A subway station space layout optimization method and system

Abstract

The present invention belongs to the technical field of rail transit construction, and discloses a method and system for optimizing the spatial layout of subway stations. The method obtains urban development planning and subway network planning data, adopts a passenger flow prediction algorithm, calculates long-term passenger flow data of different stations, and determines the scale level of each station by judging by a preset passenger flow threshold. Based on the station scale level and spatial layout, combined with the functional positioning and transfer needs of the station, a simulation algorithm is adopted to evaluate the layout plans of the station hall, platform, entrance and exit, and passageway, and obtain a layout plan with the best passenger flow diversion efficiency. According to the passenger flow change trend prediction data, a flexible space analysis is performed on the optimized layout plan with the smallest footprint and the lowest construction cost, and the reserved space and adjustable layout area for the long-term renovation and expansion of the station are determined, so as to form a flexible spatial layout plan.

Description

Technical Field

[0001] The present invention relates to the technical field of rail transit construction, and in particular to a method and system for optimizing the spatial layout of a subway station. Background Art

[0002] Optimizing subway station spatial layout is a complex, systematic project that requires comprehensive consideration of multiple factors. First, based on urban development plans and subway network planning, long-term passenger flow forecasts for different stations must be used to determine the appropriate scale and tier for each station. Second, the station's geographical environment, surrounding building layout, and road traffic organization must be fully considered to ensure that the station layout is consistent with the urban spatial form. Third, the functional positioning and transfer needs of each station must be considered, optimizing the number and layout of station halls, platforms, entrances and exits, and passageways to improve passenger flow management efficiency. Furthermore, consideration must be given to construction conditions such as the station's engineering and geological conditions, construction difficulty, and investment scale. While ensuring functional requirements are met, efforts must be made to conserve floor space and reduce construction costs. Finally, provisions must be made for future station expansion and renovation to provide flexibility to accommodate fluctuations in passenger flow. It can be seen that the optimization of subway station spatial layout involves multiple professional fields such as passenger flow forecasting, urban planning, traffic organization, architectural design, and engineering construction. It requires a lot of research and analysis, scheme comparison and repeated demonstration to find the optimal layout plan that takes into account multiple requirements such as safety, convenience, economy, and scalability, and provide a reliable spatial carrier for subway operation management. Summary of the Invention

[0003] In order to solve the above technical problems, the present invention provides a subway station spatial layout optimization method and system, which realizes the scientific, refined and dynamic optimization of the subway station spatial layout, and effectively improves the operation efficiency and service quality of the subway station.

[0004] The present invention also provides a method for optimizing the spatial layout of a subway station, the method comprising:

[0005] Obtain urban development planning and subway network planning data, use passenger flow prediction algorithms to calculate long-term passenger flow data for different stations, and determine the scale level of each station based on preset passenger flow thresholds;

[0006] Based on the station scale and spatial layout, combined with the station's functional positioning and transfer needs, a simulation algorithm is used to evaluate the layout of the station hall, platform, entrances and exits, and passageways to obtain the layout plan with the best passenger flow management efficiency;

[0007] Based on the layout plan with the best passenger flow management efficiency, obtain the engineering geology and construction difficulty data of the station. Using a multi-objective optimization algorithm, calculate the optimal layout plan with the smallest footprint and lowest construction cost while meeting the functional constraints.

[0008] Based on passenger flow trend forecast data, a flexible space analysis is conducted to identify the optimal layout plan with the smallest footprint and lowest construction cost. This will determine the reserved space and adjustable layout areas for future station expansion and renovation, thus forming a flexible spatial layout plan.

[0009] Integrate the layout plans of each link to form a spatial layout optimization plan for the entire site.

[0010] Preferably, urban development planning and subway network planning data are obtained, and a passenger flow prediction algorithm is used to calculate the long-term passenger flow data of different stations. The scale level of each station is determined by judging by a preset passenger flow threshold, including:

[0011] Obtain urban development planning and subway network planning data, pre-process the planning data, and extract features related to passenger flow prediction;

[0012] Based on the features related to passenger flow prediction, a passenger flow prediction model is established using a time series prediction algorithm;

[0013] Apply the passenger flow prediction model to each subway station to predict the long-term passenger flow data of each subway station and obtain the predicted passenger flow of each station in different time periods in the future;

[0014] Based on the predicted passenger flow, the passenger flow level of each station in different time periods is determined by comparing it with the preset passenger flow threshold.

