Street jogging network supply and demand evaluation and optimization method for high-density urban area

Abstract

The invention relates to the technical field of urban governance and management, in particular to a street jogging network supply and demand evaluation and optimization method for a high-density urban area, and the method comprises the steps: constructing a street jogging network supply and demand evaluation system; obtaining multi-source city data of a supply layer index set and a demand layer index set corresponding to each basic space unit in the target area, and respectively calculating a supply layer comprehensive evaluation index and a demand layer comprehensive evaluation index of each basic space unit in combination with a preset weight vector; calculating a supply-demand collaboration degree value and a supply-demand difference value representing a supply-demand balance state by using the supply layer comprehensive evaluation index and the demand layer comprehensive evaluation index, and taking the supply-demand collaboration degree value and the supply-demand difference value as a supply-demand evaluation result; and determining the update priority of the basic space unit according to the supply and demand evaluation result, and backtracking the short board factor in the supply layer index set for the unit with high update priority to generate a street jogging network optimization guide strategy. According to the invention, the demand of high-density urban area refined update decision making can be met.

Description

Technical Field

[0001] This application relates to the field of urban governance and management technology, and in particular to a method for evaluating and optimizing the supply and demand of street jogging networks in high-density urban areas. Background Technology

[0002] In densely populated urban areas, the increasing scarcity of land resources makes it extremely costly to add large-scale formal fitness venues such as athletic fields and sports parks, resulting in a supply of public fitness services that often fails to meet the growing demand from residents. Against this backdrop, running, due to its lower requirements for venues and facilities, is gradually shifting from professional venues to urban public spaces. The Street Jogging Network (SJN) refers to the use of the most extensive and frequently used linear street spaces in the city, within the context of informal sports land, to transform them into fitness networks capable of accommodating residents' daily running needs through multifunctional utilization.

[0003] Currently, the evaluation and optimization of street jogging networks mainly rely on the analysis of the physical characteristics of the urban built environment. At the evaluation level, existing technologies typically utilize multi-source geographic information data and running trajectory data to analyze the correlation between environmental factors such as green view rate and road width and running popularity, thereby determining the quality of the environment in specific road sections. At the optimization level, targeted improvements to the physical environment of specific road sections are often made based on runner preference factors shown in the evaluation results or by referring to general street design guidelines. For example, simply increasing green vegetation or improving pavement in high-population sections.

[0004] However, the aforementioned existing technologies have limitations in the process of transforming evaluation into optimization. Because the existing evaluation system only focuses on the static attributes of the street's physical environment quality, it fails to compare the objective supply capacity of facilities with the actual population density and intensity of movement demand within the area, thus failing to reflect the balanced distribution of facility resources across the macro-region. This lack of a supply-demand coordinated evaluation mechanism makes it difficult to determine the priority of renewal sequences for different urban units when formulating optimization strategies, and also makes it difficult to identify the core shortcomings causing supply lags in specific units. Consequently, the final optimization direction lacks targeted spatial guidance and specific element support, making it difficult to meet the needs of refined renewal decisions in high-density urban areas. Summary of the Invention

[0005] This application provides a method for evaluating and optimizing the supply and demand of street jogging networks in high-density urban areas. The constructed evaluation system can accurately reflect the degree of matching between the objective supply capacity of facilities and the subjective usage needs of residents, and accurately locate the core shortcomings leading to supply lags. This allows the final optimization direction to have targeted spatial guidance and specific element support, thus meeting the needs of refined urban renewal decision-making in high-density urban areas. This application provides the following technical solution: Firstly, this application provides a method for evaluating and optimizing the supply and demand of street jogging networks in high-density urban areas, the method comprising: A supply and demand evaluation system for a street jogging network based on preset evaluation factors is constructed. The supply and demand evaluation system divides the evaluation factors into a supply-level indicator set that represents the objective level of urban space supply services and a demand-level indicator set that represents the subjective needs of residents. Obtain multi-source city data corresponding to the supply-layer indicator set and the demand-layer indicator set for each basic spatial unit within the target area, and calculate the supply-layer comprehensive evaluation index and the demand-layer comprehensive evaluation index for each basic spatial unit by combining the preset weight vector. The supply-demand coordination value and the supply-demand difference, which characterize the supply-demand balance state, are calculated using the supply-side comprehensive evaluation index and the demand-side comprehensive evaluation index, and the supply-demand coordination value and the supply-demand difference are used as the supply-demand evaluation results. Based on the supply and demand evaluation results, the update priority of each basic spatial unit is determined, and the shortcoming factors in the supply layer indicator set are traced back for units with high update priority to generate a street jogging network optimization guidance strategy.

[0006] In a specific feasible implementation, the supply and demand evaluation system divides the evaluation factors into a supply-level indicator set that characterizes the objective level of urban spatial service supply and a demand-level indicator set that characterizes the subjective needs of residents, including: The supply-layer indicator set that characterizes the objective level of urban spatial service supply includes road network density, number of intersections, number of traffic lights, multimodal transportation connectivity, park accessibility, water accessibility, sports venue accessibility, service facility accessibility, residential area accessibility, green view rate, sky visibility rate, road slope, winter and summer temperatures, PM2.5, noise, number of lighting facilities, nighttime light intensity, congestion, traffic flow risk, and road width. The set of demand-level indicators representing subjective residents' usage needs includes running route popularity, recommended route popularity, population density, age characteristics, and gender structure.

