Method and device for generating roadside configuration information, computer equipment, readable storage medium and program product

Abstract

The invention relates to a roadside configuration information generation method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring pre-stored map information, identifying reference position data of a target position point from the map information, and acquiring real position data of the target position point; based on a preset fitting algorithm, the reference position data of the target position point and the real position data of the target position point are subjected to fitting processing, and the deviation correction information is obtained; and performing correction processing on the position data of each position point through the correction information, and generating roadside configuration information according to the corrected position data of each position point. By adopting the method, the data acquisition efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the field of Internet technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium and computer program product for generating roadside configuration information. Background Art

[0002] With the development of network technology, cars are no longer independent entities, but terminals that are interconnected with the surrounding environment. Among them, V2X (vehicle to everything) technology, as a key technology of the Internet of Vehicles, promotes the deep integration of multiple traffic elements such as "car-people-road-cloud", builds an efficient and intelligent transportation system, and enables vehicles to exchange more information.

[0003] Based on V2X communication technology, RSU (Road Side Unit) can broadcast roadside messages to passing vehicles through the PC5 air interface. The OBU (On board Unit) in the vehicle can predict dangerous road conditions in advance based on roadside messages and remind the driver in time, thereby reducing the occurrence of traffic accidents. Among them, roadside messages contain roadside configuration information, such as sign information, lane information, intersection information, etc., which plays an important role in the calculation of OBU application scenarios.

[0004] However, currently, when configuring roadside map messages and static event sign messages, it is often necessary to dispatch personnel to the site to collect longitude and latitude and fill in configuration files, which results in a huge workload and low collection efficiency. Summary of the invention

[0005] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for generating roadside configuration information in response to the above technical problems.

[0006] In a first aspect, the present application provides a method for generating roadside configuration information, comprising:

[0007] Acquire pre-stored map information, identify reference location data of a target location point from the map information, and acquire real location data of the target location point;

[0008] Perform fitting processing based on a preset fitting algorithm, the reference position data of the target position point, and the real position data of the target position point to obtain the correction information;

[0009] The position data of each position point is corrected by using the correction information, and the roadside configuration information is generated according to the corrected position data of each position point.

[0010] In one embodiment, the identifying reference location data of the target location point from the map information includes:

[0011] Determining a road shape of a target road in the map information;

[0012] Based on the location point recognition strategy corresponding to the road shape, identifying the target location point included in the target road in the map information;

[0013] The map coordinates of the target location point are extracted from the map information as reference location data of the target location point.

[0014] In one embodiment, the identifying reference location data of the target location point from the map information includes:

[0015] For each roadside unit, based on the position of the roadside unit, determine a target area related to the roadside unit, and determine a target location point within the target area;

[0016] The reference position data of the target location point is identified from the map information.

[0017] In one embodiment, the correction processing of the position data of each position point by using the correction information includes:

[0018] Determine the associated position point of the target position point, perform correction processing on the associated position point according to the correction information to obtain reference position data, and obtain the real position data of the associated position point;

[0019] determining whether a preset accuracy condition is met based on the reference position data and the real position data of at least one of the associated position points;

[0020] If the preset accuracy condition is met, the position data of each position point is corrected using the correction information.

[0021] In one embodiment, the method further comprises:

[0022] If the preset accuracy condition is not met, the associated position point is added as the target position point, and the step of returning to execute the fitting process based on the preset fitting algorithm, the reference position data of the target position point and the actual position data of the target position point to obtain the correction information step.

[0023] In one embodiment, determining the associated position point of the target position point includes:

[0024] In the map information, determining a candidate location point that satisfies a preset location proximity condition with the target location point;

[0025] According to the type of each of the candidate location points, candidate location points of the same type as the target location point are selected from the candidate location points as associated location points.

[0026] In a second aspect, the present application also provides a device for generating roadside configuration information, including:

[0027] An acquisition module, used to acquire pre-stored map information, identify reference position data of a target location point from the map information, and acquire real position data of the target location point;

[0028] A processing module, configured to perform fitting processing based on a preset fitting algorithm, the reference position data of the target position point, and the real position data of the target position point to obtain the deviation correction information;

[0029] The generating module is used to correct the position data of each position point by using the deviation correction information, and generate the roadside configuration information according to the corrected position data of each position point.

