Method, apparatus, device, and storage medium for processing height data of high-precision map

Abstract

The present application provides a method, apparatus, device, and storage medium for processing altitude data of a high-precision map. Among them, the method includes: obtaining the identification ID of a target object in the high-precision map and the OID value carried by the identification ID, where the target object includes road traffic facilities; converting the target object into a linear object and obtaining the original altitude of each shape point in the linear object; determining the fuzzy altitude of each shape point respectively based on the OID value of the target object and the original altitude of each shape point, and generating the fuzzy altitude data of the target object based on the fuzzy altitude of each shape point. Through the above method, the consistency of the deviation of each fuzziness of the same target object in the high-precision map is effectively improved, achieving the purpose of enhancing the usage effect of the high-precision map by users.

Description

Technical Field

[0001] This application relates to the technical field of high-precision maps, and particularly to a method, device, equipment and storage medium for processing height data of high-precision maps. Background Art

[0002] With the development of intelligent driving technology, intelligent driving vehicles rely on high-precision maps for positioning and planning, and have a strong dependence on high-precision maps.

[0003] When high-precision maps are actually produced, they need to be inspected for compliance. Among them, the true height of high-precision map objects (such as poles, signs) cannot be directly expressed, but a certain percentage of error needs to be added to make the high-precision map data compliant. Currently, a common method is to add a random error to the original height of the objects in the high-precision map, and the high-precision map data obtained by users is the true height ± random error.

[0004] However, by adding random errors, it may occur that the height of the same object in the high-precision map data obtained by users is different each time, which affects the use effect of the high-precision map; and when performing differential updates, a large amount of data needs to be updated repeatedly, resulting in an increase in the amount of updated data and affecting the terminal use experience; and in the case of multiple heights for objects such as guardrails and walls, using random errors will also cause deformation problems for individual linear objects. Summary of the Invention

[0005] This application provides a method, device, equipment and storage medium for processing height data of high-precision maps to at least solve one of the above technical problems.

[0006] According to one aspect of this application, a method for processing height data of high-precision maps is provided, including:

[0007] Obtain the identification ID of the target object in the high-precision map and the OID value carried by the identification ID, where the target object includes road traffic facilities;

[0008] Convert the target object into a linear object, and obtain the original height of each shape point in the linear object;

[0009] Based on the OID value of the target object and the original height of each shape point, determine the fuzzy height of each shape point respectively, and generate the fuzzy height data of the target object based on the fuzzy height of each shape point.

[0010] In an implementation manner, the converting the target object into a linear object includes:

[0011] Obtain the point cloud data and / or image data of the target object; and, determine the edge geometry of the target object based on the point cloud data and / or image data to obtain a linear object.

[0012] In one implementation, after obtaining the identification ID of the target object in the high-precision map and the OID value carried by the identification ID, it further includes:

[0013] Encrypt the OID value based on the hash digest algorithm to obtain an OID encrypted value;

[0014] The determining the fuzzy height of each shape point based on the OID value of the target object and the original height of each shape point includes: determining the fuzzy height of each shape point based on the OID encrypted value and the original height of each shape point.

[0015] In one implementation, the encrypting the OID value based on the hash digest algorithm includes:

[0016] Perform hash encoding on the OID value based on the hash digest algorithm, and replace the characters other than numbers in the encoding result with any numbers to obtain an OID encrypted value.

[0017] In one implementation, the method further includes: obtaining the minimum error value for the fuzzy processing of height data;

[0018] The determining the fuzzy height of each shape point based on the OID value of the target object and the original height of each shape point includes:

[0019] Normalize the OID value so that the normalized OID value ranges from [-1, 1]; and, determine the fuzzy height of each shape point based on the normalized OID value, the original height of each shape point, and the minimum error value.

[0020] In one implementation, the determining the fuzzy height of each shape point based on the normalized OID value, the original height of each shape point, and the minimum error value includes:

[0021] Determine the fuzziness of each shape point based on the product of the normalized OID value, the original height of each shape point, and the minimum error value;

[0022] Determine the fuzzy height of each shape point based on the height of each shape point and its corresponding fuzziness.

[0023] In one implementation, after generating the fuzzy height data of the target object based on the fuzzy height of each shape point, it further includes:

[0024] When the data compliance review requirements for the fuzzy height data are met, generate high-precision map data based on the fuzzy height data of the target object, and transmit the high-precision map data to the target user terminal.

[0025] According to another aspect of the present application, there is provided a device for processing height data of a high-precision map, including:

[0026] A first acquisition module configured to acquire the identification ID of a target object in the high-precision map and the OID value carried by the identification ID, where the target object includes road facilities;

[0027] A second acquisition module configured to acquire the linear object corresponding to the target object and acquire the original height of each shape point in the linear object;

[0028] A data processing module configured to determine the fuzzy height of each shape point based on the OID value of the target object and the original height of each shape point, and generate fuzzy height data of the target object based on the fuzzy height of each shape point.

