Method and device for evaluating radiation accessibility of subway station under influence of bus transfer

Abstract

The invention discloses a subway station radiation reachability evaluation method and device under the influence of bus transfer. The method comprises the following steps: acquiring multi-source heterogeneous traffic data, including subways, bus line networks, subway stations, entrance and exit points, bus station data, residential areas and associated attributes; performing geographic space data standardization processing, unifying a coordinate system, extracting geometric center coordinates of each element, and standardizing attribute table field naming; a public traffic map database is constructed, and a multi-dimensional topological relation network including subway station-entrance and exit connection, transfer station association, bus route connection and station-residential area coverage is established through a node relation matching algorithm; defining a multi-level radiation element path, and querying and calculating the total number of households which can reach the residential area through different transfer levels of each subway station based on the graph database; and generating a visual analysis chart, and displaying the radiation capacity distribution characteristics of each station according to the rail transit line. According to the invention, the influence of the public transport station on the urban space structure can be accurately evaluated.

Description

Technical Field

[0001] The present invention relates to a subway station radiation accessibility evaluation technology from the perspective of a public transportation map database, and specifically relates to a subway station radiation accessibility evaluation method and device that comprehensively consider bus line transfer connections. Background Art

[0002] The evaluation of the radiation accessibility of subway stations is an important research content in the fields of urban planning and traffic engineering, which involves how to quantitatively analyze the geographical scope that a subway station can serve within a certain period of time and its impact on the surrounding areas. Related technologies include Geographic Information System (GIS), traffic network analysis, multi-criteria decision-making, etc.

[0003] GIS is a computer system used for capturing, storing, analyzing, and presenting geospatial data. It allows users to collect, analyze, and visualize various geospatial data and is widely used in urban planning and management, geoscience research and applications, etc. In the spatial analysis stage, GIS provides a rich set of tools to perform various analysis tasks. For example, to evaluate the influence range of subway stations, many studies use the "Buffer" tool to create a buffer zone with a fixed distance (such as 800 meters) for each subway station and calculate indicators such as the population and employment opportunities in the affected area, as shown in the literature "Bivina G R, Gupta A, Parida M. Walk accessibility to metro stations: An analysis based on meso-ormicro-scale built environment factors[J]. Sustainable Cities and Society, 2020, 55:102047." and "Guo Peng, Chen Xiaoling. Algorithm for the passenger flow radiation area of urban rail transit stations based on GIS[J]. China Railway Science, 2007, (06):128-132.". In addition, GIS can also be used to construct a traffic network model, calculate the time cost from a subway station to different destinations, and then evaluate the interaction intensity in the cumulative opportunity or gravity model or for spatio-temporal accessibility analysis. GIS combines the time and space dimensions to simulate the changes in accessibility under actual travel conditions, as in "Zhang Gaowei, Qian Linbo. Measurement and evaluation of the accessibility of urban rail transit stations based on GIS and web map services - Taking Nanjing as an example[J]. Logistics Sci-Tech, 2022, 45(11):99-103. DOI:10.13714 / j.cnki.1002-3100.2022.11.022.". This can be achieved by creating a complex network structure containing time and space information, using GIS or Depthmap software to perform in-depth processing on the convex space, and the integration is used as an accessibility evaluation indicator, as in "Guo Qian, Wu Dianting, Li Rui, et al. Research on the evaluation method of the accessibility of urban rail transit networks - Taking the Beijing rail transit network as an example[J]. Urban Development Studies, 2014, 21(04):59-65.". In terms of result display, the powerful mapping function of GIS enables us to visually present the distribution of the radiation accessibility of subway stations. Whether it is a static map or a dynamic animation, it can effectively convey the research findings and help urban planners make decisions.

[0004] GPS technology is mainly used to provide accurate location information, especially when on-site measurement or verification is required. In the assessment of the radiation accessibility of subway stations, GPS devices can help us obtain the accurate location coordinates of the stations, ensuring that the data input into the GIS has high precision. In addition, if mobile surveys or crowd flow tracking are involved, GPS can also be used to record the travel paths of individuals, providing empirical data support for the model.

[0005] However, most of the existing subway station accessibility analysis technologies adopt single-scale or single-mode analysis, mainly focusing on the walking accessibility around subway stations, lacking an overall description of the multi-level transfer network. Although the existing methods have involved rail and bus transfers, they often fail to effectively quantify the convenience and radiation effects of transfer paths and cannot comprehensively evaluate the accessibility structure of subway stations. In particular, in a multi-mode travel environment, how to accurately depict the accessibility characteristics of subway stations by combining hierarchical analysis and the radiation characteristics of meta-paths remains a shortcoming of the current technology. Summary of the Invention

[0006] Object of the Invention: Aiming at the deficiencies of the existing technology, the present invention proposes a method and device for evaluating the radiation accessibility of subway stations under the influence of bus transfers, comprehensively considering the influence of bus stops and lines, and realizing simple and efficient evaluation of the accessibility of subway stations.

