Rail transit road network dynamic risk assessment method and system

Abstract

The invention relates to the technical field of network robustness analysis, in particular to a rail transit road network dynamic risk assessment method and system. According to the method, factors such as rail topological structure attributes, dynamic passenger flow fluctuation characteristics and station passenger flow load states are comprehensively considered, a rail network model and a passenger flow network model of a rail traffic road network are constructed, a passenger flow load redistribution strategy under initial station failure is designed, and a multi-dimensional rail traffic road network risk assessment index is calculated, so that the risk assessment accuracy of the rail traffic road network is improved. And analyzing and evaluating the operation risk of the rail transit road network under the failure of different initial stations. According to the technology, the overall connectivity of the network can be maintained, and the passenger flow load of each station can be balanced, so that the risk handling robustness of the rail transit road network is remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of network robustness analysis, in particular to a rail transit network dynamic risk assessment method and system. BACKGROUND

[0002] With the acceleration of urbanization process in China, rail transit has entered a new stage of network development, forming a complex network pattern of "ring line + radial line" and "multi-line transfer", and rail transit network has developed into a core infrastructure supporting the efficient operation of cities. Its operation safety is directly related to the stable operation of social economy and the reliability of public travel. Network risk, as a key indicator to measure the integrity of rail transit system under internal failure or external disturbance, its analysis accuracy directly determines the upper limit of emergency management capability. Especially under the current network operation background, high-density train operation and network effect-driven passenger flow are superimposed, making the initial failure of local stations easily produce cascading propagation effect through the interaction of dynamic passenger flow, thus leading to large-area service interruption. Therefore, developing a dynamic risk analysis method that can accurately depict the influence of dynamic passenger flow and effectively suppress fault diffusion has become an urgent need to ensure the resilience of rail transit system.

[0003] Currently, several typical methods have been formed for rail transit network risk assessment research. Some research focuses on network topology structure analysis, abstracting physical facilities as a complex network model, and evaluating its vulnerability based on static topological properties such as station degree and betweenness centrality. Another type of method attempts to introduce passenger flow factors, such as constructing a static passenger flow weighted network framework to analyze the cascading failure influence under fixed passenger flow mode. These methods fail to effectively couple the interaction between dynamic passenger flow and network topology. Models based on static topology cannot reflect the key influence of high peak period passenger flow load fluctuations on system stability. To further approach the actual situation, recent research has begun to focus on dynamic characteristics, such as capturing passenger flow time series changes through multi-time point modeling, or establishing a double-layer network model to depict the interaction between infrastructure and dynamic passenger flow network. Although this type of method considers time series changes, it also mainly focuses on passive simulation of fault propagation process, lacks active intervention technology for passenger flow, and cannot effectively improve robustness from the perspective of operation control.

[0004] Secondly, on the key passenger flow redistribution strategy, existing methods excessively rely on local structure attributes such as topological weight or station degree, ignoring the real-time load state of the station, a key operation indicator, which leads to the possibility of directing excessive passenger flow to stations that are already heavily loaded, thereby accelerating the propagation of cascading failure. These problems collectively result in the difficulty of existing analysis methods in comprehensively quantifying the comprehensive risk of the network under dynamic passenger flow scenarios. Therefore, it is of great significance to study the dynamic risk assessment method of rail transit network under dynamic passenger flow for ensuring its safe operation. SUMMARY

[0005] The application provides a kind of urban rail transit road network dynamic risk assessment method and system, to solve the problem of lack of efficient, accurate risk assessment means of existing urban rail transit road network under failure condition.

[0006] To solve the above technical problems, the technical scheme provided by the application is: In a first aspect, the application provides a kind of urban rail transit road network dynamic risk assessment method, comprising: S1: collect the track related information of rail transit road network, and construct the track network model of rail transit road network according to the track related information; S2: collect the passenger flow related information of rail transit road network, and construct the passenger flow network model of rail transit road network according to the passenger flow related information; S3: according to the track network model and passenger flow network model, design the passenger flow load redistribution strategy of rail transit road network under initial station failure; S4: based on the passenger flow load redistribution strategy, respectively calculate the risk assessment index of rail transit road network under initial station failure, the risk assessment index includes cascade failure scale, network efficiency and passenger flow distribution dispersion; S5: based on the risk assessment index, dynamic risk assessment is carried out.

