Map creation methods, navigation route rendering methods, and related products and devices

Abstract

This disclosure discloses a map creation method, a navigation route rendering method, and related products and devices. The map creation method includes: obtaining segments with ODD attributes on high-precision road sections from high-precision map data; determining standard-precision road segments matching the high-precision road segments in the standard-precision map data based on a pre-determined road segment matching relationship between the high-precision map data and standard-precision map data; determining matching segments of the segments in the standard-precision road segments based on the location information of the segments within the high-precision road segments; and assigning the ODD attributes of the segments to the matching segments of the standard-precision road segments. The solution provided in this disclosure can assign ODD attributes from high-precision map data to standard-precision map data, enabling related technologies implemented based on standard-precision map data (such as rendering) to utilize the ODD attributes to perform corresponding functions, thus expanding the application scenarios of standard-precision map data.

Description

Technical Field

[0001] This disclosure relates to the field of geographic information technology, and in particular to map production methods, navigation route rendering methods, and related products and devices. Background Technology

[0002] Currently, electronic maps are evolving from standard-precision maps (ordinary maps) to high-precision maps. Because high-precision maps have a lower coverage of the real world than ordinary maps, they cannot completely replace standard-precision maps in the short term. The Operational Design Domain (ODD) refers to the conditions and scope under which an autonomous driving system is designed to function, including vehicle speed, traffic conditions, road type, weather, and environment. Based on the relevant attributes of high-precision maps and following certain rules, autonomous driving segments can be created within the ODD. The inventors discovered that if autonomous driving segments could be rendered in electronic maps when users are driving, they could explicitly specify autonomous driving segments in their navigation routes or clearly understand the autonomous driving segments within their navigation or driving routes. However, due to the insufficient coverage of high-precision maps, existing electronic map rendering generally uses standard-precision maps, which do not possess ODD attributes and therefore cannot render autonomous driving segments in electronic maps. Therefore, a technical solution is needed to enable the rendering of autonomous driving segments in electronic maps.

[0003] Public content

[0004] In view of the above problems, this disclosure is made in order to provide a map making method, a navigation route rendering method, and related products and apparatus that overcome or at least partially solve the above problems.

[0005] In a first aspect, embodiments of this disclosure provide a map creation method, including:

[0006] Based on high-precision map data, obtain the segments with ODD attributes on high-precision road sections;

[0007] Based on the pre-determined road segment matching relationship between high-precision map data and standard-precision map data, standard-precision road segments that match the high-precision road segments are identified in the standard-precision map data;

[0008] Based on the location information of the section in the high-precision road section, a matching section of the section is determined in the standard-precision road section, and the ODD attribute of the section is assigned to the matching section of the standard-precision road section.

[0009] In some optional embodiments, when a high-precision road segment matches two or more topologically connected standard-precision road segments, the method further includes:

[0010] Based on the topological endpoints of the two or more standard road segments, the high-precision road segments are divided such that each segment of the high-precision road segment uniquely corresponds to one standard road segment. Furthermore, the positions and path length proportions of the segments with ODD attributes on the high-precision road segments in each segment of the high-precision road segments are obtained.

[0011] In some optional embodiments, determining the matching segment of the segment in the standard precision road segment based on the location information of the segment in the high-precision road segment specifically includes:

[0012] Based on the location and path length ratio of the section in the high-precision road section, and in accordance with the principle of equal proportion, the matching section of the section is determined in the standard-precision road section.

[0013] In some optional embodiments, the predetermined road segment matching relationship between the high-precision map data and the standard-precision map data includes:

[0014] Retrieve the high-precision road connecting two topologically adjacent high-precision road nodes in high-precision map data;

[0015] Obtain the standard-precision roads in the standard-precision map data that match the high-precision roads;

[0016] In the high-precision road, identify high-precision road segments that match the standard-precision road segments included in the standard-precision road, and establish a road segment matching relationship between the high-precision map data and the standard-precision map data.

[0017] In some optional embodiments, determining a high-precision road segment on the high-precision road that matches the standard-precision road segment included in the standard-precision road specifically includes:

[0018] If the standard precision road only includes one standard precision road segment, the high precision road is treated as a high precision road segment, and the high precision road segment is determined to match the standard precision road segment;

[0019] If the standard road includes more than one standard road segment, each standard road segment is projected onto the high-precision road to obtain a high-precision road segment that matches the standard road segment.

