Key damaged road section identification method, apparatus and device, and medium

Abstract

The invention discloses a key damaged road section recognition method, device and equipment and a medium, and relates to the field of complexity science, and the method comprises the steps: constructing a damaged road network recovery scene according to the to-be-processed information of a research region, the road section importance of the damaged road section is calculated through the three road section importance aspects of the road section importance based on the node degree, the road section importance based on the node betweenness and the road section importance based on the toughness ring, and the corresponding damaged road section recovery sequence is obtained based on the three road section importance aspects. Then the damaged road sections are recovered based on the importance degree sequences, the toughness characterization value corresponding to each importance degree sequence is calculated, the optimal damaged road section recovery sequence is determined according to the toughness characterization values corresponding to all the importance degree sequences, and then a key damaged road section set is determined; the problems that an existing method is difficult to apply to a large-scale road network and overall toughness improvement is ignored are solved, and the method is high in systematicness and flexibility.

Description

Technical Field

[0001] The present application relates to the field of complexity science, and in particular to a method, device, equipment and medium for identifying critical damaged road sections. Background Art

[0002] The road traffic network is an important infrastructure for the normal operation of modern society. Its safety and reliability are directly related to social stability and economic development. However, when natural disasters, accidents and other emergencies occur, the road network often suffers serious damage. How to quickly and effectively restore the damaged road sections and ensure the resilience and traffic capacity of the traffic network is an important scientific issue.

[0003] At present, the road section recovery strategies that consider road network resilience mainly focus on quickly repairing damaged sections to restore traffic functions as soon as possible. These strategies are mostly based on the modeling and analysis of small-scale road networks. However, the recovery methods of small-scale road networks are difficult to effectively apply to large-scale road networks. Due to the complexity and large number of nodes of large-scale road networks, more systematic and comprehensive recovery strategies are required after disasters, which may cause the failure of the road section recovery model under small-scale road networks. For large-scale road networks, the existing road section recovery strategies mainly focus on how to identify and prioritize the repair of key sections to ensure the connectivity and traffic capacity of the overall transportation network. However, the road section recovery strategy lacks consideration of the overall road network resilience, resulting in the inability to effectively guarantee important transportation needs such as emergency rescue and material transportation during post-disaster recovery. Summary of the invention

[0004] The purpose of this application is to provide a method, device, equipment and medium for identifying key damaged road sections, which can be applied to large-scale road networks and take into account the overall road network resilience, with strong systematicity and high flexibility.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for identifying a critical damaged road section, comprising:

[0007] Obtaining information to be processed in the research area; the information to be processed includes geographic longitude and latitude information and point of interest data;

[0008] Constructing a damaged road network restoration scenario based on the information to be processed in the study area; the damaged road network restoration scenario includes a damaged road section set, a road network before damage, a road network after damage, and a set of traffic demand; the damaged road network is composed of road network nodes and undamaged road sections; the starting point and end point corresponding to the traffic demand are road network nodes;

[0009] For each damaged road section in the damaged road section set, the road section importance of the damaged road section is calculated based on the road network before damage; the road section importance includes the road section importance based on node degree, the road section importance based on node betweenness and the road section importance based on toughness ring; the road section importance based on node degree is determined by the out-degree of the starting point and the in-degree of the end point in the damaged road section; the road section importance based on node betweenness is determined by the betweenness of the starting point and the betweenness of the end point in the damaged road section; the road section importance based on toughness ring represents the mutual accessibility between the starting point and the end point in the damaged road section and other nodes in the road network before damage;

[0010] For each target section importance, the target section importance of all the damaged sections are sorted to obtain the importance order corresponding to the target section importance; the target section importance is any one of the section importance based on node degree, the section importance based on node betweenness, and the section importance based on toughness ring;

[0011] In response to the set of traffic demands, for each importance order, the damaged road section is restored based on the importance order, and a toughness characterization value corresponding to the importance order is calculated; the toughness characterization value characterizes the change of the road network when the damaged road section is restored;

[0012] The optimal damaged road section restoration sequence is determined according to the toughness characterization values ​​corresponding to all the importance orders, and the key damaged road section set is determined according to all the damaged road sections corresponding to the optimal damaged road section restoration sequence.