[0007] In a second aspect, the application provides a kind of urban rail transit road network dynamic risk assessment system, comprising memory, processor and computer program stored in memory and running on processor, when the processor executes the computer program, the steps of the method described in the first aspect are realized.

[0008] Compared with the prior art, the application has the following advantages: The urban rail transit road network dynamic risk assessment method provided by the application is based on track-passenger flow double-layer coupling network and passenger flow redistribution strategy, realizes the accurate evaluation and active optimization of road network dynamic risk. The track network model and passenger flow network model of rail transit road network are constructed by comprehensively considering the track topological structure attribute, dynamic passenger flow fluctuation characteristics and station passenger flow load state and other factors, a passenger flow load redistribution strategy under initial station failure is designed, and the running risk of rail transit road network under different initial station failures is analyzed and evaluated by calculating multi-dimensional rail transit road network risk assessment index. In this way, the network overall connectivity can be maintained, and the passenger flow load of each station can be balanced, thereby significantly improving the robustness of rail transit road network in response to risk. BRIEF DESCRIPTION OF DRAWINGS

[0009] Figure 1 The flow chart of the urban rail transit road network dynamic risk assessment method of the preferred embodiment of the application is shown in the figure; Figure 2 A part of subway network diagram of Hangzhou urban rail transit, which is a preferred embodiment of the present application; Figure 3 A schematic diagram of network dynamic risk assessment index changing with time step under different initial failure modes in different time periods, which is a preferred embodiment of the present application; DETAILED DESCRIPTION The technical solutions of the present application will be described clearly and completely below. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without any creative work belong to the protection scope of the present application.

[0010] Unless otherwise defined, the technical terms or scientific terms used in the present application should be understood as the common meanings of the same by those skilled in the art. The terms “first”, “second” and similar terms used in the present application do not represent any order, number or importance, but are only used to distinguish different components. Similarly, the terms “one” or “a” and similar terms do not represent the number limitation, but represent the existence of at least one. The terms “connected” or “connected” and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms “up”, “down”, “left”, “right” and the like are only used to represent the relative positional relationship, when the absolute position of the described object is changed, the relative positional relationship is also changed accordingly.

[0011] Please refer to Figure 1 The present application provides a dynamic risk assessment method for urban rail transit network, comprising: S1: collecting track-related information of the rail transit network, and constructing a track network model of the rail transit network according to the track-related information; S2: collecting passenger flow-related information of the rail transit network, and constructing a passenger flow network model of the rail transit network according to the passenger flow-related information; S3: designing a passenger flow load redistribution strategy of the rail transit network under initial station failure according to the track network model and the passenger flow network model; S4: calculating risk assessment indexes of the rail transit network under initial station failure based on the passenger flow load redistribution strategy, the risk assessment indexes including cascade failure scale, network efficiency and passenger flow distribution dispersion; S5: performing dynamic risk assessment based on the risk assessment indexes.

[0012] The above rail transit network dynamic risk assessment method realizes accurate assessment and active optimization of the network dynamic risk based on a rail-passenger flow double-layer coupled network and a passenger flow redistribution strategy. Specifically, the method comprehensively considers factors such as rail topological structure attributes, dynamic passenger flow fluctuation characteristics and station passenger flow load states, constructs a rail network model and a passenger flow network model of the rail transit network, designs a passenger flow load redistribution strategy under an initial station failure, and analyzes and evaluates the rail transit network operation risk under different initial station failures by calculating multi-dimensional rail transit network risk assessment indexes. This technology can not only maintain the overall connectivity of the network, but also balance the passenger flow load of each station, thereby significantly improving the robustness of the rail transit network in response to risks.

[0013] The preferred embodiment of the present application takes the rail transit network of some subway lines in Hangzhou as an example for illustration, and the topological graph of the rail transit network is as shown in Figure 2 .