[0015] Preferably, the spatial layout determination method includes:

[0016] Step 1: Based on the site scale, obtain the geographical environment, building layout, and road traffic data around the site and construct a 3D spatial model;

[0017] Step 2: Based on the three-dimensional spatial model, use the spatial analysis algorithm to calculate the coordination degree between the site layout and the urban spatial form to obtain the initial coordination degree value;

[0018] Step 3: Compare the initial coordination value with the preset threshold to determine whether the coordination requirement is met;

[0019] Step 4: If the initial coordination value is lower than the preset threshold, the site location or internal layout parameters that need to be adjusted are determined based on the spatial analysis results;

[0020] Step 5: Use the optimization algorithm to search for the optimal combination of site location and internal layout parameters to maximize the coordination value;

[0021] Step 6: Based on the optimization results, adjust the site location or internal layout and update the 3D space model;

[0022] Step 7: Repeat steps 2 to 6 until the coordination value meets the preset threshold and the final site layout plan is determined.

[0023] Preferably, based on the station scale and spatial layout, combined with the station's functional positioning and transfer needs, a simulation algorithm is used to evaluate the layout plans of the station hall, platform, entrances and exits, and passageways to obtain the layout plan with the best passenger flow management efficiency, including:

[0024] Determine the functional positioning and transfer demand parameters of the station based on the station scale and spatial layout information;

[0025] The ant colony algorithm was used to optimize the layout of the station hall, platform, entrances and exits, and passageways, and several candidate layout plans were obtained.

[0026] Based on each candidate layout plan, the passenger flow trajectory and diversion situation in the station are simulated through simulation algorithms to obtain the passenger flow diversion efficiency index;

[0027] Compare the passenger flow management efficiency indicators of each candidate layout plan and determine the layout plan with the best efficiency.

[0028] Preferably, based on the layout plan with the best passenger flow diversion efficiency, the engineering geology and construction difficulty data of the station are obtained, and the optimal layout plan with the smallest footprint and lowest construction cost is calculated through a multi-objective optimization algorithm while meeting the functional constraints. The following are included:

[0029] By analyzing and quantifying construction condition data such as engineering geology and construction difficulty, a construction condition assessment model is established. Based on the construction condition assessment model, the construction conditions of different layout schemes are evaluated to obtain quantitative indicators of the construction conditions of each layout scheme;

[0030] Based on functional requirements, determine the various constraints that the layout plan needs to meet, including spatial layout constraints, traffic organization constraints, and equipment and facility configuration constraints, to form a layout plan constraint set;

[0031] A multi-objective optimization algorithm is used to optimize the layout plan with maximizing passenger flow efficiency and minimizing construction costs as the optimization goals, and minimizing the floor area as the constraint condition, to obtain the optimized layout plan with the smallest floor area and lowest construction cost.

[0032] Preferably, based on the passenger flow trend forecast data, a flexible space analysis is conducted on the optimized layout plan with the smallest footprint and lowest construction cost to determine the reserved space and adjustable layout area for the long-term renovation and expansion of the station. The flexible space layout plan includes:

[0033] Based on passenger flow forecast data, conduct flexible space analysis on the selected layout plan with the smallest footprint and lowest construction cost;

[0034] Using simulation technology, we added a certain amount of flexibility to the layout plan to simulate the station operation under the condition of future passenger flow changes;

[0035] Determine key areas in the layout plan through flexible space analysis;

[0036] Also identify non-critical areas in the layout;

[0037] Evaluate the results of the elastic space analysis and, by setting certain criteria, determine whether the elastic space of the current layout plan meets the requirements of future site renovation and expansion. If not, further layout optimization is required.

[0038] Optimize the layout plan, reserve space in key areas, dynamically adjust the layout of non-key areas, and iterate and optimize multiple times until flexible requirements are met;

[0039] Integrate the optimized site layout plans to form a complete set of flexible space site layout plans.

[0040] Preferably, the layout plans of each link are comprehensively integrated to form a spatial layout optimization plan for the entire site, including:

[0041] Based on passenger flow forecast data and site surrounding environment information, an intelligent optimization algorithm is used to generate multiple site spatial layout plans that meet the constraints;

[0042] By building a three-dimensional model of the layout plan and using virtual reality technology, we simulated the evacuation effects under different passenger flow scenarios and evaluated the evacuation efficiency of each plan;

[0043] Based on building information modeling technology, parametric design of the building structure and equipment pipelines for each layout plan is carried out, and the design is linked to the cost database to estimate the construction cost of each plan.

[0044] Taking into account multiple indicators such as drainage efficiency, construction cost and land area, a comprehensive evaluation model for the layout plan is constructed, and a multi-objective optimization algorithm is used to obtain the optimal layout plan that balances various indicators.

