Map data updating method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention provides a map data updating method and device, equipment, a storage medium and a program product, and particularly relates to the technical field of traffic information processing. The method comprises the following steps: acquiring map data of a target area, and acquiring geographic space data newly acquired in the target area; based on the geographic space data, extracting a first traffic facility set associated with a target road model in the map data; extracting a second traffic facility set from the map data based on the first traffic facility set; matching a first traffic facility in the first traffic facility set with a second traffic facility in the second traffic facility set to obtain a matching result; and according to a matching result, updating local traffic facility data of the target road model to obtain updated map data. The method is used for achieving the effect of improving the accuracy of updating the map data.

Description

Technical Field

[0001] The present application relates to the technical field of traffic information processing, and in particular to a map data updating method, apparatus, device, storage medium and program product. Background Art

[0002] Automatic map data update technology leverages advanced technologies such as multi-source data fusion, image processing, and machine learning to continuously monitor and capture information such as road infrastructure, traffic signs, lane markings, pedestrian and vehicle dynamics. After processing, fusion, and verification of this data, it automatically identifies changes in the map and instantly generates update instructions. The specific process includes data collection, preprocessing, change detection, data fusion and verification, and update release.

[0003] Common map update methods include data differencing and data fusion. Before data fusion, the parent database data and the newly collected map data are differentially processed through data comparison and attribute assignment, mainly including topological difference processing and attribute difference processing. If some map data fails to match successfully during the comparison process and cannot be differentially processed, this data will be used to generate a job task for verification and processing by the operator.

[0004] The above map update method is mainly for a single map element, such as a traffic sign or a traffic light. Due to factors such as GPS (Global Positioning System) offset or sensor error, the positioning information of the map element in the newly collected map data may contain errors, resulting in failure to correctly match during the comparison process, ultimately leading to inaccurate map data updates. Summary of the Invention

[0005] Embodiments of the present application provide a map data updating method, apparatus, device, storage medium, and program product to improve the accuracy of updated map data.

[0006] In a first aspect, an embodiment of the present application provides a map data updating method, comprising:

[0007] Obtaining map data of a target area and obtaining newly collected geospatial data within the target area;

[0008] extracting, based on the geospatial data, a first set of transportation facilities associated with a target road model in the map data;

[0009] extracting a second set of transportation facilities from the map data based on the first set of transportation facilities;

[0010] Matching a first transportation facility in the first transportation facility set with a second transportation facility in the second transportation facility set to obtain a matching result;

[0011] According to the matching result, the local traffic facility data of the target road model is updated to obtain updated map data.

[0012] In a possible implementation, matching the first transportation facility in the first transportation facility set with the second transportation facility in the second transportation facility set to obtain a matching result includes:

[0013] For any first transportation facility in the first transportation facility set, searching from the second transportation facility set for a second transportation facility whose relative distance from the first transportation facility meets a preset distance condition and is of the same type as the first transportation facility, to obtain a potential matching second transportation facility;

[0014] Based on the road models respectively associated with the first traffic facility and the potential matching second traffic facility, it is determined whether the potential matching second traffic facility matches the first traffic facility to obtain a matching result.

[0015] In a possible implementation, determining whether the potential matching second transportation facility matches the first transportation facility based on the road models associated with the first transportation facility and the potential matching second transportation facility, to obtain a matching result, includes:

[0016] If the first traffic facility and the potential matching second traffic facility are associated with the same road model, then determining that the potential matching second traffic facility matches the first traffic facility; or

[0017] If the first transportation facility and the potential matching second transportation facility are associated with different road models, but there is a passable path between the potential matching second transportation facility and the first transportation facility within a preset distance range, then it is determined that the potential matching second transportation facility matches the first transportation facility.

[0018] In a possible implementation, extracting a second set of transportation facilities from the map data based on the first set of transportation facilities includes:

[0019] Importing the first transportation facility included in the first transportation facility set and the second transportation facility included in the map data into a map platform;

[0020] Based on the first transportation facilities included in the first transportation facility set, a search area is determined; and a search is performed through the map platform to determine second transportation facilities within the search area, thereby obtaining a second transportation facility set.

[0021] In a possible implementation, determining the search area based on each first transportation facility included in the first transportation facility set includes:

[0022] connecting the first transportation facilities in the first transportation facility set on the map platform to form a trajectory line;

[0023] Taking the trajectory line as the central baseline, the specified width is extended in all directions to obtain the surrounding area of ​​the trajectory line;

[0024] The surrounding area is determined as the search area range.

[0025] In a possible implementation, extracting, based on the geospatial data, a first set of transportation facilities associated with a target road model in the map data includes:

[0026] Selecting the target road model from a plurality of road models included in the map data, the road model representing a road segment between two road nodes;

[0027] A first set of transportation facilities associated with the target road model is extracted based on the geospatial data.

[0028] In a possible implementation, extracting a first set of transportation facilities associated with the target road model based on the geospatial data includes:

[0029] Extracting map elements from the geographic spatial data to obtain first map element data, where the first map element data includes a first map element and corresponding first attribute information;

[0030] Based on the first map element data, the first map element is screened and reconstructed to obtain first traffic facility data, the first traffic facility data including a first traffic facility and corresponding second attribute information, the second attribute information including a road model associated with the first traffic facility;

[0031] The first traffic facility data is queried to determine a first traffic facility set associated with the target road model.

