Road network modeling method, system, computer device and readable storage medium

Abstract

The application relates to a road network modeling method, system, computer device and readable storage medium. The method comprises the following steps: reading a target file, obtaining an effective road layer and road line data in the effective road layer; extracting a road center line segment set in the road line data and constructing a road center line network; discretizing the road center line network to obtain a three-dimensional coordinate point set of the road center line network; segmenting the three-dimensional coordinate point set according to preset segmentation rules determined by road terminal end point boundaries, road intersection positions, road turning angle change positions and a road segment length threshold to form a plurality of basic road segments, and generating a single-line road network based on the plurality of basic road segments; obtaining configuration parameters of the road line in the target file, and constructing a multi-vehicle road network based on the configuration parameters and the single-line road network; wherein the configuration parameters comprise the number of lanes, the lane width, the driving direction and the up-and-down separation mode. The technical scheme can quickly construct an accurate road network model.

Description

Technical Field

[0001] This application relates to the field of traffic network modeling technology, and in particular to a network modeling method, system, computer equipment, and readable storage medium. Background Technology

[0002] Road network modeling aims to create a virtual road network to simulate traffic flow patterns, and it is an important means of evaluating road design schemes and traffic flow characteristics.

[0003] Traditional road network modeling primarily uses design drawings as a visual background reference, and the road network model is constructed by manually depicting geometric features. However, this modeling method relies heavily on repetitive manual operations, resulting in low construction efficiency and a tendency to produce topological errors when dealing with complex road network topologies.

[0004] There is currently no effective solution for how to quickly construct an accurate road network model in related technologies. Summary of the Invention

[0005] Therefore, it is necessary to provide a road network modeling method, system, computer equipment, and readable storage medium that can quickly construct accurate road network models to address the aforementioned technical problems.

[0006] Firstly, this application provides a road network modeling method, including:

[0007] Read the target file, obtain the valid road layer in the target file, and obtain the road alignment data in the target file from the valid road layer;

[0008] Extract the set of road centerline segments from the road alignment data, and construct a road centerline network based on the set of road centerline segments;

[0009] Discretize the road centerline network to obtain the three-dimensional coordinate point set of the road centerline network;

[0010] The three-dimensional coordinate point set is segmented according to a preset segmentation rule to form multiple basic road segments, and a single-line road network is generated based on the multiple basic road segments; wherein, the segmentation rule is determined by a combination of the road end point boundary, the road intersection position, the road turning angle change position, and the road segment length threshold.

[0011] Obtain the configuration parameters of the road alignment in the target file, and construct a multi-vehicle road network based on the configuration parameters and the single-line road network; wherein, the configuration parameters include the number of lanes, lane width, driving direction and up / down separation mode, and the up / down separation mode is used to determine whether a lane is a one-way lane or a two-way lane.

[0012] In one embodiment, extracting the set of road centerline segments from the road alignment data includes:

[0013] The road alignment data is classified into two-sided alignment data, single-center alignment data, and intersection and ramp alignment data.

[0014] Based on the classification results, road centerline segments are generated using the road centerline segment generation method corresponding to various types of road alignment data, thus forming a road centerline segment set;

[0015] When the data is bilateral alignment data or intersection and ramp alignment data, the corresponding algorithm is used to generate the road centerline segment;

[0016] When the data is a single-centerline line, it is directly used as the centerline segment of the road.

[0017] In one embodiment, generating a single-line road network based on multiple base road segments includes:

[0018] At the starting and ending points of the road, at road intersections, and at the division points of the multiple basic road segments, a unique topology node is generated, and a corresponding three-dimensional coordinate is associated with each topology node.

[0019] A single-line road network is generated based on multiple basic road segments, topological nodes, and associated three-dimensional coordinates.

[0020] In one embodiment, obtaining the configuration parameters of the road alignment in the target file and constructing a multi-vehicle road network based on the configuration parameters and the single-line road network includes:

[0021] Using the single-line road network as a reference, a planar geometric offset algorithm is used to generate multiple lanes between two topological nodes at each of the basic road segment divisions, taking into account the lane width and the number of lanes.

