A lane positioning method and device, electronic equipment and readable storage medium

Abstract

The application provides a lane positioning method and device, electronic equipment and a readable storage medium, and belongs to the technical field of communication, wherein the lane positioning method comprises the following steps: acquiring vehicle information of a target vehicle, and screening road data with same administrative region information from a graph database to obtain a first data set; according to the coordinate information of the target vehicle and the longest road length in the first data set, screening lane data located in the target region from the first data set to obtain a second data set; and calculating the distance between the coordinate points of each lane in the second data set and the target vehicle, and determining the lane where the target vehicle is located according to the distance calculation result. In the application, the graph database is constructed by using road data, and data screening is performed from the graph database when the lane positioning of the target vehicle is performed, so that the number of data points participating in operation is reduced, and the positioning efficiency of the lane is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication, in particular to a lane positioning method and device, electronic equipment and readable storage medium. BACKGROUND

[0002] At present, the specific scheme of positioning the lane where the vehicle is mainly divided into two kinds: one is to collect existing map data, and then determine the lane where the vehicle is according to the vehicle position, and the other is to rely on camera, laser radar and other hardware devices, and then combine the local road information or intersection map information issued by the road equipment, and then process through image algorithm to position the lane where the vehicle is. However, in the above first scheme, when the map data is more, the lane positioning calculation amount increases, and the lane positioning efficiency is low; in the above second scheme, additional hardware devices are needed, and the real-time response processing speed is required to be high, and the application scene is limited. SUMMARY

[0003] Therefore, the present application provides a lane positioning method and device, electronic equipment and readable storage medium, which is used to solve the problem that the current lane positioning scheme has large calculation amount, low lane positioning efficiency, or needs additional hardware devices, resulting in increased cost.

[0004] To solve the above technical problems, in a first aspect, the present application provides a lane positioning method, which comprises:

[0005] obtaining vehicle information of a target vehicle, the vehicle information comprising coordinate information and administrative region information of the target vehicle;

[0006] filtering out road data with the same administrative region information as the target vehicle from a graph database to obtain a first data set, the graph database storing a road network topology, the road network topology being constructed according to road data of a plurality of roads, the road data comprising road information, administrative region information of the road, road length, intersection information of the road, lane information contained by the road, and longitude and latitude of each coordinate point on the lane;

[0007] generating a target region with the target vehicle as the center according to the coordinate information of the target vehicle and the longest road length in the first data set, and filtering out lane data located in the target region from the first data set to obtain a second data set;

[0008] calculating the distance between each coordinate point of the lane in the second data set and the target vehicle, and determining the lane where the target vehicle is located according to the distance calculation result.

[0009] Optionally,

[0010] The construction process of the road network topology comprises:

[0011] The road information, intersection information and lane information in the road data are taken as nodes in the graph database, and each node is attached to a corresponding administrative region information attribute;

[0012] According to the relationships among roads, roads and intersections, and roads and lanes, the node relationships of the nodes in the road network topology in the graph database are determined.

[0013] Optionally, the generating of a target region centered on the target vehicle according to the coordinate information of the target vehicle and the longest road length in the first data set comprises:

[0014] According to the longest road length in the first data set, the longitude difference and the latitude difference are determined;

[0015] According to the longitude of the target vehicle and the longitude difference, the longitude range of the target region is determined, and according to the latitude of the target vehicle and the latitude difference, the latitude range of the target region is determined.

[0016] Optionally, the screening of lane data located in the target region from the first data set to obtain a second data set comprises:

[0017] The middle coordinate point of each lane in the first data set is taken as a representative point of the corresponding lane;

[0018] The data of the lane whose representative point falls within the target region is taken as the second data set.

[0019] Optionally, the distance calculation of each coordinate point of each lane in the second data set from the target vehicle and the determination of the lane in which the target vehicle is located according to the distance calculation result comprise:

[0020] The distance of each coordinate point of each lane in the second data set from the target vehicle is calculated, and the target coordinate point closest to the target vehicle and the target lane in which the target coordinate point is located are determined;

[0021] If the distance between the target coordinate point and the target vehicle is less than the lane width of the target lane, the target lane is determined as the lane in which the target vehicle is located.