[0032] In a possible implementation, updating the local traffic facility data of the target road model according to the matching result to obtain updated map data includes:

[0033] Obtaining historical matching results for the target road model;

[0034] Identifying potential updated transportation facilities based on the current matching results and in combination with the historical matching results, and determining the confidence level of the potential updated transportation facilities;

[0035] If the confidence level of the potential updated traffic facility meets a preset confidence level condition, the local traffic facility data of the target road model is updated to obtain updated map data.

[0036] In a second aspect, an embodiment of the present application provides a map data updating device, comprising:

[0037] an acquisition module, configured to acquire map data of a target area and acquire newly collected geospatial data within the target area;

[0038] a first extraction module, configured to extract, based on the geospatial data, a first set of traffic facilities associated with a target road model in the map data;

[0039] a second extraction module, configured to extract a second set of transportation facilities from the map data based on the first set of transportation facilities;

[0040] a matching module, configured to match a first transportation facility in the first transportation facility set with a second transportation facility in the second transportation facility set to obtain a matching result;

[0041] An updating module is used to update the local traffic facility data of the target road model according to the matching result to obtain updated map data.

[0042] In a possible implementation, the matching module is specifically configured to:

[0043] For any first transportation facility in the first transportation facility set, searching from the second transportation facility set for a second transportation facility whose relative distance from the first transportation facility meets a preset distance condition and is of the same type as the first transportation facility, to obtain a potential matching second transportation facility;

[0044] Based on the road models respectively associated with the first traffic facility and the potential matching second traffic facility, it is determined whether the potential matching second traffic facility matches the first traffic facility to obtain a matching result.

[0045] In a possible implementation, the matching module is specifically configured to:

[0046] If the first traffic facility and the potential matching second traffic facility are associated with the same road model, then determining that the potential matching second traffic facility matches the first traffic facility; or

[0047] If the first transportation facility and the potential matching second transportation facility are associated with different road models, but there is a passable path between the potential matching second transportation facility and the first transportation facility within a preset distance range, then it is determined that the potential matching second transportation facility matches the first transportation facility.

[0048] In a possible implementation, the second extraction module is specifically configured to:

[0049] Importing the first transportation facility included in the first transportation facility set and the second transportation facility included in the map data into a map platform;

[0050] Determining a search area based on each first transportation facility included in the first transportation facility set;

[0051] A search is performed through the map platform to determine second transportation facilities within the search area, and a second transportation facility set is obtained.

[0052] In a possible implementation, the second extraction module is specifically configured to:

[0053] connecting the first transportation facilities in the first transportation facility set on the map platform to form a trajectory line;

[0054] Taking the trajectory line as the central baseline, the specified width is extended in all directions to obtain the surrounding area of ​​the trajectory line;

[0055] The surrounding area is determined as the search area range.

[0056] In a possible implementation, the first extraction module is specifically configured to:

[0057] Selecting the target road model from a plurality of road models included in the map data, the road model representing a road segment between two road nodes;

[0058] A first set of transportation facilities associated with the target road model is extracted based on the geospatial data.

[0059] In a possible implementation, the first extraction module is specifically configured to:

[0060] Extracting map elements from the geographic spatial data to obtain first map element data, where the first map element data includes a first map element and corresponding first attribute information;

[0061] Based on the first map element data, the first map element is screened and reconstructed to obtain first traffic facility data, the first traffic facility data including a first traffic facility and corresponding second attribute information, the second attribute information including a road model associated with the first traffic facility;

[0062] The first traffic facility data is queried to determine a first traffic facility set associated with the target road model.

[0063] In a possible implementation, the update module is specifically configured to:

[0064] Obtaining historical matching results for the target road model;

[0065] Identifying potential updated transportation facilities based on the current matching results and in combination with the historical matching results, and determining the confidence level of the potential updated transportation facilities;

[0066] If the confidence level of the potential updated traffic facility meets a preset confidence level condition, the local traffic facility data of the target road model is updated to obtain updated map data.

[0067] In a third aspect, an embodiment of the present application provides a map data updating device, comprising: a memory, a processor;

[0068] The memory stores computer-executable instructions;

[0069] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0070] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementation methods of the first aspect.

[0071] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0072] The map data updating method, apparatus, device, storage medium, and program product provided in the embodiments of the present application update map data based on road models. Map data for a target area to be updated can be obtained, as well as newly collected geospatial data within the target area. Based on the geospatial data, a first set of traffic facilities associated with the target road model in the map data can be extracted. A second set of traffic facilities can then be extracted from the map data, and a first traffic facility in the first set of traffic facilities can be matched with a second traffic facility in the second set of traffic facilities. By comparing the elements in the first set of traffic facilities and the second set of traffic facilities, map elements that may need to be added or deleted can be determined. Compared to the prior art, which performs matching on individual map elements, the present application performs set matching and alignment based on road models. By performing holistic matching based on road models, the overall characteristics of the road and its related elements can be more comprehensively considered, rather than just the local characteristics of a single element. This holistic perspective can reduce the probability of mismatching and improve matching accuracy. Set matching ensures that all relevant elements of a road are considered, thereby avoiding omissions. Set matching can systematically identify the difference elements between two sets, including newly added, deleted, and modified elements. This systematic difference identification can more accurately reflect changes in map data. The map data update method of this application can reduce data update errors caused by single element matching errors, thereby improving the accuracy of updated map data. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0074] Figure 1 A schematic diagram of a scenario for the map data updating method provided in this application;