[0030] In one embodiment, the acquisition module is specifically used to:

[0031] Determining a road shape of a target road in the map information;

[0032] Based on the location point recognition strategy corresponding to the road shape, identifying the target location point included in the target road in the map information;

[0033] The map coordinates of the target location point are extracted from the map information as reference location data of the target location point.

[0034] In one embodiment, the acquisition module is specifically used to:

[0035] For each roadside unit, based on the position of the roadside unit, determine a target area related to the roadside unit, and determine a target location point within the target area;

[0036] The reference position data of the target location point is identified from the map information.

[0037] In one embodiment, the generating module is specifically used for:

[0038] Determine the associated position point of the target position point, perform correction processing on the associated position point according to the correction information to obtain reference position data, and obtain the real position data of the associated position point;

[0039] determining whether a preset accuracy condition is met based on the reference position data and the real position data of at least one of the associated position points;

[0040] If the preset accuracy condition is met, the position data of each position point is corrected using the correction information.

[0041] In one embodiment, the device further comprises:

[0042] An adding module is used to add the associated position point as a target position point if the preset accuracy condition is not met, and return to execute the fitting processing based on the preset fitting algorithm, the reference position data of the target position point and the actual position data of the target position point to obtain the correction information step.

[0043] In one embodiment, the generating module is specifically used for:

[0044] In the map information, determining a candidate location point that satisfies a preset location proximity condition with the target location point;

[0045] According to the type of each of the candidate location points, candidate location points of the same type as the target location point are selected from the candidate location points as associated location points.

[0046] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method for generating roadside configuration information when executing the computer program.

[0047] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method for generating the above-mentioned roadside configuration information are implemented.

[0048] In a fifth aspect, the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for generating roadside configuration information.

[0049] The above-mentioned method, device, computer equipment, computer-readable storage medium and computer program product for generating roadside configuration information can obtain pre-stored map information, identify the reference position data of the target position point from the map information, and obtain the real position data of the target position point; perform fitting processing based on a preset fitting algorithm, the reference position data of the target position point and the real position data of the target position point to obtain the correction information; perform correction processing on the position data of each position point through the correction information, and generate roadside configuration information based on the corrected position data of each position point. By adopting this scheme, the position data in the map information can be corrected in combination with the reference position data and the real position data, and then the roadside configuration information is automatically generated based on the corrected position data, without the need for manual collection, thereby improving the collection efficiency, and because the position data has been effectively corrected, the generated roadside configuration information can be made consistent with the real data, thereby improving the accuracy of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 A diagram of an application environment of a method for generating roadside configuration information in an embodiment;

[0052] Figure 2 A schematic diagram of a flow chart of a method for generating roadside configuration information in an embodiment;

[0053] Figure 3 A schematic flow chart of the steps of identifying reference position data of a target position point in one embodiment;

[0054] Figure 4 is a schematic diagram of a straight road in one embodiment;

[0055] Figure 5 is a schematic diagram of a curved road in one embodiment;

[0056] Figure 6 A schematic diagram of a flow chart of an example of a method for generating roadside configuration information in another embodiment;

[0057] Figure 7 It is a structural block diagram of a device for generating roadside configuration information in one embodiment;

[0058] Figure 8 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0060] The embodiment of the present application provides a method for generating roadside configuration information. The embodiment takes the method applied to a terminal as an example for explanation. It is understandable that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. Figure 1 As shown, the schematic diagram of the application scenario provided by the embodiment of the present application includes a roadside unit and a vehicle including an on-board unit, wherein the RSU can broadcast roadside messages to passing vehicles through the PC5 air interface. The OBU in the vehicle can predict dangerous road conditions in advance based on the roadside message and promptly remind the driver to pay attention, thereby reducing the occurrence of traffic accidents. Among them, the roadside message includes roadside configuration information, such as sign information, lane information, intersection information, etc., which plays an important role in the calculation of the OBU application scenario. By adopting this solution, the position data can be corrected in combination with the reference position data and the real position data, and then the roadside configuration information is automatically generated based on the corrected position data, without the need for manual collection, thereby improving the collection efficiency, and because the position data has been effectively corrected, the generated roadside configuration information can be made consistent with the real data, thereby improving the accuracy of the data.

