A method, device, and storage medium for measuring the development value of rail transit station corridor space and generating investment implementation priorities.

Abstract

This application relates to the fields of rail transit planning and decision-making, spatial data processing, and investment assessment, and discloses a method, device, and storage medium for measuring the development value of rail transit station corridor space and generating investment implementation priorities. The method acquires data on rail transit, connection networks, population employment, public services, land use, and building development intensity; constructs a multi-modal connection network; and calculates access convenience through modal reliability coefficients, modal competition correction coefficients, and a two-stage search. It combines spatial potential characteristics with nonlinear coupling and imbalance penalties to obtain a development value index; generates station-level, corridor-level, and area-level results and performs linked corrections; and outputs a structured result set containing priority ranking, implementation type, strategy label, and difference contribution fields. This application can improve the consistency and executability of station corridor space development ranking results.

Description

Technical Field

[0001] This application relates to the fields of rail transit planning and decision-making, spatial data processing and investment evaluation, and in particular to a method, apparatus and computer-readable storage medium for measuring the development value of rail transit station corridor space and generating investment implementation priorities. Background Technology

[0002] With the continued advancement of metropolitan areas, urban clusters, and integrated development of stations and cities, the spaces surrounding rail transit stations and their corridors have become key targets for the coordinated allocation of transportation infrastructure investment and land development. In actual projects, governments, platform companies, consulting firms, and developers typically need to prioritize investments among multiple candidate stations, corridors, and development zones to determine which areas should be prioritized for station-city development, connectivity enhancement, functional development, or postponement.

[0003] The common technical methods currently available mainly include the following categories: one category is accessibility evaluation methods oriented towards transportation supply capacity, which mainly measure the coverage of stations to the population or facilities; another category is single-indicator evaluation methods oriented towards urban spatial structure, which mainly analyze population density, land development intensity, facility mix, or economic linkage intensity; and the third category is node-site evaluation methods oriented towards stations, which are used to determine the degree of matching between the station's traffic attributes and the surrounding functional attributes.

[0004] At the engineering application level, existing technologies can often only be used as auxiliary evaluation modules in research and analysis tools or consulting reports. They are difficult to directly generate structured results such as project screening, investment timing, connection and renovation sequencing, or phased development suggestions. Therefore, they are difficult to serve as independently deployable data processing and decision-making output capabilities.

[0005] Existing technologies include two-step move search or Gaussian two-step move search methods, which use stations as the supply side and population or facility grids as the demand side to calculate the supply-demand ratio and overall accessibility at specific thresholds. While these methods can reflect station service coverage, their output typically only addresses accessibility levels or blind spot identification, making it difficult to directly prioritize investment.

[0006] Existing technologies include site evaluation schemes that employ node-site models or coupling coordination degree models. These schemes typically use indicators such as station entrances / exits, station spacing, and transfer conditions to characterize node attributes, and indicators such as population, POI, building density, and development intensity to characterize site attributes, in order to determine whether the station's transportation function and the surrounding spatial function are coordinated. While these schemes can reflect the degree of site suitability, they are usually geared towards single-site diagnosis and lack a holistic assessment of corridor and area investment sequence.

[0007] Existing technologies also employ project prioritization schemes based on a single development intensity, a single passenger flow forecast, or a single economic indicator. These schemes typically use land use indicators, financial calculations, or local passenger flow forecasts to determine project priorities. While they have some practicality, they do not adequately consider transportation access conditions, spatial functional structure, and regional linkages. This can easily lead to misjudgments such as projects with weak transportation accessibility but excessively high development intensity, or projects with good transportation infrastructure but untapped spatial potential.

[0008] Therefore, existing technologies typically separate accessibility analysis, site evaluation, and development prioritization, lacking a complete decision-making chain from transportation access capacity to spatial development value and investment implementation priority. At the same time, existing solutions mostly remain at the analysis and diagnosis level, unable to directly answer the questions of which sites or corridors are more worthy of investment first and how to invest in them first. In addition, most existing solutions focus on a single site or corridor, lacking a linkage value measurement and priority generation mechanism at the site, corridor, and area levels, making it difficult to support actual decision-making for TOD, station-city development, and coordinated investment in transportation infrastructure.

[0009] Furthermore, even if there are multi-modal connection evaluation, spatial development evaluation, or hierarchical ranking schemes in the existing technologies, they usually process different connection modes, traffic indicators, and spatial indicators independently, or add suggestions manually after obtaining a single score result. There is a lack of technical solutions that link mode differentiation correction, nonlinear imbalance penalty, and cross-scale linkage correction into a unified decision-making mechanism.

[0010] Therefore, there is an urgent need for a method, device, and storage medium that can simultaneously integrate the characteristics of multi-mode connection, the carrying capacity of surrounding space, and the characteristics of development potential, and further generate investment implementation priorities for the development value measurement and investment implementation priorities of rail transit station corridor space. Summary of the Invention

[0011] This application provides a method, apparatus, and storage medium for measuring the development value of rail transit station corridor space and generating investment implementation priorities, which can solve the technical problems in the prior art of the separation of accessibility analysis and development prioritization, the inconsistency between station-level results and corridor-level results, and the difficulty in directly forming investment implementation strategies.

[0012] Firstly, this application provides a method for measuring the development value of rail transit station corridor space and generating investment implementation priorities, including: acquiring rail transit station data, rail line data, ground connection network data, population distribution data, employment distribution data, public service facility data, land use data, building development intensity data, and station attribute data within the target area; constructing a multi-mode connection network based on the ground connection network data; setting mode reliability coefficients and mode competition correction coefficients for different connection modes; and calculating the access convenience index of the target station, target corridor, or target space unit under different connection modes through a two-stage search calculation method that considers the supply and demand matching relationship and the distance attenuation relationship.