[0045] The present invention also provides a subway station space layout optimization system, the system is used to implement any one of the methods described above, a passenger flow prediction and station scale determination module, a passenger flow diversion efficiency optimization module, a land occupation and cost optimization module, a flexible space layout module, and a comprehensive integration module;

[0046] The passenger flow prediction and station scale determination module is used to obtain urban development planning and subway network planning data, use passenger flow prediction algorithms to calculate long-term passenger flow data for different stations, and determine the scale level of each station based on preset passenger flow thresholds;

[0047] The passenger flow management efficiency optimization module is used to evaluate the layout plans of the station hall, platform, entrance and exit, and passage according to the station scale level and spatial layout, combined with the functional positioning and transfer needs of the station, using simulation algorithms to obtain the layout plan with the best passenger flow management efficiency;

[0048] The land occupation and cost optimization module is used to obtain the engineering geology and construction difficulty construction condition data of the station based on the layout plan with the best passenger flow diversion efficiency, and calculate the optimized layout plan with the smallest land occupation and the lowest construction cost under the condition of satisfying the functional constraints through a multi-objective optimization algorithm;

[0049] The flexible space layout module is used to perform flexible space analysis on the optimized layout plan with the smallest footprint and lowest construction cost based on the passenger flow trend forecast data, determine the reserved space and adjustable layout area for the long-term renovation and expansion of the station, and form a flexible space layout plan;

[0050] The comprehensive integration module is used to comprehensively integrate the layout plans of each link to form a spatial layout optimization plan for the entire site.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] The present invention discloses a method and system for optimizing the spatial layout of subway stations. The method determines the site scale level through a passenger flow prediction algorithm, uses a spatial analysis algorithm to evaluate the coordination between the site layout and the urban spatial form, adopts a simulation algorithm to optimize the station layout to improve the efficiency of passenger flow diversion, and uses a multi-objective optimization algorithm to minimize the floor space and construction cost while meeting functional requirements. The present invention also takes into account future passenger flow changes and conducts flexible space analysis to reserve space for renovation and expansion. Finally, the present invention comprehensively integrates the optimization results of each link to form an overall optimization plan that takes into account passenger flow diversion efficiency, floor space, construction cost and flexible development. The plan is displayed through three-dimensional visualization technology and used to guide construction. During the operation stage, it can also be continuously optimized and improved based on actual passenger flow data. The present invention realizes the scientific, refined and dynamic optimization of the spatial layout of subway stations, effectively improving the operating efficiency and service quality of subway stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0054] Figure 1 The figure is a flow chart of a subway station spatial layout optimization method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0056] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure should have the usual meanings understood by people with ordinary skills in the field to which the present disclosure belongs. The "first", "second" and similar words used in the embodiments of the present disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative position relationships. When the absolute position of the described object changes, the relative position relationship may also change accordingly.

[0057] First, some technical terms used in this invention are explained:

[0058] The spatial layout of a subway station primarily involves the following aspects: 1. Passenger service facilities: These include ticket offices, ticket gates, waiting areas, and restrooms. Their layout must consider passenger travel needs and convenience. 2. Station equipment: These include power, lighting, ventilation, and fire protection systems. Their layout must consider safety and energy conservation. 3. Commercial facilities: These include convenience stores, fast food restaurants, and cafes to meet passengers' shopping and leisure needs. 4. Spatial composition: These include operational spaces and areas where passengers wait to board trains. The design must address the needs of different demographics. 5. Flow layout: Based on market demand and operator requirements, these layouts can be divided into separate, centralized, and hybrid types to optimize passenger travel time. 6. Spatial integration and functional coordination: Subway stations should comprehensively consider various urban elements, adopting spatial integration, functional coordination, and integrated services to promote the close integration of rail transit and the city. Subway station design must not only meet passengers' basic travel needs but also prioritize their comfort and psychological well-being. Through appropriate spatial layout and facility configuration, the overall passenger experience can be enhanced.

[0059] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0060] Example 1

[0061] like Figure 1 As shown, the embodiment of the present invention provides a method for optimizing the spatial layout of a subway station, the method comprising:

[0062] Obtain urban development planning and subway network planning data, use passenger flow prediction algorithms to calculate long-term passenger flow data for different stations, and determine the scale level of each station based on preset passenger flow thresholds;

[0063] Based on the station scale and spatial layout, combined with the station's functional positioning and transfer needs, a simulation algorithm is used to evaluate the layout of the station hall, platform, entrances and exits, and passageways to obtain the layout plan with the best passenger flow management efficiency;

[0064] Based on the layout plan with the best passenger flow management efficiency, obtain the engineering geology and construction difficulty data of the station. Using a multi-objective optimization algorithm, calculate the optimal layout plan with the smallest footprint and lowest construction cost while meeting the functional constraints.