[0061] In this embodiment, Figure 2 As shown, the method comprises the following steps:

[0062] Step 202: obtain pre-stored map information, identify reference location data of the target location point from the map information, and obtain real location data of the target location point.

[0063] In an embodiment of the present application, the terminal can obtain pre-stored map information. Among them, the map information can be high-precision satellite map data. The terminal can identify the reference location data of the target location point from the map information. Specifically, the target location point can be a location point pre-specified based on project requirements, and the location point can be a location point in the map such as an intersection, a road section, a lane, a sign, an area affected by an event, etc. Alternatively, some landmarks with known accurate latitude and longitude coordinates are determined as target location points, such as famous buildings, known location points published by relevant surveying and mapping agencies, etc. In one example, the target location point can also select a road intersection, a special location point on the road, etc. The number of target location points can be multiple.

[0064] The terminal can find the location of the target location point in the map information, and collect the longitude and latitude coordinates of the target location point on the map information as reference location data. In addition, it is also possible to use a high-precision longitude and latitude calibration device on site according to actual conditions to collect the longitude and latitude coordinates of the target location point as real location data.

[0065] Step 204 , performing fitting processing based on a preset fitting algorithm, the reference position data of the target position point, and the real position data of the target position point to obtain correction information.

[0066] In an embodiment of the present application, the terminal can determine the position deviation between the reference position data of the target location point and the actual position data of the target location point, and then perform fitting processing based on the position deviation to obtain a deviation curve. The deviation curve can be used as correction information to correct the longitude and latitude coordinates of each location point.

[0067] Specifically, for each target location point, the terminal may calculate the position deviation between the longitude and latitude of the location point on the map and the actual longitude and latitude, and the position deviation may be divided into a longitude deviation and a latitude deviation.

[0068]

[0069]

[0070] in, is the longitude deviation, MapLog is the longitude of the target location point in the map, and ReferenceLon is the actual longitude of the target location point; is the latitude deviation, MapLat is the latitude of the target location in the map, and ReferenceLat is the actual latitude of the target location.

[0071] The terminal can obtain a correction formula (such as a linear equation) by fitting according to the position deviations of multiple target position points and based on a preset fitting algorithm, wherein the fitting algorithm can adopt a least squares method.

[0072]

[0073]

[0074] Among them, CorrectedLon is the corrected longitude, and CorrectedLat is the corrected latitude. The terminal can obtain correction parameters a, b, c and d, that is, correction information, through fitting calculation.

[0075]

[0076] Among them, Slon is the sum of the squares of the deviations between the true longitude of all target location points and the longitude of the coordinate point corrected by the deviation correction curve; Slat is the sum of the squares of the deviations between the true latitude of all target location points and the latitude of the coordinate point corrected by the deviation correction curve; RefLon is ReferenceLon, which represents the true longitude of the target location point; RefLat is ReferenceLat, which represents the true latitude of the target location point.

[0077] The specific solution process can be as follows:

[0078] Let Slon calculate the partial derivatives with respect to a and b respectively, and set the partial derivatives to 0, and we can get a system of equations:

[0079]

[0080]

[0081] In the above equation, n is the number of target position points. Let Slat calculate the partial derivatives with respect to c and d respectively, and set the partial derivatives to 0, and we can get a system of equations:

[0082]

[0083] By analyzing the two equations, the parameters a, b, c and d of the fitting curve are obtained.

[0084] Step 206: Correct the position data of each position point using the deviation correction information, and generate roadside configuration information based on the corrected position data of each position point.

[0085] In an embodiment of the present application, the terminal can use the correction information to correct the longitude and latitude coordinates of each location point to obtain the location data of the corrected location point. For example, the longitude and latitude coordinates of each location point in the map information can be input into the above-mentioned curve equation to calculate the corrected longitude and latitude coordinates of each location point. Specifically, the terminal can collect the longitude and latitude of coordinate points such as roads and affected areas that need to be calibrated from the map information, and then perform correction processing, and then store them according to classification information such as intersections, sections, and lanes, so as to generate roadside configuration information. The content that needs to be calibrated in the roadside configuration information can be configured according to actual needs, and the embodiment of the present application is not limited.

