Vehicle positioning method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a vehicle positioning method and device, electronic equipment and a storage medium, and the method is applied to a simulation system, and comprises the steps: collecting the current coordinates and vehicle pose data of a simulation vehicle on a target map in a process of controlling the simulation vehicle to operate in an intelligent driving simulation scene; converting the current coordinate based on the projection mode of the target map to obtain a target coordinate, the target coordinate being a coordinate corresponding to the coordinate type required by the domain controller; the target coordinates and the vehicle pose data are coupled to obtain coupling data, the coupling data are sent to a domain controller, and the coupling data are applied to vehicle positioning of the auxiliary domain controller. According to the invention, the technical problem that the precision is low when a simulation test is used for vehicle positioning in the prior art is solved.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of positioning simulation, and in particular, to a vehicle positioning method, device, electronic device, and storage medium. Background Art

[0002] With the development of intelligent driving vehicles, the importance of intelligent driving simulation has gradually emerged. However, in intelligent driving simulation tests, the positioning accuracy of vehicles will greatly affect the reliability of test results.

[0003] Due to the significant differences between the simulation system and the real environment, the differences between the simulated vehicle and the actual vehicle in aspects such as environmental perception, positioning, and control will result in low vehicle positioning accuracy in the intelligent driving simulation test system. Summary of the Invention

[0004] The embodiments of the present application provide a vehicle positioning method, device, electronic device, and storage medium, aiming to improve the problem of low accuracy in vehicle positioning using simulation tests in related technologies.

[0005] According to one aspect of the embodiments of the present invention, a vehicle positioning method is provided, which is applied to a simulation system and includes: during the process of controlling a simulated vehicle to run in an intelligent driving simulation scenario, collecting the current coordinates of the simulated vehicle on a target map and vehicle pose data; converting the current coordinates based on the projection method of the target map to obtain target coordinates, where the target coordinates are the coordinates corresponding to the coordinate type required by the domain controller; coupling the target coordinates and the vehicle pose data to obtain coupling data, and sending the coupling data to the domain controller, where the coupling data is used to assist the vehicle positioning of the domain controller.

[0006] After converting the simulation coordinates through the projection method of the target map and coupling them with the vehicle pose data to obtain coupling data that conforms to the processing format of the domain controller, it can not only flexibly adapt to maps with different projection methods, but also ensure the accuracy and compatibility of data transmission between the simulated vehicle and the domain controller of the real vehicle by coupling the data and then transmitting it to the domain controller, so that the domain controller can use the simulation data for accurate vehicle positioning.

[0007] Optionally, coupling the target coordinates and the vehicle pose data to obtain coupling data includes: obtaining the communication configuration parameters between the simulation system and the domain controller; converting the communication configuration parameters into a configuration file adapted to the simulation system; performing format conversion on the target coordinates and the vehicle pose data based on the configuration file to obtain preset coordinates and preset vehicle pose data, where the preset coordinates are the coordinates that conform to the corresponding data reception format of the domain controller, and the preset vehicle pose data is the vehicle pose data that conforms to the corresponding data reception format; integrating the preset coordinates and the preset vehicle pose data to obtain coupling data.

[0008] Determine the configuration file through communication configuration parameters, and then implement the format conversion and input of the target coordinates to the domain controller, ensuring the data communication compatibility between the simulation system and the actual vehicle domain controller, and improving the reliability of data transmission and the practicability of the simulation system.

[0009] Optionally, perform format conversion on the target coordinates and vehicle pose data based on the configuration file to obtain preset coordinates and preset vehicle pose data, including: importing the configuration file into the simulation system, and generating a communication interface between the simulation system and the domain controller based on the configuration file; mapping the target coordinates and vehicle pose data respectively based on the communication interface to obtain preset coordinates and preset vehicle pose data.

[0010] Through communication interface mapping, ensure the consistency of data conversion, thereby ensuring the correctness and efficiency of the transmission of preset coordinates, further enhancing the reliability and usability of positioning simulation, and also improving the automation level of data processing and reducing the error of human intervention.

[0011] Optionally, convert the current coordinates based on the projection method of the target map to obtain the target coordinates, including: in response to the projection method being the global positioning projection method, convert the current coordinates based on the first coordinate system and the second coordinate system to obtain the target coordinates, where the global positioning projection method is used to represent mapping the longitude and latitude coordinates on the earth's surface to the plane coordinate system; in response to the projection method being the local positioning projection method, convert the current coordinates based on the second coordinate system to obtain the target coordinates, where the local positioning projection method is used to represent projecting the earth's surface according to longitude zones to the plane coordinate system; where the second coordinate system is the coordinate system corresponding to the map used by the domain controller, and there is an encrypted offset between the first coordinate system and the second coordinate system, where the encrypted offset is used to represent applying a random offset to the coordinates.

[0012] By adopting different conversion methods for different projection methods, the coordinate conversion problem under different map projection methods can be effectively processed, ensuring that the accuracy of vehicle positioning information is not affected when using different map data sources, and is applicable to the testing and verification of intelligent driving systems in different geographical regions.

[0013] Optionally, convert the current coordinates based on the first coordinate system and the second coordinate system to obtain the target coordinates, including: converting the current coordinates into the first coordinate system to obtain the first coordinate in the first coordinate system; converting the first coordinate into the second coordinate system based on the encrypted offset to obtain the target coordinates.

[0014] By eliminating the encrypted offset step, the accuracy of vehicle positioning can be improved, avoiding errors caused by map data encryption, and ensuring that the positioning information received by the domain controller is consistent with the actual position.

[0015] Optionally, convert the current coordinates to the first coordinate system to obtain the first coordinates in the first coordinate system, including: determining the first longitude value and the first latitude value of the current coordinates in the first coordinate system based on the semi-major axis of the earth and the angular unit conversion parameter; obtaining the first coordinates based on the first longitude value and the first latitude value.

[0016] This precise coordinate conversion through parameters can ensure the accuracy of the first coordinates.

[0017] Optionally, convert the current coordinates based on the second coordinate system to obtain the target coordinates, including: determining the zone where the current coordinates are located and the zone identifier corresponding to the zone, where the zone refers to the geographical zone area formed by projecting the earth's surface onto a plane coordinate system according to longitude zones; determining the offset value of the zone based on the zone identifier; converting the current coordinates to the second coordinate system based on the offset value to obtain the target coordinates.

[0018] By determining the specific zone where the current coordinates are located and then applying the offset value of the zone for conversion, the accuracy of the coordinate conversion can be ensured, avoiding the possible errors during cross-zone conversion, and enhancing the realism of the simulation scenario and the accuracy of positioning.

