Method and device for evaluating lane line detection result, electronic equipment and storage medium

Abstract

The invention discloses a method and device for evaluating a lane line detection result, electronic equipment and a storage medium. The method comprises the following steps: acquiring a first detection result of a lane line through a truth value sensor in a vehicle driving process; wherein the truth value sensor comprises a camera and a laser radar; acquiring a second detection result of the lane line through the to-be-detected sensor; and evaluating the second detection result according to the first detection result. According to the embodiment of the invention, the method can achieve the evaluation of the detection result of the lane line through the combination of the camera and the laser radar, is more accurate in evaluation result, and can provide a reference for the rear-end planning and decision.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of intelligent driving technology, and in particular to a method, device, electronic device and storage medium for evaluating lane detection results. Background Art

[0002] With the rapid development of advanced driver assistance system technology, lane line detection is an important part of it, and its results provide important information reference for the back-end planning and decision-making modules. Functional modules such as lane departure warning, lane keeping assist, adaptive cruise, advanced cruise, and lever lane change all rely on continuous and stable lane line detection results. Lane lines are not only an important part of road traffic signs, but also the basis of vehicle navigation, path planning, and environmental perception. Therefore, accurate and stable lane line detection results are crucial to advanced driver assistance system technology, and how to evaluate lane line perception results has become an urgent task.

[0003] In the prior art, there are two types of lane line detection methods, one is lane line detection based on visual cameras, and the other is lane line detection based on laser radar. The camera is low-cost and is a passive sensor that can obtain complex environmental information around it at a high frame rate and high resolution. However, it does not emit light itself, and the imaging quality is greatly affected by the ambient brightness. It is difficult to complete the perception and detection task in harsh environments. The laser radar is expensive and is an active sensor that obtains the depth information of the target by emitting pulsed lasers and detecting the scattered light characteristics of the target. It has the characteristics of high precision, large range, and strong anti-interference ability. However, the point cloud obtained by the laser radar is sparse and disordered, making it difficult to use directly, and the monochromatic nature of the laser makes it impossible to obtain color and texture information. Summary of the invention

[0004] The present application provides a method, device, electronic device and storage medium for evaluating lane line detection results. The lane line detection results can be evaluated by combining a camera and a lidar. The evaluation results are more accurate, thereby providing a reference for back-end planning and decision-making.

[0005] In a first aspect, an embodiment of the present application provides a method for evaluating lane line detection results, the method comprising:

[0006] During the driving process of the vehicle, a first detection result of the lane line is obtained through a true value sensor; wherein the true value sensor includes: a camera and a laser radar;

[0007] Acquire a second detection result of the lane line by the sensor to be tested;

[0008] The second detection result is evaluated according to the first detection result.

[0009] In a second aspect, an embodiment of the present application further provides a device for evaluating lane line detection results, the device comprising: a first detection module, a second detection module and an evaluation module; wherein,

[0010] The first detection module is used to obtain a first detection result of the lane line through a true value sensor during the vehicle driving process; wherein the true value sensor includes: a camera and a laser radar;

[0011] The second detection module is used to obtain a second detection result of the lane line through the sensor to be tested;

[0012] The evaluation module is used to evaluate the second detection result according to the first detection result.

[0013] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0014] one or more processors;

[0015] a memory for storing one or more programs,

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for evaluating lane line detection results described in any embodiment of the present application.

[0017] In a fourth aspect, an embodiment of the present application provides a storage medium on which a computer program is stored, and when the program is executed by a processor, the method for evaluating lane line detection results described in any embodiment of the present application is implemented.

[0018] The embodiment of the present application proposes a method, device, electronic device and storage medium for evaluating lane line detection results. During the driving process of the vehicle, the first detection result of the lane line is first obtained by the true value sensor; then the second detection result of the lane line is obtained by the sensor to be tested; and then the second detection result is evaluated according to the first detection result. That is to say, in the technical solution of the present application, the first detection result of the lane line can be obtained by the camera and the laser radar, and the second detection result obtained by the sensor to be tested can be evaluated according to the first detection result. In the prior art, the method based on the visual camera is greatly affected by the ambient brightness, and it is difficult to complete the perception detection task in a harsh environment; the point cloud obtained by the laser radar method is sparse and disordered, and it is difficult to use directly, and the monochromatic characteristics of the laser make it impossible to obtain color and texture information. Therefore, compared with the prior art, the method, device, electronic device and storage medium for evaluating lane line detection results proposed in the embodiment of the present application can evaluate the detection results of the lane line by combining the camera and the laser radar, and the evaluation results are more accurate, so as to provide a reference for the back-end planning and decision-making; and the technical solution of the embodiment of the present application is simple and convenient to implement, easy to popularize, and has a wider range of application. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flowchart of a method for evaluating lane detection results provided in an embodiment of the present application;