[0007] In a specific feasible implementation, the construction of a supply and demand evaluation system for the street jogging network based on preset evaluation factors includes: Establish a multi-level hierarchical structure model, with the preset evaluation factors as the bottom indicator layer, the supply layer and the demand layer as the top target layer, and a criterion layer between the indicator layer and the target layer. When constructing the supply-side evaluation system, road network density, number of intersections, and number of traffic lights are mapped to the spatial structure and connectivity criteria layer; multimodal transportation connectivity and various accessibility indicators are mapped to the destination and service accessibility criteria layer; green view rate, sky visibility, road slope, temperature and humidity, PM2.5, and noise are mapped to the environmental comfort and landscape experience criteria layer; the number of lighting facilities, night light intensity, congestion, traffic flow risk, and road width are mapped to the safety and management guarantee criteria layer. When constructing the demand-side evaluation system, the popularity of running routes and the popularity of recommended routes are mapped to the running popularity criteria layer; population density, age characteristics, and gender structure are mapped to the population characteristics criteria layer. Based on the established hierarchical structure, the importance of each indicator under the same criterion layer is compared using a preset weight calculation method, and weights are assigned to different criterion layers, assigning a weight value to each evaluation factor; the clear hierarchical structure and the corresponding set of weight values ​​together constitute the supply and demand evaluation system for the street jogging network.

[0008] In a specific feasible implementation, the calculation of the supply-side comprehensive evaluation index and the demand-side comprehensive evaluation index of each basic spatial unit by combining a preset weight vector includes: The supply-side comprehensive evaluation index of each basic spatial unit is obtained by multiplying the normalized values ​​of each evaluation factor in the supply-side indicator set with their corresponding weights and summing the results. The formula is shown below: ; The normalized values ​​of each evaluation factor in the demand layer index set for each basic spatial unit are multiplied by their corresponding weights and summed to obtain the comprehensive demand layer evaluation index for that unit; the comprehensive demand layer evaluation index is then calculated. The formula is shown below: ; in, The total number of evaluation factors is 21 when calculating the supply-side index and 5 when calculating the demand-side index. The index representing the evaluation factor; Representing the The preset weight values ​​of each evaluation factor Representing the The standardized values ​​of each evaluation factor after normalization.

[0009] In a specific implementation scheme, the calculation of the supply-demand coordination value and the supply-demand difference value, which characterize the supply-demand balance state, using the supply-side comprehensive evaluation index and the demand-side comprehensive evaluation index includes: Calculate the coupling degree of the supply and demand system The calculation formula is as follows: ; Calculate the comprehensive coordination index of the supply and demand system The calculation formula is as follows: ; in, and The coefficients are undetermined, representing the relative importance of supply and demand; the supply-demand synergy value is calculated based on the coupling degree and the comprehensive synergy index. The calculation formula is as follows: ; Calculate the supply and demand difference The calculation formula is as follows: .

[0010] In one specific implementation scheme, determining the update priority of each basic spatial unit based on the supply and demand evaluation results includes: Based on the supply and demand difference Determine the direction of the supply-demand imbalance: when When the current basic spatial unit is determined to be in a state of supply lag, that is, the facility service level cannot meet the actual needs of runners, it belongs to the target area that needs to be optimized. when When the current basic spatial unit is determined to be in a state of demand lag or supply-demand balance, the update priority is set to low. In regions identified as experiencing supply lag, the supply-demand coordination value is used as a basis. Classify update urgency levels: When When the current basic spatial unit is determined to be in a state of severe imbalance, its update priority is set to the highest level, indicating that immediate intervention is urgently needed; when When the current basic spatial unit is determined to be in a state of imminent imbalance, its update priority is set to a higher level, representing a key update target; when When the current basic spatial unit is determined to be in a highly collaborative state, its update priority is set to medium, indicating that it can be considered as a reserve target for long-term optimization; among which, Less than ,and and All are between 0 and 1.

[0011] In a specific feasible implementation, the step of generating a street jogging network optimization guidance strategy by backtracking the bottleneck factors in the supply layer indicator set of units with high update priority includes: Retrieve the normalized values ​​of each evaluation factor in the supply layer used for calculation in the selected priority update units; The retrieved values ​​are compared with the preset scoring threshold, or the scores of each evaluation factor are sorted within the unit to identify the few evaluation factors with the lowest scores or those below the average level, and these are defined as the bottleneck factors that cause the supply lag in the unit. Based on the identified bottleneck factors and their corresponding criterion layer dimensions, targeted optimization guidance strategies for street jogging networks are generated.

[0012] Secondly, this application provides a supply and demand evaluation and optimization system for street jogging networks in high-density urban areas, employing the following technical solution: A supply and demand evaluation and optimization system for street jogging networks in high-density urban areas, comprising: The evaluation system construction module is used to construct a supply and demand evaluation system for street jogging networks based on preset evaluation factors. The supply and demand evaluation system divides the evaluation factors into a supply-level indicator set that represents the objective level of urban space supply services and a demand-level indicator set that represents the subjective needs of residents. The evaluation index calculation module is used to obtain multi-source city data corresponding to the supply-layer indicator set and the demand-layer indicator set for each basic spatial unit within the target area, and calculate the supply-layer comprehensive evaluation index and the demand-layer comprehensive evaluation index for each basic spatial unit in combination with the preset weight vector. The evaluation result generation module is used to calculate the supply-demand coordination value and the supply-demand difference, which represent the supply-demand balance state, using the supply-side comprehensive evaluation index and the demand-side comprehensive evaluation index, and to use the supply-demand coordination value and the supply-demand difference as the supply-demand evaluation result; The optimization strategy generation module is used to determine the update priority of each basic spatial unit based on the supply and demand evaluation results, and to backtrack the bottleneck factors in the supply layer indicator set for units with high update priority to generate a street jogging network optimization guidance strategy.

[0013] Thirdly, this application provides an electronic device, the device including a processor and a memory; the memory stores a program, the program being loaded and executed by the processor to implement a supply and demand evaluation and optimization method for street jogging networks in high-density urban areas as described in the first aspect.

