Map data processing method and device, electronic equipment and storage medium

Abstract

The invention provides a map data processing method and device, electronic equipment and a storage medium, and the method is applied to the field of vehicles, and comprises the steps: obtaining a plurality of pieces of map slice data of map simulation data transmitted by a server side and corresponding map identification information, the map simulation data is determined by the server side according to the position information of the target vehicle, and the map slice data is obtained by the server side through segmentation according to the geographic structure information of the map simulation data; the multiple pieces of map slice data are combined according to the map identification information to obtain recombined map data; extracting map feature data from the recombined map data according to a preset map attribute type; arranging the map feature data according to sequence feature data in the map feature data to obtain feature arrangement data; and sending the feature arrangement data to the target vehicle according to the communication protocol rule of the target vehicle. The method can solve the problem of insufficient performance in large-scale map simulation data processing and transmission.

Description

Technical Field

[0001] The present application relates to the field of vehicles, and more specifically, to a map data processing method, device, electronic device and storage medium in the field of vehicles. Background Art

[0002] At present, the map simulation data held by the map simulation is simulated based on a small segment of mileage, so the data volume is relatively small and contains fewer attribute points. A simulation environment of this scale can be easily loaded by the system at one time, and then traversed and recognized without encountering obvious performance bottlenecks. However, when faced with a significant increase in the mileage that needs to be simulated, or when the attribute points in the map become dense and complex, the amount of data that needs to be loaded and processed at one time in the simulation environment will increase significantly, which will directly lead to a sharp increase in system memory consumption, which may cause the system to run slowly, freeze, or even completely crash or freeze. Summary of the invention

[0003] The present application provides a map data processing method, device, electronic device and storage medium, which can solve the performance problem of insufficient processing and transmission of large-scale map simulation data.

[0004] In a first aspect, a map data processing method is provided, the method comprising: obtaining multiple map slice data of map simulation data transmitted by a server and map identification information corresponding to the map slice data, the map simulation data being determined by the server according to location information of a target vehicle, and the map slice data being obtained by segmenting the server according to geographic structure information of the map simulation data; combining the multiple map slice data to obtain reorganized map data according to the map identification information; extracting map feature data from the reorganized map data according to a preset map attribute type, the map attribute type being set according to functional requirements of the target vehicle; arranging the map feature data according to sequential feature data in the map feature data to obtain feature arrangement data; and sending the feature arrangement data to the target vehicle according to a communication protocol rule of the target vehicle.

[0005] By adopting the above technical scheme, the server side dynamically determines the map simulation data to be transmitted according to the location information of the target vehicle, and divides the map simulation data into multiple map slice data with small content according to the geographical structure information of the map simulation data, which can effectively reduce the amount of data transmitted at a single time; by reorganizing the multiple map slice data according to the map identification information based on the map slice data and map identification information transmitted by the server side, the integrity and accuracy of the map data are ensured; by setting the map attribute type according to the functional requirements of the target vehicle, and extracting the map feature data from the reorganized map data according to the map attribute type, the map data can be further refined and the complexity of data processing can be reduced; by arranging the feature arrangement data according to the sequential feature data in the map feature data to obtain the feature arrangement data, and transmitting the feature arrangement data according to the communication protocol rules of the target vehicle, it is helpful for the target vehicle to understand and process the map feature data more efficiently. By deploying map simulation data separately from the simulation environment, the large-scale map simulation data is divided into multiple smaller map slices through the server side, and the simulation side further extracts map feature data according to the preset map attribute type and arranges and sends the data, the memory consumption of the simulation environment is reduced, the data processing efficiency is accelerated, and performance problems such as system freezes and crashes caused by excessive data volume are avoided.

[0006] In combination with the first aspect, in some possible implementations, the multiple map slice data are combined according to the map identification information to obtain reorganized map data, including: establishing an associated data structure between the multiple map slice data according to the map identification information; and combining the multiple map slice data based on the associated data structure to obtain reorganized map data.

[0007] By adopting the above technical solution, by establishing an associated data structure between multiple map slice data according to map identification information, the relative position and association relationship between map slice data can be clearly defined, so that the data can be spliced ​​in the correct order and position during the data combination process.

[0008] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, before combining the multiple map slice data to obtain the reorganized map data according to the map identification information, it also includes: obtaining the input data requirement type, filtering the map slice data according to the data requirement type, and obtaining filtered map slice data; combining the multiple map slice data to obtain the reorganized map data according to the map identification information includes: combining the filtered map slice data to obtain the reorganized map data according to the map identification information marked by the filtered map slice data.

[0009] By adopting the above technical solution, by obtaining the input data requirement type and filtering the map slice data according to the data requirement type, this on-demand processing method can avoid loading and processing irrelevant or unnecessary map slice data, thereby improving the pertinence and efficiency of data processing.

[0010] In combination with the first aspect and the above-mentioned implementation manner, in some possible implementation manners, extracting map feature data from the reorganized map data according to a preset map attribute type includes: determining the map entity objects contained in the reorganized map data; and matching the map feature data associated with the map entity objects from the reorganized map data according to the preset map attribute type.

[0011] By adopting the above technical solution, by determining the map entity objects contained in the reorganized map data, it is possible to accurately match the associated map feature data for specific map entity objects, thereby further improving data processing efficiency.

[0012] In combination with the first aspect and the above-mentioned implementation manner, in some possible implementation manners, after extracting the map feature data from the reorganized map data according to the preset map attribute type, it also includes: standardizing the map feature data to obtain standard feature data; and performing data dimension reduction processing on the standard feature data corresponding to the target map attribute category according to the dimension reduction processing algorithm of the target map attribute category to obtain feature dimension reduction data.

[0013] By adopting the above technical solution, by standardizing the map feature data, the dimensional differences and numerical range differences between different data items can be eliminated; by performing data dimensionality reduction processing on the standard feature data corresponding to the target map attribute category, the dimension and complexity of the data can be significantly reduced while retaining key information, further reducing the cost of data storage and transmission.

[0014] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the map feature data are arranged according to the sequential feature data in the map feature data to obtain feature arrangement data, including: generating a state machine model based on a preset sequential feature type; inputting the map feature data into the state machine model in sequence, and using the state machine model to obtain the sequential feature data of the map feature data based on the preset sequential feature type; and using the state machine model to generate feature arrangement data of the map feature data according to the sequential feature data.

[0015] By adopting the above technical solution, by building a state machine model based on preset sequential feature types and using the state machine model to arrange map feature data, it is possible to automatically identify and extract sequential features in map feature data, and arrange the map feature data according to the sequential features, thereby greatly reducing the burden of manual intervention and improving the efficiency and accuracy of data processing.

[0016] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the feature arrangement data is sent to the target vehicle according to the communication protocol rules of the target vehicle, including: packaging the feature arrangement data according to the communication protocol rules of the target vehicle to obtain packaged data; establishing a communication connection with the target vehicle according to the communication protocol of the target vehicle, and sending the packaged data to the target vehicle.

[0017] By adopting the above technical solution, the characteristic arrangement data is packaged according to the communication protocol rules of the target vehicle, ensuring that the data meets the receiving standards of the target vehicle before sending. This standardized processing method avoids communication failures or data errors caused by data format mismatch and improves the accuracy and reliability of data transmission.

[0018] In a second aspect, a map data processing device is provided, the device comprising:

[0019] an acquisition unit, used for acquiring a plurality of map slice data of the map simulation data transmitted by the server and map identification information corresponding to the map slice data, wherein the map simulation data is determined by the server according to the location information of the target vehicle, and the map slice data is obtained by segmenting the server according to the geographic structure information of the map simulation data;

[0020] A recombining unit, configured to combine the plurality of map slice data to obtain recombined map data according to the map identification information;

[0021] an extraction unit, configured to extract map feature data from the reorganized map data according to a preset map attribute type, wherein the map attribute type is set according to a functional requirement of the target vehicle;

[0022] an arranging unit, configured to arrange the map feature data according to the sequential feature data in the map feature data to obtain feature arrangement data;

[0023] A sending unit is used to send the feature arrangement data to the target vehicle according to the communication protocol rule of the target vehicle.

