Map data processing method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a map data processing method and device, electronic equipment and a storage medium, and the processing method comprises the steps: obtaining map data in response to a request of a vehicle for recognizing a target intersection; determining a plurality of node data corresponding to the target intersection from the map data; wherein the type of the node data comprises a driving-in node coordinate and a driving-out node coordinate; virtual graphic information corresponding to the target intersection is constructed according to the multiple pieces of node data; obtaining driving direction information of a vehicle, and determining a target driving-in node coordinate and a target driving-out node coordinate in the plurality of node data according to the virtual graphic information and the driving direction information; and constructing a virtual driving guide line of the vehicle according to the target driving-in node coordinate and the target driving-out node coordinate. According to the embodiment of the invention, the flexibility and accuracy of intersection identification are improved, and the vehicle can stably pass through the target intersection through the virtual driving guide line.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and device for processing map data, an electronic device, and a storage medium. Background Art

[0002] Intelligent driving, also known as autonomous driving or unmanned driving, refers to the autonomous driving of vehicles through computer systems. It integrates a variety of advanced technologies such as sensor technology and computer vision, aiming to improve road safety, traffic efficiency and driving experience. With the gradual development of intelligent driving technology and the improvement of intelligent driving functions, its operating range has gradually expanded from highways and expressways to urban roads.

[0003] In the urban road scene, good vehicle crossing performance is an important part of improving intelligent driving in urban scenes. To ensure that intelligent driving vehicles can pass through intersections smoothly, it is first necessary to stably and accurately identify the intersection in front of the vehicle.

[0004] In related technologies, deep learning and visual perception are used to identify intersections. However, this solution is often limited by visual sensors and training data. Specifically, in complex scenes, visual sensors are easily blocked and cannot give satisfactory performance, such as frequent missed detections and false detections. In addition, the limited perception distance is also a major factor that restricts its performance. Therefore, related technologies have great limitations on intersection recognition and low accuracy. Summary of the invention

[0005] In view of the above problems, a method and device for processing map data, an electronic device, and a storage medium are proposed to overcome the above problems or at least partially solve the above problems, including:

[0006] A method for processing map data, the method comprising:

[0007] Responding to a request for the vehicle to identify a target intersection, acquiring map data;

[0008] Determine a plurality of node data corresponding to the target intersection from the map data; wherein the types of the node data include entry node coordinates and exit node coordinates;

[0009] Constructing virtual graphic information corresponding to the target intersection according to the plurality of node data;

[0010] Acquire the driving direction information of the vehicle, and determine the target entry node coordinates and the target exit node coordinates in the plurality of node data according to the virtual graphic information and the driving direction information;

[0011] A virtual driving guide line of the vehicle is constructed according to the target entry node coordinates and the target exit node coordinates.

[0012] Optionally, constructing virtual graphic information corresponding to the target intersection according to the plurality of node data includes:

[0013] Acquire the location information of the vehicle, and group the plurality of node data according to the location information of the vehicle to obtain a plurality of node groups; wherein each of the node groups includes a first entry node coordinate and a first exit node coordinate;

[0014] Determine the target straight line corresponding to each node group according to the first entry node coordinates and the first exit node coordinates, and determine the coordinates of the straight line intersections between each of the target straight lines;

[0015] Construct virtual graphic information corresponding to the target intersection according to the coordinates of the straight line intersections.

[0016] Optionally, the acquiring the location information of the vehicle and grouping the node data according to the location information of the vehicle to obtain a plurality of node groups includes:

[0017] Determining, according to the position information of the vehicle, from the plurality of node data, the coordinates of a second entry node closest to the vehicle;

[0018] Determine the centroid coordinates corresponding to the plurality of node data according to the plurality of node data and the total number of the plurality of node data;

[0019] Determine a first vector composed of each of the node data and the coordinates of the center of mass point, and a second vector composed of the coordinates of the second entry node and the coordinates of the center of mass point;

[0020] Determine a target angle formed by each of the first vectors and the second vector, and sort each of the node data according to the size of the target angle to obtain a node sorting result;

[0021] The plurality of node data are grouped according to the node sorting result and the location information of the vehicle to obtain a plurality of the node groups.