[0022] The direction of travel for each lane is determined based on the driving direction and the up-and-down separation mode;

[0023] The travel direction of each lane is associated with the topology node corresponding to each lane to establish the correspondence between the travel direction of each lane, the topology node corresponding to each lane, and the corresponding three-dimensional coordinates.

[0024] Based on the correspondence, the single-line road network, and the road alignment data, determine the turning lane rules corresponding to the road alignment data;

[0025] The multi-vehicle road network is constructed based on the multiple lanes, the travel direction of each lane, the correspondence, and the turning lane rules.

[0026] In one embodiment, discretizing the road centerline network to obtain a three-dimensional coordinate point set of the road centerline network includes: sampling the road centerline network along the direction of the road centerline network according to a preset step size to obtain multiple sampling points; extracting the plane X coordinate, plane Y coordinate, and elevation information corresponding to each sampling point; and generating the three-dimensional coordinate point set based on the plane X coordinate, plane Y coordinate, and corresponding elevation information of each sampling point.

[0027] In one embodiment, the road alignment data includes left and right road edge data, ramp boundary data, and hub outline data.

[0028] In one embodiment, after constructing the multi-vehicle road network, the road network modeling method further includes: outputting the constructed multi-vehicle road network as a multi-lane simulation road network file in a specific format for importing into the corresponding simulation software.

[0029] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0030] Obtain road alignment data from the target file;

[0031] Extract the set of road centerline segments from the road alignment data, and construct a road centerline network based on the set of road centerline segments;

[0032] Discretize the road centerline network to obtain the three-dimensional coordinate point set of the road centerline network;

[0033] Based on the set of three-dimensional coordinate points, a single-line road network is generated;

[0034] Obtain the configuration parameters of the road alignment in the target file, and construct a multi-vehicle road network based on the configuration parameters and the single-line road network.

[0035] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0036] Obtain road alignment data from the target file;

[0037] Extract the set of road centerline segments from the road alignment data, and construct a road centerline network based on the set of road centerline segments;

[0038] Discretize the road centerline network to obtain the three-dimensional coordinate point set of the road centerline network;

[0039] Based on the set of three-dimensional coordinate points, a single-line road network is generated;

[0040] Obtain the configuration parameters of the road alignment in the target file, and construct a multi-vehicle road network based on the configuration parameters and the single-line road network.

[0041] The aforementioned road network modeling method, system, computer equipment, and readable storage medium employ the following steps: acquiring road alignment data from a target file; extracting a set of road centerline segments from the road alignment data and constructing a road centerline network based on the road centerline segment set; discretizing the road centerline network to obtain a set of three-dimensional coordinate points for the road centerline network; generating a single-line road network based on the three-dimensional coordinate point set; acquiring configuration parameters of the road alignment in the target file; and constructing a multi-vehicle road network based on the configuration parameters and the single-line road network. This enables automated construction from raw road alignment data to a multi-vehicle road network, improving the efficiency and accuracy of road network modeling. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart illustrating a road network modeling method in one embodiment;

[0044] Figure 2 This is a schematic diagram of multi-lane generation based on topology nodes in an example embodiment;

[0045] Figure 3 This is a flowchart illustrating a road network modeling method in an example embodiment;

[0046] Figure 4 This is a structural block diagram of a road network modeling system in one embodiment;

[0047] Figure 5 This is an internal structural diagram of a computer device in an example embodiment. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0049] In one embodiment, such as Figure 1 As shown, a road network modeling method is provided, which includes the following steps:

[0050] Step 102: Read the target file, obtain the valid road layer in the target file, and obtain the road alignment data in the target file from the valid road layer.

[0051] Optionally, the target file may be a CAD, GIS, or high-precision map original surveying file.

[0052] Optionally, after reading the target file and before obtaining the valid road layers in the target file, the method further includes removing the non-road layers in the target file.