[0024] In a third aspect, an electronic device is provided, which includes a memory for storing executable program code; and a processor for calling and running the executable program code from the memory, so that the electronic device executes the method in the above-mentioned first aspect or any possible implementation of the first aspect.

[0025] In a fourth aspect, a computer program product is provided, comprising: a computer program code, which, when executed on a computer, enables the computer to execute the method in the first aspect or any possible implementation of the first aspect.

[0026] In a fifth aspect, a computer-readable storage medium is provided, which stores a computer program code. When the computer program code runs on a computer, the computer executes the method in the above-mentioned first aspect or any possible implementation manner of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a system architecture diagram of a map data processing method provided in an embodiment of the present application;

[0028] Figure 2 It is a flowchart of a map data processing method provided in an embodiment of the present application;

[0029] Figure 3 It is a flowchart of a map data processing method provided in an embodiment of the present application;

[0030] Figure 4 It is a flowchart of a map data processing method provided in an embodiment of the present application;

[0031] Figure 5 is a structural schematic diagram of a map data processing device provided in an embodiment of the present application;

[0032] Figure 6 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] The technical solution in the present application will be described clearly and in detail below in conjunction with the accompanying drawings. In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

[0034] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0035] Please refer to Figure 1 , Figure 1 This is a system architecture diagram of a map data processing method provided by an embodiment of the present application, and the system at least includes a target vehicle, a server end, and a map data processing device. Among them, the server end is a device or system with data storage, data processing and service functions. The server end is used to receive the location information transmitted by the target vehicle; determine the map simulation data according to the location information; divide the map simulation data into multiple map slice data according to the geographical structure information of the map simulation data, and mark the corresponding map identification information for each of the multiple map slice data; and send the multiple map slice data and the corresponding map identification information to the map data processing device.

[0036] In the embodiment of the present application, the map data processing device is a device for processing the map slice data and map identification information transmitted by the server, also known as the simulation end; the map data processing device can be an electronic device such as a computer, a mobile phone, a server, etc.; it can also be a vehicle-mounted terminal of a vehicle, or a map data processing module in a vehicle terminal, etc. The map data processing device receives, parses, and processes the map slice data and map identification information transmitted by the server, and then generates map feature data that conforms to a specific format or protocol, and sends the map feature data to the vehicle-mounted controller of the target vehicle to support the realization of functions such as vehicle navigation, automatic driving, path planning, and environmental perception.

[0037] The present application embodiment takes the configuration of the map data processing device in an electronic device as an example. Figure 1As shown, after the target vehicle sends its own location information to the server, the server receives the location information of the target vehicle and determines the map simulation data according to the location information; according to the geographic structure information of the map simulation data, the map simulation data is divided into a plurality of map slice data, and the corresponding map identification information is marked for each of the plurality of map slice data; the plurality of map slice data and the corresponding map identification information are sent to a map data processing device. The map data processing device is used to obtain the plurality of map slice data transmitted by the server and the map identification information corresponding to the map slice data; according to the map identification information, the plurality of map slice data are combined to obtain reorganized map data; according to the preset map attribute type, map feature data is extracted from the reorganized map data, wherein the map attribute type is set according to the communication protocol rule of the target vehicle; according to the sequence feature data of the map feature data, the map feature data is arranged to obtain feature arrangement data; according to the communication protocol rule, the feature arrangement data is sent to the target vehicle.

[0038] The system in the embodiment of the present application can effectively reduce the amount of data transmitted at a single time by dynamically determining the map simulation data to be transmitted based on the location information of the target vehicle on the server side, and dividing the map simulation data into multiple map slice data with small content according to the geographical structure information of the map simulation data; and can ensure the integrity and accuracy of the map data by reorganizing the multiple map slice data according to the map identification information based on the map slice data and map identification information transmitted by the server side; and can further refine the map data and reduce the complexity of data processing by setting the map attribute type according to the functional requirements of the target vehicle and extracting the map feature data from the reorganized map data according to the map attribute type; and can obtain the feature arrangement data according to the sequential feature data in the map feature data, and transmit the feature arrangement data according to the communication protocol rules of the target vehicle, which helps the target vehicle to understand and process the map feature data more efficiently. By deploying map simulation data separately from the simulation environment, the large-scale map simulation data is divided into multiple smaller map slices through the server side, and the simulation side further extracts map feature data according to the preset map attribute type and arranges and sends the data, the memory consumption of the simulation environment is reduced, the data processing efficiency is accelerated, and performance problems such as system freezes and crashes caused by excessive data volume are avoided.

[0039] based on Figure 1 The system architecture shown below will be combined with Figure 2-Figure 4 , the map data processing method provided in the embodiment of the present application is introduced in detail.

[0040] See also Figure 2 , which is a flowchart of a map data processing method provided in an embodiment of the present application. Figure 2 As shown, the method of the embodiment of the present application may include the following steps S101-S105.

[0041] S101, obtaining a plurality of map slice data of map simulation data transmitted by a server and map identification information corresponding to the map slice data, wherein the map simulation data is determined by the server according to the location information of the target vehicle, and the map slice data is obtained by segmenting the server according to the geographic structure information of the map simulation data;

[0042] The method provided in the embodiment of the present application can be implemented by a computer program and can be run on a computer, mobile phone, server or other electronic device or a vehicle terminal. The embodiment of the present application takes the method applied to a computer or server or other electronic device as an example.

[0043] In some embodiments, when a server transmits a plurality of map slice data of map simulation data and map identification information corresponding to the map slice data to an electronic device, the plurality of map slice data and the corresponding map identification information are obtained through the electronic device. The server is a device or system with data storage, data processing and service functions, such as a cloud computing service platform, a big data storage server, a distributed computing cluster, a data warehouse and a data lake. The server is used to receive the location information transmitted by the target vehicle; determine the map simulation data according to the location information of the target vehicle; divide the map simulation data into a plurality of map slice data according to the geographic structure information of the map simulation data, mark the corresponding map identification information for each of the plurality of map slice data; and send the plurality of map slice data and the corresponding map identification information to the electronic device. Among them, the map simulation data is map data simulated or generated based on actual geographic spatial data, and may include but is not limited to various geographic element information such as terrain, roads, buildings, and water systems. The map slice data refers to the image blocks obtained by dividing the map simulation data according to the geographic structure information, and each image block contains a small part of the map information. The geographic structure information may be the road network structure and geographic coordinates of the map. Map identification information refers to information used to uniquely identify and distinguish map slice data, and may include but is not limited to identifiers of geographic features (such as terrain type, road number, building name, etc.), location coordinates (such as latitude and longitude coordinates, three-dimensional coordinates, plane rectangular coordinates based on the Transverse Mercator Projection UTM) and other descriptive information (such as attribute data, classification information, sorting labels, etc.).

[0044] In some embodiments, data is transmitted between the server side and the electronic device through a relay routing unit, which may be a router or data transmission device with a relay function. Specifically, the server side determines the map simulation data according to the location information of the target vehicle, and divides the map simulation data into a plurality of map slice data according to the geographical structure information of the map simulation data. After marking the corresponding map identification information for each of the plurality of map slice data, the server side sends the plurality of map slice data and the corresponding map identification information to the relay routing unit. After receiving the plurality of map slice data and the corresponding map identification information sent by the server side, the relay routing unit transmits the plurality of map slice data and the corresponding map identification information to the electronic device. The electronic device receives the plurality of map slice data and the corresponding map identification information from the relay routing unit.

[0045] S102, combining the plurality of map slice data to obtain reconstructed map data according to the map identification information;

[0046] In some embodiments, after acquiring multiple map slice data and map identification information corresponding to each map slice data, the electronic device recombines the multiple map slice data to obtain reorganized map data according to the map identification information corresponding to each map slice data, such as an identifier, location coordinates, sorting number or adjacent slice information.

