A simulation modeling method, apparatus, electronic device, and storage medium

Abstract

This invention provides a simulation modeling method, apparatus, electronic device, and storage medium, relating to the field of intelligent transportation. One simulation modeling method includes: acquiring map data for a target road network area and target vehicle passage data for a specified time period; generating a simulation road network file for the target road network area based on the map data; determining vehicle trajectory information corresponding to each simulation moment in the simulation process based on vehicle passage data for each time point in the target vehicle passage data and the target correspondence; constructing a road network demand file for the target road network area using the vehicle trajectory information corresponding to each simulation moment; and constructing a traffic simulation model of the target road network area using specified simulation software based on the simulation road network file and the road network demand file. This solution can accurately recreate the real traffic scene of a road network area.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and in particular to a simulation modeling method, apparatus, electronic device, and storage medium. Background Technology

[0002] Traffic simulation modeling is an important experimental method and tool for reproducing the spatiotemporal characteristics of traffic flow, assessing traffic operation status, and verifying traffic control strategies.

[0003] In related technologies, simulation software, such as SUMO (an open-source microscopic simulation software developed by the German Aerospace Center), is used for simulation modeling. When using simulation software for simulation modeling, it is usually based on a simulated road network for the road network area created manually by the staff, as well as randomly generated simulated vehicles.

[0004] However, due to discrepancies between manually created simulated road networks and actual road network areas, and because randomly generated simulated vehicles cannot reflect real traffic conditions, the simulation modeling solutions provided by related technologies cannot accurately reproduce the real traffic scenarios in road network areas. Summary of the Invention

[0005] The purpose of this invention is to provide a simulation modeling method, device, electronic device, and storage medium to accurately reproduce the real traffic scene in a road network area. The specific technical solution is as follows:

[0006] In a first aspect, embodiments of the present invention provide a simulation modeling method, including:

[0007] Acquire map data for a target road network area and target vehicle passage data for a specified time period;

[0008] Based on the map data, a simulated road network file is generated for the target road network area; wherein, the simulated road network file is used to describe the road segments and intersections of the target road network area;

[0009] Based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence, the vehicle trajectory information corresponding to each simulation moment in the simulation process is determined; wherein, the target correspondence is the correspondence between each time point and each simulation moment in the simulation process, and the vehicle trajectory information includes the license plate number and location information of each vehicle.

[0010] Using the vehicle trajectory information corresponding to each simulation moment, a road network requirement file is constructed for the target road network area; wherein, the road network requirement file is used to describe the motion information of vehicles in the simulated road network;

[0011] Based on the simulated road network file and the road network requirement file, a traffic simulation model of the target road network area is constructed using the specified simulation software.

[0012] Optionally, the step of constructing a traffic simulation model of the target road network area using specified simulation software based on the simulated road network file and the road network demand file includes:

[0013] The simulated road network file is loaded into the specified simulation software to generate a simulated road network for the target road network area;

[0014] The road network requirement file is loaded into the simulated road network generated by the simulation software to obtain the traffic simulation model of the target road network area.

[0015] Optionally, determining the vehicle trajectory information corresponding to each simulation moment in the simulation process based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence includes:

[0016] The target vehicle passage data is broken down to obtain vehicle passage data for each time point;

[0017] For each simulation moment, the corresponding time point is determined from the target correspondence, and the vehicle passage data for the determined time point is used as the vehicle passage data for that simulation moment.

[0018] For each simulation moment, the vehicle trajectory information corresponding to that simulation moment is obtained from the vehicle passing data at that simulation moment.

[0019] Optionally, the step of constructing a road network requirement file for the target road network area using the vehicle trajectory information corresponding to each simulation time point includes:

[0020] Based on the vehicle trajectory information corresponding to the first simulation moment, the simulation vehicle information for the first simulation moment is determined; wherein, the simulation vehicle information includes: each simulation vehicle identifier and the location information corresponding to each simulation vehicle identifier, and different simulation vehicle identifiers have different license plate numbers;

[0021] The first simulation moment is taken as the current simulation moment;

[0022] Using the simulated vehicle information at the current simulation moment and the vehicle trajectory information at the next simulation moment, calculate the simulated vehicle information at the next simulation moment;

[0023] The next simulation moment is taken as the new current simulation moment, and the steps of calculating the simulation vehicle information for the next simulation moment using the simulation vehicle information at the current simulation moment and the vehicle trajectory information corresponding to the next simulation moment are returned until the simulation vehicle information for the last simulation moment is obtained.

[0024] A file containing simulation vehicle information at each simulation time is constructed to obtain the road network requirement file for the target road network area.

[0025] Optionally, the step of calculating the simulation vehicle information for the next simulation time using the simulation vehicle information at the current simulation time and the vehicle trajectory information corresponding to the next simulation time includes:

[0026] Compare the license plate numbers corresponding to each simulated vehicle identifier in the simulated vehicle information at the current simulation time with the license plate numbers in the vehicle trajectory information at the next simulation time.

[0027] Based on the comparison results, the simulation vehicle information at the current simulation moment is updated to obtain the simulation vehicle information for the next simulation moment, in the following manner:

[0028] For the first type of license plate number represented by the comparison result, the location information corresponding to the simulation vehicle identifier with the first type of license plate number in the simulation vehicle information at the current simulation time is updated according to the location information corresponding to the first type of license plate number in the vehicle trajectory information at the next simulation time; wherein, the first type of license plate number is the license plate number of a simulation vehicle identifier in the simulation vehicle information at the current simulation time, and is included in the vehicle trajectory information at the next simulation time.

[0029] For the second type of license plate number represented by the comparison result, the simulation vehicle information with the second type of license plate number and the corresponding location information are added to the simulation vehicle information at the current simulation time; wherein, the corresponding location information is the location information corresponding to the second type of license plate number in the vehicle trajectory information at the next simulation time, and the second type of license plate number is only included in the vehicle trajectory information at the next simulation time.

[0030] For the third type of license plate number represented by the comparison result, from the simulation vehicle information at the current simulation time, the simulation vehicle identifier with the second type of license plate number and its corresponding location information are removed; wherein, the third type of license plate number is only the license plate number of a simulation vehicle identifier in the simulation vehicle information at the current simulation time.

[0031] Optionally, generating a simulated road network file for the target road network area based on the map data includes:

[0032] The map data is parsed to obtain point data and line data; wherein, the point data is used to describe the location points on intersections and road segments in the target road network area, and the line data is used to describe the road segments in the target road network area, and the road segments are formed based on each location point;

[0033] The road network topology relationship of the target road network area is extracted from the point data and line data, and the extracted road network topology relationship is used to construct the point file, edge file and connection file required for the simulation process;

[0034] Using the point file, edge file, and connection file, a simulation road network file for the target road network region is generated.

[0035] Optionally, extracting the road network topology of the target road network area from the point data and line data includes:

[0036] Based on the point data, the shape and location information of the intersections in the target road network area are identified;

[0037] Based on the line data, identify road segments and lane data within the target road network area;

[0038] Based on the identified intersection location information, as well as the identified road segment and lane data, connection information is determined to characterize the road connectivity status.

[0039] Optionally, identifying the shape and location information of the intersections in the target road network area based on the point data includes:

[0040] Identify whether each location point in the point data belongs to the edge point of the intersection;

[0041] For each position point belonging to the edge point of the intersection, sort them, determine the shape formed when connecting each position point according to the sorted sequence, and use it as the shape of the intersection in the target road network area. Based on each position point belonging to the edge point of the intersection, determine the location information of the intersection.

[0042] Optionally, the identification of road segment and lane data within the target road network area based on line data includes:

[0043] Determine each endpoint of the line segment represented in the line data, and identify the start and end points of each road segment in the target road network area based on the position information of each endpoint and the position information of the identified intersection.

[0044] For each of the aforementioned road segments, determine the direction to which that road segment belongs;

[0045] From the line data, determine the lane data within each road segment.

[0046] Optionally, determining the connection information characterizing the road connectivity state based on the identified intersection location information and the identified road segment and lane data includes:

[0047] Based on the identified intersection location information, as well as the identified road segment and lane data, the lane data for each road direction and the lane data for each road direction of the intersection in the target road network area are determined to obtain connection information that characterizes the road connectivity status.

[0048] Optionally, the step of constructing the point file, edge file, and connection file required for the simulation process using the extracted road network topology includes:

[0049] Using the identified shape and location information of the intersections, point files required for the simulation process are generated;

[0050] Using the identified road segment and lane data, generate the side files required for the simulation process;

[0051] Using the identified connectivity information that characterizes road connectivity, the connection files required for the simulation process are generated.

