Optimization design method for subway entrance and exit model

Abstract

The invention relates to the technical field of metro vehicle entrance and exit design, and discloses a metro entrance and exit model optimization design method, which comprises the following steps: determining the number of entrances and exits required by a station through an oblique photography live-action model and surrounding building development planning; determining a plurality of entrance and exit positions by analyzing the three-dimensional geologic model, passenger flow prediction, passenger flow destination and surrounding building development planning; performing path optimization by adopting an improved Dijkstra algorithm, generating paths between different entrance and exit positions and the nearest entrance and exit gate position, and determining an optimal path; according to the passenger flow volume of the station, the building design specification and the evacuation time, the width of each entrance and exit and the setting form of a building escalator are calculated; and generating a subway entrance and exit model according to the number of entrances and exits, the positions of the entrances and exits, the optimal path, the widths of the entrances and exits and the setting form of stairs. Errors and deviations in the design process are reduced, and the design accuracy and efficiency can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of subway entrance and exit design, and in particular to a subway entrance and exit model optimization design method. Background Art

[0002] With the acceleration of urbanization, public transportation systems such as subways are playing an increasingly important role in urban transportation. To cope with the growing passenger volume and improve the operational efficiency and safety of subway stations, subway station design is crucial. Traditional subway design often relies on experience or simple regulatory requirements to determine the layout, width, and functionality of entrances and exits, without in-depth consideration of complex factors. Therefore, achieving more efficient and safe subway entrance and exit design has become a major challenge in transportation engineering and architectural design.

[0003] Existing methods for designing subway station entrances and exits generally rely on architectural design codes, traffic flow forecasts, and empirical data. While this approach can meet basic design requirements, it often presents several challenges. Existing methods for designing subway station entrances and exits typically rely on two-dimensional floor plans. This approach struggles to express complex three-dimensional spatial relationships, making it difficult to visually demonstrate the interaction between underground facilities and surface buildings, and to accurately assess key elements such as passenger flow, visual guidance, and emergency evacuation routes. Furthermore, insufficient attention is often paid to complex spatial relationships (such as underground soil structure, rock strata distribution, and groundwater levels), potentially leading to unexpected situations during construction and increasing project risks and costs. Current methods rely heavily on historical experience and general standards, lacking specific data analysis for specific stations. This can lead to a mismatch between entrance and exit capacity and actual demand, particularly in estimating passenger capacity.

[0004] Therefore, there is an urgent need for a subway entrance and exit model optimization design method. Through three-dimensional visualization design, a more accurate, scientific and reasonable optimization design method is needed to improve the design accuracy and implementation operability. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention provides a subway entrance and exit model optimization design method, which can improve the accuracy and efficiency of the design.

[0006] The present invention provides a method for optimizing the design of a subway entrance and exit model, comprising the following steps: Step S1: Determine the number of entrances and exits required for the station through the oblique photography real-life model and the surrounding building development plan; Step S2: Determine multiple entrance and exit locations by analyzing the three-dimensional geological model, passenger flow forecast, passenger flow destinations, and surrounding building development plans; Step S3: Using the improved Dijkstra algorithm to perform path optimization, generate paths between different entrance and exit locations and the entrance and exit gate locations closest to the entrance and exit, and determine the optimal path; Step S4: Calculate the width of each entrance and exit and the layout of the escalator based on passenger flow forecast, building design specifications, and evacuation time; Step S5: Generate a subway entrance and exit model based on the number of entrances and exits, entrance and exit locations, optimal paths, entrance and exit widths, and escalator settings.

[0007] Furthermore, in step S1, the number of entrances and exits required for the station is determined by using the oblique photography real-life model and the surrounding building development plan, specifically including: Step S11: Obtain an oblique photography real-scene model through drone aerial photography, and obtain surrounding building development plans through government platform information; Step S12: Generate a high-precision three-dimensional real-scene model of the station and its surrounding environment using oblique photography technology based on the oblique photography real-scene model and the surrounding building development plan; Step S13: Collect historical passenger flow data, analyze and identify passenger flow patterns; Step S14: Based on the high-precision three-dimensional real-scene model of the station and its surrounding environment, the passenger flow pattern is used to perform prediction to obtain predicted passenger flow data, wherein the predicted passenger flow data includes: peak hour passenger flow and super peak coefficient; Step S15: Determine the number of entrances and exits required for the station based on the predicted passenger flow data.