[0022] Optionally, the virtual graph information includes a plurality of edge information, each edge information includes at least one third entry node coordinate and at least one second exit node coordinate, and the step of determining a target entry node coordinate and a target exit node coordinate in the plurality of node data according to the virtual graph information and the driving direction information includes:

[0023] Determine, from the plurality of edge information, target entry edge information and target exit edge information matching the driving direction information;

[0024] The target entry node coordinate is determined in at least one of the third entry node coordinates of the target entry edge information, and the target exit node coordinate is determined in at least one of the second exit node coordinates of the target exit edge information.

[0025] Optionally, after determining the target straight line corresponding to each node group according to the first entry node coordinates and the first exit node coordinates, and determining the coordinates of the straight line intersections between each of the target straight lines, the method further includes:

[0026] Determine whether the coordinates of each of the straight line intersections meet a preset coordinate range;

[0027] When the coordinates of the straight line intersection point meet the preset coordinate range, the coordinates of the straight line intersection point are retained.

[0028] Optionally, determining a target angle formed by each of the first vectors and the second vector comprises:

[0029] determining a vector cross product of the first vector and the second vector, and a vector dot product of the first vector and the second vector;

[0030] The target radians of the first vector and the second vector are determined according to the vector cross product and the vector dot product, and the target radians are converted into the target angle.

[0031] Optionally, the target intersection is an intersection that is closest to the vehicle in the direction of travel of the vehicle.

[0032] A map data processing device, the device comprising:

[0033] A map data acquisition module, for acquiring map data in response to a request for a vehicle to identify a target intersection;

[0034] A node data determination module, used to determine a plurality of node data corresponding to the target intersection from the map data; wherein the types of the node data include entry node coordinates and exit node coordinates;

[0035] A virtual graphic information construction module, used to construct virtual graphic information corresponding to the target intersection according to the plurality of node data;

[0036] A target node determination module, used for acquiring the driving direction information of the vehicle, and determining the target entry node coordinates and the target exit node coordinates in the plurality of node data according to the virtual graphic information and the driving direction information;

[0037] The virtual driving guide line construction module is used to construct a virtual driving guide line of the vehicle according to the target entry node coordinates and the target exit node coordinates.

[0038] Optionally, the system comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the above-mentioned method for processing map data when executed by the processor.

[0039] Optionally, the computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the method for processing map data as described above is implemented.

[0040] The embodiment of the present invention has the following advantages: the embodiment of the present invention obtains map data in response to a request for a vehicle to identify a target intersection, determines a plurality of node data corresponding to the target intersection from the map data, wherein the type of the node data includes an entry node coordinate and an exit node coordinate, constructs virtual graphic information corresponding to the target intersection according to the plurality of node data, obtains the driving direction information of the vehicle, and determines the target entry node coordinate and the target exit node coordinate in the plurality of node data according to the virtual graphic information and the driving direction information, constructs a virtual driving guide line for the vehicle according to the target entry node coordinate and the target exit node coordinate, constructs virtual graphic information that can reflect the geometric features of the target intersection only by using the plurality of node data corresponding to the target intersection in the map data, which is equivalent to identifying the intersection without being restricted by a visual sensor, thereby improving the flexibility and accuracy of intersection identification, and also constructs a virtual guide line for vehicle driving, so that the vehicle can pass through the intersection smoothly, thereby improving the safety of intelligent driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solution of the present invention, the accompanying drawings required for use in the description of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0042] Figure 1 is a flowchart of a method for processing map data provided by an embodiment of the present invention;

[0043] Figure 2 is a flowchart of another method for processing map data provided by an embodiment of the present invention;

[0044] Figure 3 It is a structural block diagram of a map data processing device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Reference Figure 1 , shows a flowchart of a method for processing map data provided by an embodiment of the present invention, which may specifically include the following steps:

[0047] Step 101, in response to a request from a vehicle to identify a target intersection, obtaining map data;

[0048] In this embodiment, the vehicle may be a vehicle entering an intelligent driving mode, and the target intersection may be an intersection that the vehicle needs to pass in the direction of travel, preferably the first intersection ahead of the vehicle's travel route.

[0049] Map data can be lightweight map data (hereinafter referred to as light map). Light map is different from high-precision map in that it can be updated quickly and can be updated weekly. Light map can cover urban scenes. Although its content elements are much simpler than those of high-precision map, only some necessary road data, such as road lines and road feature points, are retained. However, this is also one of the reasons why it can be updated quickly.

[0050] In some embodiments of the present invention, the target intersection is an intersection that is closest to the vehicle in the direction of travel of the vehicle.