[0014] Fourthly, this application provides a computer-readable storage medium storing a program that, when executed by a processor, is used to implement a method for evaluating and optimizing the supply and demand of a street jogging network in a high-density urban area as described in the first aspect.

[0015] This application provides a method for evaluating and optimizing the supply and demand of street jogging networks in high-density urban areas. The method first constructs a supply and demand evaluation system based on preset evaluation factors, dividing these factors into a supply-layer indicator set representing the objective level of urban spatial service provision and a demand-layer indicator set representing subjective residents' usage needs. Second, it acquires multi-source urban data for each basic spatial unit within the target area and calculates comprehensive evaluation indices for the supply and demand layers using preset weight vectors. Then, it uses these indices to calculate the supply-demand synergy value and supply-demand difference, representing the supply-demand balance, as evaluation results. Finally, it determines the renewal priority of each basic spatial unit based on the evaluation results and backtracks the shortcomings in the supply-layer indicator set for high-priority units to generate optimization guidance strategies. Through this technical solution, this application achieves quantitative assessment and diagnosis of urban spatial units from both supply and demand dimensions. The constructed evaluation system accurately reflects the matching degree between the objective supply capacity of facilities and the subjective usage needs of residents and precisely identifies the core shortcomings leading to supply lags. This ensures that the final optimization guidance has targeted spatial guidance and specific element support, meeting the needs of refined renewal decisions in high-density urban areas.

[0016] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, the preferred embodiments of this application are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the supply and demand evaluation and optimization method for street jogging networks in high-density urban areas, as described in this application.

[0018] Figure 2 This is a structural block diagram of the supply and demand evaluation and optimization system for street jogging networks in high-density urban areas, as described in this application embodiment.

[0019] Figure 3 This is a block diagram of an electronic device used for supply and demand evaluation and optimization of street jogging networks in high-density urban areas, as described in this application. Detailed Implementation

[0020] The specific embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but are not intended to limit the scope of this application.

[0021] Optionally, this application uses the method for evaluating and optimizing the supply and demand of street jogging networks in high-density urban areas provided in various embodiments as an example for application in electronic devices. The electronic device is a terminal or a server. The terminal can be a computer, tablet computer, etc. This embodiment does not limit the type of electronic device.

[0022] Reference Figure 1 This is a flowchart illustrating a method for evaluating and optimizing the supply and demand of street jogging networks in high-density urban areas, provided in an embodiment of this application. The method includes at least the following steps: Step S101: Construct a supply and demand evaluation system for the street jogging network based on preset evaluation factors. The supply and demand evaluation system divides the evaluation factors into a supply-level indicator set that represents the objective level of urban space supply services and a demand-level indicator set that represents the subjective needs of residents.

[0023] In step S101, the main task is to establish basic standards for quantitatively evaluating the service status of the street jogging network (SJN). To address the problem that existing technologies only focus on environmental physical attributes while neglecting the balance between supply and demand, this embodiment establishes a two-tiered evaluation system encompassing both the supply and demand sides. By explicitly dividing the evaluation factors into supply-side and demand-side indicator sets, independent measurements can be taken from two dimensions: the objective carrying capacity of the urban built environment and the subjective intensity of residents' actual exercise needs.

[0024] Specifically, the pre-set evaluation factors cover all key elements affecting the experience and demand of street jogging, divided into supply-side evaluation factors and demand-side evaluation factors. First, the supply-side evaluation factors, which characterize the objective level of urban spatial service supply, mainly include the following: Road network density refers to the total length of roads, greenways, and trails per unit area, reflecting the spatial coverage level of jogging routes; the number of intersections refers to the total number of intersection nodes in the jogging route network, characterizing the connectivity efficiency and route selection diversity of the route; the number of traffic lights refers to the number of traffic control facilities along the jogging route that require passive interruption, directly reflecting the continuity of the running process; multimodal transportation connectivity refers to the spatial connection convenience between the jogging network and public transportation stations, usually quantified by the density of public transportation points of interest; park accessibility, water accessibility, sports venue accessibility, service facility accessibility, and residential area accessibility all refer to the Euclidean distance from any point on the route or in the residential area to the corresponding location; the shorter the distance, the more convenient the service; green view rate refers to the proportion of vegetation in the jogger's field of vision, characterizing the natural experience in the visual dimension; sky visibility... The following metrics are used to measure the jogger's comfort level: **Ratio:** The openness of the sky in the jogger's field of vision at an upward angle, used to measure spatial confinement and lighting comfort; **Road Slope:** The average or maximum longitudinal slope angle of the path, affecting energy consumption and safety during running; **Winter / Summer Temperature:** The average of the highest summer temperature and lowest winter temperature along the running path, used to measure the suitability of the thermal environment for running; **PM2.5:** The annual average concentration of fine particulate matter in the air surrounding the path, used to assess respiratory health risks; **Noise Level:** The equivalent sound level of the ambient noise along the path during jogging hours, used to measure auditory comfort; **Number of Lighting Facilities:** The density of streetlights per unit length of the jogging path at night, used to ensure nighttime visibility; **Nighttime Light Intensity:** The intensity of nighttime light radiation from satellite remote sensing, used to indirectly reflect the level of artificial lighting coverage; **Crowding Degree:** The number of people accommodated per unit area of ​​the path, used to measure the smoothness of jogging; **Traffic Risk:** The number of vehicles on the jogging path, used to quantify traffic safety hazards; **Road Width:** The effective passage width of the jogging track, determining the comfort of runners when crossing paths.

