Navigation processing method, device and electronic equipment

Abstract

The present disclosure provides a navigation processing method, device and electronic device, which relate to the field of data processing technology, and specifically to the field of autonomous driving technology. The specific implementation scheme is: obtaining N first links located at a target intersection in a first map, the target intersection is an intersection in a first navigation route of a driving object, and the first navigation route is a navigation route planned on a second map; when the driving object travels to a first target position based on the first navigation route, based on the starting node of the second link, a target link matching the second link is screened out from the N first links, the second link is a link located at the target intersection in the first navigation route and has the least mileage from the driving object, and the distance of the first target position relative to the starting node of the second link is within a preset range; when the driving object travels to a second target position based on the first navigation route, the driving object is navigated based on the target link.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, in particular to the field of autonomous driving technology, and specifically to a navigation processing method, device and electronic device. Background Art

[0002] With the rapid development of navigation technology, navigation products have been widely used in autonomous driving vehicles, which can travel according to the navigation routes planned by navigation products.

[0003] Typically, the navigation deployed by autonomous vehicles is standard definition (SD) map navigation, while the navigation required by autonomous vehicles is high definition (HD) map navigation. Therefore, SD roads need to be converted into HD roads for navigation of autonomous vehicles.

[0004] When an autonomous driving vehicle drives to an intersection, it usually dynamically obtains the HD road association results of the SD roads in the intersection based on the connectivity relationship of the SD map, and navigates at the intersection based on the associated HD roads. Summary of the invention

[0005] The present disclosure provides a navigation processing method, device and electronic device.

[0006] According to a first aspect of the present disclosure, a navigation processing method is provided, comprising:

[0007] Obtain N first links located at a target intersection in the first map, where the target intersection is an intersection in a first navigation route of the driving object, where the first navigation route is a navigation route planned on the second map, where the road position accuracy of the first map is greater than the road position accuracy of the second map, and N is a positive integer;

[0008] When the driving object travels to a first target location based on the first navigation route, a target link matching the second link is screened out from the N first links based on a starting node of the second link, the second link being a link in the first navigation route that is located at the target intersection and has the least mileage from the driving object, and the distance of the first target location relative to the starting node of the second link is within a preset range;

[0009] When the traveling object travels to a second target position based on the first navigation route, the traveling object is navigated based on the target link, and the second target position is the position of the starting node of the second link.

[0010] According to a second aspect of the present disclosure, there is provided a navigation processing device, comprising:

[0011] an acquisition module, configured to acquire N first links located at a target intersection in a first map, wherein the target intersection is an intersection in a first navigation route of a traveling object, wherein the first navigation route is a navigation route planned on a second map, wherein the road position accuracy of the first map is greater than the road position accuracy of the second map, and N is a positive integer;

[0012] a screening module, configured to screen out a target link matching the second link from the N first links based on a starting node of a second link when the traveling object travels to a first target location based on the first navigation route, the second link being a link in the first navigation route that is located at the target intersection and has the least mileage from the traveling object, and the distance of the first target location relative to the starting node of the second link being within a preset range;

[0013] The navigation module is used to navigate the traveling object based on the target link when the traveling object travels to a second target position based on the first navigation route, and the second target position is the position of the starting node of the second link.

[0014] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0015] at least one processor; and

[0016] a memory communicatively connected to at least one processor; wherein,

[0017] The memory stores instructions that can be executed by at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform any method in the first aspect.

[0018] According to a fourth aspect of the present disclosure, an autonomous driving vehicle is provided, comprising the electronic device as described in the third aspect.

[0019] According to a fifth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause a computer to execute any one of the methods in the first aspect.

[0020] According to a sixth aspect of the present disclosure, a computer program product is provided, comprising a computer program, which implements any one of the methods in the first aspect when executed by a processor.

[0021] The technology disclosed in the present invention solves the problem of poor navigation effect of autonomous driving vehicles at intersections, thereby improving the navigation effect of autonomous driving vehicles at intersections.