[0075] Figure 2 Schematic diagram of the map data update method provided in this application Figure 1 ;

[0076] Figure 3 Schematic diagram of the map data update method provided in this application Figure 2 ;

[0077] Figure 4 A schematic diagram of a first traffic facility associated with a target road model in this application;

[0078] Figure 5 This is a schematic diagram of the second transportation facility extracted for this application;

[0079] Figure 6A schematic diagram for finding a second transportation facility within the search area for this application;

[0080] Figure 7 This is a schematic diagram of the matching process of the first transportation facility set and the second transportation facility set of this application. Figure 1 ;

[0081] Figure 8 This is a schematic diagram of the matching process of the first transportation facility set and the second transportation facility set of this application. Figure 2 ;

[0082] Figure 9 This is a schematic diagram of the matching process of the first transportation facility set and the second transportation facility set of this application. Figure 3 ;

[0083] Figure 10 This is a schematic diagram of the matching process of the first transportation facility set and the second transportation facility set of this application. Figure 4 ;

[0084] Figure 11 A schematic diagram of the structure of the map data updating device provided in this application;

[0085] Figure 12 This is a structural diagram of the map data updating device provided in this application.

[0086] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0087] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0088] A link is the fundamental unit of the road model in a navigation system, while a node represents the endpoint of a link or the intersection of links. This representation directly reflects the entire road topology. Simply put, a link here refers to a section of road, not just a road boundary. This definition allows for a more accurate description and simulation of the complex structure and function of road networks in map data.

[0089] The application scenario of the present application is specifically the scenario of updating map data, wherein the map data can be updated in the server. In addition, the map data can also be updated in the terminal device, which can be a vehicle-mounted device, desktop computer, laptop computer, tablet computer and smart phone, etc.

[0090] Figure 1 A schematic diagram of a map data updating method provided in this application, such as Figure 1 As shown, the mother library data (i.e., the map data to be updated) can be stored in the server 103, and the new map data obtained by data processing the newly collected geographic spatial data can be stored in the server 101. The terminal device 102 can obtain the new map data from the server 101, and can obtain the mother library data from the server 103, determine the difference information between the new map data and the mother library data, update the mother library data based on the difference information, and obtain the updated mother library data. The updated mother library data can then be stored in the server 103, and the updated mother library data in the server 103 can be called by different entities or systems.

[0091] In view of the above scenario, in the existing technology, map update methods include data differencing and data fusion. Data differencing refers to comparing the differences between new and old data, while data fusion refers to merging data from different data sources into a unified data set. Before data fusion, the parent database data and the newly collected map data are differentially processed by data comparison and attribute assignment, mainly including topological difference processing and attribute difference processing. Topological difference processing can be comparing changes in road network structure, and attribute difference processing can be comparing changes in road attributes. If some map data fails to match successfully during the comparison process, then these data will be used to generate work tasks, which will be verified and processed by the operator. This differential algorithm is mainly for a single map element. Affected by factors such as GPS offset or sensor error, the positioning information of the map elements in the newly collected map data may have errors, resulting in failure to correctly match during the comparison process, ultimately leading to inaccurate map data updates.

[0092] To address the issue of inaccurate positioning, new algorithms and sensor fusion technologies are being explored to improve positioning accuracy. For example, data collected by cameras, satellite remote sensing, and lidar (LiDAR) can be integrated with surveying and mapping data. By integrating data from multiple sensors, data reliability and accuracy can be improved. However, environmental complexity is a major cause of inaccurate positioning. For example, changes in illumination, dynamic obstacles, and areas with repetitive or weak textures can interfere with data collection and processing by sensors (such as LiDAR and cameras), thereby affecting positioning accuracy. Furthermore, the accuracy limitations of the sensors themselves and noise interference can also introduce positioning errors. Furthermore, insufficient algorithm optimization and robustness can lead to decreased positioning performance in complex or extreme environments.

[0093] Although multi-sensor data fusion has many advantages, inaccurate positioning may still occur in practical applications. This is mainly due to the following factors:

[0094] One is the fixed deviation between sensors: Since different sensors may have fixed deviations (such as position error, timing error, etc.) during the measurement process, these deviations may be difficult to completely eliminate during the fusion process, resulting in inaccurate positioning results.

[0095] Second, the performance limitations of the sensors themselves: Sensor performance parameters such as measurement accuracy and resolution directly impact the accuracy and reliability of their data. If the sensor's performance is poor, even with multi-sensor data fusion technology, it is difficult to guarantee the accuracy of positioning results.