[0008] Furthermore, in step S2, multiple entrance and exit locations are determined by analyzing the three-dimensional geological model, predicted passenger flow data, passenger flow destinations, and surrounding building development plans, including the following steps: Step S21: Obtain a three-dimensional geological model of the area where the subway station is located through drilling survey data; Step S22: Analyze the underground soil structure, rock layer distribution, and groundwater level information using a three-dimensional geological model, and determine the preliminary location range of the entrance and exit without destroying the stability of the geological structure; Step S23: Determine traffic flow lines based on predicted passenger flow data, passenger destinations, and surrounding building development plans; Step S24: Determine multiple locations of entrances and exits based on the service radius of the subway station, traffic flow lines, and preliminary location ranges of entrances and exits.

[0009] Furthermore, the improved Dijkstra algorithm specifically includes: Step S31: Construct a graph data structure. The graph includes nodes and edges. The nodes represent the locations of different entrances and exits and the locations of the nearest entrance and exit gates. Each edge represents the connection between nodes. The attributes of the edges include distance, congestion, time, and traffic convenience. Step S32: Set the comprehensive score of the source node to 0 and the comprehensive score of other nodes to infinity; create a priority queue to store the nodes to be visited and their comprehensive costs; Step S33: Starting from the current node, traverse all adjacent nodes; Step S34: For each edge, calculate the comprehensive cost f(u,v) from the current node to the adjacent node; calculate the comprehensive score of the adjacent node based on the weight, and update the value of the comprehensive score; Step S35: Add the adjacent nodes to the priority queue and sort them in ascending order according to their comprehensive costs; Step S36: When the shortest comprehensive costs of all nodes are calculated, the algorithm terminates and outputs the optimal path from the source node to the target node.

[0010] Furthermore, the comprehensive score calculation formula is: Score(v)=w D ×D(v)+w C ×C(v)+w T ×T(v)+w P ×P(v); where Score(v) represents the comprehensive score of node v; w D , w C , w T , w P are the weight values ​​of distance, congestion, time and traffic convenience respectively, D(v), C(v), T(v), P(v) are the attribute values ​​of node v; The cost function formula of the comprehensive score is: f(u,v)=w D ×D(u,v)+w C ×C(u,v)+w T ×T(u,v)+w P ×P(u,v); Among them, f(u,v) represents the comprehensive cost from node u to node v; D(u,v) represents the physical distance between node u and node v; C(u,v) represents the congestion level between node u and node v; T(u,v) represents the travel time from node u to node v; P(u,v) represents the traffic convenience between node u and node v.

[0011] Furthermore, in step S4, the width of each entrance and exit is calculated based on the passenger flow of the station, building design specifications, and evacuation time, specifically: Step S411: Calculate the flow carrying capacity of each entrance and exit based on the predicted passenger flow data and evacuation time; Step S412: Determine the initial width of each entrance and exit based on the flow carrying capacity of each entrance and exit; Step S413: Determine the width of each entrance and exit in accordance with architectural design specifications.

[0012] Furthermore, in step S4, the escalator configuration is calculated based on passenger flow prediction, building design specifications, and evacuation time, specifically: Step S421: Calculate the number of escalators based on passenger flow forecast, evacuation time, and escalator passenger capacity; Step S422: Determine the arrangement of the escalators according to the number of escalators and building design specifications.

[0013] Furthermore, in step S5, a subway entrance and exit model is generated based on the number of entrances and exits, entrance and exit locations, optimal paths, and escalator configurations, specifically including: Step S51: Generate an escalator segment model based on the escalator setting form and arrange it at the entrance and exit positions; Step S52: Determine the parameters of the passage section model and the civil air defense section model based on the thickness of the structural top plate, the thickness of the side wall, the thickness of the bottom plate, the inner width, and the height of the ceiling; Step S53: Arrange the channel segment model and the civil air defense segment model on the optimal path according to the parameters of the channel segment model and the civil air defense segment model; Step S54: Quickly assemble the passage section, civil air defense section, and escalator section into a preliminary entrance and exit model Step S55: Repeat steps S51 to S54 according to the number of entrances and exits to generate multiple subway entrance and exit models.