[0025] Secondly, the evaluation factors representing the subjective user needs of residents mainly include the following: Running route popularity refers to the frequency of use of jogging routes generated from trajectory data of sports applications, used to empirically demonstrate the actual spatial distribution of running behavior; Recommended route popularity refers to the user adoption rate or number of completions of recommended jogging routes by sports platforms, reflecting the matching degree between planned routes and users' actual intentions; Population density refers to the ratio of the number of permanent residents to the area within the research unit, indicating the overall base of potential jogging demand; Age characteristics refer to the proportion of the population in the suitable running age group within the region, reflecting the size of the core user group; Gender structure refers to the actual participation ratio of male and female joggers or the gender composition of the population within the region.

[0026] In summary, the concepts, quantification methods, and data sources of all pre-defined evaluation factors are shown in Table 1: Table 1. List of evaluation factors, their quantification methods, and data sources

[0027] Note: Running route popularity is the frequency of jogging route usage generated based on the track data of the fitness app, recording all running tracks. Recommended route popularity is the number of times users have used the fitness platform's recommended jogging route function. The difference between it and the running route recording is that it only records recommended routes uploaded by users (generally provided by high-level runners who have used the app for a certain period of time), and the number of times the recommended routes have been completed by other users.

[0028] The specific process of constructing the supply and demand evaluation system for the street jogging network based on the above-mentioned preset evaluation factors is as follows: First, a multi-level hierarchical structure model is established. This model uses the aforementioned specific preset evaluation factors as the bottom-level indicator layer, the supply layer and demand layer as the top-level target layer, and establishes a criterion layer between the indicator layer and the target layer to achieve logical induction. Specifically, when constructing the supply-level evaluation system, road network density, number of intersections, and number of traffic lights are mapped to the spatial structure and connectivity criterion layer; multimodal transportation connectivity and various accessibility indicators are mapped to the destination and service accessibility criterion layer; green view rate, sky visibility, road slope, temperature and humidity, PM2.5, and noise are mapped to the environmental comfort and landscape experience criterion layer; and the number of lighting facilities, night light intensity, congestion, traffic flow risk, and road width are mapped to the safety and management guarantee criterion layer. When constructing the demand-level evaluation system, the popularity of running routes and the popularity of recommended routes are mapped to the running popularity criterion layer; and population density, age characteristics, and gender structure are mapped to the population characteristics criterion layer.

[0029] Secondly, a preset weight vector is configured. Based on the established hierarchical structure, a preset weight calculation method (such as the analytic hierarchy process) is used to compare the importance of various indicators under the same criterion layer, and weights are assigned to different criterion layers, thereby assigning a specific weight value to each evaluation factor. For example, in the system of this embodiment, the weight of the safety and management guarantee criterion layer in the supply layer is calculated to be higher than that of other criterion layers, and the weight of the running popularity criterion layer in the demand layer is calculated to be higher than that of the population characteristic criterion layer. Finally, the above-mentioned clearly defined hierarchical relationship of indicators and the corresponding set of weight vectors together constitute a quantifiable and calculable supply and demand evaluation system for street jogging networks, as shown in Table 2: Table 2. Street Jogging Network Supply and Demand Evaluation System

[0030] Step S102: Obtain multi-source city data of supply-side indicator sets and demand-side indicator sets corresponding to each basic spatial unit within the target area, and calculate the supply-side comprehensive evaluation index and demand-side comprehensive evaluation index of each basic spatial unit in combination with the preset weight vector.

[0031] In step S102, the objective is to transform the theoretical evaluation system constructed in step S101 into quantifiable numerical results. Since the supply and demand layers involve a wide variety of data types, including geospatial data, image data, and behavioral trajectory data, and with inconsistent dimensions, it is necessary to use a unified data collection and standardized processing procedure, combined with a scientifically determined weighting system, to map multi-source heterogeneous data into a comprehensive evaluation index that can intuitively reflect the service level and demand intensity of each basic spatial unit (such as a street), thereby providing a mathematical basis for subsequent supply-demand synergy calculations.

[0032] Specifically, the first step is to acquire, integrate, and preprocess multi-source urban data within the target area using a Geographic Information System platform (such as ArcGIS 10.5). Referring to Table 1, the data acquisition for the supply-side indicator set is as follows: For spatial structure indicators such as road network density, road width, and number of intersections, road network vector data is obtained through Open Street Maps (OSM) for calculation; for various accessibility and multimodal transportation connectivity indicators, point-of-interest (POI) data is used in conjunction with distance analysis tools for measurement; for road slope indicators, they are extracted using Digital Elevation Models (DEM); for environmental indicators such as winter and summer temperatures, PM2.5, and noise, they are obtained through various open datasets for ecological and environmental monitoring; and for micro-environmental perception indicators such as green view rate, sky visibility, number of lighting facilities, and congestion, street view image semantic segmentation technology is used. The specific operation is as follows: Collect panoramic street view images of the target area from Baidu Maps, with a sampling interval of 30 meters (a total of more than 490,000 images were collected). Then, the existing DeepLabV3+ deep learning model is used for processing. This model uses ResNet-101 pre-trained on ImageNet-1K as the backbone network and is fine-tuned on 19 classes of annotations in the Cityscapes dataset to complete the semantic segmentation of the street view. Finally, the pixel ratio or number of each environmental element is extracted from the segmentation results as key indicator values.

[0033] For the data acquisition of the demand-layer indicator set: For the running route popularity indicator, raw data was extracted from the running page of the STRAVA sports official website, and rasterized using the density map provided by the official website to obtain the final spatial density data; for the recommended route popularity indicator, the recommended route function data in the KEEP sports software was manually matched and depicted in the ArcGIS platform, obtaining trajectory data containing 1067 recommended routes and a cumulative total of over 5.65 million completions; for indicators such as population density, age characteristics, and gender structure, census data and social statistics information of the target area were directly obtained and spatially matched.