[0022] In a second aspect, the present application further provides a lane positioning device, which comprises:

[0023] A first acquisition module is configured to acquire vehicle information of a target vehicle, wherein the vehicle information comprises coordinate information and administrative region information in which the target vehicle is located;

[0024] The first screening module is configured to screen road data with the same administrative region information as the target vehicle from a graph database to obtain a first data set, wherein the graph database stores a road network topology, and the road network topology is constructed according to road data of a plurality of roads, and the road data includes road information, administrative region information of the road, road length, intersection information of the road, lane information included in the road, and longitude and latitude of each coordinate point on the lane.

[0025] The second screening module is configured to generate a target region with the target vehicle as the center according to the coordinate information of the target vehicle and the longest road length in the first data set, and screen lane data located in the target region from the first data set to obtain a second data set.

[0026] The determining module is configured to calculate the distance between each coordinate point of a lane in the second data set and the target vehicle, and determine the lane where the target vehicle is located according to the distance calculation result.

[0027] Optionally, the first screening module includes:

[0028] The node construction unit is configured to take the road information, intersection information and lane information in the road data as nodes in the graph database, and each node is attached to a corresponding administrative region information attribute.

[0029] The node relationship construction unit is configured to construct node relationships of each node of the road network topology in the graph database according to relationships between roads, between roads and intersections, and between roads and lanes.

[0030] Optionally, the second screening module includes:

[0031] The first determining unit is configured to determine the longitude difference and the latitude difference according to the longest road length in the first data set.

[0032] The second determining unit is configured to determine the longitude range of the target region according to the longitude of the target vehicle and the longitude difference, and determine the latitude range of the target region according to the latitude of the target vehicle and the latitude difference.

[0033] Optionally, the second screening module includes:

[0034] The lane unit is configured to take the middle coordinate point of each lane in the first data set as a representative point of the corresponding lane.

[0035] The screening unit is configured to take data of the lane whose representative point falls within the target region as the second data set.

[0036] Optionally, the determining module comprises:

[0037] a calculating unit configured to calculate the distance between each coordinate point of the target lane in the second data set and the target vehicle, determine the target coordinate point closest to the target vehicle and the target lane where the target coordinate point is located;

[0038] a lane determining unit configured to determine the target lane as the lane where the target vehicle is located if the distance between the target coordinate point and the target vehicle is less than the lane width of the target lane.

[0039] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; the processor implements any of the above lane positioning methods when executing the computer program.

[0040] In a fourth aspect, the present application provides a computer readable storage medium having a computer program stored thereon, the computer program being executable on a processor to implement the steps of any of the above lane positioning methods.

[0041] The above technical solutions of the present application have the following advantages:

[0042] In the embodiments of the present application, the graph database is constructed by using road data, and data filtering is performed from the graph database when positioning the lane of the target vehicle, thereby reducing the number of data points involved in the operation and improving the positioning efficiency of the lane. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 FIG. 1 is a flowchart of a lane positioning method according to an embodiment of the present application;

[0044] Figure 2 FIG. 3 is a schematic diagram of a road network topology according to an embodiment of the present application;

[0045] Figure 3 FIG. 6 is a structural schematic diagram of a lane positioning device according to an embodiment of the present application;

[0046] Figure 4 FIG. 8 is a structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0047] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions of the embodiments of the present application will be described clearly and completely below with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the described embodiments of the present application, all other embodiments obtained by a person of ordinary skill in the art belong to the scope of protection of the present application.

[0048] Please refer to Figure 1 , Figure 1 A flowchart of a lane positioning method provided by Embodiment One of the present application is shown in the figure. The method is applied to an electronic device and includes the following steps:

[0049] Step 11: Obtain vehicle information of a target vehicle, wherein the vehicle information includes coordinate information and administrative region information of the target vehicle;

[0050] Step 12: Filter road data with the same administrative region information as the target vehicle from a graph database to obtain a first data set, wherein the graph database stores a road network topology, the road network topology is constructed according to road data of multiple roads, and the road data includes road information, administrative region information of the road, road length, intersection information of the road, lane information contained by the road, and longitude and latitude of each coordinate point on the lane.

