Abnormal matching diagnosis and processing method and system in matching and positioning system

Abstract

The present invention provides a method and system for diagnosing and processing abnormal matching in a matching and positioning system. The method utilizes historical valid information and matching process information stored in the internal operation process of a multi-source fusion positioning system based on high-precision map matching to calculate the consistency between the current frame map and the camera-perceived scene, establish a tracking relationship for abnormal matching data with poor consistency, determine the matching credibility of the abnormal matching data again, and finally screen the data with normal matching, that is, the data with continuous and stable tracking results is output as the optimal solution, and establish key node information; at the same time, the area with a tracking inspection result of a map abnormality in the matching abnormality is marked, which, on the one hand, assists in map verification and updating, and on the other hand, serves as matching and positioning prior information to assist in improving the positioning stability of the corresponding abnormal area.

Description

Technical Field

[0001] The present invention relates to the field of intelligent driving positioning, and more specifically, to an abnormal matching diagnosis and processing method and system in a matching and positioning system. Background Art

[0002] The multi-source fusion positioning system based on vision and high-precision map matching relies on the assistance of high-precision maps. After the high-precision map is produced, there will be various phenomena that are inconsistent with the real scene due to changes in the external environment (such as road repairs, etc.); during the real-time positioning process, the visual camera will also produce abnormal perception output due to some special external environments. Conventional matching positioning is not able to resist abnormalities in high-precision maps and camera data. The inconsistency between map data and actual roads or abnormal camera perception will bring a series of uncertainty errors to the multi-source fusion positioning system. Summary of the invention

[0003] The present invention aims at the technical problems existing in the prior art and provides a method and system for diagnosing and processing abnormal matching in a matching and positioning system.

[0004] According to a first aspect of the present invention, a method for diagnosing and processing abnormal matching in a matching and positioning system is provided, comprising:

[0005] Calculate the confidence of the camera's current perception data based on the camera's current perception data and the camera's historical observation information, historical matching information, historical positioning and status information;

[0006] If the confidence level is normal, the current perception data of the camera is matched with the corresponding map data in the high-precision map as matching pair data, and the consistency between the map data and the current perception data of the camera is calculated;

[0007] If the consistency is good, the matching pair data is in a normal matching state; if the consistency is poor, the matching pair data is a matching abnormality suspected data pair, for which a tracking relationship of the matching abnormality suspected data pair is established, and a matching credible state of the matching abnormality suspected data pair is calculated based on the tracking relationship;

[0008] Determine the matching state of the matching abnormality suspect data pair based on the matching trustworthy state, wherein the matching state includes a matching normal state and a matching abnormal state;

[0009] The key node information is established and saved for the matching pair data matching the normal state, and the map abnormal area in the matching pair data matching the abnormal state is output.

[0010] Based on the above technical solution, the present invention can also make the following improvements.

[0011] Optionally, the step of calculating the confidence of the camera's current perception data according to the camera's current perception data and the camera's historical observation information, historical matching information, historical positioning and status information also includes:

[0012] Perform multi-information fusion through the matching positioning system to obtain the current position information of the matching positioning system;

[0013] According to the current position information of the matching positioning system, the coordinate transformation of the current perception data of the camera is performed, and the current perception data of the camera under the vehicle system is transformed into the geographic coordinate system.

[0014] Optionally, the performing multi-information fusion through the matching positioning system to obtain the current position information of the matching positioning system includes:

[0015] The matching positioning system performs multi-source information fusion based on the measurement information of the inertial measurement unit IMU, the positioning information of the global satellite positioning system GNSS, the vehicle wheel speed, and the historical matching correction information, and outputs the current position information of the matching positioning system.

[0016] Optionally, if the confidence is normal, the current perception data of the camera is matched with the corresponding map data in the high-precision map as matching pair data, and the consistency between the map data and the current perception data of the camera is calculated, including:

[0017] When the confidence level is greater than a set confidence level threshold, the confidence level is normal, and the current perception data of the camera is matched with the corresponding map data in the high-precision map as matching pair data;

[0018] In the matching process, the historical storage information and the historical matching process information are combined to calculate the consistency between the map data and the current perception data of the camera to obtain the consistency coefficient.