[0014] The embodiments of the present invention have the following technical effects: 1. By combining oblique photography real-life models with surrounding building development plans, the number of entrances and exits required for subway stations and their optimal locations can be more accurately determined. This not only allows for a more accurate determination of the number and location of entrances and exits required for stations, avoiding the errors and uncertainties inherent in traditional methods, optimizing station entrance and exit designs, but also better serving surrounding communities and improving passenger convenience and safety.

[0015] 2. Use the improved Dijkstra algorithm for path optimization, taking into account multiple factors such as distance, congestion, time, and traffic convenience, to ensure the selection of the optimal path from the entrance and exit to the gate location, reducing passenger travel time, reducing congestion risks, and improving overall operational efficiency.

[0016] 3. Comprehensive consideration of important factors such as the three-dimensional geological model, underground soil structure, and traffic flow lines can ensure that the selection of entrance and exit locations does not damage the geological structure and reduce potential risks in foundation construction. Based on historical data and predictive models, taking into account the demand during peak hours, it can ensure that the design plan meets the passenger evacuation needs in different situations. Taking into account the planning of surrounding buildings and traffic flow lines, the entrance and exit layout is more compatible with urban development, avoiding unreasonable traffic congestion and path intersections, thereby ensuring the rationality of the design plan.

[0017] 4. By integrating 3D model design, preliminary subway entrance and exit design models can be quickly generated. By combining modules such as escalator and passageway models, a complete entrance and exit design solution can be formed. This rapid model-based generation approach can improve design efficiency, shorten project cycles, and reduce potential errors and deviations during the design process. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are 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.

[0019] Figure 1 This is a flow chart of a subway entrance and exit model optimization design method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0021] Figure 1 This is a flow chart of a subway entrance and exit model optimization design method provided by an embodiment of the present invention. Figure 1 , a subway entrance and exit model optimization design method, specifically including: Step S1: Determine the number of entrances and exits required for the station through the oblique photography real-life model and the surrounding building development plan.

[0022] Step S11: Obtain an oblique photography real-scene model through drone aerial photography, and obtain surrounding building development plans through government platform information; Using drones equipped with high-resolution cameras, we captured aerial images of the station area and its surroundings, acquiring image data from various angles. To create a realistic oblique photography model, we captured the scene from multiple angles, ensuring panoramic coverage. The resulting 2D images were then processed for oblique photography modeling. The drone images were then fed into 3D modeling software for processing, generating a 3D oblique photography model.

[0023] The surrounding building development plan includes statutory plans, existing building uses, and planned building uses. Prepared annually by the urban planning authorities based on the city's master plan and zoning plan, it details the land use characteristics, development intensity, supporting facilities, road traffic, and urban design of each area within the zone. This data helps understand the changing trends of the surrounding environment and facilitates forward-looking planning for station design.

[0024] Step S12: Based on the oblique photography real-scene model and the surrounding building development plan, a high-precision three-dimensional real-scene model of the station and its surrounding environment is generated using oblique photography technology.

[0025] Integrate the surrounding building development planning data obtained from the government platform with the oblique photography real-scene model to ensure that the model reflects the latest surrounding environment planning.

[0026] Step S13: Collect historical passenger flow data, analyze and identify passenger flow patterns; Collect historical passenger flow data, optionally through video surveillance method: using video surveillance system to automatically calculate passenger flow through image recognition technology; mobile data analysis method: using mobile device signals to calculate passenger flow through big data analysis technology, etc.

[0027] Clean and organize historical passenger flow data, removing invalid, duplicate, or erroneous data to ensure data quality and accuracy. Analyze historical data using statistical methods (such as time distribution and population flow models) to identify patterns in passenger flow, such as peak hours, holiday effects, and weather-related impacts.

[0028] Step S14: Based on the high-precision three-dimensional real-scene model of the station and its surrounding environment, the passenger flow pattern is used to perform prediction to obtain predicted passenger flow data, wherein the predicted passenger flow data includes: peak hour passenger flow and super peak coefficient; Steps S11 and S12 establish a high-precision three-dimensional real-scene model of the station and its surrounding environment for display analysis in step S14. The passenger flow patterns obtained in step S14 are combined with the station's surrounding environment (transportation facilities, commercial area development, etc.) and specific time periods (such as morning rush hour and evening rush hour) to generate future predicted passenger flow.

[0029] Step S15: Determine the number of entrances and exits required for the station based on the predicted passenger flow data.

