter tolerance value is used to check each Whether the smoothness of the marked lane line on the Z axis meets the preset smoothness threshold; based on the target surface equation and the Z-axis jitter tolerance value, the jump quality inspection operation result of the target 4D lane line annotation data is determined, and the target surface equation of the vehicle drivable trajectory corresponding to the target 4D lane line annotation data is obtained, and based on the target surface equation and the Z-axis jitter tolerance value, it is determined whether there is a Z-axis lane line jump in the marked lane line, so as to improve the accuracy of the jump quality inspection operation on the target 4D lane line annotation data; based on the target quality inspection operation result, the abnormal 4D lane line annotation data in the target 4D lane line annotation data is determined, and the abnormal 4D lane line annotation data is the target 4D lane line annotation data that exceeds the target quality inspection operation represented by the target quality inspection operation result, and it is realized to determine the abnormal 4D lane line annotation data with labeling errors according to the target quality inspection operation result, so as to perform secondary quality inspection on the abnormal 4D lane line annotation data.

[0072] Embodiment 3

[0073] Figure 3 A flowchart of a 4D lane line marking data quality inspection method provided in the third embodiment of the present invention. The technical solution of this embodiment further optimizes the target quality inspection operation result of determining the target 4D lane line marking data of the above embodiment on the basis of the technical solution of the above embodiment. The scheme not described in detail in this embodiment can be found in the above embodiment. This embodiment can be combined with various optional schemes in one or more of the above embodiments. Figure 3 As shown, the method includes:

[0074] S301. Acquire target point cloud data, and determine target 4D lane line annotation data based on the target point cloud data. The target point cloud data is three-dimensional data of a target object of a vehicle in a driving scene. The target object includes at least a plurality of target lane lines. The target 4D lane line annotation data is 4D annotation data of a plurality of target lane lines. The 4D annotation data is obtained by superimposing three-dimensional data within a preset time range and then adding annotations.

[0075] S302. Segment a plurality of annotated lane lines according to the target 4D lane line annotated data to obtain a plurality of reference lane line segments.

[0076] Specifically, the annotated lane lines are formed by correspondingly connecting each node in the target 4D lane line annotation data in sequence. Therefore, several annotated lane lines can be segmented according to each node in the target 4D lane line annotation data to obtain several reference lane lines. Exemplarily, the annotated lane lines can be segmented according to nodes at different positions in the annotated lane lines, and there are nodes with a preset number of nodes between nodes at different positions in the annotated lane lines. Among them, the preset number of nodes is not less than 0 and the smaller the preset number of nodes, the better the segmentation effect of the annotated lane lines. If the preset number of nodes is 0, it means that the annotated lane lines are segmented according to two adjacent nodes in the annotated lane lines.

[0077] S303: Determine tangent vectors of several sections of reference lane lines, where the tangent vector is a vector formed by mapping the reference lane line to two endpoints on a horizontal plane.

[0078] Specifically, the tangent vector of the reference lane line may refer to the tangent vector of the reference lane line on the X-axis or Y-axis. Therefore, each section of the reference lane line may be mapped to a horizontal plane, that is, only the X-axis and Y-axis coordinates are retained for the two endpoints of the reference lane line, so that the tangent vector of the reference lane line may be determined according to the X-axis and Y-axis coordinates of the two endpoints.

[0079] For example, for the two endpoints of the reference lane line (x i ,y i , z i ) and (x i+1 ,y i+1 , z i+1 ), the tangent vector of the reference lane line It can be expressed as:

[0080]

[0081] Tangent vector After normalization, we can get:

[0082]

[0083] S304: Determine the jump quality inspection result of the target 4D lane line annotation data according to the tangent vector.

[0084] Specifically, it is possible to determine whether each marked lane line has an X-axis or Y-axis lane line jump based on the tangent vectors of each reference lane line segment in each marked lane line, and use whether the marked lane line represented by the target 4D lane line marking data has an X-axis or Y-axis lane line jump as the jump quality inspection operation result.

[0085] As an option, determining the jump quality inspection operation result of the target 4D lane line annotation data according to the tangent vector includes the following steps D1-D3:

[0086] Step D1: determine the vector angle between the tangent vectors of every two adjacent reference lane lines on each marked lane line.

[0087] Step D2: determine a preset vector angle threshold of the vector angle, where the preset vector angle threshold is used to check whether the smoothness of each marked lane line on the X-axis or the Y-axis meets the preset smoothness threshold.