[0007] Technical Solution: In the first aspect, the present invention provides a method for evaluating the radiation accessibility of subway stations under the influence of bus transfers, including the following steps:

[0008] Step S1: Obtain multi-source heterogeneous geospatial data, including linear vector data of urban subway networks and bus road networks, point vector data of subway stations, subway station entrances and exits, and bus stops, residential area polygon vector data, and the number of households in the community attribute data; the linear data contains the topological connection relationships of subway lines and bus lines, the point data contains geographic coordinate information, and the residential area polygon data contains geometric center coordinates and the number of households in the community attribute.

[0009] Step S2: Perform standardization processing on the geospatial data, unify the coordinate system, extract the geometric center coordinates of each element, standardize the field names of the attribute table, and add a "type" field to label the element type. The processed data is exported as a structured file.

[0010] Step S3: Merge the exported structured files to generate a global node table, assign a unique global ID, retain the original attribute fields and the "type" label, and the node type is defined by the "type" field; and establish the topological relationship between nodes to generate a relationship edge table, and form a public transportation map database based on the node table and the relationship edge table.

[0011] Step S4: define a path pattern extending from the subway station through the subway station entrance and exit, multi-level bus stations to the residential area, construct a multi-level radial element path, and perform a graph query to obtain the total number of households in the residential area that can be reached by each subway station through different transfer levels;

[0012] Step S5: Generate a visual analysis chart to display the distribution characteristics of the radiation capacity of each station according to the rail transit line.

[0013] Furthermore, the step S2 comprises:

[0014] S2.1: Import the data obtained in step S1 into the ArcGIS platform, convert them into the WGS84 geographic coordinate system, extract the longitude and latitude coordinates of subway stations, bus stops, and subway station entrances and exits as X and Y attributes, calculate the geometric center coordinates of the residential area surface data and assign X and Y attributes;

[0015] S2.2: Standardize data attribute fields, unify the name fields of each layer as "name", name the number of households in the residential area as "XQHS", and add the "type" field to mark the feature type; export the processed data as a structured CSV file.

[0016] Furthermore, in step S3, the relationship edge types include affiliation, spatial proximity, and line sequence connection; establishing a topological relationship between nodes includes:

[0017] Based on the name matching algorithm, the subway station and its entrance and exit are associated to generate the "subway station_subway station entrance and exit" relationship edge;

[0018] Based on the line connection order table, the affiliation edges between subway stations and subway lines, and between bus stations and bus lines are constructed;

[0019] Using ArcGIS spatial analysis tools, the subway station entrances and exits are matched with bus stations within an 800-meter radius, and the residential areas are matched with a 300-meter radius, generating "subway station entrance and exit_bus station" and "bus station_residential area" spatial proximity relationship edges;

[0020] Generate sequential connection edges between adjacent subway stations and bus stops based on the line connection sequence table, and mark the lines they belong to.

[0021] Furthermore, in step S4, the multi-level radiation element path is defined as:

[0022] p0: subway station → subway entrance and exit → residential area;

[0023] p n :Subway station → subway entrance → (bus station × n) → residential area, n∈[1,4];

[0024] Traverse the graph database through the Cypher query language to count the total number of households in the residential areas connected to the end of each meta-path.

[0025] Furthermore, the query statement includes path depth control, same-line constraints, and result aggregation logic.

[0026] Furthermore, in the query statement, the query expansion range is limited by adjusting n, the query hierarchy of bus stops is restricted by using MATCH...WHERE, and the COLLECT(DISTINCT) and REDUCE functions are combined to deduplicate residential areas and accumulate the number of households.

[0027] Furthermore, the visual analysis in step S5 includes:

[0028] Split the query results by subway line to generate a dataset of the radiation capabilities of stations on each line;

[0029] Use matplotlib to draw a multi-line line chart. The horizontal axis is the names of subway stations arranged in line order, the vertical axis is the number of affected households under different meta-paths, the path levels are distinguished by colors, and transfer stations are marked with vertical dotted lines;

[0030] Generate a spatial heat map, overlay the range of residential areas affected by subway stations, bus lines, and different path levels, and reflect the difference in household density through a color scale.

[0031] The method models the composite subway-bus-residential area network, quantifies the radiation capabilities of stations under multi-transfer scenarios, identifies weak areas in public transportation coverage, and provides data support for network optimization.