[0020] In some optional embodiments, the pre-determined road segment matching relationship between high-precision map data and standard-precision map data includes:

[0021] The road segment matching relationship between high-precision map data and standard-precision map data is determined in advance using a buffer intersection algorithm.

[0022] In some optional embodiments, it also includes:

[0023] When rendering electronic maps based on standard and detailed map data, the standard and detailed road segments with ODD attributes are rendered according to the preset rendering style.

[0024] Secondly, embodiments of this disclosure provide a navigation route rendering method, including:

[0025] Get navigation directions;

[0026] The navigation road segments included in the navigation route are matched with the high-precision map data produced based on the above map production method, and the matched navigation road segments with ODD attributes are rendered according to a preset rendering style.

[0027] Thirdly, embodiments of this disclosure provide a navigation route rendering method, including:

[0028] Based on the high-precision map data produced by the above map production method, navigation route planning is performed, and navigation road segments with ODD attributes are rendered according to the preset rendering style.

[0029] Fourthly, embodiments of this disclosure provide a map-making apparatus, comprising:

[0030] The acquisition module is used to acquire segments with ODD attributes on high-precision road sections from high-precision map data;

[0031] The first determining module is used to determine, based on the pre-determined road segment matching relationship between high-precision map data and standard-precision map data, the standard-precision road segment that matches the high-precision road segment in the standard-precision map data;

[0032] The second determining module is used to determine the matching segment of the segment in the standard precision road segment based on the location information of the segment in the high precision road segment, and to assign the ODD attribute of the segment to the matching segment of the standard precision road segment.

[0033] Fifthly, embodiments of this disclosure provide a navigation route rendering apparatus, comprising:

[0034] The acquisition module is used to obtain navigation routes;

[0035] The matching module is used to match the navigation road segments included in the navigation route obtained by the acquisition module with the high-precision map data produced based on the above map production method;

[0036] The rendering module is used to render the navigation road segments with ODD attributes matched by the matching module according to a preset rendering style.

[0037] Sixthly, embodiments of this disclosure provide a navigation route rendering apparatus, comprising:

[0038] The planning module is used to plan navigation routes based on the high-precision map data produced using the map production method described above.

[0039] The rendering module is used to render the navigation road segments with ODD attributes in the navigation route planned by the planning module according to a preset rendering style.

[0040] In a seventh aspect, embodiments of this disclosure provide a computer program product with navigation functionality, including a computer program / instruction that, when executed by a processor, implements the aforementioned map creation method or navigation route rendering method.

[0041] Eighthly, this disclosure provides a server, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described map creation method or navigation route rendering method.

[0042] The beneficial effects of the above-described technical solutions provided in this disclosure include at least the following:

[0043] (1) The map production method provided in this embodiment obtains segments with ODD attributes on high-precision road segments from high-precision map data; determines standard-precision road segments matching the high-precision road segments in the standard-precision map data according to a predetermined road segment matching relationship between high-precision map data and standard-precision map data; determines matching segments of the segments in the standard-precision road segments according to the location information of the segments in the high-precision road segments; and assigns the ODD attributes of the segments to the matching segments of the standard-precision road segments. Assigning the ODD attributes from high-precision map data to standard-precision map data simplifies the determination of ODD attributes in standard-precision map data and eliminates the data collection work required for determining ODD attributes, thus making the determination of ODD attributes in standard-precision map data efficient and cost-effective. At the same time, assigning the ODD attributes from high-precision map data to standard-precision map data enables related technologies (such as rendering) implemented based on standard-precision map data to complete corresponding functions using ODD attributes, expanding the application scenarios of standard-precision map data.

[0044] (2) The navigation route rendering method provided in this embodiment obtains a navigation route; matches the navigation road segments included in the navigation route with the high-precision map data produced based on the above-described map production method; and renders the matched navigation road segments with ODD attributes according to a preset rendering style. Alternatively, navigation route planning is performed based on the high-precision map data produced by the above-described map production method, and the navigation road segments with ODD attributes are rendered according to a preset rendering style. This allows users to understand in real time whether the section they are about to enter or have already entered is an autonomous driving section, and thus determine whether to switch to autonomous driving mode, improving the user's driving experience.

