A subway station emergency evacuation capability simulation test method and related equipment

Abstract

The present application provides a subway station emergency evacuation capacity simulation test method and related equipment, and relates to the field of subway station simulation methods. The physical environment, personnel characteristics and obstacle impacts of the subway station are modeled as a whole. The subway station model established based on subway station data reflects the actual physical environment; the pedestrian flow model takes into account the triple impact of destination attraction, crowd interaction and obstacle hindrance; the crowd flow information extracted from passenger flow data can accurately reflect the actual evacuation scenario. This multi-factor comprehensive modeling method can truly simulate the crowd behavior characteristics during emergency evacuation, avoid the defects of simple mathematical calculations that ignore actual factors, and improve the accuracy of evacuation capacity assessment.

Description

Technical Field

[0001] The present application relates to the field of subway station simulation methods, and in particular to a subway station emergency evacuation capability simulation test method and related equipment. Background Art

[0002] The safe operation of urban rail transit is directly related to the safety of life and property of passengers. The Technical Specifications for Safety Assessment before Initial Operation of Urban Rail Transit issued by the Ministry of Transport of China clearly stipulates that stations with large passenger flow must pass the emergency evacuation capacity test to ensure that in an emergency, all passengers of a fully loaded train and platform waiting personnel can be evacuated to a safe area within 6 minutes during super peak hours. This is a mandatory pre-requisite for the operation of subway stations.

[0003] At present, the evacuation capacity of subway stations is mainly evaluated by static data calculation methods. The specific approach is to use physical parameters such as the width and slope of each channel in the station, combined with the personnel passing capacity parameters specified in the specifications, to obtain the theoretical evacuation capacity through simple mathematical calculations.

[0004] However, the relevant technology ignores many practical factors in the process of evacuation. For example, in a crowded state, people will interfere with each other, avoid each other, and other complex behaviors, which will significantly affect the actual evacuation efficiency. Physical facilities such as walls, columns, and stairs in the station will change the direction of the flow of people and also have an important impact on the evacuation efficiency.

[0005] Therefore, the current relevant technologies are not realistic enough in assessing the evacuation capacity of subway stations, resulting in inaccurate assessment results. Summary of the invention

[0006] The present application provides a subway station emergency evacuation capacity simulation test method and related equipment, which are used to improve the accuracy of evacuation capacity assessment.

[0007] In a first aspect, the present application provides a method for simulating and testing the emergency evacuation capacity of a subway station, comprising: obtaining basic data, the basic data including subway station data and passenger flow data; establishing a subway station model based on the subway station data; establishing a pedestrian flow model based on the subway station data, the pedestrian flow model including expected data of pedestrians at their destination, under the influence of obstacles and other pedestrians in the subway station data; obtaining a demand scenario, the demand scenario being a scenario when an emergency evacuation capacity simulation test is desired; extracting corresponding passenger flow information and location information from the passenger flow data based on the demand scenario; establishing a pedestrian model in the subway station model based on the passenger flow information and location information; loading the pedestrian flow model in the subway station model, causing the pedestrian model to move under the action of the pedestrian flow model, and obtaining a subway station emergency evacuation capacity simulation test report.

[0008] By adopting the above technical solutions, the physical environment, personnel characteristics and obstacle impact of the subway station are modeled as a whole. The subway station model established based on subway station data reflects the actual physical environment; the pedestrian flow model takes into account the triple impact of destination attraction, crowd interaction and obstacle obstruction; the crowd flow information extracted from passenger flow data can accurately reflect the actual evacuation scene. This multi-factor comprehensive modeling method can truly simulate the behavior characteristics of the crowd during the emergency evacuation process, avoid the defects of simple mathematical calculations that ignore actual factors, and improve the accuracy of evacuation capacity assessment.

[0009] In conjunction with some embodiments of the first aspect, in some embodiments, the pedestrian streamline model includes: F i =f wiff +f ij +f iw In the formula, F i is the expected data of pedestrian i under the influence of obstacles and other pedestrians in the destination and subway station data, and f wiff is the expected data of pedestrian i under the influence of the destination, f ij is the expected data of pedestrian i under the influence of pedestrian j, f iw is the expected data of pedestrian i under the influence of obstacle w in the subway station data, m i is the mass of pedestrian i, v i is the speed of pedestrian i.

[0010] By adopting the above technical solutions, a mechanical model of pedestrian movement was established, and various influences in the crowd evacuation process were mathematically expressed. i Represents the total expected data acting on pedestrians, including destination guidance force, crowd interaction force and obstacle expectation data; This reflects the acceleration changes of pedestrians. Through this mechanical modeling method, the movement law of the crowd during the evacuation process can be accurately described, especially the impact of crowd density on individual movement, so that the simulation results are more in line with the actual situation.