[0052] Optionally, generating a simulation road network file for the target road network region using the point file, edge file, and connection file includes:

[0053] Using the target tool provided by the specified simulation software for generating road network files, the point files, edge files, and connection files are integrated into a simulated road network file for the target road network region.

[0054] Secondly, embodiments of the present invention provide a simulation modeling apparatus, comprising:

[0055] The data acquisition module is used to acquire map data for a target road network area and target vehicle passage data for a specified time period; wherein, the map data can represent the information of road segments and intersections in the target road network area, and the target vehicle passage data records the real trajectory information of each vehicle;

[0056] The file generation module is used to generate a simulated road network file for the target road network area based on the map data; wherein, the simulated road network file is used to describe the road segments and intersections of the target road network area;

[0057] The information determination module is used to determine the vehicle trajectory information corresponding to each simulation moment in the simulation process based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence relationship; wherein, the target correspondence relationship is the correspondence relationship between each time point and each simulation moment in the simulation process, and the vehicle trajectory information includes the license plate number and location information of each vehicle.

[0058] The file construction module is used to construct a road network requirement file for the target road network area using the vehicle trajectory information corresponding to each simulation time point; wherein, the road network requirement file is used to describe the motion information of vehicles in the simulated road network;

[0059] The traffic simulation module is used to construct a traffic simulation model of the target road network area using specified simulation software, based on the simulated road network file and the road network demand file.

[0060] Thirdly, embodiments of the present invention provide an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0061] Memory, used to store computer programs;

[0062] The processor, when executing a program stored in memory, implements any of the above simulation modeling methods.

[0063] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements any of the above-described simulation modeling methods.

[0064] Fifthly, embodiments of the present invention also provide a computer program product containing instructions that, when run on a computer, cause the computer to execute any of the simulation modeling methods described above.

[0065] Beneficial effects of the embodiments of the present invention:

[0066] The simulation modeling method provided in this invention utilizes map data for a target road network area to generate a simulation road network file for that area. This allows the simulation file to recreate the actual road network situation of the target area during simulation using specified simulation software. Furthermore, after acquiring target vehicle passage data for a specified time period within the target road network area, the method determines the vehicle trajectory information corresponding to each simulation moment based on the vehicle passage data at each time point and the target correspondence. Using this vehicle trajectory information, a road network requirement file for the target road network area is constructed. This allows the actual vehicle movement information of the target road network area to be recreated using the road network requirement file during simulation using specified simulation software. Therefore, this solution can accurately recreate the real traffic scene of a road network area.

[0067] Of course, implementing any product or method of the present invention does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0068] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 the present invention. For those skilled in the art, other embodiments can be obtained based on these drawings.

[0069] Figure 1 A flowchart illustrating a simulation modeling method provided in an embodiment of the present invention;

[0070] Figure 2 This is another flowchart of a simulation modeling method provided in an embodiment of the present invention;

[0071] Figure 3 This is another flowchart of a simulation modeling method provided in an embodiment of the present invention;

[0072] Figure 4 A schematic diagram illustrating the simulation principle of a simulation modeling method provided in an embodiment of the present invention;

[0073] Figure 5(a) shows a road diagram displayed using QGIS software;

[0074] Figure 5(b) is a schematic diagram of the result of converting a polygon layer to a point layer for map data;

[0075] Figure 5(c) is a schematic diagram of the line layer result converted from map data;

[0076] Figure 5(d) is a schematic diagram of the simulated road network results using the method provided in the embodiments of the present invention;

[0077] Figure 5(e) is a schematic diagram of the simulation modeling results using the method provided in the embodiments of the present invention;

[0078] Figure 6 This is a schematic diagram of the structure of a simulation modeling device provided in an embodiment of the present invention;

[0079] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0080] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art based on this application are within the scope of protection of the present invention.

[0081] Below, we will first introduce the technical terms involved in the embodiments of this invention:

[0082] Traffic simulation modeling: a process of solving dynamic traffic system models using numerical methods, which can dynamically and realistically simulate various traffic phenomena such as traffic flow and traffic events.

[0083] SUMO: An open-source microscopic simulation software developed by the German Aerospace Center. It has become the most commonly used traffic simulation technology due to its strong open-source nature, diverse application functions, fast modeling, and high running efficiency.

[0084] High-precision map data, also known as high-definition maps, is electronic map data with high-precision location information and rich content. It can possess accurate and abundant road element data, such as lane data, intersection data, and road marking data. In practical applications, high-precision maps can be obtained by acquiring maps using LiDAR (Light Detection and Ranging) technology.

[0085] QGIS (Quantum GIS): An open-source geographic information system that supports the visualization, management, editing, and analysis of map data and the production of print maps; furthermore, QGIS supports many raster and vector data formats, and new format support can be easily added using a plug-in architecture.

[0086] Road network file: also known as simulation road network file, usually named as *.net.xml, is used to describe traffic-related parts of the map, such as roads (also known as road segments) and intersection information that vehicles pass through.

[0087] Node files: also known as point files, are usually named as *.nod.xml and are XML format files used to describe the names, types, and locations of intersections in the simulated road network.

[0088] Edge files: The commonly used file naming format is *.edge.xml, which is an XML format file used to describe the road names, number of lanes, road point coordinates, road speed limits and other attributes of the road network connecting upstream and downstream intersections.

[0089] Connection files, typically named *.con.xml, describe the information about the interconnections between upstream and downstream roads in the simulated road network. They also include the names of the upstream and downstream roads and the lane numbers connected to them.

[0090] The requirements document, also known as the road network requirements document, is usually named as *.rou.xml. It is used to describe the movement information of vehicles in the simulated road network. It can be the route information of the road segments that the vehicle passes through, or the origin and destination information of the vehicle, etc.

[0091] To accurately reproduce the real traffic scene in a road network area, embodiments of the present invention provide a simulation modeling method, device, electronic device, and storage medium.

[0092] The following section first introduces a simulation modeling method provided by the embodiments of the invention.

[0093] The simulation modeling method provided in this embodiment of the invention can be applied to electronic devices. In specific applications, the electronic device can be a terminal device or a server; this embodiment of the invention does not limit the specific form of the electronic device.

[0094] Specifically, the entity executing this simulation modeling method can be a simulation modeling device. For example, when the simulation modeling method is applied to a terminal device, the simulation modeling device can be a client running on the terminal device for performing simulation modeling. For example, when the simulation modeling method is applied to a server, the simulation modeling device can be a computer program running on the server, which can be used for simulation modeling.

[0095] The simulation modeling method provided in this embodiment of the invention may include:

[0096] Acquire map data for a target road network area and target vehicle passage data for a specified time period;

[0097] Based on the map data, a simulated road network file is generated for the target road network area; wherein, the simulated road network file is used to describe the road segments and intersections of the target road network area;

[0098] Based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence, the vehicle trajectory information corresponding to each simulation moment in the simulation process is determined; wherein, the target correspondence is the correspondence between each time point and each simulation moment in the simulation process, and the vehicle trajectory information includes the license plate number and location information of each vehicle.

[0099] Using the vehicle trajectory information corresponding to each simulation moment, a road network requirement file is constructed for the target road network area; wherein, the road network requirement file is used to describe the motion information of vehicles in the simulated road network;

[0100] Based on the simulated road network file and the road network requirement file, a traffic simulation model of the target road network area is constructed using the specified simulation software.

[0101] The simulation modeling method provided in this invention utilizes map data for a target road network area to generate a simulation road network file for that area. This allows the simulation file to recreate the actual road network situation of the target area during simulation using specified simulation software. Furthermore, after acquiring target vehicle passage data for a specified time period within the target road network area, the method determines the vehicle trajectory information corresponding to each simulation moment based on the vehicle passage data at each time point and the target correspondence. Using this vehicle trajectory information, a road network requirement file for the target road network area is constructed. This allows the actual vehicle movement information of the target road network area to be recreated using the road network requirement file during simulation using specified simulation software. Therefore, this solution can accurately recreate the real traffic scene of a road network area.

[0102] Furthermore, the embodiments of the present invention use map data for the target road network area to simulate the road network. Compared with converting measured road network data with the basic lane road network, this avoids the problem of low accuracy caused by coordinate transformation. Moreover, compared with manually obtaining node data of each road segment in the road network area, such as determining lane data of the road network area based on the description of intersections, this can reduce labor costs and reduce errors that are prone to occur during manual input. At the same time, the embodiments of the present invention use map data for the target road network area to simulate the road network, which can also solve the following problems: road networks drawn manually or directly generated have certain deviations from the actual road network, and the editing and correction process is very time-consuming.

[0103] Furthermore, the embodiments of the present invention use target vehicle data for the target road network area to simulate vehicles. Compared with using randomly generated vehicle path files or road cross-sectional flow information obtained by detectors to simulate vehicles, this method can obtain the real trajectory information of each vehicle, thus accurately recreating the real traffic scene.