[0045] Other features and advantages of this disclosure will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the disclosure. The objects and other advantages of this disclosure may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0046] The technical solutions of this disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0047] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the embodiments of the present disclosure to explain the disclosure and do not constitute a limitation thereof. In the drawings:

[0048] Figure 1 This is a flowchart of the map creation method in Embodiment 1 of this disclosure;

[0049] Figure 2 This is a flowchart illustrating the specific implementation of the map creation method in Embodiment 2 of this disclosure;

[0050] Figure 3 This is an example diagram illustrating the determination of the automated driving section in Embodiment 2 of this disclosure;

[0051] Figure 4 This is another specific implementation flowchart of the map creation method in Embodiment 3 of this disclosure;

[0052] Figure 5 This is a schematic diagram of the map-making apparatus in an embodiment of the present disclosure;

[0053] Figure 6 This is a schematic diagram of the navigation route rendering device in an embodiment of the present disclosure;

[0054] Figure 7 This is a schematic diagram of another navigation route rendering device in an embodiment of this disclosure. Detailed Implementation

[0055] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0056] To address the issue that high-precision map data in existing technologies lacks ODD attributes, embodiments of this disclosure provide a map creation method, a navigation route rendering method, and related products and devices. These methods can assign ODD attributes from high-precision map data to high-precision map data, enabling related technologies (such as rendering) implemented based on high-precision map data to utilize ODD attributes to perform corresponding functions, thereby expanding the application scenarios of high-precision map data.

[0057] High-definition map (HD Map) data is electronic map data created for scenarios requiring high-definition map data, such as autonomous driving or assisted driving, and used for perception, localization, and control. It includes high-definition road geometry, lane geometry, lane marking geometry, road boundaries, roadside facilities, and road signs in the road layer. Standard definition map (SD Map) data, also known as ordinary map data, or navigation electronic maps or internet electronic maps, includes road layer attributes such as road geometry, road classification, road shape, and road name, as well as Points of Interest (POI), background, and text layers. High-definition map data has higher precision than standard definition map data.

[0058] Example 1

[0059] Embodiment 1 of this disclosure provides a map creation method, the process of which is as follows: Figure 1 As shown, it includes the following steps:

[0060] Step S11: Obtain the sections with ODD attributes on the high-precision road segments from the high-precision map data.

[0061] Specifically, "high-precision road segment" is a shorthand for road segments in high-precision map data for ease of description; "standard-precision road segment" refers to road segments in standard-precision map data.

[0062] Based on the relevant attributes in the high-precision map data, the autonomous driving road segments with ODD attributes can be determined according to certain rules. The embodiments of this disclosure are implemented on the basis of high-precision map data in which ODD attribute segments have been marked. It can be that the segments with ODD attributes on the high-precision road segments are directly obtained from the high-precision map data.

[0063] Step S12: Based on the pre-determined road segment matching relationship between high-precision map data and standard-precision map data, determine the standard-precision road segments that match the high-precision road segments in the standard-precision map data.

[0064] The matching relationship between high-precision map data and standard-precision map data includes matching road segments in both high-precision map data and standard-precision map data, meaning that both represent the same actual road segment.

[0065] Step S13: Based on the location information of the section in the high-precision road section, determine the matching section of the section in the standard-precision road section.

[0066] In one embodiment, it may include determining a matching segment of the segment in the standard precision road segment based on the position and path length proportion of the segment in the high precision road segment, according to the principle of equal proportion.

[0067] When there is a one-to-one correspondence between a high-precision road segment and a standard-precision road segment, that is, only one high-precision road segment matches the standard-precision road segment, and only one standard-precision road segment matches the high-precision road segment, then according to the position and path length ratio of the segment with ODD attribute on the high-precision road segment, the matching segment of the segment can be determined in the standard-precision road segment according to the principle of equal proportion.

[0068] Specifically, the location of a segment with the ODD attribute within a high-precision road segment refers to whether the segment with the ODD attribute is at the front, rear, or middle of the high-precision road segment; the proportion of the path length of a segment with the ODD attribute within a high-precision road segment can be the ratio of the path length of the segment with the ODD attribute to the path length of other segments within the same high-precision road segment.

[0069] In practical applications, due to the different methods for determining the matching relationship of road segments between high-precision map data and standard-precision map data, and the different rules for breaking road segments in high-precision map data and standard-precision map data, there may be situations where the matching high-precision road segments and standard-precision road segments are not in one-to-one correspondence. It is possible that one high-precision road segment matches two or more topologically connected standard-precision road segments, or two or more topologically connected high-precision road segments match one standard-precision road segment.