[0032] In a second aspect, there is provided an evaluation device for the radiation reachability of subway stations under the influence of bus transfers, including:

[0033] A data acquisition module for acquiring multi-source heterogeneous geospatial data, including linear vector data of urban subway networks and bus road networks, point vector data of subway stations, subway station entrances and exits, bus stops, residential area polygon vector data, and community household attribute data; the linear data includes the topological connection relationships of subway lines and bus lines, the point data includes geographic coordinate information, and the residential area polygon data includes geometric center coordinates and community household attributes;

[0034] A data processing module for performing standardization processing of geospatial data, unifying the coordinate system, extracting the geometric center coordinates of each element, standardizing the naming of attribute table fields, and adding a "type" field to mark the element type. The processed data is exported as a structured file;

[0035] The graph database construction module is used to merge the exported structured files to generate a global node table, assign unique global IDs, retain the original attribute fields and the "type" label, and define the node type by the "type" field; and establish the topological relationship between nodes to generate a relationship edge table, and form a public transportation graph database based on the node table and the relationship edge table.

[0036] The query module based on meta-paths is used to define the path pattern from the subway station through the subway station entrance and exit, multi-level bus stops to the residential area, construct a multi-level radiation meta-path, and execute graph queries to obtain the total number of households in the residential areas reachable by different subway stations through different transfer levels.

[0037] The visualization module is used to generate visualization analysis charts and display the distribution characteristics of the radiation capabilities of each station according to the rail transit lines.

[0038] In a third aspect, the present invention provides an electronic device, including: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the program is executed by the processor, the steps of the subway station radiation reachability evaluation method as described in the first aspect are implemented.

[0039] In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the subway station radiation reachability evaluation method as described in the first aspect are implemented.

[0040] Beneficial effects: (1) The present invention constructs a subway station reachability evaluation framework based on a graph database, and comprehensively quantifies the impact of subway-bus connections on subway station reachability through hierarchical analysis and the meta-path radiation model. (2) The present invention adopts a multi-modal travel network modeling method, which can not only evaluate the reachability changes of each subway station in the multi-modal transfer network, but also identify traffic bottlenecks, optimize the site layout and bus connection strategies. (3) In terms of technical implementation, the present invention constructs a multi-level meta-path for subway station-bus station transfer through a graph database, uses the graph algorithm query of Neo4j to directly obtain the population of residential areas radiated by nodes after passing through specific paths, quantifies the change in the influence range of subway stations caused by the participation of bus lines, indexes the obtained data to the corresponding site and residential area surface data through unique global IDs, and visualizes the influence of subway stations at different levels and the communities they affect in ArcGIS. Compared with the prior art, this method provides a new perspective for multi-scale analysis, can take into account both the macro network structure and the micro-site characteristics, has low computational cost, easy data acquisition, and strong scalability, and is suitable for the optimization analysis of different urban rail-bus systems. Description of the Drawings

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the embodiments. It should be understood that the accompanying drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other accompanying drawings based on these drawings without creative efforts.

[0042] Figure 1 Flowchart of the subway station radiation accessibility evaluation method under the influence of bus transfer provided by the embodiment of the present invention;

[0043] Figure 2 Prototype diagram of the public transportation map database provided by the embodiment of the present invention;

[0044] Figure 3 Schematic diagram of an excerpt of the Nanjing public transportation map database provided by the embodiment of the present invention;

[0045] Figure 4 Schematic diagram of the meta-path provided by the embodiment of the present invention;

[0046] Figure 5 Map of the number of households in the radiation area of the meta-path of the subway stations on Nanjing Metro Line 1 provided by the embodiment of the present invention;

[0047] Figure 6 Schematic diagram of the influence of multiple paths on residential areas at Maigaoqiao Station and Xiaozhuang Station provided by the embodiment of the present invention. Detailed implementation manners

[0048] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific implementation manners.

[0049] Embodiment 1

[0050] This embodiment provides a subway station radiation accessibility evaluation method under the influence of bus transfer. Specifically, a graph database model is established for Nanjing public transportation, and based on this, the influence ranges of subway-bus in various situations are calculated (indicated by the number of households in residential areas affected). This method can incorporate the subway-bus-residential area into a system, avoiding considering the coverage of the public transportation system only from a single dimension. The composite subway-bus accessibility can better evaluate the development level and weak points of the public transportation system in a region, providing a scientific decision-making basis for optimizing stations and lines. Refer to Figure 1 , the specific steps of the method are as follows:

[0051] Step S1: Obtain the data required for calculation.