[0104] The following description, in conjunction with the accompanying drawings, introduces a simulation modeling method provided by an embodiment of the present invention.

[0105] like Figure 1 As shown, the simulation modeling method provided in this embodiment of the invention may include the following steps:

[0106] S101, Obtain map data for the target road network area and target vehicle passage data for a specified time period;

[0107] The target road network area can be any road network area that requires simulation, such as a road network area with a high frequency of congestion, or other road network areas that require simulation. This embodiment of the invention does not limit this. In addition, for example, the so-called road network area can include road segments and intersections.

[0108] Furthermore, the map data for the target road network area can characterize the information of road segments and intersections within that area. For example, in one implementation, the map data for the target road network area can be high-precision map data obtained through LiDAR acquisition. Of course, while ensuring the road information required for simulation, this embodiment of the invention does not limit the specific type of map data for the target road network area.

[0109] Optionally, in one implementation, the map data is in JSON format, and the map features within the file are stored using a GeoJSON data structure. Specifically, map features are stored as "rings" (polylines) and "paths" (polygons), but this is not a limitation. GeoJSON is a format for encoding various geographic data structures, a geospatial information data exchange format based on JavaScript Object Notation (JSON). For example, in a specific application, the map data can be stored in two JSON files. One JSON file records road edges in the form of polylines and polygons, while the other JSON file records sign and marking information in the same form. Based on the road edge information, the coordinates and shape information of intersection center points can be automatically identified and extracted. However, the polygons containing sign and marking information, due to their complex data structure, often lack some features, resulting in incomplete information. Therefore, they cannot be automatically identified directly based on coordinate data. Manual annotation of lane widening and lane information can be used to assist in the generation of the simulated road network.

[0110] In addition, for the target vehicle passage data within a specified time period in the target road network area, the actual trajectory information and vehicle information of each vehicle passing through the target road network area within the specified time period are recorded. For example, the target vehicle passage data may include: trajectory information and license plate numbers of each vehicle appearing in the target road network area within the specified time period, as well as other information, such as: time information, vehicle color, vehicle angle, vehicle type, etc. Furthermore, there can be multiple methods for generating the target vehicle passage data. This embodiment of the invention does not limit the method of generating the target vehicle passage data. For example, the target vehicle passage data can be obtained based on image data collected by a camera device, or it can be obtained based on data collected by a radar-based device. The radar-based device is a device combining radar and camera equipment. Data collected by the radar-based device can obtain highly accurate vehicle passage data.

[0111] Understandably, the specified time period can be determined according to actual needs. For example, if 8:00-8:30 am is the peak period for the target road network area, then any weekday from 8:00-8:30 am can be selected as the specified time period; or, if there is a need to simulate from 2:00 pm to 2:30 pm, then any weekday from 2:00 pm to 2:30 pm can be selected as the specified time period, and so on.

[0112] S102, Based on the map data, generate a simulated road network file for the target road network area; wherein, the simulated road network file is used to describe the road segments and intersections of the target road network area;

[0113] After obtaining the map data for the target road network area, in order to recreate the real traffic scene of the target road network area, the map data can be pre-analyzed and processed to generate a simulation road network file for the target road network area. This simulation road network file can then be used to recreate the road network situation of the target road network area.

[0114] It is important to emphasize that any method capable of generating a simulated road network file for the target road network area based on map data can be applied to this solution. For clarity and layout, another embodiment will be used subsequently to illustrate the specific implementation method of generating a simulated road network file for the target road network area based on the map data.

[0115] S103, Based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence, determine the vehicle trajectory information corresponding to each simulation moment in the simulation process; wherein, the target correspondence is the correspondence between each time point and each simulation moment in the simulation process, and the vehicle trajectory information includes the license plate number and location information of each vehicle.

[0116] Since the simulation process is a continuous process composed of various simulation moments, to recreate the true motion information of the vehicles during the simulation, we can first determine the vehicle trajectory information corresponding to each simulation moment, that is, the real vehicle motion information related to each simulation moment. Each simulation moment can correspond to a point in time within a specified time period. Therefore, based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence, the vehicle trajectory information corresponding to each simulation moment in the simulation process can be determined. It is important to emphasize that the vehicle trajectory information can at least include the license plate number and location information of each vehicle. Of course, the vehicle trajectory information can also include: vehicle color, vehicle angle, etc.; and the target correspondence can be constructed based on the duration of the specified time period, the simulation duration, and the simulation step size.

[0117] In the vehicle simulation process, a simulation step size can be pre-set. Different simulation step sizes result in different simulation moments for the same simulation duration, leading to different time points and target correspondences. For example, if the simulation step size is one second, then each simulation moment is a simulation second. Assuming a specified time period is half an hour, the entire simulation process lasts half an hour, resulting in 1800 simulation moments, each representing one simulation second. Correspondingly, the aforementioned time points are the 1800 time points within the specified time period, i.e., 1800 seconds. The target correspondence is the relationship between the 1800 time points within the specified time period and each simulation second, with one time point corresponding to one simulation second. It is important to emphasize that the simulation step size is not limited to the second level; the specific simulation step size used can be determined based on the actual situation.

[0118] For example, in one implementation, determining the vehicle trajectory information corresponding to each simulation moment in the simulation process based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence may include steps A1-A3:

[0119] Step A1: Decompose the target vehicle passage data to obtain vehicle passage data for each time point;

[0120] Step A2: For each simulation moment, determine the time point corresponding to that simulation moment from the target correspondence relationship, and use the vehicle passage data for the determined time point as the vehicle passage data for that simulation moment.

[0121] Step A3: For each simulation moment, obtain the vehicle trajectory information corresponding to that simulation moment from the vehicle passing data at that simulation moment.

[0122] When decomposing the target vehicle passage data, the decomposition granularity can be based on a pre-set simulation step size. For example, assuming the simulation step size is one second, the simulation time is a simulation second. Accordingly, the target vehicle passage data can be decomposed at the second level to obtain the vehicle passage data for each second within a specified time period.

[0123] After obtaining the vehicle passage data at each time point, the target correspondence can be used to map the vehicle passage data at each time point to each simulation moment, obtaining the vehicle passage data corresponding to each simulation moment. Then, from the vehicle passage data corresponding to each simulation moment, the vehicle trajectory information required for each simulation moment can be extracted. It should be noted that when obtaining vehicle trajectory information, ASCII code conversion can be performed on the Chinese characters in the license plate to convert them to Chinese characters. Simultaneously, trajectory data without license plates can be discarded.

[0124] It should be emphasized that the above-described specific implementation method for determining the vehicle trajectory information corresponding to each simulation moment in the simulation process based on the vehicle passage data at each time point in the target vehicle passage data and the target correspondence is merely an example and should not constitute a limitation on the embodiments of the present invention.

[0125] S104, using the vehicle trajectory information corresponding to each simulation time point, construct a road network requirement file for the target road network area; wherein, the road network requirement file is used to describe the motion information of vehicles in the simulated road network;

[0126] After obtaining the vehicle trajectory information corresponding to each simulation moment, since subsequent simulations require the use of specific simulation software, a road network requirement file for the target road network area can be constructed using the vehicle trajectory information corresponding to each simulation moment. This road network requirement file can then be applied to the specified simulation software for simulation.

[0127] To ensure clarity of the solution and layout, the following describes, in conjunction with another embodiment, the specific implementation method of constructing a road network requirement file for the target road network area using the vehicle trajectory information corresponding to each simulation moment.

[0128] S105. Based on the simulated road network file and the road network requirement file, construct a traffic simulation model of the target road network area using the specified simulation software.

[0129] After the simulated road network file and road network requirement file are constructed, the real road network information and real vehicle movement information representing the target road network area are known. Therefore, a traffic simulation model of the target road network area can be constructed using the specified simulation software based on the simulated road network file and the road network requirement file. In this embodiment of the invention, the specific type of specified simulation software is not limited. For example, the specified simulation software can be SUMO (an open-source microscopic simulation software developed by the German Aerospace Center); of course, the specified simulation software can also be other simulation software, such as TESS NG (TESS Next Generation, a domestically developed microscopic traffic simulation software), TransModeler (a traffic simulation model based on a geographic information system), etc.

[0130] In one alternative implementation, constructing a traffic simulation model of the target road network area using specified simulation software based on the simulated road network file and the road network demand file may include steps B1-B2:

[0131] Step B1: Load the simulated road network file into the specified simulation software to generate a simulated road network for the target road network area;

[0132] Step B2: Load the road network requirement file into the simulated road network generated by the simulation software to obtain the traffic simulation model of the target road network area.