[0019] Optionally, convert the current coordinates to the second coordinate system based on the offset value to obtain the target coordinates, including: performing a zeroing process on the current coordinates based on the offset value to obtain the relative coordinates with respect to the central meridian and the equator, where the zeroing process is used to represent subtracting the offset value from the current coordinates, and the central meridian is the central meridian corresponding to the zone; converting the relative coordinates to the second latitude value based on the semi-major axis of the earth and the angular unit conversion parameter; determining the second longitude value based on the second latitude value and the central meridian; determining the target coordinates based on the second latitude value and the second longitude value.

[0020] Adopting the zeroing process, the conversion of latitude and longitude values ensures the accuracy and efficiency of the coordinate conversion, and is suitable for local map positioning requirements.

[0021] According to one aspect of the embodiments of the present invention, a vehicle positioning device is provided, including: an acquisition module for collecting the current coordinates and vehicle pose data of a simulation vehicle on a target map during the process of controlling the simulation vehicle to run in an intelligent driving simulation scenario; a conversion module for converting the current coordinates based on the projection method of the target map to obtain the target coordinates, where the target coordinates are the coordinates corresponding to the coordinate type required by the domain controller; a coupling module for coupling the target coordinates and the vehicle pose data to obtain coupling data and sending the coupling data to the domain controller, where the coupling data is used to assist the vehicle positioning of the domain controller.

[0022] According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including a processor and a memory, wherein the memory is used for storing a computer program; the processor is used for executing the program stored on the memory to implement the methods in the various embodiments of the present invention.

[0023] According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, in which a computer program is stored, and the computer program implements the methods in the various embodiments of the present invention when being executed by a processor. Description of the Drawings

[0024] Figure 1 is a flowchart of a vehicle positioning method provided by an embodiment of the present application;

[0025] Figure 2 is a schematic diagram of a coordinate system provided by an embodiment of the present application;

[0026] Figure 3 is a schematic diagram of an optional vehicle positioning method provided by an embodiment of the present application;

[0027] Figure 4 is a flowchart of an optional data transmission method provided by an embodiment of the present application;

[0028] Figure 5 is a structural diagram of a vehicle positioning device provided by an embodiment of the present application;

[0029] Figure 6 is a structural diagram of an electronic device provided by an embodiment of the present application. Detailed Embodiments

[0030] In order to make the technical problems, technical solutions and beneficial effects solved by the present application more clear and understandable, the present application will be further described in detail below with reference to the 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.

[0031] Simulation testing has become one of the typical applications of intelligent driving testing technology. Simulation testing can not only effectively reduce the testing cost, but also discover and solve problems in time before the actual road testing is carried out, thereby improving the intelligent level of intelligent driving vehicles. In intelligent driving simulation testing, the positioning accuracy of the vehicle will greatly affect the reliability of the test results.

[0032] Currently, in the related art, the global positioning system positioning method is often directly adopted, and the positioning information obtained by the global positioning system is corrected and used as the positioning coordinate. However, during the positioning process of the global positioning system, there will be phenomena such as signal reception delay and signal occlusion, which easily lead to the distortion of the positioning result and the reduction of the positioning accuracy.

[0033] Global positioning projection method: It refers to a projection method that can map the longitude and latitude coordinates on the earth's surface to a plane coordinate system. The global positioning projection method can be Mercator projection, gnomonic projection, etc.

[0034] Local positioning projection method: It refers to a projection method that can project the earth's surface according to longitude zones into a plane coordinate system. The local positioning projection usually selects the center point of a certain area as the projection center, and then projects according to the geographical features around the center point to ensure that the map presents the true geographical features of the area. The local positioning projection method can be Universal Transverse Mercator projection, equal-area conic projection, etc.

[0035] Global geographic coordinate system: It refers to a positioning system that can describe the position of an object on the earth. The global geographic coordinate system is determined based on the shape of the earth (i.e., the earth ellipsoid) and a reference ellipsoid parameter. The major axis and flattening of the earth are defined in the global geographic coordinate system, which can be used in global positioning systems and satellite navigation systems, etc. In the global geographic coordinate system, the position is identified by longitude and latitude.

[0036] Surveying and mapping coordinate system: It refers to a coordinate system that introduces a random offset, especially can be used in Internet map services to achieve the protection and management of geographical information. Through coordinate offset, the security of geographical information can be protected and unauthorized applications of geographical information can be restricted.

[0037] A vehicle positioning method provided by an embodiment of the present application includes: during the process of controlling a simulated vehicle to run in an intelligent driving simulation scenario, collecting the current coordinates of the simulated vehicle on a target map and vehicle pose data; converting the current coordinates based on the projection method of the target map to obtain target coordinates, where the target coordinates are the coordinates corresponding to the coordinate type required by the domain controller; coupling the target coordinates and the vehicle pose data to obtain coupled data, and sending the coupled data to the domain controller, where the coupled data is applied to assist the vehicle positioning of the domain controller.

[0038] The above vehicle positioning method provided by the embodiment of the present application achieves the following technical effects: After converting the simulation coordinates through the projection method of the target map and coupling them with the vehicle pose data, coupled data that conforms to the processing format of the domain controller is obtained. It can not only flexibly adapt to maps with different projection methods, but also ensure the accuracy and compatibility of data transmission between the simulated vehicle and the domain controller of the real vehicle by coupling the data and then transmitting it to the domain controller, so that the domain controller can use the simulation data for accurate vehicle positioning.

[0039] Embodiment 1

[0040] A vehicle positioning method provided by an embodiment of the present application is applied to a simulation system. Please refer toFigure 1 , including the following steps:

[0041] S110: During the process of controlling the simulation vehicle to run in the intelligent driving simulation scenario, collect the current coordinates of the simulation vehicle on the target map and the vehicle pose data.

[0042] The above simulation system can be used to simulate the actual road environment, traffic conditions, and vehicle motion behaviors. The simulation system is mainly used to test and verify the functions and performance of the intelligent driving system. It can simulate various driving conditions and working conditions in a safe and controllable environment, so as to verify the effectiveness and safety of the intelligent driving function by accurately simulating the actual road environment and vehicle postures.

[0043] The above intelligent driving simulation scenario can refer to a virtual scenario intelligent driving simulation scenario created in a computer environment. These scenarios can include, but are not limited to: urban streets, highways, rural roads, parking lots, etc. And these working conditions can also include elements such as weather, lighting, pedestrians, other vehicles, etc. Here, the scenarios are not limited and can be determined according to needs.

