A method for evaluating bus network resilience considering subway passenger evacuation and station failure propagation

Abstract

The present invention proposes a bus network resilience assessment method considering subway passenger evacuation and site failure propagation. The assessment method is used for an urban bus composite network. First, the urban public transportation network site map data, passenger flow OD data and vehicle operation related information are obtained. Then, the urban bus composite network considering the one-to-many coupling relationship between subway stations and conventional bus stations is constructed through the Space L method. At the same time, the re-decision of the travel mode of blocked passengers in the urban bus composite network under sudden interruption and the propagation process of site cascading failure are considered to define the composite network performance index considering the structure and operation performance. Based on the network performance curve, an urban bus composite network resilience assessment model is constructed to measure the resilience level of the urban bus composite network under sudden interruption. The method described in the present invention is conducive to accurately assessing the resilience of the urban bus composite network and improving the operational stability and safety of the bus system.

Description

Technical Field

[0001] The invention belongs to the technical field of emergency interruption management of public transportation systems, and in particular to a public transportation network resilience assessment method considering subway passenger evacuation and site failure propagation. Background Art

[0002] With the large-scale and multi-standard development of subway systems, the requirements for operational stability and safety of networked operation and management models are also increasing. The safety emergency management of subway operation emergencies involves organizational command systems, monitoring and early warning, information reporting, emergency response, and safeguard measures. It is necessary to take corresponding measures throughout the life cycle of disturbance events to reduce economic losses and negative social impacts.

[0003] Studying the disturbance problem of subway network from the perspective of resilience will help improve the ability of network structure to absorb disturbance and recover from disturbance damage, optimize its response process to disturbance events from the structural characteristics of the system itself, and ensure the high-quality operation of subway and conventional bus networks. Therefore, it is urgent and necessary to study the resilience of urban public transportation networks under different types of emergencies or accidents from an overall and macro perspective, so as to reduce the risks of subway and conventional bus network operations.

[0004] At present, the research objects of urban public transportation networks under sudden interruptions are mainly concentrated on subway networks, focusing on simulating continuous multi-site failures under deliberate attacks and random attacks, and analyzing the vulnerability and robustness of the network from the network topology structure level. The simulated attack method of directly deleting nodes or edges cannot fully reflect the actual situation of urban transportation networks under sudden subway interruptions, and ignores the dependence of bus networks on subway networks in performance evaluation. Therefore, how to quantify the impact of composite networks under different emergencies on passenger emergency evacuation and site cascading failure has become a key issue that needs to be solved urgently to quantify its network resilience level, and it has important practical significance. Summary of the invention

[0005] The present invention proposes a bus network resilience assessment method that takes into account subway passenger evacuation and station failure propagation. The method is conducive to accurately assessing the resilience of urban bus composite networks and improving the operational stability and safety of bus systems.

[0006] The present invention adopts the following technical solutions.

[0007] A bus network resilience assessment method considering subway passenger evacuation and station failure propagation is proposed. The assessment method is used for urban bus composite networks. First, the urban public transportation network site map data, passenger flow OD data and vehicle operation related information are obtained, and then the urban bus composite network considering the one-to-many coupling relationship between subway stations and conventional bus stations is constructed through the Space L method. At the same time, the re-decision of the travel mode of blocked passengers in the urban bus composite network under sudden interruption and the propagation process of station cascading failure are considered to define the composite network performance indicators considering structural and operational performance. Based on the network performance curve, an urban bus composite network resilience assessment model is constructed to measure the resilience level of the urban bus composite network under sudden interruption.