[0052] The required raw data include urban subway network, bus network, subway station, subway station entrances and exits, bus stops, and residential areas. These data can be in shapefile (suffix shp), dwg and other formats, and can be converted into GIS vector data files, which are convenient for subsequent import into GIS software for visualization operations. Therefore, the data needs to obtain its geographic location information, and its longitude and latitude information can be directly extracted after being converted to a unified geographic coordinate system. Among them, the urban subway network and bus network are axis line data, subway stations, subway station entrances and exits, and bus stops are point data, and residential areas are surface data. The number of households in residential areas is required. In addition, the connection order data of subway stations and bus stops needs to be obtained in csv format. The connection order is the order of arrangement between stations when the bus line / subway line runs in a certain direction. For example, for the line Line-ad, the order of station a is 1, the order of station b is 2, the order of station c is 3, and the order of station d is 4. This data can be obtained through the map platform and the open API of 8848 Bus Network. Other data sources may include OpenStreetMap, Anjuke, Beike, Shuijingweizhu, government departments or other map data platforms, and perform appropriate cleaning operations. For example, grab the basic data of the community from the real estate information platform, link the building census data released by the government department, and perform data verification in combination with remote sensing image interpretation. Figure 2 shown.

[0053] Step S2: Preprocess data.

[0054] Open ArcGIS, select WGS84 (World Geodetic System 1984) geographic coordinate system, import subway line.shp, bus line.shp, subway station.shp, bus station.shp, subway entrance.shp, residential area.shp files. Obtain the longitude and latitude data of subway station, bus station, subway entrance, residential area layer in the attribute table (where the longitude and latitude of the residential area layer is the geometric center longitude and latitude), and construct them into X attribute and Y attribute respectively. Through the calculation geometry in the GIS attribute table, the longitude and latitude information contained in the shp data is assigned to the X attribute and Y attribute, where X is longitude and Y is latitude. Finally, standardize other attributes. The object names in each file crawled from the network may be different, such as name / Name / name / community / station name, etc. The column name representing the name is uniformly changed to name, and the attribute column name representing the number of households in the residential area is changed to XQHS, and a type attribute column is constructed for each layer, such as the type of subway station is subway station, and the type of bus line is bus line. Finally, the standardized data is exported in csv file format.

[0055] Step 3: Construct nodes and relationships between nodes (types see Figure 2 ). Integrate the exported csv data. Place each csv file in the same folder. The tables will be merged, and the attribute columns will be combined with like terms. For example, if each table has name and type, then the total table will only have one column for name and type, and the unique attribute columns will also be retained. For example, only the bus line has the line attribute. Then, in this column, the data of other types are empty values. However, the id column will be re - assigned, starting from 1 in order, and each element on the total table, that is, each row, will be given a global id. Finally, obtain a total node table total_node.csv with the global id re - assigned and with the type attribute. Use total_node.csv, subway_line.csv, bus_line.csv, subway_connection_sequence.csv, and bus_connection_sequence.csv to construct the connection edges between nodes. Specifically as follows:

[0056] (1) Match the relationship between subway stations and subway entrances and exits. Use the keyword matching method to complete the connection judgment. For example, if node a is subway station A and node b is Exit 1 of subway station A, and they have the same keyword A, it means that the subway entrance and exit of node b is the corresponding subway entrance and exit of node a, and a connection needs to be established. The specific technical implementation is completed through python. Extract the name column where the type is subway station from total_node.csv, denoted as the matching data. Extract the name column where the type is subway entrance and exit, denoted as the data to be matched. For each row in the matching data, traverse and match it with the data to be matched. Find the corresponding subway entrance and exit for each subway station. And record the final result as source_id (the id of the matching data), source_name (the name of the matching data), target_id (the id of the data to be matched), target_name (the name of the data to be matched), and a new type column is added, and "subway station_subway entrance and exit" is written into the field. After traversing and matching, write the data source_id, source_name, target_id, target_name, type into the data table subway_station_subway_entrance_and_exit.csv and export it.

[0057] (2) The relationship matching between subway stations and subway lines is completed using the obtained subway connection order.csv. The subway connection order.csv contains columns: subway station, subway line, order. Each subway line passes through corresponding subway stations one by one. Therefore, source_name is the name of the subway station, source_id is the id matched with the subway station data of the corresponding name in the total node.csv, target_name is the corresponding subway line name, and target_id is the subway line id matched with the corresponding name and target_name in the total node.csv. And add a type column, with the type column being subway station_subway line. Export these 5 columns as a table named subway station_subway line.csv.

[0058] (3) The relationship matching between bus stops and bus lines is the same as (2), except that subway stations are changed to bus stops and subway lines are changed to bus lines.

[0059] (4) The matching relationship between subway entrances / exits and bus stops uses the distance matching method. Using the longitude and latitude data (X column and Y column) obtained by computational geometry, match the bus stops within 800 meters of the subway entrances / exits. Establish a connection through the nearest neighbor table or spatial join in ArcGIS called by python. The input layer is the bus stop, and the output layer is the subway entrance / exit. Match each bus stop with each subway entrance / exit within 800m of it, which will generate a connection id (bus stop id), a matching id (subway entrance / exit id), record them, and add the corresponding source_name (the name corresponding to the bus stop) and target_name (the name corresponding to the subway entrance / exit). Modify the connection id to source_id, modify the matching id_ to target_id, and add a new type column, filling in the data as subway entrance / exit_bus stop. Record the data and export it to the table subway entrance / exit_bus stop.csv.