[0014] Further, based on the above parameters, the steps of the urban rail transit network dynamic risk assessment method provided by the present application are described in detail as follows: Optionally, the S1 comprises: S11, collecting rail-related information of the rail transit network, the related information including the number of stations, the number of lines, the actual latitude and longitude positions of each station and the distance between adjacent stations; S12, constructing a rail network model of the rail transit network according to the rail-related information of the rail transit network, the formula being: (1) In the formula, denotes the rail network model of the rail transit network, denotes the set of stations in the rail transit network, , i is the station index, , is the total number of stations in the rail transit network; denotes the set of lines connecting two adjacent stations in the rail transit network, , j is the station index adjacent to i , denotes the line between station and station , if station and station are connected by a rail, then , otherwise ; denotes the set of station capacities, , denotes the i th station The site capacity, i.e., the first i Sites The maximum passenger flow capacity threshold (i.e., the maximum passenger flow capacity of the station) is calculated using the following formula: (2) In the formula, For safety margin factor, for t Time of the first i Sites Passenger load, Within the statistical period t A collection of moments This is a time index within the statistical period. , These represent the start and end times of the statistical period, respectively.

[0015] Specifically, in this embodiment, the total number of stations in the rail transit network 81; The set of lines connecting two adjacent stations in a rail transit network ,in accordance with Figure 2 The topology map of the rail transit network shows the route information between stations; safety margin factor. 0.3.

[0016] Optionally, S2 includes: S21, Collect passenger flow information related to the rail transit network, including passenger travel origin and destination routes and operation information, and passenger flow entering and exiting each station; S22, Based on the passenger flow information of the rail transit network, construct a passenger flow network model for the rail transit network, using the following formula: (3) In the formula, This represents the set of paths from the origin to the destination of passengers in a rail transit network. , m, n For site indexing, This indicates the passenger's origin and destination travel information. If the passenger is at the station... , site If there are entry and exit operations, then ,otherwise , This represents the set of passenger flow loads at a station. , for t Time of the first i Sites The passenger flow load is calculated using the following formula: (4) wherein, , , are the weight coefficients of the passenger flow load with respect to the first i station , the first-order neighbor station (i.e., the station directly adjacent to i ) of the first station , and the second-order neighbor station (i.e., the station indirectly connected through the first-order neighbor station ) of the first i station ; , , , are the betweenness centrality of the passenger flow load with respect to the first i station , the first-order neighbor station , and the second-order neighbor station ; is the set of the first-order neighbor stations i of the first station , is the set of the second-order neighbor stations (i.e., the first-order neighbor stations of the station ) of the station ; is the passenger flow load coefficient factor; , , , are the normalized passenger flow intensities of the first t station i , the first-order neighbor station of the first i station , and the second-order neighbor station of the first i station at the time , respectively, and the formulas are as follows: (5) (6) (7) wherein, is the passenger flow influence factor, , , are the first i station , the first-order neighbor station i of the first station​ , No. i Sites Second-order neighbor sites Site density; , They are respectively in t Time Station Passenger flow entering and exiting the station (number of people per hour). , They are respectively in t Time Station First-order neighbor sites Passenger flow entering and exiting the station (number of people per hour). , They are respectively in t Time Station Second-order neighbor sites Passenger flow entering the station and passenger flow exiting the station (persons / hour); , .

[0017] Specifically, in this embodiment, the set of passenger travel origin and destination paths in the rail transit network. The factors influencing passenger flow are determined by the collected information on passenger origin and destination routes and operational procedures; 1.2; , , The values ​​are 0.2, 0.3, and 0.7 respectively. , It is determined by the passenger flow data collected from each station.