[0051] Step 102, determining a plurality of node data corresponding to the target intersection from the map data; wherein the types of the node data include entry node coordinates and exit node coordinates;

[0052] In this embodiment, since the acquired map data includes multiple types of data, such as node data corresponding to non-intersection nodes, road line data, etc., it is necessary to filter the map data and only retain the node data corresponding to the target intersection.

[0053] The entry node coordinates are the coordinates of the node for vehicles to enter (hereinafter referred to as the entry point), and the exit node coordinates are the coordinates of the node for vehicles to exit (hereinafter referred to as the exit point). An intersection usually includes at least one entry point and one exit point. Taking the intersection formed by the intersection of four roads as an example, each road has at least an entry point for entering the intersection and an exit point for exiting the intersection, so the intersection contains at least 8 node data; if the road has multiple lanes, there may be more entry points and exit points.

[0054] In the specific implementation, after obtaining the map data, the node data corresponding to the non-intersection nodes are first filtered according to the attributes, and only the node data corresponding to the intersection nodes are retained, and multiple entry intersection node coordinates and multiple exit intersection node coordinates are obtained. However, at this time, it is still unclear which node data belongs to which intersection, such as the first intersection in front of the vehicle, the second intersection, or other intersections that are not in the direction of vehicle travel. Therefore, it is necessary to cluster each node data according to different intersections, and only retain the node data corresponding to the target intersection. For example, assuming that there are currently 16 node data corresponding to different intersections, after clustering, it can be determined that 8 node data belong to intersection No. 1, and the other 8 node data belong to intersection No. 2. Among them, intersection No. 1 is the target intersection, then only the 8 node data corresponding to intersection No. 1 are retained.

[0055] As an example, node data can be clustered based on the relative position relationship between each node data and the vehicle and the succession relationship between intersections. The succession relationship between intersections means that there is a spatial continuity relationship between one intersection and another intersection, and when one intersection is determined, another intersection can be determined through the continuity relationship.

[0056] Step 103, constructing virtual graphic information corresponding to the target intersection according to the plurality of node data;

[0057] In an embodiment of the present invention, since the node data includes all the entry node coordinates and exit node coordinates of the target intersection, the virtual graphic information constructed by the node data can express the geometric features of the target intersection, complete the construction of the target intersection for intelligent driving vehicles to identify, and lay the foundation for the vehicle to pass through the intersection smoothly. At the same time, the virtual graphic information can also be used to determine whether the vehicle has currently entered or exited the target intersection. As an example, the virtual graphic information can be polygonal graphic information, and each edge of the polygon can map at least one set of entry points and exit points of one of the roads constituting the intersection. For example, a rectangular virtual graphic information can be constructed for the intersection, and the four sides of the rectangle correspond to the entry points and exit points of the four roads constituting the intersection.

[0058] In some embodiments of the present invention, constructing virtual graphic information corresponding to the target intersection according to the plurality of node data includes:

[0059] Acquire the location information of the vehicle, and group the plurality of node data according to the location information of the vehicle to obtain a plurality of node groups; wherein each of the node groups includes a first entry node coordinate and a first exit node coordinate;

[0060] Determine the target straight line corresponding to each node group according to the first entry node coordinates and the first exit node coordinates, and determine the coordinates of the straight line intersections between each of the target straight lines;

[0061] Construct virtual graphic information corresponding to the target intersection according to the coordinates of the straight line intersections.

[0062] In this embodiment, since the node data corresponding to the target intersection is still disordered and is only individual coordinate data, the node data needs to be grouped to clarify which positions the node data belongs to. As an example, after obtaining the node data of the intersection, the node data can be divided into node groups such as the intersection entry group, the left turn group, the right turn group, and the straight group.

[0063] Furthermore, since it is necessary to determine the relative positional relationship between the current position of the vehicle and the intersection, for example, it is necessary to determine whether the vehicle has entered the intersection or whether the vehicle has exited the intersection, it is necessary to construct virtual information of the target intersection, that is, to construct virtual graphic information corresponding to the target intersection. Therefore, each node group includes a first entry node coordinate and a first exit node coordinate, and each node group can correspond to a target straight line. After the coordinates of the straight line intersections between the target straight lines corresponding to each node group are obtained, the virtual graphic information is constructed by the straight line intersection coordinates. The virtual graphic information constructed by these straight line intersection coordinates can fully express the geometric features of the target intersection because it will inevitably cover the target intersections corresponding to all node data, thereby improving the accuracy of constructing the virtual information corresponding to the target intersection.