[0086] In this solution, the location data in the map information can be corrected by combining the reference location data and the actual location data, and then the roadside configuration information is automatically generated based on the corrected location data, without the need for manual collection, thereby improving the collection efficiency. Moreover, since the location data has been effectively corrected, the generated roadside configuration information can be made consistent with the actual data, thereby improving the accuracy of the data.

[0087] Optional, such as Figure 3 As shown, the reference position data of the target position point is identified from the map information, including:

[0088] Step 302: determine the road shape of the target road in the map information.

[0089] In the embodiment of the present application, the target road is a pre-specified road, and the road may also be a road that needs to be calibrated later. The terminal may determine the road shape of the target road in the map information. For example, the road shape identifier of the target road may be extracted from the map information; or the terminal may locate the location area of ​​the target road in the map information, and then perform image recognition on the image data contained in the location area to obtain the road shape of the target road. The road shape may include a straight road and a curved road.

[0090] Step 304: Based on the location point identification strategy corresponding to the road shape, identify the target location point included in the target road in the map information.

[0091] In the embodiment of the present application, different road shapes correspond to different location point identification strategies. The terminal can determine the location point identification strategy corresponding to the road shape of the target road according to the correspondence between the road shape and the location point identification strategy, and then identify the target location point included in the target road in the map information through the location point identification strategy.

[0092] Take the example of a road shape that includes straight roads and curved roads. For straight roads, position point collection can be performed starting from the starting point of the target road at a preset collection interval. Optionally, the collection interval can be determined based on the length of the target road, which is positively correlated with the length of the target road and does not exceed a preset threshold, such as 50m. Figure 4 As shown in the figure, P1, P2, and P3 are the target position points in the straight road; the distance L between P1 and P2, and the distance L between P2 and P3, are the collection intervals. For curved roads, the entire curve can be divided into multiple sub-segments for collection, and the points collected include the entry point and the exit point of the curve. For the collection of position points in the curve, the method that the vertical distance from any point between two consecutive points to these two points must not exceed the maximum threshold can be followed. Figure 5 If P1 and P3 are two consecutive points on the curve, and P2 is the point with the largest vertical distance Err from the connecting line of P1 and P3, Err shall not exceed the maximum threshold. For example, Err can be 1m.

[0093] Step 306: extracting the map coordinates of the target location point from the map information as reference location data of the target location point.

[0094] In the embodiment of the present application, after the terminal identifies the target location point, it can further extract the map coordinates (ie, longitude and latitude coordinates) of the target location point from the map information as reference location data of the target location point.

[0095] In this solution, different strategies are used to select location points for different types of roads, so that the location points can be matched with the roads more accurately, thereby accurately reflecting the location of the roads.

[0096] Optionally, identifying reference position data of the target location point from map information includes: for each roadside unit, based on the position of the roadside unit, determining a target area related to the roadside unit, and determining the target location point within the target area; identifying reference position data of the target location point from map information.

[0097] In the embodiment of the present application, for each roadside unit, the terminal can determine the target area related to the roadside unit with the position of the roadside unit as the center and the preset length as the radius, and then determine the target location point in the target area, and then identify the reference location data of the target location point from the map information. The terminal classifies and stores the collected reference location data of the target location point according to different roadside units.

[0098] In this solution, for each roadside unit, the reference position data of the target location point related to the roadside unit can be collected. Then, the real location data of the target location point is obtained, and then fitting processing is performed based on the preset fitting algorithm, the reference location data of the target location point and the real location data of the target location point to obtain the correction information corresponding to the roadside unit in the map information, correct the location data in the map information, and then automatically generate the roadside configuration information based on the corrected location data. By classifying according to different RSU nodes, the nodes include the longitude and latitude coordinates of all relevant intersections, sections, lanes, events and signage impact ranges. In this way, storage can use different deviation correction curves for correction for each RSU node as needed, thereby improving the correction accuracy of each node.

[0099] Optionally, the position data of each position point is corrected through correction information, including: determining the associated position points of the target position point, correcting the associated position points through correction information to obtain reference position data, and obtaining the actual position data of the associated position points; determining whether a preset accuracy condition is met based on the reference position data and actual position data of at least one associated position point; if the preset accuracy condition is met, correcting the position data of each position point through correction information.

