A method and system for identifying key stations of a subway network considering bus substitution

Abstract

The application discloses a kind of subway network key site identification method and system considering bus substitution, based on subway and bus station and line data in research range, respectively construct subway weighted network and bus weighted network with travel time as weight, select the bus station in the walking range of subway station by space connection method, construct initial bus alternative network, combined with walking time, passenger walking perception coefficient and acceptable travel time threshold, finally weighted bus alternative network is obtained by optimization;Calculate the betweenness centrality, closeness centrality and weighted degree centrality of each subway station, establish a comprehensive importance calculation model, and identify the key stations in the subway network based on the comprehensive importance. The application is used for accurately capturing the importance of subway station in network structure and the trade-off relationship of bus alternative service availability, which can provide decision support for subway system emergency plan and connection bus line network planning.

Description

Technical Field

[0001] This invention relates to a method and system for identifying key stations in a subway network that takes into account bus alternatives, and belongs to the field of public transportation planning and control technology. Background Technology

[0002] With the deepening of urbanization, subway systems have become the backbone of public transportation in major cities worldwide. Leveraging their speed, reliability, and economy, they undertake the function of transporting large volumes of passengers and are indispensable for ensuring the normal operation of modern cities. However, subways inevitably encounter unexpected interruptions during operation. Such events not only directly disrupt the normal supply of subway services but also impact the overall urban transportation network, severely affecting residents' daily travel and socio-economic activities. To mitigate the negative impacts of subway interruptions, operators need to implement targeted passenger flow management measures, such as guiding passengers to other subway lines, regular buses, or emergency shuttle bus services. The effectiveness of these measures largely depends on a deep understanding of the subway system's structure and functions. Subway stations, as key nodes for passenger gathering and dispersal, are the starting point for planned emergency evacuation actions after an interruption—ensuring the orderly transfer of passengers between affected stations is crucial. Therefore, when assessing the robustness of stations within the subway network, it is essential to analyze the availability and substitutability of surrounding bus routes; this is a vital prerequisite for developing a scientific emergency shuttle plan.

[0003] Currently, most studies focus on the topology and dynamics of single metro networks or multimodal transportation networks, often failing to adequately consider the impact of alternative public transportation services and their potential to accommodate diverted passenger flow on station robustness under specific metro disruption scenarios. In fact, the availability of alternative public transportation services directly determines the feasibility and efficiency of passenger flow management after a disruption, and is a key dimension for assessing station robustness. Furthermore, some existing methods are insufficient in terms of robustness or do not adequately align with actual operational needs, making it difficult to accurately capture the trade-off between station centrality and the availability of alternative services. Therefore, they cannot provide metro operators with a reliable and flexible solution for identifying critical stations, ultimately affecting the effectiveness of disruption mitigation measures.

[0004] Therefore, developing a critical site identification method that can integrate alternative public transportation services and accurately assess the robustness of subway stations is a technical problem that urgently needs to be solved by those skilled in the art. Solving this technical problem will help improve the emergency response capabilities of subway systems and provide important support for the scientific planning and resilience optimization of urban public transportation networks. Summary of the Invention

[0005] Objective: To overcome the shortcomings of existing technologies that rely solely on the subway network topology to identify key stations without fully considering the impact of public transport alternative services on station criticality, this invention provides a method and system for identifying key subway network stations that considers public transport alternatives. By integrating the characteristics of the subway network topology with the accessibility of public transport alternative services, it accurately identifies key stations in the subway network, providing scientific decision support for the formulation of emergency plans, capacity allocation, and optimization of subway-connecting public transport networks.

[0006] Technical solution: To solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0007] Firstly, a method for identifying key stations in a subway network that considers public transport alternatives, specifically including:

[0008] Step 1: Construct the subway network and calculate the shortest travel time between stations within the subway network.

[0009] Step 2: Construct a public transport network and calculate the shortest travel time between each stop within the network.

[0010] Step 3: Based on the bus and subway station and route data within the research scope, use the spatial connectivity method to search for bus stations within a certain range of subway stations. When any two subway stations satisfy the condition that there are bus stations for the same route within the range, they are considered to have alternative bus connections. Based on the alternative bus connections, an initial alternative bus network is constructed.