[0030] The predicted passenger flow data includes peak hour passenger flow and super-peak coefficients. The number of entrances and exits required for the station is determined based on the predicted peak hour passenger flow and super-peak coefficient. During peak hours, the capacity requirements of each entrance and exit are calculated based on the predicted passenger flow. For example, during the morning rush hour, a station may require more entrances and exits to divert large numbers of passengers, especially in areas connected to the city center or commercial district. Considering the impact of holidays, special events, etc., it may be necessary to design additional temporary entrances and exits or temporary passages to cope with sudden passenger flows.

[0031] Step S2: Determine multiple entrance and exit locations by analyzing the three-dimensional geological model, passenger flow forecast, passenger flow destinations, and surrounding building development plans.

[0032] In some embodiments, in step S2, determining the locations of multiple entrances and exits by analyzing the three-dimensional geological model, predicted passenger flow data, passenger flow destinations, and surrounding building development plans includes the following steps: Step S21: Obtain a three-dimensional geological model of the area where the subway station is located through drilling survey data; Through geological exploration drilling, we obtain information on the depth of underground soil layers, rock strata distribution, soil physical properties (such as bearing capacity and permeability), and groundwater levels. This data is used to construct a 3D geological model, helping to analyze geological conditions and ensure that subsequent designs will not undermine the stability of geological structures. Professional 3D geological modeling software is used to process the survey data to create a complete 3D geological model that includes soil layers, rock layers, groundwater, faults, and other elements.

[0033] Step S22: Analyze the underground soil structure, rock layer distribution, and groundwater level information using a three-dimensional geological model, and determine the preliminary location range of the entrance and exit without destroying the stability of the geological structure; Based on the 3D geological model, identify locations unsuitable for entrances and exits, such as areas with hard rock, high groundwater levels, or potentially unstable geology. Avoid creating entrances and exits in these locations. Use geomechanical analysis to assess the stability of different geological regions. Select areas with relatively stable underground soil and feasible construction as candidate entrance and exit locations.

[0034] Step S23: Determine traffic flow lines based on predicted passenger flow data, passenger destinations, and surrounding building development plans; For example, a station's primary passenger flow might originate from a nearby commercial center or transportation hub, so entrances and exits should be located in these key traffic areas. Using a crowd flow simulation tool, we can simulate the flow of passengers from station entrances and exits to other parts of the city, ensuring smooth and unobstructed flow.

[0035] Step S24: Determine multiple locations of entrances and exits based on the service radius, traffic flow lines, and preliminary location ranges of the entrances and exits of the subway station; Based on the service radius of a subway station, typically a 400-600-meter walking distance, the service area is delineated on a map, and the approximate location range of entrances and exits is determined. Based on traffic flow, multiple possible locations for entrances and exits are identified. Then, by comprehensively considering the approximate entrance and exit locations determined by the service radius, the multiple possible locations determined by traffic flow, and the preliminary entrance and exit location range determined by the three-dimensional geological model, multiple rounds of optimization are conducted to simulate the impact of different entrance and exit locations and make adjustments. For example, simulation analysis determines whether each entrance and exit can divert traffic and avoid overcrowding at certain entrances and exits. A feasibility analysis of all candidate locations, taking into account factors such as traffic flow, convenience, safety, and future urban development, ultimately determines the specific entrance and exit locations.

[0036] Step S3: Use the improved Dijkstra algorithm to perform path optimization, generate paths between different entrance and exit locations and the nearest entrance and exit gate locations, and determine the optimal path; In some embodiments, the improved Dijkstra algorithm specifically includes: Step S31: Construct a graph data structure. The graph includes nodes and edges. The nodes represent the locations of different entrances and exits and the locations of the nearest entrance and exit gates. Each edge represents the connection between nodes. The attributes of the edges include distance, congestion, time, and traffic convenience. Step S32: Set the comprehensive score of the source node (starting position) to 0, indicating that the cost of starting from the source node is the lowest, and other nodes to infinity (indicating that they have not been visited yet); create a priority queue, which is used to store the nodes to be visited and their comprehensive costs; The priority queue ensures that the node removed from the queue each time is the one with the lowest overall score, allowing nodes with lower scores to be visited first. This ensures that the Dijkstra algorithm proceeds in the optimal order. After each visit to a node, the algorithm examines its neighboring nodes, calculates their overall scores, and adds these neighboring nodes to the priority queue.

