High-performance geographic information middleware system suitable for electric vehicle intelligent system

Abstract

The invention discloses a high-performance geographic information middleware system suitable for an electric vehicle intelligent system. The system comprises an online geographic data caching and topological database, a geographic data service network analysis and back-end service module and a time sequence data processing suite, a data topology analysis module, a data query coding module and an advanced geographic query module are arranged in the online geographic data cache and topologic database; a software tool for developing an electric vehicle intelligent system is provided, so that a standardized urban road information topology database is constructed, and high-performance data query and advanced geographic query implementation are provided. And constructing a rear-end API (Application Program Interface) for geographic database service, reading and cleaning time sequence and geographic mixed data of the electric vehicle, and realizing a data structuring tool. The method can effectively support deployment optimization of service nodes oriented to electric vehicle big data and personalized recommendation algorithm research work for users.

Description

Technical Field

[0001] The invention belongs to the technical field of electric vehicle management system software, and in particular is a high-performance geographic information middleware system suitable for electric vehicle intelligent systems. Background Art

[0002] As a representative of new energy vehicles, smart electric vehicles are environmentally friendly, technologically advanced, and convenient, and are gradually becoming the mainstream choice for future travel. With the continuous progress in battery technology, autonomous driving technology, and charging facilities, smart electric vehicles will become more mature and popular. In the future, smart electric vehicles are expected to achieve fully autonomous driving and become an important tool for people to travel. At the same time, smart electric vehicles will also be deeply integrated with energy, transportation, information and other fields, injecting new impetus into my country's economic development. With the development of automobile electrification, intelligence and the Internet of Things, electric vehicle users will generate massive amounts of operating data every day, among which charging and discharging and driving trajectory data have high potential value. Through this type of data, the deployment optimization of development service nodes and personalized recommendation algorithms for users have attracted the attention of more and more researchers.

[0003] However, the huge amount of relevant data and the complexity of algorithm development have limited the research on various large-scale scenarios. The limited use of commercial geographic information service data and the low reliability of network requests have restricted the implementation of advanced geographic queries during algorithm development. Summary of the invention

[0004] The purpose of the present invention is to provide a high-performance geographic information middleware system suitable for an electric vehicle intelligent system in order to solve the above-mentioned problems.

[0005] The technical solution adopted by the present invention is as follows: a high-performance geographic information middleware system suitable for an electric vehicle intelligent system, the system comprising: an online geographic data cache and topological database, a geographic data service network parsing and back-end service module, and a time series data processing suite;

[0006] The internal configuration of the online geographic data cache and topological database includes: a data topology parsing module, a data query encoding module, and an advanced geographic query module, which are respectively used for geographic data topological processing, advanced query and geographic coding, integrated algorithm functions and optimized query;

[0007] The geographic data service network parsing and backend service module includes: HTTP request advanced encapsulation, geographic data extraction and parsing, and a coroutine-based asynchronous execution framework, which implements asynchronous network requests, data cleaning, and multi-task execution framework.

[0008] The time series data processing suite includes: file indexing and parsing tools, asynchronous database request framework, preprocessing and advanced query, which are used for time series data processing and key information screening.

[0009] In a preferred embodiment, the data topology parsing module performs structural topological processing on the imported geographic data and splits the road geographic information into nodes and edges. The road data table, as a top-level index table, is an abstract implementation of the road. It only stores the top-level information of the road, such as name, type, etc., and the node index array composed of the road, and does not store specific geographic information. The association between the edge and the parent road is realized through the road index value stored in the edge. The edge consists of two index values ​​and a cost weight, and the corresponding node can be retrieved through the index value. Through the split edges and nodes, a directed graph structure data based on the road geometry data is constructed to support the deployment and implementation of various graph algorithms.

[0010] In a preferred embodiment, the data query encoding module implements some advanced query functions and geocoding in the database to reduce the computational cost of the user end. The main functions include: path rendering based on index sequence. When a query request for a group of nodes is initiated, the node index value contained in the query is matched with the database node table, and the Well-Known Binary (WKB) data of the queried node is encoded as a WKB polyline and returned to achieve fast path geometry rendering. Dynamic data update and defect correction. Based on the back-end request, the relevant nodes of the index are automatically updated and searched with reference to the path table, missing node geographic information data is added, and the latest geographic correction is synchronized.