[0011] In conjunction with some embodiments of the first aspect, in some embodiments, the pedestrian streamline model includes: In the formula, f wiff is the expected data of pedestrian i under the influence of the destination, m i is the mass of pedestrian i, is the expected speed of pedestrian i at t, v i (t) is the current speed of pedestrian i at time t, τ iis the adjusted reaction time of pedestrian i; f ij is the expected data of pedestrian i under the influence of pedestrian j, A i is the repulsive force intensity coefficient of pedestrian i, r ij is the sum of the radii of pedestrian i and pedestrian j in the subway station model, d ij is the center distance between pedestrian i and pedestrian j in the subway station model, B i is the range coefficient of pedestrian i, n ij is the unit vector from pedestrian i to pedestrian j, k is a constant coefficient, g(r ij -d ij ) is the judgment function, when r ij -d ij When g(r ij -d ij )=0, when r ij -d ij ≥0, g(r ij -d ij )=r ij -d ij , Δv ij is the tangential velocity difference between pedestrian i and pedestrian j, t ij n ij The orthogonal unit vector of iw is the expected data of pedestrian i under the influence of obstacle w in the subway station data, r i is the radius of pedestrian i in the subway station model, d iw is the center distance between pedestrian i and obstacle w in the subway station model, g(r i -d iw ) is the judgment function, when r i -d iw When g(r i -d iw )=0, when r i -d iw ≥0, g(r i -d iw )=r i -d iw , t iw n iw The orthogonal unit vectors.

[0012] By adopting the above technical solutions, a detailed mathematical model of crowd interaction is constructed. will The term reflects the individual's driving force to move toward the goal, which is regulated by the difference between the desired speed and the current speed; secondly, f ij The term represents the repulsive force and tangential force between people, reflecting the avoidance behavior when the crowd is dense; finally, f iwThe term describes the hindering effect of obstacles on crowd movement. This mathematical description enables the model to accurately reflect the complex behavioral characteristics of the crowd in a crowded state.

[0013] In combination with some embodiments of the first aspect, in some embodiments, the exit closest to the area where the pedestrian is located in the subway station data is used as the destination.

[0014] By adopting the above technical solution, by taking the nearest exit as the destination of pedestrians, it not only meets people's instinct to choose the shortest escape route in an emergency, but also avoids the local congestion caused by all people gathering at the same exit, making the simulation results closer to the actual evacuation process.

[0015] In combination with some embodiments of the first aspect, in some embodiments, the steps of extracting corresponding passenger flow information and location information from passenger flow data based on demand scenarios, and establishing a pedestrian model in a subway station model based on the passenger flow information and location information specifically include: obtaining the total passenger flow in the passenger flow data for the same scenario as the demand scenario; determining the passenger flow distribution ratio based on the difference between the time of the demand scenario and the time of the most recent departure in the passenger flow data; calculating the number of pedestrians in each area based on the passenger flow distribution ratio and the total passenger flow; establishing a pedestrian model in each area; and distributing the pedestrian model according to the spatial characteristics of the corresponding area; and randomly adding attribute features to the pedestrian model.

[0016] By adopting the above technical solutions, the total number of people is determined based on historical passenger flow data; the distribution ratio is calculated by time difference; and personnel are arranged by combining spatial characteristics and random attributes. This multi-level modeling method not only ensures the accuracy of the total number of people, but also achieves the rationality of spatial distribution, making the initial state more in line with the actual situation.

[0017] In combination with some embodiments of the first aspect, in some embodiments, the subway station data includes: station location data, including the location of the station, the passenger source areas of each entrance and exit, and the external evacuation routes; station structure data, including the actual physical structure of the station and CAD drawing data; facility and equipment data, including the type, quantity and spatial location information of the facilities and equipment in the station; operation and management data, including the equipment activation status and the passenger flow organization plan within the station.

[0018] By adopting the above technical solutions, a comprehensive subway station data system was built. Data was collected from multiple dimensions, including station location, physical structure, facilities and equipment, and operation management, providing complete basic information for the model and ensuring the accurate restoration of the physical space. The consideration of the equipment opening status makes the simulation closer to the actual operation status.

[0019] In combination with some embodiments of the first aspect, in some embodiments, after loading a pedestrian flow line model in a subway station model and causing the pedestrian model to move under the action of the pedestrian flow line model and obtaining a subway station emergency evacuation capacity simulation test report, the method also includes: extracting parameters in relevant standards and regulations as simulation boundary conditions; if the test report does not meet the simulation boundary conditions, the test fails.

[0020] By adopting the above technical solution and taking the parameters in the relevant standards and regulations as the simulation boundary conditions, an objective basis for evaluation is formed, thus ensuring the standardization of the test results.