[0070] In one embodiment, when a high-precision road segment matches two or more standard-precision road segments with topological connections, the method further includes: dividing the high-precision road segment based on the topological endpoints of the two or more standard-precision road segments, such that each segment of the divided high-precision road segment uniquely corresponds to a standard-precision road segment; and obtaining the position and path length ratio of the segments with ODD attributes on the high-precision road segment in each segment of the divided high-precision road segment.

[0071] In one embodiment, when a standard precision road segment matches two or more high precision road segments with topological connections, the method further includes dividing the standard precision road segment based on the topological endpoints of the two or more high precision road segments, such that each segment of the divided standard precision road segment uniquely corresponds to a high precision road segment.

[0072] Specifically, the above-mentioned standard or high-precision road segments can be divided according to the principle of equal proportion.

[0073] Step S14: Assign the ODD attribute of the segment to the matching segment of the standard road segment.

[0074] After identifying the matching segments of the segments with ODD attributes in the refined road segments, the ODD attributes of the segments are assigned to the matching segments on the refined road segments, thus determining that the matching segments are autonomous driving segments. This achieves the identification of autonomous driving segments in the refined map data that have ODD attributes.

[0075] Specifically, the recording method of ODD attribute segments in high-precision map data and standard-precision map data, taking standard-precision map data as an example, can be as follows: record the shape points of the standard-precision road segment corresponding to one endpoint of the ODD attribute segment (the front or back endpoint needs to be marked) and the path length of the ODD attribute segment; or record the shape points of the standard-precision road segment corresponding to the two endpoints of the ODD attribute segment; or record all the shape points of the standard-precision road segment corresponding to the ODD attribute segment; optionally, other recording methods can be adopted depending on the recording situation of the standard-precision map data. The specific recording method of ODD attribute segments is not limited in this embodiment.

[0076] The map production method provided in Embodiment 1 of this disclosure obtains segments with ODD attributes on high-precision road segments from high-precision map data; determines standard-precision road segments matching the high-precision road segments in the standard-precision map data based on a pre-determined road segment matching relationship between the high-precision map data and standard-precision map data; determines matching segments of the segments in the standard-precision road segments based on the location information of the segments in the high-precision road segments; and assigns the ODD attributes of the segments to the matching segments of the standard-precision road segments. Assigning ODD attributes from high-precision map data to standard-precision map data simplifies the determination of ODD attributes in standard-precision map data and eliminates the data collection work required for ODD attribute determination, thus making the determination of ODD attributes in standard-precision map data efficient and low-cost. Simultaneously, assigning ODD attributes from high-precision map data to standard-precision map data allows related technologies implemented based on standard-precision map data (such as rendering) to utilize ODD attributes to complete corresponding functions, expanding the application scenarios of standard-precision map data.

[0077] In one embodiment, it may further include rendering the road segments with ODD attributes according to a preset rendering style when rendering the electronic map based on the standard map data.

[0078] When navigating using high-precision electronic map data, users can determine at any time whether they have entered or are about to enter a section where autonomous driving is possible, and thus decide whether to switch to autonomous driving mode, improving the user's driving experience. In one embodiment, it may also include updating sections with ODD attributes in the high-precision map data at set intervals.

[0079] Generally, the update frequency of high-precision map data is lower than that of standard-precision map data. However, the determination of segments with ODD attributes is based on the relevant attributes recorded in the high-precision map data. Therefore, the update frequency of the high-precision map data can be used as the standard. After the high-precision map data and the segments with ODD attributes it contains are updated, the segments with ODD attributes in the current standard-precision map data can be updated in accordance with the above method.

[0080] In one embodiment, the pre-determination of the road segment matching relationship between the high-precision map data and the standard-precision map data may include: obtaining a high-precision road connected by two topologically adjacent high-precision road nodes in the high-precision map data; obtaining a standard-precision road in the standard-precision map data that matches the high-precision road; determining a high-precision road segment on the high-precision road that matches the standard-precision road segment contained in the standard-precision road; and establishing a road segment matching relationship between the high-precision map data and the standard-precision map data.

[0081] Obtaining the standard-precision road that matches the high-precision road in the standard-precision map data can include determining the matching nodes of the nodes at both ends of the high-precision road in the standard-precision map data, and determining the standard-precision road that connects the two matching nodes in the standard-precision map data as the standard-precision road that matches the high-precision road.