[0051] In this embodiment, the graph database stores the road network topology, and the graph database can be pre-built and accessed directly by the electronic device or stored locally. The road network topology is constructed according to road data of multiple roads, and the road data can include road information, administrative region information of the road, road length, intersection information of the road, lane information contained by the road, longitude and latitude of each coordinate point on the lane, etc.

[0052] In this step, when obtaining the vehicle information of the target vehicle, the vehicle information can include coordinate information of the target vehicle and administrative region information of the target vehicle.

[0053] Since the road data includes administrative region information of the road, the road data with the same administrative region information as the target vehicle can be filtered from the graph database by comparing the administrative region information, i.e., as the first data set, that is, the administrative region information of the data in the first data set is the same as the administrative region information of the target vehicle, thereby realizing one-time filtering of massive road data in the graph database, so as to reduce the operation amount of subsequent processing and improve the lane positioning efficiency.

[0054] Step 13: generating a target area centered on the target vehicle according to the coordinate information of the target vehicle and the longest road length in the first data set, and screening out lane data in the target area from the first data set to obtain a second data set.

[0055] After the above-mentioned first screening, a target area centered on the target vehicle is determined according to the coordinate information of the target vehicle and the longest road length in the screened first data set. That is, the longest road length in all roads in the first data set is found, and then the target area is determined according to the longest road length with the position of the target vehicle as the center. Then, the lane data in the first data set falling within the target area is screened out to obtain a second data set.

[0056] In this step, by drawing the target area and then screening the data in the first data set twice, the amount of calculation in subsequent processing can be further reduced, and the lane positioning efficiency is improved.

[0057] Step 14: calculating the distance between each coordinate point of the lane in the second data set and the target vehicle, and determining the lane where the target vehicle is located according to the distance calculation result.

[0058] In this embodiment, after the above-mentioned two screenings, the distance between each coordinate point of the lane in the obtained second data set and the target vehicle is calculated, and the lane closest to the target vehicle is found, and finally the lane where the target vehicle is located is determined.

[0059] The lane positioning method provided by the embodiment of the application reduces the number of data points participating in calculation by using road data to construct a graph database and screening data from the graph database when positioning the lane of the target vehicle, thereby improving the positioning efficiency of the lane.

[0060] The lane positioning method is described below.

[0061] In some embodiments of the application, the process of constructing the graph database includes the following steps:

[0062] Obtaining road data of a plurality of roads, the road data including road information, administrative region information where the road is located, road length, intersection information of the road, lane information included in the road, and longitude and latitude of each coordinate point on the lane;

[0063] According to the road data, a road network topology is constructed and stored in the graph database.

[0064] Exemplarily, road data of multiple roads located in the same regional range can be acquired, the road data can be high-definition map data, the road information can include road name, other roads connected by the road, etc., and the administrative region information where the road is located can be specifically divided into administrative province, city, district, street, etc. Then, the road data set is generated according to the road data, one road data set corresponds to the road data of one regional range, and exemplarily, each road, intersection and lane can be divided and processed, and the road data is summarized to form a road data set, an intersection data set and a lane data set respectively, and different sets save different types of data.

[0065] In the embodiment, the road data can be processed to form a road network topology and stored in a graph database to form a road network topology graph.

[0066] In one of the optional specific embodiments, the construction process of the road network topology includes:

[0067] The road information, intersection information and lane information in the road data are taken as nodes in the graph database, and each node is attached with corresponding administrative region information attribute.

[0068] According to the relationship between roads, intersections and lanes, the node relationship of each node of the road network topology in the graph database is determined.

[0069] In the embodiment, exemplarily, each road, intersection and vehicle information in the road data can be taken as a node in the Neo4j graph database, and corresponding administrative region information is added to each graph database node, for example, by adding an attribute, and the relationship between roads, intersections and lanes in the road data is taken as the node relationship between nodes in the Neo4j graph database, and finally a road network topology graph is obtained.