[0037] Step S33: Starting from the current node, traverse all adjacent nodes; Step S34: For each edge, calculate the comprehensive cost f(u,v) from the current node to the adjacent node; calculate the comprehensive score of the adjacent node based on the weight, and update the value of the comprehensive score; The cost function formula of the comprehensive score is: f(u,v)=w D ×D(u,v)+w C×C(u,v)+w T ×T(u,v)+w P ×P(u,v); Among them, f(u,v) represents the comprehensive cost from node u to node v; D(u,v) represents the physical distance between node u and node v; C(u,v) represents the congestion level between node u and node v; T(u,v) represents the travel time from node u to node v; P(u,v) represents the traffic convenience between node u and node v. Each attribute has a corresponding weight (w D ,w C ,w T ,w P ), these weights can be adjusted according to demand or user preferences, determining which attributes are more important in path optimization.

[0038] Each time an adjacent node is visited, a new comprehensive score is calculated based on the current edge attribute values ​​and weights. If the newly calculated score is lower (i.e., a lower-cost path has been found), the adjacent node's comprehensive score is updated and the node is reinserted into the priority queue.

[0039] The comprehensive score calculation formula is: Score(v)=w D ×D(v)+w C ×C(v)+w T ×T(v)+w P ×P(v); where Score(v) represents the comprehensive score of node v; w D , w C , w T , w P are the weight values ​​of distance, congestion, time and traffic convenience respectively, D(v), C(v), T(v), P(v) are the attribute values ​​of node v; Step S35: Add the adjacent nodes to the priority queue and sort them in ascending order according to their comprehensive costs; Step S36: When the shortest comprehensive costs of all nodes are calculated, the algorithm terminates and outputs the optimal path from the source node to the target node.

[0040] Through the above steps, the improved Dijkstra algorithm can optimize path selection by integrating multiple factors (such as distance, congestion, and time) to generate the optimal path. This algorithm can flexibly consider various factors such as different entrance and exit locations and gates, making it suitable for real-time path planning and optimization problems.

[0041] Step S4: Calculate the width of each entrance and exit and the layout of the escalator according to the passenger flow of the station, building design specifications, and evacuation time; Step S411: Calculate the flow carrying capacity of each entrance and exit based on the predicted passenger flow data and evacuation time; Step S412: Determine the initial width of each entrance and exit based on the flow carrying capacity of each entrance and exit; Step S413: Determine the width of each entrance and exit in accordance with architectural design specifications.

[0042] Step S421: Calculate the number of escalators based on passenger flow forecast, evacuation time, and escalator passenger capacity; Step S422: Determine the arrangement of the escalators according to the number of escalators and building design specifications.

[0043] Step S5: Generate a subway entrance and exit model based on the number of entrances and exits, entrance and exit locations, optimal paths, entrance and exit widths, and escalator settings.

[0044] Step S51: Generate an escalator segment model based on the escalator setting form and arrange it at the entrance and exit positions; Step S52: Determine the parameters of the passage section model and the civil air defense section model based on the thickness of the structural top plate, the thickness of the side wall, the thickness of the bottom plate, the inner width, and the height of the ceiling; Step S53: Arrange the channel segment model and the civil air defense segment model on the optimal path according to the parameters of the channel segment model and the civil air defense segment model; Step S54: Quickly assemble the passage section, civil air defense section, and escalator section into a preliminary entrance and exit model Step S55: Repeat steps S51 to S54 according to the number of entrances and exits to generate multiple subway entrance and exit models.

[0045] Compared with the existing technology, the present invention provides a systematic and step-by-step three-dimensional subway station entrance and exit design method. Combining oblique photography real-scene models, surrounding building development plans and three-dimensional geological models, the location and number of subway entrances and exits are determined through three-dimensional visual design, and the optimal path is determined through an improved Dijkstra algorithm. This makes the entrance and exit modeling more accurate, improves design efficiency, reduces errors, deviations and duplication of work in the design process, reduces design costs, and provides strong technical support for the construction of subway station entrances and exits.

[0046] For example, in existing designs, a standard station typically has four entrances and exits located at the four corners. Each entrance and exit has identical layouts, with two escalators and one staircase. Assuming the staircase is 1 meter wide, the escalator is 0.65 meters wide, and the passageway is 3.5 meters wide, the maximum evacuation capacity is 5,900 people per hour, and the maximum evacuation capacity for all four entrances and exits is 23,600 people per hour. The drawback is that even with identical entrance and exit designs, some entrances and exits will have significantly higher passenger flow than others, leading to congestion and significantly longer entry and exit times.