[0011] In a preferred embodiment, the advanced geographic query module defines a series of query functions in the database, integrates some algorithm functions originally processed by the backend into the database, simplifies the backend development and improves performance. Typical functions include: high-performance path routing, directly implementing path-finding algorithms such as the Dijkstra algorithm in the database, returning the node index sequence obtained by routing, and realizing rapid evaluation of the connectivity of different nodes. Geographic query optimization, by building an index tree based on geographic information, realizes rapid query based on geographic constraint information.

[0012] In a preferred embodiment, the HTTP request advanced encapsulation implements an asynchronous implementation framework for HTTP requests, and quickly defines an asynchronous network request function by defining only the request payload through a decorator. Based on this framework, a data request encapsulation for the open source geographic database OpenStreetMap is defined, which supports initiating network queries through a single function call.

[0013] In a preferred embodiment, the geographic data extraction and parsing realizes automatic cleaning and standardized reconstruction of geographic data based on the incoming network response content and regular expressions, and realizes a unified data processing framework to ensure that the data obtained based on network requests can simply and correctly generate valid data required by the load database.

[0014] In a preferred embodiment, the asynchronous execution framework based on coroutines, network requests and database queries are both IO-intensive tasks, and the asynchronous code implemented based on coroutines can well optimize the program running performance. A unified asynchronous multi-task execution framework is built for network requests and database queries, and the asynchronous functions are automatically encapsulated and the task pool is generated through simple task and parameter list definitions. Real-time monitoring of multi-task execution and unified log generation are achieved.

[0015] In a preferred embodiment, the time series data file indexing and parsing tool is compatible with mainstream text files and compressed files, and provides a decorator implementation for parsing compatible type files into byte streams. It supports the rapid design of reading functions to convert raw data into a form compatible with database structures. It implements rapid available file search based on regular expressions, and provides a decorator implementation for repeatability verification with the target database content, meeting the requirements of large amounts of raw data parsing tasks.

[0016] In a preferred embodiment, the asynchronous database request framework provides an asynchronous implementation of database processing functions for time series data. The asynchronous data processing function is constructed under the condition of defining only limited SQL statements, providing a simple implementation of paging upload and query of large batches of data.

[0017] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0018] In the present invention, a software tool for developing an intelligent system for electric vehicles is provided to build a standardized urban road information topology database and provide high-performance data query and advanced geographic query implementation. A back-end API implementation for geographic database services is built to implement tools for reading, cleaning, and structuring data for electric vehicle time series and geographic hybrid data. The present invention can effectively support the deployment optimization of service nodes for electric vehicle big data and the research work on personalized recommendation algorithms for users. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is the overall architecture diagram of the present invention;

[0020] Figure 2 The present invention is an asynchronous execution framework flow chart;

[0021] Figure 3 It is the ER diagram of the geographic database of the present invention;

[0022] Figure 4 It is a flow chart of time-space domain data processing of the present invention;

[0023] Figure 5 A flowchart for implementing the advanced road indexing application of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0025] Reference Figures 1 to 5 ,

[0026] Example:

[0027] A high-performance geographic information middleware system suitable for electric vehicle intelligent systems. The system includes: online geographic data cache and topological database, geographic data service network analysis and back-end service modules, and time series data processing suite;

[0028] The internal settings of the online geographic data cache and topology database include: data topology analysis module, data query encoding module, and advanced geographic query module, which are used for geographic data topology processing, advanced query and geographic coding, integrated algorithm function and optimized query respectively;

[0029] The geographic data service network parsing and backend service modules include: HTTP request advanced encapsulation, geographic data extraction and parsing, and a coroutine-based asynchronous execution framework. Asynchronous network requests, data cleaning, and multi-task execution frameworks are implemented.

[0030] The time series data processing suite includes: file indexing and parsing tools, asynchronous database request framework, preprocessing and advanced query, which are used for time series data processing and key information screening.

[0031] The data topology parsing module performs structural topological processing on the imported geographic data and splits the road geographic information into nodes and edges. The road data table, as a top-level index table, is an abstract implementation of roads. It only stores top-level information of roads such as name, type, etc., as well as the node index array composed of roads, and does not store specific geographic information. The association between the edge and the parent road is realized through the road index value stored in the edge. The edge consists of two index values ​​and cost weights, and the corresponding node can be retrieved through the index value. Through the split edges and nodes, a directed graph structure data based on road geometry data is constructed to support the deployment and implementation of various graph algorithms.