[0021] In a second aspect, the present application provides a subway station emergency evacuation capability simulation test system, the subway station emergency evacuation capability simulation test system comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code comprises computer instructions, and one or more processors call the computer instructions to enable the subway station emergency evacuation capability simulation test system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a third aspect, the present application provides a computer program product comprising instructions, which, when run on a subway station emergency evacuation capability simulation test system, enables the subway station emergency evacuation capability simulation test system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0023] In a fourth aspect, the present application provides a computer-readable storage medium comprising instructions, which, when executed on a subway station emergency evacuation capability simulation test system, enables the subway station emergency evacuation capability simulation test system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Model the physical environment, personnel characteristics and obstacle impact of the subway station as a whole. The subway station model established based on subway station data reflects the actual physical environment; the pedestrian flow model takes into account the triple impact of destination attraction, crowd interaction and obstacle obstruction; the crowd flow information extracted from passenger flow data can accurately reflect the actual evacuation scene. This multi-factor comprehensive modeling method can truly simulate the behavior characteristics of the crowd during the emergency evacuation process, avoid the defects of simple mathematical calculations that ignore actual factors, and improve the accuracy of evacuation capacity assessment.

[0025] 2. A mechanical model of pedestrian movement was established to mathematically express the various influences in the crowd evacuation process. iRepresents the total expected data acting on pedestrians, including destination guidance force, crowd interaction force and obstacle expectation data; This reflects the acceleration changes of pedestrians. Through this mechanical modeling method, the movement law of the crowd during the evacuation process can be accurately described, especially the impact of crowd density on individual movement, so that the simulation results are more in line with the actual situation.

[0026] 3. A detailed mathematical model of crowd interaction was constructed. will The term reflects the individual's driving force to move toward the goal, which is regulated by the difference between the desired speed and the current speed; secondly, f ij The term represents the repulsive force and tangential force between people, reflecting the avoidance behavior when the crowd is dense; finally, f iw The term describes the hindering effect of obstacles on crowd movement. This mathematical description enables the model to accurately reflect the complex behavioral characteristics of the crowd in a crowded state. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flow chart of a subway station emergency evacuation capability simulation test method in an embodiment of the present application; Figure 2 It is a specific flow chart of step S105 and step S106 in the embodiment of the present application; Figure 3 It is an exemplary hardware structure diagram of the subway station emergency evacuation capability simulation test system in the embodiment of the present application.

[0028] FIG4( a ) is a schematic diagram of the lower platform layer at the first moment in the embodiment; FIG4( b ) is a schematic diagram of the lower station hall layer at the first moment in the embodiment; FIG5( a ) is a schematic diagram of the lower platform layer at the second moment in the embodiment; FIG5( b ) is a schematic diagram of the lower station hall layer at the second moment in the embodiment; FIG6( a ) is a schematic diagram of the lower platform layer at the third moment in the embodiment; FIG6( b ) is a schematic diagram of the lower station hall layer at the third moment in the embodiment; FIG7( a ) is a schematic diagram of the lower platform layer at the fourth moment in the embodiment; FIG7( b ) is a schematic diagram of the lower station hall layer at the fourth moment in the embodiment; FIG8( a ) is a schematic diagram of the lower platform layer at the fifth moment in the embodiment; FIG8( b ) is a schematic diagram of the lower station hall layer at the fifth moment in the embodiment; FIG9( a ) is a schematic diagram of the lower platform layer at the sixth moment in the embodiment; FIG9( b ) is a schematic diagram of the lower station hall layer at the sixth moment in the embodiment; Fig.10 is a schematic diagram of the platform layer at the eighth moment in the embodiment; Fig.11 This is a schematic diagram of the lower station hall layer at the ninth moment in the embodiment; Fig.12 This is a schematic diagram of the lower station hall layer at the tenth moment in the embodiment; Fig.13 is a schematic diagram of the station hall layer at the eleventh moment in the embodiment; DETAILED DESCRIPTION

[0029] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to and includes any or all possible combinations of one or more listed items.

[0030] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0031] See also Figure 1 , Figure 1 This is a flow chart of a subway station emergency evacuation capability simulation test method in an embodiment of the present application; S101, obtaining basic data, the basic data including subway station data and passenger flow data; Among them, basic data refers to the basic information set required for the simulation test of the emergency evacuation capacity of subway stations. Subway station data refers to the data set that describes the physical characteristics and operating status of subway stations, including station location data, station structure data, facility and equipment data, and operation management data. Passenger flow data is used to represent the statistical information of personnel flow in subway stations, including the number of people entering and leaving the station in each time period, the distribution of people in the station, and passenger flow characteristics in typical scenarios. For example, total passenger flow data: records the total passenger flow in a specific scenario; time distribution data: the proportion of passenger flow distribution reflected in the relationship with the most recent departure time; spatial distribution data: the specific number of pedestrians in each area; location feature data: used to determine the distribution position of pedestrian models in each area.