[0013] In a second aspect, the present application provides a critical damaged road section identification device, comprising:

[0014] The module for obtaining information to be processed is used to obtain information to be processed in the research area; the information to be processed includes geographic longitude and latitude information and point of interest data;

[0015] A damaged road network restoration scenario construction module is used to: construct a damaged road network restoration scenario according to the information to be processed in the study area; the damaged road network restoration scenario includes a damaged road section set, a road network before damage, a road network after damage, and a set of traffic demand; the damaged road network is composed of road network nodes and undamaged road sections; the starting point and end point corresponding to the traffic demand are road network nodes;

[0016] The section importance calculation module is used to: for each damaged section in the damaged section set, calculate the section importance of the damaged section based on the road network before damage; the section importance includes the section importance based on node degree, the section importance based on node betweenness and the section importance based on toughness ring; the section importance based on node degree is determined by the out-degree of the starting point and the in-degree of the end point in the damaged section; the section importance based on node betweenness is determined by the betweenness of the starting point and the betweenness of the end point in the damaged section; the section importance based on toughness ring represents the mutual accessibility between the starting point and the end point in the damaged section and other nodes in the road network before damage;

[0017] An importance order determination module is used to: for each target road section importance, sort the target road section importances of all the damaged road sections to obtain the importance order corresponding to the target road section importance; the target road section importance is any one of the road section importance based on node degree, the road section importance based on node betweenness, and the road section importance based on toughness ring;

[0018] A toughness characterization value calculation module is used to: in response to a set of traffic demands, for each importance order, restore the damaged road section based on the importance order, and calculate a toughness characterization value corresponding to the importance order; the toughness characterization value represents a change in the road network when the damaged road section is restored;

[0019] The critical damaged road section determination module is used to: determine the best damaged road section restoration order according to all the toughness characterization values ​​corresponding to the importance order, and determine the critical damaged road section set according to all the damaged road sections corresponding to the best damaged road section restoration order.

[0020] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned method for identifying key damaged road sections.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned method for identifying key damaged road sections when executed by a processor.

[0022] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0023] The present application provides a method, device, equipment and medium for identifying critical damaged road sections. After constructing a damaged road network restoration scenario, the section importance of the damaged road section is calculated through three aspects of section importance, namely, section importance based on node degree, section importance based on node betweenness and section importance based on resilience ring. The corresponding damaged section restoration order (importance order) is obtained based on the above three aspects of section importance respectively. Then, based on each of the above importance orders, the damaged road section is restored, and the resilience characterization value corresponding to each importance order is calculated. The optimal damaged section restoration order is determined according to the resilience characterization values ​​corresponding to all importance orders, and then the set of critical damaged road sections is determined. This solves the problem that the existing methods are difficult to apply to large-scale road networks and ignore the improvement of overall resilience. The present application is highly systematic and flexible. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 This is an application environment diagram of a key damaged road section identification method in an embodiment of the present application;

[0026] Figure 2 A flowchart of a method for identifying a critical damaged road section provided in one embodiment of the present application;

[0027] Figure 3 A schematic diagram of a specific process of a method for identifying a critical damaged road section provided in an embodiment of the present application;

[0028] Figure 4 A schematic diagram of functional modules of a critical damaged road section identification device provided in one embodiment of the present application;

[0029] Figure 5 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0031] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0032] The critical damaged road section identification method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the pending information of the study area to the server 104. After the server 104 receives the pending information of the study area, for the pending information of the study area, the server 104 constructs a damaged road network recovery scenario according to the pending information of the study area, and calculates the section importance of the damaged section through three aspects of section importance, namely, the section importance based on the node degree, the section importance based on the node betweenness, and the section importance based on the toughness ring. The corresponding damaged section recovery order is obtained based on the above three aspects of section importance, and then the damaged section is restored based on each of the above importance orders, and the toughness characterization value corresponding to each importance order is calculated. The optimal damaged section recovery order is determined according to the toughness characterization values ​​corresponding to all importance orders, and then the key damaged section set is determined. The server 104 may feed back the obtained set of key damaged road sections for the study area to the terminal 102. In addition, in some embodiments, the key damaged road section identification method may also be implemented by the server 104 or the terminal 102 alone, such as the terminal 102 may directly identify the key damaged road sections for the information to be processed in the study area, or the server 104 may obtain the information to be processed in the study area from the data storage system and identify the key damaged road sections for the information to be processed in the study area.

[0033] The terminal 102 may be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.