[0034] After acquiring and normalizing the data, the comprehensive evaluation index of each basic spatial unit is calculated using a pre-defined weight vector. The pre-defined weight vector is determined using the Analytic Hierarchy Process (AHP). Specifically, experts in urban design and landscape planning (including university professors, associate professors, lecturers, planning designers, and landscape management personnel) are invited to evaluate the weights. The questionnaire uses a 1-9 level factor comparison scale commonly used in AHP. To ensure the reliability of the results, the expert scores are tested for consistency. Results that fail the test are re-evaluated by the experts until the consistency ratio (CR) is less than 0.1, ultimately yielding the weight values ​​representing the importance of each evaluation factor.

[0035] Finally, the comprehensive evaluation index of the supply side and the comprehensive evaluation index of the demand side are calculated respectively according to the following logic: The supply-side comprehensive evaluation index of each basic spatial unit is obtained by multiplying the normalized values ​​of each evaluation factor in the supply-side indicator set with their corresponding weights and summing the results. The formula is shown below: ; The normalized values ​​of each evaluation factor in the demand layer index set for each basic spatial unit are multiplied by their corresponding weights and summed to obtain the comprehensive demand layer evaluation index for that unit; the comprehensive demand layer evaluation index is then calculated. The formula is shown below: ; in, The total number of evaluation factors is 21 when calculating the supply-side index (corresponding to 21 specific factors in the supply-side indicator set) and 5 when calculating the demand-side index (corresponding to 5 specific factors in the demand-side indicator set). The index representing the evaluation factor; Representing the The preset weight values ​​of each evaluation factor Representing the The standardized values ​​of each evaluation factor after normalization.

[0036] Step S103: Calculate the supply-demand coordination degree value and supply-demand difference value, which represent the supply-demand balance state, using the supply-side comprehensive evaluation index and the demand-side comprehensive evaluation index, and use the supply-demand coordination degree value and supply-demand difference value as the supply-demand evaluation results.

[0037] In step S103, the aim is to fuse the indices of the two independent dimensions obtained in step S102 to quantitatively reveal the interactive balance between facility supply and residents' demand in urban space. Since individual supply-side comprehensive evaluation indices or demand-side comprehensive evaluation indices can only reflect one aspect (e.g., high supply but low demand, or high demand but low supply), they cannot directly determine whether supply and demand are coordinated and matched. Therefore, this embodiment introduces a supply-demand coordination model. It measures the degree of coordination between supply and demand by calculating the supply-demand coordination degree value D, and measures the direction of the quantity gap between supply and demand by calculating the supply-demand difference value d, thereby forming a complete supply-demand evaluation result and providing criteria for subsequent identification of imbalanced areas.

[0038] Specifically, the supply-layer comprehensive evaluation index of each basic spatial unit calculated in step S102 is used. Comprehensive evaluation index of demand layer Calculate using the following formula: First, calculate the coupling degree of the supply and demand system. This indicator reflects the strength of the interaction between the two subsystems of supply and demand. The calculation formula is as follows: ; Secondly, calculate the comprehensive coordination index of the supply and demand system. This indicator reflects the overall performance of supply and demand at the level of development, and its calculation formula is as follows: ; in, and , representing the relative importance of supply and demand. In this embodiment, supply and demand are considered equally important, therefore, we take . Based on the coupling degree and comprehensive synergy index calculated above, the supply-demand synergy value is calculated. This indicator integrates the intensity of interaction and the overall development level between systems, and can more accurately reflect the level of coordination between supply and demand. The calculation formula is as follows: ; Finally, calculate the supply-demand gap. This indicator uses direct difference calculations to intuitively reflect the direction of the supply-demand gap, helping to determine whether the problem is supply lagging or demand lagging. The calculation formula is as follows: ; Through the above calculations, each basic spatial unit (street) will obtain one value and a These two values ​​together constitute the supply and demand evaluation result for this unit, where... The value is used to measure the quality of collaboration (the higher the value, the better the collaboration). The value is used to measure the direction of the imbalance (positive value represents oversupply or insufficient demand, negative value represents lagging supply or excessive demand).

[0039] Step S104: Determine the update priority of each basic spatial unit based on the supply and demand evaluation results, and backtrack the bottleneck factors in the supply layer indicator set for units with high update priority to generate a street jogging network optimization guidance strategy.

[0040] In step S104, the aim is to transform the quantitative evaluation results obtained in step S103 into specific urban renewal decision support. By constructing hierarchical discrimination rules, the spatial units with the most prominent supply-demand contradictions are accurately identified, and the specific causes of their supply lag are further diagnosed, thereby outputting targeted physical environment improvement solutions.

[0041] Specifically, based on the supply and demand coordination value Supply and demand difference The update priority of each basic spatial unit is determined. The determination process mainly relies on the positive or negative attribute of the supply-demand difference, the supply-demand synergy value, and the first preset synergy threshold. and the second preset collaboration threshold The magnitudes are determined by the following conditions. The first preset collaboration threshold is less than the second preset collaboration threshold, and both the first and second preset collaboration thresholds are between 0 and 1.

[0042] First, based on the supply-demand gap Determining the direction of supply-demand imbalance: When When the current basic spatial unit is determined to be in a state of supply lag, that is, the facility service level cannot meet the actual needs of runners, it belongs to the target area that needs facility optimization; when When the current basic spatial unit is determined to be in a state of demand lag or supply-demand equilibrium, the update priority is set to low. Further, when it is determined to be supply lag (… Within the region, based on the supply and demand coordination value Classify update urgency levels: When When the current basic spatial unit is determined to be in a state of severe imbalance, its update priority is set to the highest level, indicating that immediate intervention is urgently needed; when When the current basic spatial unit is determined to be in a state of imminent imbalance, its update priority is set to a higher level, indicating that it should be a key update target in the near future; when When the current basic spatial unit is determined to be in a highly collaborative state, its update priority is set to medium level, indicating that it can be used as a reserve object for long-term optimization.

