A method of generating a junction face and related apparatus

Abstract

The embodiment of the application discloses a method for generating an intersection face and a related device, which can be applied to the field of maps and the like. The application can efficiently generate an intersection face of an intersection node, and can also obtain an intersection face that is more consistent with the expected needs of products by modifying the constraint conditions, and has strong expansibility. The method comprises the following steps: acquiring road information of a target intersection node; determining road face width information of each road according to the road information; acquiring a constraint condition and a target function, the target function being used for indicating a solving target of a region size of the intersection face of the target intersection node, and the constraint condition being used for indicating a limiting condition of the region size, the constraint condition comprising a constraint relationship between bias variables of each two adjacent roads in at least two roads; solving the target function according to the road face width information of the roads and the constraint condition to obtain a bias distance of the roads; and generating the intersection face of the target intersection node based on the road face width information of the roads and the bias distance of the roads.

Description

Technical Field

[0001] This application relates to the technical fields of maps and transportation, and specifically to a method and related apparatus for generating intersection surfaces. Background Technology

[0002] Map applications provide maps that replicate the real world as closely as possible. The maps contain a large network of roads, and intersection surfaces are areas on the map that represent the space where intersections are located. However, due to the complexity of road intersections, it is difficult to draw specific intersection surfaces.

[0003] In related technologies, the offset distance of each road is usually pre-set, and then computationally intensive pure geometric algorithms are used to calculate the intersection surface of the intersection nodes. However, due to factors such as errors in road shape points and the coupling of related geometric conditions, as well as the poor scalability of pure geometric algorithms, existing pure geometric algorithms cannot calculate accurate intersection surfaces. Moreover, for some complex road scenarios, the calculated intersection surfaces cannot meet the expected requirements of the product. Summary of the Invention

[0004] This application provides a method and related apparatus for generating intersection surfaces. It constructs constraint conditions based on the constraint relationship between the offset variables of adjacent roads, without relying on complex pure geometric algorithms, and efficiently generates intersection surfaces of intersection nodes. Furthermore, by modifying the constraint conditions, the corresponding accurate offset distance can be calculated, thereby obtaining intersection surfaces that better meet the expected needs of the product, and has strong scalability.

[0005] In a first aspect, embodiments of this application provide a method for generating an intersection surface. The method includes: acquiring road information of a target intersection node, the road information including at least two roads; determining the road surface width information of each road based on the road information; acquiring constraint conditions and an objective function, wherein the objective function indicates the objective of solving for the area size of the intersection surface of the target intersection node, the constraint conditions indicate the limiting conditions for the area size, the constraint conditions include the constraint relationship between the bias variables of every two adjacent roads in the at least two roads, and the objective function includes at least two bias variables, each bias variable indicating the distance between the target intersection node and the tangent of the corresponding road; solving the objective function based on the road surface width information and the constraint conditions to obtain the road bias distance; and generating the intersection surface of the target intersection node based on the road surface width information and the road bias distance.

[0006] Secondly, embodiments of this application provide an intersection surface generation device. This intersection surface generation device includes, but is not limited to, terminal devices, servers, etc. The intersection surface generation device includes an acquisition unit and a processing unit. The acquisition unit is used to acquire road information of a target intersection node, the road information including at least two roads. The acquisition unit is used to acquire constraint conditions and an objective function, wherein the objective function indicates the objective of solving the area size of the intersection surface of the target intersection node, the constraint conditions indicate the limiting conditions of the area size, the constraint conditions include the constraint relationship between the bias variables of every two adjacent roads among the at least two roads, and the objective function includes at least two bias variables, each bias variable indicating the distance between the tangent of the target intersection node and the corresponding road. The processing unit is used to calculate the road bias distance based on the road surface width information and the constraint conditions, the bias distance indicating the distance between the tangent of the target intersection node and the road, and generate the intersection surface of the target intersection node based on the road width information and the road bias distance.

[0007] In some optional examples, the processing unit is configured to: determine the included angle information between each pair of adjacent roads based on the road surface width information and the corresponding road offset variable, wherein the included angle information is used to indicate the intersection between the corresponding tangents of the two adjacent roads; and construct constraint conditions based on the included angle information between each pair of adjacent roads.

[0008] In some optional examples, each road surface includes a left sub-road surface and a right sub-road surface. The acquisition unit is used to: acquire the included angle between a first road and a second road, where the first road and the second road are adjacent roads among at least two roads; acquire a first included angle between the first road and the boundary line of the right sub-road surface of the first road, a second included angle between the second road and the boundary line of the left sub-road surface of the second road, and a third included angle between the boundary line of the right sub-road surface of the first road and the boundary line of the left sub-road surface of the second road; the processing unit is used to construct constraint conditions based on the included angle between the first road and the second road, and the first, second, and third included angles.

[0009] In some other alternative examples, the sum of the first included angle, the second included angle, and the third included angle is less than or equal to the included angle between the first road and the second road.

[0010] In some alternative examples, the acquisition unit is used to: acquire the coordinates of the road shape points of the first road and the road shape points of the second road. The processing unit is used to calculate the angle between the first road and the second road based on the coordinates of the road shape points of the first road and the road shape points of the second road.

[0011] In some alternative examples, the first included angle is represented by the road surface width information of the right sub-road surface of the first road and the offset variable of the first road.

[0012] In some alternative examples, the second included angle is obtained from the road surface width information of the left sub-road surface of the second road and the offset variable of the second road.

[0013] In some alternative examples, the processing unit is used to: determine the road class of each road based on the road information; and determine the road surface width information of the corresponding road based on the road class of each road.

[0014] In some other optional examples, the processing unit is used to: determine the position of the intersection shape point based on the road surface width information of each road and the corresponding road offset distance, the intersection shape point being used to indicate the regional contour features of the intersection surface; and generate the intersection surface of the target intersection node based on the position of the intersection shape point.