[0008] The evaluation method specifically comprises the following steps:

[0009] Step S1: Obtain geographic information data, passenger flow data and operation-related information of urban subways and regular bus stops;

[0010] Step S2: Using the station and line information of urban subway and regular bus stations obtained in step S1, a one-to-many coupling urban bus composite network is constructed. ;

[0011] Step S3: Using the composite network model constructed in step S2 and operation-related information, determine the operation adjustment strategy and suspension interval of the subway network ;

[0012] Step S4: Establish a cascading failure model for the composite network to determine the site status ;

[0013] Step S5: Using the network cascading failure model of step S4, a network performance function consisting of topology indicators and operational efficiency indicators is constructed. , and established an urban bus composite network resilience assessment model based on the network performance curve to measure the network resilience level.

[0014] In step S1, the urban public transportation network site map data includes: subway and regular bus sites and Location information, subway line layout, and turnaround station settings;

[0015] The information related to the operation of the urban public transportation network includes: the longitude and latitude coordinates of subway stations, passenger AFC card swiping data, the number of subway and regular bus lines and , subway and regular bus operation timetable, subway and regular bus departure frequency and , Train passenger capacity and , subway operation accident information.

[0016] In step S2, a composite urban bus network is constructed. The method is to build a single-layer urban subway network , conventional bus network , according to the coupling radius of the subway station Establish a one-to-many coupling relationship between the two sites, and then add a composite network layer edge .

[0017] The specific process of step S2 is as follows:

[0018] Step S21: Use the station and line information of the urban subway and conventional bus stations obtained in step S1 to construct a single-layer urban subway network based on the space-L method and single-deck conventional bus network , the formula is as follows:

[0019]

[0020]

[0021] in, , Respectively represent the subway and regular bus network node sets, , are nodes in the subway and regular bus network layers, , is the number of nodes in the subway and regular bus networks, , They represent the edge sets of subway and regular bus networks respectively, , is the physical relationship between the network nodes of the subway and regular bus network layers, , is the serial number of any node in the network;

[0022] Step S22: Calculate the distance between adjacent nodes in the network and identify subway stations In the coupling radius Regular bus stops within , establish new edges for subway and bus stops with coupling relationships , that is, the connection between the subway network layer and the conventional network layer ;

[0023] Step S23: Define the adjacency matrix A of the subway-conventional bus network to form a new double-decker bus network ,in is a set of composite network nodes, is the edge set of the composite network;

[0024]

[0025]

[0026]

[0027]

[0028] in, , , They are the adjacency matrices of the inter-layer relations of the subway, bus, and urban bus composite network; , They represent the connection relationship between nodes in subway and regular bus networks respectively. or Its neighboring nodes or If there is an open line between , otherwise it is 0; for a composite network, if and is a site with a coupling relationship, then ,otherwise, .

[0029] In step S3, the operation adjustment strategy and suspension interval of the subway network are determined. The method is: using the composite network model constructed in step S2 and operation related information to calculate the capacity of subway and bus stations , further set the disturbed sites under different interruption scenarios , and determine the operation adjustment strategy and suspension interval of the subway network in combination with the topological structure of the subway network and the setting of the return lines.

[0030] The specific process of step S3 is as follows:

[0031] Step S31: Calculate the edge carrying capacity between adjacent nodes in the network based on the acquired urban bus and subway operation data And the capacity of a single node , the formula is:

[0032]

[0033] In the formula, Representation Node and The number of lines that exist between Indicates subway or city bus lines The frequency of departure, Indicates the rated passenger capacity of subway or city bus;

[0034] Step S32: Based on the composite network model constructed in step S2, the stations are divided into three categories: terminal stations, general stations, and transfer stations. Station-level and one-way edge simulation attack scenarios are set up respectively. , interruption process time , , Respectively indicate the time when the interruption starts and ends;

[0035] Step S33: Along the disturbed site Search for the two nearest turnaround stations in the up and down directions of the line , , and rearrange the routes between the turnaround station and the first and last stations to ensure the normal operation of some sections of the line. The interrupted section is the section between the two turnaround stations. , where the interruption site collection , interrupt edge set , , .