[0043] Optionally, in one specific embodiment of this application, the first preset collaboration threshold is set to 0.3, and the second preset collaboration threshold is set to 0.7. In actual use, other values ​​can also be selected as thresholds, and this application does not impose any restrictions on the specific values ​​of the thresholds.

[0044] Referring to Table 3, this application determines the update priority of each basic spatial unit based on the supply and demand evaluation results.

[0045] Table 3. Supply and Demand Status and Corresponding Renewal Priority of SJN in High-Density Urban Areas

[0046] In practice, existing technologies typically rely solely on the degree of supply and demand coordination. Values ​​are used to measure the matching level between supply and demand, but this has significant technical blind spots because... As a comprehensive indicator, the supply-demand gap value can only reflect the degree of orderliness in the interaction between the supply and demand systems, but cannot reveal the specific structural direction of the imbalance. That is, it cannot distinguish between "supply shortage" caused by insufficient facilities and "supply surplus" caused by a lack of demand. This leads to the easy misclassification of areas with lagging demand that do not require physical upgrades into the optimization scope in areas with low coordination, resulting in serious resource misallocation. This application creatively introduces the supply-demand gap value. With supply and demand coordination Construct a two-dimensional judgment mechanism, in which As a core directional filter, the value can accurately isolate the "supply lag" region from all imbalance regions through its positive and negative attributes, directly clarifying the necessary prerequisite for physical environment optimization, and thus... Values ​​form deep complementarity, and after determining the direction that "needs to be repaired", they are utilized. The value further quantifies and classifies the "urgency of repair". This close cooperation between "direction locking" and "degree classification" realizes the leap from a single-dimensional fuzzy state evaluation to a precise spatial intervention orientation. This ensures that the final generated renewal strategy can accurately target the pain points of those areas where the supply capacity of facilities cannot meet the actual needs of runners, thereby greatly improving the accuracy and effectiveness of refined renewal decisions in high-density urban areas.

[0047] Secondly, the bottleneck factors in the supply-side indicator set are backtested for the selected priority update units. The normalized values ​​of each evaluation factor in the supply-side used in step S102 are retrieved for that priority update unit. These values ​​are compared with preset scoring thresholds, or the scores of each evaluation factor are sorted within the unit to identify the lowest-scoring evaluation factors or those significantly below the average level. These are defined as bottleneck factors causing supply lag in that unit. Finally, based on the identified bottleneck factors and their corresponding criterion layer dimensions, a targeted street jogging network optimization guidance strategy is generated. Differentiated spatial intervention measures are adopted for different types of bottleneck factors: If the bottleneck factor belongs to the dimension of destination and service accessibility (such as low park accessibility), the generated optimization strategy is to add pocket parks or embedded fitness trails in idle spaces around the streets; if the bottleneck factor belongs to the dimension of spatial structure and connectivity (such as a large number of intersections and poor road network connectivity), the generated optimization strategy is to optimize the organization of the pedestrian and bicycle network in the block or add three-dimensional pedestrian and bicycle crossing facilities; if the bottleneck factor belongs to the dimension of safety and management guarantee (such as high traffic risk), the generated optimization strategy is to add physical barriers separating pedestrians and vehicles or set up green buffer zones; if the bottleneck factor belongs to the dimension of environmental comfort and landscape experience (such as insufficient lighting), the generated optimization strategy is to increase the density of nighttime street lights and ground guidance lighting facilities.

[0048] In summary, this application provides a method for evaluating and optimizing the supply and demand of high-density urban street jogging networks. First, this method constructs a supply and demand evaluation system based on preset evaluation factors, dividing these factors into a supply-layer indicator set representing the objective level of urban spatial service provision and a demand-layer indicator set representing subjective residents' usage needs. Second, it acquires multi-source urban data for each basic spatial unit within the target area, and calculates the comprehensive evaluation index of the supply layer and the comprehensive evaluation index of the demand layer for each basic spatial unit using preset weight vectors. Then, it uses the comprehensive evaluation index of the supply layer and the comprehensive evaluation index of the demand layer to calculate the supply-demand synergy value and the supply-demand difference, representing the supply-demand balance state, as the evaluation results. Finally, it determines the update priority of each basic spatial unit based on the supply and demand evaluation results, and backtracks the shortcomings in the supply-layer indicator set for high-priority units to generate targeted optimization strategies for the street jogging network.

[0049] To address the problem that existing technologies focus solely on the static attributes of street physical environment quality, failing to reflect the macro-level regional distribution balance, this application constructs a two-way evaluation system encompassing both supply and demand layers. By calculating the comprehensive evaluation indices for both the supply and demand layers, it transforms the evaluation from a one-way environmental quality assessment to a two-way supply-demand relationship assessment. Specifically, by introducing supply-demand synergy values ​​and supply-demand differences as core criteria, it quantifies the matching degree between the objective supply capacity of facilities and the actual intensity of population movement demand, thus accurately reflecting the balanced distribution of facility resources across the macro-region. Furthermore, this application establishes a quantitative hierarchical screening mechanism based on the supply-demand evaluation results (synergy values ​​and differences). By identifying spatial units with lagging supply and low synergy, it can accurately pinpoint areas with the most prominent supply-demand contradictions as priority renewal targets, providing data support for formulating scientific renewal sequences. Simultaneously, this application proposes a shortcoming factor backtracking mechanism. For identified priority renewal units, by backtracking on specific factors with low scores in the supply-layer indicator set (such as low road network density or poor safety), it can accurately locate the specific causes of supply lag in that unit. Based on this, the optimization-oriented strategy is no longer a general environmental improvement, but a spatial intervention targeting specific shortcomings (such as adding streetlights and optimizing intersections), thereby achieving refined updates and decisions for the high-density urban street jogging network.