[0133] The specified simulation software can utilize the road information represented by the simulated road network file to generate a simulated road network for the target road network area; and based on the vehicle motion information represented by the road network requirement file, it displays simulated vehicles at various simulation times within the simulated road network, with each simulated vehicle having corresponding location information, thereby obtaining a traffic simulation model for the target road network area. It should be noted that the process by which the specified simulation software generates the simulated road network using the simulated road network file is not limited in this embodiment of the invention; nor is the process by which the specified simulation software uses the road network requirement file to perform vehicle simulation to obtain a traffic simulation model for the target road network area limited in this embodiment of the invention.

[0134] It is understood that the simulated road network file used in the embodiments of the present invention can better describe the road alignment and lane attributes, and can closely match the real road network environment, providing a prerequisite for improving the fidelity of traffic simulation and loading the real vehicle trajectories. Furthermore, the embodiments of the present invention use real vehicle trajectory information as the road network requirement file for the simulation model to achieve the reproduction of the real traffic environment in the simulation, thereby improving the efficiency of obtaining the road network requirement file and the fidelity of the traffic simulation model.

[0135] The simulation modeling method provided in this invention utilizes map data for a target road network area to generate a simulation road network file for that area. This allows the simulation file to recreate the actual road network situation of the target area during simulation using specified simulation software. Furthermore, after acquiring target vehicle passage data for a specified time period within the target road network area, the method determines the vehicle trajectory information corresponding to each simulation moment based on the vehicle passage data at each time point and the target correspondence. Using this vehicle trajectory information, a road network requirement file for the target road network area is constructed. This allows the actual vehicle movement information of the target road network area to be recreated using the road network requirement file during simulation using specified simulation software. Therefore, this solution can accurately recreate the real traffic scene of a road network area.

[0136] Optionally, based on the above embodiments, in another embodiment of the present invention, such as Figure 2 As shown, step S104 above may include S1041-S1045:

[0137] S1041, Based on the vehicle trajectory information corresponding to the first simulation moment, determine the simulation vehicle information for the first simulation moment;

[0138] The simulated vehicle information includes: each simulated vehicle identifier and the location information corresponding to each simulated vehicle identifier, and different simulated vehicle identifiers have different license plate numbers.

[0139] It is understood that during the simulation process, each simulated vehicle has a unique vehicle identifier, which can be called a simulated vehicle identifier. Furthermore, the simulated vehicle identifier can be used to uniformly identify the same real vehicle at different locations. This embodiment of the invention does not limit the specific content of the simulated vehicle identifier, and when using designated simulation software, simulated vehicles can be generated and displayed based on the simulated vehicle identifier.

[0140] Since the road network requirements document needs to reflect the motion information of vehicles in the simulated road network, that is, the motion information of vehicles at each simulation moment, the vehicle trajectory information at each simulation moment can be determined, and the simulated vehicle information at each simulation moment can be determined; and the same real vehicle can be associated with the same vehicle simulation identifier.

[0141] In determining the simulated vehicle information at each simulation moment, this embodiment first determines the simulated vehicle information for the first simulation moment. Then, using the simulated vehicle information for the first simulation moment as the initial simulated vehicle information, the simulated vehicle information for each subsequent simulation moment is continuously calculated. Specifically, when determining the simulated vehicle information for the first simulation moment, the number of license plate numbers for each vehicle in the vehicle trajectory information corresponding to the first simulation moment can be determined, thereby generating that number of simulated vehicle identifiers. Each simulated vehicle identifier has a license plate number, and the location information corresponding to each simulated vehicle identifier is set to the location information corresponding to the license plate number possessed by that simulated vehicle identifier. In this way, it is determined which simulated vehicle identifiers and their location information exist at the first simulation moment, i.e., which simulated vehicles exist and their location information.

[0142] S1042, take the first simulation moment as the current simulation moment;

[0143] S1043, using the simulated vehicle information at the current simulation moment and the vehicle trajectory information corresponding to the next simulation moment, calculate the simulated vehicle information at the next simulation moment;

[0144] After determining the simulation vehicle information at the first simulation moment, the first simulation moment can be used as the current simulation moment to calculate the simulation vehicle information at the next simulation moment. Thus, after determining the simulation vehicle information at the next simulation moment, the next simulation moment can be used as the new current simulation moment, and the simulation vehicle information at the next simulation moment can be iteratively calculated.

[0145] For example, in one implementation, calculating the simulation vehicle information for the next simulation moment using the simulation vehicle information at the current simulation moment and the vehicle trajectory information corresponding to the next simulation moment may include steps C1-C2:

[0146] Step C1: Compare the license plate numbers corresponding to each simulated vehicle identifier in the simulated vehicle information at the current simulation time with the license plate numbers in the vehicle trajectory information at the next simulation time.

[0147] Step C2: Based on the comparison results, update the simulation vehicle information for the current simulation moment to obtain the simulation vehicle information for the next simulation moment, as follows:

[0148] For the first type of license plate number represented by the comparison result, the location information corresponding to the simulation vehicle identifier with the first type of license plate number in the simulation vehicle information at the current simulation time is updated according to the location information corresponding to the first type of license plate number in the vehicle trajectory information at the next simulation time; wherein, the first type of license plate number is the license plate number of a simulation vehicle identifier in the simulation vehicle information at the current simulation time, and is included in the vehicle trajectory information at the next simulation time;

[0149] For the second type of license plate number represented by the comparison results, the simulation vehicle information with the second type of license plate number and the corresponding location information are added to the simulation vehicle information at the current simulation time; wherein, the corresponding location information is the location information corresponding to the second type of license plate number in the vehicle trajectory information at the next simulation time, and the second type of license plate number is only included in the vehicle trajectory information at the next simulation time.

[0150] For the third type of license plate number represented by the comparison results, the simulation vehicle identifier with the second type of license plate number and its corresponding location information are removed from the simulation vehicle information at the current simulation time; wherein, the third type of license plate number is only the license plate number of one simulation vehicle identifier in the simulation vehicle information at the current simulation time.

[0151] In the above method, the terms "Class I," "Class II," and "Class III" in the categories of Class I, Class II, and Class III license plates are merely used to distinguish different types of license plates from an order perspective and do not have any limiting meaning.

[0152] For the first type of license plate number, it is a license plate number that exists in both the vehicle trajectory information at the current simulation time and the vehicle trajectory information at the next simulation time. This indicates that the simulated vehicle with the first type of license plate number exists in both the current simulation time and the next simulation time, with the only difference being the location information. Therefore, it is possible to update only the location information corresponding to the simulated vehicle identifier with the first type of license plate number in the simulated vehicle information at the current simulation time.

[0153] For the second type of license plate number, it is a license plate number that only exists in the vehicle trajectory information corresponding to the next simulation time. This indicates that the simulation vehicle with the second type of license plate number should be a newly appearing simulation vehicle. Therefore, the simulation vehicle identifier with the second type of license plate number and the corresponding location information can be added to the simulation vehicle information at the current simulation time.

[0154] For the third type of license plate number, it is a license plate number that only exists in the vehicle trajectory information corresponding to the current simulation time. This means that the simulation vehicle with the third type of license plate number should be removed in the next simulation time. Therefore, the simulation vehicle identifier with the second type of license plate number and its corresponding location information can be removed from the simulation vehicle information at the current simulation time.

[0155] S1044, take the next simulation moment as the new current simulation moment, and return to S1043, until the simulation vehicle information of the last simulation moment is obtained;

[0156] To facilitate understanding of the process of determining the simulation vehicle information at each simulation moment, the following example illustrates the process:

[0157] Assume the vehicle trajectory information corresponding to the first simulation moment includes: license plate number 'a' and corresponding location information 'L'. a1 License plate number b and corresponding location information L b1 The vehicle trajectory information corresponding to the second simulation moment includes license plate number 'a' and the corresponding location information 'L'. a2 License plate number b and corresponding location information L b2 License plate number C and corresponding location information L c1 The vehicle trajectory information corresponding to the third simulation moment includes license plate number b and the corresponding location information L. b3 License plate number C and corresponding location information L c2 ;

[0158] Therefore, the simulated vehicle information at the first simulation moment can include: the simulated vehicle identifier A and the corresponding location information L. a1 Simulated vehicle identifier B and corresponding location information L b1 Simulated vehicle identifier A has license plate number a, and simulated vehicle identifier B has license plate number b;

[0159] Using the first simulation moment as the current simulation moment, the license plate numbers corresponding to each simulation vehicle identifier in the simulation vehicle information at the current simulation moment are compared with the license plate numbers in the vehicle trajectory information at the second simulation moment.

