Map Determination Method, Device, Equipment, and Storage Medium

Abstract

The present application discloses a method for determining a map. The method includes: obtaining a first map and a second map, where the fineness of the first map is higher than that of the second map; determining a current positioning reference point according to the second map; determining a first element index according to the first map and the positioning reference point, where the first element index is used to mark elements within a preset range of the positioning reference point; obtaining second elements within a first preset distance centered on the positioning reference point according to the first element index; and determining a target map according to the second elements and the positioning reference point. This solution can search for all elements within a certain range centered on a certain point on a standard definition map in a high-precision map, thereby forming a local high-precision map, and conveniently realizing obtaining a high-precision map starting from standard definition data, thus solving the reuse problem between the standard definition map and the high-precision map.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and particularly to a method for determining a map, a device for determining a map, a computer device, and a computer-readable storage medium. Background Art

[0002] Most of the maps on mobile phones and in-vehicle large screens currently used by people are standard-definition maps for human drivers, with few data elements and low accuracy, making it difficult to meet the application requirements of autonomous driving software. Although the high-precision maps for autonomous driving software meet the application requirements, they require an independent high-precision map navigation system and cannot reuse the very mature standard-definition navigation information on most current in-vehicle large screens. Summary of the Invention

[0003] This application provides a method for determining a map, a device for determining a map, a computer device, and a computer-readable storage medium.

[0004] The method for determining a map provided by this application includes:

[0005] Obtain a first map and a second map, where the fineness of the first map is higher than that of the second map;

[0006] Determine a current positioning reference point according to the second map;

[0007] Determine a first element index according to the first map and the positioning reference point, where the first element index is used to mark elements within a preset range of the positioning reference point;

[0008] Obtain a second element within a range of a first preset distance centered on the positioning reference point according to the first element index;

[0009] Determine a target map according to the second element and the positioning reference point.

[0010] In this way, this application obtains a positioning reference point on a map with low fineness, and then obtains all other elements within a certain range centered on this reference point on a map with high fineness. These elements and the positioning reference point together form a target map with high fineness. According to this method, all elements within a certain range centered on a certain point on a standard-definition map can be searched in a high-precision map, thereby forming a local high-precision map, conveniently realizing obtaining a high-precision map starting from standard-definition data, and thus solving the problem of reuse between standard-definition maps and high-precision maps.

[0011] After obtaining the second element within a range of a second preset distance centered on the positioning reference point according to the search index, the method further includes:

[0012] Obtain a third element associated with the second element according to the second element and the first element index;

[0013] The determining of the target map according to the second element and the positioning reference point includes:

[0014] Determine the target map according to the second element, the third element and the positioning reference point.

[0015] In this way, the present application can incorporate the elements associated with the second element into the target map, further enrich the content of the target map, improve the accuracy while avoiding information loss.

[0016] The determining of the first element index according to the first map and the positioning reference point includes:

[0017] Obtain a first element within a range of a second preset distance centered on the positioning reference point according to the first map;

[0018] In response to a grouping operation, group the first elements according to the element category;

[0019] In response to a logical organization operation, organize each group of the first elements into a retrieval operator to obtain the first element index.

[0020] In this way, the present application can group and logically organize the first elements according to the element category to form a first element index for improving the execution efficiency.

[0021] The determining of the first element index according to the first map and the positioning reference point includes:

[0022] Obtain a first element within a range of a second preset distance centered on the positioning reference point according to the first map;

[0023] In response to a grouping operation, group the first elements according to the area where the first elements are located on the first map;

[0024] In response to a logical organization operation, organize each group of the first elements into a retrieval operator to form the first element index.

[0025] In this way, the present application can group and logically organize the first elements according to the area where the first elements are located on the map to form a first element index for improving the execution efficiency.

[0026] The determining of the first element index according to the first map and the positioning reference point includes:

[0027] Determine a first map index according to the first map, where the first map index is used to improve the data processing efficiency of the first map;

[0028] Determine a first element index according to the first map index and the positioning reference point.

[0029] In this way, the present application provides another method for determining the first element index. The first map index is obtained by processing the element data on the first map, and the required data is determined based on the first map index to form the first element index.