[0020] Figure 2 A flowchart of a method for evaluating lane detection results provided by another embodiment of the present application;

[0021] Figure 3 A flowchart of a method for evaluating lane detection results provided in yet another embodiment of the present application;

[0022] Figure 4 A schematic diagram of the evaluation results provided in one embodiment of the present application;

[0023] Figure 5 A schematic diagram of the structure of a device for evaluating lane detection results provided in an embodiment of the present application;

[0024] Figure 6 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0025] The present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for ease of description, only the parts related to the present application, rather than all structures, are shown in the accompanying drawings.

[0026] Figure 1 This is a flow chart of a method for evaluating lane line detection results provided in an embodiment of the present application. The method can be performed by a device or electronic device for evaluating lane line detection results. The device or electronic device can be implemented in software and / or hardware. The device or electronic device can be integrated in any smart device with network communication function. Figure 1 As shown, the method for evaluating lane line detection results may include the following steps:

[0027] S101. During vehicle driving, obtain a first detection result of a lane line through a true value sensor; wherein the true value sensor includes: a camera and a laser radar.

[0028] In this step, the first original data and the second original data detected for the lane line can be collected by the camera and the laser radar respectively; then the first detection result is determined according to the first original data and the second original data. The cameras in the embodiment of the present application may include: a left front perimeter camera, a left rear perimeter camera, a right front perimeter camera, a right rear perimeter camera, a front narrow-angle camera, and a front wide-angle camera; wherein the front narrow-angle camera and the front wide-angle camera can be set in the center area of ​​the vehicle; in addition, the laser radar can also be set in the center area of ​​the vehicle.

[0029] S102: Obtain a second detection result of the lane line through the sensor to be tested.

[0030] In this step, the original data to be tested detected for the lane line can be collected by the sensor to be tested; and then the second detection result output by the domain control is obtained according to the original data to be tested.

[0031] S103: Evaluate the second detection result according to the first detection result.

[0032] In this step, the degree of deviation of the second test result compared to the first test result can be calculated; if the degree of deviation of the second test result compared to the first test result is too large, it can be determined that the second test result is unqualified.

[0033] The method for evaluating the lane line detection result proposed in the embodiment of the present application, during the vehicle driving process, first obtains the first detection result of the lane line through the true value sensor; then obtains the second detection result of the lane line through the sensor to be tested; and then evaluates the second detection result according to the first detection result. That is to say, in the technical solution of the present application, the first detection result of the lane line can be obtained by the camera and the laser radar, and the second detection result obtained by the sensor to be tested can be evaluated according to the first detection result. In the prior art, the method based on the visual camera is greatly affected by the ambient brightness, and it is difficult to complete the perception detection task in a harsh environment; the point cloud obtained by the laser radar method is sparse and disordered, and it is difficult to use directly, and the monochromatic characteristics of the laser make it impossible to obtain color and texture information. Therefore, compared with the prior art, the method for evaluating the lane line detection result proposed in the embodiment of the present application can evaluate the lane line detection result by combining the camera and the laser radar, and the evaluation result is more accurate, so as to provide a reference for the back-end planning and decision-making; and the technical solution of the embodiment of the present application is simple and convenient to implement, easy to popularize, and has a wider range of application.

[0034] Figure 2 A flowchart of a method for evaluating lane detection results provided in another embodiment of the present application. The above technical solution is further optimized and expanded, and can be combined with the above optional implementations. Figure 2 As shown, the method for evaluating lane line detection results may include the following steps:

[0035] S201. During vehicle driving, first original data and second original data detected for lane lines are collected by a camera and a laser radar respectively.