[0019] Optionally, the historical storage information includes historically stored map information, historically stored camera information and historically stored key node information, the key node information includes matching pair data of a normal matching state, and the historical matching process data includes historical matching position correction amount, historical matching confidence, historical matching fitting coefficient and historical matching verification status.

[0020] Optionally, when the consistency coefficient is greater than a set threshold, the consistency is good; otherwise, the consistency is poor;

[0021] Establishing a tracking relationship of the matching abnormality suspected data pair, and calculating the matching trustworthy state of the matching abnormality suspected data pair according to the tracking relationship, including:

[0022] Based on the historical storage information and the historical matching process information, the matching abnormality suspected data pair is tracked, and the state coefficient and quality coefficient of the matching abnormality suspected data pair are calculated according to the tracking relationship;

[0023] Based on the state coefficient and the quality coefficient, the matching confidence state of the matching abnormality suspect data pair is determined.

[0024] Optionally, determining the matching trustworthy state of the matching abnormality suspect data pair based on the state coefficient and the quality coefficient includes:

[0025] When the state coefficient is greater than or equal to a first set threshold and the quality coefficient is greater than or equal to a second set threshold, the matching credibility state of the matching abnormality suspected data pair is credible;

[0026] If the state coefficient is less than the first set threshold or the quality coefficient is less than the second set threshold, the matching credibility state of the matching abnormality suspected data pair is untrustworthy;

[0027] Wherein, when the matching credible state of the matching abnormality suspected data pair is credible, the matching abnormality suspected data pair is in a matching normal state;

[0028] When the matching credible state of the matching abnormality suspected data pair is untrustworthy, the matching abnormality suspected data pair is in a matching abnormal state.

[0029] According to a second aspect of the present invention, there is provided an abnormal matching diagnosis and processing system in a matching and positioning system, comprising:

[0030] A first calculation module is used to calculate the confidence of the camera's current perception data based on the camera's current perception data and the camera's historical observation information, historical matching information, historical positioning and status information;

[0031] A second calculation module is used for matching the current perception data of the camera with the corresponding map data in the high-precision map as matching pair data if the confidence is normal, and calculating the consistency between the map data and the current perception data of the camera;

[0032] A third calculation module is used for, if the consistency is good, the matching pair data is in a normal matching state; if the consistency is poor, the matching pair data is a matching abnormality suspected data pair, for the matching abnormality suspected data pair, establishing a tracking relationship of the matching abnormality suspected data pair, and calculating the matching credible state of the matching abnormality suspected data pair according to the tracking relationship;

[0033] A determination module, configured to determine a matching state of the matching abnormality suspect data pair based on the matching trustworthy state, wherein the matching state includes a matching normal state and a matching abnormal state;

[0034] The establishment module is used to establish key node information for matching pair data of a normal state and save it, and output the map abnormal area in the matching pair data of an abnormal state.

[0035] According to a third aspect of the present invention, there is provided an electronic device comprising a memory and a processor, wherein the processor is configured to implement the steps of an abnormal matching diagnosis and processing method in a matching and positioning system when executing a computer management program stored in the memory.

[0036] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium on which a computer management program is stored. When the computer management program is executed by a processor, the steps of the abnormal matching diagnosis and processing method in the matching and positioning system are implemented.

[0037] The present invention provides a method and system for diagnosing and processing abnormal matching in a matching and positioning system. The method utilizes historical valid information and matching process information stored in the internal operation process of a multi-source fusion positioning system based on high-precision map matching to calculate the consistency between the current frame map and the camera-perceived scene, establish a tracking relationship for abnormal matching data with poor consistency, determine the matching credibility of the abnormal matching data again, and finally filter out the data with normal matching, that is, the data with continuous and stable tracking results is output as the optimal solution, and establish key node information; at the same time, the area with map abnormality as the tracking inspection result in the matching abnormality is marked, which not only assists in map verification and updating, but also serves as matching and positioning prior information to assist in improving the positioning stability of the corresponding abnormal area. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A flow chart of an abnormal matching diagnosis and processing method in a matching and positioning system provided by the present invention;