[0015] In some alternative examples, the road surface width information includes the road surface width information of the left sub-road surface and the road surface width information of the right sub-road surface. The processing unit is used to: calculate the coordinates of a first intersection shape point based on the road surface width information of the right sub-road surface of the first road and the offset distance of the first road. The first intersection shape point is the intersection of the tangent of the first road and the boundary line of the right sub-road surface of the first road, and the coordinates of the first intersection shape point are used to indicate the position of the first intersection shape point; calculate the coordinates of a second intersection shape point based on the road surface width information of the left sub-road surface of the second road and the offset distance of the second road. The second intersection shape point is the intersection of the tangent of the second road and the boundary line of the left sub-road surface of the second road, and the coordinates of the second intersection shape point are used to indicate the position of the second intersection shape point; and connect the coordinates of the first intersection shape point and the coordinates of the second intersection shape point to generate the intersection surface of the target intersection node.

[0016] In some alternative examples, the processing unit is used to: solve the objective function based on a preset constraint optimization model under the constraints and the road surface width information of the road to obtain the offset distance of the road.

[0017] A third aspect of this application provides an intersection face generation apparatus, including: a memory, an input / output (I / O) interface, and a processor. The memory stores program instructions. The processor executes the program instructions in the memory to perform the intersection face generation method corresponding to the embodiment of the first aspect described above.

[0018] A fourth aspect of this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method corresponding to the embodiments of the first aspect described above.

[0019] The fifth aspect of this application provides a computer program product containing instructions that, when run on a computer or processor, causes the computer or processor to execute the method described above for performing the implementation method of the first aspect.

[0020] As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

[0021] In this embodiment, road information of the target intersection node is obtained, and the road surface width information of each road is determined based on the road information. Constraints and an objective function are also obtained. The objective function indicates the objective of determining the area size of the intersection surface of the target intersection node. Constraints include the constraint relationship between the bias variables of every two adjacent roads, which can be used to indicate the limitation conditions for the area size. The objective function includes at least two bias variables. Thus, based on the road surface width information and constraints, the objective function can be solved to calculate the bias distance of each road. Then, the intersection surface of the target intersection node is generated based on the road surface width information and the road bias distance. This method only requires constructing constraints based on the constraint relationship between the bias variables of adjacent roads and combining the road surface width information to calculate the road bias distance, without relying on complex pure geometric algorithms, thereby efficiently generating the intersection surface of the intersection node. Furthermore, in some complex road scenarios, the corresponding accurate bias distance can be calculated by modifying the constraints, thereby obtaining an intersection surface that better meets the product's expected requirements, demonstrating strong scalability. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This illustration shows an application scenario diagram of the method for generating intersection surfaces provided in this application;

[0024] Figure 2A A schematic diagram of a single-node intersection provided in an embodiment of this application is shown;

[0025] Figure 2BA schematic diagram of a composite node intersection provided in an embodiment of this application is shown;

[0026] Figure 3 A flowchart of a method for generating intersection surfaces provided in an embodiment of this application is shown;

[0027] Figure 4 This illustration shows a schematic diagram of a road widened according to an embodiment of this application;

[0028] Figure 5 This application provides a schematic diagram of the intersection of tangents in a road.

[0029] Figure 6 This illustration shows a schematic diagram of the relationship between the offset distances provided in the embodiments of this application;

[0030] Figure 7 This illustration shows a schematic diagram of tangents that do not intersect or intersect at their endpoints, provided in an embodiment of this application.

[0031] Figure 8 A schematic diagram of an intersection surface provided in an embodiment of this application is shown;

[0032] Figure 9 A schematic diagram of one embodiment of the intersection face generation device provided in this application is shown;

[0033] Figure 10 A schematic diagram of the hardware structure of the intersection face generation device provided in the embodiments of this application is shown. Detailed Implementation

[0034] This application provides a method and related apparatus for generating intersection surfaces. It constructs constraint conditions based on the constraint relationship between the offset variables of adjacent roads, without relying on complex pure geometric algorithms, and efficiently generates intersection surfaces of intersection nodes. Furthermore, by modifying the constraint conditions, the corresponding accurate offset distance can be calculated, thereby obtaining intersection surfaces that better meet the expected needs of the product, and has strong scalability.

[0035] It is understood that in the specific embodiments of this application, data such as user information are involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0036] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0037] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that implementations of the application described herein can be implemented, for example, in sequences other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0038] An intersection facet is a spatial area representing an intersection on an electronic map. Generating accurate intersection facests not only provides navigation engines with base map data at intersections, enhancing the visualization of the navigation interface, but also provides data support for autonomous driving decision-making at intersections, or for individuals using electronic maps to make driving decisions, such as drivers. This prevents vehicles from exceeding the intersection's boundaries, thereby reducing the probability of accidents at intersections and improving the safety of autonomous driving.

[0039] The method for generating intersection surfaces provided in this application involves at least the following technologies: intelligent transportation systems, cloud computing, and computer vision. For example, intersection surfaces of target intersection nodes can be generated using road network data from electronic maps. In some examples, intelligent transportation systems can also be used to provide intelligent navigation route services to drivers and other driving entities based on the location information and contours of the intersection surfaces. Alternatively, terminal devices can also utilize computer vision technologies to more realistically and clearly display high-precision 3D images corresponding to the intersection surfaces on navigation application pages or map pages.

[0040] Intelligent Traffic Systems (ITS), also known as Intelligent Transportation Systems, effectively integrate advanced science and technology (information technology, computer technology, data communication technology, sensor technology, electronic control technology, automatic control theory, operations research, artificial intelligence, etc.) into transportation, service control, and vehicle manufacturing. This strengthens the connection between vehicles, roads, and users, thereby forming a comprehensive transportation system that ensures safety, improves efficiency, enhances the environment, and saves energy.

[0041] With the research and advancement of artificial intelligence (AI) technology, it has been applied in numerous fields, including smart homes, wearable devices, virtual assistants, smart speakers, smart marketing, autonomous driving, drones, robots, smart healthcare, smart customer service, connected vehicles, and intelligent transportation. It is believed that with further technological development, AI will be applied in even more areas and play an increasingly important role. Among these, intelligent transportation, connected vehicles, autonomous driving, and driverless driving technologies typically include high-precision mapping, environmental perception, behavioral decision-making, path planning, and motion control, and currently have broad application prospects.