[0036] In step S4, a cascading failure model of the composite network is established to determine the status of the site The method is: use the obtained subway passenger card swiping data to process the data to obtain the passenger flow matrix , calculated in the interruption interval Affected passenger flow , solve the feasible path set of subway passengers in the initial network and the network after the interruption , , and load redistribution is performed based on the passenger evacuation time cost.

[0037] The specific process of step S4 is as follows:

[0038] Step S41: Clean and process the AFC card swiping data of the subway station passengers obtained in step S1, including the traveler ID, card swiping location and card swiping time, and select the subway network passenger flow data during peak hours as the passenger travel OD matrix ;

[0039] Step S42: Use the K-short path search algorithm to solve the feasible path set between stations for passengers under normal operation and sudden interruption 、 , and determine whether the passenger's shortest path travel passes through the interruption interval , which will affect passenger flow Totally Affected Passenger Flow 、 Part of the affected passenger flow is in and out of the station and affecting passenger flow during travel , expressed as:

[0040]

[0041]

[0042]

[0043]

[0044]

[0045]

[0046] In the formula, 、 They are passenger flow conversion matrix and passenger flow path matrix respectively. Indicates that the passenger to The shortest travel path to the station, , ；

[0047] Step S43: According to the feasible path set in step S42 Determine whether there is an alternative feasible path for the blocked passenger flow in the interruption interval in the interruption composite network, and calculate the different types of affected passenger flows from to Valid paths between sites Travel time cost:

[0048] For normal travel flow not affected by the interruption, the travel time

[0049] ,

[0050] For the three types of affected passenger flows, the travel time calculation formula is as follows:

[0051] ,

[0052] or

[0053] or

[0054] In the formula, middle They represent the travel time cost of the k-th affected passenger flow in the composite network, represents the travel time cost of unaffected passenger flow, , Respectively indicate that the subway and bus are on the road section arrive The running time between Indicates the subway station The transfer time between the corresponding bus stops;

[0055] Step S44: Determine the probability of the affected passenger flow path selection in the composite network according to the logit model, and divide the different travel costs As travel time impedance and the random error term The sum of nodes and Travel between the two periods will be affected by passenger choices The path travel selection model is expressed as follows:

[0056]

[0057]

[0058]

[0059] In the formula, Indicates travel mode Random costs, Indicates k Passenger flow at the node and Travel options The probability of the path, are model parameters;

[0060] Step S45: distribute the affected passenger flow matrix calculated in step S42 to the composite network path according to a certain flow distribution algorithm, and calculate the key subway nodes according to the interval flow formula Transfer to its coupled bus stop Load , the formula is as follows:

[0061]

[0062]

[0063]

[0064]

[0065]

[0066] in, For Node and The obstructed passenger flow between For subway stations The conversion coefficient of , For failed nodes A set of bus nodes with coupling relationships, Indicates edge With path relationship;

[0067] Step S46: Update the node load according to the load redistribution strategy of S45 And further determine the station status of the upper bus network ,analyze the effect of cascading failure propagation between network layers;

[0068] For bus stops, the capacity of the next node will be interrupted according to the LC model. and site status It is expressed as:

[0069]

[0070]

[0071]

[0072]

[0073] in, For bus stops The initial load, is the standard node capacity, is the load parameter, is the capacity parameter, For Node state, when or The node is considered to be failed when the node is in fault state, otherwise it is in normal operation state.

[0074] The specific process of step S5 is as follows:

[0075] Step S51: Calculate the proportion of network failure nodes based on load distribution and site cascading failure process, and construct a network performance function under the two indicators of "network structure-operation efficiency" , the formula is as follows:

[0076]

[0077]

[0078]

[0079] In the formula, is the network structure performance index, and Respectively represent the maximum number of connected network nodes in the network before and after the cascade failure, is the network operation efficiency indicator, For Node and passenger flow between is the weight coefficient, determined by the CRITIC method;

[0080] Step S52: Combine the composite network resilience assessment framework under sudden interruption and the resilience connotation to construct a resilience curve and network performance function The composite network resilience measurement model is used to measure the network resilience under sudden subway interruption. The formula is as follows:

[0081]

[0082] In the formula, Indicates that it is not affected by the interruption Network performance at Indicates that after an interrupt occurs Network performance at all times, Indicates the resilience level of the composite network.