[0039] Figure 2 A schematic diagram of the structure of an abnormal matching diagnosis and processing system in a matching and positioning system provided by the present invention;

[0040] Figure 3 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention;

[0041] Figure 4 A schematic diagram of the hardware structure of a possible computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions 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 part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In addition, the technical features in the various embodiments or single embodiments provided by the present invention can be arbitrarily combined with each other to form a feasible technical solution. This combination is not subject to the constraints of the sequence of steps and / or the structural composition mode, but must be based on the ability of ordinary technicians in this field to achieve. When the combination of technical solutions is contradictory or cannot be achieved, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0043] Conventional matching positioning is not able to resist anomalies in high-precision maps and camera data. The inconsistency between map data and actual roads or camera perception anomalies will bring a series of uncertainty errors to the multi-source fusion positioning system. The present invention embodies a method for diagnosing and processing abnormal matching in a matching positioning system, which uses the historical valid information and matching process information stored in the internal operation process of the multi-source fusion positioning system based on high-precision map matching to calculate the consistency between the current frame map and the camera perception scene, establish a tracking relationship for abnormal matching data with poor consistency, and finally select continuous and stable tracking results as the optimal solution output; at the same time, the areas where the tracking inspection results in the matching anomaly are map anomalies are marked, which, on the one hand, assists in map verification and updating, and on the other hand, serves as matching positioning prior information to assist in improving the positioning stability of the corresponding abnormal area.

[0044] Figure 1 A flow chart of an abnormal matching diagnosis method in a matching and positioning system provided by the present invention is shown as follows: Figure 1 As shown, the abnormal matching diagnosis and processing method includes:

[0045] S1, calculates the confidence of the camera's current perception data based on the camera's current perception data and the camera's historical observation information, historical matching information, historical positioning and status information.

[0046] As an embodiment, the confidence of the camera's current perception data is calculated based on the camera's current perception data and the camera's historical observation information, historical matching information, historical positioning and status information, and also includes: performing multi-information fusion through a matching and positioning system to obtain the current position information of the matching and positioning system; performing coordinate transformation on the camera's current perception data based on the matching and positioning system's current position information, and transforming the camera's current perception data under the vehicle system into the geographic coordinate system.

[0047] It can be understood that when the matching positioning system is powered on, the matching positioning system performs multi-source fusion based on the measurement information of the IMU (Inertial Measurement Unit), such as the vehicle's heading, wheel steering and other information, the positioning information measured by the GNSS (Global Navigation Satellite System), wheel speed, and historical matching correction information, and outputs information such as the system's current position.

[0048] According to the current position information of the system, the coordinate transformation is performed on the current output element information of the camera (hereinafter referred to as the current perception data of the camera), and the current perception data of the camera under the vehicle system is converted to the geographic coordinate system.

[0049] Then, the confidence of the camera's current perception data is calculated based on the camera's historical observation information, historical matching information, historical positioning and status information.

[0050] S2: If the confidence level is normal, the current perception data of the camera is matched with the corresponding map data in the high-precision map as matching pair data, and the consistency between the map data and the current perception data of the camera is calculated.

[0051] As an embodiment, if the confidence level is normal, the camera's current perception data and the corresponding map data in the high-precision map are matched as matching pair data, and the consistency of the map data and the camera's current perception data is calculated, including: when the confidence level is greater than the set confidence level threshold, the confidence level is normal, and the camera's current perception data and the corresponding map data in the high-precision map are matched as matching pair data; in the matching process, the historical storage information and the historical matching process information are combined to calculate the consistency of the map data and the camera's current perception data to obtain a consistency coefficient.

[0052] It is understandable that the above step S1 calculates the confidence of the camera's current perception data. If the confidence is greater than the set threshold, it means that the camera's current perception data is credible, otherwise, the camera's current perception data is not credible. If the camera's current perception data is credible, the camera's current perception data is matched with the corresponding map data, and the consistency of the map data and the camera's current perception data is calculated. Among them, the matched camera perception data and map data constitute matching pair data. In the matching process, the consistency of the map data and the camera's current perception data is calculated in combination with the historical storage information and the historical matching process information to obtain the consistency coefficient.