[0070] Please refer to Table 1 below, Table 1 is the node information corresponding to different nodes provided by the embodiment of the present application. As shown in Table 1, the nodes in the road network topology graph can include the following basic information: node representation, node type, node administrative attribute, predecessor node, successor node, free attribute, spatial coordinate, etc. Among them, the node type includes road, intersection and lane, the node administrative attribute is the administrative region information of the road / intersection / lane corresponding to the node, the predecessor node and the successor node are the nodes connected before and after the current node, the free attribute can include road length, lane width, etc., and the spatial coordinate can be represented by longitude and latitude coordinates.

[0071] Table 1: Node information corresponding to different nodes.

[0072]

[0073] Reference is made to Figure 2 , Figure 2 A schematic diagram of a road network topology is provided for Embodiment One of the present application. As shown in Figure 2 , the road network topology takes roads, intersections and vehicles as nodes, and the relationships between roads, between roads and intersections, and between roads and lanes as node relationships between nodes. By way of example, Figure 2 , the node with the node identifier 3841 has a predecessor node with the node identifier 3499 and a successor node with the node identifier 3481, and all three nodes are of the road type, with the corresponding roads being connected in sequence. The node with the node identifier 3804 is of the intersection type, has a predecessor node with the node identifier 3811 of the road type, and has successor nodes with the node identifiers 3869, 3852 and 3872, all of which are of the road type. Thus, the road corresponding to the node with the node identifier 3811 is connected to the intersection corresponding to the node with the node identifier 3804, and the intersection corresponding to the node with the node identifier 3804 is connected to the roads corresponding to the nodes with the node identifiers 3869, 3852 and 3872, respectively,

[0074] In some embodiments of the present application, the target region centered on the target vehicle is generated according to the coordinate information of the target vehicle and the length of the longest road in the first data set.

[0075] The longitude difference and the latitude difference are determined according to the length of the longest road in the first data set.

[0076] The longitude range of the target region is determined according to the longitude of the target vehicle and the longitude difference, and the latitude range of the target region is determined according to the latitude of the target vehicle and the latitude difference.

[0077] In this embodiment, the length of the longest road in the first data set is converted into the corresponding earth radian, and then into the longitude difference and the latitude difference. Thus, the longitude range of the target region can be the longitude of the target vehicle minus the longitude difference to the longitude of the target vehicle plus the longitude difference, and the latitude range of the target region can be the latitude of the target vehicle minus the latitude difference to the latitude of the target vehicle plus the latitude difference. That is, the target region is a rectangular region. Thus, in the case where the longitude and latitude of the target vehicle do not change, the target region will be calculated only once, and therefore the calculation will not be time-consuming.

[0078] For example, the longest road length in the first data set is L, the average radius of the earth is R, i.e. 6367000.0 meters, then the longitude difference LA = Math.toDegrees(L / R), the latitude difference LO = Math.toDegrees(L / (R*Math.cos(Math.toRadians(latitude))), wherein toDegrees and toRadians are the methods for converting radian angle in Java.

[0079] In another embodiment of the present application, the filtering of the lane data in the first data set to obtain the second data set includes:

[0080] The middle coordinate point of each lane in the first data set is taken as the representative point of the corresponding lane.

[0081] The data of the lane in which the representative point falls is taken as the second data set.

[0082] In order to simplify the operation process and improve the operation efficiency, the middle coordinate point of each lane in the first data set is taken as the representative point of the lane, and then the secondary filtering of the lane is performed by judging whether the representative point falls in the target area. Finally, the lane in the first data set that falls in the target area is filtered to obtain the second data set.

[0083] The distance between the coordinate point of each lane in the second data set and the target vehicle is calculated, and the lane in which the target vehicle is located is determined according to the distance calculation result.

[0084] The distance between the coordinate point of each lane in the second data set and the target vehicle is calculated, and the target coordinate point closest to the target vehicle and the target lane in which the target coordinate point is located are determined.

[0085] If the distance between the target coordinate point and the target vehicle is less than the lane width of the target lane, the target lane is determined as the lane in which the target vehicle is located.