[0030] The determining of the first map index according to the first map includes:

[0031] Obtain the elements within the first map according to the first map;

[0032] In response to the grouping operation, group the elements by category;

[0033] In response to the logical organization operation, organize each group of the elements into a retrieval operator to obtain the first map index.

[0034] In this way, the present application provides a method for determining the first map index by grouping and logical organization of the elements in the first map with higher accuracy.

[0035] The first map index adopts a multi-way search tree-like logical structure; the first map index can adjust the node range of the tree-like logical structure according to the area where the positioning reference point is located on the first map.

[0036] In this way, the present application provides a first map index that can be adaptive to different real-world situations.

[0037] The present application provides a map determination device, and the device includes

[0038] A data acquisition module, configured to acquire a first map and a second map;

[0039] An initial positioning module, configured to determine a current positioning reference point according to the second map;

[0040] A data processing module, configured to determine a first element index according to the first map and the positioning reference point;

[0041] An element positioning module, configured to acquire a second element within a range of a first preset distance centered on the positioning reference point according to the first element index;

[0042] A map determination module, configured to determine a target map according to the second element and the positioning reference point.

[0043] This application also relates to a computer device, which includes a memory and a processor. A computer program is stored in the memory. When the computer program is executed by the processor, the above method is implemented.

[0044] This application also relates to a computer-readable storage medium that stores a computer program. When the computer program is executed by one or more processors, the above method is implemented.

[0045] Additional aspects and advantages of the embodiments of this application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the embodiments of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The above and / or additional aspects and advantages of this application will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, where:

[0047] Figure 1 is a flowchart of the map determination method provided by this application;

[0048] Figure 2 is a flowchart of the map determination method provided by this application;

[0049] Figure 3 is a flowchart of the map determination method provided by this application;

[0050] Figure 4 is a schematic diagram of the modules of the map determination device provided by this application;

[0051] Figure 5 is an application scenario diagram of the map determination method provided for visiting relatives in this province. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] The following details the embodiments of this application. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary only for explaining the embodiments of this application and should not be construed as limiting the embodiments of this application.

[0053] This application provides a map determination method, including the following steps:

[0054] 01: Obtain a first map and a second map;

[0055] 02: Determine the current positioning reference point according to the second map;

[0056] 03: Determine the first element index according to the first map and the positioning reference point;

[0057] 04: Obtain a second element within a range of a first preset distance centered on the positioning reference point according to the first element index;

[0058] 05: Determine a target map according to the second element and the positioning reference point.

[0059] This application provides a map determination device 10. The map determination method provided by this application can be implemented by the map determination device 10. Specifically, the map determination device 10 includes a data acquisition module 11, an initial positioning module 12, a data processing module 13, an element positioning module 14, and a map determination module 15. The data acquisition module 11 is used to acquire a first map and a second map. The initial positioning module 12 is used to determine the current positioning reference point according to the second map. The data processing module 13 is used to determine the first element index according to the first map and the positioning reference point. The element positioning module 14 is used to obtain a second element within a range of a first preset distance centered on the positioning reference point according to the first element index. The map determination module 15 is used to determine the target map according to the second element and the positioning reference point.

[0060] This application provides a computer device, including a memory and a processor. The memory stores a computer program. The processor is used to acquire a first map and a second map, and is used to determine the current positioning reference point according to the second map, and is used to determine the first element index according to the first map and the positioning reference point, and is used to obtain a second element within a range of a first preset distance centered on the positioning reference point according to the first element index, and is used to determine the target map according to the second element and the positioning reference point.