[0053] Among them, the historical storage information mainly includes historically stored map information, historically stored camera information and historically stored key node information. The key node information mainly includes matching pair data of normal matching status. The historical matching process data includes historical matching position correction amount, historical matching confidence, historical matching fitting coefficient and historical matching verification status.

[0054] S3, if the consistency is good, the matching pair data is in a normal matching state; if the consistency is poor, the matching pair data is a matching abnormality suspected data pair, for which a tracking relationship is established, and the matching credible state of the matching abnormality suspected data pair is calculated based on the tracking relationship.

[0055] As an example, when the consistency coefficient is greater than or equal to the set threshold, the consistency is good, which means that the current camera perception data in the matching pair data matches the map data, and the matching state of the matching data pair is set to a normal matching state. Otherwise, if the consistency coefficient is less than the set threshold, the consistency is poor, and the matching pair data is a suspected abnormal matching data pair. At this time, it cannot be determined whether the matching data pair cannot be matched, but it is suspected that it cannot be matched, which is called a suspected abnormal matching data pair.

[0056] For matching anomaly suspected data pairs, a tracking relationship for the matching anomaly suspected data pairs is established, and the matching trustworthy state of the matching anomaly suspected data pairs is calculated based on the tracking relationship, including: tracking the matching anomaly suspected data pairs based on historical storage information and the historical matching process information, and calculating the state coefficient and quality coefficient of the matching anomaly suspected data pairs based on the tracking relationship; determining the matching trustworthy state of the matching anomaly suspected data pairs based on the state coefficient and the quality coefficient.

[0057] It can be understood that, for the matching anomaly suspected data pairs, fitting and smoothing are performed according to the historical matching position correction amount, the historical matching confidence, the historical matching fitting coefficient, and the historical matching verification status, and the matching anomaly suspected data pairs are tracked according to the historically stored map information, the historically stored camera information, the historically stored key node information and other information, and the state coefficient and quality coefficient of the matching anomaly suspected data pairs are calculated, and based on the state coefficient and the quality coefficient, the matching credibility state of the matching anomaly suspected data pairs is determined.

[0058] Specifically, based on the state coefficient and the quality coefficient, the matching trust state of the matching anomaly suspected data pair is determined, including: when the state coefficient is greater than or equal to a first set threshold and the quality coefficient is greater than or equal to a second set threshold, the matching trust state of the matching anomaly suspected data pair is trustworthy; if the state coefficient is less than the first set threshold or the quality coefficient is less than the second set threshold, the matching trust state of the matching anomaly suspected data pair is untrustworthy.

[0059] S4, determining a matching state of the matching abnormality suspected data pair based on the matching trust state, wherein the matching state includes a matching normal state and a matching abnormal state.

[0060] It is understandable that when the matching credible state of the matching abnormal suspect data pair is credible, the matching abnormal suspect data pair is in a matching normal state; when the matching credible state of the matching abnormal suspect data pair is untrustworthy, the matching abnormal suspect data pair is in a matching abnormal state.

[0061] S5, establishing key node information for the matching pair data matching the normal state and saving it, and outputting the map abnormal area in the matching pair data matching the abnormal state.

[0062] It is understandable that the matching data of the normal state is stored in the key node array, and the key node array stores historical key node information, and the key node information includes the matching data pairs of the normal state. Finally, the map abnormal area in the matching abnormal data pair is output.

[0063] The present invention evaluates and cross-verifies the quality of high-precision maps and camera perception data, constructs key nodes for matching results with good consistency, assists in tracking and calculating the state coefficients and quality coefficients of abnormal matching results, avoids uncertainty errors in positioning results caused by camera and high-precision map anomalies, and simultaneously improves the timeliness of map anomaly updates by assisting in map area output.