[0011] Step 4: Based on the initial bus alternative network, considering the passenger's walking time and the shortest travel time between each station in the bus network, calculate the total alternative travel time corresponding to each edge of the initial bus alternative network, and use it as the edge weight to construct a weighted bus alternative network.

[0012] Step 5: Based on the total alternative travel time corresponding to each edge of the weighted bus alternative network and the shortest travel time between each station in the subway network, considering the threshold for increasing the acceptable travel time for passengers, the edges in the weighted bus alternative network are filtered, the shortest alternative travel time corresponding to each edge of the weighted bus alternative network is calculated, and the edge weights of the weighted bus alternative network are calculated to construct the final weighted bus alternative network.

[0013] Step 6: Calculate the betweenness centrality of each subway station.

[0014] Step 7: Calculate the proximity centrality of each subway station.

[0015] Step 8: Consider the connectivity of subway stations to other stations in the final weighted bus substitute network and the time difference between direct subway travel and other routes, calculate the weighted degree centrality of each subway station.

[0016] Step 9: Comprehensively consider the betweenness centrality, proximity centrality, and weighted degree centrality of subway stations. Establish a comprehensive importance calculation model for each subway station, and identify key subway stations based on the comprehensive importance.

[0017] In a second aspect, a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for identifying key stations in a metro network considering public transport alternatives as described in any of the first aspects.

[0018] Thirdly, a computer device comprising:

[0019] Memory is used to store instructions.

[0020] A processor is configured to execute the instructions, causing the computer device to perform operations as described in any of the first aspects of a method for identifying key stations in a metro network that takes into account bus alternatives.

[0021] Beneficial Effects: This invention provides a method and system for identifying key stations in a subway network considering public transport alternatives. Based on subway and bus station and route data within the research scope, a subway-weighted network and a public transport-weighted network are constructed, each weighted by travel time. A spatial connectivity method is used to filter bus stations within walking distance of subway stations, constructing an initial public transport alternative network. Combining walking time, passenger walking perception coefficient, and acceptable travel time thresholds, the final weighted public transport alternative network is optimized. The betweenness centrality, proximity centrality, and weighted degree centrality of each subway station are calculated, establishing a comprehensive importance calculation model. Based on this comprehensive importance, key stations in the subway network are identified. This invention accurately captures the trade-off between the importance of subway stations in the network structure and the availability of public transport alternative services, providing decision support for subway system emergency plan development and connecting public transport network planning. Compared to existing technologies, the advantages of this invention are as follows:

[0022] 1. To address the shortcomings of existing technologies that rely solely on the subway network topology and do not fully consider the impact of bus alternative services on station criticality, this paper proposes to integrate subway network topology characteristics with bus alternative service accessibility to construct a subway weighted network, a bus weighted network, and a multi-round optimized bus alternative network. A comprehensive importance calculation model is established by combining betweenness centrality, proximity centrality, and weighted degree centrality to achieve accurate identification of critical stations.

[0023] 2. Based on basic data such as subway and bus stations and routes within the research scope, this invention can systematically evaluate the importance of subway stations in the network structure and the availability of bus alternative services without additional large-scale surveys or complex data collection. Compared with traditional single network key station identification methods, it has more comprehensive coverage and stronger adaptability.

[0024] 3. The key stations identified by this invention can accurately reflect the actual risks faced after station interruption, and can provide scientific decision support for the formulation of emergency plans for the subway system, the optimization of transportation resources, and the planning of connecting bus networks, effectively improving the emergency response capability and operation management level of urban public transportation. Attached Figure Description

[0025] Figure 1 This is a flowchart of a method for identifying key stations in a subway network that considers public transport alternatives, according to the present invention.

[0026] Figure 2 This is a subway network map of a certain area in an embodiment of the present invention.

[0027] Figure 3 This is an initial public transport alternative network diagram for a certain area in an embodiment of the present invention.

[0028] Figure 4 This is a diagram of the final public transport alternative network for a certain area in an embodiment of the present invention.

[0029] Figure 5 This is a comprehensive importance distribution map of a certain region in an embodiment of the present invention. Detailed Implementation

[0030] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0031] The present invention will be further described below with reference to specific embodiments.