[0044] The above target map can refer to a high-precision map used in the simulation system. The target map can include geographical information and the projection method of the map, etc. Here, the content of the target map is not limited and can be determined according to needs. Geographical information can include, but is not limited to: the location of roads, lane lines, traffic signs, obstacles, traffic lights, etc. Here, the geographical information is not limited and can be determined according to needs. For example, the target map can be an Open Drive map. Open Drive is an open standard format for describing road networks. The target map can also be a High-Definition (HD) map, and the accuracy of the HD map can reach the centimeter level. In the simulation system, the target map is used to provide a reference for vehicle positioning and background environment information to ensure the accuracy and authenticity of the simulation test.

[0045] The above simulation vehicle can refer to a simulated vehicle running in the simulation system. Through the simulation vehicle, the behaviors and dynamic characteristics of real vehicles can be simulated in the simulation system. By controlling the movement of the simulation vehicle in the simulation system, data such as the position, speed, and acceleration of the simulation vehicle can be collected, and then used to calibrate the positioning and movement of real vehicles.

[0046] The above-mentioned current coordinates can be simulation data generated by a simulated vehicle running in a simulation scenario. The current coordinates can reflect the real-time position information of the simulated vehicle in the simulation scenario. For example, the current coordinates can be (x, y) coordinates. The current coordinates can accurately reflect the position of the simulated vehicle in the simulation environment, so as to test and verify various functions of the vehicle intelligent driving system. However, the type of coordinates processed by the domain controller may be longitude and latitude coordinates. Therefore, it is necessary to convert the current coordinates so that the domain controller can judge information such as the position, speed, and direction of the vehicle based on the coordinates, and then precisely control the vehicle.

[0047] The above-mentioned vehicle pose data can be used to characterize the motion of the vehicle in the simulation scenario. The vehicle pose data can include but are not limited to: vehicle position, six-axis acceleration, angular acceleration, etc. There is no limitation on the vehicle pose data here, and it can be determined according to needs. Among them, the vehicle position can be represented by coordinates. The angular acceleration can be lateral acceleration, longitudinal acceleration, vertical acceleration, yaw angular acceleration, pitch angular acceleration, or roll angular acceleration. There is no limitation on the angular acceleration here, and it can be determined according to needs.

[0048] In an alternative embodiment, the motion of the simulated vehicle can be controlled by means of calling an Application Programming Interface (API for short), and the current coordinates and vehicle pose data of the simulated vehicle can be read. A control script or application program can be pre-written. The script or application program can send control instructions by calling the API of the intelligent driving simulation software, so as to control the acceleration, steering, or braking of the simulated vehicle based on the control instructions. And the API can be listened to or queried to obtain the current coordinates and vehicle pose data of the simulated vehicle. Relevant data can be collected through the API interface with low latency and high precision.

[0049] In another alternative embodiment, the operation of the simulated vehicle can be controlled by scripting the test scenario. A test scenario script can be pre-written, and the script can pre-define the motion path and behavior of the simulated vehicle. The intelligent driving simulation software executes the script to run and records the current coordinates and vehicle pose data of the simulated vehicle. Specifically, a scenario description file can be created, and parameters such as the starting point, ending point, path, speed, and acceleration of the vehicle can be defined using a scripting language. And a coordinate acquisition instruction can be added to the script to collect the current coordinates and vehicle pose data.

[0050] In yet another alternative embodiment, the current coordinates and vehicle pose data can also be collected through a sensor system. The sensor system can include but are not limited to an inertial measurement unit, lidar, or camera, etc. There is no limitation on the sensor system here, and it can be determined according to needs.

[0051] S120: Convert the current coordinates based on the projection method of the target map to obtain the target coordinates.

[0052] Among them, the target coordinates are the coordinates corresponding to the coordinate type required by the domain controller.

[0053] The above-mentioned projection method can refer to the coordinate transformation method adopted by the target map. The projection method can be Mercator projection, Lambert projection, stereographic projection, etc. There is no limitation on the projection method here and it can be determined according to needs. Through the projection of the map, the geographical coordinates on the earth's surface can be converted into coordinates on a plane, which is convenient for display and operation on the map. Different projection methods can ensure the compatibility of the map with the data output by the intelligent driving simulation system. In the intelligent driving simulation system, through the coordinate type required by the domain controller and based on an appropriate map projection method, it can be ensured that the coordinate data generated by the simulation matches the input requirements of the domain controller, thus realizing effective communication and data exchange between coordinates.

[0054] The above-mentioned target coordinates can be the position data of the vehicle in the real world or on the map. Based on the target coordinates, the position of the vehicle can be located. Through the target coordinates, it is convenient for the domain controller to perform path planning, adjust the driving direction and speed of the vehicle, and thus realize navigation. The target coordinates can also be used for obstacle avoidance decision-making. When the system identifies an obstacle, it can dynamically calculate a new driving path to ensure that the vehicle can avoid danger in time and move forward safely in a complex environment. Therefore, the target coordinates can not only be used for vehicle positioning, but also help the intelligent driving system to realize intelligent driving functions and ensure driving safety.

[0055] The above-mentioned conversion refers to the process of converting simulation coordinates into real coordinates, so as to simulate the behavior and position information of a real vehicle in different map projection environments. Through coordinate conversion, the positioning accuracy can be improved or maintained. By converting to the target coordinates corresponding to the coordinate input type, it can be ensured that the vehicle positioning information matches the input requirements of the domain controller, and it can also be ensured that the interface of the domain controller can receive and process correct coordinate data, thereby improving the accuracy and effectiveness of positioning.

[0056] In an alternative embodiment, a coordinate mapping model can be established through a machine learning model. The machine learning model can be a multi-layer perceptron or a convolutional neural network. There is no limitation on the machine learning model here and it can be determined according to needs. That is, the current coordinates can be input into the coordinate mapping model, and the output of the model is the target coordinates. The coordinate mapping model can be trained by a multi-layer perceptron based on a training set and adjusted through the backpropagation algorithm.

[0057] In another alternative embodiment, a corresponding conversion formula can be determined according to the projection method, so as to convert the current coordinates based on the conversion formula to obtain the target coordinates. The conversion formula is usually implemented based on the ellipsoid model of the earth and the principle of projection.