[0064] In the specific implementation, the coordinates of the intersection point of the straight lines can be calculated in the following way:

[0065] P intersection =I i ×I i+1

[0066] Among them, P intersection is the intersection point of the straight lines, I i ,I i+1 is the line corresponding to each node group. By constructing a homogeneous coordinate system, the coordinates of the intersection point of the lines can be obtained by cross-multiplying the equations corresponding to the two target lines.

[0067] In some embodiments of the present invention, after determining the target straight line corresponding to each node group according to the first entry node coordinates and the first exit node coordinates, and determining the coordinates of the straight line intersections between each of the target straight lines, the method further includes:

[0068] Determine whether the coordinates of each of the straight line intersections meet a preset coordinate range;

[0069] When the coordinates of the straight line intersection point meet the preset coordinate range, the coordinates of the straight line intersection point are retained.

[0070] In the embodiment of the present invention, since the two target straight lines may be parallel or approximately parallel, resulting in the straight line intersection coordinates not existing or the straight line intersection coordinates being too far from the coordinates corresponding to the vehicle, it is necessary to determine whether each of the straight line intersection coordinates meets the preset coordinate range, and if not, remove them, and if so, retain them.

[0071] In some embodiments of the present invention, the acquiring the location information of the vehicle and grouping the node data according to the location information of the vehicle to obtain a plurality of node groups includes:

[0072] Determining, according to the position information of the vehicle, from the plurality of node data, the coordinates of a second entry node closest to the vehicle;

[0073] Determine the centroid coordinates corresponding to the plurality of node data according to the plurality of node data and the total number of the plurality of node data;

[0074] Determine a first vector composed of each of the node data and the coordinates of the center of mass point, and a second vector composed of the coordinates of the second entry node and the coordinates of the center of mass point;

[0075] Determine a target angle formed by each of the first vectors and the second vector, and sort each of the node data according to the size of the target angle to obtain a node sorting result;

[0076] The plurality of node data are grouped according to the node sorting result and the location information of the vehicle to obtain a plurality of the node groups.

[0077] In the embodiment of the present invention, the second entry node coordinates are the coordinates of the reference point, the centroid is the center point of the geometric figure formed by all entry points and all exit points in the node data, and the centroid coordinates are the coordinates of the center point.

[0078] Furthermore, a first vector is formed by each node data (i.e., the entry node coordinates or exit node coordinates) and the centroid coordinates, and a second vector is formed by the second entry node coordinates and the centroid coordinates, and a target angle of each first vector and the second vector is determined. The size of the target angle can reflect the relative position information of each node data and the vehicle in the target intersection, so that each node data can be grouped to obtain a node group. For example, in the case of a crossroad, when the target angle is 75°, the entry point or exit point corresponding to the node data may be located on the left side of the vehicle's driving direction; when the target angle is 225°, the entry point or exit point corresponding to the node data may be located in front of the vehicle's driving direction; when the target angle is 320°, the entry point or exit point corresponding to the node data may be located on the right side of the vehicle's driving direction. Moreover, the target angles corresponding to the entry point and the entry and exit points belonging to the same road are also relatively close, which can facilitate the grouping of node data.

[0079] Furthermore, each node data is sorted according to the size of the corresponding target angle, so that spatially continuous node data can be obtained. For example, by sorting in descending order of the target angle, continuous node data in the counterclockwise direction with the second entry node (i.e., the reference point) as the center can be obtained.

[0080] Furthermore, the relative position relationship between the vehicle and the entry point or exit point corresponding to the node data is determined in combination with the vehicle's position information, and the node data is grouped. Taking the intersection as an example, according to the sorting results of the target angle from large to small and combined with the relative position relationship between the vehicle and each node data, the sorted node data can be divided into right turn group, straight group, left turn group, and intersection entry group in a counterclockwise direction.

[0081] In some embodiments of the present invention, determining a target angle formed by each of the first vectors and the second vector includes:

[0082] determining a vector cross product of the first vector and the second vector, and a vector dot product of the first vector and the second vector;

[0083] The target radians of the first vector and the second vector are determined according to the vector cross product and the vector dot product, and the target radians are converted into the target angle.