[0086] In the embodiment, the distance between each coordinate point of each lane in the second data set and the target vehicle is calculated, so that the target coordinate point closest to the target vehicle is found, and then the target lane closest to the target vehicle is found, that is, the lane where the target coordinate point is located is the target lane, and finally it is judged whether the distance between the target coordinate point and the target vehicle is less than the lane width of the target lane, so that the lane where the target vehicle is located is determined. Specifically, if the distance between the target coordinate point and the target vehicle is less than the lane width of the target lane, the target lane is the lane where the target vehicle is located, and if the distance between the target coordinate point and the target vehicle is greater than the lane width of the target lane, lane positioning failure information is output.

[0087] In the embodiment, since the aforementioned first screening and second screening are performed, the number of lanes in the second data set that needs to be calculated with the target vehicle is greatly reduced, thereby reducing the operation amount and improving the operation efficiency, and finally improving the lane positioning efficiency.

[0088] In the embodiment, the graph database is constructed by using the road data, and data screening is performed from the graph database when the lane positioning of the target vehicle is performed, so that the number of data points participating in the operation is reduced, and the lane positioning efficiency is improved.

[0089] Please refer to Figure 3 , Figure 3 is a structure schematic diagram of a lane positioning device provided by the embodiment two of the application, the device 30 comprises:

[0090] The first acquisition module 31 is used for acquiring vehicle information of a target vehicle, and the vehicle information comprises coordinate information and administrative region information where the target vehicle is located;

[0091] The first screening module 32 is used for screening road data with the same administrative region information as the target vehicle from a graph database to obtain a first data set, and the graph database stores a road network topology, the road network topology is constructed according to road data of a plurality of roads, and the road data comprises road information, administrative region information where the road is located, road length, intersection information of the road, lane information contained by the road, and longitude and latitude of each coordinate point on the lane;

[0092] The second screening module 33 is used for generating a target region with the target vehicle as the center according to the coordinate information of the target vehicle and the longest road length in the first data set, and screening lane data located in the target region from the first data set to obtain a second data set;

[0093] A determination module 34 is configured to calculate the distance between each coordinate point of a lane in the second data set and the target vehicle, and determine the lane in which the target vehicle is located according to the distance calculation result.

[0094] Optionally, the first screening module comprises:

[0095] A node construction unit is configured to take the road information, intersection information and lane information in the road data as nodes in the graph database, and each node is attached to a corresponding administrative region information attribute.

[0096] A node relationship construction unit is configured to construct the node relationship of each node in the graph database according to the relationship between roads, between roads and intersections, and between roads and lanes.

[0097] Optionally, the second screening module comprises:

[0098] A first determination unit is configured to determine the longitude difference and the latitude difference according to the longest road length in the first data set.

[0099] A second determination unit is configured to determine the longitude range of the target region according to the longitude of the target vehicle and the longitude difference, and determine the latitude range of the target region according to the latitude of the target vehicle and the latitude difference.

[0100] Optionally, the second screening module comprises:

[0101] A lane unit is configured to take the middle coordinate point of each lane in the first data set as a representative point of the corresponding lane.

[0102] A screening unit is configured to take the data of the lane in which the representative point falls as the second data set.

[0103] Optionally, the determination module comprises:

[0104] A calculation unit is configured to calculate the distance between each coordinate point of a lane in the second data set and the target vehicle, determine the target coordinate point closest to the target vehicle and the target lane in which the target coordinate point is located.

[0105] A lane determination unit is configured to determine the target lane as the lane in which the target vehicle is located if the distance between the target coordinate point and the target vehicle is less than the lane width of the target lane.

[0106] In the embodiment of the application, the graph database is constructed by using the road data, and data screening is performed from the graph database when the lane positioning of the target vehicle is performed, so that the number of data points participating in the operation is reduced, and the lane positioning efficiency is improved.

[0107] The embodiment of the present application is a product corresponding to the above-mentioned method embodiment I, and thus will not be described here again. Please refer to the above-mentioned embodiment I for details.