[0032] Example 1:

[0033] This embodiment introduces a method for identifying key stations in a subway network that considers public transport alternatives, such as... Figure 1 As shown, it includes the following steps:

[0034] Step 1: Obtain subway station / line data within the research scope, as well as historical AVL (automated vehicle location) data for each subway line. Construct a subway network using travel time between subway stations as weights, and calculate the shortest travel time between stations within the subway network.

[0035] Step 2: Obtain bus stop / route data within the research scope, as well as historical AVL (automated vehicle location) data for each bus route. Construct a bus network using travel time between bus stops as weights, and calculate the shortest travel time between stops within the bus network.

[0036] Step 3: Based on the bus and subway station and route data within the research scope, use the spatial connectivity method to search for bus stations within a certain range of subway stations. When any two subway stations satisfy the condition that there are bus stations for the same route within the range, they are considered to have alternative bus connections. Based on the alternative bus connections, an initial alternative bus network is constructed.

[0037] Step 4: Based on the initial bus alternative network, considering the passenger's walking time and the shortest travel time between each station in the bus network, calculate the total alternative travel time corresponding to each edge of the initial bus alternative network, and use it as the edge weight to construct a weighted bus alternative network.

[0038] Step 5: Based on the total alternative travel time corresponding to each edge of the weighted bus alternative network and the shortest travel time between each station in the subway network, considering the threshold for increasing the acceptable travel time for passengers, the edges in the weighted bus alternative network are filtered, the shortest alternative travel time corresponding to each edge of the weighted bus alternative network is calculated, and the edge weights of the weighted bus alternative network are calculated to construct the final weighted bus alternative network.

[0039] Step 6: Calculate the betweenness centrality of each subway station based on the ratio of the number of all shortest paths passing through any station in the subway network to the total number of all shortest paths in the subway network.

[0040] Step 7: Calculate the proximity centrality of each subway station based on the shortest travel time between stations within the subway network.

[0041] Step 8: Consider the connectivity of subway stations to other stations in the final weighted bus substitute network and the time difference between direct subway travel and other routes, calculate the weighted degree centrality of each subway station.

[0042] Step 9: Comprehensively consider the betweenness centrality, proximity centrality, and weighted degree centrality of subway stations. Establish a comprehensive importance calculation model for subway stations, and identify key subway stations based on the comprehensive importance.

[0043] Furthermore, step 1 is specifically described as follows:

[0044] Step 1.1: Obtain subway station data, subway line data, and historical AVL data for each subway line within the research scope. The subway station data includes station name, line, and spatial coordinate information; the subway line data includes line name, station operation sequence, and spatial path of the line; the historical AVL data for each subway line includes the arrival and departure times of the subway at each station on the line.

[0045] Step 1.2: Based on subway line and station data, establish the subway network using the network modeling method (Space L method). ,in, Indicates the subway network, Indicates a meeting point at a subway station. This indicates the number of all stations in the subway network; , This represents the set of edges in a subway network. Two stations are considered to be connected when they are adjacent on a subway line.

[0046] Step 1.3: Calculate the edge set of the metro network based on historical AVL data of the metro lines. The corresponding weight set , The weight represents the average travel time of vehicles between adjacent stations, which can be obtained by subtracting the arrival and departure times between stations from the historical AVL data of the subway. Indicates adjacent subway stations and The average travel time between;

[0047] Step 1.4: Based on the constructed subway network The shortest path algorithm (weighted Dijkstra's algorithm) is used to calculate the shortest path between any two stations in the subway network. and Shortest path time between .

[0048] Furthermore, step 2 is specifically described as follows:

[0049] Step 2.1: Obtain bus stop data, bus route data, and historical AVL data for each bus route within the research scope. Bus stop data includes the stop name, the route it belongs to, and spatial coordinates; bus route data includes the route name, stop operation sequence, and the spatial path of the route; historical AVL data for each bus route includes the time it takes for buses to arrive at each stop on the route.