[0042] Computer vision (CV) is a science that studies how to enable machines to "see." More specifically, it refers to using cameras and computers to replace human eyes for tasks such as target recognition, tracking, and measurement, and further processing images to create images more suitable for human observation or transmission to instruments. As a scientific discipline, computer vision studies related theories and technologies, attempting to build artificial intelligence systems capable of extracting information from images or multidimensional data. Computer vision technologies typically include image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content / behavior recognition, 3D object reconstruction, 3D technology, virtual reality, augmented reality, simultaneous localization and mapping (SLAM), autonomous driving, intelligent transportation, and common biometric recognition technologies such as facial recognition and fingerprint recognition.

[0043] In related technologies, the generation of intersection surfaces typically relies on pure geometric algorithms to calculate the pre-set offset distances for each road. However, pure geometric algorithms have poor scalability, and due to factors such as the coupling of related geometric conditions, the intersection surfaces generated by pure geometric algorithms often deviate significantly from the actual intersection areas, failing to meet the product's intended requirements. Furthermore, existing technologies for generating intersection surfaces for lane-level navigation primarily use high-precision map data. However, due to limitations, the coverage area of ​​high-precision map data is limited, making it impossible to generate corresponding intersection surfaces in areas without high-precision map data.

[0044] Based on this, in order to solve the aforementioned technical problems, embodiments of this application provide a method for generating intersection surfaces. This method does not rely on pure geometric algorithms with poor scalability to generate intersection surfaces of intersection nodes, and the intersection surfaces generated by the method provided in this application embodiment can meet the expected needs of the product. It is not only applicable to high-precision map scenarios, but also can obtain effects similar to those brought by high-precision map data in areas where high-precision map data is unavailable.

[0045] Figure 1 This is a schematic diagram illustrating an application scenario of the method for generating intersection surfaces provided in this application. For example... Figure 1 As shown, this application scenario includes a server. For example, it may also include terminal devices. The described server can be an application server, and the terminal device also has the application installed. The terminal device and the server can interact with each other based on the application. The server can store road information of intersection nodes, as well as road network data such as road width information for each road, and then use the road network data to generate the intersection surface of the intersection node. For example, the server can send the location information of the generated intersection surface to the terminal device, so that the terminal device can display the intersection surface based on the location information.

[0046] It should be noted that in practical applications, road network data such as road information of the target intersection node can also be stored in the terminal device, and the terminal device can generate the intersection surface based on the road network data. Specifically, in this application embodiment, the executing entity for generating the intersection surface is not limited. In the following embodiments of this application, only the server is used as the executing entity for illustration.

[0047] Additionally, the application can be a map application, a navigation application, or any application that supports displaying a map page, such as a transportation application. The terminal device can be an in-vehicle navigation terminal or in-vehicle computer, a smartphone, tablet, laptop, mobile internet device, personal digital assistant (PDA), desktop computer, smart speaker, smartwatch, etc.

[0048] A server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server or server cluster that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms. Terminal devices and servers can be connected directly or indirectly via wired or wireless communication, but are not limited to these methods. The specific connection can be determined based on the actual application scenario requirements, and is not limited here.

[0049] In addition, the above Figure 1 The intersection nodes described herein can be understood as intersections where at least two roads meet. An intersection can be understood as a location where at least two roads converge, and is generally represented by several nodes. Based on the number of nodes included, intersections can be divided into single-node intersections and composite-node intersections. Therefore, an intersection node can include both single-node and composite-node intersections. For example, Figure 2A A schematic diagram of a single-node intersection provided in an embodiment of this application is shown. For example... Figure 2A As shown, in a scenario where the intersection is a single-node intersection, four roads (link) 1 to link 4 converge at the same intersection (i.e., Figure 2A In point A). For example, Figure 2B A schematic diagram of a composite node intersection provided in an embodiment of this application is shown. Figure 2B As shown, in a scenario where the intersection is a composite intersection, it can consist of four single-node intersections. Each single-node intersection is also composed of four roads converging at the same intersection, as detailed above. Figure 2A The content shown is for your understanding and will not be elaborated upon here.

[0050] It should be noted that, for Figure 2A and Figure 2B The intersection node shown in the diagram, which converges to four roads, is merely illustrative. In practical applications, it can converge to two, three, six, ten, or more roads, etc. This application does not impose any specific limitations. Furthermore, in... Figure 2A The single-node intersection shown in the figure and Figure 2B The composite node intersection shown only illustrates the case where links are perpendicular to each other. In practical applications, there may be cases where links are not perpendicular, and this application does not impose specific limitations. Subsequent embodiments of this application will only use examples from the perspective of... Figure 2A and Figure 2B The following example illustrates mutually perpendicular links.

[0051] In addition, from Figure 2B As can be seen, a composite node intersection is actually composed of at least two single-node intersections. Therefore, in the subsequent description of the method for generating intersection surfaces provided in this application, only the example of a single-node intersection will be used. Figure 2A The single-node intersection shown is used as an example to describe the target intersection node in detail. The process of generating the corresponding intersection surface based on the composite node intersection can also be understood by referring to the process of generating the intersection surface of the single-node intersection, and will not be described in detail in this embodiment.

[0052] by Figure 2A Taking the single-node intersection scenario shown as an example, the following describes a method for generating an intersection surface provided by an embodiment of this application, in conjunction with the accompanying drawings. Figure 3 A flowchart illustrating a method for generating intersection surfaces according to an embodiment of this application is shown. Figure 3 As shown, the method for generating intersection faces may include the following steps:

[0053] 301. Obtain the road information of the target intersection node. The road information includes at least two roads.

[0054] In this example, the target intersection node can be one of the aforementioned nodes. Figure 2A The single-node intersection shown can also be Figure 2B The composite node intersection shown is not described in detail here. The following discussion will only focus on the target intersection node. Figure 2A The following example illustrates a single-node intersection. For a target intersection node, by obtaining the relevant road information, it can be determined how many roads converge towards that target intersection node. For instance, this road information may include at least two roads that jointly connect to the target intersection node. Figure 2A The single-node intersection shown can include 4 links, all of which are connected to the same target intersection node A.

[0055] 302. Determine the road surface width information for each road based on the road information.

[0056] In this example, the road mentioned is typically represented as a narrow line segment in a standard navigation map. Therefore, before generating the intersection face of the target intersection node, this narrow line segment needs to be widened into a road face with a certain width. For example, the road face width information for each road can be determined based on the road information, reflecting the specific width of the road face. The described road width information may include, but is not limited to, the width of the road face, etc., and this application does not impose specific limitations on it.