[0029] In one embodiment, the second acquisition module includes:

[0030] A data acquisition unit configured to acquire the point cloud data and / or image data of the target object; and a determination unit configured to determine the edge geometry of the target object based on the point cloud data and / or image data to obtain a linear object.

[0031] In one embodiment, the device further includes:

[0032] An encryption module configured to encrypt the OID value based on a hash digest algorithm to obtain an OID encrypted value;

[0033] The data processing module includes: a height determination unit configured to determine the fuzzy height of each shape point based on the OID encrypted value and the original height of each shape point.

[0034] In one embodiment, the encryption module is specifically configured to perform hash encoding on the OID value based on a hash digest algorithm, and replace the characters other than numbers in the encoding result with arbitrary numbers to obtain an OID encrypted value.

[0035] In one embodiment, the device further includes: a minimum error acquisition module configured to acquire the minimum error value for the fuzzy processing of height data;

[0036] The height determination unit includes: a normalization subunit configured to normalize the OID value so that the normalized OID value ranges from -1 to 1; and a determination subunit configured to determine the fuzzy height of each shape point based on the normalized OID value, the original height of each shape point, and the minimum error value.

[0037] In one embodiment, the determination subunit is specifically configured to determine the fuzziness of each shape point based on the product of the normalized OID value and the difference between the original height of each shape point and the minimum error value; and determine the fuzzy height of each shape point based on the height of each shape point and its corresponding fuzziness.

[0038] In one embodiment, the device further includes:

[0039] A data generation and transmission module configured to generate high-precision map data based on the fuzzy height data of the target object and transmit the high-precision map data to the target user terminal when the fuzzy height data meets the data compliance review requirements.

[0040] According to another aspect of the present application, there is provided an electronic device including: a processor, and a memory communicatively connected to the processor;

[0041] The memory stores computer-executable instructions;

[0042] The processor executes the computer-executable instructions stored in the memory to implement the method for processing height data of the high-precision map.

[0043] According to still another aspect of the present application, there is provided a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the method for processing height data of the high-precision map.

[0044] According to still another aspect of the present application, there is provided a computer program product including a computer program that, when executed by a processor, implements the method for processing height data of the high-precision map.

[0045] The method, apparatus, device, and storage medium for processing height data of a high-precision map provided by this application obtain the identification ID of a target object in the high-precision map and the OID value carried by the identification ID, where the target object includes road traffic facilities; convert the target object into a linear object, and obtain the original height of each shape point in the linear object; determine the fuzzy height of each shape point based on the OID value of the target object and the original height of each shape point, and generate the fuzzy height data of the target object based on the fuzzy height of each shape point. In this process, by obtaining the identification ID of the target object and using the determined OID value to perform fuzzy processing on the height of each shape point in the target object, the consistency of the deviation of each fuzzy operation of the same target object can be effectively guaranteed. When performing differential updates, there is no need to repeatedly update a large amount of data. At the same time, the deformation problem of a single linear object caused by using random errors is well solved, effectively improving the usage effect of the user's high-precision map. Moreover, using the OID value to perform fuzzy processing on the height of each shape point effectively reduces the possibility of reverse calculating the original height of the target object, improving the drawing review security in the high-precision map data. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application.

[0047] Figure 1 A possible schematic diagram of a scenario provided by an embodiment of this application;

[0048] Figure 2 A flowchart of a method for processing height data of a high-precision map provided by an embodiment of this application;

[0049] Figure 3a One of the schematic diagrams of a linear object in an embodiment of this application;

[0050] Figure 3b Another schematic diagram of a linear object in an embodiment of this application;

[0051] Figure 3c Another schematic diagram of a linear object in an embodiment of this application;

[0052] Figure 4 A flowchart of another method for processing height data of a high-precision map provided by an embodiment of this application;

[0053] Figure 5a One of the flowcharts of yet another method for processing height data of a high-precision map provided by an embodiment of this application;

[0054] Figure 5bIt is the second flowchart of another method for processing altitude data of a high-precision map provided by an embodiment of the present application;

[0055] Figure 6 It is a schematic structural diagram of a device for processing altitude data of a high-precision map provided by an embodiment of the present application;

[0056] Figure 7 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application;

[0057] Figure 8 It is a block diagram of a terminal device provided by an exemplary embodiment of the present application.