[0034] In an exemplary embodiment, Figure 2 As shown, a method for identifying a critical damaged road section is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1The server 104 in the example is used as an example to illustrate the method, which includes the following steps 201 to 206. Among them:

[0035] Step 201: Obtain the information to be processed of the study area; the information to be processed includes geographic longitude and latitude information and point of interest data.

[0036] Step 202: construct a damaged road network recovery scenario based on the information to be processed in the study area; the damaged road network recovery scenario includes a damaged road section set, a road network before damage, a road network after damage, and a set of traffic demand; the damaged road network is composed of road network nodes and undamaged road sections; the starting point and end point corresponding to the traffic demand are road network nodes.

[0037] Step 203: For each damaged road section in the damaged road section set, the section importance of the damaged road section is calculated based on the road network before damage; the section importance includes the section importance based on node degree, the section importance based on node betweenness and the section importance based on toughness ring; the section importance based on node degree is determined by the out-degree of the starting point and the in-degree of the end point in the damaged road section; the section importance based on node betweenness is determined by the betweenness of the starting point and the betweenness of the end point in the damaged road section; the section importance based on toughness ring characterizes the mutual accessibility between the starting point and the end point in the damaged road section and other nodes in the road network before damage.

[0038] Step 204: For each target section importance, sort the target section importances of all the damaged sections to obtain an importance order corresponding to the target section importance; the target section importance is any one of the section importance based on node degree, the section importance based on node betweenness, and the section importance based on resilience ring.

[0039] Step 205: In response to the set of traffic demands, for each importance order, the damaged road section is restored based on the importance order, and a toughness characterization value corresponding to the importance order is calculated; the toughness characterization value characterizes the change in the road network when the damaged road section is restored.

[0040] Step 206: determining the best damaged road section restoration sequence according to all the toughness characterization values ​​corresponding to the importance order, and determining the key damaged road section set according to all the damaged road sections corresponding to the best damaged road section restoration sequence.

[0041] Implement the above steps 201 to 206, calculate the section importance of the damaged section through three aspects of section importance, namely, section importance based on node degree, section importance based on node betweenness, and section importance based on resilience ring, obtain the corresponding damaged section restoration order based on the above three aspects of section importance, then restore the damaged section based on each of the above importance orders, calculate the resilience characterization value corresponding to each importance order, determine the best damaged section restoration order according to the resilience characterization values ​​corresponding to all importance orders, and then determine the key damaged section set, which solves the problem that the existing methods are difficult to apply to large-scale road networks and ignore the improvement of overall resilience. The present application is highly systematic and flexible. It solves the problem that the existing section restoration strategies often ignore the resilience of the overall road network, especially the definition and improvement of resilience based on specific needs (such as humanitarian passage needs). The present application has the advantages of systematicity, high flexibility, and wide application. It can effectively improve the overall resilience of large-scale road networks, ensure that important passage needs are better met in post-disaster recovery, and has good practical application value.

[0042] This application uses a large-scale disaster-affected road network as an example to illustrate the application method. Specifically, during a heavy snowstorm, a road network with tens of thousands of road sections was paralyzed, and hundreds of humanitarian traffic needs needed to be met in a short period of time; it is now necessary to identify the key damaged sections of this large-scale road network, and after restoring them, meet the humanitarian traffic needs as much as possible or as quickly as possible, thereby improving the overall resilience of the road network.

[0043] The geographic latitude and longitude information of the study area in step 201 may come from a geographic information system (GIS) or other geographic data sources.

[0044] In another exemplary embodiment of the present application, the above step 202 is replaced by the following steps 301 to 303:

[0045] Step 301: Modeling the road network before and after damage;

[0046] Step 302: matching points of interest in the road network area;

[0047] Step 303: Analyze the traffic demand that needs to be met.

[0048] The specific process of step 301 is as follows: First, the geographical boundaries of the large-scale road network are defined through the geographical longitude and latitude information of the study area. Secondly, all road sections in the study area are taken as the edge set E, the undamaged road sections are taken as the edge set E1, the damaged road sections are taken as the edge set E2, and the joints or intersections between road sections in the edge set E are taken as the node set N. Based on the complex network theory, the road network G = (N, E) before the damage and the road network G1 = (N, E1) after the damage in the study area are constructed.