[0057] In some examples, the road surface width can be varied depending on the road's classification. For instance, in urban road classification, arterial roads are classified higher than secondary arterial roads, and secondary arterial roads are classified higher than local roads. Furthermore, the higher the road classification, the wider the corresponding road surface. For example, arterial roads are generally wider than secondary arterial roads, and secondary arterial roads are wider than local roads. Based on this, the specific implementation process for determining the road surface width information of each road in step 302 can be as follows: determine the road classification of each road based on the road information, and then determine the corresponding road surface width information based on the road classification of each road.

[0058] In addition, the road surface of each road includes a left sub-road surface and a right sub-road surface. The width information of the left sub-road surface and the width information of the right sub-road surface together constitute the road surface width information of the road.

[0059] For example, as mentioned above Figure 2A Taking the single-node intersection shown as an example, Figure 4 This illustration shows a schematic diagram of a road widening according to an embodiment of this application. Figure 4 As shown, for the four roads (link1 to link4) at the target intersection node A, each road can be widened to a road surface with a certain width. For example, for link1, its corresponding road surface width information is derived from the road surface width information of the sub-road surface to the left of link1 (i.e., l w1 The road width information of the right sub-road surface of link1 (i.e., r) w1 The road width information for link2 is also composed of the road width information of the sub-road surface to the left of link2 (i.e., l). w2 The road width information of the right sub-road surface of link2 (i.e., r) w2 Similarly, the road width information for link3 and link4 can be understood by referring to the road width information for link1 and link2, and will not be elaborated here.

[0060] It should be noted that the roads described above may include, but are not limited to, main roads, secondary roads, and local roads. In practical applications, roads may also include expressways, neighborhood roads, etc., and this application embodiment does not impose specific limitations. Furthermore, regarding... Figure 4 The l shown in the middle w1 r w1 l w2 r w2 The values ​​of road surface width information can be the same or different, and this application does not specify any particular limitations.

[0061] 303. Obtain the constraints and objective function, wherein the objective function is used to indicate the objective of solving the area size of the intersection face of the target intersection node, the constraints are used to indicate the restrictions on the area size, the constraints include the constraint relationship between the bias variables of each of the at least two adjacent roads, and the objective function includes at least two bias variables, each bias variable being used to indicate the distance between the target intersection node and the tangent of the corresponding road.

[0062] In this example, if the tangents of each road intersect, the shape of the intersection surface of the target intersection node will be abnormal, failing to accurately reflect the real intersection surface. Therefore, to ensure the intersection surface shape is not abnormal, the tangents of each road must not intersect. Each road is perpendicular to its corresponding tangent, and the position of the tangent can be represented by the distance from the intersection of the tangent and the link to the target intersection node. It should be understood that the tangent intersection mentioned in this embodiment refers to the intersection at the middle part of the tangent, excluding the intersection at the endpoints of the two tangents.

[0063] If the distance from the intersection of the tangent and the link to the target intersection node is called the offset distance described later in this application, then whether the tangents corresponding to each road intersect depends on the offset distance of each road. For example, if the road offset distance is too small, the corresponding tangents will intersect in the middle of the tangent, resulting in an abnormal intersection shape. Figure 5 A schematic diagram of the tangent intersection of roads provided in an embodiment of this application is shown. For example... Figure 5As shown, the tangent line of link1 (L1) intersects the tangent line of link2 (L2). This intersection of L1 and L2 is limited by the value of the bias variable of link1 (w1) and the value of the bias variable of the adjacent link2 (w2). Similarly, the intersection of L2 and the tangent line of link3 (L3) is also limited by the value of w2 and the value of the bias variable of the adjacent link3 (w3). The cases of L3 intersecting the tangent line of link4 (L4) and L4 intersecting L1 can be understood by referring to the cases of L1 intersecting L2 or L2 intersecting L3, and will not be elaborated here. It should be understood that... Figure 5 The illustrated road tangent intersections are based on the example of all four links intersecting. In practical applications, only two or three links may intersect; this application does not impose any limitations on this. Furthermore, the mentioned bias variable can be used to indicate the distance between the target intersection node and the corresponding road tangent. For example, w1 can be used to indicate the distance between the target intersection node A and the tangent L1 of link 1. When the bias variable is assigned a specific value, it can be called the bias distance.

[0064] Based on this, the value of w1 affects the value of its neighbor w2, the value of w2 affects the value of its neighbor w3, the value of w3 affects the value of its neighbor w4, and the value of w4 affects the value of its neighbor w1. Similarly, the value of w1 affects the value of its neighbor w4, the value of w4 affects the value of its neighbor w3, the value of w3 affects the value of its neighbor w2, and the value of w2 affects the value of its neighbor w1. Clearly, regardless of whether the sorting is performed clockwise or counterclockwise on the four links of the same target intersection node, the coupling relationship between the bias variables w1, w2, w3, and w4 is circular. (See [reference needed] for details.) Figure 6 The diagram illustrating the relationship between the offset distances is provided for understanding. This coupling relationship is difficult to handle using purely geometric algorithms in existing solutions. Therefore, in this embodiment, a mathematical optimization method can be used to handle this coupling relationship, transforming the constraint relationships between the offset variables of each road into constraint equations for an optimization problem.

[0065] As mentioned before, the tangents of each road should meet the following two conditions: ① The tangent is perpendicular to the road (e.g., L1 is perpendicular to link); ② The tangents do not intersect each other or intersect only at their endpoints. Based on this, as described above... Figure 4 Taking the scenario shown as an example, establish the constraint equations that the bias variables should satisfy. For details, please refer to [reference needed]. Figure 7 The diagrams shown illustrate whether the tangents do not intersect or intersect at their endpoints.

[0066] like Figure 7 As shown, if the value of the bias variable w for each road is to be such that the tangents L of the corresponding roads do not intersect or only intersect at the endpoints, then the constraint condition can be constructed based on the constraint relationship between the bias variables of each two adjacent roads.