[0058] Through the above-mentioned drawings, specific embodiments of the present application have been shown, and more detailed descriptions will be provided later. These drawings and textual descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. Specific Embodiments

[0059] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0060] The embodiments of the present application will be explained below in combination with an application scenario. The method for processing altitude data of a high-precision map provided by the embodiments of the present application can be applied to the application scenario of intelligent driving. More specifically, it can be applied to the application scenario of autonomous driving based on vehicle cloud computing. Exemplarily, the execution subject of the method provided by the embodiments of the present application can be a server. More specifically, for example, it is the server of the high-precision map producer. The following will introduce the method provided by the embodiments of the present application with the server as the execution subject.

[0061] Figure 1 It is a schematic diagram of a method for processing altitude data of a high-precision map provided by an embodiment of the present application. As Figure 1 shown, there is a network connection between the server 110 and the intelligent vehicle 120. The server 110 generates high-precision map data and transmits the high-precision map data to the intelligent vehicle 120, and the intelligent vehicle 120 can use the high-precision map data to assist in autonomous driving. Among them, the server 110 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, and cloud computing.

[0062] Optionally, the server 110 is also connected to the terminal device 130 through a network. The terminal device 130 is used to collect the height data of objects (such as poles, signs, guardrails, etc., taking guardrails as an example in this embodiment) in the high-precision map. The terminal device 130 can be various sensors, such as cameras, lidar, etc. The terminal device 130 uses the camera to capture the image data of the guardrail and / or uses lidar to collect the point cloud data of the guardrail. The three-dimensional object is converted into a linear object according to the image data and / or point cloud data of the guardrail, and then the height data of the linear object is blurred. In some implementation manners, the terminal device 130 can also be a driving vehicle, and sensors such as cameras and lidar are installed on the driving vehicle to collect the corresponding image data and point cloud data by using the driving vehicle.

[0063] In the related art, for the height data of the high-precision map object collected in the above process, height blurring is usually performed by adding a random error. For example, if the original height of the object is a, the random error is randomly selected between 2% and 5%. When the high-precision map data is produced, the height of the object is a±(2% - 5%). However, by adding a random error, it may occur that the height of the same object in the high-precision map data obtained by the user is different each time, affecting the use effect of the high-precision map; and when performing differential updates, a large amount of data needs to be updated repeatedly, resulting in an increase in the amount of updated data and affecting the terminal use experience; and in the case where there are multiple heights for linear objects such as guardrails and walls, using a random error will also cause the deformation problem of a single linear object. If a fixed error, such as 2%, is used, the original height can be calculated inversely in the user terminal after generating the blurred height data, which does not meet the requirements of the high-precision map review compliance.

[0064] The technical solution of the present application and how the technical solution of the present application solves the above technical problems will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that these specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0065] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or fully authorized by all parties. The collection, use, and processing of relevant data need to comply with relevant laws, regulations, and standards, and corresponding operation entrances are provided for the user to choose to authorize or refuse.

[0066] Figure 2 is a flowchart of the method for processing the height data of the high-precision map provided by the embodiment of the present application. The execution subject of this embodiment can be the server 110, as Figure 2As shown in the figure, the method for processing height data of a high-precision map provided in this embodiment includes steps S201 - S203.

[0067] Step S201: Obtain the identification ID of the target object in the high-precision map and the OID value carried by the identification ID, where the target object includes road traffic facilities.

[0068] In this embodiment, the target object, that is, the object in the high-precision map that needs to be processed for height data, is road traffic facilities such as poles, signs, guardrails, and gantries.

[0069] Among them, each target object has an identification ID and a unique object ID value (i.e., OID value), and the OID value is determined and unchanged. The identification ID and the corresponding OID value can be generated and stored in the database by relevant institutions or platforms during the road construction process. In some embodiments, the server can also assign a unique identification ID and the corresponding OID value to each target object. This embodiment does not specifically limit the generation method of the identification ID and OID value of the target object.

[0070] It can be understood that the types of high-precision map objects include: poles, signs, guardrails, gantries, ground markings, etc. Among them, the pole type includes lamp poles, base station poles, camera poles, poles attached to traffic signs, etc. In this embodiment, the target objects are road traffic facilities such as poles, signs, guardrails, and gantries, which have height parameters. When generating high-precision map data, the corresponding height parameters need to be blurred. For objects such as ground markings that do not have height parameters, they may not be included in the target objects.

[0071] Step S202: Convert the target object into a linear object, and obtain the original height of each shape point in the linear object.

[0072] Taking the guardrail of the road as an example for illustration, to improve the efficiency of obtaining and processing the height of the guardrail, in this embodiment, the three-dimensional object guardrail is first converted into a linear object. When obtaining the guardrail height data, by obtaining the height data of each shape point of the guardrail, it is possible to perform blurring processing on each shape point in the subsequent steps, which can effectively ensure the consistency between the guardrail in the finally generated high-precision map data and the shape of the guardrail in reality, with only a height deviation. In addition, based on the blurred height calculated for each shape point, it is possible to effectively prevent the user side from inversely calculating the real height of the guardrail. Among them, the original height of each shape point can be obtained through the three-dimensional coordinate values of each shape point.