[0100] In an embodiment of the present application, the terminal may determine the associated location point of the target location point in the map information. The associated location point of the target location point refers to a location point that is geographically related or close to the target location point. The terminal may obtain the reference location data of the associated location point, which is the location data obtained after the location data of the associated location point in the map information is corrected by the correction information. The terminal may also obtain the real location data of the associated location point, and then determine whether the preset accuracy condition is met based on the reference location data and the real location data of at least one associated location point. Specifically, the geometric distance between the reference location data and the real location data may be calculated to obtain the location difference. If the number of associated location points whose location difference is greater than the preset threshold value among the associated location points is less than the first preset threshold value, it is determined that the preset accuracy condition is met; otherwise, it is determined that the preset accuracy condition is not met. Alternatively, the average value of the location difference of each associated location point may be determined. If the average value is less than the second preset threshold value, it is determined that the preset accuracy condition is met; otherwise, it is determined that the preset accuracy condition is not met. Alternatively, the weight of each associated position point may be initialized, and the position differences of each associated position point may be weighted averaged to obtain a weighted average value. If the weighted average value is less than a second preset threshold, it is determined that the preset accuracy condition is met; otherwise, it is determined that the preset accuracy condition is not met. The weight of each associated position point may be negatively correlated with the distance between the associated position point and the target position.

[0101] In this solution, the correction effect can be verified by associating position points to ensure the accuracy of the correction.

[0102] Optionally, the method also includes: if the preset accuracy condition is not met, the associated position point is added as the target position point, and the fitting process based on the preset fitting algorithm, the reference position data of the target position point and the actual position data of the target position point is returned to obtain the correction information step.

[0103] In an embodiment of the present application, if the preset accuracy condition is not met, the terminal adds the associated position point as a target position point, thereby increasing the number of target position points, and then performs fitting processing based on the preset fitting algorithm, the reference position data of the target position point and the actual position data of the target position point to obtain correction information. According to the newly obtained correction information, the position point is corrected again until the correction result meets the accuracy condition and the roadside configuration information is generated.

[0104] In this solution, when the accuracy is low, the target position point is updated and the correction information is regenerated, and this cycle is repeated until the preset accuracy condition is met, thereby ensuring the accuracy of the correction.

[0105] Optionally, determining associated location points of the target location point includes: determining candidate location points that meet preset location proximity conditions with the target location point in map information; and screening, according to the type of each candidate location point, candidate location points of the same type as the target location point from each candidate location point as associated location points.

[0106] In an embodiment of the present application, the terminal can determine, in the map information, a candidate location point that satisfies a preset location proximity condition with the target location point. For example, a location point whose distance from the target location point is less than a preset distance threshold can be determined as a candidate location point. Then, according to the type of each candidate location point, the terminal selects a candidate location point of the same type as the target location point from each candidate location point as an associated location point. For example, if the type of the target location point is an intersection location point, the candidate location point must also be an intersection location point.

[0107] In this solution, when the accuracy of the corrected position data is low, the target position point is updated and the position correction is performed again, and this cycle is repeated until the corrected position data meets the preset accuracy condition, thereby ensuring the accuracy of the correction.

[0108] like Figure 6 As shown, an embodiment of the present application provides an example of a method for generating roadside configuration information, including the following steps:

[0109] Step 601, obtaining pre-stored map information.

[0110] Step 602: determine the road shape of the target road in the map information.

[0111] Step 603: Based on the location point recognition strategy corresponding to the road shape, the target location point included in the target road is identified in the map information.

[0112] Step 604: extract the map coordinates of the target location point from the map information as reference location data of the target location point, and store them in a classified manner.

[0113] Step 605: Acquire the real location data of the target location point.

[0114] Step 606 , performing fitting processing based on a preset fitting algorithm, the reference position data of the target position point, and the real position data of the target position point to obtain correction information.

[0115] Step 607, in the map information, determine the associated position points of the target position point, perform correction processing on the associated position points through the correction information, obtain reference position data, and obtain the real position data of the associated position points.

[0116] Step 608, based on the reference location data and the real location data of at least one associated location point, determining whether a preset accuracy condition is met;

[0117] If the preset accuracy condition is met, step 610 is executed; if the preset accuracy condition is not met, the associated position point is added as a target position point, and the process returns to step 606 .

[0118] Step 609, correcting the position data of each position point using the correction information.