[0022] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0024] Figure 1 is a flowchart of a navigation processing method according to the first embodiment of the present disclosure;

[0025] Figure 2 It is a schematic diagram of the relationship between links at the intersection;

[0026] Figure 3 It is a schematic diagram of the relationship between links at the turning intersection;

[0027] Figure 4 is a flowchart of a navigation processing method according to a specific example of the first embodiment of the present invention;

[0028] Figure 5 is a structural diagram of a navigation processing device according to a second embodiment of the present disclosure;

[0029] Figure 6 is a schematic block diagram of an example electronic device for implementing an embodiment of the present disclosure. DETAILED DESCRIPTION

[0030] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0031] First embodiment

[0032] like Figure 1 As shown, the present disclosure provides a navigation processing method, comprising the following steps:

[0033] Step S101: Obtain N first links located at a target intersection in a first map, where the target intersection is an intersection in a first navigation route of a driving object, where the first navigation route is a navigation route planned on a second map, and where the road position accuracy of the first map is greater than the road position accuracy of the second map.

[0034] Wherein, N is a positive integer.

[0035] In this embodiment, the navigation processing method relates to the field of data processing technology, and in particular to the field of autonomous driving technology, and can be widely used in navigation scenarios. The navigation processing method of the disclosed embodiment can be executed by the navigation processing device of the disclosed embodiment. The navigation processing device of the disclosed embodiment can be configured in any electronic device to execute the navigation processing method of the disclosed embodiment.

[0036] The first map may refer to a high-precision electronic map, namely, an HD map, or may be a lane-level electronic map. The first map in the following embodiment will be described using an HD map as an example.

[0037] The target intersection may refer to an intersection in the first navigation route of the driving object, and the target intersection may be a crossroad, a T-shaped intersection, a turning intersection, etc. The driving object may refer to any vehicle, such as an autonomous driving vehicle, and the first navigation route may be a navigation route planned on the second map, and the second map may be a standard navigation electronic map, i.e., an SD map, and the road position accuracy of the SD map is less than that of the HD map.

[0038] The first link can be a high-precision link, i.e., an HD link. The difference in road morphology between an HD link and a low-precision link, i.e., an SD link, lies not only in the difference in physical geometric attributes, but also in the difference in semantic attributes. For example, compared with an SD link, an HD link has richer and more accurate geometric attributes of objects. For example, the location planning of an HD link is more accurate, the depiction of traffic signs on an HD link is richer, and its semantic attributes are more detailed. For example, an HD link plans the link at the lane level, while an SD link plans the link at the road level. The semantic planning granularity of an HD link is more detailed.

[0039] Taking an intersection as an example, when planning the intersection on an SD map, its shape is usually a "well" shape with 4 links, while when planning the intersection on an HD map, its shape can be a mesh shape with 12 links or even more.

[0040] The acquisition timing of the N first links may be when the navigation processing device acquires the first navigation route, and the target intersection may be all the intersections that need to be passed in the first navigation route, that is, when navigating based on the first navigation route, the HD links at all the intersections have been pre-acquired. The acquisition timing of the N first links may also be when the driving object drives to the vicinity of the intersection based on the first navigation route, and the target intersection may be the intersection that the driving object is about to pass in the first navigation route.

[0041] The navigation processing device can be deployed in an autonomous driving vehicle. The navigation processing device is deployed with a standard navigation electronic map service, and users can use the service to plan navigation routes.

[0042] In one embodiment, when the navigation processing device receives a user's determination to navigate based on the first navigation route, the navigation processing device may send the first navigation route to the service background, and the service background may send the HD link that matches the SD link outside the intersection in the first navigation route to the navigation processing device, and at the same time, may send the HD link at the intersection to the navigation processing device for the navigation processing device to match the HD link at the intersection. Accordingly, the navigation processing device may receive N first links.

[0043] In another embodiment, when the navigation processing device detects that the driving object is near the intersection of the first navigation route, the location information can be sent to the service background, and the service background can send the HD link at the target intersection to the navigation processing device for the navigation processing device to match the HD link at the target intersection. Accordingly, the navigation processing device can receive N first links.

[0044] It should be noted that the first link may be represented by data in a corresponding format. Accordingly, obtaining N first links may refer to obtaining data used to represent the N first links.

[0045] Step S102: When the traveling object travels to the first target position based on the first navigation route, a target link matching the second link is screened out from the N first links based on the starting node of the second link, the second link being the link in the first navigation route that is located at the target intersection and has the shortest mileage from the traveling object, and the distance of the first target position relative to the starting node of the second link is within a preset range.

[0046] In this step, the second link may be a link in the first navigation route that is located at the target intersection and has the shortest mileage from the driving object, and the second link may be an SD link. The navigation processing device may monitor the position of the driving object, specifically, the distance between the position of the driving object and the starting node of the second link.