[0096] The map data updating method provided by the present application is performed on a road model basis, and the map data of the target area to be updated and the newly collected geospatial data in the target area can be obtained. Based on the geospatial data, a first set of traffic facilities associated with the target road model in the map data can be extracted, and then a second set of traffic facilities can be extracted from the map data, and the first traffic facility in the first set of traffic facilities can be matched with the second traffic facility in the second set of traffic facilities. By comparing the elements in the first set of traffic facilities and the second set of traffic facilities, it is determined that a new map element may need to be added, or a map element may need to be deleted. Compared to the prior art that matches a single map element, the present application performs set matching and alignment on a road model basis. By performing overall matching on a road model basis, the overall characteristics of the road and its related elements can be more comprehensively considered, rather than just the local characteristics of a single element. This overall perspective can reduce the probability of mismatching and improve the accuracy of matching. Set matching can ensure that all relevant elements of the road are taken into account, thereby avoiding omissions. Set matching can systematically identify the difference elements between two sets, including newly added, deleted, and modified elements. This systematic difference identification can more accurately reflect changes in map data. The map data update method of this application can reduce data update errors caused by single element matching errors, and solve the technical problem of inaccurate map data updates.

[0097] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0098] Figure 2Schematic diagram of the map data update method provided in this application Figure 1 ,like Figure 2 As shown, the method includes:

[0099] S201: Acquire map data of a target area, and acquire newly collected geographic spatial data within the target area.

[0100] The map data for the target area is the map data to be updated. Geospatial data can be point cloud data or image data. Point cloud data is three-dimensional spatial data collected by sensors such as lidar and cameras. Each point contains location information in three-dimensional space. Point cloud data may also contain additional attributes, such as reflection intensity and color, which can further describe the characteristics of the target object.

[0101] The map data includes multiple road models. A road model (ie, a link) may include only one line segment, or may include multiple line segments.

[0102] S202: Extract a first set of transportation facilities associated with a target road model in the map data based on the geographic space data.

[0103] The map data updating method of the present embodiment is performed on a road model basis. It can be assumed that the local traffic facility data of the target road model is updated. The traffic facilities extracted based on the geospatial data can be referred to as first traffic facilities. The first traffic facility set is a collection of first traffic facilities. The first traffic facilities can include one or more of traffic lights, traffic signs, and traffic markings.

[0104] In an embodiment of the present application, transportation facilities can be identified on the geospatial data to obtain first transportation facilities. For the identified first transportation facilities, first transportation facilities associated with the target road model are selected to obtain a first transportation facility set. All first transportation facilities in the first transportation facility set are associated with the target road model.

[0105] S203 : Extracting a second transportation facility set from the map data based on the first transportation facility set.

[0106] The traffic facilities extracted from the map data are referred to as second traffic facilities. The second traffic facility set is a set of second traffic facilities. The second traffic facilities may include one or more of traffic lights, traffic signs and traffic markings.

[0107] In the embodiment of the present application, based on the geometric features of the first transportation facilities included in the first transportation facility set, the second transportation facility set can be extracted from the map data.

[0108] S204: Match the first transportation facility in the first transportation facility set with the second transportation facility in the second transportation facility set to obtain a matching result.

[0109] The transportation facilities in the two sets are matched by location and attribute to obtain matching results. The matching results can include successfully matched transportation facilities and unsuccessfully matched transportation facilities. Unsuccessfully matched transportation facilities can be considered as map features that need to be updated.

[0110] S205: Update the local traffic facility data of the target road model according to the matching result to obtain updated map data.

[0111] In an embodiment of the present application, the local traffic facility data of the target road model is updated based on the matching results. For example, for a traffic facility that is not successfully matched, if it is the first traffic facility in the first traffic facility set, the traffic facility can be added to the database storing the map data, and if it is the second traffic facility in the second traffic facility set, the traffic facility can be deleted from the database storing the map data.

[0112] The map data updating method provided in the embodiment of the present application, compared to the prior art that matches a single map element, performs set matching and alignment based on the road model. By performing overall matching based on the road model, the overall characteristics of the road and its related elements can be more comprehensively considered, rather than just the local characteristics of a single element. This overall perspective can reduce the probability of mismatching and improve the accuracy of matching. Set matching can ensure that all relevant elements of the road are taken into account, thereby avoiding omissions. Set matching can systematically identify the difference elements between two sets, including newly added, deleted, and modified elements. This systematic difference identification can more accurately reflect changes in map data. The map data updating method of the present application can reduce data update errors caused by single element matching errors, thereby improving the accuracy of updated map data.

[0113] Figure 3 Schematic diagram of the map data update method provided in this application Figure 2 ,like Figure 3 As shown, this embodiment Figure 2 Based on the embodiment, a map data updating method is described in detail. The method includes:

[0114] S301: Acquire map data of a target area, and acquire newly collected geographic spatial data within the target area.

[0115] Geospatial data can be sensor data such as point cloud data or image data, and map features can be extracted based on this data.

[0116] S302: Extract a first set of transportation facilities associated with a target road model in the map data based on the geographic space data.

[0117] In a possible implementation, extracting a first set of transportation facilities associated with a target road model in map data based on geospatial data may specifically include:

[0118] Selecting a target road model from a plurality of road models included in the map data, the road model representing a road segment between two road nodes;

[0119] A first transportation facility set associated with a target road model is extracted based on the geospatial data.

[0120] The map data updating method of the embodiment of the present application is performed in units of road models. A target road model for updating local traffic facility data can be selected from multiple road models contained in the map data, and a first traffic facility set associated with the target road model can be extracted based on geographic spatial data.