[0088] Step D3: determining the jump quality inspection operation result of the target 4D lane line marking data based on the vector angle and the preset vector angle threshold.

[0089] Specifically, the vector angle between the tangent vectors of every two adjacent reference lane lines on each marked lane line can be calculated by traversal, and then compared with the preset vector angle threshold in turn. If the vector angle between the tangent vectors of two adjacent reference lane lines is greater than the preset vector angle threshold, the endpoints shared by the two adjacent reference lane lines are marked, indicating that the marked lane lines to which the two adjacent reference lane lines belong have an X-axis or Y-axis jump at the endpoint, so that the smoothness of the marked lane lines to which the two adjacent reference lane lines belong on the X-axis or Y-axis does not meet the preset smoothness threshold. By analogy, it can be determined whether there is an X-axis or Y-axis lane line jump for each marked lane line as the jump quality inspection operation result.

[0090] For example, Figure 4 The annotated lane lines shown in the figure are used to calculate the tangent vectors of each reference lane line as shown in Table 1:

[0091] Table 1 Schematic diagram of tangent vectors of reference lane lines

[0092] Reference lane line Tangent Vector A, B (0.8，0.5) B, C (0.8，0.5) C, D (0.6，0.4) D, E (0.5，0.4) E, F (0，0.9) F, G (0.7，-0.3) G, H (0.6，0.5)

[0093] Furthermore, according to the vector angle between the tangent vectors of every two adjacent reference lane lines, it can be determined that the marked lane line jumps at point F.

[0094] S305. Determine abnormal 4D lane line marking data in the target 4D lane line marking data based on the target quality inspection operation result, where the abnormal 4D lane line marking data is the target 4D lane line marking data that exceeds the target quality inspection operation as indicated by the target quality inspection operation result.

[0095] The technical solution of the embodiment of the present invention obtains target point cloud data and determines target 4D lane line annotation data based on the target point cloud data. The target point cloud data is three-dimensional data of the target object of the vehicle in the driving scene. The target object includes at least several target lane lines. The target 4D lane line annotation data is 4D annotation data of several target lane lines. The 4D annotation data is obtained by superimposing the three-dimensional data within a preset time range and then adding annotations, thereby realizing the acquisition of the target 4D lane line annotation data and providing actual data support for the subsequent quality inspection process; according to the target 4D lane line annotation data, several annotated lane lines are segmented to obtain several reference lane lines; and the tangent vectors of several reference lane lines are determined, and the tangent vectors are the reference lane lines mapped onto the horizontal plane. a vector formed by the two endpoints of ; the jump quality inspection operation result of the target 4D lane line annotation data is determined according to the tangent vector, and it is realized that based on the tangent vectors of several sections of reference lane lines in the labeled lane line, it is determined whether there is an X-axis or Y-axis lane line jump in the labeled lane line, so as to further improve the accuracy of the jump quality inspection operation on the target 4D lane line annotation data; based on the target quality inspection operation result, the abnormal 4D lane line annotation data in the target 4D lane line annotation data is determined, and the abnormal 4D lane line annotation data is the target 4D lane line annotation data that exceeds the target quality inspection operation represented by the target quality inspection operation result, and it is realized that the abnormal 4D lane line annotation data with labeling errors is determined according to the target quality inspection operation result, so as to perform secondary quality inspection on the abnormal 4D lane line annotation data.

[0096] Embodiment 4

[0097] Figure 5 This is a schematic diagram of the structure of a 4D lane line marking data quality inspection device provided in the fourth embodiment of the present invention. The embodiment of the present invention can be applied to the situation of quality inspection of 4D lane line marking data. The device can be implemented in the form of hardware and / or software, and can be configured in an electronic device that implements the 4D lane line marking data quality inspection method. Figure 5 As shown, the device comprises:

[0098] The first determination module 401 is used to obtain target point cloud data, and determine target 4D lane line annotation data according to the target point cloud data, the target point cloud data is the three-dimensional data of the target object of the vehicle in the driving scene, the target object includes at least a plurality of target lane lines, and the target 4D lane line annotation data is the 4D annotation data of the plurality of target lane lines, and the 4D annotation data is obtained by superimposing the three-dimensional data within a preset time range and then adding annotations;