[0073] In one implementation manner, in step S202, converting the target object into a linear object can determine the edge geometry through point cloud data and / or image data to convert the target object into a linear object, which includes three methods, specifically as follows:

[0074] Method 1: Obtain the point cloud data of the target object; and, based on the point cloud data and determine the edge geometry of the target object, obtain a linear object.

[0075] In one implementation, a lidar can be used to collect the point cloud data of the guardrail, and preprocess the point cloud data (such as removing redundant data), and use a point cloud contour extraction algorithm to determine the edge geometry of the guardrail, and the corresponding edge geometry is the linear object of the guardrail.

[0076] Among them, the point cloud contour extraction algorithm is illustrated by taking the concave point mining algorithm based on the convex hull as an example. First, extract the convex hull of the point cloud, and then calculate the point density sorting of the vertices of each side of the convex hull. If the vertex point density is greater than X times the length of the side where it is located (X can be adaptively set), then delete the side, and select a point that satisfies the largest included angle from the internal points, insert it into the boundary edge, and form two new boundary edges. Iterate the above steps until X times of all boundary edges is less than the point density of their endpoints, and the algorithm ends to determine the corresponding edge geometry.

[0077] Method 2: Obtain the image data of the target object; and, based on the point image data, determine the edge geometry of the target object, and obtain a linear object.

[0078] In one implementation, it is possible to imagine collecting the image data of the guardrail. Taking the guardrail picture as an example, use drawing software to draw the edge geometry corresponding to the guardrail in the picture.

[0079] Method 3: Obtain the point cloud data and image data of the target object; and, based on the point cloud data and image data, determine the edge geometry of the target object, and obtain a linear object.

[0080] This method combines the point cloud data of Method 1 and the image data of Method 2 to determine the edge geometry of the guardrail, which can effectively improve the accuracy of the linear object of the guardrail. This method can effectively compensate for the error problems caused by data loss or data ambiguity in the above methods. In one implementation, the corresponding edge geometry can be generated based on the picture data and the point cloud data respectively, and the final linear object is determined by matching the edge geometry. The matching process can select one of them according to the clarity and integrity of the corresponding data in the area where the edge geometry is different, or use the average distance method to determine. In other implementations, other methods can also be used to determine the edge geometry based on the picture data and the point cloud data. For example, first generate the edge geometry based on the point cloud data. In the case where there is a lack of point cloud data or the data is redundant and unclear in some areas of the guardrail, the edge determined by the corresponding picture data is used to replace this area, and the two are combined to determine the final edge geometry.

[0081] Step S203: Determine the fuzzy height of each shape point based on the OID value of the target object and the original height of each shape point, and generate the fuzzy height data of the target object based on the fuzzy height of each shape point.

[0082] The following is combined with Figures 3a - 3c as shown to illustrate the acquisition of the original height of each shape point in the linear object and the height fuzzy processing of each shape point, as Figure 3a is the linear object corresponding to the guardrail obtained from the point cloud data and / or camera data of the target object, with the road as a reference, Figure 3b where p1, p2, …, pn are the coordinate values of 1 to n shape points, and z1, z2, …, zn correspond to the original height of each shape point, Figure 3c where p1, p2, …, pn represent the coordinate values of each shape point after height fuzzy processing, and zs1, zs2, …, zsn correspond to the fuzzy height of each shape point.

[0083] In one implementation, the OID value can be encrypted, and then the fuzzy height of the shape point can be calculated using the encrypted OID value and the original height to improve the security of the introduced OID value, thereby improving the security of the high-precision map data review.

[0084] In this embodiment, the determined OID value is introduced to perform fuzzy processing on the height of each shape point. Since the OID value of the target object is stable and unchanged, when performing height fuzzy processing on the target object, the deviation of each fuzzy is also consistent. The height of the same object in the high-precision map data obtained by the user is also unchanged. During differential update, there is no need to repeat the update of a large amount of data. At the same time, it well solves the deformation problem of a single linear object caused by random errors, effectively improving the use effect of the user's high-precision map. In addition, using the OID value to perform fuzzy processing on the height of each shape point effectively avoids reverse calculation to obtain the original height of the target object. Moreover, the fuzzy height of the target object in this embodiment is generated based on the fuzzy height of each shape point, which can effectively ensure the consistency between the guardrail in the finally generated high-precision map data and the shape of the guardrail in reality, with only a height deviation, making the high-precision map data more in line with the actual situation.