[0013] Based on the population distribution data, employment distribution data, public service facility data, land use data, building development intensity data, and site attribute data, spatial feature indicators characterizing the development potential of target sites, target corridors, or target spatial units are extracted. A station-corridor spatial value feature vector is constructed based on the access convenience index and the spatial feature indicators. Nonlinear coupling calculation and imbalance penalty calculation are then performed on the station-corridor spatial value feature vector to obtain a development value index. Based on the development value index, site-level, corridor-level, and area-level development value results are generated respectively, and the site-level, corridor-level, and area-level development value results are then linked and corrected.

[0014] Based on the results of the linkage correction and the preset constraints, an investment implementation priority ranking result is generated; based on the investment implementation priority ranking result, the development implementation type or connection improvement strategy is output.

[0015] According to the first aspect, in a first embodiment, the multimodal connection network includes at least two of a pedestrian connection network, a cycling connection network, and a public transport connection network.

[0016] According to the first aspect or the first implementation method, in the second implementation method, the access convenience index is obtained by a two-stage search calculation method that considers the supply and demand matching relationship and the distance attenuation relationship, and a mode reliability coefficient and a mode competition correction coefficient are set for different connection modes respectively; wherein, the mode reliability coefficient is used to characterize the differences in stability, timeliness or feasibility of different connection modes, and the mode competition correction coefficient is used to characterize the differences in the intensity of supply competition under different connection modes.

[0017] According to the second embodiment, in the third embodiment, the distance attenuation relationship adopts a continuous attenuation function, preferably a Gaussian attenuation function.

[0018] According to any one of the first to third embodiments, in the fourth embodiment, the target space unit Convenience of multi-mode access Represented as:

[0019] in, Indicates the connection mode. Indicates the total number of connection modes. Represents the reliability coefficient of the mode. Indicates site In shuttle mode The service supply ratio adjusted for supply and demand competition is as follows. ( ) represents the target space unit to station In shuttle mode The distance decay function.

[0020] According to any one of the first to fourth embodiments, in the fifth embodiment, the spatial characteristic indicators include at least two of the following: population density, employment intensity, public service facility density, facility mix, built-up area ratio, building density, node attribute indicators, and place attribute indicators.

[0021] According to any one of the first to fifth embodiments, in the sixth embodiment, the station corridor space value feature vector is coupled and calculated after unifying the dimensions, wherein the unified dimensions include one of range standardization, interval mapping standardization or translation standardization, and the coupled calculation includes the coupled enhancement calculation between traffic convenience and spatial potential.

[0022] According to the sixth implementation method, in the seventh implementation method, the standard value of the target object's traffic convenience is denoted as... The standard value of space potential is denoted as Its development value index Represented as:

[0023] in, and The weights for transportation convenience and space potential are respectively... + = 1; It serves as a coupling enhancement factor between transportation convenience and spatial potential; This represents the imbalance penalty coefficient.

[0024] According to the seventh embodiment, in the eighth embodiment, the coupling enhancement factor Represented as:

[0025] in, To prevent tiny constants with a denominator of zero.

[0026] According to any one of the first to eighth embodiments, in the ninth embodiment, an imbalance penalty term between transportation convenience and spatial potential is further introduced when calculating the development value index, so as to reduce the development value index of target objects whose difference between transportation convenience and spatial potential exceeds a preset range.

[0027] According to any one of the first to ninth embodiments, in the tenth embodiment, the preset constraints include one or more of the following: construction cost constraints, service deficiency constraints, development intensity constraints, passenger flow demand constraints, or policy constraints.

[0028] According to any one of the first to tenth embodiments, in the eleventh embodiment, the investment implementation priority ranking result includes at least two categories among priority development, connection reinforcement, functional cultivation, and postponement of implementation.

[0029] According to the eleventh implementation method, in the twelfth implementation method: when the development value index is not lower than the first threshold, and the access convenience and space potential are both not lower than the second threshold, it is determined to be a priority development type; when the development value index is not lower than the first threshold, and the space potential is higher than the third threshold but the access convenience is lower than the second threshold, it is determined to be a connection reinforcement type; when the development value index is in a preset middle range, and the access convenience meets the basic requirements but the space potential is insufficient, it is determined to be a function cultivation type; when the development value index is lower than the fourth threshold, or when the construction cost constraint and demand constraint are not met, it is determined to be a postponed implementation type.

[0030] According to any one of the first to twelfth embodiments, in the thirteenth embodiment, at least one of the mode reliability coefficient, mode competition correction coefficient, imbalance penalty coefficient, linkage correction weight, or threshold used to generate investment implementation priority ranking results is determined through a parameter calibration process. The parameter calibration process includes: obtaining a calibration sample set containing historical implementation types of the target object, manual evaluation types, or constraint satisfaction results; generating multiple sets of candidate parameter combinations within a preset candidate parameter range; and performing development value measurement and implementation type determination on the calibration sample set based on the candidate parameter combinations.

[0031] The matching degree between the judgment result and the known type or constraint satisfaction result in the calibration sample set is calculated, as well as the separation degree between adjacent implementation types; the candidate parameter combination that meets the preset matching degree and has the largest separation degree is selected as the target parameter combination.

[0032] According to any one of the first to thirteenth embodiments, in the fourteenth embodiment, the development implementation type or connection improvement strategy includes one or more of the following: comprehensive development, functional composite development, station-city integrated development, public transport connection optimization, slow-moving system reinforcement, shared mobility configuration, public service supplementation, or temporary suspension of construction, and the development implementation type or connection improvement strategy is automatically generated by the investment implementation priority ranking result; the output result further includes one or more of the following: target object identifier, development value index, corrected priority position, implementation type label, strategy label, constraint trigger label, benchmark evaluation type, benchmark ranking position, difference contribution field, or linkage correction reason field.