[0082] In the process of identifying high-precision road segments that match the standard-precision road segments contained in the high-precision road, it can be specifically included as follows: if the standard-precision road includes only one standard-precision road segment, the high-precision road is treated as a single high-precision road segment, and the high-precision road segment is matched with the standard-precision road segment; if the standard-precision road includes more than one standard-precision road segment, each standard-precision road segment is projected onto the high-precision road to obtain the high-precision road segment that matches the standard-precision road segment.

[0083] Optionally, a buffer intersection algorithm can be used to establish the road segment matching relationship between high-precision map data and standard-precision map data. This embodiment does not limit the specific method for determining the road segment matching relationship between high-precision map data and standard-precision map data.

[0084] Due to the different methods for determining the matching relationship of road segments between high-precision map data and standard-precision map data, and the different rules for breaking road segments in high-precision map data and standard-precision map data, there may be a situation where one high-precision road segment matches two or more topologically connected standard-precision road segments, or two or more topologically connected high-precision road segments match one standard-precision road segment.

[0085] However, in practical applications, generally only one of the above situations will exist. When there is a situation in the road segment matching relationship between high-precision map data and standard-precision map data where one high-precision road segment matches two or more topologically connected standard-precision road segments, the method for creating standard-precision map data is applicable to the following embodiment two. When there is a situation in the road segment matching relationship between high-precision map data and standard-precision map data where two or more topologically connected high-precision road segments match one standard-precision road segment, the method for creating standard-precision map data is applicable to the following embodiment three.

[0086] Example 2

[0087] Embodiment 2 of this disclosure provides a specific implementation of a map creation method, the process of which is as follows: Figure 2 As shown, it includes the following steps:

[0088] Step S21: Obtain the sections with ODD attributes on the high-precision road segments from the high-precision map data.

[0089] Step S22: Based on the pre-determined road segment matching relationship between high-precision map data and standard-precision map data, determine the standard-precision road segments that match the high-precision road segments in the standard-precision map data.

[0090] Step S23: Determine whether the standard road segment that matches the high-precision road segment is a standard road segment with two or more topological connections.

[0091] If yes, proceed to step S24; otherwise, proceed directly to step S27.

[0092] Step S24: Based on the topological endpoints of two or more standard road segments that match the high-precision road segment, the high-precision road segment is segmented.

[0093] Specifically, this can include determining the projection points of the topological endpoints of the high-precision road segments in the high-precision map data, determining the matching shape points on the high-precision road segments based on the projection points, using the shape points as the dividing points of the high-precision road segments, and dividing the high-precision road segments so that each segment of the high-precision road segments uniquely corresponds to a high-precision road segment.

[0094] Alternatively, the high-precision road segment can be divided according to the path length ratio and arrangement order of each high-precision road segment that matches the high-precision road segment, following the principle of equal proportion.

[0095] Step S25: Obtain the position and path length percentage of the segments with ODD attributes on the high-precision road segment in each segment of the segmented high-precision road segment.

[0096] In step S24, during the segmentation of the high-precision road segment, if the segmentation point is located inside a segment with ODD attribute, then the ODD attribute segment is further segmented using that segmentation point to obtain the position and path length ratio of the ODD attribute segment on each segment of the high-precision road segment.

[0097] Step S26: For the segmented high-precision road segments with ODD attribute segments, determine the matching segment of the segment in the corresponding high-precision road segments based on the position information of the ODD attribute segments in the segmented high-precision road segments.

[0098] The ODD attribute segment mentioned above may be the original segment or a segment after splitting.

[0099] Reference Figure 3 As shown, the high-precision road segment HD link (AB) in the high-precision map data matches two standard-precision road segments SD links (SD link1 and SD link2) in the standard-precision map data. The high-precision road segment HD link has an ODD attribute segment HD odd range (autonomous driving segment, i.e., CD segment). Based on the number of SD links (2) and the path length ratio between SD link1 and SD link2, the HD link is split according to the principle of equal proportion. The matching split point E in the HD link is determined to be E', resulting in two HD links (AE' and E'B). Since the split point E' is inside the autonomous driving section, the HD link is split along with its included autonomous driving section HD odd range, resulting in HD range1 (CE') and HD range2 (E'D). For HD range1, based on the path length ratio between HD range1 and other sections AC in the high-precision road section AE', and the position of HD range1 in the high-precision road section AE', the matching section of HD range1 in the high-precision road section SD link1 in the high-precision map data is determined to be C'E, i.e., SD link1 range, according to the principle of proportionality. For HD range2, based on the path length ratio between HD range2 and other sections DB in the high-precision road section E'B, and the position of HD range2 in the high-precision road section E'B, the matching section of HD range2 in the high-precision road section SD link2 in the high-precision map data is determined to be ED', i.e., SD link2 range, according to the principle of proportionality.