[0064] See also Figure 2 , is a matching abnormality diagnosis and processing system in a matching positioning system of the present invention, the system comprises a first calculation module 201, a second calculation module 202, a third calculation module 203, a determination module 204 and an establishment module 205, wherein:

[0065] A first calculation module 201 is used to calculate the confidence of the camera's current perception data based on the camera's current perception data and the camera's historical observation information, historical matching information, historical positioning and status information;

[0066] A second calculation module 202 is used for matching the current perception data of the camera with the corresponding map data in the high-precision map as matching pair data if the confidence is normal, and calculating the consistency between the map data and the current perception data of the camera;

[0067] The third calculation module 203 is used for, if the consistency is good, the matching pair data is in a normal matching state; if the consistency is poor, the matching pair data is a matching abnormality suspected data pair, for the matching abnormality suspected data pair, establishing a tracking relationship of the matching abnormality suspected data pair, and calculating the matching credible state of the matching abnormality suspected data pair according to the tracking relationship;

[0068] A determination module 204, configured to determine a matching state of the matching abnormality suspect data pair based on the matching trustworthy state, wherein the matching state includes a matching normal state and a matching abnormal state;

[0069] The establishing module 205 is used to establish key node information for the matching pair data of the normal matching state and save it, and output the map abnormal area in the matching pair data of the abnormal matching state.

[0070] It can be understood that the matching abnormality diagnosis and processing system in the matching and positioning system provided by the present invention corresponds to the matching abnormality diagnosis and processing method in the matching and positioning system provided by the aforementioned embodiments. The relevant technical features of the matching abnormality diagnosis and processing system in the matching and positioning system can refer to the relevant technical features of the matching abnormality diagnosis and processing method in the matching and positioning system, which will not be repeated here.

[0071] See also Figure 3 , Figure 3 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, an embodiment of the present invention provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the computer program 311, the steps of the matching abnormality diagnosis and processing method in the matching positioning system are implemented.

[0072] See also Figure 4 , Figure 4 Schematic diagram of an embodiment of a computer-readable storage medium provided by the present invention. Figure 4 As shown, this embodiment provides a computer-readable storage medium 400 on which a computer program 411 is stored. When the computer program 411 is executed by a processor, the steps of the matching abnormality diagnosis and processing method in the matching and positioning system are implemented.

[0073] The embodiment of the present invention provides a matching anomaly diagnosis and processing method and system in a matching positioning system. The method uses the historical valid information and matching process information stored in the internal operation process of a multi-source fusion positioning system based on high-precision map matching to calculate the consistency between the current frame map and the camera-perceived scene, establish a tracking relationship for abnormal matching data with poor consistency, and finally screen out continuous and stable tracking results as the optimal solution output; at the same time, the area in the matching anomaly where the tracking inspection result is a map anomaly is output to assist in map verification and updating and matching area constraints, and to assist in improving the positioning stability of the map anomaly area.

[0074] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0075] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0076] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0077] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0078] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0079] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0080] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for diagnosing and processing abnormal matching in a matching and positioning system, characterized in that: include: Calculate the confidence of the camera's current perception data based on the camera's current perception data and the camera's historical observation information, historical matching information, historical positioning and status information; If the confidence level is normal, the current perception data of the camera is matched with the corresponding map data in the high-precision map as matching pair data, and the consistency between the map data and the current perception data of the camera is calculated; If the consistency is good, the matching pair data is in a normal matching state; if the consistency is poor, the matching pair data is a matching abnormality suspected data pair, for which a tracking relationship of the matching abnormality suspected data pair is established, and a matching credible state of the matching abnormality suspected data pair is calculated based on the tracking relationship; Determine the matching state of the matching abnormality suspect data pair based on the matching trustworthy state, wherein the matching state includes a matching normal state and a matching abnormal state; The key node information is established and saved for the matching pair data matching the normal state, and the map abnormal area in the matching pair data matching the abnormal state is output.

2. The abnormal matching diagnosis and processing method according to claim 1, characterized in that: The confidence level of the camera's current perception data is calculated based on the camera's current perception data and the camera's historical observation information, historical matching information, historical positioning and status information, and the like, and the confidence level of the camera's current perception data is also ... historical observation information, historical matching information, historical positioning Perform multi-information fusion through the matching positioning system to obtain the current position information of the matching positioning system; According to the current position information of the matching positioning system, the coordinate transformation of the current perception data of the camera is performed, and the current perception data of the camera under the vehicle system is transformed into the geographic coordinate system.