[0033] According to any one of the first to the fourteenth embodiments, in the fifteenth embodiment, in step S5, a site-level investment implementation priority, a corridor-level investment implementation priority, and a district-level investment implementation priority are generated respectively, and the three types of priorities are linked and corrected.

[0034] According to the fifteenth embodiment, in the sixteenth embodiment, the target site Value after linkage correction Represented as:

[0035] in, The site's original development value index. For the site The average development value index of the corridor is as follows: For the site The average development value index of the area is as follows: , and For linkage correction weights, and + + = 1.

[0036] According to the fifteenth or sixteenth implementation method, in the seventeenth implementation method, when the original development value index of the target site is higher than the preset value but the average development value index of the corridor or area to which it belongs is lower than the preset threshold, the investment implementation priority of the target site is downgraded; when the development value index of the target area is higher than the preset value and the access convenience of the associated site is lower than the preset threshold, the corresponding implementation type is changed from priority development to development after connection reinforcement.

[0037] Secondly, this application provides a device for measuring the development value of rail transit station corridor space and generating investment implementation priorities, comprising: a data acquisition module for acquiring rail transit station data, rail line data, road network data, ground public transport network data, slow traffic network data, population distribution data, employment distribution data, public service facility data, land use data, building development intensity data, and station attribute data within a target area; and an access convenience calculation module for constructing a multi-mode connection network based on the road network data, ground public transport network data, and slow traffic network data, and calculating the access convenience index of the target station, target corridor, or target space unit under different connection modes.

[0038] The spatial feature extraction module is used to extract spatial feature indicators that characterize the development potential of target sites, corridors, or spatial units; the value measurement module is used to construct a spatial value feature vector for stations and corridors, and obtain a development value index based on nonlinear coupling calculation and imbalance penalty calculation; the linkage correction module is used to generate development value results at the site, corridor, and area levels, and perform linkage correction; the priority generation module is used to generate investment implementation priority ranking results based on the results of linkage correction and preset constraints; the strategy output module is used to output development implementation type or connection improvement strategy based on the investment implementation priority ranking results, and generate a structured result set and interpretable output fields.

[0039] In some optional embodiments, this application also provides a system for measuring the development value of rail transit station corridor space and generating investment implementation priorities, including a server, a database, and a user terminal; the database is used to store data related to rail transit, transportation connections, population, employment, public service facilities, land use, and building development intensity; the server is used to execute the method described in the first aspect above; the user terminal is used to display the investment implementation priority ranking results, structured result sets, interpretable output fields, and corresponding development implementation types or connection improvement strategies.

[0040] In some alternative embodiments, this application also provides a computing device including a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, implements the method described in the first aspect above.

[0041] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect above.

[0042] The technical solution provided in this application, by constructing a multi-mode connection network and setting mode reliability coefficients and mode competition correction coefficients respectively, can more accurately characterize the actual service contribution of different connection modes in the station corridor space; by performing nonlinear coupling calculation of traffic convenience and spatial potential and introducing an imbalance penalty term, it can avoid the inflated scores of objects with imbalanced traffic and spatial characteristics; by linking and correcting the development value results at the station level, corridor level, and area level, and by correcting the priority of cross-scale conflict objects, it can improve the consistency and executability of the priority ranking results of multi-scale investment implementation.

[0043] By generating benchmark evaluation results, difference ranking, difference contribution fields, and linkage correction reason fields, the investment implementation priority ranking results can have an explainable source of difference compared with ordinary accessibility evaluation, node-site evaluation, or non-linkage correction evaluation. By mapping the priority ranking results to specific development implementation types or connection improvement strategies and outputting a machine-readable ranking result set, it can directly support the investment decision of rail transit station corridor space.

[0044] Furthermore, the technical solution provided in this application can output a site development priority list, a corridor phased implementation sequence list, a regional development implementation type list, and a list of connection reinforcement objects, so that this application can not only be used for technical analysis, but also as a commercial delivery capability for government departments, platform companies, rail companies, TOD development entities, and consulting agencies. Attached Figure Description

[0045] Figure 1 System architecture diagram.

[0046] Figure 2 Schematic diagram of the main process flow.

[0047] Figure 3 A schematic diagram illustrating the process of constructing and measuring the access convenience of a multi-mode connection network.

[0048] Figure 4 A schematic diagram illustrating the process of constructing the value feature vector of the station corridor space and calculating the development value index.

[0049] Figure 5 A schematic diagram of the investment implementation priority generation and implementation strategy matching process.

[0050] Figure 6 Schematic diagram of coordinated correction at the station level, corridor level, and area level.

[0051] Figure 7 Schematic diagram of the device structure.

[0052] Figure 8 Schematic diagram of the computing device. Detailed Implementation

[0053] The system architecture and application scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. Those skilled in the art will understand that, with the evolution of system architecture and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0055] like Figure 1 As shown in the embodiment of this application, the rail transit station corridor space development value measurement and investment implementation priority generation system 100 includes a data layer 110, an analysis and calculation layer 120, and a decision output layer 130. The data layer 110 is used to collect rail transit station data, rail line data, ground connection network data, population distribution data, employment distribution data, public service facility data, land use data, building development intensity data, and station attribute data. The analysis and calculation layer 120 is used to perform multi-mode access convenience calculation, spatial feature extraction, development value measurement, and linkage correction. The decision output layer 130 is used to generate investment implementation priority ranking results and output development implementation type or connection improvement strategy.

[0056] The data layer 110 includes a data acquisition submodule 111, a data cleaning submodule 112, and a spatial unit construction submodule 113. The data acquisition submodule 111 is used to acquire multi-source data; the data cleaning submodule 112 is used to perform missing value correction, coordinate unification, and outlier handling; the spatial unit construction submodule 113 is used to construct station units, grid units, corridor buffer units, or area units.