[0050] Step 2.2: Based on bus route and stop data, establish a bus network using the Space L method (a network modeling approach). ,in, Indicates the public transportation network. Indicates a collection of bus stops. This indicates the number of all stops in the public transport network. , This represents the set of edges in a public transport network. Two stops are considered to be connected if they are adjacent on a bus route.

[0051] Step 2.3: Calculate the edge set of the bus network at each station based on historical AVL data of the bus routes. The corresponding weight set , The weight represents the average travel time of vehicles between adjacent stops, which can be obtained by subtracting the arrival and departure times between stops from the historical AVL data of public transport. Indicates adjacent bus stops and The average travel time between;

[0052] Step 2.4: Based on the constructed public transport network The shortest path algorithm (weighted Dijkstra's algorithm) is used to calculate the shortest path between any two stops in the public transport network. and Shortest path time between .

[0053] Furthermore, step 3 is specifically described as follows:

[0054] Step 3.1: Based on the spatial location of subway and bus stations, establish a buffer zone with radius r centered on each subway station. Use the spatial connectivity method to search for bus station and route information within the buffer zone. For any subway station... The bus stop information within its buffer zone is represented as a set. The bus route information within its buffer zone is represented as follows: .in, , Indicates bus stops within the buffer zone; , Indicates bus stops within the buffer zone The corresponding bus route.

[0055] Step 3.2: For any two subway stations in the subway network and If the sets of bus routes within its buffer zone intersect and are not empty, that is... Then determine the subway station and There are alternative bus connections between them, and alternative bus connections are represented as follows: .

[0056] Step 3.3: Obtain alternative bus connections between any pair of stations in the subway network and establish an initial alternative bus network. .in, , representing the initial set of stations in the bus alternative network; , Let f(x) represent the set of edges in the initial bus alternative network.

[0057] Furthermore, step 4 is specifically described as follows:

[0058] Step 4.1: For the initial bus alternative network Any edge in First, count all feasible alternative public transport routes for the connected edge. The total number of routes is the number of connected edges. Corresponding subway station and The number of bus routes that pass through together, i.e. .

[0059] Step 4.2: For each feasible alternative public transport route, calculate the subway station. Bus stops corresponding to feasible alternative public transport routes walking distance between and subway stations Bus stops corresponding to feasible alternative public transport routes walking distance between This distance can be obtained by calling the Smart Map API.

[0060] Step 4.3: Calculate the walking time for feasible alternative public transport routes, denoted as [missing information]. The calculation formula is as follows:

[0061]

[0062] in, Indicates from subway station To the bus stop Walking time from the subway station To the bus stop The sum of walking times, and These are stops on the same bus route; This indicates the passenger's walking speed.

[0063] Step 4.4: Based on the constructed public transport network Get bus stops with bus stops Shortest path time between .

[0064] Step 4.5: Calculate the total time for feasible alternative public transport routes, denoted as . The calculation formula is as follows:

[0065]

[0066] in, Indicates from subway station Walk to the bus stop Take the bus from the station To the station Then from the bus stop Walk to the subway station Total duration; The walking time perception coefficient measures the intensity of a passenger's subjective perception of walking time.

[0067] Step 4.6: Calculate the total time for all feasible public transport alternatives and extract the one with the shortest total time. As a connecting edge The duration is denoted as .

[0068] Step 4.7: Construct a weighted transit alternative network , of which , Let be the set of durations corresponding to the edges. Characterizing subway stations and The shortest alternative public transport route in terms of travel time.

[0069] Furthermore, step 5 is specifically described as follows:

[0070] Step 5.1: For weighted transit alternative networks Each edge in Based on the constructed subway network Get subway station with bus stops Shortest path time between .

[0071] Step 5.2: Set the maximum acceptable time difference for passengers using alternative public transport routes as a threshold. .

[0072] Step 5.3: When the edge The total time for corresponding feasible alternative public transport routes Shortest path time with subway When the subtraction exceeds the threshold, that is... Then delete the weighted public transport alternative network. The corresponding edges in the network are used to obtain the filtered network edges. .