[0060] (5) The matching relationship between subway entrances / exits and residential areas is similar to (4), denoted as subway entrance / exit_residential area.csv.

[0061] (6) The distance matching threshold between bus stops and residential areas is 300m, that is, establish an edge relationship with the residential areas within 300 meters of the bus stops. Establish a connection through the nearest neighbor table or spatial join in ArcGIS. The input layer is the residential area, and the output layer is the bus stop. The detailed steps are similar to (4). Finally, output the five columns of source_id, source_name, target_id, target_name, and type. The type column is bus stop_residential area. Finally, export the table bus stop_residential area.csv.

[0062] (7) The connections between subway stations are obtained from the subway connection order.csv to generate the subway_station_subway_station.csv. The subway connection order.csv contains columns: subway station, subway line, order. The data in the order column are numbers 1, 2, 3, 4... This represents the order in which subway stations are passed through successively when the subway line runs in a specific direction. Therefore, the subway stations belonging to the subway line can be connected in sequence, and adjacent subway stations need to be connected, such as 1-2, 2-3, 3-4. If the maximum value of the order is n, then the names of the subway stations corresponding to the orders 1-(n-1) are filled in the source_name column in sequence, and the corresponding ids are matched according to the total node.csv. Then, the names of the subway stations corresponding to the orders 2-n are written in the target_name column in sequence, and the global ids are matched. In addition, write the attribute type, subway_station_subway_station, and write the attribute Line to record the data of the subway line, such as Line 1, etc. Write the final 6-column attributes into the table subway_station_subway_station.csv and export it. (8) For bus stops, they are matched according to the bus connection order.csv, following the steps in (7). Write the type column as bus_stop_bus_stop, and write the attribute column Line, such as Line 102 (from Nanjing South to Gulou). Write the data into the table bus_stop_bus_stop.csv and export it.

[0063] Merge the edge relationship files of the above steps (1)-(8) to obtain the total connection.csv, which has columns source_id, source_name, target_id, target_name, type, line.

[0064] Step 4: Graph database construction. The graph database construction and query of this method are based on the Neo4j platform (Neo4j Desktop-1.5.9). The total node.csv and total connection.csv obtained in step 3 are batch-imported into nodes and edges through the pyneo library. The type column in the csv file is used as the label. Other columns including name, id, etc. are written as attributes into the database. The graph database constructed by this method is an LPG (Label Property Graph) database. The generated graph database is as Figure 3 shown.

[0065] Step 5: Data query and preparation. Construct query meta-paths to explore the radiation ability of nodes through extended nodes. Specifically, this method defines a radiation path: subway station - subway station entrance - bus stop *n - residential area. By calculating the sum of the number of households in the residential areas connected under the given meta-path, the radiation area of public transportation under the subway-bus transfer background can be reflected. By changing the number n of bus stops, the radiation level can be controlled. Figure 4The relationship of meta-paths in the global network is shown, where (a) is the connection type between nodes defined in this paper; (b) is a meta-path extracted from it: subway station-subway entrance and exit-residential area, abbreviated as MR; (c) is a schematic diagram of the meta-path: subway station-subway station entrance and exit-bus station-residential area, abbreviated as MBR. This method constructs the following meta-path based on Neo4j's cypher query statement:

[0066] p1: subway station-subway station entrance-residential area; abbreviated as MR;

[0067] p2: subway station - subway station entrance and exit - bus station - bus station - residential area; abbreviated as M1BR;

[0068] p3: subway station-subway station entrance-bus station-bus station-bus station-residential area; abbreviated as M2BR;

[0069] p4: subway station-subway station entrance-bus station-bus station-bus station-bus station-residential area; abbreviated as M3BR;

[0070] p5: subway station-subway station entrance-bus station-bus station-bus station-bus station-bus station-bus station-residential area; abbreviated as M4BR;

[0071] To ensure the accuracy and efficiency of the query, this method adopts the following key control strategies in Neo4j:

[0072] (I) Control query depth:

[0073] 1. By adjusting n (the number of bus stop levels), the query expansion range is limited to avoid infinite search and improve computational efficiency.

[0074] 2. Use MATCH...WHERE to limit the query level to ensure that the n-level bus stops are only connected to residential areas and do not continue to expand.

[0075] (II) Preventing path duplication:

[0076] 1. Use a path deduplication mechanism to ensure that the stops on each bus line are not counted repeatedly.

[0077] 2. Use COLLECT(DISTINCT...) to keep only unique residential area connections to avoid duplicate counting.