[0067] The constraint relationship between the bias variables of each pair of adjacent roads can be constructed using the included angle information between them. For example, the included angle information between each pair of adjacent roads can be determined based on the road width information and the corresponding road bias variables, and then constraint conditions can be constructed based on this included angle information. The included angle information is used to indicate the intersection between the corresponding tangents of the two adjacent roads. The specific details of the intersection between the tangents can be found in the foregoing description. Figure 5 The content shown in the image is for your understanding and will not be elaborated upon here.

[0068] Alternatively, the constraints can be constructed as follows: Obtain the included angle between the first road and the second road, where the first road and the second road are adjacent roads among at least two roads; obtain the first included angle between the first road and the boundary line of its right sub-road surface, the second included angle between the second road and the boundary line of its left sub-road surface, and the third included angle between the boundary line of the right sub-road surface of the first road and the boundary line of the left sub-road surface of the second road. Then, construct the constraints based on the included angle between the first road and the second road, as well as the first, second, and third included angles.

[0069] For example, the coordinates of the road shape points of the first road and the second road can be obtained. Then, based on the coordinates of the road shape points of the first and second roads, the angle between the first and second roads can be calculated. It should be noted that if the road shapes of the first and second roads are fixed, then the angle between the roads calculated from the coordinates of the road shape points is also fixed; that is, the angle between the first and second roads obtained is a specific value.

[0070] Furthermore, the first included angle can also be obtained from the road width information of the right sub-road surface of the first road and the bias variable of the first road. Similarly, the second included angle can be obtained from the road width information of the left sub-road surface of the second road and the bias variable of the second road. It should be noted that the described first and second included angles are functions related to the bias variable w of the corresponding roads.

[0071] The descriptions of the left and right sub-road surfaces can be found in the preceding text. Figure 4 The content described herein will be understood in detail here, and will not be repeated.

[0072] The sum of the first, second, and third included angles mentioned above is less than or equal to the included angle between the first road and the second road.

[0073] For example, with Figure 7 Taking the diagram in the upper right corner as an example, Figure 7 In this diagram, link1 can be understood as the first road, and link2 as the second road; link1 and link2 are adjacent. Point A can be considered the target road node. The intersection of tangent L1 and the boundary line of the right sub-road surface of link1 is P1, and the intersection of tangent L2 and the boundary line of the left sub-road surface of link2 is P2.

[0074] Using point A as the origin, the angle between link1 and link2, α, can be calculated from the coordinates of the road shape points of link1 and link2. 12 .

[0075] Similarly, taking point A as the origin, the first included angle, α1, can be obtained by calculating the angle between link1 and P1A. For example, since tangent L1 is perpendicular to link1, and the width of the road surface on the right side of link1 is r... w1 Therefore, the width of the right sub-road surface of link1 can be determined by the arctangent function. w1 The bias variable w1 of link1 is processed to obtain...

[0076] The second included angle, α2, can be obtained by calculating the angle between link2 and P2A. For example, since the tangent L2 is perpendicular to link2, and the width of the road surface on the left side of link2 is l... w2 Therefore, the width of the road surface of the left sub-road surface of link2 can also be determined by the arctangent function. w2 The bias variable w2 of link2 is processed to obtain...

[0077] To ensure that L1 and L2 do not intersect or intersect only at their endpoints, the included angles α1 and α2 should satisfy: α1 + α2 + mina1 ≤ α 12 ,Right now: Wherein, mina1 is the minimum value of the included angle P1AP2, that is, the included angle between the boundary line of the right sub-road surface of link1 and the boundary line of the left sub-road surface of link2. In addition, a1≥0.

[0078] Generally, if a target intersection node is associated with n (n>1) roads, then n constraints should be constructed. For example, regarding the aforementioned... Figure 7 Given a target intersection node A, which is associated with 4 roads, 4 constraints can be constructed for this target intersection node A, as follows:

[0079]

[0080]

[0081]

[0082]

[0083] It should be noted that It is constructed based on the angle information between link3 and link3, where α3 is the angle between link2 and P3A, α4 is the angle between link2 and P4A, and a2 is the angle between P3A and P4A. It is constructed based on the angle information between link3 and link4, where α5 is the angle between link3 and P5A, α6 is the angle between link4 and P6A, and a3 is the angle between P5A and P6A. It is constructed based on the angle information between link4 and link1, where α7 is the angle between link4 and P7A, α8 is the angle between link1 and P8A, and a4 is the angle between P7A and P8A. For details, please refer to the aforementioned... Figure 7 The constraints between link1 and link2 are explained in the text, but will not be elaborated on here.

[0084] Furthermore, under the premise of satisfying the constraints described above, it is desirable to minimize the intersection face of the generated target intersection node. In this case, the size of the intersection face of the target intersection node can be used as the objective function, and this size can be limited by the constraints constructed above. It should be noted that this objective function includes at least two bias variables, and the constraint relationship between each bias variable can be understood by referring to the constraints constructed above, which will not be elaborated here. In other words, the size of the intersection face is affected by the value of the bias variable of the road associated with the target intersection node. Therefore, the value of the bias variable w of the road associated with the target intersection node can be used as a representation of the size of the intersection face of the target intersection node. For example, for... Figure 7For the target intersection node A, when the size of the intersection area is represented by the sum of the squares of the bias variables w, the size of the intersection area can be expressed as: V = w1 2 +w2 2 +w3 2 +w4 2 Where w1, w2, w3, and w4 are the bias variables of the corresponding links1, link2, link3, and link4.

[0085] It should be noted that, in addition to using the sum of squares of the bias variables to represent the size of the intersection area, in practical applications, it may also be represented by the sum of cubes of the bias variables, the sum of N (N≥2) powers, the sum of absolute values, etc., but no specific limitation is made in the embodiments of this application.

[0086] In this way, we can construct an objective function for the size of the area of ​​the intersection, namely minV = w1. 2 +w2 2 +w3 2 +w4 2 .

[0087] 304. Solve the objective function based on the road width information and the constraints to obtain the offset distance of the road.