[0083] Compared with the prior art, the present invention has the following beneficial effects:

[0084] (1) The present invention constructs a composite urban bus network model with a "one-to-many" coupling relationship between urban subways and conventional buses, which can effectively depict the mutual influence between traveling passengers and subway and conventional bus systems, and make up for the heterogeneity of different transportation networks that is difficult to reflect in a single-layer network;

[0085] (2) The present invention considers the passenger evacuation behavior and station failure propagation under sudden interruption, establishes the correlation relationship between "failed station-stranded passengers-load distribution", and describes the cascading failure process of a composite transportation network that is more in line with the actual passenger travel situation.

[0086] (3) The urban bus composite network resilience assessment method proposed in the present invention, which takes into account passenger evacuation behavior and station failure propagation, can effectively measure the composite network resilience and provide a theoretical basis for public management departments to formulate emergency connection plans and emergency response measures. It makes up for the shortcomings of existing technical solutions in that the resilience of a single subway network is inaccurate, and it is difficult to accurately judge the impact of sudden accidents and flexibly take emergency measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0088] Attached Figure 1 It is a schematic diagram of the implementation flow of the method provided by the embodiment of the present invention;

[0089] Attached Figure 2 It is a schematic diagram of a process of acquiring urban subway and conventional bus geographic spatial data and constructing an urban bus composite network according to an embodiment of the present invention;

[0090] Attached Figure 3 It is a schematic diagram of a flow chart of designing different subway sudden interruption scenarios provided by an embodiment of the present invention;

[0091] Attached Figure 4 is a flow chart of a station cascading failure process simulating passenger evacuation in an embodiment of the present invention;

[0092] Attached Figure 5 It is a flow chart of constructing a composite network resilience assessment model based on network performance curves in an embodiment of the present invention. DETAILED DESCRIPTION

[0093] In order to make the features and advantages of this patent more obvious and easy to understand, the following embodiments are specifically described in detail as follows:

[0094] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0095] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0096] A bus network resilience assessment method considering subway passenger evacuation and station failure propagation is proposed. The assessment method is used for urban bus composite networks. First, the urban public transportation network site map data, passenger flow OD data and vehicle operation related information are obtained, and then the urban bus composite network considering the one-to-many coupling relationship between subway stations and conventional bus stations is constructed through the Space L method. At the same time, the re-decision of the travel mode of blocked passengers in the urban bus composite network under sudden interruption and the propagation process of station cascading failure are considered to define the composite network performance indicators considering structural and operational performance. Based on the network performance curve, an urban bus composite network resilience assessment model is constructed to measure the resilience level of the urban bus composite network under sudden interruption.

[0097] like Figure 1 As shown, the evaluation method specifically includes the following steps:

[0098] Step S1: Obtain geographic information data, passenger flow data and operation-related information of urban subways and regular bus stops;

[0099] Step S2: Using the station and line information of urban subway and regular bus stations obtained in step S1, a one-to-many coupling urban bus composite network is constructed. ;

[0100] Step S3: Using the composite network model constructed in step S2 and operation-related information, determine the operation adjustment strategy and suspension interval of the subway network ;

[0101] Step S4: Establish a cascading failure model for the composite network to determine the site status ;

[0102] Step S5: Using the network cascading failure model of step S4, a network performance function consisting of topology indicators and operational efficiency indicators is constructed. , and established an urban bus composite network resilience assessment model based on the network performance curve to measure the network resilience level.