[0085] Please refer to Figure 4 , Figure 4It is a schematic flowchart of another method for processing height data of a high-precision map provided by an embodiment of the present application. On the basis of the above content, in this embodiment, the OID is encrypted by using a hash digest algorithm, and the obtained OID encrypted value is irreversible. It is difficult to reverse-calculate the original height before blurring from the result after generating the height blur data, which further improves the security of map review for high-precision map data. Specifically, in addition to the above steps S201 - S203, after obtaining the identification ID of the target object in the high-precision map and the OID value carried by the identification ID in step S201, step S401 may further be included, and step S203 is further divided into step S203a.

[0086] Step S401: Encrypt the OID value based on the hash digest algorithm to obtain an OID encrypted value.

[0087] It can be understood that the hash digest algorithm is also known as the hash algorithm or the digest algorithm. It calculates a fixed-length output digest for any set of input data, and its operation result is irreversible. Through the hash function, an "array fingerprint" (hash value) can be created for the data. The hash value is usually a short string composed of random letters and numbers.

[0088] It should be noted that step S401 in this embodiment is performed after step S202. In some embodiments, step S401 may also be performed after step S201 and before step S202. This embodiment does not specifically limit the specific execution order of step S401.

[0089] Specifically, step S401 encrypting the OID value based on the hash digest algorithm may include the following steps:

[0090] Perform hash encoding on the OID value based on the hash digest algorithm, and replace the characters other than numbers in the encoding result with any numbers to obtain an OID encrypted value.

[0091] Step S203a: Determine the blurred height of each shape point based on the OID encrypted value and the original height of each shape point, and generate the blurred height data of the target object based on the blurred height of each shape point.

[0092] In this embodiment, taking the OID of the target object as 6678945 as an example, the OID value is hash-coded. Taking MD5 16-bit as an example, MD5(OID) = DA815E629A221C13. Then, the encoded content is digitized, and the characters other than numbers in the encoding result are replaced with arbitrary numbers, for example, all are replaced with 1, and the positive and negative values of MD5(OID) can be taken (for example, the first single digit is taken as positive and the double digit is taken as negative). In this example, the digitized encoding result MD5(OID)_num = 1181516291221113.

[0093] Further, to reduce the amount of computation, MD5(OID)_num can be normalized and then input into step S203a to perform blurring processing on the original height.

[0094] In one implementation manner, the method may further include the following error: obtaining the minimum error value for the blurring processing of the height data.

[0095] It can be understood that the minimum error value can be determined by an authoritative institution and can be a certain ratio. In the related art, the height data is mainly blurred by generating a random error based on this minimum error value.

[0096] Specifically, step S203 of determining the blurred height of each shape point based on the OID value of the target object and the original height of each shape point may include the following steps:

[0097] Normalize the OID value so that the normalized OID value ranges from [-1, 1]; and, based on the normalized OID value, the original height of each shape point, and the minimum error value, determine the blurred height of each shape point.

[0098] In this embodiment, taking the above-mentioned OID encrypted value after hash encryption as an example, (OID)_num is normalized to obtain the normalized OID encrypted value SeedValue = 1181516291221113 / 9999999999999999 = 0.1181516291221113. Then, based on the normalized OID value, the original height of each shape point, and the minimum error value, determine the blurred height of each shape point.

[0099] In this process, the original height of the shape point is blurred based on the minimum error value, so that the blurred height data can meet the minimum error, ensure that the data used at the user end meets the height compliance requirements of the high-precision map, and effectively reduce the amount of computation at the same time.

[0100] Further, the fuzzy height of the shape points is obtained by first determining the fuzziness of the shape points, so as to facilitate the fuzzy processing of the height. Specifically, the steps of determining the fuzzy height of each shape point based on the normalized OID value, the original height of each shape point, and the minimum error value may include the following steps:

[0101] Determine the fuzziness of each shape point based on the product of the normalized OID value, the original height of each shape point, and the minimum error value;

[0102] Determine the fuzzy height of each shape point based on the height of each shape point and its corresponding fuzziness.

[0103] In one implementation, the above-mentioned determination of the fuzzy height of each shape point can be obtained through the following formula (1):

[0104] H Shift = H + H * E + SeedValue

[0105] In the formula, H Shift represents the fuzzy height of a certain shape point, H represents the original height of the shape point, E represents the minimum error value, and SeeValue represents the normalized OID encrypted value. Among them, (H * E + SeedValue) is the fuzziness of the shape point. In some examples, the fuzziness can also be determined in other ways according to the product of the OID (encrypted) value, the original height of each shape point, and the minimum error value. For example In this formula, abs represents the absolute function, and the specific determination method of the fuzziness in this embodiment is not specifically limited.