[0073] Step 5.4: Construct the final weighted transit alternative network ,in These are the network edges that have been filtered in the previous step. , The weights corresponding to the filtered network edges can be calculated using the following formula:

[0074]

[0075] Furthermore, the method for calculating the betweenness centrality of each subway station is expressed as follows:

[0076]

[0077] in: Indicates subway station Betweenness centrality; Indicating in the subway network From the subway station to subway station The number of all shortest paths; Indicating in the subway network From the subway station to subway station Passing through subway station Number of shortest paths.

[0078] Furthermore, the method for calculating the proximity centrality of each subway station is expressed as follows:

[0079]

[0080] in: Indicates subway station Proximity centrality; This represents the total number of stations in the subway network; Indicates subway station and In the subway network The shortest path time.

[0081] Furthermore, the weighted degree centrality calculation method for each subway station is expressed as follows:

[0082]

[0083] in: Indicates subway station Weighted degree centrality; This represents the total number of stations in the subway network; This indicates that the final weighted bus can replace the network edge. The weights; This indicates that the final weighted bus can replace the network edge. The weight.

[0084] Furthermore, the comprehensive importance calculation model for each subway station is expressed as follows:

[0085]

[0086] in: Indicates subway station The higher the overall importance value, the greater its importance to the entire subway network.

[0087] Based on the overall importance of each subway station, all stations are sorted in descending order of overall importance. A key station screening threshold is set according to actual operational needs. Subway stations ranked within the threshold range are considered key stations in the subway network, thus completing the identification of key subway stations.

[0088] Example 2:

[0089] This embodiment describes a computer-readable storage medium storing a computer program that, when executed by a processor, implements a method for identifying key stations in a subway network considering public transport alternatives, as described in any of Embodiment 1.

[0090] Example 3:

[0091] This embodiment describes a computer device, including:

[0092] Memory is used to store instructions.

[0093] A processor is configured to execute the instructions, causing the computer device to perform operations as described in any of Embodiment 1 of a method for identifying key stations in a metro network that takes into account bus alternatives.

[0094] Example 4:

[0095] This embodiment takes a certain city as the research scope. The subway network in this area includes 10 lines and 226 subway stations, covering the city's core functional areas such as commercial centers, transportation hubs, and residential areas. The supporting conventional bus network includes 685 bus lines and 18,691 bus stops. The spatial coupling between buses and subway stations is strong, exhibiting typical characteristics of multi-network integration in urban public transportation.

[0096] 1. Obtain subway station / line data within the research scope, as well as historical AVL data for each line, and construct the subway network using travel time between stations as weights.

[0097] The subway station and line data includes information such as station number, station name, line name, and spatial coordinates (latitude and longitude). The specific data format is shown in Table 1.

[0098] Table 1. Example of subway station and line data

[0099]

[0100] Based on historical AVL data of each subway line, the time weights corresponding to the subway network edges of each station are calculated, and a subway network is established. Table 2 shows examples of the edges and weights of the subway network, which includes 226 subway stations and 432 edges. The subway network diagram is shown below. Figure 2 As shown.

[0101] Table 2. Example of weighted network data for subway systems

[0102]

[0103] 2: Obtain bus stop / route data within the research scope, as well as historical AVL data for each route, and construct a bus network using travel time between stops as weights.

[0104] The bus stop and route data includes information such as stop number, stop name, route name, and spatial coordinates (latitude and longitude). The specific data format is shown in Table 3.

[0105] Table 3. Example of bus route and stop data

[0106]

[0107] Based on historical AVL data for each bus route, the time weights corresponding to the bus network edges at each station are calculated, and a bus network is established. Table 4 shows examples of the edges and weights of the public transport network, which includes 18,691 bus stops and 32,227 edges.

[0108] Table 4. Example of weighted network data for public transport

[0109]

[0110] 3. Use the spatial connectivity method to search for bus stops within a certain range of subway stations. When any two subway stations satisfy the condition that there are bus stops for the same line within the range, they are considered to have alternative bus connections, and an initial alternative bus network is constructed based on this.

[0111] Based on the spatial buffer zone range of subway stations and the spatial distribution data of bus stops, a buffer zone with a radius of 600 meters is established with each subway station as the center. A spatial connection method is used to identify bus stops and bus routes within the buffer zone. An initial bus alternative network is constructed by determining whether the intersection of the bus route sets within the buffer zones of any two subway stations in the subway network is empty. .like Figure 3 As shown, the initial bus alternative network contains a total of 9001 candidate alternative edges.