[0053] Optionally, reading the target file and obtaining the valid road layers in the target file includes: obtaining layers containing road design specification keywords from the target file, the keywords including centerline; excluding non-road layers such as labels, text, and legends; filtering invalid geometric elements based on spatial characteristics such as line length, continuity, and alignment consistency, the invalid geometric elements including broken lines, short lines, and repeated lines; and retaining the filtered valid road layers for road network modeling.

[0054] Step 104: Extract the set of road centerline segments from the road alignment data, and construct a road centerline network based on the set of road centerline segments.

[0055] Optionally, when constructing a road centerline network based on the set of road centerline segments, the set of road centerline segments is first normalized to obtain a road centerline network that is uninterrupted, abrupt, continuous, smooth, and perfectly conforms to the design alignment; wherein, the normalization process includes breakpoint repair, misalignment correction, corner smoothing, and overlap elimination.

[0056] Step 106: Discretize the road centerline network to obtain the three-dimensional coordinate point set of the road centerline network.

[0057] Optionally, after obtaining the set of three-dimensional coordinate points, the set of three-dimensional coordinate points is output as a standardized text dataset.

[0058] Step 108: Divide the three-dimensional coordinate point set into segments according to preset segmentation rules to form multiple basic road segments, and generate a single-line road network based on the multiple basic road segments; wherein, the segmentation rules are determined by a combination of road end point boundaries, road intersection positions, road turning angle change positions, and road segment length thresholds.

[0059] Optionally, before segmenting the three-dimensional coordinate point set according to a preset segmentation rule, the three-dimensional coordinate point set is further preprocessed. The preprocessing includes: based on the three-dimensional coordinate point set, removing duplicate coordinate points, smoothing elevation change points, and distinguishing between straight road segments and curved road segments to obtain a preprocessed three-dimensional coordinate point set.

[0060] Step 110: Obtain the configuration parameters of the road alignment in the target file, and construct a multi-vehicle road network based on the configuration parameters and the single-line road network; wherein, the configuration parameters include the number of lanes, lane width, driving direction and up / down separation mode, and the up / down separation mode is used to determine whether a lane is a one-way lane or a two-way lane.

[0061] Optionally, the configuration parameters may be manually input parameters.

[0062] It is understood that the configuration parameters also include other parameters, which can be set according to specific tasks.

[0063] In the above road network modeling method, road alignment data is obtained from the effective road layer of the target file, the road centerline segment set is extracted and the road centerline network is constructed, the three-dimensional coordinate point set is obtained through discretization to generate a single-line road network, and a multi-vehicle road network is constructed in combination with configuration parameters. This realizes the automated construction from the original road alignment data to the multi-vehicle road network, improving the efficiency and accuracy of road network modeling.

[0064] In one embodiment, extracting the road centerline segment set from the road alignment data includes: classifying the road alignment data into bilateral alignment data, single centerline alignment data, and intersection and ramp alignment data; generating road centerline segments according to the classification results using the road centerline segment generation method corresponding to each type of road alignment data to form a road centerline segment set; when it is bilateral alignment data or intersection and ramp alignment data, generating road centerline segments using the corresponding algorithm; when it is single centerline alignment data, directly using it as the road centerline segment.

[0065] Optionally, when the data is a two-sided alignment, the centerline algorithm is used to calculate the center position point by point to generate the road centerline segment; when the data is an intersection and ramp alignment, the circular arc tangent and smooth transition algorithm is used for fitting to generate the road centerline segment.

[0066] This embodiment enables targeted processing of different road alignment data types, ensuring the accuracy of road centerline segment extraction.

[0067] In one embodiment, generating a single-line road network based on multiple basic road segments includes: generating a unique topology node at the starting and ending points of the road, at road intersections, and at the division points of the multiple basic road segments, and associating a corresponding three-dimensional coordinate at each topology node; and generating a single-line road network based on the multiple basic road segments, the topology nodes, and the associated three-dimensional coordinates.