[0065] Based on passenger flow trend forecast data, a flexible space analysis is conducted to identify the optimal layout plan with the smallest footprint and lowest construction cost. This will determine the reserved space and adjustable layout areas for future station expansion and renovation, thus forming a flexible spatial layout plan.

[0066] Integrate the layout plans of each link to form a spatial layout optimization plan for the entire site.

[0067] In this embodiment, urban development planning and subway network planning data are obtained, and a passenger flow prediction algorithm is used to calculate long-term passenger flow data for different stations. The scale level of each station is determined by judging by a preset passenger flow threshold, including:

[0068] Obtain urban development plan and subway network planning data, preprocess the planning data, and extract features relevant to passenger flow forecasting. Based on the preprocessed planning data, a passenger flow forecasting model is developed using time series forecasting algorithms, such as ARIMA models or LSTM neural networks. This passenger flow forecasting model is applied to each subway station to predict long-term passenger flow data, generating predicted passenger flows for each station at different time periods. The predicted passenger flow data is compared with preset passenger flow thresholds to determine the passenger flow level for each station during different time periods. Based on the passenger flow level of each station, combined with the urban development plan and subway network planning, a clustering algorithm is used to classify stations into different scale groups. Differentiated site planning strategies are developed for each scale group, such as large hub stations, medium-sized transfer stations, and small ordinary stations, to optimize site layout. A site planning report is generated, including the scale level of each station, passenger flow forecasts, and layout optimization recommendations, providing decision support for urban subway planning and construction.

[0069] In this embodiment, the spatial layout determination method includes:

[0070] Step 1: Based on the site scale, obtain the geographical environment, building layout, and road traffic data around the site and construct a 3D spatial model;

[0071] Step 2: Based on the three-dimensional spatial model, use the spatial analysis algorithm to calculate the coordination degree between the site layout and the urban spatial form to obtain the initial coordination degree value;

[0072] Step 3: Compare the initial coordination value with the preset threshold to determine whether the coordination requirement is met;

[0073] Step 4: If the initial coordination value is lower than the preset threshold, the site location or internal layout parameters that need to be adjusted are determined based on the spatial analysis results;

[0074] Step 5: Use the optimization algorithm to search for the optimal combination of site location and internal layout parameters to maximize the coordination value;

[0075] Step 6: Based on the optimization results, adjust the site location or internal layout and update the 3D space model;

[0076] Step 7: Repeat steps 2 to 6 until the coordination value meets the preset threshold and the final site layout plan is determined.

[0077] In this embodiment, based on the station scale and spatial layout, combined with the station's functional positioning and transfer needs, a simulation algorithm is used to evaluate the layout plans of the station hall, platform, entrances and exits, and passageways. The layout plan with the best passenger flow management efficiency is obtained, including:

[0078] Determine the functional positioning and transfer demand parameters of the station based on the station scale and spatial layout information;

[0079] The ant colony algorithm was used to optimize the layout of the station hall, platform, entrances and exits, and passageways, and several candidate layout plans were obtained.

[0080] Based on each candidate layout plan, the passenger flow trajectory and diversion situation in the station are simulated through simulation algorithms to obtain the passenger flow diversion efficiency index;

[0081] Compare the passenger flow management efficiency indicators of each candidate layout plan and determine the layout plan with the best efficiency.

[0082] Among them, the ant colony algorithm was used to optimize the layout of the station hall, platform, entrances and exits, and passages, and several candidate layout solutions were obtained, including:

[0083] Based on the layout requirements of subway station concourses, platforms, entrances and exits, and passageways, the objective function and constraints for layout optimization are determined, and an improved ant colony algorithm model is constructed. Key parameters in the layout plan, such as passageway width and entrance and exit locations, are assigned reasonable value ranges as decision variables for the ant colony algorithm. A certain number of ant colony individuals are randomly generated, each representing a feasible layout plan. The individual's position information represents the value of the layout parameters. The fitness of each ant colony individual is calculated based on the objective function value of the layout plan. A higher fitness indicates a better overall evaluation metric for the layout plan. Through the pheromone update and path selection mechanisms of the ant colony algorithm, ants are directed toward layout plans with higher fitness, continuously optimizing the layout parameters. The ant colony algorithm's convergence criteria are then determined. If so, the optimal layout plan is output; otherwise, iterative optimization continues until the maximum number of iterations is reached. Multiple candidate layout plans generated by the ant colony algorithm are evaluated and compared, and the optimal layout plan is selected as the final solution, taking into account factors such as passenger travel efficiency and transfer convenience.