[0061] Specifically, the present application is mainly used in the field of autonomous driving and is a solution proposed for the contradiction between the high-precision maps adopted by autonomous driving systems and the standard-definition maps commonly used by human drivers. The purpose is to generate a high-precision map within a certain range around the current positioning point based on the current positioning point on the standard-definition map. When there are enough current positioning points to form a navigation path, a relatively large-scale high-precision map generated based on the standard-definition map can meet all the needs of the autonomous driving system on the current navigation path. In the example, the first map is a high-precision map, and the second map is a standard-definition map, and the area ranges they represent are the same. Obtain the current positioning reference point from the second map, that is, from the standard-definition map, which can be specifically achieved through satellite positioning technologies such as GPS and Beidou, and no limitation is made here. Then find this positioning reference point on the first map and obtain the elements within a preset range around this positioning reference point on the first map. These elements are the first elements, and the logical retrieval operator composed of the first elements is the first element index. The preset range can be the entire map, or the map partition where the positioning reference point is located, or the elements within a certain distance range around the positioning reference point. The elements on the map refer to data packets directly representing objects such as signs, markings, buildings, and traffic signal devices in the real situation. After obtaining the first element index, use this index to determine the second elements within the first preset distance range centered on this positioning reference point. Generally, the value of the first preset distance is relatively small. The main reason is that this step is used to determine all the elements around the positioning reference point under the premise of high precision to generate the target map. Generally, the value of the first preset distance is between 80 and 150 meters, and generally takes 100 meters in the example. The second elements are the elements around the above-mentioned positioning reference point. The second elements and the positioning reference point together constitute a target map with high precision.

[0062] In this way, the present application can search for all the elements within a certain range centered on a certain point on the standard-definition map in the high-precision map, thereby forming a local high-precision map, and conveniently realizing obtaining a high-precision map starting from the standard-definition data, thus solving the reuse problem between the standard-definition map and the high-precision map.

[0063] After step 04, it further includes:

[0064] 041: According to the second elements and the first element index, obtain the third elements associated with the second elements;

[0065] Meanwhile, step 05 includes:

[0066] 051: According to the second elements, the third elements, and the positioning reference point, determine the target map.

[0067] The element positioning module 14 is further configured to obtain a third element associated with the second element according to the second element and the first element index; the map determination module 15 is further configured to determine a target map according to the second element, the third element, and the positioning reference point.

[0068] The processor is further configured to obtain a third element associated with the second element according to the second element and the first element index, and to determine a target map according to the second element, the third element, and the positioning reference point.

[0069] Specifically, the target map obtained only from the second element and the positioning reference point may have the problem of missing map elements. The reason is that compared with the high-precision map, the standard definition map may have elements that exist in the high-precision map but do not exist in the standard definition map due to differences in clarity. Therefore, other elements can be further supplemented based on the second element to solve this problem. In the example, all elements associated with the second element are obtained from the first element index and defined as the third element. Two associated elements refer to elements that are directly connected or have an inclusion relationship with each other on the map, such as a lane or a lane line in a certain road, a traffic light at a certain intersection, two directly connected or intersecting roads, etc. The third element, the second element, and the positioning reference point are jointly subjected to a map generation operation to obtain a target map with high precision.

[0070] In this way, the present application can incorporate elements associated with the second element into the target map, further enrich the content of the target map, improve the accuracy, and avoid information loss.

[0071] Step 03 includes:

[0072] 031: Obtain a first element within a range of a second preset distance centered on the positioning reference point according to the first map;

[0073] 032: In response to a grouping operation, group the first elements according to the element category or group the first elements according to the area where the first elements are located on the first map;

[0074] 033: In response to a logical organization operation, organize each group of first elements into a retrieval operator to obtain a first element index.

[0075] The data processing module 13 is further configured to obtain a first element within a range of a second preset distance centered on the positioning reference point according to the first map, and to group the first elements according to the element category or group the first elements according to the area where the first elements are located on the first map in response to a grouping operation, and to organize each group of first elements into a retrieval operator to obtain a first element index.

[0076] The processor is further configured to obtain first elements within a range of a second preset distance centered on the positioning reference point according to the first map, and to group the first elements according to element categories or group the first elements according to the regions where the first elements are located on the first map in response to a grouping operation, and to organize each group of first elements into a retrieval operator in response to a logical organization operation to obtain a first element index.