[0088] In this example, after the aforementioned step 303, where the constraints and objective function are constructed and obtained, the objective function can be solved based on the road width information and the constraints. This allows for the calculation of the specific value of each bias variable in the objective function, thus obtaining the bias distance for each road. For instance, after constructing the constraints and objective function, the present application can be constructed. Figure 7 The optimal mathematical model for the target intersection node is as follows:

[0089] minV=w1 2 +w2 2 +w3 2 +w4 2

[0090] st

[0091]

[0092]

[0093]

[0094]

[0095] w1>0

[0096] w2>0

[0097] w3>0

[0098] w4>0

[0099] In this way, under the constraints and road width information, the objective function can be solved using a pre-defined constraint optimization model such as the interior point method. For example, after obtaining the road width information for each road (including the road width information of the left and right sub-roads), the pre-defined constraint optimization model can be used to process the road width information for each road, thereby obtaining the specific value of the bias variable for each road, i.e., obtaining the optimal solution for the bias distance of each road.

[0100] 305. Generate the intersection surface of the target intersection node based on the road surface width information and the road offset distance.

[0101] In this example, after calculating the offset distance of each road, the intersection face of the target intersection node can be generated based on the road width information of each road and the corresponding offset distance. For example, the position of the intersection shape point can be determined based on the road width information of each road and the corresponding offset distance. Thus, after obtaining the position of the intersection shape point, the intersection face of the target intersection node can be generated based on the position of the intersection shape point. It should be noted that the described intersection shape point can indicate the regional contour features of the intersection face, such as those mentioned above. Figure 7 The eight intersection shape points, P1 to P8, can accurately describe the regional outline of the intersection face.

[0102] Schematic illustration: The determination of the location of each intersection shape point can be implemented as follows: Based on the road width information of the right sub-road surface of the first road and the offset distance of the first road, calculate the coordinates of the first intersection shape point. The first intersection shape point is the intersection of the tangent of the first road and the boundary line of the right sub-road surface of the first road. The coordinates of the first intersection shape point indicate its location. Based on the road width information of the left sub-road surface of the second road and the offset distance of the second road, calculate the coordinates of the second intersection shape point. The second intersection shape point is the intersection of the tangent of the second road and the boundary line of the left sub-road surface of the second road. The coordinates of the second intersection shape point indicate its location. Then, by connecting the coordinates of the first intersection shape point and the coordinates of the second intersection shape point, the intersection surface of the target intersection node can be generated.

[0103] For example, with Figure 8Taking P1 as the shape point of the first intersection and P2 as the shape point of the second intersection as an example, the road width information of the right sub-road surface of link1 has already been calculated, i.e., r. w1 And step 304 calculates the specific value of the bias variable w1 of link1. At this point, the coordinates of point P1 can be calculated simply by taking the target landmark node A as the origin and applying the Pythagorean theorem. Similarly, the road width information of the left sub-road surface of link2, i.e., l, has already been calculated. w2 Furthermore, step 304 calculates the specific value of the bias variable w2 for link2. At this point, the coordinates of point P2 can be calculated by using the Pythagorean theorem with the target landmark node A as the origin.

[0104] Based on the same principle, the coordinates of the remaining intersection shape points (i.e., P3 to P8) can be obtained. Connecting these intersection shape points with straight lines yields the intersection surface. See the attached diagram for details. Figure 8 Please refer to the schematic diagram of the intersection shown for comprehension.

[0105] In some examples, after the intersection surface is generated, it can also be displayed on a terminal device.

[0106] In this embodiment, road information of the target intersection node is obtained, and the road surface width information of each road is determined based on the road information. Constraints and an objective function are also obtained. The objective function indicates the objective of determining the area size of the intersection surface of the target intersection node. Constraints include the constraint relationship between the bias variables of every two adjacent roads, which can be used to indicate the limitation conditions for the area size. The objective function includes at least two bias variables. Thus, based on the road surface width information and constraints, the objective function can be solved to calculate the bias distance of each road. Then, the intersection surface of the target intersection node is generated based on the road surface width information and the road bias distance. This method only requires constructing constraints based on the constraint relationship between the bias variables of adjacent roads and combining the road surface width information to calculate the road bias distance, without relying on complex pure geometric algorithms, thereby efficiently generating the intersection surface of the intersection node. Furthermore, in some complex road scenarios, the corresponding accurate bias distance can be calculated by modifying the constraints, thereby obtaining an intersection surface that better meets the product's expected requirements, demonstrating strong scalability.

[0107] The foregoing primarily describes the solutions provided by the embodiments of this application from a methodological perspective. It is understood that to achieve the above functions, corresponding hardware structures and / or software modules are included to execute each function. Those skilled in the art should readily recognize that, based on the modules and algorithm steps described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0108] This application embodiment can divide the device into functional modules according to the above method example. For example, each function can be divided into its own functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0109] The intersection surface generation device in the embodiments of this application will be described in detail below. Figure 9 This is a schematic diagram of one embodiment of the intersection surface generation device provided in this application. Figure 9 As shown, the intersection face generation device may include an acquisition unit 901 and a processing unit 902.

[0110] The acquisition unit 901 acquires road information for the target intersection node, including at least two roads. The processing unit 902 determines the road surface width information for each road based on the road information. The acquisition unit 901 acquires constraints and an objective function. The objective function indicates the objective of determining the size of the intersection surface of the target intersection node, and the constraints indicate the limitations on the size of the area. The constraints include the constraint relationship between the bias variables of each pair of adjacent roads in the at least two roads. The objective function includes at least two bias variables, each indicating the distance between the tangent of the target intersection node and the corresponding road. The processing unit 902 calculates the road bias distance based on the road surface width information and the constraints, and generates the intersection surface of the target intersection node based on the road width information and the road bias distance.

[0111] In some optional examples, the processing unit 902 is used to: determine the included angle information between each pair of adjacent roads based on the road width information of each pair of adjacent roads and the corresponding road offset variable, wherein the included angle information is used to indicate the intersection between the corresponding tangents of the two adjacent roads; and construct constraint conditions based on the included angle information between each pair of adjacent roads.

[0112] In some optional examples, each road surface includes a left sub-road surface and a right sub-road surface. The acquisition unit 901 is used to: acquire the included angle between the first road and the second road, where the first road and the second road are adjacent roads among at least two roads; acquire a first included angle between the first road and the boundary line of the right sub-road surface of the first road, a second included angle between the second road and the boundary line of the left sub-road surface of the second road, and a third included angle between the boundary line of the right sub-road surface of the first road and the boundary line of the left sub-road surface of the second road; the processing unit 902 is used to construct constraint conditions based on the included angle between the first road and the second road, and the first, second, and third included angles.