[0032] The data query encoding module implements some advanced query functions and geocoding in the database to reduce the computational cost on the user side. The main functions include: path rendering based on index sequence. When a query request is initiated for a group of nodes, the node index value contained in the query is matched with the database node table, and the Well-KnownBinary (WKB) data of the queried node is encoded as a WKB polyline and returned to achieve fast path geometry rendering. Dynamic data update and defect correction. Based on the back-end request, the path table is referenced to automatically update and search the relevant nodes of the index, add the missing node geographic information data, and synchronize the latest geographic correction.

[0033] The advanced geographic query module defines a series of query functions inside the database, integrates some algorithm functions originally processed by the backend into the database, simplifies backend development and improves performance. Typical functions include: high-performance path routing, directly implementing path-finding algorithms such as the Dijkstra algorithm inside the database, returning the node index sequence obtained by routing, and realizing rapid evaluation of the connectivity of different nodes. Geographic query optimization, by building an index tree based on geographic information, realizes rapid query based on geographic constraint information.

[0034] HTTP request high-level encapsulation implements the asynchronous implementation framework of HTTP request. It uses decorators to quickly define an asynchronous network request function when only the request payload is defined. Based on this framework, data request encapsulation for the open source geographic database OpenStreetMap is defined, which supports initiating network queries through a single function call.

[0035] Geographic data extraction and parsing, based on the incoming network response content and regular expressions, realize automatic cleaning and standardized reconstruction of geographic data. A unified data processing framework is implemented to ensure that the data obtained based on network requests can simply and correctly generate valid data required by the load database.

[0036] Asynchronous execution framework based on coroutines. Network requests and database queries are both IO-intensive tasks. Asynchronous code implemented based on coroutines can optimize program performance. A unified asynchronous multi-task execution framework is built for network requests and database queries. Through simple task and parameter list definitions, asynchronous functions are automatically encapsulated and task pools are generated. Real-time monitoring of multi-task execution and unified log generation are achieved.

[0037] Time series data file indexing and parsing tool, compatible with mainstream text files and compressed files, provides decorator implementation for parsing compatible type files into byte streams. Supports fast design of reading functions to convert raw data into a form compatible with database structures. Based on regular expressions, it realizes fast available file search and provides decorator implementation for duplication verification with target database content to meet the needs of parsing tasks for large amounts of raw data.

[0038] The asynchronous database request framework provides an asynchronous implementation of database processing functions for time series data. It builds asynchronous data processing functions under the condition of defining only limited SQL statements, and provides a simple implementation of paging upload and query of large batches of data.

[0039] Time series data preprocessing and advanced time series query can realize the cleaning of raw data and reconstruction based on time series, and support fast data indexing based on time domain definition in the back end. According to the characteristics of electric vehicle data, it provides key point extraction and other functions to realize the preliminary screening of key information.

[0040] The overall structure of the middleware software is based on the pip package built in Python language and is divided into 4 main modules: utils, extension, scraper, and spatiotime. Utils provides advanced encapsulation of database connections to achieve fast connections based on configuration files. At the same time, it defines a general reading scheme for data files, which provides further data parsing implementation interfaces as decorators. Scraper defines data acquisition implementations for OpenStreetMap and PeMS, including automatically building a data queue to be queried based on the incoming city name, putting it into the asynchronous execution framework TranMQ for asynchronous concurrent requests, and comparing and synchronizing with the database after data parsing. It provides data compatibility implementation for the query interface defined by Overpassapi, and converts network query data based on the database table structure. It provides an automated download tool for PeMS to achieve concurrent downloading of a large number of files, as well as data reading, cleaning, and database uploading of downloaded files. Extension defines important extensions for asynchronous implementation, and implements the asynchronous queue framework TranMQ and TranMQ's extension SQLLoader for database operations. SQLLoader maintains a TranMQ instance and automatically builds a paging concurrent execution implementation for the database specified query method, which greatly alleviates the memory pressure caused by large batches of data and improves query efficiency. timescla defines the database.

[0041] The call implementation of the defined advanced query method can realize tasks such as obtaining the shortest path based on road geographic data and obtaining time series data within a specified time period through related functions.