[0099] The second determination module 402 is used to determine the target quality inspection operation result of the target 4D lane line annotation data. The target quality inspection operation result is the result obtained after performing the target quality inspection operation on the target 4D lane line annotation data. The target quality inspection operation includes: a jump quality inspection operation, a type quality inspection operation and a preset quality inspection operation. The jump quality inspection operation is used to check whether the smoothness of each annotated lane line meets the preset smoothness threshold. The annotated lane line is a lane line that represents the target lane line according to the target 4D lane line annotation data. The type quality inspection operation is used to check the annotation type of the target 4D lane line annotation data based on the intersection state between every two annotated lane lines. The preset quality inspection operation is used to check the specified annotation task. The annotation task is a task of performing quality inspection on the target 4D lane line annotation data within the same time range.

[0100] The third determination module 403 is used to determine abnormal 4D lane line marking data in the target 4D lane line marking data based on the target quality inspection operation result, where the abnormal 4D lane line marking data is the target 4D lane line marking data that exceeds the target quality inspection operation as indicated by the target quality inspection operation result.

[0101] Optionally, determining a target quality inspection operation result of the target 4D lane line annotation data includes:

[0102] Determine a target surface equation of the target 4D lane line annotation data, where the target surface equation is used to fit a drivable vehicle trajectory corresponding to the target 4D lane line annotation data;

[0103] Determine the Z-axis jitter tolerance value of the target 4D lane line annotation data, where the three dimensions of the target 4D lane line annotation data are the X-axis, the Y-axis, and the Z-axis. The Z-axis jitter tolerance value is used to check whether the smoothness of each annotated lane line on the Z-axis meets a preset smoothness threshold;

[0104] The jump quality inspection operation result of the target 4D lane line marking data is determined based on the target surface equation and the Z-axis jitter tolerance value.

[0105] Optionally, determining a target surface equation of target 4D lane line annotation data includes:

[0106] Determine the drivable trajectory of the vehicle corresponding to the target 4D lane line marking data according to the target point cloud data;

[0107] Segment the drivable trajectory of the vehicle according to the preset segmentation distance;

[0108] Determine the target plane equation corresponding to each segment of the vehicle's drivable trajectory;

[0109] The target surface equation is obtained by weighted summing of the target plane equations of each segment of the vehicle's drivable trajectory.

[0110] Optionally, determining a target quality inspection operation result of the target 4D lane line annotation data includes:

[0111] According to the target 4D lane line annotation data, several annotated lane lines are segmented to obtain several reference lane lines;

[0112] Determine the tangent vectors of several reference lane lines, where the tangent vector is a vector formed by mapping the reference lane line to two endpoints on a horizontal plane;

[0113] The jump quality inspection result of the target 4D lane line annotation data is determined according to the tangent vector.

[0114] Optionally, the jump quality inspection operation result of the target 4D lane line annotation data is determined according to the tangent vector, including:

[0115] Determine the vector angle between the tangent vectors of every two adjacent reference lane lines on each marked lane line;

[0116] Determine a preset vector angle threshold of the vector angle, where the preset vector angle threshold is used to check whether the smoothness of each marked lane line on the X-axis or the Y-axis meets the preset smoothness threshold;

[0117] The jump quality inspection operation result of the target 4D lane line annotation data is determined based on the vector angle and the preset vector angle threshold.

[0118] Optionally, determining a target quality inspection operation result of the target 4D lane line annotation data includes:

[0119] Determine the intersection state between every two marked lane lines among the plurality of marked lane lines;

[0120] The type quality inspection operation result of the target 4D lane line annotation data is determined according to the intersection status.

[0121] Optionally, determining a target quality inspection operation result of the target 4D lane line annotation data includes:

[0122] Determine the target quality inspection object in the labeling task, where the target quality inspection object is the object for quality inspection of the target 4D lane line labeling data;

[0123] Determine the reference configuration operations of the target quality inspection object, which include: target configuration, action configuration, condition configuration, and logical relationship configuration;

[0124] The preset quality inspection operation result of the target 4D lane line annotation data is determined according to the target quality inspection object and the reference configuration operation.