[0018] Optionally, S3 includes: S31, from the perspective of station congestion, defines the first in the rail transit network. i Sites The operating status is given by the formula: (8) In the formula, express t Time of the first i Sites In a normal state, the first one in a normal state i Sites Recorded as a normal site ; express t Time of the first i Sites In a state of complete failure, the first [unit / item] in a state of complete failure will be [the next / next / end]. i Sites Record as invalid site , represents t the passenger flow load of the i-th station at the initial time point, i the passenger flow load of the i-th station at the initial time point, represents the station capacity of the i-th station; i S32, the set of failed stations at the initial time point in the statistical period is constructed as ; the initial failed stations in the set of failed stations are reordered in ascending order, and the set of initial failed station information at the initial time point in the statistical period is constructed as , wherein , , respectively represent the i-th failed station at the initial time point, the failure state of the i-th failed station, and the passenger flow load of the i-th failed station, represents the total number of failed stations at the initial time point; the initial normal stations except the initial failed stations in the set of initial failed stations are reordered in ascending order, and the set of initial normal station information at the initial time point in the statistical period under the initial station failure is constructed as , , represents the total number of normal stations at the initial time point, and .

[0019] the passenger flow load at the i-th initial failed station at the initial time point is set to zero, and the formula is: (9) wherein, represents the i-th initial failed station at the initial time point, ​​​​​​​​​​​​​​​​​​​​​​​​​​​​Passenger load at an initially failed site; Specifically, in this embodiment, three initial failure modes are set to simulate different failure scenarios, namely: (1) Random Failure Mode: A site is randomly selected as the initial failure site. At this time, Total number of sites that fail at any time 1. Total number of normal sites 80.

[0020] (2) Betweenness-based failure mode: The site with the highest betweenness centrality is selected as the initial failure site. At this time, Total number of sites that fail at any time 1. Total number of normal sites 80.

[0021] (3) Degree-based failure mode: Select the site with the highest site degree (number of connections) as the initial failure site. At this time, Total number of sites that fail at any time 1. Total number of normal sites 80.

[0022] S33, Design a strategy for redistributing passenger load when a site fails.

[0023] exist At that moment, Time of the first One failed site Initial passenger load Assigned to the k normal site ,in or , yes Time of the first One failed site First-order neighbor sites (i.e. with) A set of directly adjacent stations. yes Time of the first One failed site Second-order neighbor sites (i.e., through first-order neighbor sites) With dead sites Indirectly connected sites), that is, sites The set of first-order neighbor sites; assigned to the first-order neighbor site. k normal site The formula for calculating passenger flow load is: (10) (11) (12) In the formula, In order to be in At all times Time of the first One failed site Passenger load Assigned to the k normal site Passenger load, , They are respectively Time of the first One failed site and the k Initial normal site The station load redistribution function relates to track topology attributes in the track network model and to passenger load attributes in the passenger flow network model. They are , The weighting coefficients, , For the first k normal site The betweenness (dimensionless), , These are adjustment parameters for track topology attributes and passenger flow load attributes, respectively. for Time of the first k normal site Passenger load, for Time of the first k normal site The site capacity, i.e., the first k normal site The maximum passenger flow capacity threshold (i.e., the maximum passenger flow capacity of the station). Specifically, in this embodiment, under the random failure mode, The values ​​are 0.4 and 0.6 respectively; based on the failure modes of betweenness, The values ​​are 0.4 and 0.6 respectively; based on the degree-based failure mode, The values ​​are 0.4 and 0.6 respectively; , They are 4 and 16 respectively.

[0024] S34. Construct a passenger flow load model for the rail transit network under passenger flow load redistribution. The calculation formula is as follows: (13) In the formula, , They are respectively Time of the first One failed site , No. k normal site Passenger load, , They are respectively Time of the first One failed site , No. k normal site Passenger load, , They represent The total number of sites that are currently down and those that are currently active; S35, execute S31 and S32, calculate and update. The first in the time-sharing rail transit network One failed site Information collection.

[0025] S36, if no new failed sites are generated, then... , If the condition is met, proceed to S4 for execution; otherwise, execute S33 and S34.

[0026] Specifically, in one example, .

[0027] Optionally, S4 includes: S41, Calculate the cascading fault scale of the rail transit network based on the passenger flow load model of the rail transit network under passenger flow redistribution. The formula is: (14) In the formula, express The total number of sites that are constantly down. .