[0058] In yet another alternative embodiment, coordinate conversion can be achieved through a look-up table and interpolation method. The look-up table includes pre-calculated results, and through the look-up table, the real-time calculation speed can be accelerated. The coordinate values of key points under the target map projection can be pre-calculated and stored in the look-up table. When the current coordinates need to be converted, the key points can be determined by the distance between the current coordinates and the key points, and then the target coordinates can be calculated through interpolation methods, such as linear interpolation and bilinear interpolation.

[0059] S130: Couple the target coordinates and vehicle pose data to obtain coupled data, and send the coupled data to the domain controller.

[0060] Among them, the coupled data is applied to assist the vehicle positioning of the domain controller.

[0061] The above-mentioned coupled data can be applied to assist the vehicle positioning of the domain controller. In the simulation system, the coupled data can refer to combining the target coordinates and vehicle pose data to form vehicle state data, which can more accurately reflect the running state of the vehicle in the virtual environment. The coupled data can be used for intelligent driving operations such as navigation, path planning, and decision-making. The coupled data can also make the data transmission and processing process clearer and more efficient.

[0062] In an alternative embodiment, a data fusion module can be used to couple the target coordinates and vehicle pose data to obtain coupled data. This module is equipped with a data fusion algorithm, and the data fusion algorithm can be Kalman filtering or particle filtering. Here, the data fusion algorithm is not limited and can be determined according to needs. The target coordinates and vehicle pose data can be input into the data fusion algorithm, and the fused data is output. Then, the coupled data can be sent to the domain controller through a communication protocol. The communication protocol can be a standard network protocol such as the User Datagram Protocol or the Transmission Control Protocol, or a custom protocol.

[0063] In another alternative embodiment, middleware technology can also be used for data coupling. The middleware provides a flexible data publishing and subscribing mechanism, which can integrate multiple different types of data streams into one topic or service and then send it to the domain controller. For example, the target coordinates and vehicle pose data can be respectively published to two different topics of the middleware, and then a topic for coupled data is created at the subscribing end of the middleware. The subscribing end integrates the two types of data after receiving them and then publishes the coupled data.

[0064] After the above vehicle positioning method provided by the embodiment of the present application converts the simulation coordinates through the projection method of the target map and couples them with the vehicle pose data, coupled data conforming to the processing format of the domain controller can be obtained. This can not only flexibly adapt to maps with different projection methods, but also ensure the accuracy and compatibility of data transmission between the simulation vehicle and the domain controller of the real vehicle by coupling the data and then transmitting it to the domain controller, so that the domain controller can use the simulation data for accurate vehicle positioning.

[0065] Step S130 includes: obtaining the communication configuration parameters between the simulation system and the domain controller; converting the communication configuration parameters into a configuration file adapted to the simulation system; performing format conversion on the target coordinates and the vehicle pose data based on the configuration file to obtain preset coordinates and preset vehicle pose data, where the preset coordinates are coordinates conforming to the corresponding data reception format of the domain controller, and the preset vehicle pose data is the vehicle pose data conforming to the corresponding data reception format; and integrating the preset coordinates and the preset vehicle pose data to obtain coupled data.

[0066] The above communication configuration parameters can be used to define and configure the communication rules between the simulation system and the domain controller. For example, the communication configuration parameters can be used for the multi-service transmission protocol. The multi-service transmission protocol is a protocol used for communication between different electronic control units in a vehicle network. Through this protocol, it is convenient for multiple services to be transmitted on a single network connection to achieve vehicle network communication. The communication configuration parameters can include but are not limited to: deployment information, service interfaces, data types, serialization parameters, and service discovery parameters, etc. There is no limitation on the communication configuration parameters here, and they can be determined according to needs. Through the communication configuration parameters, communication services can be defined to ensure a secure network connection.

[0067] In an alternative embodiment, the communication configuration parameters can be obtained through the communication module in the simulation software. Or, the communication configuration parameters can also be obtained by parsing a pre-set communication configuration file. Then, based on the configuration template, the communication configuration parameters can be converted into a configuration file adapted to the simulation system, or the communication configuration parameters can also be imported into the configuration tool, and the configuration tool can automatically generate the configuration file.

[0068] Furthermore, the configuration file can be parsed through a scripting language to extract the conversion formula and parameters, so that the target coordinates and vehicle pose data can be converted into the preset coordinates and preset vehicle pose data in a corresponding format that meets the receiving conditions of the domain controller through the conversion formula and parameters. Alternatively, the preset format can also be obtained by reading the configuration file through a plug-in, and the target coordinates and vehicle pose data can be format-converted into the preset coordinates and preset vehicle pose data based on the conversion algorithm integrated in the plug-in. Finally, the preset coordinates and preset vehicle pose data can be input into the data coupling algorithm integrated in the domain controller, and the data coupling algorithm can calculate based on the preset coordinates and preset vehicle pose data to obtain the coupling data. Alternatively, the coupling data can also be predicted through a data prediction model. The data prediction model can be trained by one of the following: convolutional neural network, recurrent neural network, or long short-term memory network. There is no limitation on the data prediction model here and it can be determined according to needs.

[0069] By accurately obtaining the communication configuration parameters, the consistency of the data in the intelligent driving simulation environment with the real environment is ensured, making the simulation results more reliable and realistic. Further determine the configuration file to adapt to different test scenarios. Format-converting the target coordinates and vehicle pose data and then sending them to the domain controller for processing can effectively reduce the simulation error and improve the security and reliability of data communication.

[0070] Optionally, format-converting the target coordinates and vehicle pose data based on the configuration file to obtain the preset coordinates and preset vehicle pose data includes: importing the configuration file into the simulation system and generating a communication interface between the simulation system and the domain controller based on the configuration file; mapping the target coordinates and vehicle pose data respectively based on the communication interface to obtain the preset coordinates and preset vehicle pose data.

[0071] In an alternative embodiment, the configuration file can be imported into the middleware, and the middleware can parse the configuration file to obtain the service definition and communication rules, thereby configuring the communication interface. Alternatively, the configuration file can also be read through a scripting language, and then the communication interface can be automatically generated according to the parsing result using the script. Then, the format requirements corresponding to the communication interface can be read through the scripting language, and thus the target coordinates and vehicle pose data can be respectively converted into the preset coordinates and preset vehicle pose data through the conversion algorithm. Alternatively, the target coordinates and vehicle pose data of the communication interface can also be input into the data mapping model, and the preset coordinates and preset vehicle pose data can be predicted through the data mapping model. The data mapping model can be trained by one of the following: convolutional neural network, recurrent neural network, or long short-term memory network. There is no limitation on the data mapping model here and it can be determined according to needs.