[0160] For license plate numbers a and b (corresponding to the first type of license plate numbers mentioned above) represented by the comparison results, in the simulated vehicle information at the first simulation time, the location information corresponding to the simulated vehicle identifier A is updated to L. a2 Update the location information corresponding to the simulated vehicle identifier B to L. b2 For the newly appearing license plate number c (corresponding to the second type of license plate number mentioned above) represented by the comparison results, the simulation vehicle identifier C and the corresponding location information L are added to the simulation vehicle information corresponding to the first simulation time.c1 The final simulated vehicle information obtained at the second simulation moment includes: simulated vehicle identifier A and its corresponding location information updated to L. a2 The simulated vehicle identifier B and its corresponding location information are updated to L. b2 Simulated vehicle identifier C and corresponding location information L c1 Furthermore, the simulated vehicle identifier A has license plate number a, the simulated vehicle identifier B has license plate number b, and the simulated vehicle identifier C has license plate number c.

[0161] The second simulation time is taken as the new current simulation time. The license plate numbers corresponding to each simulation vehicle identifier in the simulation vehicle information of the current simulation time (i.e. the second simulation time) are compared with the license plate numbers in the vehicle trajectory information corresponding to the third simulation time.

[0162] For license plate numbers b and c (corresponding to the first type of license plate numbers mentioned above) represented by the comparison results, in the simulated vehicle information at the second simulation time, the location information corresponding to the simulated vehicle identifier b is updated to L. b3 Update the location information corresponding to the simulated vehicle identifier C to L. c2 For the license plate number 'a' (corresponding to the third type of license plate number mentioned above) that has disappeared as represented by the comparison results, at this time, the simulation vehicle identifier A and the corresponding location information L are removed from the simulation vehicle information corresponding to the second simulation time. a2 The final calculated simulation vehicle information for the third simulation moment includes: simulation vehicle identifier B and its corresponding location information updated to L. b3 Simulated vehicle identifier C and corresponding location information L c2 Furthermore, the simulated vehicle identifier B has license plate number b, and the simulated vehicle identifier C has license plate number c.

[0163] S1045, construct a file containing simulation vehicle information at each simulation time to obtain the road network requirement file for the target road network area.

[0164] After obtaining the simulated vehicle information at the last simulation moment, the simulated vehicle information at each simulation moment can be used to construct a file containing the simulated vehicle information at each simulation moment, thus obtaining the road network requirement file for the target road network area. The road network requirement file can be in XML format, but is not limited to this.

[0165] In this embodiment, the simulated vehicle information at the first simulation moment is first determined, and the simulated vehicle information at the first simulation moment is used as the initial simulated vehicle information. The simulated vehicle information at each subsequent simulation moment is continuously calculated. This ensures accurate and fast simulated vehicle information at each simulation moment, thereby ensuring the rapid generation of effective road network requirement files. Ultimately, it ensures the effective restoration of real vehicle information and achieves the goal of accurately restoring the real traffic scene in the road network area.

[0166] Optionally, based on the above embodiments, in another embodiment of the present invention, such as Figure 3 As shown, step S102 above may include S1021-S1024:

[0167] Step S1021: Parse the map data to obtain point data and line data; wherein, the point data is used to describe the location points on the intersections and road segments of the target road network area, and the line data is used to describe the road segments of the target road network area, which are road segments formed based on each location point;

[0168] To obtain a simulated road network file for a target road network area, point and line data for that area can be parsed from map data using a specific method. This breaks down the area-based map data into point and line data. Subsequently, based on the parsed point and line data, the road network topology of the target area is analyzed, and a simulated road network file for the target road network is generated. The point and line data can be in GeoJSON format, but this is not a limitation.

[0169] In one implementation, the map data is parsed to obtain point data and line data, which may include:

[0170] The map data is imported into a designated geographic information system (GIS) to display the map data. After detecting the location points marked by the configuration personnel on the map data, the location information and attribute information of each location point are obtained to obtain point data. The location points are then connected to form a line segment, and the location information and attribute information of the line segment are obtained to obtain line data. The connected line segment is a road segment.

[0171] For example, the specified geographic information system can be QGIS, but it is not limited to this. The location information of each point is latitude and longitude coordinates, or WGS84 coordinates (World Geodetic System 1984, a coordinate system established for use by the GPS global positioning system), but it is not limited to these. The attribute information of each point can include: node ID (i.e., location point ID), node name (i.e., location point name), the type of the location point, etc. The location information of a line segment is the latitude and longitude information of the line segment, or WGS84 coordinates, while the attribute information of the line segment can include: the name of the road segment to which the line segment belongs, lane number, number of lanes, lane width, lane turn, lane direction, lane type, and the start and end points of widened lanes, etc. It can be understood that the type of the location point includes: road node type, edge intersection type, signalized intersection type, and non-signalized intersection type. For any given location point, if it is on a road segment but not at the end of the road, its type is road node; if it is at the end of the road, its type is edge intersection; if it is near the center of an intersection, its type is a signalized intersection if the intersection is a traffic light-controlled intersection, and a non-signalized intersection if the intersection is not. Signalized and non-signalized intersections are distinguished by whether or not traffic lights are installed. Signalized intersections can also be called signalized intersections, and non-signalized intersections can also be called non-signalized intersections.

[0172] S1022, Extract the road network topology of the target road network area from point data and line data;

[0173] The road network topology of the target road network area can be fully described by intersection data, road segment data, lane data, and connection data. There are mutual mapping relationships between the basic road network data. The start and end point information of road segment data can be obtained from the point data, and detailed information of lane data can be obtained from the road segment information (i.e., line data). The complete mutual mapping between these types of information ensures the integrity of the road network topology represented by the road network data, thus guaranteeing the high quality and usability of the final simulated road network.

[0174] For example, extracting the road network topology of a target road network area from point data and line data includes steps D1-D3:

[0175] Step D1: Based on point data, identify the shape and location information of intersections in the target road network area;

[0176] Step D2: Based on the line data, identify the road segment and lane data within the target road network area;

[0177] Step D3: Based on the identified intersection location information, as well as the identified road segment and lane data, determine the connection information used to characterize the road connectivity status.

[0178] Regarding step D1, in one implementation, it is possible to identify whether each location point in the point data belongs to the edge point of the intersection; sort the location points that belong to the edge point of the intersection, determine the shape formed when connecting the location points according to the sorted sequence, and use this shape as the shape of the intersection in the target road network area; and determine the location information of the intersection based on the location points that belong to the edge point of the intersection.

[0179] The method for identifying whether each location point in the point data belongs to the edge point of the intersection may include: obtaining the latitude and longitude coordinates of each location point in the point data; calculating the distance between every two location points based on the latitude and longitude coordinates of each location point; for each point set containing three location points, determining whether the radius of the circle formed by the three location points in the point set meets the predetermined intersection conditions based on the distance between every two location points in the point set; if it meets the conditions, then the three location points in the point set are determined to be edge points of the intersection. It can be understood that, for example, the predetermined intersection conditions are a predetermined range of radius values; and the location information of each location point can be represented by WGS84 (World Geodesic System 1984, a coordinate system established for use by the GPS global positioning system). In this case, for ease of calculation, WGS84 can be converted to latitude and longitude coordinates when identifying the edge points of the intersection.

[0180] In addition, before calculating the distance between location points, duplicate points can be removed. For example, duplicate points with the same location coordinates can be removed, or line segments with the same start and end points can be merged into one line segment.

[0181] Regarding step D2, in one implementation, the endpoints of the line segments represented in the line data can be determined. Based on the location information of each endpoint and the location information of the identified intersections, the start and end points of each road segment in the target road network area can be identified. For example, the start and end points of the road can be identified by recognizing the proximity of each endpoint to the intersection. For each road segment, the direction to which the road segment belongs can be determined. For example, when divided by four directions (east, south, west, and north), the road segment can be determined to belong to one of the four directions. From the line data, the lane data within each road segment can be determined. The lane data may include, but is not limited to, lane number, number of lanes, lane width, lane turn, lane direction, lane type, and / or the start and end points of widened lanes.

[0182] Regarding step D3, based on the identified intersection location information, as well as the identified road segment and lane data, the lane data for each road direction and the lane data for each road direction's approach lanes at the intersections in the target road network area can be determined to obtain connection information characterizing the road connectivity status. It is understood that the lane data determined here is obtained from the aforementioned road segment information (i.e., line data).

[0183] S1023, using the extracted road network topology, construct the point file, edge file, and connection file required for the simulation process;

[0184] The process of constructing the point files, edge files, and connection files required for the simulation process using the extracted road network topology may include: generating the point files required for the simulation process using the shape and location information of the identified intersections; generating the edge files required for the simulation process using the identified road segment and lane data; and generating the connection files required for the simulation process using the identified connection information used to characterize the road connectivity status.