[0068] Optionally, after generating the single-line road network, the geometric dimensions, elevation continuity, and topological connectivity of the generated single-line road network are verified according to road design specifications, and abnormal topological structures are automatically corrected.

[0069] In this embodiment, an accurate single-line road network can be constructed by reconstructing the three-dimensional space of the topology nodes.

[0070] In one embodiment, obtaining the configuration parameters of the road alignment in the target file and constructing a multi-vehicle road network based on the configuration parameters and the single-line road network includes: using the single-line road network as a reference, employing a planar geometric offset algorithm, and utilizing the lane width and the number of lanes, generating multiple lanes between two topological nodes at each of the basic road segment divisions; determining the travel direction of each lane according to the driving direction and the up / down separation mode; associating the travel direction of each lane with the corresponding topological node of each lane to establish a correspondence between the travel direction of each lane, the corresponding topological node of each lane, and the corresponding three-dimensional coordinates; determining the turning lane rules corresponding to the road alignment data based on the correspondence, the single-line road network, and the road alignment data; and constructing the multi-vehicle road network based on the multiple lanes, the travel direction of each lane, the correspondence, and the turning lane rules.

[0071] Optionally, when the up-and-down separation mode is determined to be a one-way multi-lane road, the travel direction of each lane is set to be consistent with the driving direction, and the lane closer to the center line of the road is marked as a fast lane and the lane closer to the shoulder is marked as a slow lane to indicate lane priority; when the up-and-down separation mode is determined to be a two-way multi-lane road, the lanes are grouped into up-way lane groups and down-way lane groups according to the up-and-down separation mode, and the up-way lane groups and down-way lane groups are assigned opposite travel directions according to the driving direction.

[0072] Optionally, after determining the travel direction of each lane, attribute verification is performed based on the travel direction of each lane and the geometric orientation of the road centerline network. The attribute verification includes: determining whether the geometric orientation contradicts the travel direction of each lane, and determining whether the logical association of the travel direction of each lane in the correspondence is complete. When there is a contradiction or incompleteness, an early warning instruction is generated to prompt manual verification and correction.

[0073] Optionally, after determining the travel direction of each lane, the method further includes associating the travel direction of each lane, multiple basic road segments, and the three-dimensional coordinates corresponding to the multiple basic road segments; and incorporating the travel direction of each lane into the merging and diverging rules to construct a multi-vehicle road network.

[0074] Optionally, when data corresponding to a ramp is identified in the road alignment data, the connection relationship between the ramp and the main lane and the type of the ramp are determined based on the correspondence and the single-line road network to determine the corresponding turning lane rules; when data corresponding to a hub area is identified in the road alignment data, the connection relationship between the lanes in the hub area and the main lane and the function of the lanes in the hub area are determined based on the correspondence and the single-line road network to determine the corresponding turning lane rules; when data corresponding to a road intersection is identified in the road alignment data, the number of lanes at each approach lane of the road intersection, the traffic direction of each approach lane, and the type of the road intersection are determined based on the correspondence and the single-line road network to determine the corresponding turning lane rules.

[0075] Optionally, when the configuration parameters are updated, the multi-vehicle road network is updated accordingly.

[0076] In this embodiment, by combining geometric offset with traffic logic rules, an accurate multi-vehicle road network with complete traffic logic is generated.

[0077] In one example embodiment, such as Figure 2 As shown, when the number of lanes in the configuration parameters is 4, four lanes will be generated between topology node A and topology node B at a basic road segment segment, namely lane 1, lane 2, lane 3 and lane 4.

[0078] In one embodiment, discretizing the road centerline network to obtain a three-dimensional coordinate point set of the road centerline network includes: sampling the road centerline network along the direction of the road centerline network according to a preset step size to obtain multiple sampling points; extracting the plane X coordinate, plane Y coordinate, and elevation information corresponding to each sampling point; and generating the three-dimensional coordinate point set based on the plane X coordinate, plane Y coordinate, and corresponding elevation information of each sampling point.