[0121] In a possible implementation, extracting a first set of transportation facilities associated with a target road model based on geospatial data may specifically include:

[0122] Extracting map elements from the geographic spatial data to obtain first map element data, where the first map element data includes a first map element and corresponding first attribute information;

[0123] Based on the first map element data, the first map element is screened and reconstructed to obtain first traffic facility data, where the first traffic facility data includes the first traffic facility and its corresponding second attribute information, where the second attribute information includes a road model associated with the first traffic facility;

[0124] The first traffic facility data is queried to determine a first traffic facility set associated with the target road model.

[0125] In an embodiment of the present application, map element extraction can be performed on the acquired geographic spatial data to obtain a first map element and its corresponding first attribute information, wherein the first map element can include multiple map element types, such as traffic lights, crosswalks, traffic signs, etc.

[0126] Screening specifically refers to screening out map elements belonging to transportation facilities from the first map elements, and reconstruction specifically refers to cleaning and organizing the first attribute information of the screened map elements belonging to transportation facilities, such as performing standardization, normalization, deduplication and merging operations to ensure the accuracy, consistency and completeness of these attribute information.

[0127] Based on the acquired first map element data, the first map element is screened and reconstructed. Specifically, the first map element can be screened and reconstructed based on attribute information such as virtuality, color, material, shape, and text of the first map element to obtain the first transportation facility and its corresponding second attribute information. In this process, an association between the first transportation facility and the road model in the map data can also be established, and the first transportation facility and its corresponding second attribute information can be stored in a database. The second attribute information of the first transportation facility includes information such as the road model associated with the first transportation facility, the type of the first transportation facility, and the location coordinates of the first transportation facility.

[0128] By querying the first traffic facility data, the first traffic facility set associated with the target road model can be obtained. Figure 4 , which is a schematic diagram of the first traffic facility associated with the target road model of the present application, including traffic lights, hazard signs and speed limit signs.

[0129] S303: Extract a second transportation facility set from the map data based on the first transportation facility set.

[0130] The map data can be preprocessed to extract the second transportation facility and its corresponding third attribute information. The third attribute information of the second transportation facility includes information such as the road model associated with the second transportation facility, the type of the second transportation facility, and the location coordinates of the second transportation facility. The second transportation facility data can be stored in a PostgreSQL database that supports spatial queries or calculations.

[0131] Reference Figure 5 As shown, this is a schematic diagram of the second traffic facility extracted by this application, which includes crosswalks, traffic lights, hazard signs, speed limit signs, etc.

[0132] After preprocessing the map data to obtain the second traffic facility data, the second traffic facility set may be extracted from the second traffic facility data based on the geometric features of the first traffic facilities included in the first traffic facility set.

[0133] In a possible implementation, extracting the second set of transportation facilities from map data based on the first set of transportation facilities may specifically include:

[0134] Importing the first transportation facility included in the first transportation facility set and the second transportation facility included in the map data into the map platform;

[0135] Determining a search area based on each first transportation facility included in the first transportation facility set;

[0136] A search is performed through a map platform to determine the second transportation facilities within the search area and obtain a second transportation facility set.

[0137] In order to eliminate the influence of positioning errors, in an embodiment of the present application, a search area range may be determined to search for second transportation facilities within the search area range.

[0138] In a possible implementation, determining the search area range based on each first transportation facility included in the first transportation facility set may specifically include:

[0139] connecting the first transportation facilities in the first transportation facility set on the map platform to form a trajectory line;

[0140] Taking the trajectory line as the center baseline, expand the specified width in all directions to obtain the surrounding area of ​​the trajectory line;

[0141] Determine the surrounding area as the search area range.

[0142] Reference Figure 6 The figure shows a schematic diagram of searching for the second transportation facility within the search area. Connect the five first transportation facilities on the left to obtain a trajectory line. Using the trajectory line as the center baseline, expand 50 meters in all directions to obtain a surrounding area, which is the search area.

[0143] S304: For any first transportation facility in the first transportation facility set, search from the second transportation facility set for a second transportation facility whose relative distance to the first transportation facility meets a preset distance condition and is of the same type as the first transportation facility to obtain a potential matching second transportation facility.

[0144] S305 : Determine whether the potential matching second transportation facility matches the first transportation facility based on the road models associated with the first transportation facility and the potential matching second transportation facility, to obtain a matching result.

[0145] In one possible implementation, determining whether the potential matching second transportation facility matches the first transportation facility based on the road models associated with the first transportation facility and the potential matching second transportation facility to obtain a matching result may specifically include:

[0146] If the first traffic facility and the potential matching second traffic facility are associated with the same road model, then determining that the potential matching second traffic facility matches the first traffic facility; or,

[0147] If the first transportation facility and the potential matching second transportation facility are associated with different road models, but there is a traversable path between the potential matching second transportation facility and the first transportation facility within a preset distance range, then the potential matching second transportation facility is determined to match the first transportation facility.

[0148] Assuming that the first transportation facilities included in the first transportation facility set are A1, A2, A3, A4, and A5, and the second transportation facilities included in the second transportation facility set are B1, B2, B3, and B4, the matching process may include:

[0149] 1. Match A1 and calculate the relative distance between A1 and each second transportation facility in the second transportation facility set. The distance calculation formula can be:

[0150]

[0151] Among them, lon1 represents the longitude of the first transportation facility, lat1 represents the latitude of the first transportation facility, and z1 represents the elevation of the first transportation facility; lon2 represents the longitude of the second transportation facility, lat2 represents the latitude of the second transportation facility, and z2 represents the elevation of the second transportation facility.