[0049] The method for determining the damaged road sections is as follows: This application can determine the damaged road sections through two levels: structural or functional. Among them, the determination method at the structural level is: including visible physical damage, such as cracks, collapses, and fractures on the road surface; the determination method at the functional level is: whether the road cannot meet its designed functions due to blizzard disasters, such as the speed limit of the road is reduced, the number of vehicle types allowed to pass is reduced, etc. If the current road speed is less than the set speed or the number of vehicle types currently allowed to pass is less than the set number of vehicle types, the current road section is considered to be a damaged section.

[0050] The specific meaning of the point of interest (POI) described in step 302 is as follows: a point of interest refers to a place or facility with a certain meaning or value in a specific geographical area. These points of interest can be natural or artificial, and are usually used in geographic information systems (GIS) and navigation systems to help people find important or interesting places. For example, large settlements, large stadiums, railway stations, airports, energy facilities, schools, hospitals and government agencies.

[0051] The specific process in step 302 is as follows: for each point of interest within the boundary of the study area, calculate the distance between it and each node in the node set N, and replace the longitude and latitude coordinates of the point of interest with the longitude and latitude of the nearest node to achieve the matching of the point of interest in the road network, thereby providing support for the traffic demand between the points of interest in step 303. In the optional scheme of this embodiment, the calculation of the distance between the point of interest and the road network node can adopt methods such as the great circle distance. The calculation formula of the great circle distance between the point of interest and the road network node is as follows:

[0052] d=radius×arccos(sin(x1)×sin(x2)+cos(x1)×cos(x2)×cos(y1-y2)) (1);

[0053] Where d is the great circle distance between the point of interest and the road network node, usually 6371.016371.01 (unit: km); (x1, y1) and (x2, y2) are the latitude and longitude of the point of interest and the road network node respectively.

[0054] The specific meaning of the traffic demand in step 303 is as follows: the number of people or objects that need to pass from a certain point of interest (O) to a certain point of interest (D) in the road network. For example, after a disaster, there is a large amount of humanitarian rescue support traffic demand from warehouses to supply sites in the road network.

[0055] The specific process of step 303 is as follows: first, the total amount of traffic demands that need to be met is counted; second, by analyzing the location information of the starting point O and the end point D of the traffic demands, the distribution characteristics of all traffic demands in the geographical space are analyzed, such as dispersed or dense. Dispersed means that all traffic demands are distributed relatively evenly in space; dense means that all traffic demands are distributed relatively densely in space, for example, they all start from the same place or go to the same place or pass through a certain important section of the road.

[0056] It should be noted that the distribution of traffic demand is closely related to key damaged sections. Under dense traffic demand distribution, nodes with high importance are likely to appear in the road network. If these nodes are damaged, repairing them will greatly increase traffic demand and improve the resilience of the road network, so these nodes are likely to become key damaged sections.

[0057] In another exemplary embodiment of the present application, the above step 203 is replaced by the following steps 401 to 402:

[0058] Step 401: Propose a road section importance index based on complex network theory;

[0059] Step 402: Propose a road section importance index based on the resilience ring.

[0060] Based on complex network theory, node importance indicators are selected from the local level and the global level respectively. Combined with the road damage background, a node importance indicator based on resilience ring is proposed. The resilience ring of a node refers to the shortest detour distance from a node back to the node. Based on the node importance indicator, a road section importance indicator is proposed.

[0061] The specific process of step 401 is as follows: at the local level, the out-degree of the starting point and the in-degree of the end point of a damaged section are calculated in the road network G = (N, E) before damage, and the sum of the out-degree of the starting point and the in-degree of the end point of the damaged section is used as the section importance index based on the node degree of the damaged section; at the global level, the betweenness of the starting point and the betweenness of the end point of a damaged section are calculated in the road network G = (N, E) before damage, and the sum of the betweenness of the starting point and the betweenness of the end point of the damaged section is used as the section importance index based on the node betweenness of the damaged section.

[0062] Considering the road network as a directed graph, the out-degree of the starting point of a road segment is the number of edges starting from the starting point, that is, the number of other nodes in the road network that can be reached by passing through only one road segment.

[0063] The in-degree of a road segment endpoint is the number of edges entering the endpoint, that is, the number of other nodes in the road network that can be directly connected to the endpoint of the road segment through only one road segment.