[0079] Optionally, after extracting the plane X coordinate, plane Y coordinate and corresponding elevation information of the sampling points, duplicate points, points with a spacing less than a preset threshold and abnormal abrupt changes are removed, and all sampling points are arranged continuously and orderly according to the road travel direction.

[0080] Optionally, the preset step length can be a fixed length or dynamically adjusted according to the curvature of the road alignment. The preset step length can be a value between 0.5m and 2.5m. It is understood that the preset step length can be set according to actual needs.

[0081] This embodiment allows for the discretization of the road centerline network, providing a data foundation for constructing a single-line road network.

[0082] In one embodiment, the road alignment data includes left and right road edge data, ramp boundary data, and hub outline data.

[0083] It is understood that the road alignment data also includes other data that can characterize the road's geometric features or topological relationships, which can be obtained as needed.

[0084] This embodiment enables a wider variety of raw data input types for modeling, enhancing the modeling coverage of special road sections such as highway hubs and complex ramps.

[0085] In one embodiment, after constructing the multi-vehicle road network, the road network modeling method further includes: outputting the constructed multi-vehicle road network as a multi-lane simulation road network file in a specific format for importing into the corresponding simulation software.

[0086] Optionally, the specific format includes, but is not limited to, the .inpx format.

[0087] This embodiment enables format adaptation between the multi-vehicle road network model and simulation software, allowing the constructed multi-vehicle road network to be directly read and called by the simulation software. This avoids the inefficiency and error-prone problems caused by manually rebuilding the road network or manually converting the format, thereby improving the automation and accuracy of multi-vehicle road network simulation modeling.

[0088] In one example embodiment, a road network modeling method is provided. Figure 3 The flowchart of this method includes the following steps:

[0089] The target file is read, and non-road layers are removed to obtain valid road layers. Road alignment data is then extracted from the valid road layers. The road alignment data is classified, and based on the classification results, road centerline segments are generated using a method corresponding to each type of road alignment data to form a road centerline segment set. A road centerline network is constructed based on the road centerline segment set. The road centerline network is discretized to obtain a set of three-dimensional coordinate points for the road centerline network.

[0090] The three-dimensional coordinate point set is segmented according to a preset segmentation rule to form multiple basic road segments. The segmentation rule is determined by a combination of road start and end point boundaries, road intersection locations, road turning angle change locations, and road segment length thresholds. At the road start and end point locations, road intersection locations, and the division points of multiple basic road segments, a unique topology node is generated, and a corresponding three-dimensional coordinate is associated with each topology node. Based on the multiple basic road segments, topology nodes, and associated three-dimensional coordinates, a single-line road network is generated.

[0091] Obtain the configuration parameters of the road alignment in the target file, including the number of lanes, lane width, driving direction, and up / down separation mode;

[0092] Using a single-line road network as a reference, a planar geometric offset algorithm is employed to generate multiple lanes between two topological nodes at each basic road segment segmentation point, based on the lane width and the number of lanes. The travel direction of each lane is determined according to the driving direction and the up / down separation mode. The travel direction of each lane is then associated with its corresponding topological node to establish a correspondence between the travel direction of each lane, the corresponding topological node, and the corresponding three-dimensional coordinates. Based on this correspondence, the single-line road network, and road alignment data, turning lane rules corresponding to the road alignment data are determined. Finally, a multi-vehicle road network is constructed based on multiple lanes, the travel direction of each lane, the correspondence, and the turning lane rules.

[0093] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0094] Based on the same inventive concept, this application also provides a road network modeling system for implementing the road network modeling method described above. The solution provided by this system is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more road network modeling system embodiments provided below can be found in the limitations of the road network modeling method described above, and will not be repeated here.