[0084] In the specific implementation, the coordinates of the second entry node are recorded as P r , the coordinates of the centroid are

[0085] Among them, P iFor each entry node coordinate or exit node coordinate, n is all node data, that is, the total number of all entry node coordinates and exit node coordinates, and the first vector is V ci , the second vector is V cr , let the target angle be θ, then the target angle can be obtained by the following method:

[0086]

[0087] Among them, V ci ×V cr is the vector cross product, V ci ·V cr That is the vector dot product. By processing the vector cross product and the vector dot product through inverse trigonometric functions, the target radian formed by the first vector and the second vector can be obtained, and then the target radian can be converted into the target angle through the RAD_DEG() function.

[0088] Step 104, obtaining the driving direction information of the vehicle, and determining the target entry node coordinates and the target exit node coordinates in the plurality of node data according to the virtual graphic information and the driving direction information;

[0089] In this embodiment, the virtual graphic information can reflect the geometric characteristics of the target intersection. Therefore, combined with the vehicle's driving direction information, the target entry node coordinates and target exit node coordinates required to pass through the target intersection in the vehicle's driving direction can be quickly determined so that the vehicle can pass through the target intersection smoothly.

[0090] In some embodiments of the present invention, the virtual graph information includes a plurality of edge information, each edge information includes at least one third entry node coordinate and at least one second exit node coordinate, and determining the target entry node coordinate and the target exit node coordinate in the plurality of node data according to the virtual graph information and the driving direction information includes:

[0091] Determine, from the plurality of edge information, target entry edge information and target exit edge information matching the driving direction information;

[0092] The target entry node coordinate is determined in at least one of the third entry node coordinates of the target entry edge information, and the target exit node coordinate is determined in at least one of the second exit node coordinates of the target exit edge information.

[0093] In a specific implementation, taking a crossroad as an example, the corresponding virtual graphic information is a rectangle, with the rectangular side closest to the vehicle's driving direction as side 1, and the other rectangular sides are recorded as sides 2, 3, and 4 in a clockwise direction, and each rectangular side (i.e., side information) corresponds to at least one exit point and entry point and their corresponding coordinates. When the vehicle is determined to be traveling straight through the vehicle's driving direction information, side 1 can be determined as the target entry side information, and side 3 opposite to side 1 can be determined as the target exit side information.

[0094] Further, the target entry node coordinates are determined from multiple third entry node coordinates in edge No. 1, ie, the target entry edge information, and the target exit point coordinates are determined from multiple second exit node coordinates in edge No. 3, ie, the target exit edge information.

[0095] Step 105 : constructing a virtual driving guide line of the vehicle according to the target entry node coordinates and the target exit node coordinates.

[0096] In this embodiment, since lane lines are often not planned at each intersection in an urban scene, a virtual driving guide line for the vehicle can be constructed through the target entry node coordinates and the target exit node coordinates, so that the vehicle can smoothly pass through the target intersection. As an example, after the target entry node coordinates and the target exit node coordinates are determined, a smooth curve can be used to connect the entry point corresponding to the target entry node coordinates and the exit point corresponding to the target exit node coordinates, and the curve is the virtual driving guide line of the vehicle.

[0097] In some embodiments of the present invention, Figure 2 As shown, a map data processing flow is also provided, which is as follows:

[0098] 1. Receive light map data, cluster the node data corresponding to different intersections, and determine the node data corresponding to the target intersection.

[0099] 2. Sort the node data (i.e. road nodes) and determine the reference road node (i.e. the second road node)

[0100] 3. After sorting, the node data is grouped and clustered into multiple node groups.

[0101] 4. If the total number of node data meets the threshold (for example, greater than 2), and the node data includes at least one entry node coordinate and an exit node, a convex polygon corresponding to the target intersection (ie, virtual graphic information corresponding to the target intersection) is constructed.

[0102] 5. Based on the virtual graphic information, connect the predecessor and successor relationships of each node to construct a virtual driving guide line.

[0103] The embodiment of the present invention has the following advantages: the embodiment of the present invention obtains map data in response to a request for a vehicle to identify a target intersection, determines a plurality of node data corresponding to the target intersection from the map data, wherein the type of the node data includes an entry node coordinate and an exit node coordinate, constructs virtual graphic information corresponding to the target intersection according to the plurality of node data, obtains the driving direction information of the vehicle, and determines the target entry node coordinate and the target exit node coordinate in the plurality of node data according to the virtual graphic information and the driving direction information, constructs a virtual driving guide line for the vehicle according to the target entry node coordinate and the target exit node coordinate, constructs virtual graphic information that can reflect the geometric features of the target intersection only by using the plurality of node data corresponding to the target intersection in the map data, which is equivalent to identifying the intersection without being restricted by a visual sensor, thereby improving the flexibility and accuracy of intersection identification, and also constructs a virtual guide line for vehicle driving, so that the vehicle can pass through the intersection smoothly, thereby improving the safety of intelligent driving.