[0064] The betweenness of a node is the ratio of the number of all shortest paths passing through the node to the number of all shortest paths. The shortest path is the path with the least total number of sections or the smallest path cost (such as distance, time) among all possible paths from a starting node to a target node in a road network. This path can be composed of multiple nodes and sections. The number of all shortest paths is calculated as follows: for each pair of nodes in the road network, the number of all shortest paths from the starting node (starting point of the section) to the target node (end point of the section) is calculated, and then the number of all shortest paths of all node pairs is summed up. The calculation formula for the betweenness of a node is as follows:

[0065]

[0066] Among them, BC(i) is the betweenness of node i; g st is the number of all shortest paths from the starting point s to the end point t of the damaged road section, is the g from node s to t st The number of shortest paths passing through i among the shortest paths.

[0067] The node-betweenness-based link importance index of the damaged link (i, j) = BC(i) + BC(j), where BC(j) is the betweenness of the end point j.

[0068] The specific process of step 402 is as follows: for each damaged road section, the toughness ring at the starting point and the toughness ring at the end point of the damaged road section are calculated in the road network G = (N, E) before damage; the toughness ring at the starting point and the toughness ring at the end point of the damaged road section are averaged and normalized to obtain the road section importance index based on the toughness ring of the damaged road section; the greater the importance of each damaged road section based on the toughness ring, the worse the mutual accessibility between the starting point and the end point of the damaged road section and other nodes in the network, and the lower the degree of substitutability of the road section for connecting its starting point and end point, indicating that the damaged road section is likely to be a key link for restoring the connectivity of the road network. The calculation formula of the road section importance based on the toughness ring is as follows:

[0069]

[0070] Cycle i =min(d ik +d km +...+d nl +d li ), (i,k)...(l,i)∈G (5);

[0071] Among them, Cycle ij Cycle is the importance of the road segment (i, j) based on the toughness cycle; i ' jis the toughness cycle of the road section (i, j) before normalization; c is a constant; Cycle i Cycle is the resilient ring of node i in the road network; j is the resilient ring of the network node j; d ik Represents the distance of the edge (i, k) in the road network; (i, k) to (l, i) represent all the edges in the shortest detour path from the road network node i to the road network node i; G represents the road network before damage.

[0072] The specific process of step 204 is as follows: for each damaged section in the damaged section set E2, calculate the section importance based on node degree, the section importance based on node betweenness, and the section importance based on resilience ring respectively; for each target section importance, arrange all damaged sections in descending order of importance. Taking the section importance based on resilience ring as an example, the importance order corresponding to the section importance based on resilience ring is shown in formula (7):

[0073] {e1, e2, …, e i , e j ,…,e n},e i ∈E2, (6);

[0074]

[0075] In the formula, e i is the damaged road section in the damaged road section set E2, and n is the number of damaged road sections.

[0076] According to the importance index obtained in step 203, the damaged road sections are sorted; the damaged road sections are restored from the largest to the smallest importance according to the road section, and the changes in the road network resilience index are compared; the road section restoration order that will maximize the improvement in road network resilience is selected, and the first M damaged road sections are selected as the key damaged road sections according to the actual restoration resource constraints. M is a set number.

[0077] In another exemplary embodiment of the present application, the above-mentioned step 205 specifically includes: for each traffic demand, the damaged road section is restored based on each importance order, and the resilience characterization value corresponding to each importance order of the traffic demand is calculated based on the road network resilience characterization based on the degree of connectivity or the road network resilience characterization based on the shortest travel time; all the traffic demands are based on the resilience characterization value corresponding to each importance order to form the resilience characterization value corresponding to the importance order.

[0078] Specifically, the damaged sections are restored in order of importance; according to the actual traffic demand, the resilience representation R based on connectivity is selected. C Or the toughness characterization R based on the shortest transit time T, and calculate the changes in the toughness representation value when restoring the damaged road section according to different orders of importance.

[0079] The calculation formula of the resilience characterization value calculated based on the road network resilience characterization of the degree of connectivity for each traffic demand is as follows:

[0080]

[0081]

[0082] Among them, R C The resilience characterization value calculated based on the road network resilience characterization of the connectivity for each traffic demand; and is a 0 / 1 variable, indicating whether at least one feasible path can be found in the road network before restoration and in the road network after restoration, respectively, so that the starting point O and the end point D of the traffic demand are connected. A value of 1 indicates that the traffic demand is connected, and a value of 0 indicates that the traffic demand is not connected; and It is a 0 / 1 variable, which indicates whether the road section (i, j) is in a damaged state in the road network before restoration and in the road network after restoration. The value of 1 indicates that the road section (i, j) is not damaged, and the value of 0 indicates that the road section (i, j) is damaged; m represents all feasible paths between the starting point O and the end point D in the road network before damage.