[0103] In step S1, the urban public transportation network site map data includes: subway and regular bus sites and Location information, subway line layout, and turnaround station settings;

[0104] The information related to the operation of the urban public transportation network includes: the longitude and latitude coordinates of subway stations, passenger AFC card swiping data, the number of subway and regular bus lines and , subway and regular bus operation timetable, subway and regular bus departure frequency and , Train passenger capacity and , subway operation accident information.

[0105] In step S2, a composite urban bus network is constructed. The method is to build a single-layer urban subway network , conventional bus network , according to the coupling radius of the subway station Establish a one-to-many coupling relationship between the two sites, and then add a composite network layer edge .

[0106] like Figure 2 As shown, the specific process of step S2 is as follows:

[0107] Step S21: Use the station and line information of the urban subway and conventional bus stations obtained in step S1 to construct a single-layer urban subway network based on the space-L method and single-deck conventional bus network , the formula is as follows:

[0108]

[0109]

[0110] in, , Respectively represent the subway and regular bus network node sets, , are nodes in the subway and regular bus network layers, , is the number of nodes in the subway and regular bus networks, , They represent the edge sets of subway and regular bus networks respectively, , is the physical relationship between the network nodes of the subway and regular bus network layers, , is the serial number of any node in the network;

[0111] Step S22: Calculate the distance between adjacent nodes in the network and identify subway stations In the coupling radius Regular bus stops within , establish new edges for subway and bus stops with coupling relationships , that is, the connection between the subway network layer and the conventional network layer ;

[0112] Step S23: Define the adjacency matrix A of the subway-conventional bus network to form a new double-decker bus network ,in is a set of composite network nodes, is the edge set of the composite network;

[0113]

[0114]

[0115]

[0116]

[0117] in, , , They are the adjacency matrices of the inter-layer relations of the subway, bus, and urban bus composite network; , They represent the connection relationship between nodes in subway and regular bus networks respectively. or Its neighboring nodes or If there is an open line between , otherwise it is 0; for a composite network, if and is a site with a coupling relationship, then ,otherwise, .

[0118] In step S3, the operation adjustment strategy and suspension interval of the subway network are determined. The method is: using the composite network model constructed in step S2 and operation related information to calculate the capacity of subway and bus stations , further set the disturbed sites under different interruption scenarios , and determine the operation adjustment strategy and suspension interval of the subway network in combination with the topological structure of the subway network and the setting of the return lines.

[0119] like Figure 3 As shown, the specific process of step S3 is as follows:

[0120] Step S31: Calculate the edge carrying capacity between adjacent nodes in the network based on the acquired urban bus and subway operation data And the capacity of a single node , the formula is:

[0121]

[0122] In the formula, Representation Node and The number of lines that exist between Indicates subway or city bus lines The frequency of departure, Indicates the rated passenger capacity of subway or city bus;

[0123] Step S32: Based on the composite network model constructed in step S2, the stations are divided into three categories: terminal stations, general stations, and transfer stations. Station-level and one-way edge simulation attack scenarios are set up respectively. , interruption process time , , Respectively indicate the time when the interruption starts and ends;

[0124] Step S33: Along the disturbed site Search for the two nearest turnaround stations in the up and down directions of the line , , and rearrange the routes between the turnaround station and the first and last stations to ensure the normal operation of some sections of the line. The interrupted section is the section between the two turnaround stations. , where the interruption site collection , interrupt edge set , , .

[0125] In step S4, a cascading failure model of the composite network is established to determine the status of the site The method is: use the obtained subway passenger card swiping data to process the data to obtain the passenger flow matrix , calculated in the interruption interval Affected passenger flow , solve the feasible path set of subway passengers in the initial network and the network after the interruption , , and load redistribution is performed based on the passenger evacuation time cost.