[0028] The assessment is based on the following criteria: the larger the value of the cascading failure scale, the more accumulated number of failed sites during the cascading failure process, and the greater the spatial diffusion range of the failure propagation, thus achieving a direct measurement of the breadth of the failure's impact.

[0029] S42: Calculate the network efficiency of the rail transit network NE The formula is as follows: (15) In the formula, express t Time from the first k normal site To the jnormal site The shortest path length, ; for A collection of information on normal sites when a site is temporarily unavailable; The evaluation criteria are as follows: the higher the network efficiency value, the higher the overall network performance, the higher the effectiveness of connections between sites in the network, and the lower the risk of failure.

[0030] S43: Calculate the passenger flow dispersion of the rail transit network The formula is as follows: (16) In the formula, This represents the total number of stations in the rail transit network. for t Time of the first k normal site Passenger load, for t Time of the first k normal site Site capacity.

[0031] It is worth explaining that in formula (15) , The determination comes from S31, S32, S33, S34, and S35, after... , …, After the passenger flow load is redistributed due to the failure at the current time, the number and location of the failed stations determined at time t will be different. t The number and location of normal stations vary at different times, until... At any given moment, the number of failed stations is not increased. The dynamic evaluation in this application requires calculation, passenger flow redistribution, and evaluation at every moment. In other words, formula (15) is determined and constructed based on the processes of S31, S32, S33, S34, and S35.

[0032] The assessment was based on the following criteria: the higher the passenger flow dispersion value, the more concentrated the passenger flow is among a few stations, and the higher the risk to the reliability of the rail transit system service.

[0033] Furthermore, calculate the comprehensive risk index of the rail transit network. The formula is: (17) In the formula, , , These are the weighting coefficients for cascading failure scale, network efficiency, and passenger flow dispersion in the comprehensive risk index. Furthermore, based on the comprehensive risk index... A risk assessment is conducted; the higher the value of the comprehensive risk index, the higher the risk faced by the rail transit network operation. In one example, , , The values ​​are 0.3, 0.4, and 0.3. At time step t=20, the comprehensive risk index RAI reaches its maximum value of 24.2627. This is only an example and is not a limitation.

[0034] Specifically, in this embodiment, Figure 3 The results of road network risk assessments are presented under three different initial failure modes and at different time periods. The three different initial failure modes include Random Failure Mode (RM), Betweenness-Based Failure Mode (BM), and Degree-Based Failure Mode (DBM). (DM). Each subplot contains three types of curves: circles represent initial failure modes based on station degree, rectangles represent initial failure modes based on station betweenness, and triangles represent initial failure modes based on random stations. (a) shows the CFS of the rail transit network over time under three different initial failure modes (DM, BM, RM) during the morning rush hour. (b) shows the NE of the rail transit network over time under three different initial failure modes (DM, BM, RM) during the morning rush hour. (c) shows the PFD of the rail transit network over time under three different initial failure modes (DM, BM, RM) during the morning rush hour. (d) shows the CFS of the rail transit network over time under three different initial failure modes (DM, BM, RM) during the midday period. The curves showing the changes in FS over time are as follows: (e) shows the changes in NE of the rail transit network over time under three different initial failure modes (DM, BM, RM) during the midday period. (f) shows the changes in PFD of the rail transit network over time under three different initial failure modes (DM, BM, RM) during the midday period. (g) shows the changes in CFS of the rail transit network over time under three different initial failure modes (DM, BM, RM) during the evening peak period. (h) shows the changes in NE of the rail transit network over time under three different initial failure modes (DM, BM, RM) during the evening peak period. (i) shows the changes in PFD of the rail transit network over time under three different initial failure modes (DM, BM, RM) during the evening peak period.

[0035] Furthermore, the present invention also provides a dynamic risk assessment system for rail transit networks, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method described in the first aspect above. This dynamic risk assessment system for rail transit networks can implement various embodiments of the above-described dynamic risk assessment method for rail transit networks and achieve the same beneficial effects; therefore, further details are omitted here.