[0047] When it is detected that the driving object travels to a position within a preset range relative to the starting node of the second link based on the first navigation route, that is, when the distance between the position of the driving object and the starting node of the second link is within the preset range, HD link matching of the second link at the target intersection can be performed based on the starting node of the second link. The preset range can be set according to actual conditions, such as within a range of 100 meters to 500 meters, and is not specifically limited here.

[0048] The starting node of the second link can be used as a constraint node to perform node matching with the N first links. In an optional implementation, dual-node matching can be performed, and the starting node of the second link can be matched with the starting node of each of the N first links, and the terminating node of the second link can be matched with the terminating node of each of the N first links. When both the starting node and the terminating node are successfully matched, the first link with the successful dual-node matching is determined as the target link.

[0049] In another optional implementation, single-node matching can be performed to determine whether the first link is connected to the starting node of the second link. If connected to the starting node of the second link, it can be determined that the first link is successfully matched with the second link node. Accordingly, the first link with successful single-node matching is determined as the target link.

[0050] It should be noted that the first link that matches the second link among the N first links may be one, two or even more. When there are two or more first links that match the second link, the best matching first link may be further selected from the first links that match the second link as the target link.

[0051] Step S103: When the traveling object travels to a second target location based on the first navigation route, the traveling object is navigated based on the target link, and the second target location is the location of the starting node of the second link.

[0052] In this step, when the target link is matched, the navigation processing device may continue to monitor the position of the traveling object, and specifically may monitor the distance between the position of the traveling object and the starting node of the second link.

[0053] When it is monitored that the traveling object travels to the position of the starting node of the second link based on the first navigation route, the traveling object can be navigated based on the target link to provide the traveling object with a more precise and accurate HD link at the target intersection, thereby avoiding the situation where the traveling object has disordered driving at the target intersection due to insufficient accuracy of the link used for navigation and link matching errors.

[0054] In this embodiment, N first links located at the target intersection in the first map are obtained, and when the driving object travels to the first target location based on the first navigation route, a target link matching the second link is screened out from the N first links based on the starting node of the second link, and when the driving object travels to the second target location based on the first navigation route, the driving object is navigated based on the target link. In this way, the HD link matching accuracy at the intersection can be improved, the probability of accidents occurring at the intersection for the driving object can be reduced, and the driving safety of the driving object can be improved.

[0055] Optionally, the step S102 specifically includes:

[0056] Determine M candidate links from the N first links, where the M candidate links match the start node of the second link, and M is a positive integer;

[0057] A target link matching the second link is screened out from the M candidate links.

[0058] In this implementation, since there may be two or more first links among the N first links that match the starting node of the second link during the node matching process, the first link among the N first links that matches the starting node of the second link can be determined as a candidate link, thereby obtaining M candidate links.

[0059] The matching of the starting nodes of the first link and the second link may refer to that the starting node of the first link is consistent with the starting node of the second link, or may refer to that the starting nodes of the first link and the second link are connected, which is not specifically limited here.

[0060] Accordingly, the link that best matches the second link can be further selected from the M candidate links as the target link, thereby further improving the matching accuracy of the HD link.

[0061] Optionally, before determining the M candidate links from the N first links, the method further includes:

[0062] Determining the intersection type of the target intersection based on the connectivity relationship of the N first links;

[0063] The determining M candidate links from the N first links includes:

[0064] Based on the intersection type, M candidate links are determined from the N first links.

[0065] In this embodiment, the connectivity relationship of the N first links may refer to the connection relationship of the N first links, and the intersection type may include two types, namely the first type and the second type. In the HD map, the first type may indicate that at least two of the N first links have an intersection, and in the SD map, the first type may indicate that the second link has an intersection with other SD links at the target intersection, and the intersection node may be a confluence node or a divergence node, that is, there is a confluence node or a divergence node between the second link and other links located at the target intersection. The first type of intersection may be a crossroads, a T-shaped intersection, etc.

[0066] Take the crossroads as an example. Figure 2 As shown, the nodes of the second link 201 except the starting node 2011 and the SD link 203 at the target intersection 202 have an intersection node 2012 , which can be a converging node or a diverging node, and the intersection node can be the terminating node of the second link 201 .

[0067] In the HD map, the second type can represent that there is no intersection between any two links among the N first links, and in the SD map, the second type can represent that there is no intersection between the second link and other SD links at the target intersection, that is, there is no intersection node or divergence node between the second link and other SD links at the target intersection. The second type of intersection can be a turning intersection, such as a dead-end intersection.