[0106] It can be seen from the above formula (1) that the fuzzy height of the shape points calculated in this embodiment introduces a fixed encryption error value on the basis of the minimum error, which can ensure that the increased error remains stable and unchanged when the ID does not change, and can maintain irreversibility. Usually, the user side cannot reverse-calculate the original height of the target object from the fuzzy height data.

[0107] Please refer to Figure 5a , Figure 5a which is one of the schematic flowcharts of another method for processing height data of a high-precision map provided by the embodiment of the present application. On the basis of the above content, this embodiment uses the fuzzy height data of the target object to generate high-precision map data and transmits it to the target user terminal for use, improving the user's experience of using the high-precision map. Specifically, in addition to the above steps S201 - S203, after generating the fuzzy height data of the target object based on the fuzzy height of each shape point in step S203, step S501 is further included.

[0108] Step S501: When the fuzzy height data meets the data compliance review requirements for map drawing, generate high-precision map data based on the fuzzy height data of the target object, and transmit the high-precision map data to the target user terminal.

[0109] In this embodiment, the data compliance detection of the fuzzy height data can be performed in the server. The server stores the corresponding data compliance review requirements in advance. The review requirements can be the height error requirements for high-precision maps determined by an authoritative institution. By detecting whether the fuzzy height data of the target object meets the review requirements, if it meets the review requirements, it indicates that the data is compliant, and high-precision map data is generated based on the fuzzy height data of the target object.

[0110] In some embodiments, the server can also transmit the fuzzy height data to other third-party devices for data compliance detection, then obtain the corresponding detection results, and decide whether to generate high-precision map data according to whether the fuzzy height data meets the data compliance review requirements.

[0111] In practical applications, the height data of multiple target objects in the high-precision map can be blurred and processed simultaneously to quickly generate high-precision map data.

[0112] In some embodiments, to further ensure the data compliance of the high-precision map data, after generating the high-precision map data, all target objects in the high-precision map data can be detected again to check whether all target objects have been height-blurred and the blurring process meets the corresponding data compliance review requirements. After the detection passes, the high-precision map data is transmitted to the target user terminal for application. Among them, the target user terminal can be Figure 1 An intelligent vehicle in an application scenario.

[0113] For the convenience of understanding this technical solution, as shown in Figure 5b, Figure 5b This is the second flowchart of the method for processing the height data of another high-precision map provided by the embodiment of the present application.

[0114] It can be understood that the production process of high-precision maps mainly includes processes such as field data collection, indoor data editing and entry, product conversion, and data compliance review. The generation of linear objects in this embodiment is mainly achieved in the field data collection and indoor data editing and entry stages, and the processing of height data is mainly reflected in the product conversion link of high-precision map data. Taking the guardrail of a road as an example for illustration.

[0115] In the field data collection link, collect the photographic data and point cloud data of the guardrail;

[0116] In the in - house editing and inputting stage, obtain the photographic data and point cloud data collected in the field survey stage, and generate a linear object corresponding to the guardrail based on the photographic data and point cloud data. At the same time, the three - dimensional coordinates of each shape point in the linear object can be recorded;

[0117] In the output conversion stage, first obtain the OID = 6678945 corresponding to the linear object, and perform a hash encoding on the OID value. Taking MD5 16 - bit as an example, MD5(OID)=DA815E629A221C13. Then digitize the encoded content, replace the characters other than numbers in the encoding result with any number, for example, replace all with 1, and the MD5(OID) can be taken as positive or negative (for example, take the first digit as positive if it is odd and negative if it is even). In this example, the digitized encoding result MD5(OID)_num = 1181516291221113. Then perform a normalization process on it to get SeedValue = 1181516291221113 / 9999999999999999 = 0.1181516291221113. Then calculate the fuzzy height of each shape point according to SeedValue, and perform data output according to the calculation result;

[0118] In the data compliance map review stage, detect whether the heights of all target objects in the high - precision map are all blurred. If they are all blurred, further perform data compliance detection on the fuzzy heights of each target object. When the detection passes, transmit the high - precision map data to the target user terminal. At this time, the high - precision map data obtained by the user terminal is data that meets the requirements of data compliance detection, realizing the auxiliary function of the high - precision map data in vehicle driving, and it is difficult to perform reverse calculation to obtain the real height of the objects in the high - precision map.

[0119] Please refer to Figure 6 , Figure 6 FIG. is a schematic structural diagram of a height data processing device for a high - precision map provided by an embodiment of the present application, including a first acquisition module 61, a second acquisition module 62, and a data processing module 63, where,

[0120] The first acquisition module 61 is configured to acquire the identification ID of the target object in the high - precision map and the OID value carried by the identification ID, and the target object includes road facilities;

[0121] The second acquisition module 62 is configured to acquire the linear object corresponding to the target object and acquire the original height of each shape point in the linear object;

[0122] A data processing module 63, configured to determine the fuzzy height of each shape point based on the OID value of the target object and the original height of each shape point, and generate fuzzy height data of the target object based on the fuzzy height of each shape point.