[0032] In some specific embodiments, the subway station data includes: Station location data, including the station's location, passenger source areas at each entrance and exit, and external evacuation routes; Station structure data, including the actual physical structure of the station and CAD drawing data; Facility and equipment data, including the type, quantity and spatial location information of the facilities and equipment within the station; Operation management data, including equipment activation status and passenger flow organization plan within the station.

[0033] It can be seen that a comprehensive subway station data system has been built. Data is collected from multiple dimensions such as station location, physical structure, facilities and equipment, and operation management, providing complete basic information for the model and ensuring the accurate restoration of the physical space. The consideration of the equipment opening status makes the simulation closer to the actual operation status.

[0034] S102, establishing a subway station model based on the subway station data; The subway station model refers to a two-dimensional space model or a three-dimensional space model that digitally expresses the actual subway station.

[0035] After the basic data is acquired, it is necessary to build a digital model of the subway station that can support subsequent simulation calculations. In some embodiments, the process of building a subway station model includes: first parsing the CAD drawing data and extracting spatial geometric information; then converting the two-dimensional plane data into a three-dimensional model and adding three-dimensional information such as height and slope; then repairing and optimizing the model in detail to ensure the continuity and integrity of the space; and finally adding necessary physical properties and functional properties to each component in the model.

[0036] In some specific embodiments, CAD drawing data is imported into the modeling software; the identified components are automatically converted into a three-dimensional model.

[0037] S103, establishing a pedestrian flow model based on the subway station data, where the pedestrian flow model includes expected data of pedestrians under the influence of obstacles and other pedestrians in the destination and subway station data; Among them, the pedestrian streamline model refers to a mathematical model that describes the movement trajectory and behavior characteristics of pedestrians. The destination refers to the spatial location point that pedestrians expect to reach. Obstacles refer to fixed facilities or temporary structures that affect pedestrian movement. Expected data is used to represent the ideal movement direction and speed of pedestrians under the influence of various factors, including spatial constraints, target attraction, and interpersonal interaction.

[0038] After building the subway station model, it is necessary to build a streamline model that describes the movement of pedestrians. In some embodiments, the process of building a pedestrian streamline model includes: first determining the basic rules of pedestrian movement, including the shortest path selection, obstacle avoidance behavior, and group effect; then building an interactive relationship model between pedestrians and the environment, taking into account spatial constraints and facility impacts; then building an interaction model between pedestrians, including social forces such as following and avoiding; and finally integrating each sub-model into a complete pedestrian streamline model.

[0039] In some specific embodiments, the pedestrian flow model includes: F i =f wiff +f ij +f iw In the formula, F i is the expected data of pedestrian i under the influence of obstacles and other pedestrians in the destination and subway station data, and f wiff is the expected data of pedestrian i under the influence of the destination, f ij is the expected data of pedestrian i under the influence of pedestrian j, f iw is the expected data of pedestrian i under the influence of obstacle w in the subway station data, m i is the mass of pedestrian i, v i is the speed of pedestrian i.

[0040] It can be seen that the mechanical model of pedestrian movement is established, and the various influences in the crowd evacuation process are mathematically expressed. i Represents the total expected data acting on pedestrians, including destination guidance force, crowd interaction force and obstacle expectation data; This reflects the acceleration changes of pedestrians. Through this mechanical modeling method, the movement law of the crowd during the evacuation process can be accurately described, especially the impact of crowd density on individual movement, so that the simulation results are more in line with the actual situation.

[0041] Continuing with the above example, in some embodiments, the pedestrian flow model includes: In the formula, f wiff is the expected data of pedestrian i under the influence of the destination, m i is the mass of pedestrian i, is the expected speed of pedestrian i at t, v i (t) is the current speed of pedestrian i at time t, τ i is the adjusted reaction time of pedestrian i; f ijis the expected data of pedestrian i under the influence of pedestrian j, A i is the repulsive force intensity coefficient of pedestrian i, r ij is the sum of the radii of pedestrian i and pedestrian j in the subway station model, d ij is the center distance between pedestrian i and pedestrian j in the subway station model, B i is the range coefficient of pedestrian i, n ij is the unit vector from pedestrian i to pedestrian j, k is a constant coefficient, g(r ij -d ij ) is the judgment function, when r ij -d ij When g(r ij -d ij )=0, when r ij -d ij ≥0, g(r ij -d ij )=r ij -d ij , Δv ij is the tangential velocity difference between pedestrian i and pedestrian j, t ij n ij The orthogonal unit vectors of ; f iw is the expected data of pedestrian i under the influence of obstacle w in the subway station data, r i is the radius of pedestrian i in the subway station model, d iw is the center distance between pedestrian i and obstacle w in the subway station model, g(r i -d iw ) is the judgment function, when r i -d iw When g(r i -d iw )=0, when r i -d iw ≥0, g(r i -d iw )=r i -d iw , t iw n iw The orthogonal unit vectors.