[0104] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0105] Reference Figure 3 , shows a schematic diagram of the structure of a device for generating game voices provided by an embodiment of the present invention, which may specifically include the following modules:

[0106] A map data acquisition module 301 is used to acquire map data in response to a request for a vehicle to identify a target intersection;

[0107] A node data determination module 302 is used to determine a plurality of node data corresponding to the target intersection from the map data; wherein the types of the node data include entry node coordinates and exit node coordinates;

[0108] A virtual graph information construction module 303, configured to construct virtual graph information corresponding to the target intersection according to the plurality of node data;

[0109] A target node determination module 304 is used to obtain the driving direction information of the vehicle, and determine the target entry node coordinates and the target exit node coordinates in the plurality of node data according to the virtual graphic information and the driving direction information;

[0110] The virtual driving guide line construction module 305 is used to construct a virtual driving guide line of the vehicle according to the target entry node coordinates and the target exit node coordinates.

[0111] In some embodiments of the present invention, the virtual graphics information construction module 303 includes:

[0112] A grouping submodule, used to obtain the location information of the vehicle, and group the plurality of node data according to the location information of the vehicle to obtain a plurality of node groups; wherein each of the node groups includes a first entry node coordinate and a first exit node coordinate;

[0113] A straight line intersection coordinate determination submodule, used to determine the target straight line corresponding to each node group according to the first entry node coordinates and the first exit node coordinates, and determine the straight line intersection coordinates between each of the target straight lines;

[0114] The virtual graphic information construction submodule is used to construct the virtual graphic information corresponding to the target intersection according to the coordinates of the straight line intersections.

[0115] In some embodiments of the present invention, the grouping submodule includes:

[0116] A second entry node coordinate determination subunit, configured to determine, according to the position information of the vehicle, from the plurality of node data, the coordinates of a second entry node that is closest to the vehicle;

[0117] A centroid coordinate determination subunit, used to determine the centroid coordinates corresponding to the plurality of node data according to the plurality of node data and the total number of the plurality of node data;

[0118] A first vector and second vector determination subunit, used to determine a first vector composed of each of the node data and the mass center coordinates, and a second vector composed of the second entry node coordinates and the mass center coordinates;

[0119] A node sorting result determination subunit is used to determine a target angle formed by each of the first vectors and the second vector, and sort each of the node data according to the size of the target angle to obtain a node sorting result;

[0120] The grouping subunit is used to group the plurality of node data according to the node sorting result and the location information of the vehicle to obtain a plurality of the node groups.

[0121] In some embodiments of the present invention, the target node determination module 304 includes:

[0122] a target side information determination submodule, configured to determine, from the plurality of side information, target entry side information and target exit side information that match the driving direction information;

[0123] The target node determination submodule is used to determine the target entry node coordinate in at least one of the third entry node coordinates of the target entry edge information, and to determine the target exit node coordinate in at least one of the second exit node coordinates of the target exit edge information.

[0124] In some embodiments of the present invention, the device further comprises:

[0125] A straight line intersection coordinate judgment module is used to determine whether the coordinates of each straight line intersection meet a preset coordinate range;

[0126] A straight line intersection coordinate filtering module is used to retain the straight line intersection coordinates when the straight line intersection coordinates meet the preset coordinate range.

[0127] In some embodiments of the present invention, the node sorting result determination subunit includes:

[0128] a vector product determination subunit, configured to determine a vector cross product of the first vector and the second vector, and a vector dot product of the first vector and the second vector;

[0129] The target angle determination subunit is used to determine the target radians of the first vector and the second vector according to the vector cross product and the vector dot product, and convert the target radians into the target angle.

[0130] Some embodiments of the present invention further provide an electronic device, which may include a processor, a memory, and a computer program stored in the memory and capable of running on the processor, and when the computer program is executed by the processor, the above-mentioned map data processing method is implemented.

[0131] Some embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned method for processing map data is implemented.

[0132] Some embodiments of the present invention further provide a computer program product, including a computer program, which implements the above map data processing method when executed by a processor.