[0113] In some other alternative examples, the sum of the first included angle, the second included angle, and the third included angle is less than or equal to the included angle between the first road and the second road.

[0114] In some alternative examples, the acquisition unit 901 is used to acquire the coordinates of the road shape points of the first road and the road shape points of the second road. The processing unit 902 is used to calculate the angle between the first road and the second road based on the coordinates of the road shape points of the first road and the road shape points of the second road.

[0115] In some alternative examples, the first included angle is represented by the road surface width information of the right sub-road surface of the first road and the offset variable of the first road.

[0116] In some alternative examples, the second included angle is obtained from the road surface width information of the left sub-road surface of the second road and the offset variable of the second road.

[0117] In some alternative examples, the processing unit 902 is used to: determine the road class of each road based on the road information; and determine the road surface width information of the corresponding road based on the road class of each road.

[0118] In some alternative examples, the processing unit 902 is used to: determine the position of the intersection shape point based on the road surface width information of each road and the corresponding road offset distance, the intersection shape point being used to indicate the regional contour features of the intersection surface; and generate the intersection surface of the target intersection node based on the position of the intersection shape point.

[0119] In some alternative examples, the road surface width information includes the road surface width information of the left sub-road surface and the road surface width information of the right sub-road surface. Processing unit 902 is configured to: calculate the coordinates of a first intersection shape point based on the road surface width information of the right sub-road surface of the first road and the offset distance of the first road; the first intersection shape point is the intersection of the tangent of the first road and the boundary line of the right sub-road surface of the first road, and the coordinates of the first intersection shape point are used to indicate the position of the first intersection shape point; calculate the coordinates of a second intersection shape point based on the road surface width information of the left sub-road surface of the second road and the offset distance of the second road; the second intersection shape point is the intersection of the tangent of the second road and the boundary line of the left sub-road surface of the second road, and the coordinates of the second intersection shape point are used to indicate the position of the second intersection shape point; and connect the coordinates of the first intersection shape point and the coordinates of the second intersection shape point to generate the intersection surface of the target intersection node.

[0120] In some alternative examples, the processing unit 902 is used to: solve the objective function based on a preset constraint optimization model under the constraints and the road surface width information of the road to obtain the road offset distance.

[0121] The intersection surface generation device in this application embodiment has been described above from the perspective of modular functional entities. The intersection surface generation device in this application embodiment has been described below from the perspective of hardware processing. Figure 10 This is a schematic diagram of the hardware structure of the intersection face generation device provided in this application embodiment. The intersection face generation device can vary considerably due to differences in configuration or performance. The intersection face generation device may include at least one processor 1001, a communication line 1007, a memory 1003, and at least one communication interface 1004.

[0122] The processor 1001 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (server IC), or one or more integrated circuits used to control the execution of the program of the present application.

[0123] The communication line 1007 may include a path for transmitting information between the aforementioned components.

[0124] Communication interface 1004 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0125] The memory 1003 can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions. The memory can exist independently and be connected to the processor via communication line 1007. The memory can also be integrated with the processor.

[0126] The memory 1003 stores computer execution instructions for implementing the scheme of this application, and the processor 1001 controls the execution. The processor 1001 executes the computer execution instructions stored in the memory 1003, thereby implementing the method for generating intersection surfaces provided in the above embodiments of this application.

[0127] Optionally, the computer execution instructions in the embodiments of this application may also be referred to as application code, and the embodiments of this application do not specifically limit this.

[0128] In a specific implementation, as one example, the voice recognition device may include multiple processors, such as... Figure 10 Processors 1001 and 1002 are described herein. Each of these processors may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor here may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0129] In a specific implementation, as one embodiment, the intersection face generation device may further include an output device 1005 and an input device 1006. The output device 1005 communicates with the processor 1001 and can display information in various ways. The input device 1006 communicates with the processor 1001 and can receive input from the target object in various ways. For example, the input device 1006 may be a mouse, a touch screen device, or a sensor device, etc.

[0130] The aforementioned intersection face generation device can be a general-purpose device or a dedicated device. In specific implementations, the intersection face generation device can be a server, a terminal, or something similar. Figure 10 A device with a similar structure. The embodiments of this application do not limit the type of the intersection face generation device.

[0131] It should be noted that Figure 10 The processor 1001 can invoke computer execution instructions stored in the memory 1003 to cause the intersection surface generation device to perform actions such as... Figure 3 The method in the corresponding method embodiment.

[0132] Specifically, Figure 9 The function / implementation process of the processing unit 902 in the middle can be achieved through Figure 10 The processor 1001 in the memory calls computer execution instructions stored in the memory 1003 to achieve this. Figure 9 The function / implementation process of the acquisition unit 901 can be achieved through... Figure 10 It is implemented using the communication interface 1004.

[0133] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0134] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0135] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0136] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0137] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0138] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0139] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, they can be implemented in whole or in part in the form of a computer program product.

[0140] A computer program product includes one or more computer instructions. When these computer instructions are loaded and executed on a computer, they generate, in whole or in part, the processes or functions according to embodiments of this application. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions may be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., SSDs), etc.

[0141] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for generating intersection surfaces, characterized in that, include: Obtain road information for the target intersection node, wherein the road information includes at least two roads; The road surface width information of each road is determined based on the road information; Obtain constraints and an objective function, wherein the objective function indicates the objective of solving for the size of the intersection face of the target intersection node, and the objective is to minimize the size of the intersection face of the target intersection node; the constraints indicate the restrictions on the size of the area, and the constraints include the constraint relationship between the bias variables of each two adjacent roads in the at least two roads, and the constraints are used to ensure that the tangents of each two adjacent roads do not intersect each other or intersect only at the endpoints of the tangents; the objective function includes at least two bias variables, each bias variable indicating the distance between the target intersection node and the tangent of the corresponding road; The objective function is solved based on the road width information and the constraints to obtain the offset distance of the road. The intersection face of the target intersection node is generated based on the road surface width information and the road offset distance.