[0072] By means of a configuration file, the communication interface is adaptively determined, providing flexibility in data conversion. Moreover, the target coordinate mapping based on the communication interface can ensure that the preset coordinates and preset vehicle pose data meet the requirements of the domain controller, improving the efficiency and accuracy of testing.

[0073] Step S120 includes: in response to the projection mode being the global positioning projection mode, converting the current coordinates based on the first coordinate system and the second coordinate system to obtain the target coordinates, where the global positioning projection mode is used to represent mapping the longitude and latitude coordinates on the earth's surface to a plane coordinate system; in response to the projection mode being the local positioning projection mode, converting the current coordinates based on the second coordinate system to obtain the target coordinates, where the local positioning projection mode is used to represent projecting the earth's surface according to longitude zones to a plane coordinate system; where the second coordinate system is the coordinate system corresponding to the map used by the domain controller, and there is an encrypted offset between the first coordinate system and the second coordinate system, where the encrypted offset is used to represent applying a random offset to the coordinates.

[0074] Generally, for the pilot assist driving on highways, the map usually adopts the global positioning projection mode, and for the pilot assist driving on urban roads, the map usually adopts the local positioning projection mode.

[0075] The above-mentioned global positioning projection mode can be used to represent mapping the longitude and latitude coordinates on the earth's surface to a plane coordinate system. The local positioning projection mode can be used to represent projecting the earth's surface according to longitude zones to a plane coordinate system. The above-mentioned second coordinate system can be the coordinate system corresponding to the map used by the domain controller. The first coordinate system is obtained by applying an encrypted offset to the second coordinate system. The encrypted offset can be used to represent applying a random offset to the coordinates.

[0076] As Figure 2 described, two coordinate systems are provided. In Figure 2 it, on the left is the earth coordinate system, and it is unbiased. The earth coordinate system is represented by (x, y, z) coordinates. In the earth coordinate system, 1 is the earth's centroid, 2 is the prime meridian, and w is the earth's angular velocity of rotation. This coordinate system can be used for maps adopting the universal transverse Mercator projection mode, and the universal transverse Mercator projection mode belongs to a global positioning projection mode.

[0077] Figure 2 On the right is the surveying coordinate system. The surveying coordinate system is obtained by applying an offset to the coordinates in the earth coordinate system. The surveying coordinate system is represented by plane longitude and latitude. This surveying coordinate system can be used for maps adopting the local Mercator projection mode. The local Mercator projection mode belongs to a local positioning projection mode.

[0078] In an alternative embodiment, when the projection method is the global positioning projection method, the current coordinates can be converted based on the first coordinate system and the second coordinate system to obtain the target coordinates. Specifically, the current coordinates can be converted based on the first coordinate system and the second coordinate system in combination with the corresponding coordinate conversion library to obtain the target coordinates. Alternatively, a first conversion table can be formed in advance by pairing coordinate conversions. When performing coordinate conversion, look up or perform interpolation calculations in the first conversion table to convert the current coordinates to the target coordinates.

[0079] When the projection method is the local positioning projection method, the current coordinates can be converted based on the second coordinate system to obtain the target coordinates. Specifically, the current coordinates can be converted to the second coordinate system through a preset conversion formula or an online geographic information conversion service. For example, the current coordinates can be used as parameters to send a conversion request to the geographic information conversion service. After receiving the request, the geographic information conversion service returns the coordinate values in the second coordinate system.

[0080] By using different conversion methods for different projection methods, the coordinate conversion problem under different map projection methods can be effectively handled, ensuring that the accuracy of vehicle positioning information is not affected when using different map data sources, which is applicable to the testing and verification of intelligent driving systems in different geographical regions.

[0081] Optionally, converting the current coordinates based on the first coordinate system and the second coordinate system to obtain the target coordinates includes: converting the current coordinates into the first coordinate system to obtain the first coordinates in the first coordinate system; based on the encrypted offset, converting the first coordinates into the second coordinate system to obtain the target coordinates.

[0082] In an alternative embodiment, the current coordinates can be converted into the first coordinate system through a preset conversion formula or an online geographic information conversion service. For example, the current coordinates can be used as parameters to send a conversion request to the geographic information conversion service. After receiving the request, the geographic information conversion service returns the coordinate values in the first coordinate system.

[0083] Then, based on the preset offset formula or by invoking the coordinate conversion service, the coordinates in the first coordinate system can be encrypted and offset processed to obtain the target coordinates.

[0084] Eliminating the encrypted offset can improve the accuracy of vehicle positioning, avoid errors caused by map data encryption, and ensure that the positioning information received by the domain controller is consistent with the actual position.

[0085] Optionally, converting the current coordinates into the first coordinate system to obtain the first coordinates in the first coordinate system includes: determining the first longitude value and the first latitude value of the current coordinates in the first coordinate system based on the semi-major axis of the earth and the angular unit conversion parameter; based on the first longitude value and the first latitude value, obtaining the first coordinates.

[0086] In an alternative embodiment, a preset conversion formula can be used to calculate the first longitude value and the first latitude value of the current coordinate in the first coordinate system. Alternatively, the coordinates can also be determined by calling a coordinate conversion function. That is, the semi-major axis of the earth, the angle unit conversion parameter, and the current coordinate can be input, and the first longitude value and the first latitude value can be automatically calculated through the coordinate conversion function. Or, coordinate conversion can also be achieved through a global geographic information system tool. The semi-major axis of the earth, the angle unit conversion parameter, and the current coordinate are imported into the global geographic information system tool, and the output of this tool is the first longitude value and the first latitude value. Then, by combining the first longitude value and the first latitude value, the first coordinate can be obtained.

[0087] For example, the first latitude value can be determined by the following formula.

[0088]

[0089] In the formula, X is the first latitude value, x is the plane abscissa, r is the angle unit conversion parameter, α is the semi-major axis of the earth, α is a fixed value, and α is 6378137.0.

[0090] The first longitude value can be determined by the following formula.

[0091]

[0092] In the formula, Y is the first longitude value, y is the plane ordinate, r is the angle unit conversion parameter, α is the semi-major axis of the earth, α is a fixed value, and α is 6378137.0.

[0093] This process realizes precise coordinate conversion through parameters, which can ensure the accuracy of the first coordinate.

[0094] Optionally, the current coordinate is converted based on the second coordinate system to obtain the target coordinate, including: determining the zone where the current coordinate is located and the zone identifier corresponding to the zone. Here, the zone refers to the geographical zone area formed by projecting the earth's surface onto a plane coordinate system according to longitude zones; determining the offset value of the zone based on the zone identifier; and converting the current coordinate to the second coordinate system based on the offset value to obtain the target coordinate.