[0057] The analysis and calculation layer 120 includes an access convenience calculation submodule 121, a spatial feature extraction submodule 122, a value vector construction submodule 123, a development value index calculation submodule 124, and a linkage correction submodule 125. The access convenience calculation submodule 121 calculates access convenience under walking, cycling, and public transport connection modes respectively; the spatial feature extraction submodule 122 extracts population, employment, facility mix, building density, built-up area ratio, node attributes, and location attributes; the value vector construction submodule 123 unifies the dimensions of various indicators and constructs value feature vectors; and the development value index calculation submodule 124 performs nonlinear coupling calculations and imbalance penalty calculations.

[0058] The linkage correction submodule 125 is used to perform consistency correction on the results at the station level, corridor level, and area level.

[0059] The decision output layer 130 includes a priority generation submodule 131 and a strategy matching submodule 132. The priority generation submodule 131 is used to generate investment implementation priority ranking results based on the development value results after linkage correction and preset constraints; the strategy matching submodule 132 is used to output development implementation types or connection improvement strategies such as comprehensive development, connection reinforcement, functional cultivation, or postponement of implementation.

[0060] like Figure 2 As shown, the method for measuring the development value of rail transit station corridor space and generating investment implementation priorities provided in this application embodiment includes steps S201 to S207.

[0061] Step S201: Obtain data on rail transit stations, rail lines, ground connection networks, population distribution, employment distribution, public service facilities, land use, building development intensity, and station attributes within the target area.

[0062] Step S202: Construct a multi-mode connection network based on the ground connection network data, and calculate the access convenience index of the target site, target corridor or target space unit under different connection modes.

[0063] Step S203: Based on the population distribution data, employment distribution data, public service facility data, land use data, building development intensity data, and site attribute data, extract spatial characteristic indicators that characterize the development potential of the target site, target corridor, or target spatial unit.

[0064] Step S204: Construct a station corridor space value feature vector based on the access convenience index and the spatial feature index, and perform nonlinear coupling calculation and imbalance penalty calculation based on the station corridor space value feature vector to obtain the development value index.

[0065] Step S205: Generate site-level, corridor-level, and area-level development value results based on the development value index, and perform linkage correction on the site-level, corridor-level, and area-level development value results.

[0066] Step S206: Generate the investment implementation priority ranking result based on the results of the linkage correction and the preset constraints.

[0067] Step S207: Output the development implementation type or connection enhancement strategy based on the investment implementation priority ranking result.

[0068] like Figure 3 As shown, step S202 includes steps S311 to S315.

[0069] Step S311: Construct at least two of the following: a pedestrian shuttle network, a cycling shuttle network, and a public transport shuttle network. As one implementation, the pedestrian shuttle network, cycling shuttle network, and public transport shuttle network each employ different impedance parameters and search thresholds. Preferably, the pedestrian mode, cycling mode, and public transport mode may each employ different speed parameters or equivalent time impedance parameters.

[0070] Step S312: For each connection mode, calculate the supply and demand relationship with rail transit stations as the supply side and target space units as the demand side.

[0071] Step S313: Set a mode reliability coefficient and a mode competition correction coefficient for each connection mode. The mode reliability coefficient is used to reflect the differences in stability, timeliness, and feasibility among different connection modes; the mode competition correction coefficient is used to reflect the differences in the intensity of supply competition among different modes.

[0072] Step S314: Perform a two-stage search calculation based on the supply-demand matching relationship and the distance attenuation relationship to obtain the access convenience result for each connection mode. Preferably, the distance attenuation relationship adopts a continuous attenuation function, and more preferably, a Gaussian attenuation function.

[0073] Step S315: Merge the convenience results of each connection mode to obtain a multi-mode access convenience index for the target site, target corridor, or target space unit.

[0074] As a preferred implementation method, the target space unit Convenience of multi-mode access This can be expressed as formula (1):

[0075] in, Indicates the connection mode. Indicates the total number of connection modes. Represents the reliability coefficient of the mode. Indicates site In shuttle mode The service supply ratio adjusted for supply and demand competition is as follows. ( ) represents the target space unit to station In shuttle mode The distance decay function.

[0076] Furthermore, the site In shuttle mode Service supply ratio adjusted by supply and demand competition This can be expressed as formula (2):

[0077] in, Indicates site The supply of services Represents the competition correction coefficient of the mode. Representing the demand unit The intensity of demand.

[0078] As an feasible parameter scheme, the mode reliability coefficient and mode competition correction coefficient This can be determined through a parameter calibration process. Specifically, a calibration sample set can be constructed based on service stability indicators of connection modes, equivalent travel time fluctuation indicators, supply and demand competition intensity indicators, or manual assessment types; multiple sets of data can be generated within the candidate coefficient range. and Combine; calculate the access convenience ranking results under different candidate coefficient combinations respectively; determine the target coefficient combination based on the stability of the ranking results, the matching degree of known implementation types, or the matching degree of constraint satisfaction results.

[0079] When a calibration sample set is missing, the mode reliability coefficient The mode competition correction coefficient can be selected within the range of 0.20 to 0.60. It can be selected in the range of 0.50 to 1.50.

[0080] like Figure 4 As shown, steps S203 and S204 include steps S411 to S416.

[0081] Step S411: Extract spatial characteristic indicators representing development potential. Preferably, the spatial characteristic indicators include at least two of the following: population density, employment intensity, public service facility density, facility mix, built-up area ratio, building density, node attribute indicators, and place attribute indicators.

[0082] Step S412: Perform unified dimensional processing on the access convenience index and spatial characteristic index. One implementation method can be range standardization, interval mapping standardization, or translation standardization.

[0083] Step S413: Construct a value feature vector for the station corridor space. The value feature vector includes at least the dimensions of transportation convenience and spatial potential.

[0084] Step S414: Perform nonlinear coupling calculations on transportation convenience and spatial potential to reflect the degree of matching between the two.