2. The method according to claim 1, characterized in that, Obtaining constraints includes: The included angle information between each pair of adjacent roads is determined based on the road width information of each pair of adjacent roads and the corresponding road offset variable, wherein the included angle information is used to indicate the intersection between the corresponding tangents of the two adjacent roads. Constraints are constructed based on the angle information between each pair of adjacent roads.

3. The method according to claim 2, characterized in that, Each of the aforementioned roads comprises a left sub-road surface and a right sub-road surface. The constraint conditions constructed based on the angle information between any two adjacent roads include: Obtain the angle between the first road and the second road, wherein the first road and the second road are adjacent roads among the at least two roads; Obtain the first included angle between the boundary line of the first road and the right sub-road surface of the first road, the second included angle between the boundary line of the second road and the left sub-road surface of the second road, and the third included angle between the boundary line of the right sub-road surface of the first road and the boundary line of the left sub-road surface of the second road. Constraints are constructed based on the angle between the first road and the second road, as well as the first angle, the second angle, and the third angle.

4. The method according to claim 3, characterized in that, The sum of the first included angle, the second included angle, and the third included angle is less than or equal to the included angle between the first road and the second road.

5. The method according to claim 3 or 4, characterized in that, The step of obtaining the angle between the first road and the second road includes: Obtain the coordinates of the road shape points of the first road and the road shape points of the second road; Based on the coordinates of the road shape points of the first road and the road shape points of the second road, calculate the angle between the first road and the second road.

6. The method according to claim 3 or 4, characterized in that, The first included angle is obtained by the road surface width information of the right sub-road surface of the first road and the offset variable of the first road.

7. The method according to claim 3 or 4, characterized in that, The second included angle is obtained by the road surface width information of the left sub-road surface of the second road and the offset variable of the second road.

8. The method according to any one of claims 1 to 4, characterized in that, Determining the road surface width information of each road based on the road information includes: The road classification of each road is determined based on the road information; The road surface width information of each road is determined based on its road grade.

9. The method according to any one of claims 3 to 4, characterized in that, The process of generating the intersection face of the target intersection node based on the road surface width information and the road offset distance includes: Based on the road width information of each road and the corresponding road offset distance, the position of the intersection shape point is determined, and the intersection shape point is used to indicate the regional contour features of the intersection surface; The intersection face of the target intersection node is generated based on the position of the intersection shape point.

10. The method according to claim 9, characterized in that, The road surface width information includes the road surface width information of the left sub-road surface and the road surface width information of the right sub-road surface; determining the position of the intersection shape point based on the road surface width information of each road and the corresponding road offset distance includes: Based on the road width information of the right sub-road surface of the first road and the offset distance of the first road, the coordinates of the first intersection shape point are calculated. The first intersection shape point is the intersection between the tangent of the first road and the boundary line of the right sub-road surface of the first road. The coordinates of the first intersection shape point are used to indicate the position of the first intersection shape point. Based on the road width information of the left sub-road surface of the second road and the offset distance of the second road, the coordinates of the second intersection shape point are calculated. The second intersection shape point is the intersection of the tangent of the second road and the boundary line of the left sub-road surface of the second road. The coordinates of the second intersection shape point are used to indicate the position of the second intersection shape point. Generating the intersection face of the target intersection node based on the position of the intersection shape point includes: Connect the coordinates of the first intersection shape point with the coordinates of the second intersection shape point to generate the intersection surface of the target intersection node.

11. The method according to any one of claims 1 to 4, characterized in that, The step of solving the objective function based on the road width information and the constraints to obtain the road offset distance includes: Under the constraints and the road width information, the objective function is solved based on the preset constraint optimization model to obtain the offset distance of the road.

12. A road surface generation device, characterized in that, include: An acquisition unit is used to acquire road information of a target intersection node, wherein the road information includes at least two roads; The processing unit is used to determine the road surface width information of each road based on the road information; The acquisition unit is used to acquire constraints and an objective function, wherein the objective function is used to indicate the objective of solving the area size of the intersection face of the target intersection node, and the objective is to minimize the area size of the intersection face of the target intersection node; the constraints are used to indicate the restrictions on the area size, and the constraints include the constraint relationship between the bias variables of each of the at least two roads, and the constraints are used to ensure that the tangents of each of the two adjacent roads do not intersect each other or intersect only at the endpoints of the tangents; the objective function includes at least two bias variables, and each bias variable is used to indicate the distance between the target intersection node and the tangent of the corresponding road; The processing unit is used to calculate the offset distance of the road based on the road surface width information and the constraint conditions. The processing unit is used to generate the intersection face of the target intersection node based on the road width information and the road offset distance.

13. The apparatus according to claim 12, characterized in that, The processing unit is configured to determine the included angle information between each pair of adjacent roads based on the road width information and the corresponding road offset variable, wherein the included angle information is used to indicate the intersection between the corresponding tangents of the two adjacent roads; and to construct constraint conditions based on the included angle information between each pair of adjacent roads.

14. The apparatus according to claim 13, characterized in that, Each of the aforementioned roads includes a left sub-road surface and a right sub-road surface. The acquisition unit is configured to: acquire the included angle between the first road and the second road, wherein the first road and the second road are adjacent roads among the at least two roads; acquire a first included angle between the boundary line of the first road and the right sub-road surface of the first road, a second included angle between the boundary line of the second road and the left sub-road surface of the second road, and a third included angle between the boundary line of the right sub-road surface of the first road and the boundary line of the left sub-road surface of the second road; The processing unit is used to construct constraint conditions based on the angle between the first road and the second road, as well as the first angle, the second angle, and the third angle.

15. The apparatus according to claim 14, characterized in that, The sum of the first included angle, the second included angle, and the third included angle is less than or equal to the included angle between the first road and the second road.

16. A road surface generation device, characterized in that, include: Input / output (I / O) interface, processor, and memory, wherein program instructions are stored in the memory; The processor is configured to execute program instructions stored in the memory to perform the method as described in any one of claims 1 to 11.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes instructions that, when executed on a computer device, cause the computer device to perform the method as described in any one of claims 1 to 11.

18. A computer program product, characterized in that, The computer program product includes instructions that, when executed on a computer device, cause the computer device to perform the method as described in any one of claims 1 to 11.

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