[0095] The above-mentioned zone can refer to the geographical zone area formed by projecting the earth's surface onto a plane coordinate system according to longitude zones. The division of zones is to reduce the error when the earth ellipsoid is projected onto a plane coordinate system and improve the local accuracy.

[0096] In an alternative embodiment, the strip and strip identifier corresponding to the current coordinates can be determined through a strip mapping list. Alternatively, the strip in which the current coordinates are located can be calculated based on the current coordinates, and then the strip identifier corresponding to the strip can be determined. Then, based on the strip offset mapping list, the offset value of the strip can be determined. Alternatively, the offset value of the strip can also be determined by comparing the hash value corresponding to the strip identifier with the hash value of the offset value through a hash algorithm. Finally, the offset formula can be used to transform the current coordinates to obtain the target coordinates.

[0097] In another alternative embodiment, the world geographic information library can also be called to automatically identify the strip in which the current coordinates are located and the strip identifier corresponding to the strip. Then, the conversion function in the world geographic information library can be called to transform the current coordinates based on the offset value to obtain the target coordinates.

[0098] By determining the specific strip in which the current coordinates are located and then applying the offset value of the strip for transformation, the accuracy of coordinate transformation can be ensured, the errors that may occur during cross-strip transformation can be avoided, and the realism of the simulation scenario and the accuracy of positioning can be enhanced.

[0099] Optionally, transforming the current coordinates to the second coordinate system based on the offset value to obtain the target coordinates includes: performing a zeroing process on the current coordinates based on the offset value to obtain the relative coordinates with respect to the central meridian and the equator, where the zeroing process is used to represent subtracting the offset value from the current coordinates, and the central meridian is the central meridian corresponding to the strip; converting the relative coordinates to the second latitude value based on the semi-major axis of the earth and the angular unit conversion parameter; determining the second longitude value based on the second latitude value and the central meridian; and determining the target coordinates based on the second latitude value and the second longitude value.

[0100] The above zeroing process can be used to represent subtracting the offset value from the current coordinates.

[0101] In an alternative embodiment, an offset model can be used to input the offset value and the current coordinates into the offset model, and the offset model can output the relative coordinates. The offset model can be the least squares method, and the offset model can also be trained based on machine learning algorithms such as decision trees and support vector machines. Alternatively, the coordinate transformation library can also be called. After defining the offset value and inputting the current coordinates, the relative coordinates can be obtained. The coordinate transformation library contains a projection formula to project the current coordinates after subtracting the offset value to obtain the relative coordinates.

[0102] Then, the preset conversion formula can be used to calculate the second latitude value of the relative coordinates in the second coordinate system. Alternatively, the coordinates can also be determined by calling a coordinate conversion function. That is, the semi-major axis of the earth, the angle unit conversion parameter, and the relative coordinates can be input, and the second latitude value can be automatically calculated through the coordinate conversion function. Or, coordinate conversion can also be achieved through a global geographic information system tool. The semi-major axis of the earth, the angle unit conversion parameter, and the relative coordinates are imported into the global geographic information system tool, and the output of this tool is the second latitude value.

[0103] Finally, a longitude conversion model can be trained using regression analysis or a neural network algorithm. After inputting the second latitude value and the central meridian into this longitude conversion model, the second longitude value is output. Thus, based on the second latitude value and the second longitude value, the target coordinates can be determined.

[0104] Through zeroing processing and dimension conversion, coordinate offset is effectively eliminated, ensuring the accuracy of vehicle positioning information. It is applicable to scenarios where the intelligent driving system requires high-precision positioning information, such as automatic parking or high-precision map matching.

[0105] Step S110 includes collecting the current coordinates and initial vehicle pose data of the simulation vehicle on the target map; and filling the initial vehicle pose data based on the preset communication fields to obtain the vehicle pose data.

[0106] In an alternative embodiment, the movement of the simulation vehicle can be controlled by means of API calls, and the current coordinates and initial vehicle pose data of the simulation vehicle can be read. Or, the operation of the simulation vehicle can also be controlled by scripting the test scenario. The intelligent driving simulation software executes the script to run and records the current coordinates and initial vehicle pose data of the simulation vehicle.

[0107] Then, the preset communication fields can be read through a data filling script. The data filling script can map the initial vehicle pose data onto the preset communication fields, thereby obtaining the vehicle pose data. Or, a data filling service can also be defined through middleware. The middleware configures service parameters according to the preset communication fields, so that the middleware service receives the initial vehicle pose data and performs data filling according to the service parameters to obtain the vehicle pose data.

[0108] By filling the vehicle pose data, the coordinate data and pose data can be comprehensively utilized to more comprehensively simulate the vehicle state, improving the accuracy of the positioning result and the integrity of the simulation test.

[0109] The vehicle positioning method provided by the embodiments of the present application further includes: based on the target map, building an intelligent driving simulation scenario based on the preset working conditions scenario.

[0110] The above-mentioned preset working condition scenarios may include, but are not limited to, traffic flow, road obstacles, weather conditions, etc. There is no limitation on the preset working condition scenarios here, and they can be determined according to needs.

[0111] In an alternative embodiment, a scenario description language can be used to build an intelligent driving simulation scenario based on a target map and preset working condition scenarios. A scenario file is written using the scenario description language, and the scenario file may include the starting position of the vehicle in the simulation scenario, the driving path, traffic rules, the behaviors of other vehicles and pedestrians, and even environmental factors such as light and weather. Then, the scenario file is imported into the intelligent driving simulation software to automatically generate an intelligent driving simulation scenario.

[0112] In another alternative embodiment, an intelligent driving scenario construction tool with a graphical user interface can also be used to build an intelligent driving simulation scenario by means of dragging, drawing, etc. After selecting the target map, the intelligent driving scenario construction tool adaptively provides construction elements for the user to select according to the target map. Alternatively, a preset working condition scenario can also be automatically constructed by writing a script.

[0113] Based on the target map, building an intelligent driving simulation scenario can accurately reflect the real road environment and vehicle behaviors, ensuring a high degree of authenticity in the simulation test.

[0114] Step S140 further includes: sending a service request to the domain controller; in response to receiving a subscription instruction from the domain controller for the service request, sending the coupled data to the domain controller.

[0115] In an alternative embodiment, a service request can be sent to the domain controller through a multi-service transmission protocol, a data distribution service protocol, or a message publishing and subscribing protocol to obtain the required simulation data through the service request.