[0185] It is understandable that a node information dictionary can be generated using the shape and location information of the intersection, combined with the intersection ID and type. Simultaneously, a road segment and lane information dictionary can be generated using the identified road segment and lane data, combined with road segment type, intersection ID, road alignment of the widened section, road segment speed limit, and road priority information. Furthermore, a connection information dictionary can be generated using connection information, combined with the intersection ID and intersection direction order. Then, according to the storage formats of *.node.xml, *.edge.xml, and *.con.xml files, the node information dictionary, road segment and lane information dictionary, and connection information are written into the corresponding fields to obtain the point file, edge file, and connection file, respectively. It is understandable that intersection types can be divided into edge intersection types, signalized intersection types, and non-signalized intersection types. The method for determining the intersection type can include: determining the type of the location point at the intersection. Furthermore, road segment types can be divided into arterial roads, secondary arterial roads, local roads, and expressways. The road segment type can be one of the attributes assigned to the line segment mentioned above.

[0186] S1024 uses point files, edge files, and connection files to generate a simulation road network file for the target road network area.

[0187] For example, in one implementation, generating a simulation road network file for a target road network region using point files, edge files, and connection files may include:

[0188] Using the target tool provided by the specified simulation software for generating road network files, the point files, edge files, and connection files are integrated into a simulated road network file for the target road network area.

[0189] If the specified simulation software is SUMO, the target tool can be the NETCONVERT command. The NETCONVERT command is a command-line application that imports digital road networks from different sources and generates road networks that can be used by other tools in the software package.

[0190] In this embodiment, map data belonging to area data is parsed into point data and line data. The road network topology of the target road network area can be extracted from this data, and the extracted topology is used to construct the point file, edge file, and connection file required for the simulation process. Using these files, a simulation road network file for the target road network area is generated. Therefore, the simulation road network file obtained in this way can represent road network information that closely matches the actual road network, allowing for accurate reconstruction of the real traffic scene in the road network area.

[0191] The following is an example illustrating the process of using QGIS software to parse the map data and obtain point and line data:

[0192] The basic approach to parsing map data using QGIS software to obtain point and line data can include:

[0193] Map data is imported into QGIS software for display. Points are manually labeled and their attributes assigned. QGIS then uses its built-in functions to extract these points, generating point data. This point data is then concatenated into line data by linking the points together to create line segments. These line segments are then manually assigned attributes. Finally, the point and line data are exported in GeoJSON format.

[0194] Specifically, the steps for parsing map data using QGIS software may include:

[0195] 1) Create a new polygon layer; 2) Convert the polygon layer to a point layer; 3) Create a new line layer; 4) Export the data.

[0196] Step 1) involves the following steps: First, setting the properties of the polygon layer, such as polygon layer ID and type (e.g., polygon layer type); then, drawing closed polygons at the center of the intersection and the endpoints of the upstream and downstream road segments based on the loaded map data, which are considered as the intersections connected by the road segments, thus drawing the road network area containing the intersections; finally, drawing various location points on the road edge through manual annotation, which can also be called interior points.

[0197] Step 2) involves converting the surface layer to a point layer. Specifically, the tool functions in QGIS software are used to detect the location information of each point and assign corresponding attribute information to obtain point data.

[0198] Step 3) involves the following steps: First, setting the attribute information of the line layer, such as: line layer ID, starting segment, ending segment, number of lanes, lane details, lane direction, etc.; then, connecting the various points in the point layer to form a line, which serves as the road segment, and using a tool to measure the width of the lane graphic in the loaded map data to fill in the attribute information about the lane. After assigning the corresponding attribute information to the road segment, the line data is obtained.

[0199] Step 4) includes exporting data. Specifically, the point data and line data are exported in GeoJson format. The exported data results describe the data structure of nodes and line segments in the road network. The key fields of the point data can include node ID, node name, node type, and latitude and longitude coordinates, where a node is a location point. The key fields of the road segment to which the line segment belongs can include road segment ID, road segment name, upstream node of the road segment, downstream node of the road segment, speed limit of the road segment, number of lanes contained in the road segment, road segment direction, road segment width, latitude and longitude coordinates of the road segment, and width information of each lane, etc.

[0200] To facilitate understanding of the simulation principles, the specific simulation principles in the simulation scheme using QGIS to acquire point and line data can be found in [reference needed]. Figure 4 The content.

[0201] like Figure 4 As shown, after acquiring high-precision map data for the target road network area, the simulation modeling device can use QGIS to parse the high-precision map data to obtain point data and line data. The file generated when exporting point data is node.geojson, and the file generated when exporting line data is edge.geojson. Geojson is a format for encoding various geographic data structures.

[0202] Furthermore, the simulation modeling device can extract the road network topology relationship from point data and line data, thereby obtaining a point file (i.e., Figure 4 *.nod.xml), side files (i.e. Figure 4 The *.edge.xml file and the link file (i.e. Figure 4 (in *.con.xml).

[0203] Then, the simulation modeling device automatically generates a simulation road network file (i.e., ...) from the point file, edge file, and connection file using the SUMO software command "NETCONVER". Figure 4 (in *.net.xml).

[0204] Finally, the simulation modeling device analyzes the acquired target vehicle data, that is, it parses the radar-visible trajectory to obtain the road network requirement file; and then, it loads the simulated road network file and the road network requirement file into the specified simulation software, thus realizing the loading of the simulated vehicle trajectory into the simulated road network, and finally obtaining the traffic simulation model.

[0205] To facilitate understanding of the solution, the following section introduces a simulation modeling method provided by an embodiment of the present invention, using specific examples.

[0206] In this specific example, based on pre-collected high-precision map data and radar-guided vehicle passage data of a certain intersection (corresponding to the target road network area mentioned above), the simulation construction method proposed in this invention is used to reproduce the real traffic scene of the intersection. The specific process is described below:

[0207] The pre-collected high-precision map data is stored in a JSON data structure. It can be understood that this high-precision map data allows for the acquisition of road feature data structures and road edge data.

[0208] The simulation modeling device loads the collected high-precision map data into the QGIS software to view the information contained in the high-precision map data. A schematic diagram of the map data in the QGIS software can be seen in Figure 5(a). By viewing the high-precision map data, it was found that it does not contain the mutual topological relationships between geometric elements, but only a data snapshot of the actual road elements.

[0209] Furthermore, the high-precision map data collected was further refined using QGIS software. Specifically, QGIS software first created a polygon layer, then drew the road segments of the intersections and the interior points of the road segments (corresponding to the aforementioned location points) based on the loaded map data. The road segments were drawn by QGIS software according to the edge information of the map data, while the interior points were manually marked. Next, QGIS software's utility functions were used to extract the location information of the interior points and assign them corresponding attribute information, thus obtaining point data. This achieved the conversion from a polygon layer to a point layer. Then, the location points in the point data were connected to obtain line segments, and corresponding attribute information was assigned to the line segments, thus obtaining line data. This achieved the conversion from a point layer to a line layer. The result of converting the polygon layer to a point layer is shown in Figure 5(b), and the result of creating the line layer is shown in Figure 5(c). It should be noted that Figure 5(b) is used to show the location of each interior point, and the identification information of each interior point is not limited. Figure 5(c) is used to show the effect after the interior points are connected into line segments.

[0210] Next, the QGIS software exports the point and line data into a GeoJson format data structure;

[0211] Then, the simulation modeling device automatically extracts the road network topology relationships from the point data and line data, and automatically creates the point files, edge files and connection files required for simulation; the simulation modeling device automatically generates the simulation road network file with the help of the SUMO software command "NETCONVER".

[0212] Finally, the pre-collected radar-based vehicle data is converted into a road network requirement file; the simulated road network file and the road network requirement file are then loaded using SUMO software to achieve simulation modeling of the intersection.

[0213] The simulation road network result generated by SUMO software by loading the simulation road network file is shown in Figure 5(d); the simulation modeling result after loading the road network requirement file is shown in Figure 5(e). In Figures 5(d) and (e), the dark gray area is merely the background of the simulation road network interface, while the black area represents the road network portion of the simulation road network.

[0214] In this solution, simulation modeling is performed by combining high-precision map data and radar-based vehicle data, which can accurately recreate the real traffic scene in the road network area.

[0215] Corresponding to the above method embodiments, such as Figure 6 As shown, this embodiment of the invention also provides a simulation modeling apparatus, which may include:

[0216] The data acquisition module 610 is used to acquire map data for a target road network area and target vehicle passage data for a specified time period; wherein, the map data can represent the information of road segments and intersections in the target road network area, and the target vehicle passage data records the real trajectory information of each vehicle.