[0042] It can be seen that a detailed mathematical model of crowd interaction is constructed, f will The term reflects the individual's driving force to move toward the goal, which is regulated by the difference between the desired speed and the current speed; secondly, f ij The term represents the repulsive force and tangential force between people, reflecting the avoidance behavior when the crowd is dense; finally, f iwThe term describes the hindering effect of obstacles on crowd movement. This mathematical description enables the model to accurately reflect the complex behavioral characteristics of the crowd in a crowded state.

[0043] Continuing with the above example, the nearest exit to the area where the pedestrian is located in the subway station data is taken as the destination.

[0044] It can be seen that by taking the nearest exit as the destination of pedestrians, it not only meets people's instinct to choose the shortest escape route in an emergency, but also avoids the local congestion caused by all people gathering at the same exit, making the simulation results closer to the actual evacuation process.

[0045] S104, obtaining a demand scenario, where the demand scenario is a scenario when an emergency evacuation capability simulation test is desired; The demand scenario refers to the emergency evacuation test environment under specific conditions. Emergency evacuation capability refers to the efficiency and effectiveness of subway stations in evacuating passengers in an emergency.

[0046] In some embodiments, considering a scenario in which a train enters a station during peak hours, all passengers on the train get off and all passengers waiting on the platform evacuate, during the evacuation process, except for the escalator under maintenance, all other escalators are used as evacuation routes.

[0047] S105, extracting corresponding passenger flow information and location information from passenger flow data based on demand scenarios; Among them, the flow of people information refers to the number of people passing through a specific area per unit time. Location information refers to the distribution status data of people in space.

[0048] After determining the demand scenario, it is necessary to obtain specific data that meets the scenario characteristics from the existing passenger flow data. In some embodiments, the process of extracting corresponding information includes: first determining data screening conditions according to the scenario requirements, such as time period, location area, etc.; then retrieving matching records from the passenger flow database; then classifying and summarizing the data to obtain the spatiotemporal distribution characteristics of the passenger flow; and finally converting the extracted data into a standard format for subsequent modeling.

[0049] S106, establishing a pedestrian model in the subway station model based on the passenger flow information and location information; The pedestrian model refers to the digital expression of a single pedestrian in a simulation environment, and the establishment process refers to the method of converting statistical data such as pedestrian flow and location into a specific pedestrian individual model.

[0050] After obtaining specific pedestrian flow data, it is necessary to generate corresponding individual pedestrian models in the subway station model. In some embodiments, the process of establishing pedestrian models includes: first determining the number of pedestrians to be generated based on the pedestrian flow; then assigning the initial positions of pedestrians according to the position information; then randomly assigning individual attributes that meet the statistical characteristics to each pedestrian model; and finally placing all pedestrian models at corresponding positions in the subway station model.

[0051] See also Figure 2 , Figure 2 It is a specific flow chart of step S105 and step S106 in the embodiment of the present application; In some specific embodiments, step S105 and step S106 specifically include: S201, obtaining the total passenger flow in the same scene as the demand scene in the passenger flow data; Among them, the same scene means a state with similarities in environmental conditions, time period characteristics, etc. The total passenger flow refers to the number of all passengers passing through the station within a specific time period. After determining the specific test demand scenario, it is necessary to obtain passenger flow data under similar circumstances in historical data as a reference. In some embodiments, the process of obtaining the total passenger flow of the same scene includes: first determining the key features of the scene, such as weekdays / holidays, morning and evening peaks / off-peaks, etc.; then retrieving historical records with the same features in the passenger flow database; then performing statistical analysis on the filtered data to calculate the average passenger flow; finally, making corrections based on the characteristics of the specific scene to obtain the final total passenger flow data.

[0052] S202. Determine the passenger flow distribution ratio according to the difference between the time of the demand scenario and the time of the latest departure in the passenger flow data; wherein the departure time refers to the specific time when the train departs from the platform. The time difference represents the interval between two time points. The passenger flow distribution ratio refers to the percentage of passenger flow at different time points in the total volume.

[0053] In some embodiments, the process of determining the crowd distribution ratio includes: first obtaining the specific time point of the demand scenario; then querying the nearest departure time within the time period; then calculating the difference between the two time points; and finally, according to a pre-established time difference-distribution ratio correspondence table, finding and obtaining the crowd distribution ratio corresponding to the current difference.