3. The abnormal matching diagnosis and processing method according to claim 2, characterized in that: The performing multi-information fusion through the matching positioning system to obtain the current position information of the matching positioning system includes: The matching positioning system performs multi-source information fusion based on the measurement information of the inertial measurement unit IMU, the positioning information of the global satellite positioning system GNSS, the vehicle wheel speed, and the historical matching correction information, and outputs the current position information of the matching positioning system.

4. The abnormal matching diagnosis and processing method according to claim 1, characterized in that: If the confidence is normal, the current perception data of the camera is matched with the corresponding map data in the high-precision map as matching pair data, and the consistency between the map data and the current perception data of the camera is calculated, including: When the confidence level is greater than a set confidence level threshold, the confidence level is normal, and the current perception data of the camera is matched with the corresponding map data in the high-precision map as matching pair data; In the matching process, the historical storage information and the historical matching process information are combined to calculate the consistency between the map data and the current perception data of the camera to obtain the consistency coefficient.

5. The abnormal matching diagnosis and processing method according to claim 4, characterized in that: The historical storage information includes historically stored map information, historically stored camera information and historically stored key node information, the key node information includes matching pair data of a normal matching state, and the historical matching process data includes historical matching position correction amount, historical matching confidence, historical matching fitting coefficient and historical matching verification status.

6. The abnormal matching diagnosis and processing method according to claim 5, characterized in that: When the consistency coefficient is greater than a set threshold, the consistency is good; Otherwise, the consistency is poor; Establishing a tracking relationship of the matching abnormality suspected data pair, and calculating the matching trustworthy state of the matching abnormality suspected data pair according to the tracking relationship, including: Based on the historical storage information and the historical matching process information, the matching abnormality suspected data pair is tracked, and the state coefficient and quality coefficient of the matching abnormality suspected data pair are calculated according to the tracking relationship; Based on the state coefficient and the quality coefficient, the matching confidence state of the matching abnormality suspect data pair is determined.

7. The abnormal matching diagnosis and processing method according to claim 6, characterized in that: Determining the matching trustworthy state of the matching abnormality suspect data pair based on the state coefficient and the quality coefficient includes: When the state coefficient is greater than or equal to a first set threshold and the quality coefficient is greater than or equal to a second set threshold, the matching credibility state of the matching abnormality suspected data pair is credible; If the state coefficient is less than the first set threshold or the quality coefficient is less than the second set threshold, the matching credibility state of the matching abnormality suspected data pair is untrustworthy; Wherein, when the matching credible state of the matching abnormality suspected data pair is credible, the matching abnormality suspected data pair is in a matching normal state; When the matching credible state of the matching abnormality suspected data pair is untrustworthy, the matching abnormality suspected data pair is in a matching abnormal state.

8. A system for diagnosing and processing abnormal matching in a matching and positioning system, characterized in that: include: A first calculation module is used to calculate the confidence of the camera's current perception data based on the camera's current perception data and the camera's historical observation information, historical matching information, historical positioning and status information; A second calculation module is used for matching the current perception data of the camera with the corresponding map data in the high-precision map as matching pair data if the confidence is normal, and calculating the consistency between the map data and the current perception data of the camera; A third calculation module is used for, if the consistency is good, the matching pair data is in a normal matching state; if the consistency is poor, the matching pair data is a matching abnormality suspected data pair, for the matching abnormality suspected data pair, establishing a tracking relationship of the matching abnormality suspected data pair, and calculating the matching credible state of the matching abnormality suspected data pair according to the tracking relationship; A determination module, configured to determine a matching state of the matching abnormality suspect data pair based on the matching trustworthy state, wherein the matching state includes a matching normal state and a matching abnormal state; The establishment module is used to establish key node information and save the matching pair data in the normal matching state.

9. An electronic device, characterized in that: It includes a memory and a processor, and the processor is used to implement the steps of the abnormal matching diagnosis and processing method in the matching and positioning system as described in any one of claims 1 to 7 when executing the computer management program stored in the memory.

10. A computer-readable storage medium, characterized in that: A computer management program is stored thereon, and when the computer management program is executed by the processor, the steps of the abnormal matching diagnosis and processing method in the matching and positioning system as described in any one of claims 1 to 7 are implemented.

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