[0116] For example, a service request can be sent to the domain controller through a multi-service transmission protocol. After receiving the service request, the domain controller discovers and selectively subscribes to the required services through the service discovery function of the multi-service transmission protocol, so as to obtain the coupled data by sending a subscription instruction. Alternatively, a service request can also be sent using the data distribution service protocol, declaring that vehicle attitude and positioning data will be provided. The domain controller sends a subscription request as a subscriber. When the intelligent driving simulation system receives the subscription instruction, it sends the coupled data to the domain controller through the data reading and writing function.

[0117] Through the service request and subscription process, it can be ensured that the domain controller can actively select and subscribe to the specific service data required, thereby avoiding unnecessary data transmission and reducing network load and energy consumption.

[0118] Figure 3It is a schematic diagram of an optional vehicle positioning method provided by an embodiment of the present application. As Figure 3 shown, the method includes four processes: local pose, global positioning, integrated transmission, and domain controller processing.

[0119] The local pose process includes obtaining the vehicle pose after setting up the rendering simulation scene.

[0120] The global positioning process includes inputting a high-precision map and determining whether it is a local positioning projection method. If the high-precision map is in the local positioning projection method, the target coordinates are output using a third coordinate conversion module. Otherwise, it is determined whether it is a global positioning projection method. If the high-precision map is in the global positioning projection method, after conversion using the first coordinate conversion module and then passing through the second coordinate conversion module, the target coordinates are output.

[0121] The integrated transmission is implemented through a data sending module, and the domain controller processing is implemented through a domain control map and positioning module. The data sending module can send the vehicle pose and target coordinates to the domain control map and positioning module to perform vehicle positioning using the domain control map and positioning module.

[0122] Figure 4 It is a flowchart of an optional data transmission method provided by an embodiment of the present application. As Figure 4 shown, the method includes the following:

[0123] S410: Obtain the communication configuration matrix of the inertial navigation unit, as well as the vehicle pose data and global positioning data.

[0124] S420: Generate a corresponding configuration file from the communication configuration matrix.

[0125] S430: Import the configuration file into the simulation scene software and generate a communication interface according to the configuration file.

[0126] S440: According to the communication interface, map the vehicle pose data and global positioning data to obtain the positioning coordinates of the vehicle.

[0127] Embodiment 2

[0128] The embodiment of the present application also provides a vehicle positioning device 50. Please refer to Figure 5, including: an acquisition module 510, configured to collect the current coordinates and vehicle pose data of a simulation vehicle on a target map during the process of controlling the simulation vehicle to run in an intelligent driving simulation scenario; a conversion module 520, configured to perform a step of converting the current coordinates based on the projection method of the target map to obtain target coordinates, where the target coordinates are coordinates corresponding to the coordinate type required by the domain controller; a coupling module 530, configured to perform a step of coupling the target coordinates and the vehicle pose data to obtain coupling data, and sending the coupling data to the domain controller, where the coupling data is used to assist the vehicle positioning of the domain controller.

[0129] Optionally, the coupling module is further configured to obtain the communication configuration parameters between the simulation system and the domain controller; convert the communication configuration parameters into a configuration file adapted to the simulation system; perform format conversion on the target coordinates and the vehicle pose data based on the configuration file to obtain preset coordinates and preset vehicle pose data, where the preset coordinates are coordinates that conform to the data reception format corresponding to the domain controller, and the preset vehicle pose data is vehicle pose data that conforms to the data reception format; integrate the preset coordinates and the preset vehicle pose data to obtain coupling data.

[0130] Optionally, the coupling module is further configured to import the configuration file into the simulation system, generate a communication interface between the simulation system and the domain controller based on the configuration file; map the target coordinates and the vehicle pose data respectively based on the communication interface to obtain preset coordinates and preset vehicle pose data.

[0131] Optionally, the conversion module is further configured to, in response to the projection method being a global positioning projection method, convert the current coordinates based on the first coordinate system and the second coordinate system to obtain target coordinates, where the global positioning projection method is used to represent mapping the longitude and latitude coordinates on the earth's surface to a plane coordinate system; in response to the projection method being a local positioning projection method, convert the current coordinates based on the second coordinate system to obtain target coordinates, where the local positioning projection method is used to represent projecting the earth's surface according to longitude zones to a plane coordinate system; where the second coordinate system is the coordinate system corresponding to the map used by the domain controller, and there is an encrypted offset between the first coordinate system and the second coordinate system, where the encrypted offset is used to represent applying a random offset to the coordinates.

[0132] Optionally, the conversion module is further configured to convert the current coordinates into the first coordinate system to obtain the first coordinate in the first coordinate system; convert the first coordinate into the second coordinate system based on the encrypted offset to obtain the target coordinates.

[0133] Optionally, the conversion module is further configured to determine the first longitude value and the first latitude value of the current coordinates in the first coordinate system based on the earth's semi-major axis and the angular unit conversion parameter; obtain the first coordinate based on the first longitude value and the first latitude value.

[0134] Optionally, the conversion module is further configured to determine the zone where the current coordinate is located and the zone identifier corresponding to the zone. Here, the zone refers to the geographical zone area formed by projecting the earth's surface onto a plane coordinate system according to longitude zones; determine the offset value of the zone based on the zone identifier; and convert the current coordinate to the second coordinate system based on the offset value to obtain the target coordinate.

[0135] Optionally, the conversion module is further configured to perform zeroing processing on the current coordinate based on the offset value to obtain the relative coordinate with respect to the central meridian and the equator. Here, the zeroing processing is used to represent subtracting the offset value from the current coordinate, and the central meridian is the central meridian corresponding to the zone; convert the relative coordinate to the second latitude value based on the earth's semi-major axis and the angular unit conversion parameter; determine the second longitude value based on the second latitude value and the central meridian; and determine the target coordinate based on the second latitude value and the second longitude value.

[0136] Optionally, the acquisition module is further configured to collect the current coordinate and the initial vehicle pose data of the simulation vehicle on the target map; and perform data filling on the initial vehicle pose data based on the preset communication field to obtain the vehicle pose data.

[0137] Optionally, the above device further includes a construction module, and the construction module is configured to construct an intelligent driving simulation scenario based on the preset working condition scenario on the basis of the target map.

[0138] Optionally, the coupling module is further configured to send a service request to the domain controller; and in response to receiving the subscription instruction of the domain controller for the service request, send the coupling data to the domain controller.