[0042] Figure 2 For asynchronous execution of the framework flow chart, the framework execution steps are as follows:

[0043] 1. Initialize the class object and determine whether the incoming task function is an asynchronous function. If it is not an asynchronous function, convert it to an asynchronous function by opening a thread encapsulation

[0044] 2. Based on the passed function parameter list, combined with the task function, create a task list and initialize the task pool

[0045] 3. Start the task queue and maintain an event loop. Check the task callback in each loop. If a task callback is generated, generate a task report and exit the task. Check whether there is a new task in the task pool. If so, add the new task to the task queue to start the task. When the task queue is empty or the user interrupt is detected, close the task pool, combine the reports of all tasks, generate the final report and product results, and end.

[0046] Figure 3 This is the ER diagram of the geographic database. The structure of the database is as follows:

[0047] 1. The point table is an entity representing a node, containing a unique index primary key, node type, road node type description, and point geometry data using the 4326 spatial reference system.

[0048] 2. The road table is an entity representing roads. id: the unique identifier of the road, used as the primary key. type: a description of the type of road, such as expressway, city road, etc. nodes: an array that stores the IDs of the nodes that make up the road. highway: a classification of roads, such as main roads, secondary roads, etc. lanes: a description of the number of lanes on the road. name: the name of the road. weight: a search weight used for road routing, with a default value of 1.0.

[0049] 3. The edge table is an entity representing the edge. source and target: vertex IDs representing the starting and ending points of the edge, respectively, form a composite primary key. This establishes a relationship with the points table, indicating the two vertices connected by the edge. road_id: establishes a relationship with the roads table, indicating the road to which the edge belongs. weight: the weight of the edge, the default value is 1.0.

[0050] 4. The vertex table is an entity representing vertices and is a direct extension of points. id: The unique identifier of the vertex, as the primary key, has a one-to-one mapping relationship with points. cnt: Degree, the sum of out-degree and in-degree. in_degree: In-degree, indicating the number of edges pointing to the vertex. out_degree: Out-degree, indicating the number of edges emanating from the vertex.

[0051] Figure 4 This is a flow chart of time-space domain data processing, and the main implementation steps are:

[0052] 1. Regularly read vehicle data and convert longitude and latitude text into numerical values ​​to meet standardized geographic workflows.

[0053] 2. Read road topology data and build an association mapping between vehicle operation data and geographic topology structure.

[0054] 3. Build a database connection pool instance to synchronously transmit the extracted operation data and topological road data to the database.

[0055] 4. Establish a grid mapping table, map the running data in segments according to time and space, compress the mapping space, and improve the query indexing speed.

[0056] Figure 5 Implement a flowchart for the advanced road indexing application. The implementation process is:

[0057] 1. Obtain open source road geography data through asynchronous processing framework and general network application tools

[0058] 2. Through geometric relationship index construction, nodes are discovered and intersections are disconnected for continuous roads to construct graph-structured road topology data.

[0059] 3. Topological road data is extended by building database applications to implement shortest path search algorithms such as Djikstra.

[0060] 4. Back-end service layer, which implements the calling of database extension functions and the expansion of back-end functions.

[0061] From the above we can know:

[0062] In the present invention, a software tool for developing an intelligent system for electric vehicles is provided to build a standardized urban road information topology database and provide high-performance data query and advanced geographic query implementation. A back-end API implementation for geographic database services is built to implement tools for reading, cleaning, and structuring data for electric vehicle time series and geographic hybrid data. The present invention can effectively support the deployment optimization of service nodes for electric vehicle big data and the research work on personalized recommendation algorithms for users.

[0063] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprises" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0064] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A high-performance geographic information middleware system suitable for electric vehicle intelligent systems, characterized by: The system includes: online geographic data cache and topological database, geographic data service network analysis and back-end service module and time series data processing suite; The internal configuration of the online geographic data cache and topological database includes: a data topology parsing module, a data query coding module, and an advanced geographic query module, which are respectively used for geographic data topological processing, advanced query and geographic coding, integrated algorithm function and optimized query; The geographic data service network parsing and back-end service module includes: HTTP request advanced encapsulation, geographic data extraction and parsing, and a coroutine-based asynchronous execution framework; implementing an asynchronous network request, data cleaning, and multi-task execution framework; The time series data processing suite includes: file indexing and parsing tools, asynchronous database request framework, preprocessing and advanced query, which are used for time series data processing and key information screening.