[0085] Step S415: Based on the nonlinear coupling calculation results, an imbalance penalty term is introduced to suppress the excessively high scores obtained by target objects with large differences in traffic convenience and spatial potential.

[0086] Step S416: Obtain the development value index of the target site, target corridor, or target area.

[0087] As a preferred implementation method, the standard value for the traffic convenience of the target object is denoted as: The standard value of space potential is denoted as Its development value index This can be expressed as formula (3):

[0088] in, and The weights for transportation convenience and space potential are respectively... + = 1; It serves as a coupling enhancement factor between transportation convenience and spatial potential; This represents the imbalance penalty coefficient.

[0089] Furthermore, the coupling enhancement factor This can be expressed as formula (4):

[0090] in, To prevent tiny constants with a denominator of zero.

[0091] As an feasible parameter scheme, It can be from 0.30 to 0.70, preferably from 0.40 to 0.60; It can be from 0.30 to 0.70, preferably from 0.40 to 0.60; It can be from 0.10 to 0.60, preferably from 0.20 to 0.40; It can be between 0.0001 and 0.01.

[0092] Through the above design, this application avoids obtaining the development value index by simply weighting and summing, thereby reducing the risk of inflated scores for objects with imbalanced traffic and spatial characteristics.

[0093] like Figure 5 As shown, steps S206 and S207 include steps S511 to S516.

[0094] Step S511: Obtain one or more of the following constraints: construction cost, service shortcomings, development intensity, passenger flow demand, or policy constraints.

[0095] Step S512: Perform preliminary sorting of target objects based on the development value index.

[0096] Step S513: Determine the investment implementation type of the target object by combining preset thresholds and constraints.

[0097] Step S514: Match the corresponding development and implementation strategy or connection improvement strategy to different implementation types.

[0098] Step S515: Rank the investment implementation priorities of target sites, target corridors, or target areas.

[0099] Step S516: Output development and implementation types such as priority development, connection reinforcement, function nurturing or postponement, and corresponding strategy suggestions.

[0100] As a preferred implementation method, the investment implementation types include the following four categories:

[0101] 1. Priority Development Type: When the development value index is not lower than the first threshold, and the access convenience and space potential are both not lower than the second threshold, it is determined to be a priority development type;

[0102] 2. Connection Enhancement Type: When the development value index is not lower than the first threshold and the space potential is higher than the third threshold but the access convenience is lower than the second threshold, it is judged as connection enhancement type;

[0103] 3. Functional development type: When the development value index is in the preset middle range and the access convenience meets the basic requirements but the space potential is insufficient, it is judged as functional development type;

[0104] 4. Implementation Delayed: When the development value index is lower than the fourth threshold, or when both construction cost constraints and demand constraints are not met, it is determined to be an implementation delay.

[0105] As an implementable parameter scheme, the first threshold, second threshold, third threshold, and fourth threshold can be determined through a parameter calibration process. Specifically, multiple candidate threshold combinations can be generated within a preset candidate threshold range. Based on each candidate threshold combination, the implementation type of the calibration sample set is determined, and the matching degree between the determination result and the known implementation type, manual evaluation type, or constraint satisfaction result in the calibration sample set, as well as the separation degree between adjacent implementation types, are calculated. The candidate threshold combination that meets the preset matching degree and has the largest separation degree is selected as the target threshold combination.

[0106] When a calibration sample set is unavailable, the first threshold can be 0.65 to 0.80, the second threshold can be 0.50 to 0.70, the third threshold can be 0.60 to 0.80, and the fourth threshold can be 0.30 to 0.50.

[0107] As one implementation method, the corresponding development implementation type or connection improvement strategy includes one or more of the following: comprehensive development, functional composite development, station-city integrated development, public transport connection optimization, slow-moving system enhancement, shared mobility configuration, public service supplementation, or postponement of construction. It is automatically generated through pre-established priority-action mapping rules. The generated results can be further encapsulated into a structured result record containing target object identifier, development value index, corrected priority ranking, implementation type label, strategy label, constraint trigger label, benchmark evaluation type, benchmark ranking, difference contribution field, or linkage correction reason field.

[0108] The benchmark evaluation type is used to identify one of the following: general accessibility evaluation, node-site evaluation, or non-linkage correction evaluation. The benchmark ranking position is used to record the ranking result of the target object under the corresponding benchmark evaluation. The difference contribution field or linkage correction reason field is used to record the reasons for the ranking change, such as mode correction, imbalance penalty, constraint triggering, or cross-scale correction.

[0109] Preferably, the priority-action mapping rule includes at least:

[0110] When a target object is determined to be a priority development type, output at least one of the following: comprehensive development, functional composite development, or station-city integrated development, and record the corresponding priority development tag;

[0111] When the target object is determined to be a connection reinforcement type, output at least one of the following: bus connection optimization, slow traffic system reinforcement, or shared mobility configuration, and record the corresponding connection deficiency trigger tag.

[0112] When the target object is determined to be a function development target, output suggestions for public service supplementation or function import, and record the corresponding function development tag;

[0113] When the target object is determined to be of the type to be postponed, a suggestion to postpone construction is output, and the corresponding constraint failure label is recorded.

[0114] like Figure 6 As shown, step S205 includes steps S611 to S615.

[0115] Step S611: Generate site-level development value results, corridor-level development value results, and area-level development value results based on the development value index.

[0116] Step S612: Establish the attribution relationship between the station and the corridor, and the attribution relationship between the station and the area.

[0117] Step S613: Perform linkage correction based on the original development value index of the site, the average development value index of the corridor to which it belongs, and the average development value index of the area to which it belongs.

[0118] Step S614: Priority correction is performed on target objects that have cross-scale conflicts after linkage correction.

[0119] Step S615: Output the sorting results at the station level, corridor level, and area level after linkage correction.