[0083] The calculation formula of the toughness characterization value calculated based on the road network toughness characterization of the shortest travel time for each travel demand is as follows:

[0084]

[0085] Among them, R T The resilience characterization value calculated based on the road network resilience characterization of the shortest travel time for each travel demand; and is a non-negative continuous variable, which represents the reciprocal of the shortest travel time of the traffic demand with O and D as the starting point and end point, respectively, in the road network before restoration and after restoration. The larger the value, the higher the traffic efficiency of the traffic demand, and vice versa. and is a non-negative continuous variable, which represents the travel time required to pass the road section (i, j) in the road network before restoration and after restoration respectively; the travel time of a road section is obtained by dividing the length of the road section by the travel speed; and Represents all feasible paths with starting point O and end point D in the road network before and after restoration respectively.

[0086] In step 206, the optimal damaged road section restoration sequence is determined according to the toughness characterization values ​​corresponding to all the importance orders, specifically including:

[0087] When calculating the toughness characterization value using the road network toughness characterization based on the degree of connectivity, the importance order corresponding to the toughness characterization value with the largest value is determined as the optimal damaged road section restoration order;

[0088] When the toughness characterization value is calculated using the road network toughness characterization based on the shortest travel time, the importance order corresponding to the smallest toughness characterization value is determined as the optimal damaged road section restoration order.

[0089] That is, the order of importance with the largest or fastest increase in toughness characterization value is regarded as the best order for restoring damaged sections.

[0090] In step 206, a set of key damaged sections is determined according to all damaged sections corresponding to the optimal damaged section restoration sequence, specifically including:

[0091] The first set number of damaged road sections in the optimal damaged road section restoration sequence are determined as key damaged road sections; and all the key damaged road sections constitute a key damaged road section set.

[0092] In actual restoration scenarios, due to limited human and material resources, the number of roads that can be restored within the specified restoration time cannot exceed a certain number. Therefore, this application takes into account the actual restoration resource constraints, such as the number of repaired roads cannot exceed M, and the first M damaged sections are selected from the above-determined optimal damaged section restoration order as the key damaged sections.

[0093] The present application also provides an application scenario, which applies the above-mentioned critical damaged road section identification method. Specifically: the critical damaged road section identification method provided in this embodiment can be applied in content distribution scenarios. The road rescue scenario includes an information acquisition link, a critical damaged road section identification link, and a road restoration link; the information to be processed in the study area enters the critical damaged road section identification link from the information acquisition link, obtains the corresponding critical damaged road section set, and enters the downstream road restoration link. The critical damaged road section identification method provided in this embodiment belongs to the critical damaged road section identification link. Specifically, in the process of identifying the key damaged sections of the information to be processed in the study area, a damaged road network recovery scenario can be constructed based on the information to be processed in the study area, and the section importance of the damaged sections can be calculated through three aspects of section importance: section importance based on node degree, section importance based on node betweenness, and section importance based on resilience ring. Based on the above three aspects of section importance, the corresponding damaged section recovery order is obtained, and then the damaged sections are restored based on each of the above importance orders, and the resilience representation value corresponding to each importance order is calculated. The optimal damaged section recovery order is determined according to the resilience representation values ​​corresponding to all importance orders, and then the set of key damaged sections is determined.

[0094] like Figure 3 As shown, this application mainly proposes a set of systematic solutions for how to identify critical damaged sections in large-scale road networks. First, by constructing a restoration scenario for a large-scale damaged road network, including modeling of the road network before and after damage, matching of points of interest within the road network area, and analysis of traffic demand, a preliminary damaged road network model is established; then, the road network resilience is defined based on traffic demand, including resilience characterization in two dimensions: connectivity and shortest travel time; then, a road section importance index is proposed, which is defined based on complex network theory and the resilience ring method respectively; finally, by combining road network resilience and road section importance, a method for identifying critical damaged sections is proposed, including the sorting of sections under different importance indicators, the selection of the best restoration order, and the identification of critical sections considering actual restoration resource constraints. The method for identifying critical damaged sections that considers the resilience of large-scale road networks adopted in this application solves the problem that existing methods are difficult to apply to large-scale road networks and ignore the improvement of overall resilience.