[0217] The file generation module 620 is used to generate a simulated road network file for the target road network area based on the map data; wherein the simulated road network file is used to describe the road segments and intersections of the target road network area;

[0218] The information determination module 630 is used to determine the vehicle trajectory information corresponding to each simulation moment in the simulation process based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence relationship; wherein, the target correspondence relationship is the correspondence relationship between each time point and each simulation moment in the simulation process, and the vehicle trajectory information includes the license plate number and location information of each vehicle.

[0219] The file construction module 640 is used to construct a road network requirement file for the target road network area using the vehicle trajectory information corresponding to each simulation time; wherein, the road network requirement file is used to describe the motion information of vehicles in the simulated road network;

[0220] The traffic simulation module 650 is used to construct a traffic simulation model of the target road network area using specified simulation software based on the simulation road network file and the road network demand file.

[0221] The simulation modeling device provided in this invention generates a simulation road network file for a target road network area using map data of that area. This allows the device to recreate the actual road network situation of the target area using specified simulation software. Furthermore, after acquiring target vehicle passage data for a specified time period within the target road network area, the device determines the vehicle trajectory information corresponding to each simulation moment based on the vehicle passage data at each time point and the target correspondence. Using this vehicle trajectory information, a road network requirement file for the target road network area is constructed. Thus, when performing simulations using specified simulation software, the actual vehicle movement information of the target road network area can be recreated using the road network requirement file. Therefore, this solution can accurately recreate the real traffic scene of a road network area.

[0222] Optionally, the traffic simulation module is specifically used for:

[0223] The simulated road network file is loaded into the specified simulation software to generate a simulated road network for the target road network area;

[0224] The road network requirement file is loaded into the simulated road network generated by the simulation software to obtain the traffic simulation model of the target road network area.

[0225] Optionally, the information determination module is specifically used for:

[0226] The target vehicle passage data is broken down to obtain vehicle passage data for each time point;

[0227] For each simulation moment, the corresponding time point is determined from the target correspondence, and the vehicle passage data for the determined time point is used as the vehicle passage data for that simulation moment.

[0228] For each simulation moment, the vehicle trajectory information corresponding to that simulation moment is obtained from the vehicle passing data at that simulation moment.

[0229] Optionally, the file building module includes:

[0230] The first determination submodule is used to determine the simulation vehicle information at the first simulation time based on the vehicle trajectory information corresponding to the first simulation time. The simulation vehicle information includes: each simulation vehicle identifier and the location information corresponding to each simulation vehicle identifier, and different simulation vehicle identifiers have different license plate numbers.

[0231] The second determining submodule is used to take the first simulation moment as the current simulation moment;

[0232] The calculation submodule is used to calculate the simulation vehicle information for the next simulation time using the simulation vehicle information at the current simulation time and the vehicle trajectory information corresponding to the next simulation time.

[0233] The loop submodule is used to take the next simulation moment as the new current simulation moment and trigger the calculation submodule to calculate the simulation vehicle information of the next simulation moment using the simulation vehicle information of the current simulation moment and the vehicle trajectory information corresponding to the next simulation moment, until the simulation vehicle information of the last simulation moment is obtained.

[0234] The construction submodule is used to build a file containing simulation vehicle information at each simulation time, thereby obtaining the road network requirement file for the target road network area.

[0235] Optionally, the computing submodule is specifically used for:

[0236] Compare the license plate numbers corresponding to each simulated vehicle identifier in the simulated vehicle information at the current simulation time with the license plate numbers in the vehicle trajectory information at the next simulation time.

[0237] Based on the comparison results, the simulation vehicle information at the current simulation moment is updated to obtain the simulation vehicle information for the next simulation moment, in the following manner:

[0238] For the first type of license plate number represented by the comparison result, the location information corresponding to the simulation vehicle identifier with the first type of license plate number in the simulation vehicle information at the current simulation time is updated according to the location information corresponding to the first type of license plate number in the vehicle trajectory information at the next simulation time; wherein, the first type of license plate number is the license plate number of a simulation vehicle identifier in the simulation vehicle information at the current simulation time, and is included in the vehicle trajectory information at the next simulation time.

[0239] For the second type of license plate number represented by the comparison result, the simulation vehicle information with the second type of license plate number and the corresponding location information are added to the simulation vehicle information at the current simulation time; wherein, the corresponding location information is the location information corresponding to the second type of license plate number in the vehicle trajectory information at the next simulation time, and the second type of license plate number is only included in the vehicle trajectory information at the next simulation time.

[0240] For the third type of license plate number represented by the comparison result, from the simulation vehicle information at the current simulation time, the simulation vehicle identifier with the second type of license plate number and its corresponding location information are removed; wherein, the third type of license plate number is only the license plate number of a simulation vehicle identifier in the simulation vehicle information at the current simulation time.

[0241] Optionally, the file generation module includes:

[0242] The parsing unit is used to parse the map data to obtain point data and line data; wherein, the point data is used to describe the location points on the intersections and road segments of the target road network area, and the line data is used to describe the road segments of the target road network area, wherein the road segments are formed based on each location point;

[0243] The file construction unit is used to extract the road network topology relationship of the target road network area from the point data and line data, and to use the extracted road network topology relationship to construct the point file, edge file and connection file required for the simulation process.

[0244] The file generation unit is used to generate a simulated road network file for the target road network area using the point file, edge file, and connection file.

[0245] Optionally, the file construction unit extracts the road network topology relationship of the target road network area from the point data and line data, including:

[0246] Based on the point data, the shape and location information of the intersections in the target road network area are identified;

[0247] Based on the line data, identify road segments and lane data within the target road network area;

[0248] Based on the identified intersection location information, as well as the identified road segment and lane data, connection information is determined to characterize the road connectivity status.

[0249] Optionally, the file construction unit identifies the shape and location information of intersections in the target road network area based on the point data, including:

[0250] Identify whether each location point in the point data belongs to the edge point of the intersection;

[0251] For each position point belonging to the edge point of the intersection, sort them, determine the shape formed when connecting each position point according to the sorted sequence, and use it as the shape of the intersection in the target road network area. Based on each position point belonging to the edge point of the intersection, determine the location information of the intersection.

[0252] Optionally, the file construction unit identifies road segment and lane data within the target road network area based on the line data, including:

[0253] Determine each endpoint of the line segment represented in the line data, and identify the start and end points of each road segment in the target road network area based on the position information of each endpoint and the position information of the identified intersection.

[0254] For each of the aforementioned road segments, determine the direction to which that road segment belongs;

[0255] From the line data, determine the lane data within each road segment.

[0256] Optionally, the file construction unit determines connection information to characterize the road connectivity status based on the identified intersection location information and the identified road segment and lane data, including:

[0257] Based on the identified intersection location information, as well as the identified road segment and lane data, the lane data for each road direction and the lane data for each road direction of the intersection in the target road network area are determined to obtain connection information that characterizes the road connectivity status.

[0258] Optionally, the file construction unit utilizes the extracted road network topology relationships to construct the point files, edge files, and connection files required for the simulation process, including:

[0259] Using the identified shape and location information of the intersections, point files required for the simulation process are generated;

[0260] Using the identified road segment and lane data, generate the side files required for the simulation process;

[0261] Using the identified connectivity information that characterizes road connectivity, the connection files required for the simulation process are generated.

[0262] Optionally, the file generation unit is specifically used for:

[0263] Using the target tool provided by the specified simulation software for generating road network files, the point files, edge files, and connection files are integrated into a simulated road network file for the target road network region.

[0264] This invention also provides an electronic device, such as... Figure 7 As shown, it includes a processor 701, a communication interface 702, a memory 703, and a communication bus 704, wherein the processor 701, the communication interface 702, and the memory 703 communicate with each other through the communication bus 704.

[0265] Memory 703 is used to store computer programs;

[0266] The processor 701 is used to execute the program stored in the memory 703 to implement the steps of the simulation modeling method provided in the embodiments of the present invention.

[0267] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0268] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0269] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0270] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0271] In another embodiment of the present invention, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps of the above-described simulation modeling method.

[0272] In another embodiment of the present invention, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to perform the steps of the simulation modeling method in the above embodiments.