[0120] As a preferred implementation method, the target site Value after linkage correction This can be expressed as formula (5):

[0121] in, The site's original development value index. For the site The average development value index of the corridor is as follows: For the site The average development value index of the area is as follows: , and For linkage correction weights, and + + = 1.

[0122] As an feasible parameter scheme, , and This can be determined through a parameter calibration process. Specifically, it can be determined when the following conditions are met. + + Multiple candidate linkage correction weights are generated from the candidate weight set with a value of 1. The station-level, corridor-level, and area-level priority consistency indices are calculated for each candidate linkage correction weight. The candidate weight combination that reduces the number of cross-scale conflicting objects and meets the preset priority consistency index requirements is selected as the target linkage correction weight. When a calibration sample set is lacking... It can be between 0.30 and 0.70. It can be between 0.10 and 0.40. It can be between 0.10 and 0.40.

[0123] Furthermore, when the original development value index of a target site is higher than the preset value but the average development value index of its corridor or area is lower than the preset threshold, the investment priority of the target site will be downgraded; when the development value index of the target area is higher than the preset value and the access convenience of the associated site is lower than the preset threshold, the corresponding implementation type will be changed from priority development to development after connection reinforcement.

[0124] like Figure 7 As shown, the device 700 provided in this application embodiment includes a data acquisition module 710, an access convenience calculation module 720, a spatial feature extraction module 730, a value measurement module 740, a linkage correction module 750, a priority generation module 760, and a strategy output module 770.

[0125] The data acquisition module 710 is used to acquire data on rail transit stations, rail lines, road networks, ground public transport networks, slow-moving traffic networks, population distribution, employment distribution, public service facilities, land use, building development intensity, and station attribute data within the target area.

[0126] The access convenience calculation module 720 is used to construct a multi-mode connection network based on the road network data, ground public transport network data and slow traffic network data, and to calculate the access convenience index of the target station, target corridor or target spatial unit under different connection modes.

[0127] The spatial feature extraction module 730 is used to extract spatial feature indicators that characterize the development potential of target sites, target corridors, or target spatial units.

[0128] The value measurement module 740 is used to construct the value feature vector of the station corridor space and obtain the development value index based on nonlinear coupling calculation and imbalance penalty calculation.

[0129] The linkage correction module 750 is used to generate site-level, corridor-level, and area-level development value results and perform linkage correction.

[0130] The priority generation module 760 is used to generate investment implementation priority ranking results based on the results of linkage correction and preset constraints.

[0131] The strategy output module 770 is used to output the development implementation type or connection enhancement strategy based on the investment implementation priority ranking result.

[0132] like Figure 8 The diagram shows a structural schematic of a computing device 800 suitable for implementing embodiments of this application. The computing device 800 includes a processor 810, a memory 820, an input / output interface 830, and a communication interface 840. The processor 810 can execute program instructions stored in the memory 820 to implement the method for measuring the development value of rail transit station corridor space and generating investment implementation priorities as described in the above embodiments.

[0133] The memory 820 can be used to store data on rail transit stations, lines, road networks, ground public transport networks, slow-moving traffic networks, population distribution, employment distribution, public service facilities, land use, building development intensity, station attribute data, and program code.

[0134] The input / output interface 830 can be used to receive user input constraints, threshold configurations, and scenario parameters, and output the investment implementation priority ranking results and the corresponding development implementation type or connection improvement strategy.

[0135] The communication interface 840 can be used to interact with databases, business platforms, or user terminals.

[0136] In one implementation, the evaluation targets multiple rail transit stations within the metropolitan area. As a practical data implementation method, the target area is the Beijing-Tianjin-Hebei metropolitan area's urban (suburban) railway network. The basic data includes records of 38 suburban railway stations and 8 lines, namely the Tongmi Line, Huaimi Line, Sub-center Line, S2, Beijing-Xiong'an Line, Beijing-Tianjin Line, Beijing-Guangzhou Line, and Beijing-Shanghai Line. The data scope includes population, employment, POI, buildings, land use, road network, public transport network, and pedestrian network data within a certain service radius of the stations; connection modes include walking, cycling, and public transport; output types include priority development, connection enhancement, functional development, and deferred implementation.

[0137] First, the multi-modal connection conditions and spatial development potential characteristics around each station are obtained. Then, using 8312 grid records as demand-side spatial units, accessibility indicators are calculated based on accessibility results including POP, walking AI, cycling AI, public transport AI, and comprehensive fields. Next, the station accessibility index records, node value records, place value records, and coupling coordination records of 38 stations are mapped into station corridor spatial value feature vectors, and development value indices are calculated. Afterward, station investment priorities are formed by combining cost constraints and service shortcomings. Finally, development strategy recommendations for different stations are output.

[0138] In the above-described practical data implementation, the site accessibility index record may include the Name, Shape_Area, and AJ fields.

[0139] Among them, the Name field is the site name field, the Shape_Area field is the spatial area field in the data table, and the AJ field is the site accessibility index field, which is used to represent the original value of the site-level comprehensive access convenience of the corresponding site; AJ is the original data field name and is not used as a mathematical symbol defined separately in this application.

[0140] In subsequent sample parameter configurations, the AJ field can be standardized by range to obtain the standard value of transportation convenience. .

[0141] For example, the AJ value at Beijing West Railway Station is 0.003182, at Beijing South Railway Station it is 0.002324, at Beijing Railway Station it is 0.002185, and at Beijing North Railway Station it is 0.002174.

[0142] Node-site and coupling coordination records may include fields such as Name, Node Price, Site Price, Overall Price, D, and Coupling Coordination Site Class. For example, Beijing South Station has a node price of 0.527927, a site price of 0.471849, and D of 0.706471, with a site class of Development-Guiding Site; Bazhou North Station has a node price of 0.121003, a site price of 0.038892, and D of 0.261917, with a site class of Connection-Optimization Site.