[0100] Figure 3This is just an example of the process of determining the autonomous driving section in the high-precision map data. In reality, due to the difference in precision between high-precision map data and high-precision map data, the path lengths of the road segments that match the two are generally not exactly the same.

[0101] Step S27: Based on the location information of the section in the high-precision road section, determine the matching section of the section in the standard-precision road section.

[0102] Step S28: Assign the ODD attribute of the segment to the matching segment of the standard road segment.

[0103] Specifically, it can be done by traversing each high-precision road segment in the high-precision map data. When the segment with the ODD attribute is currently being traversed, subsequent steps S22 to S28 are executed. Alternatively, it can be done by first traversing all high-precision road segments in the high-precision map data, determining all high-precision road segments with the ODD attribute, and then executing steps S22 to S28 for each high-precision road segment with the ODD attribute.

[0104] Example 3

[0105] Embodiment 3 of this disclosure provides a specific implementation of another map creation method, the process of which is as follows: Figure 4 As shown, it includes the following steps:

[0106] Step S41: Traverse the standard road segments in the standard map data, and determine the high-precision road segments that match the standard road segments in the high-precision map data according to the pre-determined road segment matching relationship between the high-precision map data and the standard map data.

[0107] Step S42: Determine whether there is at least one segment with the ODD attribute among the matched high-precision road segments.

[0108] If yes, proceed to step S43; otherwise, continue with step S41.

[0109] Step S43: Determine whether there is only one matching high-precision road segment.

[0110] If not, proceed to step S44; if yes, proceed to step S45.

[0111] Step S44: Obtain the topological endpoints of two or more high-precision road segments that are topologically connected to the standard road segment, and segment the standard road segment based on the obtained topological endpoints.

[0112] Specifically, this can include determining the projection points of the topological endpoints of high-precision road segments in the high-precision map data, determining matching shape points on the high-precision road segments based on the projection points, using these shape points as the dividing points of the high-precision road segments, and dividing the high-precision road segments so that each segment of the high-precision road segments uniquely corresponds to a high-precision road segment.

[0113] Alternatively, the standard road segment can be divided according to the proportion and arrangement order of the path lengths of each high-precision road segment that matches the standard road segment, following the principle of equal proportion.

[0114] Step S45: Based on the location information of the segment with ODD attribute in the high-precision road segment, determine the matching segment of the segment in the standard-precision road segment.

[0115] Step S46: Assign the ODD attribute of the segment to the matching segment of the standard road segment.

[0116] Specifically, the aforementioned high-precision road segment may be the original high-precision road segment or a segmented high-precision road segment. When only one high-precision road segment is determined to match in step S43, the aforementioned high-precision road segment is the original high-precision road segment; when more than one high-precision road segment is determined to match in step S43, the aforementioned high-precision road segment is a segmented high-precision road segment that matches a high-precision road segment with ODD attribute.

[0117] Step S47: Continue until all the refined road segments in the refined map data have been traversed.

[0118] Optionally, one can first complete the traversal of all the high-precision road segments in the high-precision map data, determine at least one high-precision road segment that matches each high-precision road segment, and then execute steps S42 to S46 for each set of high-precision road segments and at least one matching high-precision road segment.

[0119] Based on the inventive concept of this disclosure, embodiments of this disclosure also provide a navigation route rendering method, including:

[0120] Obtain the navigation route; match the navigation road segments included in the navigation route with the high-precision map data produced based on the above map production method, and render the matched navigation road segments with ODD attributes according to the preset rendering style.

[0121] Based on the inventive concept of this disclosure, embodiments of this disclosure also provide another navigation route rendering method, including:

[0122] Based on the high-precision map data produced by the above map production method, navigation route planning is performed, and navigation road segments with ODD attributes are rendered according to the preset rendering style.