[0126] like Figure 4 As shown, the specific process of step S4 is as follows:

[0127] Step S41: Clean and process the AFC card swiping data of the subway station passengers obtained in step S1, including the traveler ID, card swiping location and card swiping time, and select the subway network passenger flow data during peak hours as the passenger travel OD matrix ;

[0128] Step S42: Use the K-short path search algorithm to solve the feasible path set between stations for passengers under normal operation and sudden interruption 、 , and determine whether the passenger's shortest path travel passes through the interruption interval , which will affect passenger flow Totally Affected Passenger Flow 、 Part of the affected passenger flow is in and out of the station and affecting passenger flow during travel , expressed as:

[0129]

[0130]

[0131]

[0132]

[0133]

[0134]

[0135] In the formula, 、 They are passenger flow conversion matrix and passenger flow path matrix respectively. Indicates that the passenger to The shortest travel path to the station, , ；

[0136] Step S43: According to the feasible path set in step S42 Determine whether there is an alternative feasible path for the blocked passenger flow in the interruption interval in the interruption composite network, and calculate the different types of affected passenger flows from to Valid paths between sites Travel time cost:

[0137] For normal travel flow not affected by the interruption, the travel time

[0138] ,

[0139] For the three types of affected passenger flows, the travel time calculation formula is as follows:

[0140] ,

[0141] or

[0142] or

[0143] In the formula, middle They represent the travel time cost of the k-th affected passenger flow in the composite network, represents the travel time cost of unaffected passenger flow, , Respectively indicate that the subway and bus are on the road section arrive The running time between Indicates the subway station The transfer time between the corresponding bus stops;

[0144] Step S44: Determine the probability of the affected passenger flow path selection in the composite network according to the logit model, and divide the different travel costs As travel time impedance and the random error term The sum of nodes and Travel between the two periods will be affected by passenger choices The path travel selection model is expressed as follows:

[0145]

[0146]

[0147]

[0148] In the formula, Indicates travel mode Random costs, Indicates k Passenger flow at the node and Travel options The probability of the path, are model parameters;

[0149] Step S45: distribute the affected passenger flow matrix calculated in step S42 to the composite network path according to a certain flow distribution algorithm, and calculate the key subway nodes according to the interval flow formula Transfer to its coupled bus stop Load , the formula is as follows:

[0150]

[0151]

[0152]

[0153]

[0154]

[0155] in, For Node and The obstructed passenger flow between For subway stations The conversion coefficient of , For failed nodes A set of bus nodes with coupling relationships, Indicates edge With path relationship;

[0156] Step S46: Update the node load according to the load redistribution strategy of S45 And further determine the station status of the upper bus network ,analyze the effect of cascading failure propagation between network layers;

[0157] For bus stops, the capacity of the next node will be interrupted according to the LC model. and site status It is expressed as:

[0158]

[0159]

[0160]

[0161]

[0162] in, For bus stops The initial load, is the standard node capacity, is the load parameter, is the capacity parameter, For Node state, when or The node is considered to be failed when the node is in fault state, otherwise it is in normal operation state.

[0163] like Figure 5 As shown, the specific process of step S5 is as follows:

[0164] Step S51: Calculate the proportion of network failure nodes based on load distribution and site cascading failure process, and construct a network performance function under the two indicators of "network structure-operation efficiency" , the formula is as follows:

[0165]

[0166]

[0167]

[0168] In the formula, is the network structure performance index, and Respectively represent the maximum number of connected network nodes in the network before and after the cascade failure, is the network operation efficiency indicator, For Node and passenger flow between is the weight coefficient, determined by the CRITIC method;

[0169] Step S52: Combine the composite network resilience assessment framework under sudden interruption and the resilience connotation to construct a resilience curve and network performance function The composite network resilience measurement model is used to measure the network resilience under sudden subway interruption. The formula is as follows:

[0170]

[0171] In the formula, Indicates that it is not affected by the interruption Network performance at Indicates that after an interrupt occurs Network performance at all times, Indicates the resilience level of the composite network.