[0143] In this implementation, the station accessibility index or comprehensive accessibility value can be used as the benchmark for transportation convenience. At least two of the following are considered as spatial potential characteristics: node value, location value, comprehensive value, POI mix, and population or building density. A development value index is generated according to the aforementioned nonlinear coupling and imbalance penalty method. The structured result set can also record the accessibility benchmark ranking, node-location benchmark ranking, corrected priority ranking, difference contribution field, and linkage correction reason field. This implementation method can distinguish between priority development sites with strong transportation convenience and high development potential, and connection reinforcement sites with high spatial potential but weak connectivity.

[0144] In one implementation, the evaluation targets multiple rail transit corridors. The evaluation unit employs a corridor buffer zone unit or a corridor control area unit. As a practical data implementation method, the route records include the Tongmi Line, Huaimi Line, Sub-center Line, S2, Beijing-Xiong'an Line, Beijing-Tianjin Line, Beijing-Guangzhou Line, and Beijing-Shanghai Line. The route length field can be used to form the basic constraints at the corridor scale. Value characteristics include the comprehensive access convenience of the station clusters within the corridor, population and employment scale, facility mix, and development intensity. Output types include near-term priority implementation, medium-term development implementation, and long-term reserved implementation.

[0145] First, the indicators of each station are aggregated according to the corridor; then, the accessibility blind spot classification results are used to identify the corridor service shortcomings of 8312 grid records, and the corridor service shortcomings constraints are formed by combining the two-kilometer blind spot sub-objects; next, the corridor-level development value index is formed; then, it is sorted according to the investment scale and service shortcomings constraints; finally, the phased implementation sequence of the corridor is output.

[0146] This implementation method avoids determining the construction sequence of the entire corridor based solely on the conditions of a single station, making it more suitable for coordinated investment decisions on regional transportation and land use.

[0147] In one implementation, the evaluation object is multiple development zones or gridded spatial units surrounding the station. Constraints include development intensity constraints, land use compatibility constraints, and public service deficiency constraints. As a practical data implementation method, area-level service deficiencies can be identified based on the POP, walking AI, cycling AI, public transport AI, and comprehensive fields in the comprehensive accessibility results, as well as the accessibility blind field in the accessibility blind spot classification results. Furthermore, based on the station category field in the station classification optimization results, related stations can be classified into development-oriented stations, development and construction-oriented stations, or connection optimization-oriented stations. Output types include comprehensive development type, connection enhancement type, functional cultivation type, and controlled development type.

[0148] First, construct area-level spatial units; then, calculate the access convenience and spatial development potential of each area; next, generate an area development value index; then, automatically match implementation strategies based on different value index ranges and constraints; finally, output area-level development recommendations.

[0149] This implementation method allows for a further refinement of whether development is worthwhile to determine how development is appropriate, thereby enhancing the direct application value of the technical solution presented in this application.

[0150] In the above embodiments, the site category field in the actual data includes three types: guiding development sites, development and construction sites, and connection optimization sites, with 5 guiding development sites, 22 development and construction sites, and 11 connection optimization sites. The coupling coordination field in the actual data includes types such as high-quality coordination, intermediate coordination, primary coordination, and near-discord, with 22 primary coordinations, 11 near-discord, 4 intermediate coordinations, and 1 high-quality coordination. The above classification results can be used as the basic data or verification data for generating implementation type labels, constraint trigger labels, and linkage correction reason fields in this application.

[0151] As an example parameter configuration, the result of the station accessibility index after range standardization can be used as the transportation convenience, and the node-location comprehensive value can be used as the spatial potential. = 0.5、 = 0.5、 = 0.3, and is adjusted in conjunction with the site benchmark development value index weight of 0.8 and the average value of the corridor to which it belongs of 0.2. Under this example parameter configuration, Beijing West Station's accessibility benchmark ranking is 1st, and its adjusted priority ranking is 2nd; Tianjin Station's node-site benchmark ranking is 1st, and its adjusted priority ranking is 5th; Langfang Station's node-site benchmark ranking is 6th, its accessibility benchmark ranking is 31st, and its implementation type label is connection reinforcement type.

[0152] Therefore, the structured result set can reflect the ranking differences after the combined effects of accessibility benchmark evaluation, node-site benchmark evaluation, imbalance penalty and corridor linkage correction.

[0153] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for measuring the development value of rail transit station corridor space and generating investment implementation priorities, characterized in that, include: Acquire data on rail transit stations, rail lines, ground connection networks, population distribution, employment distribution, public service facilities, land use, building development intensity, and station attributes within the target area; A multi-mode connection network is constructed based on the ground connection network data. Mode reliability coefficient and mode competition correction coefficient are set for different connection modes. The access convenience index of target sites, target corridors or target spatial units under different connection modes is calculated by considering the supply and demand matching relationship and the distance attenuation relationship in a two-stage search calculation method. Based on the population distribution data, employment distribution data, public service facility data, land use data, building development intensity data, and site attribute data, spatial characteristic indicators that characterize the development potential of target sites, target corridors, or target spatial units are extracted. Based on the access convenience index and the spatial characteristic index, a station corridor spatial value feature vector is constructed, and nonlinear coupling calculation and imbalance penalty calculation are performed based on the station corridor spatial value feature vector to obtain the development value index. Based on the development value index, site-level, corridor-level, and area-level development value results are generated respectively, and the site-level, corridor-level, and area-level development value results are linked and corrected. Based on the results of the linkage correction and the preset constraints, an investment implementation priority ranking result is generated; The development implementation type or connection enhancement strategy is output based on the investment implementation priority ranking results.

2. The method according to claim 1, characterized in that, The multi-mode connection network includes at least two of the following: a pedestrian connection network, a cycling connection network, and a public transport connection network; the mode reliability coefficient is used to characterize the differences in stability, timeliness, or feasibility of different connection modes; the mode competition correction coefficient is used to characterize the differences in supply competition intensity under different connection modes; the distance attenuation relationship adopts a continuous attenuation function, preferably a Gaussian attenuation function.