[0123] Based on the inventive concept of this disclosure, embodiments of this disclosure also provide a map-making apparatus, the structure of which is as follows: Figure 5 As shown, it includes:

[0124] The acquisition module 51 is used to acquire the segments with ODD attributes on high-precision road segments from high-precision map data;

[0125] The first determining module 52 is used to determine, based on the pre-determined road segment matching relationship between high-precision map data and standard-precision map data, a standard-precision road segment in the standard-precision map data that matches the high-precision road segment;

[0126] The second determining module 53 is used to determine the matching segment of the segment in the standard precision road segment based on the location information of the segment in the high precision road segment, and to assign the ODD attribute of the segment to the matching segment of the standard precision road segment.

[0127] In one embodiment, the above-described apparatus further includes a segmentation module 54, configured to:

[0128] When a high-precision road segment matches two or more standard-precision road segments with topological connections, the high-precision road segment is divided based on the topological endpoints of the two or more standard-precision road segments, so that each segment of the divided high-precision road segment uniquely corresponds to a standard-precision road segment, and the position and path length ratio of the segments with ODD attributes on the high-precision road segment in each segment of the divided high-precision road segment are obtained.

[0129] In one embodiment, the second determining module 52, based on the location information of the segment in the high-precision road segment, determines the matching segment of the segment in the standard-precision road segment, specifically for:

[0130] Based on the location and path length ratio of the section in the high-precision road section, and in accordance with the principle of equal proportion, the matching section of the section is determined in the standard-precision road section.

[0131] In one embodiment, the above apparatus further includes a rendering module 55, configured to:

[0132] When rendering electronic maps based on standard and detailed map data, the standard and detailed road segments with ODD attributes are rendered according to the preset rendering style.

[0133] Based on the inventive concept of this disclosure, embodiments of this disclosure also provide a navigation route rendering device, the structure of which is as follows: Figure 6 As shown, it includes:

[0134] Module 61 is used to obtain navigation routes;

[0135] The matching module 62 is used to match the navigation road segments included in the navigation route obtained by the acquisition module 61 with the high-precision map data produced based on the above map production method.

[0136] The rendering module 63 is used to render the navigation road segments with ODD attributes matched by the matching module 62 according to a preset rendering style.

[0137] Based on the inventive concept of this disclosure, embodiments of this disclosure also provide a navigation route rendering device, the structure of which is as follows: Figure 7 As shown, it includes:

[0138] Planning module 71 is used for navigation route planning based on the high-precision map data produced by the above map production method;

[0139] The rendering module 72 is used to render the navigation road segments with ODD attributes in the navigation route planned by the planning module 71 according to a preset rendering style.

[0140] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0141] Based on the inventive concept of this disclosure, embodiments of this disclosure also provide a computer program product with navigation function, including a computer program / instruction that, when executed by a processor, implements the above-described map creation method or navigation route rendering method.

[0142] Based on the inventive concept of this disclosure, embodiments of this disclosure also provide a server, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described map creation method or navigation route rendering method.

[0143] Unless otherwise specifically stated, terms such as processing, calculation, operation, determination, display, etc., may refer to the actions and / or processes of one or more processing or computing systems or similar devices that represent the manipulation and conversion of data representing physical (e.g., electronic) quantities within the registers or memory of the processing system into other data similarly representing physical quantities within the memory, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals can be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, symbols, and chips mentioned throughout the above description can be represented by voltage, current, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0144] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.

[0145] In the above detailed description, various features are combined together in a single embodiment to simplify this disclosure. This approach to disclosure should not be construed as reflecting an intention that embodiments of the claimed subject matter require more features than are explicitly stated in each claim. Rather, as reflected in the appended claims, this disclosure is in a state of having fewer features than all of the features of a single disclosed embodiment. Therefore, the appended claims are hereby explicitly incorporated into the detailed description, with each claim representing a separate preferred embodiment of this disclosure.

[0146] Those skilled in the art will also understand that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in alternative ways for each specific application; however, such implementation decisions should not be construed as departing from the scope of this disclosure.

[0147] The steps of the methods or algorithms described in conjunction with the embodiments herein can be directly embodied in hardware, software modules executed by a processor, or a combination thereof. The software modules can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. Alternatively, the processor and storage medium can exist as discrete components in the user terminal.

[0148] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. This software code can be stored in memory units and executed by a processor. The memory units can be implemented within the processor or outside the processor; in the latter case, they are communicatively coupled to the processor via various means, as is well known in the art.