[0036] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A rail transit network dynamic risk assessment method, characterized in that, The method comprises the following steps: S1: collecting track-related information of the rail transit network, and constructing a track network model of the rail transit network according to the track-related information; S2: collecting passenger flow-related information of the rail transit network, and constructing a passenger flow network model of the rail transit network according to the passenger flow-related information; S3: designing an initial station failure passenger flow load redistribution strategy of the rail transit network according to the track network model and the passenger flow network model; S4: calculating a risk assessment index of the rail transit network under the initial station failure based on the passenger flow load redistribution strategy, wherein the risk assessment index comprises a cascade failure scale, a network efficiency and a passenger flow distribution dispersion; S5: performing dynamic risk assessment based on the risk assessment index.

2. The rail transit network dynamic risk assessment method according to claim 1, characterized in that, The S1 comprises: S11: collecting track-related information of the rail transit network, wherein the track-related information comprises a number of stations, a number of lines, actual latitude and longitude positions of each station and distances between adjacent stations; S12: constructing a track network model of the rail transit network according to the track-related information, and satisfying the following relationship: （1） In the formula, denotes a rail network model of a rail transit network, denotes a set of stations in the rail transit network, , i is a station index, , is a total number of stations in the rail transit network; denotes a set of lines connecting two adjacent stations in the rail transit network, , j is a station index adjacent to i , denotes a line between station and station , if station and station have a rail connection, then , otherwise ; denotes a set of station capacities, , denotes a station capacity of the i th station , i.e. a passenger flow load threshold value that the i th station can accommodate, and the calculation formula is as follows: （2） wherein is a safety margin coefficient, is t is the passenger flow load of the i site at the moment, is the set of moments within the statistical period, t is the set of moments within the statistical period, is the index of the moment within the statistical period, , is the start, end moment of the statistical period, respectively.

3. The rail transit network dynamic risk assessment method according to claim 1, characterized in that, The S2 comprises: S21: collecting passenger flow-related information of the rail transit network, wherein the passenger flow-related information comprises passenger trip origin-destination path and operation information, and in-and-out station passenger flow of each station; S22: constructing a passenger flow network model of the rail transit network according to the passenger flow-related information, and satisfying the following relationship: （3） In the formula, A passenger flow network model representing a rail transit network. This represents the set of paths from the origin to the destination of passengers in a rail transit network. , m, n For site indexing, This indicates the passenger's origin and destination travel information. If the passenger is at the station... , site If there are entry and exit operations, then ,otherwise , This represents the set of passenger flow loads at a station. , for t Time of the first i Sites The passenger flow load is calculated using the following formula: （4） wherein , , are weight coefficients of the passenger flow load with respect to the first i station , the first-order neighbor station i , the second-order neighbor station of the first station i ; , , , , are betweenness centrality of the passenger flow load with respect to the first i station , the first-order neighbor station , the second-order neighbor station ; is a set of the first-order neighbor stations i of the first station , is a set of the second-order neighbor stations of the station ; is a passenger flow load coefficient factor; , , are normalized passenger flow intensities of the first t station i , the first-order neighbor station , the second-order neighbor station i of the first station , the first i station at the time , respectively, and the formulas are as follows: （5） （6） （7） In the formula, As a factor influencing passenger flow, , , The first i Sites , No. i Sites First-order neighbor sites , No. i Sites Second-order neighbor sites Site density; , They are respectively in t Time Station Passenger flow entering and exiting the station , They are respectively in t Time Station First-order neighbor sites Passenger flow entering and exiting the station , They are respectively in t Time Station Second-order neighbor sites Passenger flow entering and exiting the station; , , Within the statistical period t A collection of moments This is a time index within the statistical period. , These represent the start and end times of the statistical period, respectively.