[0084] Specifically, the specific process of the improved ant colony algorithm model is as follows: (I) Initialize the grid, including the starting point, target point, obstacles, etc., and set the pheromone concentration within a certain range; (II) Put m ants into n elements; (III) Select the next grid to go to based on the transition probability; (IV) Select the route of the only ant as the best path and update the taboo table; (V) Update the formula according to the new pheromone concentration; (VI) Determine whether the maximum number of iterations has been reached. If so, output the optimal result; if not, take adaptive adjustment of the pheromone concentration and return.

[0085] In addition, in order to change the shortcoming of decreased convergence speed that may be caused by a wide distribution of solutions, the present invention adaptively adjusts the pheromone volatilization rate. The specific algorithm is as follows: (I) After each cycle is completed, the optimal solution that needs to be retained is confirmed; (II) the pheromone volatilization rate ρ value is adjusted in an adaptive manner. Pheromone volatilization will cause the concentration of undetected pheromones to drop to 0, thereby weakening the algorithm's exploration efficiency in the entire search domain; setting the ρ value too high will cause previously explored solutions to be repeatedly selected, and at the same time weaken the global search performance. Although the intensity of the global search can be improved by reducing the ρ value, it will also slow down the convergence process of the algorithm. Based on this, the present invention adjusts the ρ value according to the actual situation, that is, the initial ρ value is set to 1. If the algorithm does not significantly improve the optimization of the optimal solution after multiple rounds of iterations, the ρ value is appropriately lowered:

[0086]

[0087] Among them, ρ min is a lower bound on the parameter ρ.

[0088] In this embodiment, based on the layout plan with the best passenger flow diversion efficiency, data on the engineering geology and construction difficulty of the station are obtained. Using a multi-objective optimization algorithm, the optimal layout plan with the smallest footprint and lowest construction cost is calculated while satisfying functional constraints. The following are included:

[0089] Based on the relationship between passenger flow management efficiency and layout options, a passenger flow management efficiency evaluation model was established. Using simulation methods, the passenger flow management efficiency of different layout options was evaluated and compared, resulting in the layout option with the optimal passenger flow management efficiency. By analyzing and quantifying construction condition data, such as engineering geology and construction difficulty, a construction condition evaluation model was established to evaluate the construction conditions of different layout options and obtain quantitative construction condition indicators for each layout option. Based on functional requirements, the various constraints that the layout option must meet were determined, including spatial layout constraints, traffic organization constraints, and equipment and facility configuration constraints, forming a set of layout constraint conditions. Using a multi-objective optimization algorithm, with maximizing passenger flow management efficiency and minimizing construction costs as the optimization objectives and minimizing floor space as the constraint, the layout options were optimized multi-objectively to obtain the optimal layout option with the smallest floor space and lowest construction cost. By performing 3D visualization of the planar layout, spatial layout, and traffic organization of the optimized layout option, a 3D model of the optimized layout option was generated, allowing for intuitive display and analysis of the optimized layout option. Utilizing simulation technology, we simulated passenger flow management for the optimized layout plan, analyzed its effectiveness, and verified its feasibility and effectiveness. Taking into account factors such as passenger flow management efficiency, construction conditions, floor space, and construction costs, we conducted a comprehensive evaluation of the optimized layout plan, determined the final site layout plan, and provided guidance for site planning, design, and construction implementation.

[0090] Among them, a multi-objective optimization algorithm is used to optimize the layout plan with maximizing passenger flow efficiency and minimizing construction costs as the optimization goals, and minimizing the occupied area as the constraint condition. The optimized layout plan with the smallest occupied area and the lowest construction cost is obtained, including:

[0091] Based on multiple optimization objectives, including passenger flow management efficiency, construction cost, and floor space, a multi-objective optimization model was established. Key parameters of the layout plan were used as decision variables to form a mathematical model for the optimization solution. A simulated annealing algorithm was used to solve the multi-objective optimization model. By setting parameters such as the initial temperature and cooling coefficient, the algorithm's convergence speed and global search capability were controlled to prevent the algorithm from falling into local optima. During the simulated annealing algorithm's iterations, the weight coefficients of each optimization objective were dynamically adjusted based on the current temperature, allowing the algorithm to focus on different optimization objectives at different stages, improving the efficiency and quality of the optimization solution. A penalty function was introduced to incorporate the floor space minimization constraint into the objective function. When a layout plan exceeds the constraint, the objective function value is penalized, ensuring that the constraint is automatically satisfied during the search process. During each iteration of the simulated annealing algorithm, the key parameters of the layout plan are perturbed to generate a new layout plan. The algorithm then calculates its comprehensive evaluation value under multiple optimization objectives, which serves as the basis for accepting the new solution. When the simulated annealing algorithm reaches its termination condition, the optimal layout solution is output as the result of the multi-objective optimization. This solution achieves a balance between maximizing passenger flow management efficiency and minimizing construction costs while satisfying the constraint of minimizing floor space. The layout solution obtained through multi-objective optimization is evaluated, and its passenger flow management effectiveness and construction costs in actual applications are analyzed through simulation and other methods. Based on the evaluation results, the layout solution is further revised and improved to obtain the final optimized layout solution.

[0092] Specifically, the present invention establishes a multi-objective optimization model using the NSGA-II algorithm based on a back-propagation neural network. The data processing flow under this model is as follows: (1) selecting the optimization target variable and determining the optimization strategy; (2) determining the value range of the variable; (3) determining the number of iterations and the population size, and generating a population O; (4) encoding the individuals in the population, and calculating the individual fitness using a back-propagation neural network prediction model; (5) transferring individuals with satisfactory fitness to the next generation population A, performing crossover and mutation processing on them, and then generating a new population B and re-evaluating its fitness until a predetermined number of iterations is reached, ultimately obtaining the optimal solution set.

[0093]

[0094] Among them, T is the current temperature, X is the passenger flow diversion efficiency, Y in is the construction cost, Z in is the floor area, Z out is the minimum floor area, Y out For the lowest construction cost.

[0095] In this embodiment, based on passenger flow trend forecast data, a flexible space analysis is conducted on the optimized layout plan with the smallest footprint and lowest construction cost to determine the reserved space and adjustable layout areas for future station expansion and renovation. The flexible space layout plan includes the following:

[0096] Historical passenger flow data and related influencing factors are collected, and a passenger flow forecasting model is developed using a time series forecasting algorithm to generate forecast data on passenger flow trends over the next period of time. For each candidate site layout, its footprint is calculated using CAD software. Construction cost estimates for each plan are then derived using a construction cost estimation model. The layout plan with the smallest footprint and lowest construction cost is selected. Based on the passenger flow forecast data, a flexible space analysis is performed on the selected site layout plans. Using simulation technology, a certain amount of flexible space is incorporated into the layout plan to simulate site operation under future passenger flow fluctuations. This flexible space analysis identifies key areas within the layout plan where sufficient space needs to be reserved to accommodate future site expansion needs. Non-critical areas within the layout are also identified as areas that can be adjusted to accommodate future passenger flow fluctuations. The results of the flexible space analysis are evaluated, and specific criteria are used to determine whether the flexible space within the current layout plan meets future site expansion and renovation needs. If not, further optimization is required. The layout plan is optimized by reserving more space in key areas and dynamically adjusting the layout of non-critical areas. This optimization process is repeated repeatedly until the flexible space requirements are met. During this process, it's crucial to consider the rational layout of each station's functional areas to ensure the optimal layout is scientific and rational. The optimized station layout plans are then integrated to form a complete, flexible station layout plan. This plan, while meeting current passenger flow demands, allows for sufficient flexibility for future station expansion and renovation, adapting to dynamic changes in passenger flow.

[0097] In this embodiment, the layout plans of each link are comprehensively integrated to form the spatial layout optimization plan of the entire site, including:

[0098] Based on passenger flow forecast data and site surrounding environment information, an intelligent optimization algorithm is used to generate multiple site spatial layout plans that meet the constraints;

[0099] By building a three-dimensional model of the layout plan and using virtual reality technology, we simulated the evacuation effects under different passenger flow scenarios and evaluated the evacuation efficiency of each plan;

[0100] Based on building information modeling technology, parametric design of the building structure and equipment pipelines for each layout plan is carried out, and the design is linked to the cost database to estimate the construction cost of each plan.

[0101] Taking into account multiple indicators such as drainage efficiency, construction cost and land area, a comprehensive evaluation model for the layout plan is constructed, and a multi-objective optimization algorithm is used to obtain the optimal layout plan that balances various indicators.