[0119] Step 610: Generate roadside configuration information based on the corrected position data of each position point.

[0120] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0121] Based on the same inventive concept, the embodiment of the present application also provides a roadside configuration information generation device for implementing the roadside configuration information generation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the one or more roadside configuration information generation device embodiments provided below can refer to the limitations of the roadside configuration information generation method above, and will not be repeated here.

[0122] In an exemplary embodiment, Figure 7 As shown, a device for generating roadside configuration information is provided, including: an acquisition module 710, a processing module 720 and a generation module 730, wherein:

[0123] The acquisition module 710 is used to acquire pre-stored map information, identify reference location data of a target location point from the map information, and acquire real location data of the target location point;

[0124] A processing module 720 is used to perform fitting processing based on a preset fitting algorithm, the reference position data of the target position point and the real position data of the target position point to obtain the correction information;

[0125] The generating module 730 is used to correct the position data of each position point by using the correction information, and generate the roadside configuration information according to the corrected position data of each position point.

[0126] In one embodiment, the acquisition module is specifically used to:

[0127] Determining a road shape of a target road in the map information;

[0128] Based on the location point recognition strategy corresponding to the road shape, identifying the target location point included in the target road in the map information;

[0129] The map coordinates of the target location point are extracted from the map information as reference location data of the target location point.

[0130] In one embodiment, the acquisition module is specifically used to:

[0131] For each roadside unit, based on the position of the roadside unit, determine a target area related to the roadside unit, and determine a target location point within the target area;

[0132] The reference position data of the target location point is identified from the map information.

[0133] In one embodiment, the generating module is specifically used for:

[0134] Determine the associated position point of the target position point, perform correction processing on the associated position point according to the correction information to obtain reference position data, and obtain the real position data of the associated position point;

[0135] determining whether a preset accuracy condition is met based on the reference position data and the real position data of at least one of the associated position points;

[0136] If the preset accuracy condition is met, the position data of each position point is corrected using the correction information.

[0137] In one embodiment, the device further comprises:

[0138] An adding module is used to add the associated position point as a target position point if the preset accuracy condition is not met, and return to execute the fitting processing based on the preset fitting algorithm, the reference position data of the target position point and the actual position data of the target position point to obtain the correction information step.

[0139] In one embodiment, the generating module is specifically used for:

[0140] In the map information, determining a candidate location point that satisfies a preset location proximity condition with the target location point;

[0141] According to the type of each of the candidate location points, candidate location points of the same type as the target location point are selected from the candidate location points as associated location points.

[0142] Each module in the above-mentioned roadside configuration information generation device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0143] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 8 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a method for generating roadside configuration information is realized. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0144] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0145] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0146] Acquire pre-stored map information, identify reference location data of a target location point from the map information, and acquire real location data of the target location point;

[0147] Perform fitting processing based on a preset fitting algorithm, the reference position data of the target position point, and the real position data of the target position point to obtain the correction information;

[0148] The position data of each position point is corrected by using the correction information, and the roadside configuration information is generated according to the corrected position data of each position point.

[0149] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0150] Determining a road shape of a target road in the map information;

[0151] Based on the location point recognition strategy corresponding to the road shape, identifying the target location point included in the target road in the map information;

[0152] The map coordinates of the target location point are extracted from the map information as reference location data of the target location point.

[0153] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0154] For each roadside unit, based on the position of the roadside unit, determine a target area related to the roadside unit, and determine a target location point within the target area;

[0155] The reference position data of the target location point is identified from the map information.

[0156] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0157] Determine the associated position point of the target position point, perform correction processing on the associated position point according to the correction information to obtain reference position data, and obtain the real position data of the associated position point;

[0158] determining whether a preset accuracy condition is met based on the reference position data and the real position data of at least one of the associated position points;

[0159] If the preset accuracy condition is met, the position data of each position point is corrected using the correction information.

[0160] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0161] If the preset accuracy condition is not met, the associated position point is added as the target position point, and the step of returning to execute the fitting process based on the preset fitting algorithm, the reference position data of the target position point and the actual position data of the target position point to obtain the correction information step.

[0162] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0163] In the map information, determining a candidate location point that satisfies a preset location proximity condition with the target location point;

[0164] According to the type of each of the candidate location points, candidate location points of the same type as the target location point are selected from the candidate location points as associated location points.