4. The rail transit network dynamic risk assessment method of claim 1, wherein, The S3 comprises: S31: Defining the first station in the rail transit network based on station congestion levels i Sites The operating state satisfies the following relationship: （8） In the formula, denotes t the time instant, i the first site, is in a normal state, the first site, i in a normal state is denoted as normal site ; denotes t the time instant, i the first site, is in a completely failed state, the first site, i in a completely failed state is denoted as failed site ; , denotes t the passenger flow site load of the first site, i at the time instant, denotes i the site capacity of the first site, ​​​ S32: Construct initial time point within statistical period The failure site set of the time point is: ; For the set of failed sites Initial failure site ,according to Reorder the data in ascending order to construct the initial time within the statistical period. The initial set of failed site information is as follows: ； wherein , , respectively represent the failure status of the th failure site, the passenger flow load of the th failure site, represent the total number of failure sites at the moment;​ All normal sites except the initial failure site in the set are reordered in descending order of the number of times of occurrence of the initial time point, and the initial normal site information set under the initial site failure in the statistical period is constructed as follows: The initial normal site information set under the initial site failure in the statistical period is as follows: ​ ； wherein, , , respectively represent the normal state of the th normal station, the normal state of the th normal station, the passenger flow load of the th normal station, represents the total number of normal stations at the moment, and ; Set the passenger flow load at the initial failed site to zero as follows: the time the initial failed site the initial failed site （9） In the formula, represents the time of the passenger flow load of the initial failure site S33: designing a passenger flow load redistribution strategy under station failure as follows: exist At that moment, Time of the first One failed site Initial passenger load Assigned to the k normal site ,in or , yes Time of the first One failed site First-order neighbor sites The set, yes Time of the first One failed site Second-order neighbor sites That is, the site The set of first-order neighbor sites; assigned to the first-order neighbor site. k normal site The formula for calculating passenger flow load is as follows: （10） （11） （12） In the formula, at the moment at the moment at the moment at the moment at the moment at the moment k at the moment at the moment , at the moment at the moment at the moment at the moment k at the moment at the moment are weight coefficients of , , , at the moment k at the moment at the moment , are adjustment parameters of the rail topology attribute and the passenger flow load attribute respectively, at the moment at the moment k at the moment at the moment at the moment at the moment k at the moment at the moment S34: constructing a passenger flow load model of the rail transit network under passenger flow load redistribution, and the calculation formula is as follows: （13） In the formula, , They are respectively Time of the first One failed site , No. k normal site Passenger load, , They are respectively Time of the first One failed site , No. k normal site Passenger load, , They represent The total number of sites that are currently down and those that are currently active; S35: repeatedly performing S31-S32, calculating and updating the time instant at which the first failed site set of information; S36: If no new failed sites are generated, at this time , , go to S4 for execution; otherwise, execute S33 and S34.

5. The rail transit network dynamic risk assessment method according to claim 1, characterized in that, The S4 comprises: S41: calculating the cascade failure scale of the rail transit network based on the passenger flow load model of the rail transit network under the passenger flow redistribution The formula is as follows: （14） In the formula, represents the total number of expired sites at the time, ; S42: Calculate the network efficiency of the rail transit network NE The formula is as follows: （15） In the formula, represents t the shortest path length from the first normal site k to the nth normal site ; j ; is the normal site information set under the site failure at the moment ;​​ S43: Calculate the passenger flow dispersion degree of the rail transit network The formula is as follows: （16） In the formula, is the total number of stations in the rail transit network, is t is the passenger flow load of the i-th normal station at the j-th time point, k is the passenger flow load of the i-th normal station at the j-th time point, is the passenger flow load of the i-th normal station at the j-th time point, is t is the station capacity of the i-th normal station at the j-th time point, k is the station capacity of the i-th normal station at the j-th time point, is the station capacity of the i-th normal station at the j-th time point.

6. The rail transit network dynamic risk assessment method according to claim 5, characterized in that, The S5 comprises: Computing a comprehensive risk indicator for a rail transit network satisfies the following relationship: （17） In the formula, , , are weight coefficients of the cascade failure scale, network efficiency and passenger flow dispersion in the comprehensive risk index, respectively. Based on the comprehensive risk index Perform risk assessment; wherein the greater the value of the comprehensive risk index, the higher the risk faced by the rail transit network operation. 7.A rail transit network dynamic risk assessment system, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, The processor implements the steps of the method of any one of claims 1-6 when executing the computer program.

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