[0273] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center 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 can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0274] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0275] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, embodiments such as apparatus, devices, and storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0276] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A simulation modeling method, characterized in that, include: Acquire map data for a target road network area and target vehicle passage data for a specified time period; wherein, the target vehicle passage data includes: the actual trajectory information of each vehicle passing through the target road network area within the specified time period; Based on the map data, a simulated road network file is generated for the target road network area; wherein, the simulated road network file is used to describe the road segments and intersections of the target road network area; Based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence, the vehicle trajectory information corresponding to each simulation moment in the simulation process is determined; wherein, the target correspondence is the correspondence between each time point and each simulation moment in the simulation process, and the vehicle trajectory information includes the license plate number and location information of each vehicle; wherein, the step of determining the vehicle trajectory information corresponding to each simulation moment in the simulation process based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence includes: decomposing the target vehicle passage data to obtain vehicle passage data for each time point; for each simulation moment, determining the time point corresponding to the simulation moment from the target correspondence, and using the vehicle passage data for the determined time point as the vehicle passage data for that simulation moment; for each simulation moment, obtaining the vehicle trajectory information corresponding to that simulation moment from the vehicle passage data for that simulation moment; the vehicle trajectory information corresponding to each simulation moment is the real vehicle motion information related to each simulation moment; the target correspondence is constructed based on the duration of a specified time period, the simulation duration, and the simulation step size; Using the vehicle trajectory information corresponding to each simulation moment, a road network requirement file is constructed for the target road network area; wherein, the road network requirement file is used to describe the motion information of vehicles in the simulated road network; Based on the simulated road network file and the road network requirement file, a traffic simulation model of the target road network area is constructed using the specified simulation software.

2. The method according to claim 1, characterized in that, The step of constructing a traffic simulation model of the target road network area using specified simulation software based on the simulated road network file and the road network demand file includes: The simulated road network file is loaded into the specified simulation software to generate a simulated road network for the target road network area; The road network requirement file is loaded into the simulated road network generated by the simulation software to obtain the traffic simulation model of the target road network area.

3. The method according to claim 1 or 2, characterized in that, The process of constructing a road network requirement file for the target road network area using vehicle trajectory information at each simulation time point includes: Based on the vehicle trajectory information corresponding to the first simulation moment, the simulation vehicle information for the first simulation moment is determined; wherein, the simulation vehicle information includes: each simulation vehicle identifier and the location information corresponding to each simulation vehicle identifier, and different simulation vehicle identifiers have different license plate numbers; The first simulation moment is taken as the current simulation moment; Using the simulated vehicle information at the current simulation moment and the vehicle trajectory information at the next simulation moment, calculate the simulated vehicle information at the next simulation moment; The next simulation moment is taken as the new current simulation moment, and the steps of calculating the simulation vehicle information for the next simulation moment using the simulation vehicle information at the current simulation moment and the vehicle trajectory information corresponding to the next simulation moment are returned until the simulation vehicle information for the last simulation moment is obtained. A file containing simulation vehicle information at each simulation time is constructed to obtain the road network requirement file for the target road network area.

4. The method according to claim 3, characterized in that, The step of calculating the simulation vehicle information for the next simulation moment using the simulation vehicle information at the current simulation moment and the vehicle trajectory information corresponding to the next simulation moment includes: Compare the license plate numbers corresponding to each simulated vehicle identifier in the simulated vehicle information at the current simulation time with the license plate numbers in the vehicle trajectory information at the next simulation time. Based on the comparison results, the simulation vehicle information at the current simulation moment is updated to obtain the simulation vehicle information for the next simulation moment, in the following manner: For the first type of license plate number represented by the comparison result, the location information corresponding to the simulation vehicle identifier with the first type of license plate number in the simulation vehicle information at the current simulation time is updated according to the location information corresponding to the first type of license plate number in the vehicle trajectory information at the next simulation time; wherein, the first type of license plate number is the license plate number of a simulation vehicle identifier in the simulation vehicle information at the current simulation time, and is included in the vehicle trajectory information at the next simulation time; For the second type of license plate number represented by the comparison result, the simulation vehicle information with the second type of license plate number and the corresponding location information are added to the simulation vehicle information at the current simulation time; wherein, the corresponding location information is the location information corresponding to the second type of license plate number in the vehicle trajectory information at the next simulation time, and the second type of license plate number is only included in the vehicle trajectory information at the next simulation time. For the third type of license plate number represented by the comparison result, from the simulation vehicle information at the current simulation time, the simulation vehicle identifier with the second type of license plate number and its corresponding location information are removed; wherein, the third type of license plate number is only the license plate number of a simulation vehicle identifier in the simulation vehicle information at the current simulation time.

5. The method according to claim 1 or 2, characterized in that, The step of generating a simulated road network file for the target road network area based on the map data includes: The map data is parsed to obtain point data and line data; wherein, the point data is used to describe the location points on intersections and road segments in the target road network area, and the line data is used to describe the road segments in the target road network area, and the road segments are formed based on each location point; The road network topology relationship of the target road network area is extracted from the point data and line data, and the extracted road network topology relationship is used to construct the point file, edge file and connection file required for the simulation process; Using the point file, edge file, and connection file, a simulation road network file for the target road network region is generated.

6. The method according to claim 5, characterized in that, The step of extracting the road network topology relationship of the target road network area from the point data and line data includes: Based on the point data, the shape and location information of the intersections in the target road network area are identified; Based on the line data, identify road segments and lane data within the target road network area; Based on the identified intersection location information, as well as the identified road segment and lane data, connection information is determined to characterize the road connectivity status.

7. The method according to claim 6, characterized in that, The step of identifying the shape and location information of intersections in the target road network area based on the point data includes: Identify whether each location point in the point data belongs to the edge point of the intersection; For each position point belonging to the edge point of the intersection, sort them, determine the shape formed when connecting each position point according to the sorted sequence, and use it as the shape of the intersection in the target road network area. Based on each position point belonging to the edge point of the intersection, determine the location information of the intersection.

8. The method according to claim 6, characterized in that, The method of identifying road segments and lane data within the target road network area based on line data includes: Determine each endpoint of the line segment represented in the line data, and identify the start and end points of each road segment in the target road network area based on the position information of each endpoint and the position information of the identified intersection. For each of the aforementioned road segments, determine the direction to which that road segment belongs; From the line data, determine the lane data within each road segment.

9. The method according to claim 6, characterized in that, The process of determining connection information to characterize road connectivity based on the identified intersection location information, as well as the identified road segment and lane data, includes: Based on the identified intersection location information, as well as the identified road segment and lane data, the lane data for each road direction and the lane data for each road direction of the intersection in the target road network area are determined to obtain connection information that characterizes the road connectivity status.

10. The method according to claim 6, characterized in that, The process of constructing point files, edge files, and connection files required for the simulation using the extracted road network topology includes: Using the identified shape and location information of the intersections, point files required for the simulation process are generated; Using the identified road segment and lane data, generate the side files required for the simulation process; Using the identified connectivity information that characterizes road connectivity, the connection files required for the simulation process are generated.

11. The method according to claim 5, characterized in that, The step of generating a simulation road network file for the target road network region using the point file, edge file, and connection file includes: Using the target tool provided by the specified simulation software for generating road network files, the point files, edge files, and connection files are integrated into a simulated road network file for the target road network region.

12. A simulation modeling device, characterized in that, include: The data acquisition module is used to acquire map data for a target road network area and target vehicle passage data for a specified time period; wherein, the map data can represent the information of road segments and intersections in the target road network area, and the target vehicle passage data records the actual trajectory information of each vehicle; wherein, the target vehicle passage data includes: the actual trajectory information of each vehicle passing through the target road network area within the specified time period; The file generation module is used to generate a simulated road network file for the target road network area based on the map data; wherein, the simulated road network file is used to describe the road segments and intersections of the target road network area; The information determination module is used to determine the vehicle trajectory information corresponding to each simulation moment in the simulation process based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence relationship; wherein, the target correspondence relationship is the correspondence relationship between each time point and each simulation moment in the simulation process, and the vehicle trajectory information includes the license plate number and location information of each vehicle; wherein, the step of determining the vehicle trajectory information corresponding to each simulation moment in the simulation process based on the vehicle passage data for each time point in the target vehicle passage data and the target correspondence relationship includes: decomposing the target vehicle passage data to obtain vehicle passage data for each time point; for each simulation moment, determining the time point corresponding to the simulation moment from the target correspondence relationship, and using the vehicle passage data for the determined time point as the vehicle passage data under that simulation moment; for each simulation moment, obtaining the vehicle trajectory information corresponding to that simulation moment from the vehicle passage data under that simulation moment; the vehicle trajectory information corresponding to each simulation moment is the real vehicle motion information related to each simulation moment; the target correspondence relationship is constructed based on the duration of a specified time period, the simulation duration, and the simulation step size; The file construction module is used to construct a road network requirement file for the target road network area using the vehicle trajectory information corresponding to each simulation time point; wherein, the road network requirement file is used to describe the motion information of vehicles in the simulated road network; The traffic simulation module is used to construct a traffic simulation model of the target road network area using specified simulation software, based on the simulated road network file and the road network demand file.

13. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the steps of the method described in any one of claims 1-11.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method described in any one of claims 1-11.

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