[0152] 2. Assuming that the relative distance between A1 and B2 is the shortest, we can further verify whether the types of A1 and B2 are the same. If the types of A1 and B2 are the same, we can further verify whether the road models associated with A1 and B2 are the same. If the types of A1 and B2 are the same, and the road models associated with A1 and B2 are the same, then A1 and B2 can be considered to be temporarily matched. Alternatively, if the types of A1 and B2 are the same, A1 and B2 are associated with different road models, but there is a passable path between A1 and B2 within 50m, then A1 and B2 can also be considered to be temporarily matched; except for the above situation, it can be considered that A1 and B2 do not match. In the case that A1 and B2 do not match, we can look for Bi with the closest relative distance to A1, and perform the steps of verifying whether its type is the same as A1, and verifying whether its associated road model is the same as A1 again. If it is finally determined that A1 does not match any Bi, then A1 is skipped and matching is performed for A2. If Figure 7 As shown, it is a schematic diagram of the matching process of the first transportation facility set and the second transportation facility set of this application. Figure 1 , each small circle in the figure represents a set element, and the same color represents the same type. Figure 7 It can be seen that A1 and B2 are temporarily matched successfully.

[0153] 3. Perform a match on A2. Assuming that A2 and B1 are closest, A2 and B1 are of the same type, and A2 and B1 are associated with the same road model, then A2 and B1 can be considered to be temporarily matched. Figure 8 As shown, it is a schematic diagram of the matching process of the first transportation facility set and the second transportation facility set of this application. Figure 2 ,As can be seen from the figure, A2 and B1 are temporarily matched successfully.

[0154] 4. Perform a match on A3. Assume that A3 is closest to B2, A3 and B2 are of the same type, and A2 and B1 have the same associated road model. However, since B2 has already matched A1, it is necessary to further compare the distance from B2 to A1 and the distance from B2 to A3. Assuming that the distance from B2 to A3 is closer, it is necessary to adjust the matching relationship and mark A3 and B2 as temporarily matched, while A1 and B2 are not matched. Figure 9 As shown, it is a schematic diagram of the matching process of the first transportation facility set and the second transportation facility set of this application. Figure 3 ,As can be seen from the figure, A3 and B2 are temporarily matched successfully.

[0155] 5. Perform matching for A4. Assuming that the types of A4 and the second transportation facilities in the second transportation facility set are all different, it can be considered that A4 does not match any Bi.

[0156] 6. Perform a match on A5. Assuming that A5 is closest to B4, A5 and B4 are of the same type, and A5 and B4 have the same associated road model, and B4 has no matching object, then it can be considered that A5 and B4 are matched successfully. Since A5 is the last element in the first traffic facility set, the entire matching process is completed. Finally, it can be determined that A2 and B1 are matched successfully, A3 and B2 are matched successfully, and A5 and B4 are matched successfully. Figure 10 As shown, it is a schematic diagram of the matching process of the first transportation facility set and the second transportation facility set of this application. Figure 4 As can be seen from the figure, the final matching results are A2 and B1, A3 and B2, and A5 and B4. The unsuccessfully matched transportation facilities include A1, A4, and B3. A1, A4, and B3 can be called potential updated transportation facilities, among which A1 and A4 can be called potential new transportation facilities, and it is suspected that they need to be added to the database storing map data. B3 can be called a potential redundant transportation facility, and it is suspected that it needs to be deleted from the database storing map data.

[0157] It should be noted that the verification types are the same, specifically whether they are all traffic lights, or whether they are all hazard signs to pay attention to pedestrians, or whether they are all hazard signs prohibiting overtaking, or whether they are all speed limit signs with a speed limit of 40 kilometers per hour, etc. The more detailed the classification of traffic facilities types, the higher the matching accuracy.

[0158] S306: Update the local traffic facility data of the target road model according to the matching result to obtain updated map data.

[0159] In a possible implementation, updating the local traffic facility data of the target road model according to the matching results to obtain updated map data may specifically include:

[0160] Obtain historical matching results for the target road model;

[0161] Based on the current matching results and in combination with the historical matching results, potential updated transportation facilities are identified and the confidence level of the potential updated transportation facilities is determined;

[0162] If the confidence level of the potential updated traffic facilities meets the preset confidence level condition, the local traffic facility data of the target road model is updated to obtain updated map data.

[0163] If the same road model has been matched with a single-leg trajectory line, it can be said that there is a single-leg trajectory coverage. Since the single-leg trajectory line data is easily affected by factors such as GPS offset or sensor error, in order to minimize the impact, the frequency of geospatial data collection can be increased, and multi-leg trajectory lines can be used to match the road model to improve the reliability and accuracy of map data updates.

[0164] In this embodiment, historical matching results for the target road model can be obtained. The historical matching results can be matching results obtained by processing the geospatial data after the geospatial data was collected last time or several times. Assuming that the current matching result indicates that the traffic facilities that were not successfully matched are A1, A4 and B3, and one of the historical matching results indicates that the traffic facilities that were not successfully matched are A1, and the other historical matching result indicates that the traffic facilities that were not successfully matched are A1 and B3, it can be determined that the confidence of A1 is 3, the confidence of A4 is 1, and the confidence of B3 is 2. Since the confidence of A1 is greater than the preset confidence threshold, A1 can be added to the database storing map data, while the confidence of A4 and B3 is not greater than the preset confidence threshold, so they are not processed.