[0123] In one embodiment, the second acquisition module 62 includes:

[0124] A data acquisition unit, configured to acquire point cloud data and / or image data of the target object; and a determination unit, configured to determine the edge geometry of the target object based on the point cloud data and / or image data to obtain a linear object.

[0125] In one embodiment, the device further includes:

[0126] An encryption module, configured to encrypt the OID value based on a hash digest algorithm to obtain an OID encrypted value;

[0127] The data processing module 63 includes: a height determination unit, configured to determine the fuzzy height of each shape point based on the OID encrypted value and the original height of each shape point.

[0128] In one embodiment, the encryption module is specifically configured to perform hash encoding on the OID value based on a hash digest algorithm, and replace the characters other than numbers in the encoding result with arbitrary numbers to obtain an OID encrypted value.

[0129] In one embodiment, the device further includes: a minimum error acquisition module, configured to acquire a minimum error value for fuzzy processing of height data;

[0130] The height determination unit includes: a normalization subunit, configured to normalize the OID value so that the normalized OID value ranges from [-1, 1]; and a determination subunit, configured to determine the fuzzy height of each shape point based on the normalized OID value, the original height of each shape point, and the minimum error value.

[0131] In one embodiment, the determination subunit is specifically configured to determine the fuzziness of each shape point based on the product of the normalized OID value, the original height of each shape point, and the minimum error value; and determine the fuzzy height of each shape point based on the height of each shape point and its corresponding fuzziness.

[0132] In one embodiment, the device further includes:

[0133] A data generation and transmission module, which is configured to generate high-precision map data based on the fuzzy height data of the target object and transmit the high-precision map data to the target user terminal when the data compliance review requirements conforming to the fuzzy height data are met.

[0134] For relevant descriptions, reference can be made to Figures 2 - 5a the relevant descriptions and effects corresponding to the steps in the corresponding embodiments, and details are not elaborated here.

[0135] An embodiment of the present application further provides an electronic device, as Figure 7 shown, including: a processor 71 and a memory 72 communicatively connected to the processor 71;

[0136] The memory 71 stores computer-executable instructions;

[0137] The processor 72 executes the computer-executable instructions stored in the memory 71 to implement the method for processing the height data of the high-precision map. Among them, the memory 72 and the processor 71 are connected through a bus 73.

[0138] For relevant descriptions, reference can be made to Figures 2 - 5a the relevant descriptions and effects corresponding to the steps in the corresponding embodiments, and details are not elaborated here.

[0139] An embodiment of the present application further provides a chip, including a memory and a processor. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory to execute the method for processing the height data of the high-precision map.

[0140] For relevant descriptions, reference can be made to Figures 2 - 5a the relevant descriptions and effects corresponding to the steps in the corresponding embodiments, and details are not elaborated here.

[0141] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. The computer program is executed by a processor to implement the Figures 2 - 5a method for processing the height data of the high-precision map provided in any one of the corresponding embodiments of the present application.

[0142] Among them, the computer-readable storage medium can be ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0143] An embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the Figures 2 - 5a method for processing the height data of the high-precision map provided in any one of the corresponding embodiments of the present application.

[0144] Figure 8 It is a block diagram of a terminal device shown in an exemplary embodiment of the present application. The terminal device 800 can be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0145] The terminal device 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0146] The processing component 802 generally controls the overall operation of the terminal device 800, such as operations associated with display, telephone calls, data communication, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above methods. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0147] The memory 804 is configured to store various types of data to support the operation of the terminal device 800. Examples of such data include instructions for any application or method operating on the terminal device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disk.

[0148] The power component 806 provides power to various components of the terminal device 800. The power component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the terminal device 800.

[0149] The multimedia component 808 includes a screen that provides an output interface between the terminal device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors can sense not only the boundaries of touch or swipe actions but also detect the duration and pressure associated with the touch or swipe operations. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the terminal device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each of the front camera and the rear camera can be a fixed optical lens system or have focal length and optical zoom capabilities.

[0150] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC) that is configured to receive external audio signals when the terminal device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals can be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, the audio component 810 further includes a speaker for outputting audio signals.

[0151] The I / O interface 812 provides an interface between the processing component 802 and a peripheral interface module, which can be a keyboard, a click wheel, buttons, etc. These buttons can include but are not limited to: a home button, a volume button, a power button, and a lock button.