[0095] This application has the following beneficial effects:

[0096] 1. Systematic: This application systematically integrates the information of various important elements in the road network by constructing a recovery scenario for a large-scale damaged road network, including road network modeling before and after damage, point of interest matching, and traffic demand analysis. This comprehensive approach can fully reflect the changes and recovery needs of the road network before and after the disaster, which helps to fully understand and improve the overall resilience of large-scale road networks, thereby providing more accurate recovery strategies.

[0097] 2. High flexibility: This application uses connectivity and the shortest travel time as resilience indicators, which can flexibly reflect different types of travel needs. At the same time, a road section importance index based on complex network theory and resilience ring is proposed. According to actual conditions and needs, the resilience representation and importance calculation method can be flexibly adjusted to adapt to the road network recovery needs in different scenarios, thereby providing a more adaptable solution.

[0098] 3. Wide application: The critical damaged road section identification method proposed in this application has a wide range of application value. It is not only suitable for the restoration of large-scale road networks, but also can ensure the rapid and efficient restoration of critical road sections after disasters under different disaster and accident scenarios by sorting road sections under different importance indicators, selecting the best restoration sequence, and considering actual restoration resource constraints. In addition, through the combination of systematicity and flexibility, this method can provide effective road network restoration solutions in various complex and dynamically changing environments, ensuring that critical traffic needs can be prioritized in emergency situations.

[0099] Based on the same inventive concept, the embodiment of the present application also provides a critical damaged road section identification device for implementing the critical damaged road section identification method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations of one or more critical damaged road section identification device embodiments provided below can refer to the limitations of the critical damaged road section identification method above, and will not be repeated here.

[0100] In an exemplary embodiment, Figure 4 As shown, a key damaged road section identification device is provided, comprising:

[0101] The module T1 for obtaining information to be processed is used to obtain information to be processed in the research area; the information to be processed includes geographic longitude and latitude information and point of interest data;

[0102] The damaged road network restoration scenario construction module T2 is used to: construct a damaged road network restoration scenario according to the information to be processed in the study area; the damaged road network restoration scenario includes a damaged road section set, a road network before damage, a road network after damage, and a set of traffic demand; the damaged road network is composed of road network nodes and undamaged road sections; the starting point and end point corresponding to the traffic demand are road network nodes;

[0103] The section importance calculation module T3 is used to: for each damaged section in the damaged section set, calculate the section importance of the damaged section based on the road network before damage; the section importance includes the section importance based on node degree, the section importance based on node betweenness and the section importance based on toughness ring; the section importance based on node degree is determined by the out-degree of the starting point and the in-degree of the end point in the damaged section; the section importance based on node betweenness is determined by the betweenness of the starting point and the betweenness of the end point in the damaged section; the section importance based on toughness ring characterizes the mutual accessibility between the starting point and the end point in the damaged section and other nodes in the road network before damage;

[0104] The importance order determination module T4 is used to: sort the importance of each target road section according to the target road section importance of all the damaged road sections to obtain the importance order corresponding to the target road section importance; the target road section importance is any one of the road section importance based on node degree, the road section importance based on node betweenness and the road section importance based on toughness ring;

[0105] The toughness characterization value calculation module T5 is used to: in response to the set of traffic demands, for each importance order, restore the damaged road section based on the importance order, and calculate the toughness characterization value corresponding to the importance order; the toughness characterization value represents the change of the road network when the damaged road section is restored;

[0106] The critical damaged road section determination module T6 is used to determine the best damaged road section restoration sequence according to all the toughness characterization values ​​corresponding to the importance order, and determine the critical damaged road section set according to all the damaged road sections corresponding to the best damaged road section restoration sequence.

[0107] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. 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 key damaged road section identification data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a key damaged road section identification method is implemented.

[0108] Those skilled in the art will understand that Figure 5 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.