[0078] The specific implementation is as follows:

[0079] WITH station,bl,b1

[0080] MATCH(b1)-[:bus stop_bus stop]->(b2:bus stop)

[0081] -[:Bus Stop_Bus Stop]->(b3:Bus Stop)

[0082] -[:Bus Stop_Bus Stop]->(b4:Bus Stop)

[0083] WHERE (b1)-[:Bus Stop_Bus Route]->(bl)

[0084] AND (b2)-[:Bus Stop_Bus Route]->(bl)

[0085] AND (b3)-[:Bus Stop_Bus Route]->(bl)

[0086] AND (b4)-[:Bus Stop_Bus Route]->(bl)

[0087] Note: Among them, b1, b2, b3... are all bus stop nodes, and bl is the bus route node

[0088] (III). Statistics and Duplicate Removal of the Number of Households in Residential Areas

[0089] 1. Since the same residential area may be connected multiple times in different paths, to prevent duplicate counting, this method uses COLLECT(DISTINCT residential area) for duplicate removal and calculates the sum of the number of unique households through REDUCE.

[0090] 2. OPTIONAL MATCH is used at the end of the path to ensure that paths not connected to the residential area do not affect the result statistics.

[0091] The specific implementation is shown as follows:

[0092] OPTIONAL MATCH (b4)-[:Bus Stop_Residential Area]->(residentialArea:Residential Area)

[0093] WITH station, COLLECT(DISTINCT residentialArea) AS uniqueResidentialAreas, bl

[0094] WITH

[0095] station.id AS Subway Station ID,

[0096] station.name AS Subway Station Name,

[0097] [r IN uniqueResidentialAreas | r.name] AS List of Residential Area Names,

[0098] REDUCE(totalXQHS = 0.0, r IN uniqueResidentialAreas | totalXQHS + toFloat(r.XQHS)) AS totalXQHS,

[0099] bl.name AS busLineName

[0100] RETURN

[0101] subwayStationID,

[0102] subwayStationName,

[0103] totalXQHS AS totalResidentialAreaXQHS,

[0104] COALESCE(apoc.text.join(listOfResidentialAreaNames, ";"), "No residential areas") AS deduplicatedResidentialAreaNames,

[0105] COALESCE(busLineName, "No bus line") AS busLineName

[0106] ORDER BY totalXQHS DESC;

[0107] And the sum of the household numbers of the residential areas connected by each subway station through different meta - paths, as well as the IDs of the residential areas, are exported as meta - path household numbers.csv.

[0108] Step 6: Visual expression. For the convenience of subsequent analysis, the meta - path household numbers.csv is divided into multiple sub - files according to different subway lines through code, such as 1 - line meta - path household numbers.csv, and the sub - files are split in the same folder line.file. Use the matplotlib library to complete the charting of the data. Use the code to sequentially read the csv files in line.file and draw a line chart of multiple lines. For example Figure 5 , the abscissa (X - axis) represents the subway station name, arranged in the order of the subway stations on the line. Each subway station name is extracted from the name column of the csv file and used as an independent point on the chart. The ordinate (Y - axis) represents the household numbers of the communities connected by each path. Different paths are represented by lines in different colors. In addition, the black vertical dotted line in the figure is the transfer station, which is convenient for readers to quickly locate the station.

[0109] The method of the present invention is used to model the Nanjing public transportation with a graph database, and based on this, the influence ranges of subway-bus in various situations are calculated (indicated by the number of households in residential areas affected). This method can incorporate the subway-bus-residential area into a system, avoiding considering the coverage of the public transportation system only from a single dimension. The combined subway-bus accessibility can better evaluate the development level and weaknesses of the public transportation system in a region, providing a scientific decision-making basis for optimizing stations and lines.

[0110] The present invention provides a method for analyzing the accessibility of subway stations under the background of rail transit integration. This invention helps to discover problems existing in the layout of public transportation lines or stations in each city. By analyzing the hierarchical changes of the affected residential areas around specific stations, the public transportation connection conditions around different subway stations can be compared. It can be found that the evaluation results in some areas are poor under a certain path or the whole path, which restricts public transportation trips. Taking Maigaoqiao Subway Station and Xiaozhuang Subway Station as examples, they are adjacent stations on Nanjing Metro Line 1. There is no obvious difference in terms of location. Under the condition of path p1, the number of residential areas affected by the two stations is similar, but Maigaoqiao Station has a slight advantage. However, when considering the radiation effect of bus lines, the influence of Xiaozhuang Station significantly exceeds that of Maigaoqiao Station. Figure 6 In (a) and (b), the yellow areas represent the residential areas affected under path p1, where Maigaoqiao Station has a greater influence. And in Figure 6 (b), the number of orange, dark orange and brown squares is larger and the coverage area is wider, indicating that as the path extends, the influence of Xiaozhuang Station grows faster and has a wider coverage range, showing a linear trend. This is because Xiaozhuang Station is a stop for multiple bus lines, further verifying the effectiveness of the meta-path influence analysis method. To sum up, by comparing and analyzing the changes in the influence of Maigaoqiao Station and Xiaozhuang Station under different path conditions, it can be found that due to its status as a hub for multiple bus lines, the influence of Xiaozhuang Station on the surrounding residential areas is significantly enhanced after considering the bus radiation effect. This result not only reflects the important influence of bus lines on the radiation range of subway stations, but also proves that the influence analysis method based on meta-path can accurately evaluate the influence of public transportation stations on the urban spatial structure.