[0068] Take the turning intersection as an example. Figure 3 As shown, the link 301 before the turn and the link 302 after the turn can both be part of the second link, that is, at the turning intersection 303, the link 302 after the turn is connected to the starting node 3011 of the second link under the bridge of the link 301 before the turn.

[0069] When the connectivity relationship of the N first links indicates that at least two links have an intersection, the intersection type of the target intersection is determined to be the first type; when the connectivity relationship of the N first links indicates that any two links do not have an intersection, the intersection type of the target intersection is determined to be the second type.

[0070] Accordingly, M candidate links can be determined from N first links based on the intersection type of the target intersection, and the method of determining M candidate links from N first links can be different according to the intersection type of the target intersection. For example, when the intersection type of the target intersection is the first type, the starting node and the ending node of the second link can be used as constraint nodes, and the candidate link can be determined from the N first links by double-node matching. For another example, when the intersection type of the target intersection is the second type, the starting node of the second link can be used as a constraint node, and the candidate link can be determined from the N first links by single-node matching.

[0071] In this implementation, by combining the intersection type of the target intersection, M candidate links are determined from the N first links, which can further improve the accuracy of HD link matching.

[0072] Optionally, the determining, based on the intersection type, M candidate links from the N first links includes at least one of the following:

[0073] When the intersection type is the first type, a link whose starting node is consistent with the starting node of the second link and whose ending node is consistent with the ending node of the second link among the N first links is determined as a candidate link, to obtain the M candidate links, wherein the first type indicates that there is a converging node or a diverging node between the second link and other links located at the target intersection;

[0074] When the intersection type is the second type, the link connected to the starting node of the second link among the N first links is determined as a candidate link to obtain the M candidate links, and the second type characterizes that there is no intersection node and divergence node between the second link and other links located at the target intersection.

[0075] In this implementation, when the target intersection type is the first type, the starting node and the ending node of the second link can be used as constraint nodes, and a candidate link can be determined from the N first links by double node matching. Specifically, the link whose starting node among the N first links is consistent with the starting node of the second link, and whose ending node is consistent with the ending node of the second link can be determined as a candidate link. Among them, the ending node of the second link can be a junction node or a divergence node with other SD links at the target intersection.

[0076] When the intersection type of the target intersection is the second type, the starting node of the second link can be used as a constraint node, and a candidate link can be determined from the N first links by single node matching. Specifically, the link connected to the starting node of the second link among the N first links can be determined as a candidate link.

[0077] In this implementation, depending on the type of intersection at the target intersection, the starting node of the second link is used as a constraint node, and a candidate link is determined from the N first links by a double-node matching method and a single-node matching method, respectively. In this way, the candidate links can be screened from the N first links by node matching, and then the target link can be screened.

[0078] Optionally, when the intersection type is the first type, selecting a target link matching the second link from the M candidate links includes:

[0079] Acquire a link node at a preset position in the second link to obtain K first link nodes, where K is a positive integer;

[0080] For each candidate link in the M candidate links, obtain K second link nodes in the candidate link that are matched one-to-one with the K first link nodes; based on the K first link nodes and the K second link nodes, calculate the distance between the candidate link and the second link;

[0081] The candidate link with the smallest distance from the second link among the M candidate links is determined as the target link.

[0082] In this implementation manner, when the intersection type of the target intersection is the first type, the target link can be screened from the M candidate links by distance matching.

[0083] Specifically, K link nodes corresponding to K preset positions in the second link can be obtained one by one to obtain K first link nodes. The preset position can be a pre-stored position in the second link, that is, the first link node is a pre-stored node in the second link. The preset position can also be a position evenly divided in the second link, that is, points can be evenly inserted in the second link in a specified number to obtain K first link nodes.

[0084] For each candidate link in the M candidate links, the second link node that matches each first link node in the candidate link can be obtained. Among them, the second link node that matches the first link node can refer to the node on the pre-stored candidate link whose position is closest to the preset position, or it can be a second link node that matches the first link node by evenly inserting points in the candidate link in the same way as the second link. Afterwards, for each first link node, based on the position coordinates of the first link node and the second link node, the distance between the first link node and the matching second link node is calculated, and the distance can be the Euclidean distance. Based on the distance between the K link nodes, the distance between the candidate link and the second link is calculated, and the distance can be the mean distance or the sum of the distances between the K link nodes, and the distance can be the curve distance between the two links.