[0125] The technical solution of the embodiment of the present invention obtains target point cloud data and determines target 4D lane line annotation data based on the target point cloud data. The target point cloud data is the three-dimensional data of the target object of the vehicle in the driving scene. The target object includes at least a plurality of target lane lines. The target 4D lane line annotation data is the 4D annotation data of the plurality of target lane lines. The 4D annotation data is obtained by superimposing the three-dimensional data within a preset time range and then adding annotations, thereby realizing the acquisition of the target 4D lane line annotation data and providing actual data support for the subsequent quality inspection process; determining the target quality inspection operation result of the target 4D lane line annotation data. The target quality inspection operation result is the result obtained after performing the target quality inspection operation on the target 4D lane line annotation data. The target quality inspection operation includes: a jump quality inspection operation, a type quality inspection operation and a preset quality inspection operation. The jump quality inspection operation is used to check whether the smoothness of each annotated lane line meets the preset smoothness threshold. The annotated lane line is based on The target 4D lane line annotation data represents the lane line of the target lane line. The type quality inspection operation is used to inspect the annotation type of the target 4D lane line annotation data based on the intersection state between every two annotated lane lines. The preset quality inspection operation is used to inspect the specified annotation task. The annotation task is a task to perform quality inspection on the target 4D lane line annotation data belonging to the same time range. The target quality inspection operation is performed on the target 4D lane line annotation data, which improves the efficiency and accuracy of quality inspection on the target 4D lane line annotation data and reduces labor costs. The abnormal 4D lane line annotation data in the target 4D lane line annotation data is determined based on the target quality inspection operation result. The abnormal 4D lane line annotation data is the target 4D lane line annotation data that exceeds the target quality inspection operation represented by the target quality inspection operation result. The abnormal 4D lane line annotation data with annotation errors is determined according to the target quality inspection operation result, so as to facilitate secondary quality inspection of the abnormal 4D lane line annotation data.

[0126] The 4D lane line marking data quality inspection device provided in the embodiment of the present invention can execute the 4D lane line marking data quality inspection method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0127] Embodiment 5

[0128] Figure 6A schematic diagram of the structure of an electronic device for implementing a 4D lane line marking data quality inspection method provided in Example 5 of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) 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 invention described and / or required herein.

[0129] like Figure 6 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0130] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0131] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the 4D lane line marking data quality inspection method.

[0132] In some embodiments, the 4D lane marking data quality inspection method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the 4D lane marking data quality inspection method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the 4D lane marking data quality inspection method in any other appropriate manner (e.g., by means of firmware).

[0133] 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), load 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.

[0134] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program 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.

[0135] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. 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.

[0136] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device 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 a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0137] The systems and techniques described herein may 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 may 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), a blockchain network, and the Internet.

[0138] A computing 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 client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0139] 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 the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0140] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A 4D lane line marking data quality inspection method, characterized in that: The method comprises: Acquire target point cloud data, and determine target 4D lane line annotation data according to the target point cloud data, wherein the target point cloud data is three-dimensional data of a target object of a vehicle in a driving scene, wherein the target object includes at least a plurality of target lane lines, and the target 4D lane line annotation data is 4D annotation data of the plurality of target lane lines, wherein the 4D annotation data is obtained by superimposing three-dimensional data within a preset time range and then adding annotations; Determine a target quality inspection operation result of the target 4D lane line annotation data, the target quality inspection operation result is a result obtained after performing a target quality inspection operation on the target 4D lane line annotation data, the target quality inspection operation includes: a jump quality inspection operation, a type quality inspection operation and a preset quality inspection operation, the jump quality inspection operation is used to check whether the smoothness of each annotated lane line meets a preset smoothness threshold, the annotated lane line is a lane line that represents the target lane line according to the target 4D lane line annotation data, the type quality inspection operation is used to check the annotation type of the target 4D lane line annotation data based on the intersection state between every two of the annotated lane lines, and the preset quality inspection operation is used to check a specified annotation task, the annotation task is a task of performing quality inspection on the target 4D lane line annotation data belonging to the same time range; Abnormal 4D lane line marking data in the target 4D lane line marking data is determined based on the target quality inspection operation result, and the abnormal 4D lane line marking data is the target 4D lane line marking data that exceeds the target quality inspection operation indicated by the target quality inspection operation result.