[0111] The present invention provides a scientific basis for urban planners, helps to optimize the layout of the public transportation network, improves the convenience of residents' travel and the quality of life. At the same time, it also provides a new perspective and method for further exploring the interaction relationship between public transportation stations and urban functional areas.

[0112] Embodiment 2

[0113] This embodiment provides an evaluation device for the radiation accessibility of subway stations under the influence of bus transfer, including:

[0114] A data acquisition module, which is used to acquire multi-source heterogeneous geospatial data, including linear vector data of urban subway networks and bus road networks, point vector data of subway stations, subway station entrances and exits, and bus stops, residential area polygon vector data, and the number of households in the community attribute data; the linear data contains the topological connection relationships of subway lines and bus lines, the point data contains geographic coordinate information, and the residential area polygon data contains geometric center coordinates and the number of households in the community attribute;

[0115] A data processing module, which is used to perform standardization processing of geospatial data, unify the coordinate system, extract the geometric center coordinates of each element, standardize the naming of the fields in the attribute table, and add a "type" field to label the element type. The processed data is exported as a structured file;

[0116] A graph database construction module, which is used to merge the exported structured files to generate a global node table, assign a unique global ID, retain the original attribute fields and the "type" label, and the node type is defined by the "type" field; and establish the topological relationship between nodes to generate a relationship edge table, and form a public transportation graph database based on the node table and the relationship edge table;

[0117] A query module based on meta-paths, which is used to define a path pattern from a subway station through subway station entrances and exits, multi-level bus stops to a residential area, construct a multi-level radiation meta-path, and execute a graph query to obtain the total number of households in the residential areas that can be reached by each subway station through different transfer levels;

[0118] A visualization module, which is used to generate visualization analysis charts and display the distribution characteristics of the radiation capabilities of each station according to the rail transit lines.

[0119] It should be understood that the evaluation device for the radiation accessibility of subway stations under the influence of bus transfers in the embodiments of the present invention can implement all the technical solutions in the above method embodiments. The functions of its various functional modules can be specifically implemented according to the methods in the above method embodiments, and the specific implementation process can refer to the relevant descriptions in the above embodiments and will not be elaborated here.

[0120] Embodiment Three

[0121] This embodiment provides an electronic device, including: one or more processors; a memory; and one or more programs, where the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the program is executed by the processor, it implements the steps of the method for evaluating the radiation accessibility of subway stations under the influence of bus transfers as described above.

[0122] Embodiment Four

[0123] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the subway station radiation accessibility evaluation method under the influence of bus transfer as described above are implemented.

[0124] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a device, a computer device, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0125] The present invention is described with reference to the flowchart of the method according to the embodiments of the present invention. It should be understood that each process in the flowchart and the combination of processes in the flowchart can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a system for implementing the functions specified in Figure 1 one process or multiple processes.

[0126] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction system that implements the functions specified in Figure 1 one process or multiple processes.

[0127] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one process or multiple processes.

Claims

1. A method for evaluating the radiation accessibility of subway stations under the influence of bus transfers, characterized in that: The following steps are involved: Step S1: Acquire multi-source heterogeneous geographic spatial data, including linear vector data of urban subway network and bus network, point vector data of subway stations, subway station entrances and exits, and bus stations, surface vector data of residential areas, and attribute data of the number of households in the residential area; the linear data contains the topological connection relationship of subway lines and bus lines, the point data contains geographic coordinate information, and the surface data of residential areas contains geometric center coordinates and attributes of the number of households in the residential area; Step S2: Perform standardization of geospatial data, unify the coordinate system, extract the geometric center coordinates of each element, standardize the field naming of the attribute table, and add the "type" field to mark the element type. The processed data is exported as a structured file; Step S3: Merge the exported structured files to generate a global node table, assign a unique global ID, retain the original attribute fields and "type" label, and the node type is defined by the "type" field; And establish the topological relationship between nodes, generate the relationship edge table, and form a public transportation graph database based on the node table and the relationship edge table; Step S4: define a path pattern extending from the subway station through the subway station entrance and exit, multi-level bus stations to the residential area, construct a multi-level radial element path, and perform a graph query to obtain the total number of households in the residential area that can be reached by each subway station through different transfer levels; Step S5: Generate a visual analysis chart to display the distribution characteristics of the radiation capacity of each station according to the rail transit line.