[0085] A link with the smallest distance to the second link is selected from the M candidate links as a target link. The target link is the first link that best matches the second link.

[0086] In this implementation, when the intersection type of the target intersection is the first type, the target link can be screened from the M candidate links by distance matching.

[0087] Optionally, when the intersection type is the second type, the step of selecting a target link matching the second link from the M candidate links includes:

[0088] For each candidate link in the M candidate links, determine the similarity between the candidate link and the second link; based on the similarity, determine the matching probability of the second link in the candidate links;

[0089] The candidate link with the highest matching probability among the M candidate links is determined as the target link.

[0090] In this implementation, the candidate link and the second link may be matched by a probability model such as a Hidden Markov Model (HMM).

[0091] Specifically, each candidate link can be traversed to determine the similarity between the candidate link and the second link, and the similarity may include attribute similarity and direction similarity. In an optional implementation, the attribute information of the candidate link and the second link (which may include physical geometric attribute information and semantic attribute information) can be obtained, and the attribute information of the two links can be compared to determine the attribute similarity between the candidate link and the second link. Based on the position coordinates of the nodes on the candidate link, the direction information of the candidate link is calculated. Based on the position coordinates of the nodes on the second link, the direction information of the second link is calculated. Based on the direction information of the candidate link and the direction information of the second link, the direction similarity of the two links is calculated.

[0092] Afterwards, the data representing the candidate link, the data representing the second link, and the similarity of the two links are input into the HMM, which comprehensively considers the attribute similarity and direction similarity of the two links when calculating the emission probability, and obtains the emission probability corresponding to the two links. The emission probability is the matching probability of the second link in the candidate links. The candidate link with the largest matching probability among the M candidate links is determined as the target link.

[0093] In this implementation, the candidate link is matched with the second link through HMM, so that the target link can be screened from the M candidate links.

[0094] Optionally, after step S103, the method further includes:

[0095] Associating the second link with the target link to obtain association information;

[0096] The associated information is used for the traveling object to call the target link for navigation when the traveling object travels to the target intersection and is located at the second link.

[0097] In this implementation, the link matching results of the target intersection can be associated, that is, the second link is statically associated with the target link to participate in the generation of a static association table to obtain association information. The static association table can be stored in the navigation processing device, so that the next time the autonomous driving vehicle passes the target intersection and is located at the second link, it can call the target link associated with the second link in the static association table for navigation. In this way, there is no need for dynamic matching, which can save computing resources of the autonomous driving vehicle.

[0098] The navigation processing method of this embodiment is described in detail below with a specific example.

[0099] Figure 4 is a flowchart of a navigation processing method according to a specific example of the present embodiment. Figure 4 As shown, all HD links at the target intersection can be obtained, and node matching is performed according to the intersection type. Node matching can be divided into link matching with double node constraints and link matching with single node constraints. The purpose of link matching is to filter out the HD link that best matches the SD link at the target intersection from all HD links at the target intersection for navigation of the autonomous driving vehicle.

[0100] When the intersection type is the first type, M candidate links are determined from the HD link through the double-node constraint, and the candidate links and the second link are evenly interpolated with equal numbers to obtain link node pairs. The curve distance between the two links is calculated based on the link node pairs, and the candidate link with the shortest curve distance to the second link is determined as the link matching result, i.e., the target link.

[0101] When the intersection type is the second type, M candidate links are determined from the HD link through single-node constraints, and the attribute similarity and direction similarity between the candidate link and the second link are calculated. The attribute similarity, direction similarity and data of the two links are input into HMM for link matching, and the matching probability of the second link in the candidate links is obtained. The candidate link with the largest matching probability is determined as the link matching result, i.e., the target link.

[0102] Second embodiment

[0103] like Figure 5 As shown, the present disclosure provides a navigation processing device 500, comprising:

[0104] An acquisition module 501 is used to acquire N first links located at a target intersection in a first map, where the target intersection is an intersection in a first navigation route of a traveling object, where the first navigation route is a navigation route planned on a second map, where the road position accuracy of the first map is greater than the road position accuracy of the second map, and N is a positive integer;

[0105] A screening module 502 is used for screening a target link matching the second link from the N first links based on a starting node of the second link when the traveling object travels to a first target location based on the first navigation route, the second link being a link in the first navigation route that is located at the target intersection and has the shortest mileage from the traveling object, and the distance of the first target location relative to the starting node of the second link being within a preset range;

[0106] The navigation module 503 is used to navigate the traveling object based on the target link when the traveling object travels to a second target position based on the first navigation route, and the second target position is the position of the starting node of the second link.