[0172] In summary, the present invention provides a method for evaluating the resilience of an urban bus composite network taking into account passenger evacuation behavior and site failure propagation. By acquiring geographic information data, passenger flow data and operation-related information of urban subways and conventional bus sites, an urban bus composite network model considering a one-to-many coupling relationship between subway sites and conventional bus sites is constructed. The re-decision of travel modes of blocked passenger flows under sudden interruptions and the propagation process of network cascade failures are considered to construct an urban bus composite network resilience evaluation model based on network performance curves to measure the resilience level of the urban bus network under sudden interruptions. The present invention can effectively evaluate the resilience of an urban bus composite network taking into account the emergency evacuation of passengers under sudden disturbances, analyze the failure propagation mechanism of disturbances in the network, make up for the lack of consideration of the impact of conventional bus evacuation in the resilience assessment of urban subway networks, and provide a reference for subway emergency management departments to take emergency response measures and improve the quality of bus network operations.

[0173] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0174] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0175] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0176] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0177] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

Claims

1. A bus network resilience assessment method considering subway passenger evacuation and station failure propagation, characterized by: The evaluation method is used for the urban public transport composite network. First, the urban public transport network site map data, passenger flow OD data and vehicle operation related information are obtained. Then, the urban public transport composite network considering the one-to-many coupling relationship between subway stations and conventional bus stations is constructed by the Space L method. At the same time, the re-decision of the travel mode of blocked passengers in the urban public transport composite network under sudden interruption and the propagation process of the cascading failure of the station are considered to define the composite network performance index considering the structure and operation performance. Based on the network performance curve, the resilience evaluation model of the urban public transport composite network is constructed to measure the resilience level of the urban public transport composite network under sudden interruption. The evaluation method specifically comprises the following steps: Step S1: Obtain geographic information data, passenger flow data and operation-related information of urban subways and regular bus stops; Step S2: Using the station and line information of the urban subway and regular bus stations obtained in step S1, a one-to-many coupling relationship urban bus composite network model is constructed; Step S3: using the composite network model constructed in step S2 and operation-related information, determine the operation adjustment strategy and suspension interval of the subway network; Step S4: Establishing a cascading failure model of the composite network to determine the status of the site; Step S5: Using the cascading failure model of step S4, a network performance function consisting of topology indicators and operational efficiency indicators is constructed. , and establish an urban bus composite network resilience assessment model based on the network performance curve to measure the network resilience level; In step S4, a method for establishing a cascading failure model of a composite network to determine the station status is as follows: using the acquired subway passenger card swiping data to perform data processing to obtain a passenger flow matrix, calculating the affected passenger flow under the influence of the interruption interval, solving the feasible path set of subway passengers in the initial network and the network after the interruption, and performing load redistribution based on the passenger evacuation time cost; The specific process of step S4 is as follows: Step S41: Clean and process the AFC card swiping data of the subway station passengers obtained in step S1, including the traveler ID, card swiping location and card swiping time information, and select the subway network passenger flow data during peak hours as the passenger travel OD matrix; Step S42: Use the K-short path search algorithm to solve the feasible path set between stations under normal operation and sudden interruption of passengers, and determine whether the shortest path of passengers passes through the interruption interval in turn, and divide the affected passenger flow into completely affected passenger flow 、 Part of the affected passenger flow includes the passenger flow in and out of the station and the passenger flow in travel. Step S43: Determine whether there is an alternative feasible path for the blocked passenger flow in the interruption interval in the interruption composite network according to the feasible path set in step S42, and calculate the different types of affected passenger flows from to The travel time cost of the effective paths between stations; Step S44: determining the probability of affected passenger flow path selection in the composite network according to the logit model, taking different travel costs as the sum of travel time impedance and random error terms; Step S45: distribute the affected passenger flow matrix calculated in step S42 to the composite network path according to the flow distribution algorithm, and calculate the key subway nodes according to the interval flow formula Transfer to its coupled bus stop Load; Step S46: Update the node load according to the load redistribution strategy of S45 and further determine the station status of the upper-level public transportation network, and analyze the cascading failure propagation effect between network layers.

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