[0095] In one embodiment, such as Figure 4As shown, a road network modeling system is provided, including:

[0096] Data parsing module 41 is used to read the target file, obtain the valid road layer in the target file, and obtain the road alignment data in the target file from the valid road layer;

[0097] The road centerline network construction module 42 is used to extract the road centerline segment set from the road alignment data and construct the road centerline network based on the road centerline segment set;

[0098] The coordinate transformation module 43 is used to discretize the road centerline network to obtain a three-dimensional coordinate point set of the road centerline network;

[0099] The single-line road network generation module 44 is used to segment the three-dimensional coordinate point set according to a preset segmentation rule to form multiple basic road segments, and generate a single-line road network based on the multiple basic road segments; wherein, the segmentation rule is determined by a combination of the road end point boundary, the road intersection position, the road turning angle change position and the road segment length threshold.

[0100] The configuration parameter acquisition module 45 is used to acquire the configuration parameters of the road alignment in the target file; wherein, the configuration parameters include the number of lanes, lane width, driving direction and up / down separation mode, and the up / down separation mode is used to determine whether the lane is a one-way lane or a two-way lane;

[0101] Multi-vehicle road network construction module 46 is used to construct a multi-vehicle road network based on the configuration parameters and the single-line road network.

[0102] The aforementioned road network modeling system obtains road alignment data from the valid road layers of the target file, extracts the road centerline segment set and constructs the road centerline network, obtains a three-dimensional coordinate point set through discretization to generate a single-line road network, and constructs a multi-vehicle road network in combination with configuration parameters. This achieves automated construction from raw road alignment data to a multi-vehicle road network, improving the efficiency and accuracy of road network modeling.

[0103] Each module in the aforementioned road network modeling system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0104] Further, the extraction of the road centerline segment set from the road alignment data includes: classifying the road alignment data into bilateral alignment data, single centerline alignment data, and intersection and ramp alignment data; generating road centerline segments according to the classification results using the road centerline segment generation method corresponding to each type of road alignment data to form a road centerline segment set; when it is bilateral alignment data or intersection and ramp alignment data, generating road centerline segments using the corresponding algorithm; when it is single centerline alignment data, directly using it as the road centerline segment.

[0105] Furthermore, the step of generating a single-line road network based on multiple basic road segments includes: generating a unique topology node at the starting and ending points of the road, at road intersections, and at the division points of the multiple basic road segments, and associating a corresponding three-dimensional coordinate at each topology node; and generating a single-line road network based on the multiple basic road segments, the topology nodes, and the associated three-dimensional coordinates.

[0106] Further, the step of obtaining the configuration parameters of the road alignment in the target file and constructing a multi-vehicle road network based on the configuration parameters and the single-line road network includes: using the single-line road network as a reference, employing a planar geometric offset algorithm, and utilizing the lane width and the number of lanes, generating multiple lanes between two topological nodes at each of the basic road segment divisions; determining the travel direction of each lane according to the driving direction and the up-and-down separation mode; associating the travel direction of each lane with the topological node corresponding to each lane to establish a correspondence between the travel direction of each lane, the topological node corresponding to each lane, and the corresponding three-dimensional coordinates; determining the turning lane rules corresponding to the road alignment data based on the correspondence, the single-line road network, and the road alignment data; and constructing the multi-vehicle road network based on the multiple lanes, the travel direction of each lane, the correspondence, and the turning lane rules.

[0107] Further, the discretization of the road centerline network to obtain the three-dimensional coordinate point set of the road centerline network includes: sampling the road centerline network along the direction of the road centerline network according to a preset step size to obtain multiple sampling points; extracting the plane X coordinate, plane Y coordinate, and elevation information corresponding to each sampling point; and generating the three-dimensional coordinate point set based on the plane X coordinate, plane Y coordinate, and corresponding elevation information of each sampling point.

[0108] Furthermore, the road alignment data includes left and right road edge data, ramp boundary data, and hub outline data.

[0109] Furthermore, the road network modeling system also includes a data export module, which is used to output the constructed multi-vehicle road network as a multi-lane simulation road network file in a specific format after the multi-vehicle road network is constructed, so as to import it into the corresponding simulation software.

[0110] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores road alignment data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements a road network modeling method.