[0108] Please refer to Figure 4 , Figure 4 is a structural schematic diagram of an electronic device provided in the embodiment III of the present application. The electronic device 40 comprises a processor 41, a memory 42, and a computer program stored in the memory 42 and capable of running on the processor 41. When the processor 41 executes the computer program, the following steps are realized:

[0109] obtaining vehicle information of a target vehicle, wherein the vehicle information comprises coordinate information and administrative region information of the target vehicle;

[0110] filtering road data with the same administrative region information as the target vehicle from a graph database to obtain a first data set, wherein the graph database stores a road network topology, the road network topology is constructed according to road data of a plurality of roads, and the road data comprises road information, administrative region information of the road, road length, intersection information of the road, lane information contained by the road, and longitude and latitude of each coordinate point on the lane;

[0111] generating a target region with the target vehicle as the center according to the coordinate information of the target vehicle and the longest road length in the first data set, and filtering lane data located in the target region from the first data set to obtain a second data set;

[0112] calculating the distance between each coordinate point of a lane in the second data set and the target vehicle, and determining the lane where the target vehicle is located according to the distance calculation result.

[0113] In the embodiment of the present application, optionally, when the processor 41 executes the computer program, the following steps can also be realized:

[0114] the road network topology is constructed according to the road data and stored in the graph database, comprising:

[0115] the road information, the intersection information, and the lane information in the road data are taken as nodes in the graph database, and each node is attached with corresponding administrative region information attribute;

[0116] the node relationship of each node of the road network topology in the graph database is determined according to the relationship between roads, between a road and an intersection, and between a road and a lane.

[0117] Optionally, the generating a target area centered on the target vehicle according to the coordinate information of the target vehicle and the longest road length in the first data set comprises:

[0118] determining a longitude difference and a latitude difference according to the longest road length in the first data set;

[0119] determining a longitude range of the target area according to the longitude of the target vehicle and the longitude difference, and determining a latitude range of the target area according to the latitude of the target vehicle and the latitude difference.

[0120] Optionally, the filtering lane data in the first data set to obtain a second data set comprises:

[0121] taking a middle coordinate point of each lane in the first data set as a representative point of the corresponding lane;

[0122] taking data of a lane on which the representative point falls as the second data set.

[0123] Optionally, the calculating a distance between each coordinate point of a lane in the second data set and the target vehicle, and determining a lane in which the target vehicle is located according to a distance calculation result comprises:

[0124] calculating a distance between each coordinate point of a lane in the second data set and the target vehicle, and determining a target coordinate point closest to the target vehicle and a target lane on which the target coordinate point is located;

[0125] if the distance between the target coordinate point and the target vehicle is less than a lane width of the target lane, determining the target lane as the lane in which the target vehicle is located.

[0126] In the embodiment of the application, the graph database is constructed by using the road data, and data is filtered from the graph database when the lane positioning of the target vehicle is performed, so that the number of data points participating in the operation is reduced, and the lane positioning efficiency is improved.

[0127] The specific working process of the embodiment of the application is consistent with that of the above-described method embodiment one, and thus will not be described here again. For details, please refer to the description of the method steps in the above-described embodiment one.

[0128] The embodiment four of the application provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the steps in any lane positioning method in the above-described embodiment one. For details, please refer to the description of the method steps in the above-described corresponding embodiment.

[0129] The computer readable storage medium described above includes permanent and non-permanent, removable and non-removable media, which can realize information storage by any method or technology. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0130] The above is the preferred embodiment of the present application, it should be pointed out that for those skilled in the art, without departing from the principles of the present application, can also make a number of improvements and refinements, these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. A lane positioning method, characterized in that, include: Obtain vehicle information of the target vehicle, including coordinate information and administrative region information of the target vehicle; The first dataset is obtained by filtering out road data with the same administrative region information as the target vehicle from the graph database. The graph database stores road network topology, which is constructed based on road data of multiple roads. The road data includes road information, administrative region information of the road, road length, intersection information, lane information of the road, and longitude and latitude of each coordinate point on the lane. Based on the coordinates of the target vehicle and the longest road length in the first dataset, a target area centered on the target vehicle is generated, and lane data within the target area are filtered out from the first dataset to obtain a second dataset. The distance between the coordinates of each lane in the second dataset and the target vehicle is calculated, and the lane where the target vehicle is located is determined based on the distance calculation results. The step of generating a target region centered on the target vehicle based on the coordinate information of the target vehicle and the longest road length in the first dataset includes: Based on the longest road length in the first dataset, the longitude difference and latitude difference are determined; The longitude range of the target area is determined based on the longitude of the target vehicle and the longitude difference, and the latitude range of the target area is determined based on the latitude of the target vehicle and the latitude difference; wherein, the target area is a rectangular area.