[0047] In some embodiments, multiple map slice data are combined to obtain reorganized map data. For example, the association characteristics between each map slice data are determined based on the map identification information corresponding to each map slice data, and an association data structure between the multiple map slice data is established; based on the established association data structure, the multiple map slice data are combined to obtain the reorganized map data.

[0048] According to some embodiments, a plurality of map slice data are combined to obtain reorganized map data. For example, the electronic device first parses the map identification information corresponding to each map slice data to obtain the identification feature data contained in the map identification information. The identification feature data may include an identifier, a position coordinate, a sorting number, and adjacent slice information. Among them, the identifier can be used to represent the geographical elements contained in the map slice data, the position coordinate can be used to determine the specific position of the map slice data on the map, the sorting number can be used to identify the slice order or hierarchical relationship of the map slice data, and the adjacent slice information can be used to determine the map identification information of the adjacent map slice data. Different identification feature data correspond to different types of associated data structures. The type of associated data structure is determined according to the identification feature data obtained by parsing. The associated data structure may include types such as a two-dimensional array, a chain structure, a tree structure, or a graph structure. Based on the determined type of associated data structure and its structure establishment strategy, the association characteristics between the identification feature data corresponding to each map slice data are determined, and a corresponding associated data structure is established based on the association characteristics. The associated data structure is used to represent the associated data structure between multiple map slice data. For example, when the identification feature data contained in the map identification information is a sorting label, the type of associated data structure determined according to the sorting label is a chain structure; based on the structure establishment strategy of the chain structure, the label order of the sorting label corresponding to each map slice data is determined, and based on the label order, the sorting label corresponding to each map slice data is established into a corresponding chain structure, and the chain structure is used to represent the chain structure between multiple map slice data.

[0049] According to some embodiments, based on the established associative data structure between the plurality of map slice data, the adjacent map slice data of each map slice data is determined, and the map slice data and its adjacent map slice data are merged to obtain the reorganized map data.

[0050] In some embodiments, before combining multiple map slice data to obtain reorganized map data according to map identification information, a step of filtering the map slice data according to the data requirement type may also be included. Specifically, the input data requirement type is obtained, and the data requirement type refers to the user's selected requirement for a specific data type of the map slice data. The data requirement type may include but is not limited to types such as geographic area, map layer, and resolution requirements. The map tangent data is filtered according to the input data requirement type to obtain filtered map slice data. Thereafter, according to the map identification information marked by the filtered map slice data, the filtered map slice data is combined to obtain the reorganized map data.

[0051] According to some embodiments, the input data requirement type is obtained, and the map slice data is filtered according to the data requirement type. For example, the data requirement instruction input by the user is read, and the data requirement type is obtained according to the data requirement instruction. The data requirement type can be one or more of a geographical area, a map layer, and a resolution requirement. The map layer can include but is not limited to a road layer, a water system layer, a building layer, etc. The map slice data is filtered according to the determined data requirement type. For example, if the data requirement type is a geographical area, the map coordinate range is determined according to the input specific geographical area, and the map slice data corresponding to the map coordinate range is matched from the map slice data as the filtered map slice data; if the data requirement type is a map layer, the geographical element type is determined according to the input specific map layer, and the map slice data corresponding to the geographical element type is matched from the map slice data as the filtered map slice data; if the data requirement type is a resolution requirement, each map slice data is traversed and the pixel value of each map slice data is determined, and the pixel value of each map slice data is matched with the input specific resolution requirement, and the map slice data that meets the specific resolution requirement is used as the filtered map slice data.

[0052] S103, extracting map feature data from the reorganized map data according to a preset map attribute type, wherein the map attribute type is set according to a functional requirement of the target vehicle;

[0053] In some embodiments, the corresponding map attribute type is set in advance according to the functional requirements of the target vehicle, and the map attribute type refers to the map attribute that needs to be extracted based on the vehicle functional requirements. Among them, the vehicle functional requirements may include but are not limited to the navigation requirements of the vehicle, the decision requirements of the automatic driving or assisted driving system, and the vehicle's perception requirements of the environment. The map attribute type may include but is not limited to road type, intersection structure, traffic sign type, obstacle type and geographical location. The corresponding map attribute type is set according to the functional requirements of the target vehicle. For example, when the functional requirement of the target vehicle is the decision requirement of the automatic driving system, the map attribute type that needs to be extracted is determined to be road type, intersection structure, traffic sign type and lane information.

[0054] In some embodiments, a conditional screening mechanism is used to match the map attribute type with the attribute category of each data in the reorganized map data. When the attribute category of the reorganized map data matches the map attribute type, the reorganized map data corresponding to the matched attribute category is extracted as the map feature data corresponding to the map attribute type.

[0055] In some embodiments, map feature data is extracted from the reorganized map data according to a preset map attribute type. For example, the map entity objects contained in the reorganized map data are determined. The map entity objects refer to digital representations or models used to represent actual geographical elements on the map, such as roads, schools, hospitals, buildings, rivers, and parks. Optionally, the map entity object can be represented by a specific identifier (ID), name, string, or type tag. The map feature data associated with the map entity object is matched from the reorganized map data according to the preset map attribute type. Specifically, for each map entity object, the data associated with the map entity object is traversed from the reorganized map data, such as searching for corresponding data from the reorganized map data according to the ID, name, string, or type tag of the map entity object, matching the found data with the preset map attribute type, and extracting the map feature data matching the map attribute type.

[0056] In some embodiments, after extracting map feature data from the reorganized map data according to the preset map attribute type, a step of performing dimensionality reduction processing on the map feature data may also be included. Specifically, the map feature data is standardized to obtain standard feature data; and according to the dimensionality reduction processing algorithm of the target map attribute category, the standard feature data corresponding to the target map attribute category is subjected to data dimensionality reduction processing to obtain feature dimensionality reduction data.

[0057] According to some embodiments, the map feature data is standardized by calculating the mean and standard deviation of the map feature data to obtain standard feature data, so as to eliminate the differences in dimensions and sizes between different features. A target map attribute category is determined from preset map attribute types, and the target map attribute category can be one or more map attribute types in the map attribute type, or can be all map attribute types. According to the dimensionality reduction processing algorithms corresponding to different target map attribute categories, the standard feature data corresponding to the target map attribute category is subjected to data dimensionality reduction processing to obtain feature dimensionality reduction data. Among them, the dimensionality reduction processing algorithm can include but is not limited to one or more of principal component analysis (PCA), linear discriminant analysis (LDA), t-distributed stochastic neighbor embedding (t-SNE), and autoencoders.

[0058] S104, arranging the map feature data according to the sequential feature data in the map feature data to obtain feature arrangement data;

[0059] In some embodiments, the extracted map feature data is arranged according to the sequential feature data of each map feature data to obtain feature arrangement data. The sequential feature data is data used to represent the sequential attribute of the map feature data, and the sequential feature type may include but is not limited to geographic location coordinates, geographic location distance, timestamp or other sequential identifiers. For example, when the sequential feature type of the map feature data is determined to be geographic location distance, the geographic location distance values ​​of each map feature data are extracted, and according to the preset near to far sorting rule, the geographic location distance values ​​of each map feature data are arranged from near to far to obtain feature arrangement data.

[0060] Optionally, after performing dimensionality reduction processing on the map feature data to obtain feature dimensionality reduction data, the feature dimensionality reduction data is arranged according to the sequence feature data of each feature dimensionality reduction data to obtain feature arrangement data.

[0061] In some embodiments, sequential feature data of map feature data are arranged to obtain feature arrangement data. For example, a state machine model is generated based on a preset sequential feature type; the map feature data are sequentially input into the state machine model, and the sequential feature data of the map feature data is obtained based on the preset sequential feature type using the state machine model; and feature arrangement data of the map feature data is generated based on the sequential feature data using the state machine model.