2. The high-performance geographic information middleware system suitable for electric vehicle intelligent system as claimed in claim 1, characterized in that: The data topology analysis module performs structural topology processing on the imported geographic data and splits the road geographic information into nodes and edges; The road data table is a top-level index table and an abstract implementation of roads. It only stores top-level information about roads, including name, type, and node index arrays of roads, but does not store specific geographic information. The road index values ​​stored in the edges are used to associate the edges with parent roads. The edges consist of two index values ​​and a cost weight, and the corresponding nodes can be retrieved through the index values. Through the split edges and nodes, directed graph structure data based on road geometry data is constructed to support the deployment and implementation of various graph algorithms.

3. The high-performance geographic information middleware system suitable for electric vehicle intelligent system as claimed in claim 1, characterized in that: The data query coding module implements some advanced query functions and geocoding in the database, reducing the computational cost on the user side; The main functions include: path rendering based on index sequence. When a query request is initiated for a group of nodes, the node index value contained in the query is matched with the database node table, and the Well-KnownBinary data of the queried node is encoded as a WKB polyline and returned to achieve fast path geometry rendering; dynamic data update and defect correction. Based on the back-end request, the relevant nodes of the index are automatically updated and searched with reference to the path table, missing node geographic information data is added, and the latest geographic correction is synchronized.

4. The high-performance geographic information middleware system suitable for electric vehicle intelligent system as claimed in claim 1, characterized in that: The advanced geographic query module defines a series of query functions inside the database, integrates some algorithm functions originally processed by the backend into the database, simplifies backend development and improves performance; typical functions include: high-performance path routing, directly implementing the Dijkstra algorithm pathfinding algorithm inside the database, returning the node index sequence obtained by routing, and realizing rapid evaluation of the connectivity of different nodes; geographic query optimization, by building an index tree based on geographic information, realizing rapid query based on geographic constraint information, including querying nodes within a certain rectangular range.

5. The high-performance geographic information middleware system suitable for electric vehicle intelligent system as claimed in claim 1, characterized in that: The HTTP request advanced encapsulation implements an asynchronous implementation framework for HTTP requests, and quickly defines an asynchronous network request function by means of decorators when only the request payload is defined; based on the framework, a data request encapsulation for the open source geographic database OpenStreetMap is defined, which supports initiating network queries through a single function call.

6. The high-performance geographic information middleware system suitable for electric vehicle intelligent system as claimed in claim 1, characterized in that: The geographic data extraction and analysis realizes automatic cleaning and standardized reconstruction of geographic data based on the incoming network response content and regular expressions; realizes a unified data processing framework to ensure that the data obtained based on the network request can simply and correctly generate valid data required by the load database.

7. The high-performance geographic information middleware system suitable for electric vehicle intelligent system as claimed in claim 1, characterized in that: The coroutine-based asynchronous execution framework, network requests and database queries are both IO-intensive tasks, and the asynchronous code implemented based on coroutines can well optimize the program running performance; a unified asynchronous multi-task execution framework is built for network requests and database queries, and through simple task and parameter list definitions, asynchronous functions are automatically encapsulated and task pools are generated; Realize real-time monitoring of multi-task execution and unified log generation.

8. The high-performance geographic information middleware system suitable for electric vehicle intelligent system as claimed in claim 1, characterized in that: The time series data file indexing and parsing tool is compatible with mainstream text files and compressed files, and provides a decorator implementation for parsing compatible type files into byte streams; it supports the rapid design of reading functions and converts raw data into a form compatible with database structures; It implements fast available file search based on regular expressions and provides a decorator implementation for duplication verification with the target database content to meet the needs of parsing tasks for large amounts of raw data.

9. The high-performance geographic information middleware system suitable for electric vehicle intelligent system as claimed in claim 1, characterized in that: The asynchronous database request framework provides an asynchronous implementation of database processing functions for time series data; it builds asynchronous data processing functions under the condition of defining only limited SQL statements, and provides a simple implementation of paging upload and query of large batches of data.

10. The high-performance geographic information middleware system suitable for electric vehicle intelligent system according to claim 1, characterized in that: The time series data preprocessing and advanced time series query realize the cleaning of raw data and reconstruction based on time series, and support the fast data indexing based on time domain definition at the back end; according to the characteristics of electric vehicle data, a key point extraction function is provided to realize the preliminary screening of key information.

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