[0139] The embodiment of the present application further provides an electronic device 60. Please refer to Figure 6 , which includes a processor 610 and a memory 620. Here, the memory 610 is used to store a computer program; the processor 620 is used to execute the program stored on the memory 610 to implement the vehicle positioning method introduced in any embodiment of the present application.

[0140] The embodiment of the present application further provides a computer-readable storage medium, and a computer program is stored in the computer-readable storage medium. When the computer program is executed by a processor, the vehicle positioning method introduced in any embodiment of the present application is implemented.

[0141] In the present application, "a plurality of" means two or more.

[0142] In this application, unless otherwise clearly defined, the terms "install", "connect", and "couple" shall be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a structural connection or an electrical connection; it may be a direct connection or an indirect connection through an intermediate medium, and it may be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0143] The terms "first", "second", "third", "fourth", etc. (if any) in this application are used to distinguish similar objects and do not necessarily describe a specific order or sequence.

[0144] The term "and / or" in this application is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this application generally represents an "or" relationship between the related objects before and after.

[0145] If there is no special instruction, all steps of this application can be carried out in sequence or randomly. For example, the method includes steps A and B, indicating that the method may include steps A and B carried out in sequence, or may also include steps B and A carried out in sequence. For example, it is mentioned that the method may further include step C, indicating that step C can be added to the method in any order. For example, the method may include steps A, B, and C, or may also include steps A, C, and B, or may include steps C, A, and B, etc.

[0146] The above are only the preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of this application shall be included within the protection scope of this application.

Claims

1. A vehicle positioning method, characterized in that: Applied to simulation systems, including: In the process of controlling the simulated vehicle to run in the intelligent driving simulation scene, collecting the current coordinates and vehicle posture data of the simulated vehicle on the target map; The current coordinates are converted based on the projection mode of the target map to obtain target coordinates, wherein the target coordinates are coordinates corresponding to the coordinate type required by the domain controller; The target coordinates and the vehicle posture data are coupled to obtain coupled data, and the coupled data is sent to the domain controller, wherein the coupled data is used to assist the domain controller in vehicle positioning.

2. The vehicle positioning method according to claim 1, characterized in that: The target coordinates and the vehicle posture data are coupled to obtain coupled data, including: Acquiring communication configuration parameters between the simulation system and the domain controller; Converting the communication configuration parameters into a configuration file adapted to the simulation system; Based on the configuration file, the target coordinates and the vehicle posture data are formatted to obtain preset coordinates and preset vehicle posture data, wherein the preset coordinates are coordinates that conform to a data receiving format corresponding to the domain controller, and the preset vehicle posture data are vehicle posture data that conform to the data receiving format; The preset coordinates and the preset vehicle posture data are integrated to obtain the coupling data.

3. The vehicle positioning method according to claim 2, characterized in that: The target coordinates and the vehicle posture data are formatted based on the configuration file to obtain preset coordinates and preset vehicle posture data, including: Importing the configuration file into the simulation system, and generating a communication interface between the simulation system and the domain controller based on the configuration file; Based on the communication interface, the target coordinates and the vehicle posture data are mapped respectively to obtain the preset coordinates and the preset vehicle posture data.

4. The vehicle positioning method according to claim 1, characterized in that: The current coordinates are converted based on the projection mode of the target map to obtain the target coordinates, including: In response to the projection mode being a global positioning projection mode, converting the current coordinates based on a first coordinate system and a second coordinate system to obtain the target coordinates, wherein the global positioning projection mode is used to represent mapping the longitude and latitude coordinates on the surface of the earth into a plane coordinate system; In response to the projection mode being a local positioning projection mode, converting the current coordinates based on the second coordinate system to obtain the target coordinates, wherein the local positioning projection mode is used to indicate that the surface of the earth is projected into the plane coordinate system according to the longitude zone division; The second coordinate system is a coordinate system corresponding to a map used by the domain controller, and there is an encrypted offset between the first coordinate system and the second coordinate system, wherein the encrypted offset is used to indicate that a random offset is applied to the coordinates.

5. The vehicle positioning method according to claim 4, characterized in that: The current coordinates are converted based on the first coordinate system and the second coordinate system to obtain the target coordinates, including: Convert the current coordinates into the first coordinate system to obtain first coordinates in the first coordinate system; The first coordinates are converted into the second coordinate system based on the encrypted offset to obtain the target coordinates.

6. The vehicle positioning method according to claim 4, characterized in that: Converting the current coordinates into the first coordinate system to obtain first coordinates in the first coordinate system includes: Determine a first longitude value and a first latitude value of the current coordinates in the first coordinate system based on the earth's semi-major axis and an angle unit conversion parameter; The first coordinate is obtained based on the first longitude value and the first latitude value.

7. The vehicle positioning method according to claim 4, characterized in that: The step of converting the current coordinates based on the second coordinate system to obtain the target coordinates includes: Determine the zone where the current coordinates are currently located and the zone identifier corresponding to the zone, wherein the zone refers to a geographical zone area formed by projecting the earth's surface according to the longitude zone graduations onto the plane coordinate system; Determine an offset value of the band based on the band identifier; The current coordinates are converted to the second coordinate system based on the offset value to obtain the target coordinates.

8. The vehicle positioning method according to claim 7, characterized in that: The method further comprises: converting the current coordinates into the second coordinate system based on the offset value to obtain the target coordinates, comprising: Based on the offset value, the current coordinates are reset to zero to obtain relative coordinates relative to the central meridian and the equator, wherein the reset to zero is used to indicate that the offset value is subtracted from the current coordinates, and the central meridian is the central meridian corresponding to the zone; Converting the relative coordinates to a second latitude value based on the earth's semi-major axis and an angular unit conversion parameter; Determining a second longitude value based on the second latitude value and the central meridian; The target coordinates are determined based on the second latitude value and the second longitude value.

9. A vehicle positioning device, applied to a simulation system, characterized in that: include: An acquisition module, used to collect the current coordinates and vehicle posture data of the simulated vehicle on the target map during the process of controlling the simulated vehicle to run in the intelligent driving simulation scene; A conversion module, used for converting the current coordinates based on the projection mode of the target map to obtain target coordinates, wherein the target coordinates are coordinates corresponding to the coordinate type required by the domain controller; A coupling module is used to couple the target coordinates and the vehicle posture data to obtain coupling data, and send the coupling data to the domain controller, wherein the coupling data is used to assist the domain controller in vehicle positioning.

10. An electronic device, characterized in that: comprising a processor and a memory, wherein Memory, used to store computer programs; A processor, used to execute a program stored in a memory to implement the method described in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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