[0062] According to some embodiments, a state machine model is a tool that describes how to respond to input and change states in different states. A corresponding state machine model is constructed based on a preset sequential feature type, and the state machine model defines a state transition rule based on the preset sequential feature type, and performs state transfer and output when the input map feature data meets the state transition rule. Specifically, the extracted multiple map feature data are sequentially input into the state machine model, and the state machine model is used to obtain the sequential feature data in the currently input map feature data based on the preset sequential feature type, and the sequential feature data in the currently input map feature data is compared with the feature arrangement data generated by the previous state to obtain the arrangement position of the currently input map feature data, and the currently input map feature data is added to the feature arrangement data generated by the previous state according to the arrangement position, and the feature arrangement data in the current state is updated. After all the input map feature data are arranged, feature arrangement data for multiple map feature data is generated.

[0063] S105: sending the feature arrangement data to the target vehicle according to the communication protocol rule of the target vehicle.

[0064] In some embodiments, for the generated feature arrangement data, the electronic device packages the feature arrangement data according to the communication protocol rules of the target vehicle to generate packaged data that meets the protocol communication requirements. Furthermore, the electronic device establishes a communication connection with the target vehicle according to the communication protocol of the target vehicle and sends the generated packaged data to the target vehicle.

[0065] According to some embodiments, the relevant communication protocol rules are determined according to the communication protocol of the target vehicle, and the communication protocol rules may include but are not limited to protocol specifications, data formats, transmission rates and timing requirements. The data structure of the feature arrangement data is determined, and a mapping relationship between the feature arrangement data and the protocol data field is established according to the protocol specifications and data structure. The feature arrangement data is mapped to the corresponding protocol data field based on the mapping relationship, and the data is formatted according to the data format requirements of the communication protocol. The mapped and formatted data are assembled to generate package data. According to the communication protocol of the target vehicle, a communication connection is established between the electronic device and the target vehicle, and the generated package data is sent to the target vehicle.

[0066] In some embodiments, the method of sending feature arrangement data to the target vehicle can also be, for example, to transmit data between the target vehicle and the electronic device through a relay routing unit. Specifically, the electronic device sends the feature arrangement data to the relay routing unit, which receives the feature arrangement data, packages the feature arrangement data according to the communication protocol rules of the target vehicle, and generates packaged data that meets the protocol communication requirements. Afterwards, the relay routing unit establishes a communication connection with the target vehicle according to the communication protocol of the target vehicle, and sends the generated packaged data to the target vehicle.

[0067] In some embodiments, the target vehicle receives the packaged data and parses the packaged data according to the communication protocol rules of the target vehicle to obtain parsed feature arrangement data; the feature arrangement data is processed according to the functional requirements of the target vehicle to support the realization of vehicle navigation, automatic driving, path planning, environmental perception and other functions.

[0068] In the embodiment of the present application, the server side dynamically determines the map simulation data that needs to be transmitted according to the location information of the target vehicle, and divides the map simulation data into multiple map slice data with small content according to the geographical structure information of the map simulation data, which can effectively reduce the amount of data transmitted at a single time; by reorganizing the multiple map slice data according to the map identification information based on the map slice data and map identification information transmitted by the server side, the integrity and accuracy of the map data are ensured; by setting the map attribute type according to the functional requirements of the target vehicle, and extracting the map feature data from the reorganized map data according to the map attribute type, the map data can be further refined and the complexity of data processing can be reduced; by arranging the feature arrangement data according to the sequential feature data in the map feature data to obtain the feature arrangement data, and transmitting the feature arrangement data according to the communication protocol rules of the target vehicle, it helps the target vehicle to understand and process the map feature data more efficiently. By deploying map simulation data separately from the simulation environment, the large-scale map simulation data is divided into multiple smaller map slices through the server side, and the simulation side further extracts map feature data according to the preset map attribute type and arranges and sends the data, the memory consumption of the simulation environment is reduced, the data processing efficiency is accelerated, and performance problems such as system freezes and crashes caused by excessive data volume are avoided.

[0069] See also Figure 3 , which is a flowchart of a map data processing method provided in an embodiment of the present application. Figure 3 As shown, the method of the embodiment of the present application may include the following steps S201-S213.

[0070] S201, obtaining a plurality of map slice data of map simulation data transmitted by a server and map identification information corresponding to the map slice data;

[0071] Specifically, the specific process of step S201 can be found in the description of step S101 in the above embodiment, which will not be repeated here.

[0072] S202, obtaining an input data requirement type, filtering the map slice data according to the data requirement type, and obtaining filtered map slice data;

[0073] In some embodiments, an input data requirement type is obtained, and the data requirement type refers to a user's selected requirement for a specific data type of map slice data. The data requirement type may include, but is not limited to, geographic area, map layer, and resolution requirements. The map tangent data is filtered according to the input data requirement type to obtain filtered map slice data.

[0074] According to some embodiments, the data requirement instruction input by the user is read, and the data requirement type is obtained according to the data requirement instruction. The data requirement type may be one or more of a geographic area, a map layer, and a resolution requirement. The map layer may include, but is not limited to, a road layer, a water system layer, a building layer, etc. The map slice data is filtered according to the determined data requirement type. For example, if the data requirement type is a geographic area, the map coordinate range is determined according to the input specific geographic area, and the map slice data corresponding to the map coordinate range is matched from the map slice data as the filtered map slice data; if the data requirement type is a map layer, the geographic element type is determined according to the input specific map layer, and the map slice data corresponding to the geographic element type is matched from the map slice data as the filtered map slice data; if the data requirement type is a resolution requirement, each map slice data is traversed and the pixel value of each map slice data is determined, and the pixel value of each map slice data is matched with the input specific resolution requirement, and the map slice data that meets the specific resolution requirement is used as the filtered map slice data.

[0075] In the embodiment of the present application, by obtaining the input data requirement type and filtering the map slice data according to the data requirement type, this on-demand processing method can avoid loading and processing irrelevant or unnecessary map slice data, thereby improving the pertinence and efficiency of data processing.

[0076] S203, establishing a correlation data structure between the plurality of map slice data according to the map identification information;

[0077] S204, combining the plurality of map slice data based on the associated data structure to obtain reorganized map data;

[0078] In some embodiments, the association characteristics between the map slice data are determined based on the map identification information corresponding to each map slice data, and an association data structure between multiple map slice data is established; based on the established association data structure, multiple map slice data are combined to obtain reorganized map data.

[0079] According to some embodiments, the electronic device first parses the map identification information corresponding to each map slice data to obtain the identification feature data contained in the map identification information. The identification feature data may include an identifier, a position coordinate, a sorting number, and adjacent slice information. Among them, the identifier can be used to represent the geographic elements contained in the map slice data, the position coordinate can be used to determine the specific position of the map slice data on the map, the sorting number can be used to identify the slice order or hierarchical relationship of the map slice data, and the adjacent slice information can be used to determine the map identification information of the adjacent map slice data.

[0080] According to some embodiments, different identification feature data correspond to different types of associated data structures. The type of associated data structure is determined based on the identification feature data obtained through analysis, and the associated data structure may include types such as a two-dimensional array, a chain structure, a tree structure, or a graph structure. Based on the determined type of associated data structure and its structure establishment strategy, the association characteristics between the identification feature data corresponding to each map slice data are determined, and a corresponding associated data structure is established based on the association characteristics. The associated data structure is used to represent the association data structure between multiple map slice data. For example, when the identification feature data contained in the map identification information is a sorting number, the type of associated data structure determined based on the sorting number is a chain structure; based on the structure establishment strategy of the chain structure, the order of the sorting numbers corresponding to each map slice data is determined, and a corresponding chain structure is established for the sorting numbers corresponding to each map slice data based on the order of the numbers. The chain structure is used to represent the chain structure between multiple map slice data.

[0081] According to some embodiments, based on the established associative data structure between the plurality of map slice data, the adjacent map slice data of each map slice data is determined, and the map slice data and its adjacent map slice data are merged to obtain the reorganized map data.

[0082] Optionally, an associated data structure is established between the plurality of filtered map slice data according to the map identification information; and the plurality of filtered map slice data are combined based on the associated data structure to obtain reorganized map data.