[0107] Optionally, the screening module 502 includes:

[0108] A determination submodule, configured to determine M candidate links from the N first links, wherein the M candidate links match the starting node of the second link, and M is a positive integer;

[0109] The screening submodule is used to screen out a target link matching the second link from the M candidate links.

[0110] Optionally, the device further comprises:

[0111] A type determination module, configured to determine the intersection type of the target intersection based on the connectivity relationship of the N first links;

[0112] The determination submodule is specifically configured to determine M candidate links from the N first links based on the intersection type.

[0113] Optionally, the determining submodule includes:

[0114] a first determining unit, configured to, when the intersection type is a first type, determine a link among the N first links whose starting node is consistent with the starting node of the second link and whose ending node is consistent with the ending node of the second link as a candidate link, to obtain the M candidate links, wherein the first type indicates that there is a converging node or a diverging node between the second link and other links located at the target intersection;

[0115] The second determination unit is used to determine the link connected to the starting node of the second link among the N first links as a candidate link to obtain the M candidate links when the intersection type is the second type, and the second type represents that there is no intersection node and divergence node between the second link and other links located at the target intersection.

[0116] Optionally, the screening submodule is specifically used for:

[0117] When the intersection type is the first type, obtaining a link node at a preset position in the second link to obtain K first link nodes, where K is a positive integer;

[0118] For each candidate link in the M candidate links, obtain K second link nodes in the candidate link that are matched one-to-one with the K first link nodes; based on the K first link nodes and the K second link nodes, calculate the distance between the candidate link and the second link;

[0119] The candidate link with the smallest distance from the second link among the M candidate links is determined as the target link.

[0120] Optionally, the screening submodule is specifically used for:

[0121] In the case where the intersection type is the second type, for each candidate link in the M candidate links, determining a similarity between the candidate link and the second link; and determining a matching probability of the second link in the candidate links based on the similarity;

[0122] The candidate link with the highest matching probability among the M candidate links is determined as the target link.

[0123] Optionally, the device further comprises:

[0124] an association module, configured to associate the second link with the target link to obtain association information;

[0125] The associated information is used for the traveling object to call the target link for navigation when the traveling object travels to the target intersection and is located at the second link.

[0126] The navigation processing device 500 provided in the present disclosure can implement each process implemented by the navigation processing method embodiment and can achieve the same beneficial effects. To avoid repetition, it will not be described again here.

[0127] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0128] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0129] Figure 6A schematic block diagram of an example electronic device that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0130] like Figure 6 As shown, the device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 can also be stored. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0131] A number of components in the device 600 are connected to the I / O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0132] The computing unit 601 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 601 performs the various methods and processes described above, such as the navigation processing method. For example, in some embodiments, the navigation processing method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the navigation processing method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the navigation processing method in any other appropriate manner (e.g., by means of firmware).

[0133] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0134] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0135] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0136] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0137] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0138] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0139] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0140] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A navigation processing method, comprising: Obtain N first links located at a target intersection in the first map, where the target intersection is an intersection in a first navigation route of the driving object, where the first navigation route is a navigation route planned on the second map, where the road position accuracy of the first map is greater than the road position accuracy of the second map, and N is a positive integer; In a case where the traveling object travels to a first target location based on the first navigation route, determining M candidate links from the N first links, the M candidate links matching the start node of the second link, where M is a positive integer; The second link is a link in the first navigation route that is located at the target intersection and has the shortest mileage from the driving object, and the distance of the first target position relative to the starting node of the second link is within a preset range; Filtering a target link matching the second link from the M candidate links; When the traveling object travels to a second target location based on the first navigation route, navigating the traveling object based on the target link, the second target location being the location of a starting node of the second link; The step of selecting a target link matching the second link from the M candidate links includes at least one of the following: When the intersection type of the target intersection is the second type, determining, for each candidate link in the M candidate links, a similarity between the candidate link and the second link; Based on the similarity, determining a matching probability of the second link in the candidate links; Determine the candidate link with the highest matching probability among the M candidate links as the target link, wherein the second type indicates that there is no intersection node or divergence node between the second link and other links located at the target intersection; When the intersection type is the first type, obtaining link nodes at preset positions in the second link to obtain K first link nodes, where K is a positive integer; for each candidate link in the M candidate links, obtaining K second link nodes in the candidate links that match the K first link nodes one by one; Based on the K first link nodes and the K second link nodes, calculating a distance between the candidate link and the second link; The candidate link with the smallest distance from the second link among the M candidate links is determined as the target link.