[0047] The entrances and exits designed with this invention analyze passenger flow by region. For high-traffic areas, the number of entrances and exits is increased, reducing the size of individual entrances; for low-traffic areas, the size of entrances and exits is reduced, reducing investment. By reducing the size of individual entrances and exits, increasing the number of entrances and exits, and implementing a more scientific and rational entrance and exit layout design, peak traffic can be increased by 10%, shortening passenger congestion by 10 minutes. The reduced entrance and exit size reduces construction difficulty, investment, and construction costs by 5%.

[0048] This invention utilizes advanced oblique photography technology and a modified Dijkstra algorithm to improve passenger flow efficiency. By performing high-precision 3D modeling of the subway station and its surroundings, combined with passenger flow forecasting analysis, the number and location of entrances and exits can be precisely determined, ensuring that each entrance and exit can effectively serve the large number of passengers during peak hours. Furthermore, a path optimization algorithm, based on a comprehensive consideration of multiple factors, minimizes the travel distance and time from the subway station to the destination, significantly improving the passenger travel experience. Secondly, in terms of spatial utilization, innovative integration of the surrounding environment is achieved to achieve efficient spatial planning. During the design process, full consideration was given to the subway station's connection with key locations such as surrounding commercial areas and transportation hubs, ensuring efficient distribution of passenger flow and reducing congestion. Analysis of the 3D geological model prevented damage to underground structures and ensured the safety and stability of entrance and exit construction. Furthermore, by adjusting entrance and exit locations based on future development plans, the system not only meets current needs but also adapts to future changes, thereby achieving long-term and efficient resource utilization.

[0049] Finally, this application improves the service quality of subway stations through scientific and reasonable layout, and also promotes the efficient use of urban space resources.

[0050] After completing the entrance and exit model, the subway entrance and exit model and the oblique photography model can be integrated into BIM software to reserve space for the upper part. Based on the location and surrounding environment of the subway entrance and exit, creative ideas can be developed to propose a variety of upper part design options. Characteristic elements such as art installations, cultural symbols, and lighting fixtures can be added based on cultural characteristics and historical background. Using 3D modeling tools in BIM software, detailed design of the upper part can be carried out. This design scheme can be combined with oblique photography and the subway entrance and exit to ensure that the subway entrance and exit design is consistent with the overall urban landscape, thus forming a distinctive entrance and exit model.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A subway entrance and exit model optimization design method, characterized in that: The design method comprises the following steps: Step S1: Determine the number of entrances and exits required for the station through the oblique photography real scene model and the surrounding building development plan; Step S2: determining multiple entrance and exit locations by analyzing the three-dimensional geological model, passenger flow prediction, passenger flow destinations, and surrounding building development plans; Step S3: using the improved Dijkstra algorithm to perform path optimization, generate paths between different entrance and exit locations and the entrance and exit gate locations closest to the entrance and exit, and determine the optimal path; Step S4: Calculate the width of each entrance and exit and the setting form of the escalator according to passenger flow prediction, building design specifications and evacuation time; Step S5: Generate a subway entrance and exit model based on the number of entrances and exits, entrance and exit locations, optimal paths, entrance and exit widths, and escalator settings.

2. The subway entrance and exit model optimization design method according to claim 1, characterized in that: In step S1, the number of entrances and exits required for the station is determined through the oblique photography real-life model and the surrounding building development plan, including: Step S11, obtaining an oblique photography real-scene model through drone aerial photography, and obtaining surrounding building development plans through government platform information; Step S12: Generate a high-precision three-dimensional real-scene model of the station and its surrounding environment using the oblique photography technology according to the oblique photography real-scene model and the surrounding building development plan; Step S13: Collect historical passenger flow data, analyze and identify passenger flow patterns; Step S14: Based on the high-precision three-dimensional real-scene model of the station and its surrounding environment, the passenger flow law is used to make a prediction to obtain predicted passenger flow data, wherein the predicted passenger flow data includes: peak hour passenger flow and super peak coefficient; Step S15: Determine the number of entrances and exits required for the station based on the predicted passenger flow data.