[0036] In this step, the first raw data detected for the lane line is collected by the camera, which may include the following operations: 1) Install the camera: install the camera at an appropriate position of the vehicle, such as the center of the front windshield or the roof, to ensure that the road conditions ahead can be captured. 2) Calibrate the camera: calibrate the parameters of the camera, including focal length, aperture size, image resolution, etc., to ensure that the image quality meets the requirements. 3) Data acquisition: use the camera to continuously capture the video stream of the road ahead. These video frames are the first raw data, which contain visual features such as the color and shape of the lane line. 4) Storage and transmission: store the collected data locally or transmit it to the processing unit through the network for subsequent processing. In addition, the second raw data detected for the lane line is collected by the laser radar, which may include the following operations: 1) Install the laser radar: install the laser radar on the vehicle and select a position that can cover the road ahead and detect the lane line. 2) Calibrate the laser radar: adjust the angle and position of the laser radar to ensure that it accurately measures the target distance. 3) Data acquisition: use the laser radar to scan the road ahead and collect point cloud data. These point cloud data reflect the distance information of various objects on the road, including the position of the lane line. 4) Storage and transmission: The point cloud data collected by the lidar also needs to be stored or transmitted to the processing unit for further analysis.

[0037] S202: Determine a first detection result according to the first original data and the second original data.

[0038] In this step, the first raw data and the second raw data may be preprocessed respectively to obtain the preprocessed first reference data and the second reference data; then the 2D anchor frame and the 3D anchor frame of the lane line are obtained in the first reference data and the second reference data respectively; and the 2D anchor frame is fitted into the 3D anchor frame to obtain the first detection result. The preprocessing in the embodiment of the present application may include: cleaning, parsing, slicing and alignment. The 2D anchor frame in the embodiment of the present application refers to a rectangular frame used to surround the target object (such as the lane line) in a two-dimensional image; the 3D anchor frame refers to a cuboid or other polygonal frame used to represent the position, size and direction of the target object in three-dimensional space. Obtaining the 2D anchor frame from the first reference data (camera data) may include the following operations: 1) Image preprocessing: preprocessing the image captured by the camera, such as adjusting the contrast, brightness, removing noise, etc. 2) Feature extraction: using a convolutional neural network (CNN) or other image processing methods to extract features in the image. 3) Lane line detection: using the trained model to detect the lane line and output a bounding box (bounding boxes), i.e., a 2D anchor frame. 4) Post-processing: Post-process the detection results, such as non-maximum suppression (NMS), to improve detection accuracy. In addition, obtaining a 3D anchor frame from the second reference data (lidar data) may include the following operations: 1) Point cloud preprocessing: Filtering, denoising, and other processing are performed on the point cloud data captured by the lidar to better extract useful information. 2) Feature extraction: Feature extraction is performed on the point cloud data, which may include height features, density features, etc. 3) Lane line detection: Use a model trained with point cloud data to detect lane lines, and output a 3D anchor frame containing the lane line position, size, and orientation. 4) Coordinate conversion: Since the data provided by the lidar is a point cloud in three-dimensional space, it needs to be converted into a format suitable for the 3D detection model.

[0039] S203 , collecting the raw data to be tested detected for the lane line through the sensor to be tested.

[0040] S204: Obtain a second detection result output by the domain controller according to the original data to be tested.

[0041] In this step, the original data to be tested may be sent to a background server, and the background server processes the original data to be tested to output a second test result.

[0042] S205: Evaluate the second detection result according to the first detection result.

[0043] The method for evaluating the lane line detection result proposed in the embodiment of the present application, during the vehicle driving process, first obtains the first detection result of the lane line through the true value sensor; then obtains the second detection result of the lane line through the sensor to be tested; and then evaluates the second detection result according to the first detection result. That is to say, in the technical solution of the present application, the first detection result of the lane line can be obtained by the camera and the laser radar, and the second detection result obtained by the sensor to be tested can be evaluated according to the first detection result. In the prior art, the method based on the visual camera is greatly affected by the ambient brightness, and it is difficult to complete the perception detection task in a harsh environment; the point cloud obtained by the laser radar method is sparse and disordered, and it is difficult to use directly, and the monochromatic characteristics of the laser make it impossible to obtain color and texture information. Therefore, compared with the prior art, the method for evaluating the lane line detection result proposed in the embodiment of the present application can evaluate the lane line detection result by combining the camera and the laser radar, and the evaluation result is more accurate, so as to provide a reference for the back-end planning and decision-making; and the technical solution of the embodiment of the present application is simple and convenient to implement, easy to popularize, and has a wider range of application.