[0102] The optimal layout plan was designed in detail, and parametric modeling technology enabled the one-click generation of multiple alternative spatial forms, enhancing the plan's flexibility and adaptability. The detailed design plan was converted into a 3D visualization model, and combined with virtual reality and augmented reality technologies to create an immersive presentation of the plan, facilitating understanding and review by all parties. Simulation analysis was used to simulate and analyze the plan's passenger flow management, disaster prevention and hazard avoidance, and equipment operation and maintenance, assessing its feasibility and safety and optimizing weak links.

[0103] Example 2

[0104] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present invention further provides a subway station spatial layout optimization system, the system being configured to implement any of the above-mentioned methods, including a passenger flow prediction and station scale determination module, a passenger flow diversion efficiency optimization module, a land occupation and cost optimization module, a flexible space layout module, and a comprehensive integration module;

[0105] The passenger flow prediction and station scale determination module is used to obtain urban development planning and subway network planning data, use passenger flow prediction algorithms to calculate the long-term passenger flow data of different stations, and determine the scale level of each station based on the preset passenger flow threshold;

[0106] The passenger flow management efficiency optimization module is used to evaluate the layout of station halls, platforms, entrances and exits, and passageways based on the station scale and spatial layout, combined with the station's functional positioning and transfer needs, using simulation algorithms to obtain the layout plan with the best passenger flow management efficiency.

[0107] The Land and Cost Optimization module is used to obtain the engineering geology and construction difficulty data of the station based on the layout plan with the best passenger flow diversion efficiency. Through a multi-objective optimization algorithm, it calculates the optimal layout plan with the smallest land area and the lowest construction cost while meeting the functional constraints.

[0108] The flexible space layout module is used to conduct flexible space analysis on the optimized layout plan with the smallest footprint and lowest construction cost based on passenger flow trend forecast data. This module determines the reserved space and adjustable layout areas for future site expansion and renovation, thus forming a flexible space layout plan.

[0109] The comprehensive integration module is used to integrate the layout plans of each link to form a spatial layout optimization plan for the entire site.

[0110] The embodiments of the present disclosure are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A method for optimizing the spatial layout of a subway station, characterized in that: The method comprises: Obtain urban development planning and subway network planning data, use passenger flow prediction algorithms to calculate long-term passenger flow data for different stations, and determine the scale level of each station based on preset passenger flow thresholds; Based on the station scale and spatial layout, combined with the station's functional positioning and transfer needs, a simulation algorithm is used to evaluate the layout of the station hall, platform, entrances and exits, and passageways to obtain the layout plan with the best passenger flow management efficiency; Based on the layout plan with the best passenger flow management efficiency, obtain the engineering geology and construction difficulty data of the station. Using a multi-objective optimization algorithm, calculate the optimal layout plan with the smallest footprint and lowest construction cost while meeting the functional constraints. Based on passenger flow trend forecast data, a flexible space analysis is conducted to identify the optimal layout plan with the smallest footprint and lowest construction cost. This will determine the reserved space and adjustable layout areas for future station expansion and renovation, thus forming a flexible spatial layout plan. Integrate the layout plans of each link to form a spatial layout optimization plan for the entire site.

2. The method according to claim 1, characterized in that Obtain urban development planning and subway network planning data, use passenger flow prediction algorithms to calculate long-term passenger flow data for different stations, and determine the scale level of each station by pre-set passenger flow thresholds, including: Obtain urban development planning and subway network planning data, pre-process the planning data, and extract features related to passenger flow prediction; Based on the features related to passenger flow prediction, a passenger flow prediction model is established using a time series prediction algorithm; Apply the passenger flow prediction model to each subway station to predict the long-term passenger flow data of each subway station and obtain the predicted passenger flow of each station in different time periods in the future; Based on the predicted passenger flow, the passenger flow level of each station at different time periods is determined by comparing it with the preset passenger flow threshold; According to the passenger flow level of the station, combined with urban development planning and subway network planning, a clustering algorithm is used to classify the stations and obtain station groups of different scale levels.

3. The method according to claim 1, characterized in that Based on the station scale and spatial layout, combined with the station's functional positioning and transfer needs, a simulation algorithm is used to evaluate the layout plans of the station hall, platform, entrances and exits, and passageways. The layout plan with the best passenger flow management efficiency includes: Determine the functional positioning and transfer demand parameters of the station based on the station scale and spatial layout information; The ant colony algorithm was used to optimize the layout of the station hall, platform, entrances and exits, and passageways, and several candidate layout plans were obtained. Based on each candidate layout plan, the passenger flow trajectory and diversion situation in the station are simulated through simulation algorithms to obtain the passenger flow diversion efficiency index; Compare the passenger flow management efficiency indicators of each candidate layout plan and determine the layout plan with the best efficiency.