[0050] Figure 2 This is a structural block diagram of a supply and demand evaluation and optimization system for street jogging networks in high-density urban areas, provided in one embodiment of this application. The system includes at least the following modules: The evaluation system construction module is used to build a supply and demand evaluation system for the street jogging network based on preset evaluation factors. The supply and demand evaluation system divides the evaluation factors into a supply-level indicator set that represents the objective level of urban space supply services and a demand-level indicator set that represents the subjective needs of residents. The evaluation index calculation module is used to obtain multi-source urban data of the supply-side indicator set and demand-side indicator set corresponding to each basic spatial unit in the target area, and calculate the supply-side comprehensive evaluation index and demand-side comprehensive evaluation index of each basic spatial unit by combining the preset weight vector. The evaluation result generation module is used to calculate the supply-demand coordination value and supply-demand difference, which represent the supply-demand balance state, using the supply-side comprehensive evaluation index and the demand-side comprehensive evaluation index, and uses the supply-demand coordination value and supply-demand difference as the supply-demand evaluation results; The optimization strategy generation module is used to determine the update priority of each basic spatial unit based on the supply and demand evaluation results, and to backtrack the bottleneck factors in the supply layer indicator set for units with high update priority, thereby generating an optimization guidance strategy for the street jogging network.

[0051] For relevant details, please refer to the above method implementation examples.

[0052] Figure 3 This is a block diagram of an electronic device provided in one embodiment of this application. The device includes at least a processor 301 and a memory 302.

[0053] Processor 301 may include one or more processing cores, such as a quad-core processor or an octa-core processor. Processor 301 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 301 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 301 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 301 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0054] The memory 302 may include one or more computer-readable storage media, which may be non-transitory. The memory 302 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 302 is used to store at least one instruction, which is executed by the processor 301 to implement the supply and demand evaluation and optimization method for street jogging networks in high-density urban areas provided in the method embodiments of this application.

[0055] In some embodiments, the electronic device may optionally include a peripheral device interface and at least one peripheral device. The processor 301, memory 302, and peripheral device interface can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface via a bus, signal line, or circuit board. Indicatively, peripheral devices include, but are not limited to, radio frequency circuits, touch displays, audio circuits, and power supplies.

[0056] Of course, electronic devices may also include fewer or more components, and this embodiment does not limit this.

[0057] Optionally, this application also provides a computer-readable storage medium storing a program that is loaded and executed by a processor to implement the supply and demand evaluation and optimization method for street jogging networks in high-density urban areas described in the above method embodiments.

[0058] Optionally, this application also provides a computer product including a computer-readable storage medium storing a program, which is loaded and executed by a processor to implement the supply and demand evaluation and optimization method for street jogging networks in high-density urban areas described in the above method embodiments.

[0059] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0060] The above embodiments merely illustrate several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for evaluating and optimizing the supply and demand of street jogging networks in high-density urban areas, characterized in that, The method includes: A supply and demand evaluation system for a street jogging network based on preset evaluation factors is constructed. The supply and demand evaluation system divides the evaluation factors into a supply-level indicator set that represents the objective level of urban space supply services and a demand-level indicator set that represents the subjective needs of residents. Obtain multi-source city data corresponding to the supply-layer indicator set and the demand-layer indicator set for each basic spatial unit within the target area, and calculate the supply-layer comprehensive evaluation index and the demand-layer comprehensive evaluation index for each basic spatial unit by combining the preset weight vector. The supply-demand coordination value and the supply-demand difference, which characterize the supply-demand balance state, are calculated using the supply-side comprehensive evaluation index and the demand-side comprehensive evaluation index, and the supply-demand coordination value and the supply-demand difference are used as the supply-demand evaluation results. Based on the supply and demand evaluation results, the update priority of each basic spatial unit is determined, and the shortcoming factors in the supply layer indicator set are traced back for units with high update priority to generate a street jogging network optimization guidance strategy.

2. The method for supply and demand evaluation and optimization of street jogging networks in high-density urban areas according to claim 1, characterized in that, The supply and demand evaluation system divides the evaluation factors into a supply-level indicator set that characterizes the objective level of urban spatial service supply and a demand-level indicator set that characterizes subjective residents' usage needs, including: The supply-layer indicator set that characterizes the objective level of urban spatial service supply includes road network density, number of intersections, number of traffic lights, multimodal transportation connectivity, park accessibility, water accessibility, sports venue accessibility, service facility accessibility, residential area accessibility, green view rate, sky visibility rate, road slope, winter and summer temperatures, PM2.5, noise, number of lighting facilities, nighttime light intensity, congestion, traffic flow risk, and road width. The set of demand-level indicators representing subjective residents' usage needs includes running route popularity, recommended route popularity, population density, age characteristics, and gender structure.

3. The method for supply and demand evaluation and optimization of street jogging networks in high-density urban areas according to claim 2, characterized in that, The construction of a supply and demand evaluation system for street jogging networks based on preset evaluation factors includes: Establish a multi-level hierarchical structure model, with the preset evaluation factors as the bottom indicator layer, the supply layer and the demand layer as the top target layer, and a criterion layer between the indicator layer and the target layer. When constructing the supply-side evaluation system, road network density, number of intersections, and number of traffic lights are mapped to the spatial structure and connectivity criteria layer; multimodal transportation connectivity and various accessibility indicators are mapped to the destination and service accessibility criteria layer; green view rate, sky visibility, road slope, temperature and humidity, PM2.5, and noise are mapped to the environmental comfort and landscape experience criteria layer; the number of lighting facilities, night light intensity, congestion, traffic flow risk, and road width are mapped to the safety and management guarantee criteria layer. When constructing the demand-side evaluation system, the popularity of running routes and the popularity of recommended routes are mapped to the running popularity criteria layer; population density, age characteristics, and gender structure are mapped to the population characteristics criteria layer. Based on the established hierarchical structure, the importance of each indicator under the same criterion layer is compared using a preset weight calculation method, and weights are assigned to different criterion layers, assigning a weight value to each evaluation factor; the clear hierarchical structure and the corresponding set of weight values ​​together constitute the supply and demand evaluation system for the street jogging network.