2. The method according to claim 1, characterized in that Determining the target quality inspection operation result of the target 4D lane line annotation data includes: Determine a target surface equation of the target 4D lane line marking data, wherein the target surface equation is used to fit a drivable vehicle trajectory corresponding to the target 4D lane line marking data; Determine a Z-axis jitter tolerance value of the target 4D lane line annotation data, wherein the three dimensions of the target 4D lane line annotation data are respectively an X-axis, a Y-axis, and a Z-axis, and the Z-axis jitter tolerance value is used to check whether the smoothness of each of the annotated lane lines on the Z-axis meets a preset smoothness threshold; The jump quality inspection operation result of the target 4D lane line marking data is determined based on the target surface equation and the Z-axis jitter tolerance value.

3. The method according to claim 2, characterized in that Determining the target surface equation of the target 4D lane line annotation data includes: Determine a drivable vehicle trajectory corresponding to the target 4D lane line marking data according to the target point cloud data; Segmenting the drivable trajectory of the vehicle according to a preset segmentation distance; Determine the target plane equation corresponding to each segment of the vehicle's drivable trajectory; The target surface equation is obtained by weighted summing the target plane equations of each segment of the vehicle's drivable trajectory.

4. The method according to claim 1, characterized in that: Determining the target quality inspection operation result of the target 4D lane line annotation data includes: Segmenting a plurality of the annotated lane lines according to the target 4D lane line annotated data to obtain a plurality of reference lane line segments; Determine tangent vectors of several segments of the reference lane line, where the tangent vector is a vector formed by mapping the reference lane line to two endpoints on a horizontal plane; Determine a jump quality inspection operation result of the target 4D lane line annotation data according to the tangent vector.

5. The method according to claim 4, characterized in that Determining the jump quality inspection operation result of the target 4D lane line annotation data according to the tangent vector includes: Determine the vector angle between the tangent vectors of every two adjacent reference lane lines on each of the marked lane lines; Determine a preset vector angle threshold of the vector angle, wherein the preset vector angle threshold is used to check whether the smoothness of each of the marked lane lines on the X-axis or the Y-axis meets the preset smoothness threshold; A jump quality inspection operation result of the target 4D lane line marking data is determined based on the vector angle and the preset vector angle threshold.

6. The method according to claim 1, characterized in that Determining the target quality inspection operation result of the target 4D lane line annotation data includes: Determining an intersection state between every two of the plurality of marked lane lines; A type quality inspection result of the target 4D lane line marking data is determined according to the intersection state.

7. The method according to claim 1, characterized in that Determining the target quality inspection operation result of the target 4D lane line annotation data includes: Determine a target quality inspection object in the labeling task, where the target quality inspection object is an object when quality inspection is performed on the target 4D lane line labeling data; Determine a reference configuration operation of the target quality inspection object, wherein the reference configuration operation includes: target configuration, action configuration, condition configuration, and logical relationship configuration; A preset quality inspection operation result of the target 4D lane line marking data is determined according to the target quality inspection object and the reference configuration operation.

8. A 4D lane marking data quality inspection device, characterized in that: The device comprises: A first determination module is used to obtain target point cloud data, and determine target 4D lane line annotation data according to the target point cloud data, wherein the target point cloud data is three-dimensional data of a target object of a vehicle in a driving scene, wherein the target object includes at least a plurality of target lane lines, and the target 4D lane line annotation data is 4D annotation data of the plurality of target lane lines, wherein the 4D annotation data is obtained by superimposing the three-dimensional data within a preset time range and then adding annotations; A second determination module is used to determine a target quality inspection operation result of the target 4D lane line annotation data, the target quality inspection operation result is a result obtained after performing a target quality inspection operation on the target 4D lane line annotation data, the target quality inspection operation includes: a jump quality inspection operation, a type quality inspection operation and a preset quality inspection operation, the jump quality inspection operation is used to check whether the smoothness of each annotated lane line meets a preset smoothness threshold, the annotated lane line is a lane line that represents the target lane line according to the target 4D lane line annotation data, the type quality inspection operation is used to check the annotation type of the target 4D lane line annotation data based on the intersection state between every two annotated lane lines, and the preset quality inspection operation is used to check a specified annotation task, and the annotation task is a task of performing quality inspection on the target 4D lane line annotation data belonging to the same time range; The third determination module is used to determine abnormal 4D lane line marking data in the target 4D lane line marking data based on the target quality inspection operation result, and the abnormal 4D lane line marking data is the target 4D lane line marking data that exceeds the target quality inspection operation as indicated by the target quality inspection operation result.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the 4D lane line marking data quality inspection method described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the 4D lane line marking data quality inspection method according to any one of claims 1 to 7 when executed.

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