[0112] 4. Considering passengers' walking time and travel time between bus stops, calculate the total alternative travel time corresponding to each edge in the bus alternative network, using this as the edge weight to construct a weighted bus alternative network. Furthermore, consider a threshold for increasing the acceptable travel time for passengers to filter the edges in the bus alternative network, thus constructing the final weighted bus alternative network.

[0113] Based on the travel time between stops in the public transport network, and considering walking time (walking speed 5km / h) and walking perception coefficient, the total time for alternative trips is calculated. A maximum public transport alternative trip time difference threshold of 30 minutes is set, and 665 optimal alternative edges are ultimately selected. A final weighted public transport alternative network is then constructed. Table 5 shows an example of the final weighted bus alternative network data, including the starting and ending subway stations, the subway line, the alternative bus line, the bus boarding station, the bus alighting station, the subway journey duration, the total alternative travel time (minutes), and edge weight data. Specific data examples are shown in Table 5. The final bus alternative network graph is shown below. Figure 4 As shown.

[0114] Table 5. Examples of Final Weighted Bus Alternative Network Data

[0115]

[0116] 5: Based on the constructed subway network and ultimately weighted alternative public transport networks Calculate the betweenness centrality, proximity centrality, and weighted degree centrality of each subway station.

[0117] The results of betweenness centrality, proximity centrality, and weighted degree centrality of each subway station are shown in Table 6.

[0118] Table 6 Examples of three types of centrality indicators for subway stations

[0119]

[0120] 6. A comprehensive importance calculation model for subway stations is established, taking into account betweenness centrality, proximity centrality, and weighted degree centrality. Key subway stations are identified based on this comprehensive importance.

[0121] Based on the three types of centrality indicators of each station, a comprehensive importance calculation model is established to calculate the criticality level of the station. This indicator comprehensively reflects the trade-off between the station's role as a network hub and the availability of public transport alternative services. The higher the value, the more critical the station is and the weaker the alternative service. Table 7 shows the top 10 stations in terms of comprehensive importance. Figure 5 The distribution of the overall importance of subway stations is plotted based on the calculation results in Table 7.

[0122] Table 7 Top 10 Metro Stations by Keyness Ranking

[0123]

[0124] This invention discloses a method for identifying key stations in a metro network that considers public transport alternatives. It integrates the topological characteristics of the metro network with the accessibility of public transport alternative services. First, it acquires station and route data for both metro and bus services within the study area, constructing a metro-weighted network and a bus-weighted network, respectively, weighted by travel time. Then, it searches for bus stops within a certain range of metro stations using spatial connectivity methods, constructing an initial public transport alternative network. Combining walking time, travel time between bus stops, and passenger walking time perception coefficients, it calculates the total alternative travel time, constructing a weighted public transport alternative network. By setting a threshold for acceptable travel time for passengers, it optimizes and obtains the final weighted public transport alternative network. Finally, it calculates the betweenness centrality, proximity centrality, and weighted degree centrality of each metro station, establishing a comprehensive importance calculation model, and identifying key metro stations based on this model. This invention can accurately identify key stations in a metro network, providing scientific decision support for metro system emergency plan development, capacity allocation, and optimization of metro-connecting public transport networks.

[0125] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied 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.