[0054] S203, calculating the number of pedestrians in each area according to the distribution ratio of pedestrian flow and the total pedestrian flow; Among them, the area division means dividing the station space into multiple functional blocks. The number of pedestrians refers to the number of people in each area. In some embodiments, the process of calculating the number of pedestrians in each area includes: first determining the division of each functional area in the station; then calculating the actual number of people at the current time point based on the total passenger flow and distribution ratio, and calculating the specific number of pedestrians in each area.

[0055] S204. Establish a pedestrian model in each area; and scatter the pedestrian model according to the spatial characteristics of the corresponding area; wherein the pedestrian model represents a digital expression of a single pedestrian individual. Spatial characteristics refer to the physical environment and layout characteristics of the area. After calculating the number of pedestrians in each area, it is necessary to generate a corresponding pedestrian model in the virtual environment. In some embodiments, the process of establishing and scattering the pedestrian model includes: first determining the available space based on the shape and area of ​​the area; then dividing the standing area considering the location of fixed facilities and obstacles; then determining the scattering grid according to the personnel density requirements; then creating a pedestrian model at the grid point; and finally randomly fine-tuning the pedestrian position to increase the sense of reality.

[0056] S205. Randomly add attribute features to the pedestrian model.

[0057] Among them, the attribute features represent the inherent characteristic parameters of individual pedestrians. In some embodiments, the process of adding attribute features includes: first determining the attribute type that needs to be assigned, such as weight, walking speed, etc.; then determining the distribution characteristics of each attribute based on statistical data; then randomly generating attribute values ​​that conform to the distribution law for each pedestrian; and finally making appropriate adjustments based on the correlation between attributes to ensure the rationality of the feature combination.

[0058] It can be seen that the total number of people is determined based on historical passenger flow data; the distribution ratio is calculated by time difference; and personnel are arranged in combination with spatial characteristics and random attributes. This multi-level modeling method not only ensures the accuracy of the total number of people, but also achieves the rationality of spatial distribution, making the initial state more in line with the actual situation.

[0059] S107. Load a pedestrian flow model into the subway station model, so that the pedestrian model moves under the action of the pedestrian flow model, and obtain a subway station emergency evacuation capacity simulation test report.

[0060] After completing the attribute configuration of the pedestrian model, it is necessary to simulate its evacuation behavior in an emergency situation. In some embodiments, the process of pedestrian movement simulation includes: first importing the preset pedestrian streamline model into the subway station model; then establishing the association between the pedestrian model and the streamline model; then setting the movement parameters of the pedestrian following the streamline; then starting the simulation calculation engine for dynamic simulation; and finally recording the time, path, density and other key data of the entire evacuation process to form a test report.

[0061] It can be seen that the physical environment, personnel characteristics and obstacle influence of the subway station are modeled as a whole. The subway station model established based on the subway station data reflects the actual physical environment; the pedestrian flow model takes into account the triple influence of destination attraction, crowd interaction and obstacle obstruction; the crowd flow information extracted from the passenger flow data can accurately reflect the actual evacuation scene. This multi-factor comprehensive modeling method can truly simulate the crowd behavior characteristics during the emergency evacuation process, avoid the defects of simple mathematical calculations that ignore actual factors, and improve the accuracy of evacuation capacity assessment.

[0062] In some embodiments, after step S107, the method further includes: S108, extracting parameters in relevant standards and regulations as simulation boundary conditions; Among them, standard regulations refer to normative documents issued by the state, industry or locality. Parameters represent specific numerical requirements specified in the specifications. Simulation boundary conditions refer to the restrictions that must be followed in the simulation test. Before starting the simulation test of emergency evacuation capacity, key parameters need to be extracted from relevant standards as boundary conditions for the test. In some embodiments, the parameter extraction process includes: first collecting relevant specifications such as "Subway Design Specifications", "Subway Design Fire Protection Standards", and "Subway Safety Evacuation Specifications"; then extracting the evacuation number requirements, and calculating the number of passengers and waiting personnel on a train during the super peak hour of the long-term forecast passenger flow; then determining the capacity parameters of various facilities, such as entrances and exits, stairs, escalators, etc.; then setting restrictions on safety exits and areas; at the same time, extracting operating parameters such as crowd density limits, pre-reaction time, and equipment availability; finally, setting these parameters as boundary conditions for the simulation system.

[0063] S109: If the test report does not meet the simulation boundary conditions, the test fails.

[0064] After completing the emergency evacuation capability simulation test, it is necessary to determine whether the test results meet the boundary condition requirements. In some embodiments, the test result determination process includes: first extracting key indicator data in the test report; then comparing these data with the pre-set boundary conditions item by item; if any indicator exceeds the limit range of the boundary condition, the test is determined to have failed; and at the same time, specific unqualified items are marked to provide a basis for subsequent optimization.