[0083] In some embodiments, the map identification information corresponding to each filtered map slice data is parsed to obtain the identification feature data contained in the map identification information. The type of associated data structure is determined based on the identification feature data obtained by the analysis, and the associated characteristics between the identification feature data corresponding to each filtered map slice data are determined based on the determined associated data structure type and its structure establishment strategy. Based on the associated characteristics, a corresponding associated data structure is established, and the associated data structure is used to represent the associated data structure between multiple filtered map slice data. Based on the established associated data structure between multiple filtered map slice data, the adjacent map slice data of each filtered map slice data is determined, and the filtered map slice data and its adjacent map slice data are merged to obtain reorganized map data.

[0084] In the embodiment of the present application, by establishing an associated data structure between multiple map slice data according to map identification information, the relative position and association relationship between the map slice data can be clearly defined, so that the data can be spliced ​​in the correct order and position during the data combination process.

[0085] S205, determining the map entity objects included in the reorganized map data;

[0086] S206, matching the map feature data associated with the map entity object from the reorganized map data according to a preset map attribute type;

[0087] In some embodiments, the map entity objects contained in the reorganized map data are determined, and the map entity objects refer to digital representations or models used to represent actual geographical elements on the map, such as roads, schools, hospitals, buildings, rivers and parks. Optionally, the map entity object can be represented by a specific identifier (ID), a name, a string or a type tag. The map feature data associated with the map entity object is matched from the reorganized map data according to a preset map attribute type, and the map attribute type refers to the map attribute that needs to be extracted based on the vehicle functional requirements. Among them, the vehicle functional requirements may include but are not limited to the navigation requirements of the vehicle, the decision requirements of the automatic driving or assisted driving system, and the vehicle's perception requirements of the environment. The map attribute type may include but is not limited to the road type, intersection structure, traffic sign type, obstacle type and geographical location. The corresponding map attribute type is set according to the functional requirements of the target vehicle. For example, when the functional requirements of the target vehicle are the decision requirements of the automatic driving system, the map attribute type to be extracted is determined to be the road type, intersection structure, traffic sign type and lane information.

[0088] According to some embodiments, a conditional screening mechanism is adopted, and for each map entity object, data associated with the map entity object is traversed from the reorganized map data, such as searching for corresponding data from the reorganized map data according to the ID, name, string or type tag of the map entity object, matching the found data with a preset map attribute type, and extracting map feature data matching the map attribute type.

[0089] In the embodiment of the present application, by determining the map entity objects included in the reorganized map data, it is possible to accurately match the associated map feature data for the specific map entity objects, thereby further improving the data processing efficiency.

[0090] S207, performing standardization processing on the map feature data to obtain standard feature data;

[0091] S208, performing data dimensionality reduction processing on the standard feature data corresponding to the target map attribute category according to the dimensionality reduction processing algorithm of the target map attribute category to obtain feature dimensionality reduction data;

[0092] In some embodiments, the map feature data is standardized by calculating the mean and standard deviation of the map feature data to obtain standard feature data, so as to eliminate the differences in dimensions and sizes between different features. The target map attribute category is determined from the preset map attribute types, and the target map attribute category can be one or more map attribute types in the map attribute type, or can be all map attribute types. According to the dimensionality reduction processing algorithms corresponding to different target map attribute categories, the standard feature data corresponding to the target map attribute category is subjected to data dimensionality reduction processing to obtain feature dimensionality reduction data. Among them, the dimensionality reduction processing algorithm can include but is not limited to one or more of principal component analysis (PCA), linear discriminant analysis (LDA), t-distributed stochastic neighbor embedding (t-SNE), and autoencoders.

[0093] In the embodiment of the present application, by standardizing the map feature data, the dimensional differences and numerical range differences between different data items can be eliminated; by performing data dimensionality reduction processing on the standard feature data corresponding to the target map attribute category, the dimension and complexity of the data can be significantly reduced while retaining key information, further reducing the cost of data storage and transmission.

[0094] S209, generating a state machine model based on a preset sequential feature type;

[0095] S210, inputting the map feature data into the state machine model in sequence, and using the state machine model to obtain sequential feature data of the map feature data based on a preset sequential feature type;

[0096] S211, using the state machine model to generate feature arrangement data of the map feature data according to the sequential feature data;

[0097] In some embodiments, a corresponding state machine model is constructed based on a preset sequential feature type, and the state machine model defines a state transition rule based on the preset sequential feature type, and performs state transfer and output when the input map feature data meets the state transition rule. Specifically, the extracted multiple map feature data are sequentially input into the state machine model, and the state machine model is used to obtain the sequential feature data in the currently input map feature data based on the preset sequential feature type, and the sequential feature data in the currently input map feature data is compared with the feature arrangement data generated by the previous state to obtain the arrangement position of the currently input map feature data, and the currently input map feature data is added to the feature arrangement data generated by the previous state according to the arrangement position, and the feature arrangement data in the current state is updated. After all the input map feature data are arranged, feature arrangement data for multiple map feature data is generated.

[0098] Optionally, the feature dimension reduction data is sequentially input into the state machine model, and the state machine model is used to obtain sequential feature data of the feature dimension reduction data based on a preset sequential feature type; the state machine model is used to generate feature arrangement data of the feature dimension reduction data according to the sequential feature data.

[0099] In some embodiments, after performing dimensionality reduction processing on map feature data to obtain feature dimensionality reduction data, the processed multiple feature dimensionality reduction data are sequentially input into the state machine model, and the state machine model is used to obtain sequential feature data in the currently input feature dimensionality reduction data based on a preset sequential feature type, and the sequential feature data in the currently input feature dimensionality reduction data is compared with the feature arrangement data generated by the previous state to obtain the arrangement position of the currently input feature dimensionality reduction data, and the currently input feature dimensionality reduction data is added to the feature arrangement data generated by the previous state according to the arrangement position, and the feature arrangement data in the current state is updated. After all the input feature dimensionality reduction data are arranged, feature arrangement data for multiple feature dimensionality reduction data are generated.

[0100] The embodiment of the present application constructs a state machine model based on a preset sequential feature type and arranges map feature data using the state machine model. It is therefore possible to automatically identify and extract sequential features in map feature data and arrange the map feature data according to the sequential features, thereby greatly reducing the burden of manual intervention and improving the efficiency and accuracy of data processing.

[0101] S212, packaging the characteristic arrangement data according to the communication protocol rule of the target vehicle to obtain packaged data;

[0102] S213, establishing a communication connection with the target vehicle according to the communication protocol of the target vehicle, and sending the packaged data to the target vehicle.

[0103] Specifically, for the specific process of steps S212-S213, please refer to the description of step S105 in the above embodiment, which will not be repeated here.

[0104] In the embodiment of the present application, the characteristic arrangement data is packaged according to the communication protocol rules of the target vehicle, ensuring that the data meets the receiving standard of the target vehicle before sending. This standardized processing method avoids communication failure or data error caused by data format mismatch and improves the accuracy and reliability of data transmission.

[0105] See also Figure 4 , which is a flowchart of a map data processing method according to an embodiment of the present application. The present application embodiment takes the method being applied to a server end and an electronic device (i.e., a simulation end) as an example. The method according to the embodiment of the present application may include the following steps S301 to S313.

[0106] S301, when the target vehicle sends the location information of the target vehicle, the server receives the location information transmitted by the target vehicle, and determines the map simulation data according to the location information;

[0107] S302, using the server side to divide the map simulation data into a plurality of map slice data according to the geographic structure information of the map simulation data, and marking the corresponding map identification information for each of the plurality of map slice data;

[0108] S303, using the server to send multiple map slice data and corresponding map identification information to the relay routing unit;

[0109] In some embodiments, when the target vehicle sends the location information of the target vehicle, the server side is used to receive the location information transmitted by the target vehicle; the map simulation data is determined according to the location information of the target vehicle; according to the geographic structure information of the map simulation data, the map simulation data is divided into a plurality of map slice data, and the corresponding map identification information is respectively marked for the plurality of map slice data; the plurality of map slice data and the corresponding map identification information are sent to the relay routing unit. Among them, the map simulation data is map data simulated or generated based on the actual geographic spatial data, and may include but not limited to terrain, roads, buildings, water systems and other geographic element information. The map slice data refers to the image blocks obtained after the map simulation data is divided according to the geographic structure information, and each image block contains a small part of the map information. The geographic structure information may be the road network structure and geographic coordinates of the map. The map identification information refers to the information used to uniquely identify and distinguish the map slice data, and may include but not limited to the identifier of the geographic element (such as terrain type, road number, building name, etc.), the location coordinates (such as latitude and longitude coordinates, three-dimensional coordinates, plane rectangular coordinates based on the transverse Mercator projection UTM) and other descriptive information (such as attribute data, classification information, sorting number, etc.).