[0044] Figure 3 A flowchart of a method for evaluating lane detection results provided in another embodiment of the present application. The above technical solution is further optimized and expanded, and can be combined with the above optional implementation methods. Figure 3 As shown, the method for evaluating lane line detection results may include the following steps:

[0045] S301. During the driving of the vehicle, first original data and second original data detected for the lane line are collected by a camera and a laser radar respectively.

[0046] S302 , preprocess the first original data and the second original data respectively to obtain preprocessed first reference data and second reference data.

[0047] S303 , respectively obtaining a 2D anchor frame and a 3D anchor frame of the lane line from the first reference data and the second reference data.

[0048] S304: Fit the 2D anchor frame into the 3D anchor frame to obtain a first detection result.

[0049] In this step, the following operations may be included: 1) 2D anchor frame detection: Use camera images to detect 2D anchor frames of lane lines or other targets. 2) Depth information acquisition: Obtain depth information of the target from lidar or other depth perception sensors. 3) 2D to 3D mapping: Use camera internal and external parameters to map the 2D anchor frame to 3D space. 4) 3D anchor frame estimation: Estimate the position, size and direction of the 3D anchor frame based on the mapping results. 5) Fusion of multi-sensor data: If there is multi-sensor data, perform data fusion to improve accuracy. 6) Result output: Output the final 3D anchor frame as the first detection result.

[0050] S305 , collecting the raw data detected for the lane line through the sensor to be tested.

[0051] S306: Obtain a second detection result output by the domain controller according to the original data to be tested.

[0052] S307: Calculate the degree of deviation of the second detection result compared with the first detection result.

[0053] The offset index in the embodiment of the present application may include: position offset, size offset, direction offset and shape offset. In order to comprehensively evaluate the offset degree between two detection results, the offset degrees of the above various aspects may be combined. For example, a comprehensive score may be calculated, or a weight may be set according to a specific application to evaluate the importance of the offset degree.

[0054] S308: If the deviation of the second test result from the first test result is too large, determine that the second test result is unqualified.

[0055] Figure 4 This is a schematic diagram of the evaluation results provided by an embodiment of the present application. Figure 4 As shown in the figure, the green dotted line is the first detection result, the blue dotted line is the second detection result, and the green solid line is the lane centerline. By fitting the first detection result with the second detection result, we can get Figure 4 From Figure 4 It can be clearly seen that the first detection result is closest to the actual road lane line (white dotted line), while the second detection result has a significant deviation.

[0056] The method for evaluating the lane line detection result proposed in the embodiment of the present application, during the vehicle driving process, first obtains the first detection result of the lane line through the true value sensor; then obtains the second detection result of the lane line through the sensor to be tested; and then evaluates the second detection result according to the first detection result. That is to say, in the technical solution of the present application, the first detection result of the lane line can be obtained by the camera and the laser radar, and the second detection result obtained by the sensor to be tested can be evaluated according to the first detection result. In the prior art, the method based on the visual camera is greatly affected by the ambient brightness, and it is difficult to complete the perception detection task in a harsh environment; the point cloud obtained by the laser radar method is sparse and disordered, and it is difficult to use directly, and the monochromatic characteristics of the laser make it impossible to obtain color and texture information. Therefore, compared with the prior art, the method for evaluating the lane line detection result proposed in the embodiment of the present application can evaluate the lane line detection result by combining the camera and the laser radar, and the evaluation result is more accurate, so as to provide a reference for the back-end planning and decision-making; and the technical solution of the embodiment of the present application is simple and convenient to implement, easy to popularize, and has a wider range of application.

[0057] Figure 5 A schematic diagram of the structure of a device for evaluating lane line detection results provided in an embodiment of the present application. Figure 5 As shown, the device for evaluating lane line detection results includes: a first detection module 501, a second detection module 502 and an evaluation module 503; wherein,

[0058] The first detection module 501 is used to obtain a first detection result of a lane line through a true value sensor during vehicle driving; wherein the true value sensor includes: a camera and a laser radar;

[0059] The second detection module 502 is used to obtain a second detection result of the lane line through the sensor to be tested;

[0060] The evaluation module 503 is used to evaluate the second detection result according to the first detection result.