[0077] Specifically, the second preset distance is used to limit the amount of data. Generally, the value of the second preset range is between 1 km and 2 km, and 1.5 km can be taken in the example. If the second preset distance is too large, resulting in an excessive amount of data of the first elements, it may cause the hardware device used for map generation to report an error due to data overload during the map generation process, thereby causing the map generation process to be abnormal. For example, in the example, all elements within a range of 1.5 km centered on the positioning reference point are obtained from the first map and defined as the first elements. Next, in order to facilitate organizing the first elements into a first element index, the first elements need to be grouped in advance. Two grouping methods are provided in the example. One is to group according to the category of the first elements themselves. For example, the first elements are divided into groups such as traffic lights, lane lines, intersections, roads, buildings, etc. The category of each group is used as the label of the element itself, and then all elements are organized into a tree-like logical operator according to this label. The logical operator can use intersections and roads as nodes to spread out all the first elements in a tree-like structure; the other is to group according to the regions where the first elements are located on the first map. Generally, digital maps store data in a partitioned form, so directly using the partition name as the grouping label can naturally divide the first elements into several groups, and then spread out all the elements in a tree-like structure with regions and roads as nodes. This can efficiently generate a first element index.

[0078] In this way, the present application can group the first elements according to element categories or the regions where the first elements are located on the first map and perform logical organization to form a first element index, so as to improve the execution efficiency of the map generation process.

[0079] Step 03 further includes:

[0080] 034: Determine a first map index according to the first map;

[0081] 035: Determine a first element index according to the first map index and the positioning reference point.

[0082] The data processing module 13 is further configured to determine a first map index according to the first map, where the first map index is used to improve the data processing efficiency of the first map, and to determine a first element index according to the first map index and the positioning reference point.

[0083] The processor is also used to determine the first element index according to the first map index and the positioning reference point.

[0084] Specifically, in addition to the method described above, the first element index can also be directly obtained from the first map. In the example, the first map can also be directly converted into a first map index with a large amount of data. Although this will occupy a large amount of hardware space, the elements in the first map can be logically organized to form a logical index, and the efficiency of obtaining and organizing the first element through the index is higher. After obtaining the first map index, the first element is directly screened out within the index, and the original logical structure is maintained to directly obtain the first element index. This example is suitable for situations with high hardware conditions.

[0085] Thus, the present application provides another method for determining the first element index. The first map index is obtained by processing the element data on the first map, and the required data is determined based on the first map index to form the first element index.

[0086] Step 034 includes:

[0087] 0341: Obtain the elements within the first map according to the first map;

[0088] 0342: In response to the grouping operation, group the elements according to their categories;

[0089] 0343: In response to the logical organization operation, organize each group of elements into a retrieval operator to obtain the first map index.

[0090] The data processing module 13 is used to obtain the elements within the first map according to the first map, and to group the elements according to their categories in response to the grouping operation, and to organize each group of elements into a retrieval operator to obtain the first map index in response to the logical organization operation.

[0091] The processor is used to obtain the elements within the first map according to the first map, and to group the elements according to their categories in response to the grouping operation, and to organize each group of elements into a retrieval operator to obtain the first map index in response to the logical organization operation.

[0092] Specifically, for the first map index, in addition to grouping and logically organizing the elements in the first map by map area, the method of element classification can also be adopted. For example, the elements can be divided into groups such as traffic lights, lane lines, intersections, roads, buildings, etc., and the category of each group is used as the label of the element itself. In the example, as Figure 5 shown, taking the lane line element as an example, Figure 5It is a visual block diagram of the lane line element tree logic. The block diagram is divided into four areas numbered 1 to 4. Taking area 1 as an example: there are multiple rectangular boxes in the area. The first rectangular box with the largest range represents the geometric range occupied by at most 16 adjacent lane lines. The second rectangular box with the second largest range represents the geometric range occupied by at most 4 adjacent lane lines. The third rectangular box with the smallest range represents the geometric range occupied by 1 lane line. When it is necessary to query which lane lines are near the position indicated by the pentagram symbol in the figure, most of the lane lines in the first map that are not near this position can be conveniently filtered out, improving the retrieval efficiency.

[0093] Thus, the present application provides a method for determining a first map index by grouping and logically organizing elements in a first map with relatively high accuracy. The index obtained by this method, combined with the first map and the second map, can solve the problem of inconsistent elements in the standard definition map and the high-precision map.