[0165] The map data updating method provided in the embodiment of the present application, compared to the prior art that matches a single map element, performs set matching and alignment based on the road model. By performing overall matching based on the road model, the overall characteristics of the road and its related elements can be more comprehensively considered, rather than just the local characteristics of a single element. This overall perspective can reduce the probability of mismatching and improve the accuracy of matching. Set matching can ensure that all relevant elements of the road are taken into account, thereby avoiding omissions. Set matching can systematically identify the difference elements between two sets, including newly added, deleted, and modified elements. This systematic difference identification can more accurately reflect changes in map data. The map data updating method of the present application can reduce data update errors caused by single element matching errors, thereby improving the accuracy of updated map data.

[0166] The map data update method provided in the embodiments of the present application, for any road model, after N-trip trajectory coverage, can automatically add or delete data if the confidence level of a potential updated traffic facility (i.e., a traffic facility suspected of needing to be updated) is determined to meet a preset confidence level. Hardware errors and GPS point drift have a greater impact on a single-trip trajectory. By adding a reasonable matching algorithm and multi-trip data, the accuracy of the data can be effectively improved. Therefore, map data can be automatically updated more accurately.

[0167] Figure 11 This is a schematic diagram of the structure of the map data updating device provided by this application, such as Figure 11 As shown, the map data updating device 110 provided in this embodiment includes:

[0168] An acquisition module 1101 is used to acquire map data of a target area and acquire newly collected geographic spatial data within the target area;

[0169] A first extraction module 1102 is configured to extract a first set of transportation facilities associated with a target road model in the map data based on the geospatial data;

[0170] A second extraction module 1103 is configured to extract a second set of transportation facilities from the map data based on the first set of transportation facilities;

[0171] A matching module 1104 is configured to match a first transportation facility in the first transportation facility set with a second transportation facility in the second transportation facility set to obtain a matching result;

[0172] The updating module 1105 is used to update the local traffic facility data of the target road model according to the matching results to obtain updated map data.

[0173] In a possible implementation, the matching module is specifically configured to:

[0174] For any first transportation facility in the first transportation facility set, searching from the second transportation facility set for a second transportation facility whose relative distance to the first transportation facility meets a preset distance condition and is of the same type as the first transportation facility, to obtain a potential matching second transportation facility;

[0175] Based on the road models respectively associated with the first traffic facility and the potential matching second traffic facility, it is determined whether the potential matching second traffic facility matches the first traffic facility to obtain a matching result.

[0176] In a possible implementation, the matching module is specifically configured to:

[0177] If the first traffic facility and the potential matching second traffic facility are associated with the same road model, then determining that the potential matching second traffic facility matches the first traffic facility; or,

[0178] If the first transportation facility and the potential matching second transportation facility are associated with different road models, but there is a traversable path between the potential matching second transportation facility and the first transportation facility within a preset distance range, then the potential matching second transportation facility is determined to match the first transportation facility.

[0179] In a possible implementation, the second extraction module is specifically configured to:

[0180] Importing the first transportation facility included in the first transportation facility set and the second transportation facility included in the map data into the map platform;

[0181] Determining a search area based on each first transportation facility included in the first transportation facility set;

[0182] A search is performed through a map platform to determine the second transportation facilities within the search area and obtain a second transportation facility set.

[0183] In a possible implementation, the second extraction module is specifically configured to:

[0184] connecting the first transportation facilities in the first transportation facility set on the map platform to form a trajectory line;

[0185] Taking the trajectory line as the center baseline, expand the specified width in all directions to obtain the surrounding area of ​​the trajectory line;

[0186] Determine the surrounding area as the search area range.

[0187] In a possible implementation, the first extraction module is specifically configured to:

[0188] Selecting a target road model from a plurality of road models included in the map data, the road model representing a road segment between two road nodes;

[0189] A first transportation facility set associated with a target road model is extracted based on the geospatial data.

[0190] In a possible implementation, the first extraction module is specifically configured to:

[0191] Extracting map elements from the geographic spatial data to obtain first map element data, where the first map element data includes a first map element and corresponding first attribute information;

[0192] Based on the first map element data, the first map element is screened and reconstructed to obtain first traffic facility data, where the first traffic facility data includes the first traffic facility and its corresponding second attribute information, where the second attribute information includes a road model associated with the first traffic facility;

[0193] The first traffic facility data is queried to determine a first traffic facility set associated with the target road model.

[0194] In a possible implementation, the update module is specifically configured to:

[0195] Obtain historical matching results for the target road model;

[0196] Based on the current matching results and in combination with the historical matching results, potential updated transportation facilities are identified and the confidence level of the potential updated transportation facilities is determined;

[0197] If the confidence level of the potential updated traffic facilities meets the preset confidence level condition, the local traffic facility data of the target road model is updated to obtain updated map data.

[0198] The map data updating device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effects are similar and will not be described in detail in this embodiment.

[0199] Figure 12 This is a schematic diagram of the structure of the map data update device provided in this application. Figure 12 As shown, the map data updating device 120 provided in this embodiment includes: at least one processor 1201 and a memory 1202. Optionally, the device 120 also includes a communication component 1203. The processor 1201, the memory 1202 and the communication component 1203 are connected via a bus.