2. The method according to claim 1, characterized in that, The process of constructing the road network topology includes: The road information, intersection information, and lane information in the road data are used as nodes in the graph database, and each node is associated with a corresponding administrative region information attribute. Based on the relationships between roads, roads and intersections, and roads and lanes, the node relationships of each node in the road network topology of the graph database are determined.

3. The method according to claim 1, characterized in that, The step of filtering lane data located within the target area from the first dataset to obtain the second dataset includes: The middle coordinate point of each lane in the first dataset is used as the representative point of the corresponding lane. The data of lanes where the representative point falls within the target area are used as the second dataset.

4. The method according to claim 1, characterized in that, The step of calculating the distance between the coordinates of each lane in the second dataset and the target vehicle, and determining the lane where the target vehicle is located based on the distance calculation results, includes: Calculate the distance between the coordinates of each lane in the second dataset and the target vehicle, and determine the target coordinates closest to the target vehicle and the target lane where the target coordinates are located; If the distance between the target coordinate point and the target vehicle is less than the width of the target lane, then the target lane is determined as the lane where the target vehicle is located.

5. A lane positioning device, characterized in that, include: The first acquisition module is used to acquire vehicle information of the target vehicle, including coordinate information and administrative region information of the target vehicle. The first filtering module is used to filter out road data with the same administrative region information as the target vehicle from the graph database to obtain the first dataset. The graph database stores road network topology, which is constructed based on road data of multiple roads. The road data includes road information, administrative region information of the road, road length, intersection information, lane information of the road, and longitude and latitude of each coordinate point on the lane. The second filtering module is used to generate a target area centered on the target vehicle based on the coordinate information of the target vehicle and the longest road length in the first dataset, and to filter out lane data located in the target area from the first dataset to obtain a second dataset. The determination module is used to calculate the distance between the coordinates of each lane in the second dataset and the target vehicle, and determine the lane where the target vehicle is located based on the distance calculation results; The second filtering module includes: The first determining unit is used to determine the longitude difference and latitude difference based on the longest road length in the first dataset; The second determining unit is used to determine the longitude range of the target area based on the longitude of the target vehicle and the longitude difference, and to determine the latitude range of the target area based on the latitude of the target vehicle and the latitude difference; wherein the target area is a rectangular area.

6. The apparatus according to claim 5, characterized in that, The first filtering module includes: The node construction unit is used to use the road information, intersection information, and lane information in the road data as nodes in the graph database, and each node is attached with a corresponding administrative region information attribute; The node relationship construction unit is used to determine the node relationships of each node in the road network topology of the graph database based on the relationships between roads, roads and intersections, and roads and lanes.

7. The apparatus according to claim 5, characterized in that, The second filtering module includes: Lane unit, used to take the middle coordinate point of each lane in the first dataset as the representative point of the corresponding lane; A filtering unit is used to select the data of lanes where the representative point falls within the target area as the second dataset.

8. The apparatus according to claim 5, characterized in that, The determining module includes: The calculation unit is used to calculate the distance between the coordinate point of each lane in the second dataset and the target vehicle, and to determine the target coordinate point closest to the target vehicle and the target lane where the target coordinate point is located; The lane determination unit is used to determine the target lane as the lane where the target vehicle is located if the distance between the target coordinate point and the target vehicle is less than the lane width of the target lane.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; characterized in that, When the processor executes the computer program, it implements the lane positioning method as described in any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps in the lane positioning method as described in any one of claims 1 to 4.

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