2. The method according to claim 1, before determining the M candidate links from the N first links, further comprising: Determining the intersection type of the target intersection based on the connectivity relationship of the N first links; The determining M candidate links from the N first links includes: Based on the intersection type, M candidate links are determined from the N first links.

3. The method according to claim 2, wherein: The determining, based on the intersection type, M candidate links from the N first links comprises at least one of the following: When the intersection type is the first type, a link whose starting node is consistent with the starting node of the second link and whose ending node is consistent with the ending node of the second link among the N first links is determined as a candidate link, to obtain the M candidate links, wherein the first type indicates that there is a converging node or a diverging node between the second link and other links located at the target intersection; When the intersection type is the second type, a link among the N first links that is connected to a starting node of the second link is determined as a candidate link, thereby obtaining the M candidate links.

4. The method according to claim 1, after navigating the traveling object based on the target link, further comprising: Associating the second link with the target link to obtain association information; The associated information is used for the traveling object to call the target link for navigation when the traveling object travels to the target intersection and is located at the second link.

5. A navigation processing device, comprising: an acquisition module, configured to acquire N first links located at a target intersection in a first map, wherein the target intersection is an intersection in a first navigation route of a traveling object, wherein the first navigation route is a navigation route planned on a second map, wherein a road position accuracy of the first map is greater than a road position accuracy of the second map, and N is a positive integer; a screening module, configured to screen out a target link matching the second link from the N first links based on a starting node of a second link when the traveling object travels to a first target location based on the first navigation route, the second link being a link in the first navigation route that is located at the target intersection and has the least mileage from the traveling object, and the distance of the first target location relative to the starting node of the second link being within a preset range; a navigation module, configured to navigate the traveling object based on the target link when the traveling object travels to a second target location based on the first navigation route, the second target location being a location of a starting node of the second link; The screening module comprises: A determination submodule, configured to determine M candidate links from the N first links, wherein the M candidate links match the starting node of the second link, and M is a positive integer; A screening submodule, used to screen out a target link matching the second link from the M candidate links; The screening submodule is specifically used for at least one of the following: In the case where the intersection type is the second type, for each candidate link in the M candidate links, determining the similarity between the candidate link and the second link; determining the matching probability of the second link in the candidate links based on the similarity; determining the candidate link with the largest matching probability among the M candidate links as the target link, the second type indicating that there is no intersection node and divergence node between the second link and other links located at the target intersection; In the case where the intersection type is the first type, a link node at a preset position in the second link is obtained to obtain K first link nodes, where K is a positive integer; for each candidate link in the M candidate links, K second link nodes in the candidate links that are matched one-to-one with the K first link nodes are obtained; based on the K first link nodes and the K second link nodes, a distance between the candidate link and the second link is calculated; and the candidate link with the smallest distance between the candidate link and the second link among the M candidate links is determined as the target link.

6. The apparatus according to claim 5, further comprising: A type determination module, configured to determine the intersection type of the target intersection based on the connectivity relationship of the N first links; The determination submodule is specifically configured to determine M candidate links from the N first links based on the intersection type.

7. The device according to claim 6, wherein: The determination submodule comprises: a first determining unit, configured to, when the intersection type is a first type, determine a link among the N first links whose starting node is consistent with the starting node of the second link and whose ending node is consistent with the ending node of the second link as a candidate link, to obtain the M candidate links, wherein the first type indicates that there is a converging node or a diverging node between the second link and other links located at the target intersection; The second determining unit is configured to determine, when the intersection type is the second type, a link in the N first links that is connected to a starting node of the second link as a candidate link, to obtain the M candidate links.

8. The apparatus according to claim 5, further comprising: an association module, configured to associate the second link with the target link to obtain association information; The associated information is used for the traveling object to call the target link for navigation when the traveling object travels to the target intersection and is located at the second link.

9. An electronic device, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 4.

10. An autonomous driving vehicle comprising the electronic device as claimed in claim 9.

11. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-4.

12. A computer program product, comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 4.

Images