[0094] The first map index adopts a multi-way search tree logic structure; the first map index can adjust the node range of the tree logic structure according to the area where the positioning reference point is located on the first map.

[0095] Specifically, in order to improve the retrieval efficiency or accuracy of the index, the logic structure of the first map index can select other logic structures, such as the multi-way search tree logic structure (B-tree), etc. And due to the too small or too large element density in some display situations, it may cause the range represented by the generated target map to be unsuitable for use by the autonomous driving system. Therefore, the first map index can identify the element density according to the area where the positioning reference point is located. If the element density is too large, the range of the screening nodes can be appropriately narrowed, and vice versa, the range of the screening nodes should be appropriately expanded to ensure that the geographical range represented by the generated target map is suitable for identification and use by the autonomous driving system.

[0096] The present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when called and executed by one or more processors, implements the above-mentioned map determination method.

[0097] All or part of the processes in the above-described implementation methods of this application can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above various methods. Among them, any reference to a memory, storage, database, or other medium used in the various implementation methods provided in this application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or an external cache. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0098] In the description of this specification, descriptions with reference to terms such as "certain embodiments", "in one example", "exemplarily", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiments or examples are included in at least one embodiment or example of this application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0099] Any process or method description shown in the flowchart or described in other ways herein can be understood to represent a module, segment, or part of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of this application includes additional implementations, where the functions can be executed in a substantially simultaneous manner or in the reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art of the embodiments of this application.

[0100] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A method for determining a map, characterized in that, The method includes: Obtaining a first map and a second map, where the fineness of the first map is higher than that of the second map; Determining a current positioning reference point according to the second map; Determining a first element index according to the first map and the positioning reference point, where the first element index is used to mark elements within a preset range of the positioning reference point; Obtaining a second element within a range of a first preset distance centered on the positioning reference point according to the first element index; Obtaining a third element associated with the second element according to the second element and the first element index; Determining a target map according to the second element, the third element, and the positioning reference point.

2. The method according to claim 1, wherein The determining a first element index according to the first map and the positioning reference point includes: Obtaining a first element within a range of a second preset distance centered on the positioning reference point according to the first map; In response to a grouping operation, grouping the first elements according to element categories; In response to a logical organization operation, organizing each group of the first elements into a retrieval operator to obtain the first element index.

3. The method according to claim 1, characterized in that, The determining a first element index according to the first map and the positioning reference point includes: Obtaining a first element within a range of a second preset distance centered on the positioning reference point according to the first map; In response to a grouping operation, grouping the first elements according to the regions where the first elements are located on the first map; In response to a logical organization operation, organizing each group of the first elements into a retrieval operator to obtain the first element index.

4. The method according to claim 1, wherein The determining a first element index according to the first map and the positioning reference point includes: Determining a first map index according to the first map, where the first map index is used to improve the data processing efficiency of the first map; Determining a first element index according to the first map index and the positioning reference point.

5. The method according to claim 4, wherein The determining a first map index according to the first map includes: Obtaining the elements within the first map according to the first map; In response to a grouping operation, grouping the elements according to categories; In response to a logical organization operation, organizing each group of the elements into a retrieval operator to obtain the first map index.

6. The method according to claim 4, characterized in that The first map index adopts a multi-way search tree-like logical structure; the first map index can adjust the node range of the tree-like logical structure according to the region where the positioning reference point is located on the first map.

7. A map determination device, characterized in that, The device includes A data acquisition module for obtaining a first map and a second map; An initial positioning module for determining a current positioning reference point according to the second map; A data processing module for determining a first element index according to the first map and the positioning reference point; An element positioning module for obtaining a second element within a range of a first preset distance centered on the positioning reference point according to the first element index; The element positioning module is further configured to obtain a third element associated with the second element according to the second element and the first element index; A map determination module, configured to determine a target map according to the second element, the third element, and the positioning reference point.

8. A computer device, characterized in that, The computer device includes a memory and a processor; the memory stores a computer program, and when the computer program is executed by the processor, the processor is caused to execute the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by one or more processors, the method according to any one of claims 1-6 is implemented.

Images