3. The method according to claim 2, characterized in that, Target space unit Multimode access convenience is represented as: in, Indicates the connection mode. Indicates the total number of connection modes. Represents the reliability coefficient of the mode. Indicates site In shuttle mode The service supply ratio adjusted for supply and demand competition is as follows. ( ) represents the target space unit to station In shuttle mode The distance decay function. The station In the transfer mode The service supply ratio after the supply-demand competition correction Is expressed as: in, Indicates site The supply of services Represents the competition correction coefficient of the mode. Representing the demand unit The intensity of demand.

4. The method of claim 1, wherein, The spatial characteristic indicators include at least two of the following: population density, employment intensity, public service facility density, facility mix, built-up area ratio, building density, node attribute indicators, and place attribute indicators; the station corridor spatial value feature vector is coupled and calculated after unifying the dimensions, the unified dimensions include one of range standardization, interval mapping standardization, or translation standardization, and the coupled calculation includes the coupled enhancement calculation between traffic convenience and spatial potential.

5. The method according to claim 4, characterized in that, The standard value for the traffic convenience of the target object is denoted as The standard value of space potential is denoted as Its development value index Represented as: in, and The weights for transportation convenience and space potential are respectively... + = 1; It serves as a coupling enhancement factor between transportation convenience and spatial potential; This represents the imbalance penalty coefficient. The coupling enhancement factor is represented as: wherein Is a small constant to prevent the denominator from being zero. Furthermore, when calculating the development value index, a penalty term for imbalance between transportation convenience and spatial potential is introduced to reduce the development value index of target objects whose difference between transportation convenience and spatial potential exceeds a preset range.

6. The method of claim 1, wherein, The preset constraints include one or more of the following: construction cost constraints, service deficiency constraints, development intensity constraints, passenger flow demand constraints, or policy constraints; the investment implementation priority ranking results include at least two of the following: priority development, connection enhancement, functional cultivation, and postponement; wherein: when the development value index is not lower than the first threshold, and both access convenience and space potential are not lower than the second threshold, it is determined to be priority development; when the development value index is not lower than the first threshold, and the space potential is higher than the third threshold but the access convenience is lower than the second threshold, it is determined to be connection enhancement; when the development value index is in the preset middle range, and the access convenience meets the basic requirements but the space potential is insufficient, it is determined to be functional cultivation; when the development value index is lower than the fourth threshold, or both construction cost constraints and demand constraints are not met, it is determined to be postponement.

7. The method according to claim 1 or 6, characterized in that, At least one of the following factors—the model reliability coefficient, the model competition correction coefficient, the imbalance penalty coefficient, the linkage correction weight, or the threshold used to generate the investment implementation priority ranking result—is determined through a parameter calibration process. This parameter calibration process includes: acquiring a calibration sample set containing historical implementation types, manual evaluation types, or constraint satisfaction results of the target object; generating multiple candidate parameter combinations within a preset candidate parameter range; measuring the development value and determining the implementation type of the calibration sample set based on the candidate parameter combinations; calculating the matching degree between the determination result and the known types or constraint satisfaction results in the calibration sample set, as well as the separation degree between adjacent implementation types; and selecting the candidate parameter combination that meets the preset matching degree and has the largest separation degree as the target parameter combination.

8. The method of claim 1, wherein, The development implementation type or connection improvement strategy includes one or more of the following: comprehensive development, functional composite development, station-city integrated development, public transport connection optimization, slow-moving system enhancement, shared mobility configuration, public service supplementation, or postponement of construction. The development implementation type or connection improvement strategy is automatically generated by matching the investment implementation priority ranking result. The automatic matching generation process includes determining the corresponding strategy label based on the priority type label or constraint trigger label; generating station-level investment implementation priority, corridor-level investment implementation priority, and area-level investment implementation priority based on the development value index; and performing linkage correction on the three priority types. Target site The linkage-corrected value is expressed as: in, The site's original development value index. For the site The average development value index of the corridor is as follows: For the site The average development value index of the area is as follows: , and For linkage correction weights, and + + = 1. When the original development value index of a target site is higher than the preset value, but the average development value index of its corridor or area is lower than the preset threshold, the investment priority of the target site will be downgraded; when the development value index of the target area is higher than the preset value and the access convenience of the associated site is lower than the preset threshold, the corresponding implementation type will be changed from priority development to development after connection reinforcement. The investment implementation priority ranking results are output in the form of a structured result set, which includes at least three of the following: target object identifier, development value index, corrected priority ranking, implementation type label, strategy label, constraint trigger label, benchmark evaluation type, benchmark ranking ranking, difference contribution field, or linkage correction reason field.

9. A device for measuring the development value of rail transit station corridor space and generating investment implementation priorities, characterized in that, include: The data acquisition module is used to acquire data on rail transit stations, rail lines, ground connection networks, population distribution, employment distribution, public service facilities, land use, building development intensity, and station attributes within the target area. The access convenience calculation module is used to construct a multi-mode access network based on the ground access network data, and to calculate the access convenience index of the target site, target corridor or target space unit under different access modes respectively. The spatial feature extraction module is used to extract spatial feature indicators that characterize the development potential of target sites, target corridors, or target spatial units. The value measurement module is used to construct the value feature vector of the station corridor space and obtain the development value index based on nonlinear coupling calculation and imbalance penalty calculation. The linkage correction module is used to generate development value results at the site, corridor, and area levels, and to perform linkage correction. The priority generation module is used to generate investment implementation priority ranking results based on the results of linkage correction and preset constraints. The strategy output module is used to output the development implementation type or connection improvement strategy according to the investment implementation priority ranking result, and generate a structured result set and interpretable output fields.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 8.

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