[0065] It can be seen that by using the parameters in relevant standards and regulations as simulation boundary conditions, an objective basis for evaluation is formed, ensuring the standardization of the test results.

[0066] The following introduces an exemplary subway station emergency evacuation capability simulation test system 300 provided in an embodiment of the present application. Figure 3 It is a schematic diagram of an exemplary hardware structure of a subway station emergency evacuation capability simulation test system 300 provided in an embodiment of the present application.

[0067] In some embodiments, the subway station emergency evacuation capability simulation test system 300 is a computer device or the subway station emergency evacuation capability simulation test system 300 includes a computer device. The computer device includes a processor, a memory and a network interface connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The network interface of the computer device is used to communicate with other external terminals or servers through a network connection. In some embodiments, the network interface can be a wired network interface, and in some embodiments, the network interface can also be a wireless network interface. When the computer program is executed by the processor, the method in the embodiment of the present application is implemented.

[0068] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0069] A specific embodiment is given below to illustrate the method.

[0070] The section passenger flow and passenger boarding and alighting flow are shown in Table 1.

[0071] Table 1, passenger flow statistics of a station According to the passenger flow forecast results, the maximum section passenger flow is the downward section during the morning peak, the peak hour section passenger flow is 7043 people / h, the number of people boarding the train downward during the peak hour is 301 people / h, and the number of people boarding the train upward during the peak hour is 5544 people / h. The passenger flow super peak coefficient is 1.32. The vehicles are mountain city As type vehicles, and the initial and recent trains are composed of 6 cars, and the long-term use is 7 cars. The number of trains running in the long-term peak hour is 20 pairs / h. It is calculated that during the super peak hour, a train entering the station carries 465 passengers and 386 people waiting on the platform. Therefore, the total number of simulated evacuees is 851.

[0072] The test scenario of the throughput simulation was set to evacuate passengers from a train entering the station and the waiting personnel on the platform during an ultra-peak hour with a long-term predicted passenger flow. To ensure the accuracy of the test results, multiple repeated experiments were conducted, and the simulation test results are as follows.

[0073] Please participate in the picture Figure 4(a) to Figure 13 , FIG4( a ) is a schematic diagram of the lower platform layer at the first moment in the embodiment; FIG4( b ) is a schematic diagram of the lower station hall layer at the first moment in the embodiment; FIG5( a ) is a schematic diagram of the lower platform layer at the second moment in the embodiment; FIG5( b ) is a schematic diagram of the lower station hall layer at the second moment in the embodiment; FIG6( a ) is a schematic diagram of the lower platform layer at the third moment in the embodiment; FIG6( b ) is a schematic diagram of the lower station hall layer at the third moment in the embodiment; FIG7( a ) is a schematic diagram of the lower platform layer at the fourth moment in the embodiment; FIG7( b ) is a schematic diagram of the lower station hall layer at the fourth moment in the embodiment; FIG8( a ) is a schematic diagram of the lower platform layer at the fifth moment in the embodiment; FIG8( b ) is a schematic diagram of the lower station hall layer at the fifth moment in the embodiment; FIG9( a ) is a schematic diagram of the lower platform layer at the sixth moment in the embodiment; FIG9( b ) is a schematic diagram of the lower station hall layer at the sixth moment in the embodiment; Fig.10 is a schematic diagram of the platform layer at the eighth moment in the embodiment; Fig.11 This is a schematic diagram of the lower station hall layer at the ninth moment in the embodiment; Fig.12 This is a schematic diagram of the lower station hall layer at the tenth moment in the embodiment; Fig.13 is a schematic diagram of the station hall layer at the eleventh moment in the embodiment; At the beginning of the simulated evacuation process, passengers are distributed on the train and the platform. After the evacuation begins, passengers on the train rush into the platform and evacuate to the platform level through escalators and stairs. Due to the limited capacity of the escalators, a large number of evacuees gather at the escalators. At the same time, it can be seen that around 150 seconds, most of the people who need to be evacuated on the platform level have been evacuated to the station hall level and left the station through the station exit. Only a small number of people who need to be evacuated gather in front of the escalator; at about 180 seconds, all simulated evacuees have left the platform, and the evacuation process has been completed, leaving only a few passengers on the station hall level; at about 240 seconds, all passengers have left the station hall level and reached the outside of the station through the exit escalator.