3. The subway entrance and exit model optimization design method according to claim 1, characterized in that: In step S2, multiple entrance and exit locations are determined by analyzing the three-dimensional geological model, predicted passenger flow data, passenger flow destinations, and surrounding building development plans, including the following steps: Step S21, obtaining a three-dimensional geological model of the area where the subway station is located through drilling survey data; Step S22: Analyze the underground soil structure, rock layer distribution and groundwater level information through the three-dimensional geological model, and determine the preliminary location range of the entrance and exit without destroying the stability of the geological structure; Step S23, determining the traffic flow line according to the predicted passenger flow data, the passenger flow destination and the surrounding building development plan; Step S24: Determine multiple locations of entrances and exits based on the service radius of the subway station, traffic flow lines, and preliminary location ranges of entrances and exits.

4. The subway entrance and exit model optimization design method according to claim 1, characterized in that: The improved Dijkstra algorithm specifically includes: Step S31, constructing a graph data structure, wherein the graph includes nodes and edges, wherein the nodes are different entrance and exit locations and the entrance and exit gate locations closest to the entrance and exit, and each edge represents the connection relationship between the nodes, and the attributes of the edge include: distance, congestion, time, and traffic convenience; Step S32: Set the comprehensive score of the source node to 0 and other nodes to infinity; create a priority queue to store the nodes to be visited and their comprehensive costs; Step S33, starting from the current node, traverse all adjacent nodes; Step S34: For each edge, calculate the comprehensive cost from the current node to the adjacent node; calculate the comprehensive score of the adjacent node according to the weight, and update the value of the comprehensive score; Step S35, adding the adjacent nodes to the priority queue and sorting them in ascending order according to the comprehensive cost; Step S36: When the shortest comprehensive costs of all nodes are calculated, the algorithm terminates and outputs the optimal path from the source node to the target node.

5. The subway entrance and exit model optimization design method according to claim 4 is characterized in that: The comprehensive score calculation formula is: Score(v)=w D ×D(v)+w C ×C(v)+w T ×T(v)+w p ×P(v); where Score(v) represents the comprehensive score of node v; w D , w C , w T , w P are the weight values ​​of distance, congestion, time and traffic convenience respectively, D(v), C(v), T(v), P(v) are the attribute values ​​of node v; The cost function formula of the comprehensive score is: f(u,v)=w D ×D(u,v)+w C ×C(u,v)+w T ×T(u,v)+w P ×P(u,v); Among them, f(u,v) represents the comprehensive cost from node u to node v; D(u,v) represents the physical distance between node u and node v; C(u,v) represents the congestion level between node u and node v; T(u,v) represents the travel time from node u to node v; P(u,v) represents the traffic convenience between node u and node v.

6. The subway entrance and exit model optimization design method according to claim 1, characterized in that: In step S4, the width of each entrance and exit is calculated according to the passenger flow of the station, the building design specifications, and the evacuation time, specifically: Step S411, calculating the flow carrying capacity of each entrance and exit according to the predicted passenger flow data and evacuation time; Step S412: Determine the preliminary width of each entrance and exit according to the flow carrying capacity of each entrance and exit; Step S413: Determine the width of each entrance and exit in accordance with the building design specifications.

7. The subway entrance and exit model optimization design method according to claim 1, characterized in that: In step S4, the escalator configuration is calculated based on passenger flow prediction, building design specifications, and evacuation time, specifically: Step S421, calculating the number of escalators according to passenger flow prediction, evacuation time and passenger carrying capacity of the escalators; Step S422: Determine the arrangement of the escalators according to the number of escalators and building design specifications.

8. The subway entrance and exit model optimization design method according to claim 1, characterized in that: In step S5, a subway entrance and exit model is generated according to the number of entrances and exits, the locations of entrances and exits, the optimal path, and the setting form of escalators, which specifically includes: Step S51, generating an escalator segment model according to the setting form of the escalator, and arranging it at the entrance and exit positions; Step S52, determining the parameters of the passage section model and the civil air defense section model through the thickness of the structural top plate, the thickness of the side wall, the thickness of the bottom plate, the inner width and the height of the ceiling; Step S53: Arrange the channel segment model and the civil air defense segment model on the optimal path according to the parameters of the channel segment model and the civil air defense segment model; Step S54: Splice the passage section, civil air defense section, and escalator section into a preliminary entrance and exit model Step S55, repeat steps S51 to S54 according to the number of entrances and exits to generate multiple subway entrance and exit models.

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