[0061] The above-mentioned device for evaluating lane line detection results can execute the method provided by any embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not fully described in this embodiment, please refer to the method for evaluating lane line detection results provided by any embodiment of the present application.

[0062] Figure 6 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application. Figure 6 A block diagram of an exemplary electronic device suitable for implementing the embodiments of the present application is shown. Figure 6The electronic device 12 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0063] like Figure 6 As shown, the electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0064] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0065] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0066] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 6 not shown, usually called a "hard drive"). Although Figure 6 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical medium) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present application.

[0067] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in the memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0068] The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), may communicate with one or more devices that enable a user to interact with the electronic device 12, and / or may communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via the bus 18. It should be understood that although Figure 6 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0069] The processing unit 16 executes various functional applications and data processing by running the programs stored in the system memory 28, such as implementing the method for evaluating lane detection results provided in the embodiment of the present application.

[0070] The embodiment of the present application also provides a computer storage medium.

[0071] The computer-readable storage medium of the embodiment of the present application can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, - but not limited to - a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive lists) of computer-readable storage media include: an electrical connection with one or more wires, 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 above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, a device or a device or used in combination with it.

[0072] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0073] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0074] Computer program code for performing the operation of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0075] The embodiment of the present application also provides a computer program product.

[0076] Various embodiments 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 embodiments can include: being implemented in one or more computer program products, which can include one or more computer programs, which 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, which 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] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A method for evaluating lane detection results, characterized in that: The method comprises: During the driving process of the vehicle, a first detection result of the lane line is obtained through a true value sensor; wherein the true value sensor includes: a camera and a laser radar; Acquire a second detection result of the lane line by the sensor to be tested; The second detection result is evaluated according to the first detection result.

2. The method according to claim 1, characterized in that: The first detection result of the lane line is obtained by the true value sensor, including: Collecting first original data and second original data detected for the lane line through a camera and a laser radar respectively; The first detection result is determined according to the first original data and the second original data.

3. The method according to claim 2, characterized in that Determining the first detection result according to the first original data and the second original data includes: Preprocessing the first original data and the second original data respectively to obtain preprocessed first reference data and second reference data; Acquire a 2D anchor frame and a 3D anchor frame of the lane line in the first reference data and the second reference data respectively; The 2D anchor frame is fitted into the 3D anchor frame to obtain the first detection result.

4. The method according to claim 3, characterized in that Acquiring a 2D anchor frame and a 3D anchor frame of the lane line in the first reference data and the second reference data respectively includes: extracting a first lane line feature and a second lane line feature from the first reference data and the second reference data respectively; The first lane line feature and the second lane line feature are aligned, and a 2D anchor frame and a 3D anchor frame of the lane line are respectively obtained based on the aligned first lane line feature and the second lane line feature.

5. The method according to claim 4, characterized in that The method further comprises: The 3D anchor frame of the lane line is converted into a world coordinate system, and the pose of the 2D anchor frame of the lane line is optimized based on the converted 3D anchor frame.

6. The method according to claim 1, characterized in that Acquiring a second detection result of the lane line by the sensor to be tested includes: Collecting the raw data to be tested detected for the lane line by the sensor to be tested; The second detection result output by the domain control is obtained according to the original data to be tested.

7. The method according to claim 1, characterized in that Evaluating the second detection result according to the first detection result includes: Calculating the degree of deviation of the second detection result compared to the first detection result; If the deviation degree of the second detection result is too large compared with the first detection result, it is determined that the second detection result is unqualified.

8. A device for evaluating lane line detection results, characterized in that: The device comprises: a first detection module, a second detection module and an evaluation module; wherein, The first detection module is used to obtain a first detection result of the lane line through a true value sensor during the vehicle driving process; wherein the true value sensor includes: a camera and a laser radar; The second detection module is used to obtain a second detection result of the lane line through the sensor to be tested; The evaluation module is used to evaluate the second detection result according to the first detection result.

9. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method for evaluating lane line detection results as described in any one of claims 1 to 7.

10. A storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for evaluating lane line detection results as described in any one of claims 1 to 7 is implemented.

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