[0074] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0075] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0076] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0077] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A subway station emergency evacuation capability simulation test method, characterized in that: include: Acquire basic data, wherein the basic data includes subway station data and passenger flow data; Establishing a subway station model based on the subway station data; Establishing a pedestrian flow model based on the subway station data, the pedestrian flow model including expected data of pedestrians under the influence of obstacles and other pedestrians in the destination, subway station data; Obtaining a demand scenario, where the demand scenario is a scenario when an emergency evacuation capability simulation test is desired; Extracting corresponding passenger flow information and location information from the passenger flow data based on the demand scenario; Establishing a pedestrian model in the subway station model based on the pedestrian flow information and the location information; The pedestrian flow model is loaded into the subway station model, and the pedestrian model is made to move under the action of the pedestrian flow model, so as to obtain a simulation test report on the emergency evacuation capacity of the subway station.

2. The method according to claim 1, characterized in that The pedestrian flow model includes: F i =f wiff +f ij +f iw In the formula, F i is the expected data of pedestrian i under the influence of obstacles and other pedestrians in the destination and subway station data, and f wiff is the expected data of pedestrian i under the influence of the destination, f ij is the expected data of pedestrian i under the influence of pedestrian j, f iw is the expected data of pedestrian i under the influence of obstacle w in the subway station data, m i is the mass of pedestrian i, v i is the speed of pedestrian i.

3. The method according to claim 2, characterized in that The pedestrian flow model includes: In the formula, f wiff is the expected data of pedestrian i under the influence of the destination, m i is the mass of pedestrian i, is the expected speed of pedestrian i at t, v i (t) is the current speed of pedestrian i at t, τ i is the adjusted reaction time of pedestrian i; f ij is the expected data of pedestrian i under the influence of pedestrian j, A i is the repulsive force intensity coefficient of pedestrian i, r ij is the sum of the radii of pedestrian i and pedestrian j in the subway station model, d ij is the center distance between pedestrian i and pedestrian j in the subway station model, B i is the range coefficient of pedestrian i, n ij is the unit vector from pedestrian i to pedestrian j, k is a constant coefficient, g(r ij -d ij ) is the judgment function, when r ij -d ij <0, g(r ij -d ij )=0, when r ij -d ij When ≥0, g(r ij -d ij )=r ij -d ij , Δv ij is the tangential velocity difference between pedestrian i and pedestrian j, t ij n ij The orthogonal unit vectors of ; f iw is the expected data of pedestrian i under the influence of obstacle w in the subway station data, r i is the radius of pedestrian i in the subway station model, d iw is the center distance between pedestrian i and obstacle w in the subway station model, g(r i -d iw ) is the judgment function, when r i -d iw <0, g(r i -d iw )=0, when r i -d iw When ≥0, g(r i -d iw )=r i -d iw , t iw n iw The orthogonal unit vectors.

4. The method according to claim 2 or 3, characterized in that: The exit closest to the area where the pedestrian is located in the subway station data is used as the destination.

5. The method according to claim 1, characterized in that The step of extracting corresponding passenger flow information and location information from the passenger flow data based on the demand scenario, and establishing a pedestrian model in the subway station model based on the passenger flow information and the location information specifically includes: Obtaining the total passenger flow in the same scene as the demand scene in the passenger flow data; Determine the passenger flow distribution ratio according to the difference between the time of the demand scenario and the time of the latest departure in the passenger flow data; Calculate the number of pedestrians in each area according to the crowd distribution ratio and the total crowd flow; Establishing pedestrian models in each of the regions; and distributing the pedestrian models according to the spatial characteristics of the corresponding regions; Randomly add attribute features to the pedestrian model.

6. The method according to claim 1, characterized in that The subway station data includes: Station location data, including the station's location, passenger source areas at each entrance and exit, and external evacuation routes; Station structure data, including the actual physical structure of the station and CAD drawing data; Facility and equipment data, including the type, quantity and spatial location information of the facilities and equipment within the station; Operation management data, including equipment activation status and passenger flow organization plan within the station.

7. The method according to claim 1, characterized in that After the step of loading the pedestrian flow model into the subway station model, causing the pedestrian model to move under the action of the pedestrian flow model, and obtaining a subway station emergency evacuation capacity simulation test report, the method further includes: Extract parameters from relevant standards and regulations as simulation boundary conditions; If the test report does not meet the simulation boundary conditions, the test fails.

8. A subway station emergency evacuation capability simulation test system, characterized in that: The subway station emergency evacuation capacity simulation test system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the subway station emergency evacuation capacity simulation test system to execute the method described in any one of claims 1-7.

9. A computer program product comprising instructions, characterized in that When the computer program product runs on a subway station emergency evacuation capability simulation test system, the subway station emergency evacuation capability simulation test system is enabled to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on the subway station emergency evacuation capability simulation test system, the subway station emergency evacuation capability simulation test system is caused to execute the method as claimed in any one of claims 1 to 7.

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