2. The method according to claim 1, characterized in that: The step S2 comprises: S2.1: Import the data obtained in step S1 into the ArcGIS platform, convert them into the WGS84 geographic coordinate system, extract the longitude and latitude coordinates of subway stations, bus stops, and subway station entrances and exits as X and Y attributes, calculate the geometric center coordinates of the residential area surface data and assign X and Y attributes; S2.2: Standardize data attribute fields, unify the name fields of each layer as "name", name the number of households in the residential area as "XQHS", and add the "type" field to mark the feature type; export the processed data as a structured CSV file.

3. The method according to claim 1, characterized in that: In step S3, the relationship edge types include affiliation, spatial proximity, and line sequence connection; establishing a topological relationship between nodes includes: Based on the name matching algorithm, the subway station and its entrance and exit are associated to generate the "subway station_subway station entrance and exit" relationship edge; Based on the line connection order table, the affiliation edges between subway stations and subway lines, and between bus stations and bus lines are constructed; Using ArcGIS spatial analysis tools, the subway station entrances and exits are matched with bus stations within an 800-meter radius, and the residential areas are matched with a 300-meter radius, generating "subway station entrance and exit_bus station" and "bus station_residential area" spatial proximity relationship edges; Generate sequential connection edges between adjacent subway stations and bus stops based on the line connection sequence table, and mark the lines they belong to.

4. The method according to claim 1, characterized in that: In step S4, the multi-level radiation element path is defined as: p0: subway station → subway entrance and exit → residential area; p n :Subway station → subway entrance → (bus station × n) → residential area, n∈[1,4]; The graph database is traversed through the Cypher query language to count the total number of households in the residential areas connected to the end of each meta-path.

5. The method according to claim 4, characterized in that The query statement includes path depth control, same-line constraints, and result aggregation logic.

6. The method according to claim 5, characterized in that In the query statement, n is adjusted to limit the extended scope of the query, MATCH...WHERE is used to limit the query level of bus stops, and COLLECT(DISTINCT) and REDUCE functions are combined to remove duplicates in residential areas and accumulate the number of households.

7. The method according to claim 1, characterized in that The visual analysis in step S5 includes: Split the query results by subway line to generate a data set of radiation capacity of stations on each line; Use matplotlib to draw a multi-line line graph, with the horizontal axis representing the names of subway stations arranged in line order, and the vertical axis representing the number of households affected by different meta-paths. Use colors to distinguish path levels, and vertical dotted lines to mark transfer stations. Generate a spatial heat map, superimpose the residential areas affected by subway stations, bus routes and different path levels, and reflect the differences in household density through color scale. The method quantifies the station radiation capacity under multiple transfer scenarios through composite subway-bus-residential area network modeling, identifies areas with weak public transportation coverage, and provides data support for line network optimization.

8. A method for evaluating the radiation accessibility of subway stations under the influence of bus transfers, characterized in that: include: The data acquisition module is used to acquire multi-source heterogeneous geographic spatial data, including linear vector data of urban subway networks and bus networks, point vector data of subway stations, subway station entrances and exits, and bus stations, and surface vector data of residential areas and attribute data of the number of households in the community; the linear data contains the topological connection relationship of subway lines and bus lines, the point data contains geographic coordinate information, and the surface data of residential areas contains geometric center coordinates and attributes of the number of households in the community; The data processing module is used to standardize geospatial data, unify the coordinate system, extract the geometric center coordinates of each element, standardize the field naming of the attribute table, and add the "type" field to mark the element type. The processed data is exported as a structured file; The graph database construction module is used to merge the exported structured files to generate a global node table, assign a unique global ID, retain the original attribute fields and the "type" label, and the node type is defined by the "type" field; and establish the topological relationship between nodes, generate a relationship edge table, and form a public transportation graph database based on the node table and the relationship edge table; The query module based on meta-path is used to define the path pattern extending from the subway station through the subway station entrance and exit, multi-level bus station to the residential area, construct a multi-level radial meta-path, and perform graph query to obtain the total number of households in the residential area that can be reached by each subway station through different transfer levels; The visualization module is used to generate visual analysis charts to display the distribution characteristics of the radiation capacity of each station according to the rail transit line.

9. An electronic device, characterized in that: include: one or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the method for evaluating the radiation accessibility of a subway station under the influence of bus transfer as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for evaluating the radiation accessibility of a subway station under the influence of bus transfers as described in any one of claims 1 to 7 are implemented.

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