[0133] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0134] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0135] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0136] Those skilled in the art will appreciate that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0137] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0138] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0139] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0140] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0141] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the above elements.

[0142] The map data processing method and device, electronic device, and storage medium provided above are introduced in detail. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for processing map data, characterized in that: The method comprises: Responding to a request for the vehicle to identify a target intersection, acquiring map data; Determine a plurality of node data corresponding to the target intersection from the map data; wherein the types of the node data include entry node coordinates and exit node coordinates; Constructing virtual graphic information corresponding to the target intersection according to the plurality of node data; Acquire the driving direction information of the vehicle, and determine the target entry node coordinates and the target exit node coordinates in the plurality of node data according to the virtual graphic information and the driving direction information; A virtual driving guide line of the vehicle is constructed according to the target entry node coordinates and the target exit node coordinates.

2. The method according to claim 1, characterized in that: The step of constructing virtual graphic information corresponding to the target intersection according to the plurality of node data includes: Acquire the location information of the vehicle, and group the plurality of node data according to the location information of the vehicle to obtain a plurality of node groups; wherein each of the node groups includes a first entry node coordinate and a first exit node coordinate; Determine the target straight line corresponding to each node group according to the first entry node coordinates and the first exit node coordinates, and determine the coordinates of the straight line intersections between each of the target straight lines; Construct virtual graphic information corresponding to the target intersection according to the coordinates of the straight line intersections.

3. The method according to claim 2, characterized in that The acquiring the location information of the vehicle and grouping the node data according to the location information of the vehicle to obtain a plurality of node groups includes: Determining, according to the position information of the vehicle, from the plurality of node data, the coordinates of a second entry node closest to the vehicle; Determine the centroid coordinates corresponding to the plurality of node data according to the plurality of node data and the total number of the plurality of node data; Determine a first vector composed of each of the node data and the coordinates of the center of mass point, and a second vector composed of the coordinates of the second entry node and the coordinates of the center of mass point; Determine a target angle formed by each of the first vectors and the second vector, and sort each of the node data according to the size of the target angle to obtain a node sorting result; The plurality of node data are grouped according to the node sorting result and the location information of the vehicle to obtain a plurality of the node groups.

4. The method according to claim 1, characterized in that: The virtual graph information includes a plurality of edge information, each edge information includes at least one third entry node coordinate and at least one second exit node coordinate, and the step of determining a target entry node coordinate and a target exit node coordinate in the plurality of node data according to the virtual graph information and the driving direction information includes: Determine, from the plurality of edge information, target entry edge information and target exit edge information matching the driving direction information; The target entry node coordinate is determined in at least one of the third entry node coordinates of the target entry edge information, and the target exit node coordinate is determined in at least one of the second exit node coordinates of the target exit edge information.

5. The method according to claim 2, characterized in that: After determining the target straight line corresponding to each node group according to the first entry node coordinates and the first exit node coordinates, and determining the coordinates of the straight line intersections between each of the target straight lines, the method further includes: Determine whether the coordinates of each of the straight line intersections meet a preset coordinate range; When the coordinates of the straight line intersection point meet the preset coordinate range, the coordinates of the straight line intersection point are retained.

6. The method according to claim 3, characterized in that The determining a target angle formed by each of the first vectors and the second vector comprises: determining a vector cross product of the first vector and the second vector, and a vector dot product of the first vector and the second vector; The target radians of the first vector and the second vector are determined according to the vector cross product and the vector dot product, and the target radians are converted into the target angle.

7. The method according to claim 1, characterized in that The target intersection is an intersection closest to the vehicle in the direction of travel of the vehicle.

8. A map data processing device, characterized in that: The device comprises: A map data acquisition module, for acquiring map data in response to a request for a vehicle to identify a target intersection; A node data determination module, used to determine a plurality of node data corresponding to the target intersection from the map data; wherein the types of the node data include entry node coordinates and exit node coordinates; A virtual graphic information construction module, used to construct virtual graphic information corresponding to the target intersection according to the plurality of node data; A target node determination module, used for acquiring the driving direction information of the vehicle, and determining the target entry node coordinates and the target exit node coordinates in the plurality of node data according to the virtual graphic information and the driving direction information; The virtual driving guide line construction module is used to construct a virtual driving guide line of the vehicle according to the target entry node coordinates and the target exit node coordinates.

9. An electronic device, characterized in that: The invention comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the method for processing map data according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for processing map data according to any one of claims 1 to 7 is implemented.

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