[0165] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0166] Acquire pre-stored map information, identify reference location data of a target location point from the map information, and acquire real location data of the target location point;

[0167] Perform fitting processing based on a preset fitting algorithm, the reference position data of the target position point, and the real position data of the target position point to obtain the correction information;

[0168] The position data of each position point is corrected by using the correction information, and the roadside configuration information is generated according to the corrected position data of each position point.

[0169] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0170] Determining a road shape of a target road in the map information;

[0171] Based on the location point recognition strategy corresponding to the road shape, identifying the target location point included in the target road in the map information;

[0172] The map coordinates of the target location point are extracted from the map information as reference location data of the target location point.

[0173] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0174] For each roadside unit, based on the position of the roadside unit, determine a target area related to the roadside unit, and determine a target location point within the target area;

[0175] The reference position data of the target location point is identified from the map information.

[0176] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0177] Determine the associated position point of the target position point, perform correction processing on the associated position point according to the correction information to obtain reference position data, and obtain the real position data of the associated position point;

[0178] determining whether a preset accuracy condition is met based on the reference position data and the real position data of at least one of the associated position points;

[0179] If the preset accuracy condition is met, the position data of each position point is corrected using the correction information.

[0180] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0181] If the preset accuracy condition is not met, the associated position point is added as the target position point, and the step of returning to execute the fitting process based on the preset fitting algorithm, the reference position data of the target position point and the actual position data of the target position point to obtain the correction information step.

[0182] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0183] In the map information, determining a candidate location point that satisfies a preset location proximity condition with the target location point;

[0184] According to the type of each of the candidate location points, candidate location points of the same type as the target location point are selected from the candidate location points as associated location points.

[0185] It should be noted that the user information (including but not limited to user device identification, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0186] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0187] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0188] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for generating roadside configuration information, characterized in that: The method comprises: Acquire pre-stored map information, identify reference location data of a target location point from the map information, and acquire real location data of the target location point; Perform fitting processing based on a preset fitting algorithm, the reference position data of the target position point, and the real position data of the target position point to obtain correction information; The position data of each position point is corrected by using the correction information, and the roadside configuration information is generated according to the corrected position data of each position point.

2. The method according to claim 1, characterized in that The reference position data for identifying the target position point from the map information includes: Determining a road shape of a target road in the map information; Based on the location point recognition strategy corresponding to the road shape, identifying the target location point included in the target road in the map information; The map coordinates of the target location point are extracted from the map information as reference location data of the target location point.

3. The method according to claim 1, characterized in that The reference position data for identifying the target position point from the map information includes: For each roadside unit, based on the position of the roadside unit, determine a target area related to the roadside unit, and determine a target location point within the target area; The reference position data of the target location point is identified from the map information.

4. The method according to claim 1, characterized in that The correction processing of the position data of each position point by using the correction information includes: Determine the associated position point of the target position point, perform correction processing on the associated position point according to the correction information to obtain reference position data, and obtain the real position data of the associated position point; determining whether a preset accuracy condition is met based on the reference position data and the real position data of at least one of the associated position points; If the preset accuracy condition is met, the position data of each position point is corrected using the correction information.

5. The method according to claim 4, characterized in that The method further comprises: If the preset accuracy condition is not met, the associated position point is added as the target position point, and the step of returning to execute the fitting process based on the preset fitting algorithm, the reference position data of the target position point and the actual position data of the target position point to obtain the correction information step.

6. The method according to claim 4, characterized in that The step of determining the associated position point of the target position point includes: In the map information, determining a candidate location point that satisfies a preset location proximity condition with the target location point; According to the type of each of the candidate location points, candidate location points of the same type as the target location point are selected from the candidate location points as associated location points.

7. A device for generating roadside configuration information, characterized in that: include: An acquisition module, used to acquire pre-stored map information, identify reference position data of a target location point from the map information, and acquire real position data of the target location point; A processing module, configured to perform fitting processing based on a preset fitting algorithm, the reference position data of the target position point and the real position data of the target position point to obtain the correction information; The generating module is used to correct the position data of each position point by using the deviation correction information, and generate the roadside configuration information according to the corrected position data of each position point.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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