[0200] During the specific implementation process, at least one processor 1201 executes the computer-executable instructions stored in the memory 1202, so that the at least one processor 1201 performs the above method.

[0201] The specific implementation process of the processor 1201 can be found in the above method embodiment. Its implementation principle and technical effects are similar and will not be repeated here in this embodiment.

[0202] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly implemented by a hardware processor or implemented by a combination of hardware and software modules in the processor.

[0203] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0204] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be classified into address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0205] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0206] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0207] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile memory 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, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0208] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0209] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, either through an interface, electrical, mechanical, or other means.

[0210] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0211] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0212] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0213] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0214] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A map data updating method, characterized in that: include: Acquiring map data of a target area, and acquiring newly collected geospatial data in the target area; extracting, based on the geospatial data, a first set of transportation facilities associated with a target road model in the map data; extracting a second set of transportation facilities from the map data based on the first set of transportation facilities; Matching a first transportation facility in the first transportation facility set with a second transportation facility in the second transportation facility set to obtain a matching result; According to the matching result, the local traffic facility data of the target road model is updated to obtain updated map data.

2. The method according to claim 1, characterized in that The matching of the first transportation facility in the first transportation facility set with the second transportation facility in the second transportation facility set to obtain a matching result includes: For any first transportation facility in the first transportation facility set, searching from the second transportation facility set for a second transportation facility whose relative distance to the first transportation facility meets a preset distance condition and is of the same type as the first transportation facility, to obtain a potential matching second transportation facility; Based on the road models respectively associated with the first transportation facility and the potential matching second transportation facility, it is determined whether the potential matching second transportation facility matches the first transportation facility to obtain a matching result.

3. The method according to claim 2, characterized in that The determining whether the potential matching second transportation facility matches the first transportation facility based on the road models respectively associated with the first transportation facility and the potential matching second transportation facility to obtain a matching result includes: If the first traffic facility and the potential matching second traffic facility are associated with the same road model, then determining that the potential matching second traffic facility matches the first traffic facility; or, If the first transportation facility and the potential matching second transportation facility are associated with different road models, but there is a traversable path between the potential matching second transportation facility and the first transportation facility within a preset distance range, it is determined that the potential matching second transportation facility matches the first transportation facility.

4. The method according to any one of claims 1 to 3, characterized in that: The step of extracting a second set of transportation facilities from the map data based on the first set of transportation facilities includes: Importing the first transportation facility included in the first transportation facility set and the second transportation facility included in the map data into the map platform; Determining a search area range based on each first transportation facility included in the first transportation facility set; A search is performed through the map platform to determine second transportation facilities within the search area, and a second transportation facility set is obtained.

5. The method according to claim 4, characterized in that The determining of the search area range based on each first transportation facility included in the first transportation facility set includes: Connecting each first transportation facility in the first transportation facility set on the map platform to form a trajectory line; Taking the trajectory line as the central baseline, the specified width is extended in all directions to obtain the surrounding area of ​​the trajectory line; The surrounding area is determined as the search area range.

6. The method according to any one of claims 1 to 3, characterized in that: The extracting, based on the geospatial data, a first set of traffic facilities associated with a target road model in the map data comprises: Selecting the target road model from a plurality of road models included in the map data, the road model representing a road segment between two road nodes; Based on the geospatial data, a first set of traffic facilities associated with the target road model is extracted.

7. The method according to claim 6, characterized in that The extracting, based on the geospatial data, a first set of traffic facilities associated with the target road model comprises: Extracting map elements from the geographic spatial data to obtain first map element data, wherein the first map element data includes a first map element and its corresponding first attribute information; Based on the first map element data, the first map element is screened and reconstructed to obtain first traffic facility data, wherein the first traffic facility data includes a first traffic facility and its corresponding second attribute information, and the second attribute information includes a road model associated with the first traffic facility; The first traffic facility data is queried to determine a first traffic facility set associated with the target road model.

8. The method according to any one of claims 1 to 3, characterized in that: The updating of the local traffic facility data of the target road model according to the matching result to obtain updated map data includes: Acquire historical matching results for the target road model; According to the current matching result, combined with the historical matching result, potential updated transportation facilities are identified, and the confidence of the potential updated transportation facilities is determined; If the confidence of the potential updated traffic facility meets the preset confidence condition, the local traffic facility data of the target road model is updated to obtain updated map data.

9. A map data updating device, characterized in that: include: An acquisition module, used to acquire map data of a target area and acquire newly collected geospatial data in the target area; A first extraction module, configured to extract a first set of traffic facilities associated with a target road model in the map data based on the geospatial data; A second extraction module, configured to extract a second set of transportation facilities from the map data based on the first set of transportation facilities; a matching module, configured to match a first transportation facility in the first transportation facility set with a second transportation facility in the second transportation facility set to obtain a matching result; An updating module is used to update the local traffic facility data of the target road model according to the matching result to obtain updated map data.

10. A map data updating device / computer readable storage medium / computer program product, characterized in that: The map data updating device comprises a memory and a processor, the memory stores computer-executable instructions, and the processor executes the computer-executable instructions stored in the memory, so that the processor executes the method according to any one of claims 1 to 8; and / or, The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor; and / or, The computer program product comprises a computer program, which implements the method according to any one of claims 1 to 8 when executed by a processor.

Images