4. The method for supply and demand evaluation and optimization of street jogging networks in high-density urban areas according to claim 1, characterized in that, The comprehensive evaluation index of the supply layer and the comprehensive evaluation index of the demand layer for each basic spatial unit are calculated by combining the preset weight vectors, including: The supply-side comprehensive evaluation index of each basic spatial unit is obtained by multiplying the normalized values ​​of each evaluation factor in the supply-side indicator set with their corresponding weights and summing the results. The formula is shown below: ； The normalized values ​​of each evaluation factor in the demand layer index set for each basic spatial unit are multiplied by their corresponding weights and summed to obtain the comprehensive demand layer evaluation index for that unit; the comprehensive demand layer evaluation index is then calculated. The formula is shown below: ； in, The total number of evaluation factors is 21 when calculating the supply-side index and 5 when calculating the demand-side index. The index representing the evaluation factor; Representing the The preset weight values ​​of each evaluation factor Representing the The standardized values ​​of each evaluation factor after normalization.

5. The method for supply and demand evaluation and optimization of street jogging networks in high-density urban areas according to claim 4, characterized in that, The calculation of the supply-demand coordination value and supply-demand difference value, which characterize the supply-demand balance state, using the supply-side comprehensive evaluation index and the demand-side comprehensive evaluation index includes: Calculate the coupling degree of the supply and demand system The calculation formula is as follows: ； Calculate the comprehensive coordination index of the supply and demand system The calculation formula is as follows: ； in, and The coefficients are undetermined, representing the relative importance of supply and demand; the supply-demand synergy value is calculated based on the coupling degree and the comprehensive synergy index. The calculation formula is as follows: ； Calculate the supply and demand difference The calculation formula is as follows: 。 6. The method for supply and demand evaluation and optimization of street jogging networks in high-density urban areas according to claim 1, characterized in that, The process of determining the update priority of each basic spatial unit based on the supply and demand evaluation results includes: Based on the supply and demand difference Determine the direction of the supply-demand imbalance: when When the current basic spatial unit is determined to be in a state of supply lag, that is, the facility service level cannot meet the actual needs of runners, it belongs to the target area that needs to be optimized. when When the current basic spatial unit is determined to be in a state of demand lag or supply-demand balance, the update priority is set to low. In regions identified as experiencing supply lag, the supply-demand coordination value is used as a basis. Classify update urgency levels: When When the current basic spatial unit is determined to be in a state of severe imbalance, its update priority is set to the highest level, indicating that immediate intervention is urgently needed; when When the current basic spatial unit is determined to be in a state of imminent imbalance, its update priority is set to a higher level, representing a key update target; when When the current basic spatial unit is determined to be in a highly collaborative state, its update priority is set to medium, indicating that it can be considered as a reserve target for long-term optimization; among which, Less than ,and and All are between 0 and 1.

7. The method for supply and demand evaluation and optimization of street jogging networks in high-density urban areas according to claim 1, characterized in that, The process of generating a street jogging network optimization guidance strategy by backtracking the supply-layer indicator set of units with high update priority to identify bottleneck factors includes: Retrieve the normalized values ​​of each evaluation factor in the supply layer used for calculation in the selected priority update units; The retrieved values ​​are compared with the preset scoring threshold, or the scores of each evaluation factor are sorted within the unit to identify the few evaluation factors with the lowest scores or those below the average level, and these are defined as the bottleneck factors that cause the supply lag in the unit. Based on the identified bottleneck factors and their corresponding criterion layer dimensions, targeted optimization guidance strategies for street jogging networks are generated.

8. A supply and demand evaluation and optimization system for street jogging networks in high-density urban areas, characterized in that, include: The evaluation system construction module is used to construct a supply and demand evaluation system for street jogging networks based on preset evaluation factors. The supply and demand evaluation system divides the evaluation factors into a supply-level indicator set that represents the objective level of urban space supply services and a demand-level indicator set that represents the subjective needs of residents. The evaluation index calculation module is used to obtain multi-source city data corresponding to the supply-layer indicator set and the demand-layer indicator set for each basic spatial unit within the target area, and calculate the supply-layer comprehensive evaluation index and the demand-layer comprehensive evaluation index for each basic spatial unit in combination with the preset weight vector. The evaluation result generation module is used to calculate the supply-demand coordination value and the supply-demand difference, which represent the supply-demand balance state, using the supply-side comprehensive evaluation index and the demand-side comprehensive evaluation index, and to use the supply-demand coordination value and the supply-demand difference as the supply-demand evaluation result; The optimization strategy generation module is used to determine the update priority of each basic spatial unit based on the supply and demand evaluation results, and to backtrack the bottleneck factors in the supply layer indicator set for units with high update priority to generate a street jogging network optimization guidance strategy.

9. An electronic device, characterized in that, The device includes a processor and a memory; the memory stores a program, which is loaded and executed by the processor to implement a method for supply and demand evaluation and optimization of street jogging networks in high-density urban areas as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a program that, when executed by a processor, is used to implement a method for evaluating and optimizing the supply and demand of street jogging networks in high-density urban areas as described in any one of claims 1 to 7.

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