[0110] S304, using a relay routing unit to transmit a plurality of map slice data and corresponding map identification information to a simulation end;

[0111] In some embodiments, a relay routing unit is used to receive multiple map slice data and corresponding map identification information sent from the server end, and transmit the multiple map slice data and corresponding map identification information to the simulation end.

[0112] S305, using the simulation end to obtain multiple map slice data and corresponding map identification information transmitted by the relay routing unit;

[0113] In some embodiments, a simulation end is used to receive a plurality of map slice data and corresponding map identification information transmitted from a relay routing unit.

[0114] S306, using the simulation end to obtain the input data requirement type, filtering the map slice data according to the data requirement type, and obtaining the filtered map slice data;

[0115] In some embodiments, the simulation end is used to obtain the input data requirement type, which refers to the user's selected requirement for a specific data type of map slice data. The data requirement type may include but is not limited to geographic area, map layer, and resolution requirements. The map tangent data is filtered according to the input data requirement type to obtain the filtered map slice data.

[0116] According to some embodiments, the simulation end is used to read the data requirement instruction input by the user, and the data requirement type is obtained according to the data requirement instruction. The data requirement type can be one or more of a geographical area, a map layer, and a resolution requirement. The map layer can include but is not limited to a road layer, a water system layer, a building layer, etc. The map slice data is filtered according to the determined data requirement type. For example, if the data requirement type is a geographical area, the map coordinate range is determined according to the input specific geographical area, and the map slice data corresponding to the map coordinate range is matched from the map slice data as the filtered map slice data; if the data requirement type is a map layer, the geographical element type is determined according to the input specific map layer, and the map slice data corresponding to the geographical element type is matched from the map slice data as the filtered map slice data; if the data requirement type is a resolution requirement, each map slice data is traversed and the pixel value of each map slice data is determined, and the pixel value of each map slice data is matched with the input specific resolution requirement, and the map slice data that meets the specific resolution requirement is used as the filtered map slice data.

[0117] S307, using the simulation end to establish a correlation data structure between the plurality of filtered map slice data according to the map identification information; combining the plurality of filtered map slice data based on the correlation data structure to obtain recombined map data;

[0118] In some embodiments, the map identification information corresponding to each filtered map slice data is parsed by a simulation end to obtain identification feature data contained in the map identification information. The type of associated data structure is determined based on the identification feature data obtained by the analysis, and the associated characteristics between the identification feature data corresponding to each filtered map slice data are determined based on the determined associated data structure type and its structure establishment strategy. Based on the associated characteristics, a corresponding associated data structure is established, and the associated data structure is used to represent the associated data structure between multiple filtered map slice data. Based on the established associated data structure between multiple filtered map slice data, the adjacent map slice data of each filtered map slice data is determined, and the filtered map slice data and its adjacent map slice data are merged to obtain reorganized map data.

[0119] S308, extracting map feature data from the reorganized map data according to a preset map attribute type using the simulation end;

[0120] In some embodiments, the simulation end is used to determine the map entity objects contained in the reorganized map data. The map entity object refers to a digital representation or model used to represent actual geographical elements on the map, such as roads, schools, hospitals, buildings, rivers and parks. Optionally, the map entity object can be represented by a specific identifier (ID), name, string or type tag. The map feature data associated with the map entity object is matched from the reorganized map data according to the preset map attribute type. The map attribute type refers to the map attribute that needs to be extracted based on the vehicle functional requirements. Among them, the vehicle functional requirements may include but are not limited to the navigation requirements of the vehicle, the decision requirements of the automatic driving or assisted driving system, and the vehicle's perception requirements of the environment. The map attribute type may include but is not limited to the road type, intersection structure, traffic sign type, obstacle type and geographical location. The corresponding map attribute type is set according to the functional requirements of the target vehicle. For example, when the functional requirements of the target vehicle are the decision requirements of the automatic driving system, the map attribute type to be extracted is determined to be the road type, intersection structure, traffic sign type and lane information.

[0121] According to some embodiments, a conditional screening mechanism is adopted, and for each map entity object, data associated with the map entity object is traversed from the reorganized map data, such as searching for corresponding data from the reorganized map data according to the ID, name, string or type tag of the map entity object, matching the found data with a preset map attribute type, and extracting map feature data matching the map attribute type.

[0122] S309, using the simulation end to perform standardization processing on the map feature data to obtain standard feature data; according to the dimension reduction processing algorithm of the target map attribute category, perform data dimension reduction processing on the standard feature data corresponding to the target map attribute category to obtain feature dimension reduction data;

[0123] In some embodiments, the simulation end is used to calculate the mean and standard deviation of the map feature data to standardize the map feature data to obtain standard feature data, so as to eliminate the differences in dimensions and sizes between different features. The target map attribute category is determined from the preset map attribute types, and the target map attribute category can be one or more map attribute types in the map attribute type, or can be all map attribute types. According to the dimensionality reduction processing algorithms corresponding to different target map attribute categories, the standard feature data corresponding to the target map attribute category is subjected to data dimensionality reduction processing to obtain feature dimensionality reduction data. Among them, the dimensionality reduction processing algorithm can include but is not limited to one or more of principal component analysis (PCA), linear discriminant analysis (LDA), t-distributed stochastic neighbor embedding (t-SNE), and autoencoders.

[0124] S310, using the simulation end to generate a state machine model based on a preset sequential feature type; inputting the feature dimension reduction data into the state machine model in sequence, and using the state machine model to obtain sequential feature data of the feature dimension reduction data based on a preset sequential feature type; using the state machine model to generate feature arrangement data of the feature dimension reduction data according to the sequential feature data.

[0125] In some embodiments, a simulation end is used to construct a corresponding state machine model based on a preset sequential feature type. The state machine model defines a state transition rule based on the preset sequential feature type, and performs state transfer and output when the input map feature data meets the state transition rule. Specifically, the extracted multiple map feature data are sequentially input into the state machine model, and the state machine model is used to obtain the sequential feature data in the currently input map feature data based on the preset sequential feature type, and the sequential feature data in the currently input map feature data is compared with the feature arrangement data generated by the previous state to obtain the arrangement position of the currently input map feature data. According to the arrangement position, the currently input map feature data is added to the feature arrangement data generated by the previous state, and the feature arrangement data in the current state is updated. After all the input map feature data are arranged, feature arrangement data for multiple map feature data is generated.

[0126] S311, using the simulation end to establish a communication connection between the simulation end and the data relay routing unit, and sending the feature arrangement data to the relay routing unit;

[0127] S312, using a relay routing unit to package the characteristic arrangement data according to a communication protocol rule to obtain packaged data;

[0128] S313, using the relay routing unit to establish a communication connection with the target vehicle according to the communication protocol of the target vehicle, and sending the packaged data to the on-board controller of the target vehicle.

[0129] In some embodiments, a simulation end is used to establish a communication connection between the simulation end and a data relay routing unit, and the feature arrangement data is sent to the relay routing unit. The feature arrangement data is received by the relay routing unit, and the feature arrangement data is packaged according to the communication protocol rules of the target vehicle to generate packaged data that meets the protocol communication requirements. Afterwards, the relay routing unit is used to establish a communication connection with the target vehicle according to the communication protocol of the target vehicle, and the generated packaged data is sent to the target vehicle.

[0130] Afterwards, the target vehicle receives the package data sent by the relay routing unit, and the vehicle controller of the target vehicle parses the package data according to the communication protocol rules of the target vehicle to obtain the parsed feature arrangement data; the feature arrangement data is processed according to the functional requirements of the target vehicle to support the realization of functions such as vehicle navigation, automatic driving, path planning, and environmental perception.