[0111] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0112] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0113] The process involves: reading the target file, obtaining the valid road layer from the target file, and extracting the road alignment data from the valid road layer; extracting the road centerline segment set from the road alignment data and constructing a road centerline network based on the road centerline segment set; discretizing the road centerline network to obtain the three-dimensional coordinate point set of the road centerline network; segmenting the three-dimensional coordinate point set according to a preset segmentation rule to form multiple basic road segments, and generating a single-line road network based on the multiple basic road segments; wherein the segmentation rule is comprehensively determined by the road end-point boundaries, road intersection positions, road turning angle change positions, and road segment length thresholds; obtaining the configuration parameters of the road alignment in the target file, and constructing a multi-vehicle road network based on the configuration parameters and the single-line road network; wherein the configuration parameters include the number of lanes, lane width, driving direction, and up / down separation mode, the up / down separation mode being used to determine whether a lane is a one-way lane or a two-way lane.

[0114] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0115] The process involves: reading the target file, obtaining the valid road layer from the target file, and extracting the road alignment data from the valid road layer; extracting the road centerline segment set from the road alignment data and constructing a road centerline network based on the road centerline segment set; discretizing the road centerline network to obtain the three-dimensional coordinate point set of the road centerline network; segmenting the three-dimensional coordinate point set according to a preset segmentation rule to form multiple basic road segments, and generating a single-line road network based on the multiple basic road segments; wherein the segmentation rule is comprehensively determined by the road end-point boundaries, road intersection positions, road turning angle change positions, and road segment length thresholds; obtaining the configuration parameters of the road alignment in the target file, and constructing a multi-vehicle road network based on the configuration parameters and the single-line road network; wherein the configuration parameters include the number of lanes, lane width, driving direction, and up / down separation mode, the up / down separation mode being used to determine whether a lane is a one-way lane or a two-way lane.

[0116] 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, data stored, data displayed, 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 the relevant data must comply with relevant regulations.

[0117] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0118] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0119] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A road network modeling method, characterized in that, include: Read the target file, obtain the valid road layer in the target file, and obtain the road alignment data in the target file from the valid road layer; Extract the set of road centerline segments from the road alignment data, and construct a road centerline network based on the set of road centerline segments; Discretize the road centerline network to obtain the three-dimensional coordinate point set of the road centerline network; The three-dimensional coordinate point set is segmented according to a preset segmentation rule to form multiple basic road segments, and a single-line road network is generated based on the multiple basic road segments; wherein, the segmentation rule is determined by a combination of the road end point boundary, the road intersection position, the road turning angle change position, and the road segment length threshold. Obtain the configuration parameters of the road alignment in the target file, and construct a multi-vehicle road network based on the configuration parameters and the single-line road network; wherein, the configuration parameters include the number of lanes, lane width, driving direction and up / down separation mode, and the up / down separation mode is used to determine whether a lane is a one-way lane or a two-way lane; The step of generating a single-line road network based on multiple basic road segments includes: generating a unique topology node at the starting and ending points of the road, at road intersections, and at the division points of the multiple basic road segments, and associating a corresponding three-dimensional coordinate at each topology node; and generating a single-line road network based on the multiple basic road segments, the topology nodes, and the associated three-dimensional coordinates. The construction of a multi-vehicle road network based on the configuration parameters and the single-line road network includes: using the single-line road network as a reference, generating multiple lanes between two topological nodes at each of the basic road segment divisions using the lane width and the number of lanes; determining the travel direction of each lane according to the driving direction and the up / down separation mode; associating the travel direction of each lane with the corresponding topological node to establish a correspondence between the travel direction of each lane, the corresponding topological node of each lane, and the corresponding three-dimensional coordinates; and constructing a multi-vehicle road network based on the correspondence, the single-line road network, the road alignment data, the multiple lanes, and the travel direction of each lane.