[0152] The sensor component 814 includes one or more sensors for providing status assessments of various aspects of the terminal device 800. For example, the sensor component 814 can detect the on / off state of the terminal device 800, the relative positioning of components, such as the display and the keypad of the terminal device 800. The sensor component 814 can also detect a change in the position of the terminal device 800 or a component of the terminal device 800, the presence or absence of user contact with the terminal device 800, the orientation or acceleration / deceleration of the terminal device 800, and the temperature change of the terminal device 800. The sensor component 814 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor component 814 can also include a light sensor, such as a CMOS or a CCD image sensor, for use in imaging applications. In some embodiments, the sensor component 814 can further include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0153] The communication component 816 is configured to facilitate communication between the terminal device 800 and other devices in a wired or wireless manner. The terminal device 800 can access a communication standard-based wireless network, such as WiFi, 3G, 4G, 5G, or other standard communication networks, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on Radio Frequency Identification (RFID) technology, Infrared Data Association (IrDA) technology, Ultra-Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0154] In an exemplary embodiment, the terminal device 800 can be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the methods provided in any of the embodiments corresponding to the present application Figures 2 - 5a described above.

[0155] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the above instructions can be executed by a processor 820 of the terminal device 800 to complete the above methods. For example, the non-transitory computer-readable storage medium can be a ROM, Random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0156] The embodiments of the present application also provide a non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of the terminal device, enabling the terminal device 800 to execute the methods provided in any of the embodiments corresponding to the present application Figures 2 - 5a described above.

[0157] In several embodiments provided by the present application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of modules is only a logical function division, and there can be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or modules can be in electrical, mechanical, or other forms.

[0158] Other embodiments of the present application will be readily apparent to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include known common general knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and examples are only illustrative, and the true scope and spirit of the present application are pointed out by the following claims.

[0159] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A method for processing height data of a high-precision map, characterized in that, Including: Obtain the identification ID of the target object in the high-precision map and the OID value carried by the identification ID, where the target object includes road traffic facilities; Convert the target object into a linear object, and obtain the original height of each shape point in the linear object; Based on the OID value of the target object and the original height of each shape point, determine the fuzzy height of each shape point respectively, and generate the fuzzy height data of the target object based on the fuzzy height of each shape point.

2. The method according to claim 1, wherein The converting the target object into a linear object includes: Obtain the point cloud data and / or image data of the target object; and determine the edge geometry of the target object based on the point cloud data and / or image data to obtain a linear object.

3. The method according to claim 1, wherein After obtaining the identification ID of the target object in the high-precision map and the OID value carried by the identification ID, it further includes: Encrypt the OID value based on the hash digest algorithm to obtain an OID encrypted value; The determining the fuzzy height of each shape point based on the OID value of the target object and the original height of each shape point includes: determining the fuzzy height of each shape point based on the OID encrypted value and the original height of each shape point.

4. The method according to claim 1, wherein The method further includes: obtaining the minimum error value for the fuzzy processing of height data; The determining the fuzzy height of each shape point based on the OID value of the target object and the original height of each shape point includes: Normalize the OID value so that the normalized OID value ranges from [-1, 1]; and determine the fuzzy height of each shape point based on the normalized OID value, the original height of each shape point, and the minimum error value.

5. The method according to claim 4, characterized in that The determining the fuzzy height of each shape point based on the normalized OID value, the original height of each shape point, and the minimum error value includes: Determine the fuzziness of each shape point based on the product of the normalized OID value, the original height of each shape point, and the minimum error value; Determine the fuzzy height of each shape point based on the height of each shape point and its corresponding fuzziness.

6. The method according to claim 1, wherein After generating the fuzzy height data of the target object based on the fuzzy height of each shape point, it further includes: When the fuzzy height data meets the data compliance review requirements, generate high-precision map data based on the fuzzy height data of the target object, and transmit the high-precision map data to the target user terminal.

7. A height data processing device for a high-precision map, characterized in that, Including: A first acquisition module configured to obtain the identification ID of the target object in the high-precision map and the OID value carried by the identification ID, where the target object includes road facilities; A second acquisition module configured to obtain the linear object corresponding to the target object, and obtain the original height of each shape point in the linear object; A data processing module configured to determine the fuzzy height of each shape point based on the OID value of the target object and the original height of each shape point, and generate the fuzzy height data of the target object based on the fuzzy height of each shape point.

8. An electronic device, comprising: A processor, and a memory communicatively connected to the processor; The memory stores computer execution instructions; The processor executes the computer-executable instructions stored in the memory to implement the high-precision map altitude data processing method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, Computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to implement the high-precision map altitude data processing method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, The computer program, when executed by a processor, implements the high-precision map altitude data processing method according to any one of claims 1 to 6.

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