[0131] In the embodiment of the present application, by deploying map simulation data and simulation environment separately, the server side divides the large-scale map simulation data into multiple smaller map slice data, and the simulation side further extracts map feature data according to preset map attribute types and arranges and sends the data, thereby reducing the memory consumption of the simulation environment, speeding up data processing efficiency, and avoiding system freezes, crashes and other performance problems caused by excessive data volume. By using a relay routing unit to transmit data between the server side and the electronic device, and by using the relay routing unit to transmit data between the target vehicle and the electronic device, the data transmission efficiency is further improved.

[0132] based on Figure 1 The system architecture will be combined with the attached Figure 5 , the device provided in the embodiment of the present application is described in detail. It should be noted that the attached Figure 5 The device in the present application is used to execute Figure 1-Figure 4 For the convenience of explanation, only the part related to the embodiment of the present application is shown. For the specific technical details not disclosed, please refer to the present application. Figure 1-Figure 4 The embodiment shown.

[0133] See also Figure 5, which shows a schematic diagram of the structure of the device provided by the exemplary embodiment of this specification. The device can be implemented as all or part of the device through software, hardware or a combination of both. The device 1 at least includes an acquisition unit 10, a reorganization unit 20, an extraction unit 30, an arrangement unit 40 and a sending unit 50.

[0134] An acquisition unit 10 is used to acquire a plurality of map slice data of map simulation data transmitted by a server and map identification information corresponding to the map slice data, wherein the map simulation data is determined by the server according to the location information of the target vehicle, and the map slice data is obtained by segmenting the server according to the geographic structure information of the map simulation data;

[0135] A recombining unit 20, configured to combine the plurality of map slice data to obtain recombined map data according to the map identification information;

[0136] An extraction unit 30, configured to extract map feature data from the reorganized map data according to a preset map attribute type, wherein the map attribute type is set according to a functional requirement of the target vehicle;

[0137] an arranging unit 40, configured to arrange the map feature data according to the sequential feature data in the map feature data to obtain feature arrangement data;

[0138] The sending unit 50 is used to send the feature arrangement data to the target vehicle according to the communication protocol rule of the target vehicle.

[0139] According to some embodiments, the reorganization unit 20 may include a structure building subunit 201 and a data combining subunit 202, wherein the reorganization unit 20 is configured to combine the plurality of map slice data to obtain reorganized map data according to the map identification information:

[0140] A structure establishing subunit 201 is used to establish an associated data structure between the plurality of map slice data according to the map identification information;

[0141] The data combining subunit 202 is used to combine the plurality of map slice data based on the associated data structure to obtain reorganized map data.

[0142] According to some embodiments, the apparatus 1 may further include a filtering unit 60, wherein before the recombining unit 20 is configured to combine the plurality of map slice data to obtain the recombined map data according to the map identification information:

[0143] A filtering unit 60, configured to obtain an input data requirement type, filter the map slice data according to the data requirement type, and obtain filtered map slice data;

[0144] The recombining unit 20 is further used to combine the filtered map slice data to obtain recombined map data according to the map identification information marked by the filtered map slice data.

[0145] According to some embodiments, the extraction unit 30 may include an object determination subunit 301 and a data matching subunit 302, wherein the extraction unit 30 is configured to extract map feature data from the reorganized map data according to a preset map attribute type:

[0146] The object determination subunit 301 is used to determine the map entity objects included in the reorganized map data;

[0147] The data matching subunit 302 is used to match the map feature data associated with the map entity object from the reorganized map data according to a preset map attribute type.

[0148] According to some embodiments, the apparatus 1 may further include a dimensionality reduction unit 70, wherein after the extraction unit 30 is configured to extract the map feature data from the reorganized map data according to a preset map attribute type:

[0149] The dimension reduction unit 70 is used to perform standardization processing on the map feature data to obtain standard feature data; according to the dimension reduction processing algorithm of the target map attribute category, perform data dimension reduction processing on the standard feature data corresponding to the target map attribute category to obtain feature dimension reduction data.

[0150] According to some embodiments, the arrangement unit 40 may include a model generation subunit 401, a data input subunit 402 and a data arrangement subunit 403, wherein the arrangement unit 40 is used to arrange the map feature data according to the sequential feature data in the map feature data to obtain the feature arrangement data:

[0151] The model generation subunit 401 is used to generate a state machine model based on a preset sequential feature type;

[0152] A data input subunit 402, used to sequentially input the map feature data into the state machine model, and use the state machine model to obtain sequential feature data of the map feature data based on a preset sequential feature type;

[0153] The data arrangement subunit 403 is used to generate feature arrangement data of the map feature data according to the sequential feature data using the state machine model.

[0154] According to some embodiments, the sending unit 50 may include a data packaging subunit 501 and a data sending subunit 502, wherein the sending unit 50 is used to send the feature arrangement data to the target vehicle according to the communication protocol rule of the target vehicle:

[0155] The data packaging subunit 501 is used to package the characteristic arrangement data according to the communication protocol rule of the target vehicle to obtain packaged data;

[0156] The data sending subunit 502 is used to establish a communication connection with the target vehicle according to the communication protocol of the target vehicle, and send the packaged data to the target vehicle.

[0157] In the embodiment of the present application, the server side dynamically determines the map simulation data to be transmitted according to the location information of the target vehicle, and divides the map simulation data into multiple map slice data with small content according to the geographical structure information of the map simulation data, which can effectively reduce the amount of data transmitted at a single time; by reorganizing the multiple map slice data according to the map identification information based on the map slice data and map identification information transmitted by the server side, the integrity and accuracy of the map data are ensured; by setting the map attribute type according to the functional requirements of the target vehicle, and extracting the map feature data from the reorganized map data according to the map attribute type, the map data can be further refined and the complexity of data processing can be reduced; by arranging the feature arrangement data according to the sequential feature data in the map feature data to obtain the feature arrangement data, and transmitting the feature arrangement data according to the communication protocol rules of the target vehicle, it helps the target vehicle to understand and process the map feature data more efficiently. By deploying map simulation data separately from the simulation environment, the large-scale map simulation data is divided into multiple smaller map slices through the server side, and the simulation side further extracts map feature data according to the preset map attribute type and arranges and sends the data, the memory consumption of the simulation environment is reduced, the data processing efficiency is accelerated, and performance problems such as system freezes and crashes caused by excessive data volume are avoided.

[0158] See also Figure 6 , which is a schematic diagram of the structure of a vehicle provided in the embodiment of the present application. Figure 6 As shown, the vehicle 500 includes a processor 501 and a memory 502. The processor 501 is electrically connected to the memory 502.

[0159] The processor 501 is the control center of the electronic device 500 and may include one or more processing cores. The processor 501 uses various interfaces and lines to connect various parts of the entire electronic device, and executes various functions of the electronic device and processes data by running or calling computer programs stored in the memory 502, and calling data stored in the memory 502, so as to control the electronic device as a whole. Optionally, the processor 501 can be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 501 can integrate one or a combination of CPU, graphics processing unit (GPU), modem, etc. Among them, the CPU mainly processes the operating system, user pages, and applications; the GPU is responsible for rendering and drawing display content; and the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 501, but may be implemented separately through a communication chip.

[0160] The memory 502 can be used to store software programs and modules, and the processor 501 executes various functional applications and data processing by running the computer programs and modules stored in the memory 502. The memory 502 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, a computer program required for at least one function, etc.; the data storage area can store data created according to the use of the electronic device, etc.

[0161] In addition, the memory 502 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage device. Accordingly, the memory 502 may also include a memory controller to provide the processor 501 with access to the memory 502.