2. The method according to claim 1, characterized in that, The extraction of the road centerline segment set from the road alignment data includes: The road alignment data is classified into two-sided alignment data, single-center alignment data, and intersection and ramp alignment data. Based on the classification results, road centerline segments are generated using the road centerline segment generation method corresponding to various types of road alignment data, thus forming a road centerline segment set; When the data is bilateral alignment data or intersection and ramp alignment data, the corresponding algorithm is used to generate the road centerline segment; When the data is a single-centerline line, it is directly used as the centerline segment of the road.

3. The method according to claim 1, characterized in that, The step of generating multiple lanes between two topological nodes at each of the basic road segment divisions, using the single-line road network as a reference benchmark and utilizing the lane width and the number of lanes, includes: Using the single-line road network as a reference, a planar geometric offset algorithm is used to generate multiple lanes between two topological nodes at each of the basic road segment divisions, taking into account the lane width and the number of lanes. The construction of a multi-vehicle road network based on the correspondence, the single-line road network, the road alignment data, the multiple lanes, and the travel direction of each lane includes: determining the turning lane rules corresponding to the road alignment data based on the correspondence, the single-line road network, and the road alignment data; and constructing the multi-vehicle road network based on the multiple lanes, the travel direction of each lane, the correspondence, and the turning lane rules.

4. The method according to claim 1, characterized in that, The discretization of the road centerline network to obtain the three-dimensional coordinate point set of the road centerline network includes: sampling the road centerline network along the direction of the road centerline network according to a preset step size to obtain multiple sampling points; extracting the plane X coordinate, plane Y coordinate, and elevation information corresponding to each sampling point; and generating the three-dimensional coordinate point set based on the plane X coordinate, plane Y coordinate, and corresponding elevation information of each sampling point.

5. The method according to claim 1, characterized in that, The road alignment data includes left and right road edge data, ramp boundary data, and hub outline data.

6. The method according to claim 1, characterized in that, After constructing the multi-vehicle road network, the method further includes: outputting the constructed multi-vehicle road network as a multi-lane simulation road network file in a specific format for importing into the corresponding simulation software.

7. A road network modeling system, characterized in that, The system includes: The data parsing module is used to read the target file, obtain the valid road layer in the target file, and obtain the road alignment data in the target file from the valid road layer; The road centerline network construction module is used to extract the road centerline segment set from the road alignment data and construct the road centerline network based on the road centerline segment set; The coordinate transformation module is used to discretize the road centerline network to obtain a three-dimensional coordinate point set of the road centerline network; A single-line road network generation module is used to segment the three-dimensional coordinate point set according to a preset segmentation rule to form multiple basic road segments, and generate a single-line road network based on the multiple basic road segments; wherein, the segmentation rule is determined by a combination of the road end point boundaries, road intersection positions, road turning angle change positions, and road segment length thresholds. The configuration parameter acquisition module is used to acquire the configuration parameters of the road alignment in the target file; wherein, the configuration parameters include the number of lanes, lane width, driving direction and up / down separation mode, and the up / down separation mode is used to determine whether a lane is a one-way lane or a two-way lane; A multi-vehicle road network construction module is used to construct a multi-vehicle road network based on the configuration parameters and the single-line road network. The step of generating a single-line road network based on multiple basic road segments includes: generating a unique topology node at the starting and ending points of the road, at road intersections, and at the division points of the multiple basic road segments, and associating a corresponding three-dimensional coordinate at each topology node; and generating a single-line road network based on the multiple basic road segments, the topology nodes, and the associated three-dimensional coordinates. The construction of a multi-vehicle road network based on the configuration parameters and the single-line road network includes: using the single-line road network as a reference, generating multiple lanes between two topological nodes at each of the basic road segment divisions using the lane width and the number of lanes; determining the travel direction of each lane according to the driving direction and the up / down separation mode; associating the travel direction of each lane with the corresponding topological node to establish a correspondence between the travel direction of each lane, the corresponding topological node of each lane, and the corresponding three-dimensional coordinates; and constructing a multi-vehicle road network based on the correspondence, the single-line road network, the road alignment data, the multiple lanes, and the travel direction of each lane.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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