[0149] The foregoing description includes examples of one or more embodiments. It is certainly impossible to describe all possible combinations of components or methods in order to describe the above embodiments, but those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. Furthermore, the term “comprising” as used in the specification or claims is interpreted in a manner similar to the term “including,” as it is understood when used as a conjunction in the claims. Additionally, the use of any term “or” in the specification of the claims is intended to mean “non-exclusive or.” The terms “first,” “second,” and “third” are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

Claims

1. A map-making method, wherein, include: From high-precision map data, obtain the segments with ODD attributes on high-precision road segments, wherein the high-precision road segments are road segments in the high-precision map data; Based on the pre-determined road segment matching relationship between high-precision map data and standard-precision map data, standard-precision road segments that match the high-precision road segments are determined in the standard-precision map data, wherein the standard-precision road segments are road segments in the standard-precision map data; Based on the location information of the section in the high-precision road section, the matching section of the section is determined in the standard-precision road section, and the ODD attribute of the section is assigned to the matching section of the standard-precision road section, so as to realize the determination of the autonomous driving section in the standard-precision map data that has the ODD attribute.

2. The method as described in claim 1, wherein, When a high-precision road segment matches two or more standard-precision road segments with topological connections, the method further includes: Based on the topological endpoints of the two or more standard road segments, the high-precision road segments are divided such that each segment of the high-precision road segment uniquely corresponds to one standard road segment. Furthermore, the positions and path length proportions of the segments with ODD attributes on the high-precision road segments in each segment of the high-precision road segments are obtained.

3. The method as described in claim 1 or 2, wherein, The step of determining the matching segment of the segment in the standard precision road segment based on the location information of the segment in the high-precision road segment specifically includes: Based on the location and path length ratio of the section in the high-precision road section, and in accordance with the principle of equal proportion, the matching section of the section is determined in the standard-precision road section.

4. The method of claim 3, wherein, The pre-determined road segment matching relationship between the high-precision map data and the standard-precision map data includes: Retrieve the high-precision road connecting two topologically adjacent high-precision road nodes in high-precision map data; Obtain the standard-precision roads that match the high-precision roads from the standard-precision map data; In the high-precision road, identify the high-precision road segments that match the standard-precision road segments included in the standard-precision road, and establish a road segment matching relationship between the high-precision map data and the standard-precision map data.

5. The method of claim 3, wherein, The pre-determined road segment matching relationship between high-precision map data and standard-precision map data includes: The road segment matching relationship between high-precision map data and standard-precision map data is determined in advance using a buffer intersection algorithm.

6. The method of claim 3, wherein, Also includes: When rendering electronic maps based on standard and detailed map data, the standard and detailed road segments with ODD attributes are rendered according to the preset rendering style.

7. A method for rendering navigation routes, wherein, include: Get navigation directions; The navigation route includes navigation road segments that are matched with high-precision map data produced based on any one of the map production methods of claims 1 to 6, and the matched navigation road segments with ODD attributes are rendered according to a preset rendering style.

8. A method for rendering navigation routes, wherein, include: Navigation route planning is performed based on the high-precision map data produced by any one of the map production methods of claims 1 to 6, and the navigation road segments with ODD attributes are rendered according to a preset rendering style.

9. A map-making apparatus, wherein, include: The acquisition module is used to acquire segments with ODD attributes on high-precision road segments from high-precision map data, wherein the high-precision road segments are road segments in the high-precision map data; The first determining module is used to determine, based on the pre-determined road segment matching relationship between high-precision map data and standard-precision map data, a standard-precision road segment that matches the high-precision road segment in the standard-precision map data, wherein the standard-precision road segment is a road segment in the standard-precision map data; The second determining module is used to determine the matching segment of the segment in the standard precision road segment based on the location information of the segment in the high precision road segment, and assign the ODD attribute of the segment to the matching segment of the standard precision road segment, so as to realize the determination of the segment with ODD attribute in the standard precision map data as the segment for autonomous driving.

10. A computer program product with navigation function, comprising a computer program / instructions, wherein, When the program / instruction is executed by the processor, it implements the map creation method according to any one of claims 1 to 6, or the navigation route rendering method according to claim 7 or 8.

11. A server, wherein, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the map making method according to any one of claims 1 to 6, or to implement the navigation route rendering method according to claim 7 or 8.

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