[0162] In this embodiment, the processor 501 in the electronic device 500 also loads instructions corresponding to the processes of one or more computer programs into the memory 502 according to the following steps, and the processor 501 runs the computer program stored in the memory 502 to implement various functions, as follows:

[0163] Acquire multiple map slice data of map simulation data transmitted by the server and map identification information corresponding to the map slice data, wherein the map simulation data is determined by the server according to the location information of the target vehicle, and the map slice data is obtained by segmenting the server according to the geographic structure information of the map simulation data;

[0164] Combining the plurality of map slice data to obtain reconstructed map data according to the map identification information;

[0165] extracting map feature data from the reorganized map data according to a preset map attribute type, wherein the map attribute type is set according to a functional requirement of the target vehicle;

[0166] Arranging the map feature data according to the sequential feature data in the map feature data to obtain feature arrangement data;

[0167] The feature arrangement data is sent to the target vehicle according to the communication protocol rules of the target vehicle.

[0168] Optionally, when the processor 501 combines the plurality of map slice data to obtain reconstructed map data according to the map identification information, the processor 501 specifically performs:

[0169] Establishing a correlation data structure between the plurality of map slice data according to the map identification information;

[0170] The plurality of map slice data are combined based on the associated data structure to obtain reorganized map data.

[0171] Optionally, before combining the plurality of map slice data to obtain reconstructed map data according to the map identification information, the processor 501 may further execute:

[0172] Obtaining an input data requirement type, filtering the map slice data according to the data requirement type, and obtaining filtered map slice data;

[0173] When the processor 501 combines the plurality of map slice data to obtain reconstructed map data according to the map identification information, the processor 501 specifically executes:

[0174] According to the map identification information marked by the filtered map slice data, the filtered map slice data are combined to obtain recombined map data.

[0175] Optionally, when the processor 501 extracts the map feature data from the reorganized map data according to the preset map attribute type, it specifically performs:

[0176] Determining the map entity objects included in the reorganized map data;

[0177] The map feature data associated with the map entity object is matched from the reorganized map data according to a preset map attribute type.

[0178] Optionally, after extracting map feature data from the reorganized map data according to a preset map attribute type, the processor 501 may further execute:

[0179] Performing standardization processing on the map feature data to obtain standard feature data;

[0180] According to the dimension reduction processing algorithm of the target map attribute category, data dimension reduction processing is performed on the standard feature data corresponding to the target map attribute category to obtain feature dimension reduction data.

[0181] Optionally, when the processor 501 arranges the map feature data according to the sequential feature data in the map feature data to obtain feature arrangement data, the processor 501 specifically executes:

[0182] Generate a state machine model based on a preset sequential feature type;

[0183] Inputting the map feature data into the state machine model in sequence, and using the state machine model to obtain sequential feature data of the map feature data based on a preset sequential feature type;

[0184] The state machine model is used to generate feature arrangement data of the map feature data according to the sequential feature data.

[0185] Optionally, when the processor 501 sends the feature arrangement data to the target vehicle according to the communication protocol rule of the target vehicle, it specifically executes:

[0186] Packaging the characteristic arrangement data according to the communication protocol rule of the target vehicle to obtain packaged data;

[0187] A communication connection is established with the target vehicle according to the communication protocol of the target vehicle, and the packaged data is sent to the target vehicle.

[0188] It should be understood that the device provided in the embodiment of the present application is used to execute the above-mentioned map data processing method, and thus can achieve the same effect as the above-mentioned implementation method.

[0189] In the case of an integrated unit, the device may include a processing module and a storage module. When the device is applied to a vehicle, the processing module may be used to control and manage the actions of the vehicle. The storage module may be used to support the vehicle in executing relevant program codes, etc.

[0190] The processing module may be a processor or a controller, which may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc. The storage module may be a memory.

[0191] In addition, the device provided in the embodiment of the present application may specifically be a chip, a component or a module, and the chip may include a connected processor and a memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute a map data processing method provided in the above embodiment.

[0192] An embodiment of the present application also provides a computer-readable storage medium, in which a computer program code is stored. When the computer program code is executed on a computer, the computer executes the above-mentioned related method steps to implement a map data processing method provided in the above-mentioned embodiment.

[0193] This embodiment further provides a computer program product. When the computer program product is run on a computer, the computer is enabled to execute the above-mentioned related steps to implement a map data processing method provided by the above-mentioned embodiment.

[0194] Among them, the device, computer-readable storage medium, computer program product or chip provided in this embodiment is used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method provided above, and will not be repeated here.

[0195] Through the description of the above implementation methods, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0196] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0197] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A map data processing method, characterized in that: The method comprises: Acquire multiple map slice data of map simulation data transmitted by the server and map identification information corresponding to the map slice data, wherein the map simulation data is determined by the server according to the location information of the target vehicle, and the map slice data is obtained by segmenting the server according to the geographic structure information of the map simulation data; Combining the plurality of map slice data to obtain reconstructed map data according to the map identification information; extracting map feature data from the reorganized map data according to a preset map attribute type, wherein the map attribute type is set according to a functional requirement of the target vehicle; Arranging the map feature data according to the sequential feature data in the map feature data to obtain feature arrangement data; The feature arrangement data is sent to the target vehicle according to the communication protocol rules of the target vehicle.

2. The method according to claim 1, characterized in that Combining the plurality of map slice data to obtain reorganized map data according to the map identification information includes: Establishing a correlation data structure between the plurality of map slice data according to the map identification information; The plurality of map slice data are combined based on the associated data structure to obtain reorganized map data.

3. The method according to any one of claims 1 to 2, characterized in that: Before combining the plurality of map slice data to obtain reorganized map data according to the map identification information, the method further includes: Obtaining an input data requirement type, filtering the map slice data according to the data requirement type, and obtaining filtered map slice data; Combining the plurality of map slice data to obtain reorganized map data according to the map identification information includes: According to the map identification information marked by the filtered map slice data, the filtered map slice data are combined to obtain recombined map data.

4. The method according to claim 1, characterized in that: The extracting of map feature data from the reorganized map data according to a preset map attribute type includes: Determining the map entity objects included in the reorganized map data; The map feature data associated with the map entity object is matched from the reorganized map data according to a preset map attribute type.

5. The method according to claim 1, characterized in that After extracting map feature data from the reorganized map data according to the preset map attribute type, the method further includes: Performing standardization processing on the map feature data to obtain standard feature data; According to the dimension reduction processing algorithm of the target map attribute category, data dimension reduction processing is performed on the standard feature data corresponding to the target map attribute category to obtain feature dimension reduction data.

6. The method according to claim 1, characterized in that Arranging the map feature data according to the sequential feature data in the map feature data to obtain feature arrangement data includes: Generate a state machine model based on a preset sequential feature type; Inputting the map feature data into the state machine model in sequence, and using the state machine model to obtain sequential feature data of the map feature data based on a preset sequential feature type; The state machine model is used to generate feature arrangement data of the map feature data according to the sequential feature data.

7. The method according to claim 1, characterized in that The step of sending the feature arrangement data to the target vehicle according to the communication protocol rule of the target vehicle comprises: Packaging the characteristic arrangement data according to the communication protocol rule of the target vehicle to obtain packaged data; A communication connection is established with the target vehicle according to the communication protocol of the target vehicle, and the packaged data is sent to the target vehicle.

8. A map data processing device, characterized in that: The device comprises: an acquisition unit, used for acquiring a plurality of map slice data of the map simulation data transmitted by the server and map identification information corresponding to the map slice data, wherein the map simulation data is determined by the server according to the location information of the target vehicle, and the map slice data is obtained by segmenting the server according to the geographic structure information of the map simulation data; A recombining unit, configured to combine the plurality of map slice data to obtain recombined map data according to the map identification information; an extraction unit, configured to extract map feature data from the reorganized map data according to a preset map attribute type, wherein the map attribute type is set according to a functional requirement of the target vehicle; an arranging unit, configured to arrange the map feature data according to the sequential feature data in the map feature data to obtain feature arrangement data; A sending unit is used to send the feature arrangement data to the target vehicle according to the communication protocol rule of the target vehicle.

9. An electronic device, characterized in that: The electronic device comprises: A memory for storing executable program codes; A processor, configured to call and run the executable program code from the memory, so that the vehicle executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed, the method according to any one of claims 1 to 7 is implemented.

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