[0126] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0127] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0128] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0129] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for identifying key stations in a subway network considering public transport alternatives, characterized in that: Specifically, it includes: Step 1: Construct the subway network and calculate the shortest travel time between stations within the network; Step 2: Construct a public transport network and calculate the shortest travel time between each stop within the network; Step 3: Based on the bus and subway station and route data within the research scope, use the spatial connection method to search for bus stations within the subway station range. When any two subway stations satisfy the condition that there are bus stations for the same route within the range, it is considered that there is a substitute bus connection edge, and an initial bus substitute network is constructed based on the substitute bus connection edge. Step 4: Based on the initial bus alternative network, considering the passenger's walking time and the shortest travel time between each station in the bus network, calculate the total alternative travel time corresponding to each edge of the initial bus alternative network, and use it as the edge weight to construct a weighted bus alternative network. Step 5: Based on the total alternative travel time corresponding to each edge of the weighted bus alternative network and the shortest travel time between each station in the subway network, considering the threshold for increasing the acceptable travel time for passengers, the edges in the weighted bus alternative network are filtered, the shortest alternative travel time corresponding to each edge of the weighted bus alternative network is calculated, and the edge weights of the weighted bus alternative network are calculated to construct the final weighted bus alternative network. Step 6: Calculate the betweenness centrality of each subway station; Step 7: Calculate the proximity centrality of each subway station; Step 8: Consider the connectivity of subway stations to other stations in the final weighted bus substitute network and the time difference between direct subway travel and the subway, calculate the weighted degree centrality of each subway station. Step 9: Take into account the betweenness centrality, proximity centrality and weighted degree centrality of the subway stations; establish a comprehensive importance calculation model for each subway station, and identify key subway stations based on the comprehensive importance.

2. The method for identifying key stations in a subway network considering public transport alternatives according to claim 1, characterized in that: The specific method for step 1 is as follows: Step 1.1: Obtain subway station data, subway line data, and historical AVL data for each subway line within the research scope; the subway station data includes station name, line to which it belongs, and spatial coordinate information; the subway line data includes line name, station operation sequence, and spatial path of the line; the historical AVL data for each subway line includes the time when the subway arrives at and departs from each station on the line. Step 1.2: Based on subway line and station data, establish the subway network using network modeling methods. ,in, Indicates the subway network, Indicates a meeting point at a subway station. This indicates the number of stations in the subway network; , This represents the set of edges in a subway network. Two stations are considered to be connected if they are adjacent on a subway line. Step 1.3: Calculate the edge set of the metro network based on historical AVL data of the metro lines. The corresponding weight set , The weight represents the average travel time of vehicles between adjacent stations, which can be obtained by subtracting the arrival and departure times between stations from the historical AVL data of the subway. Indicates adjacent subway stations and The average travel time between; Step 1.4: Based on the constructed subway network The shortest path algorithm is used to calculate the distance between any two stations in the subway network. and Shortest path time between .

3. The method for identifying key stations in a subway network considering public transport alternatives according to claim 1, characterized in that: Step 2 is specifically described as follows: Step 2.1: Obtain bus stop data, bus route data, and historical AVL data for each bus route within the research scope; the bus stop data includes the stop name, the route to which it belongs, and spatial coordinate information; the bus route data includes the route name, the stop operation sequence, and the spatial path of the route; The historical AVL data for each bus route includes the time it takes for a bus to arrive at each stop on the route. Step 2.2: Based on bus route and stop data, establish a bus network using network modeling methods. ,in, Indicates the public transportation network. Indicates a collection of bus stops. This indicates the number of all stops in the public transport network. , This represents the set of edges in a public transport network. Two stops are considered to be connected if they are adjacent on a bus route. Step 2.3: Calculate the edge set of the bus network at each station based on historical AVL data of the bus routes. The corresponding weight set , The weight represents the average travel time of vehicles between adjacent stops, which is obtained by subtracting the arrival and departure times between stops in the historical AVL data of public transport. Indicates adjacent bus stops and The average travel time between; Step 2.4: Based on the constructed public transport network The shortest path algorithm is used to calculate the distance between any two stops in the public transport network. and Shortest path time between .

4. The method for identifying key stations in a subway network considering public transport alternatives according to claim 1, characterized in that: Step 3 is specifically described as follows: Step 3.1: Based on the spatial location of subway and bus stations, establish a buffer zone with radius r centered on the subway station, and use the spatial connectivity method to search for bus station and route information within the buffer zone; for any subway station... The bus stop information within its buffer zone is represented as a set. The bus route information within its buffer zone is represented as follows: ;in, , Indicates bus stops within the buffer zone; , Indicates bus stops within the buffer zone The corresponding bus route; Step 3.2: For any two subway stations in the subway network and If the sets of bus routes within its buffer zone intersect and are not empty, that is... Then determine the subway station and There are alternative bus connections between them, and alternative bus connections are represented as follows: ; Step 3.3: Obtain alternative bus connections between any pair of stations in the subway network and establish an initial alternative bus network. ;in, , representing the initial set of stations in the bus alternative network; , Let f(x) represent the set of edges in the initial bus alternative network.