4. The method according to claim 1, wherein Based on the layout plan with the best passenger flow management efficiency, we obtain the engineering geology and construction difficulty data of the station. Using a multi-objective optimization algorithm, we calculate the optimal layout plan with the smallest footprint and lowest construction cost while meeting the functional constraints. The following solutions are included: By analyzing and quantifying the engineering geology, construction difficulty and construction condition data, a construction condition assessment model is established. Based on the construction condition assessment model, the construction conditions of different layout schemes are evaluated to obtain the quantitative indicators of the construction conditions of each layout scheme; Based on functional requirements, determine the various constraints that the layout plan needs to meet, including spatial layout constraints, traffic organization constraints, and equipment and facility configuration constraints, to form a layout plan constraint set; A multi-objective optimization algorithm is used to optimize the layout plan with maximizing passenger flow efficiency and minimizing construction costs as the optimization goals, and minimizing the floor area as the constraint condition, to obtain the optimized layout plan with the smallest floor area and lowest construction cost.

5. The method according to claim 1, wherein Based on passenger flow trend forecast data, a flexible space analysis is conducted to identify the optimal layout plan with the smallest footprint and lowest construction cost. This determines the reserved space and adjustable layout areas for future station expansion and renovation, and forms a flexible space layout plan including: Based on passenger flow forecast data, conduct flexible space analysis on the selected layout plan with the smallest footprint and lowest construction cost; Using simulation technology, we added pre-set flexible space to the layout plan to simulate the station operation under the condition of future passenger flow changes; Determine key areas in the layout plan through flexible space analysis; Also identify non-critical areas in the layout; Evaluate the results of the elastic space analysis and, by setting preset evaluation criteria, determine whether the elastic space of the current layout plan meets the requirements of future site renovation and expansion. If not, further layout optimization is required. Optimize the layout plan, reserve space in key areas, dynamically adjust the layout of non-key areas, and iterate and optimize multiple times until flexible requirements are met; Integrate the optimized site layout plans to form a complete set of flexible space site layout plans.

6. The method according to claim 1, characterized in that The layout plans of each link are comprehensively integrated to form the spatial layout optimization plan of the whole site, including: Based on passenger flow forecast data and site surrounding environment information, an intelligent optimization algorithm is used to generate multiple site spatial layout plans that meet the constraints; By building a three-dimensional model of the layout plan and using virtual reality technology, we simulated the evacuation effects under different passenger flow scenarios and evaluated the evacuation efficiency of each plan; Based on building information modeling technology, parametric design of the building structure and equipment pipelines for each layout plan is carried out, and the design is linked to the cost database to estimate the construction cost of each plan. Taking into account multiple indicators such as drainage efficiency, construction cost and land area, a comprehensive evaluation model for the layout plan is constructed, and a multi-objective optimization algorithm is used to obtain the optimal layout plan that balances various indicators.

7. A subway station spatial layout optimization system, the system being used to implement the method according to any one of claims 1 to 6, characterized in that: include: Passenger flow prediction and station scale determination module, passenger flow management efficiency optimization module, land occupation and cost optimization module, flexible space layout module, and comprehensive integration module; The passenger flow prediction and station scale determination module is used to obtain urban development planning and subway network planning data, use passenger flow prediction algorithms to calculate long-term passenger flow data for different stations, and determine the scale level of each station based on preset passenger flow thresholds; The passenger flow management efficiency optimization module is used to evaluate the layout plans of the station hall, platform, entrance and exit, and passage according to the station scale level and spatial layout, combined with the functional positioning and transfer needs of the station, using simulation algorithms to obtain the layout plan with the best passenger flow management efficiency; The land occupation and cost optimization module is used to obtain the engineering geology and construction difficulty construction condition data of the station based on the layout plan with the best passenger flow diversion efficiency, and calculate the optimized layout plan with the smallest land occupation and the lowest construction cost under the condition of satisfying the functional constraints through a multi-objective optimization algorithm; The flexible space layout module is used to perform flexible space analysis on the optimized layout plan with the smallest footprint and lowest construction cost based on the passenger flow trend forecast data, determine the reserved space and adjustable layout area for the long-term renovation and expansion of the station, and form a flexible space layout plan; The comprehensive integration module is used to comprehensively integrate the layout plans of each link to form a spatial layout optimization plan for the entire site.

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