5. The method for identifying key stations in a subway network considering public transport alternatives according to claim 1, characterized in that: Step 4 is specifically described as follows: Step 4.1: For the initial bus alternative network Any edge in Count all feasible alternative public transport routes for the connected edge; the total number of routes is the number of connected edges. Corresponding subway station and The number of bus routes that pass through together, i.e. ; Step 4.2: For each feasible alternative public transport route, calculate the subway station. Bus stops corresponding to feasible alternative public transport routes walking distance between and subway stations Bus stops corresponding to feasible alternative public transport routes walking distance between ; Step 4.3: Calculate the walking time for feasible alternative public transport routes, denoted as [missing information]. The calculation formula is as follows: ； in, Indicates from subway station To the bus stop Walking time from the subway station To the bus stop The sum of walking times, and These are stops on the same bus route; Indicates the passenger's walking speed; Step 4.4: Based on the constructed public transport network Get bus stops with bus stops Shortest path time between ; Step 4.5: Calculate the total time for feasible alternative public transport routes, denoted as . The calculation formula is as follows: ； in, Indicates from subway station Walk to the bus stop Take the bus from the station To the station Then from the bus stop Walk to the subway station Total duration; Indicates the perceived walking time coefficient; Step 4.6: Calculate the total time for all feasible public transport alternatives and extract the one with the shortest total time. As a connecting edge The duration is denoted as ; Step 4.7: Construct a weighted transit alternative network ,in, , Let be the set of durations corresponding to the edges. Characterizing subway stations and The shortest alternative public transport route in terms of travel time.

6. The method for identifying key stations in a subway network considering public transport alternatives according to claim 1, characterized in that: Step 5 is specifically described as follows: Step 5.1: For weighted transit alternative networks Each edge in Based on the constructed subway network Get subway station with bus stops Shortest path time between ; Step 5.2: Set the maximum acceptable time difference for passengers using alternative public transport routes as a threshold. ; Step 5.3: When the edge The total time for corresponding feasible alternative public transport routes Shortest path time with subway When the subtraction exceeds the threshold, that is... Then delete the weighted public transport alternative network. The corresponding edges in the network are used to obtain the filtered network edges. ; Step 5.4: Construct the final weighted transit alternative network ,in, , The weights corresponding to the filtered network edges can be calculated using the following formula: 。 7. The method for identifying key stations in a subway network considering public transport alternatives according to claim 1, characterized in that: The comprehensive importance calculation model for each subway station is expressed as follows: ； in: Indicates subway station The overall importance, Indicates subway station betweenness centrality, Indicates subway station Proximity centrality Indicates subway station Weighted degree centrality.

8. The method for identifying key stations in a subway network considering public transport alternatives according to claim 1, characterized in that: The method for calculating the betweenness centrality of each subway station is expressed as follows: ； in: Indicates subway station Betweenness centrality; Indicating in the subway network From the subway station to subway station The number of all shortest paths; Indicating in the subway network From the subway station to subway station Passing through subway station Number of shortest paths; The method for calculating the proximity centrality of each subway station is expressed as follows: ； in: Indicates subway station Proximity centrality; This represents the total number of stations in the subway network; Indicates subway station and In the subway network The shortest path time in; The weighted degree centrality calculation method for each subway station is expressed as follows: ； in: Indicates subway station Weighted degree centrality; This represents the total number of stations in the subway network; This indicates that the final weighted bus can replace the network edge. The weights; This indicates that the final weighted bus can replace the network edge. The weight.

9. A computer-readable storage medium, characterized in that: It stores a computer program that, when executed by a processor, implements a method for identifying key stations in a metro network that considers public transport alternatives, as described in any one of claims 1 to 8.

10. A computer device, characterized in that: include: Memory, used to store instructions; A processor for executing the instructions, causing the computer device to perform the operation of a method for identifying key stations in a metro network considering public transport alternatives as described in any one of claims 1 to 8.

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