[0109] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0110] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0111] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0112] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0113] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0114] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0115] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for identifying critical damaged road sections, characterized in that: The key damaged road section identification method comprises: Obtaining information to be processed in the research area; the information to be processed includes geographic longitude and latitude information and point of interest data; Constructing a damaged road network restoration scenario based on the information to be processed in the study area; the damaged road network restoration scenario includes a damaged road section set, a road network before damage, a road network after damage, and a set of traffic demand; the damaged road network is composed of road network nodes and undamaged road sections; the starting point and end point corresponding to the traffic demand are road network nodes; For each damaged road section in the damaged road section set, the road section importance of the damaged road section is calculated based on the road network before damage; the road section importance includes the road section importance based on node degree, the road section importance based on node betweenness and the road section importance based on toughness ring; the road section importance based on node degree is determined by the out-degree of the starting point and the in-degree of the end point in the damaged road section; the road section importance based on node betweenness is determined by the betweenness of the starting point and the betweenness of the end point in the damaged road section; the road section importance based on toughness ring characterizes the mutual accessibility between the starting point and the end point in the damaged road section and other nodes in the road network before damage; For each target section importance, the target section importance of all the damaged sections are sorted to obtain the importance order corresponding to the target section importance; the target section importance is any one of the section importance based on node degree, the section importance based on node betweenness, and the section importance based on toughness ring; In response to the set of traffic demands, for each importance order, the damaged road section is restored based on the importance order, and a toughness characterization value corresponding to the importance order is calculated; the toughness characterization value characterizes the change of the road network when the damaged road section is restored; The optimal damaged road section restoration sequence is determined according to the toughness characterization values ​​corresponding to all the importance orders, and the key damaged road section set is determined according to all the damaged road sections corresponding to the optimal damaged road section restoration sequence.

2. The critical damaged road section identification method according to claim 1 is characterized in that: In response to the set of traffic demands, for each importance order, the damaged road section is restored based on the importance order, and the toughness characterization value corresponding to the importance order is calculated, specifically including: For each traffic demand, the damaged road section is restored based on each importance order, and the resilience characterization value corresponding to each importance order of the traffic demand is calculated according to the road network resilience characterization based on the degree of connectivity or the road network resilience characterization based on the shortest travel time; the resilience characterization value corresponding to each importance order of all the traffic demands based on the resilience characterization value corresponding to the importance order constitutes the resilience characterization value corresponding to the importance order.

3. The critical damaged road section identification method according to claim 2 is characterized in that: The calculation formula for the resilience characterization value of each traffic demand based on the road network resilience characterization of connectivity is as follows: Among them, R C The resilience characterization value calculated based on the road network resilience characterization of the degree of connectivity for each traffic demand; and They respectively indicate whether at least one feasible path can be found in the road network before restoration and in the road network after restoration to connect the starting point O and the end point D of the traffic demand; and They respectively indicate whether the road section (i, j) is in a damaged state in the road network before restoration and in the road network after restoration; m represents all feasible paths between the starting point O and the end point D in the road network before damage; the road network after restoration is the road network after the damaged sections are restored based on the order of importance.

4. The critical damaged road section identification method according to claim 2 is characterized in that: The calculation formula of the toughness characterization value calculated based on the road network toughness characterization of the shortest travel time for each travel demand is as follows: Among them, R T The resilience characterization value calculated based on the road network resilience characterization of the shortest travel time for each travel demand; and Respectively represent the traffic demand with O and D as the starting point and end point, and the reciprocal of the shortest travel time in the road network before and after restoration; and Respectively represent the travel time required to pass through the road section (i, j) in the road network before restoration and in the road network after restoration; and Represents all feasible paths with starting point O and end point D in the road network before and after restoration respectively.

5. The critical damaged road section identification method according to claim 1, characterized in that: The calculation formula of the road section importance based on the toughness ring is as follows: Cycle i =min(d ik +d km +...+d nl +d li ),(i,k)...(l,i)∈G; Among them, Cycle ij Cycle is the importance of the road segment (i, j) based on the toughness cycle; i ' j is the toughness cycle of the road section (i, j) before normalization; c is a constant; Cycle i Cycle is the resilient ring of node i in the road network; j is the resilient ring of the network node j; d ik Represents the distance of the edge (i, k) in the road network; (i, k) to (l, i) represent all the edges in the shortest detour path from the road network node i to the road network node i; G represents the road network before damage.

6. The critical damaged road section identification method according to claim 2 is characterized in that: The optimal damaged road section restoration sequence is determined according to the toughness characterization values ​​corresponding to all the importance orders, specifically including: When calculating the toughness characterization value using the road network toughness characterization based on the degree of connectivity, the importance order corresponding to the toughness characterization value with the largest value is determined as the optimal damaged road section restoration order; When the toughness characterization value is calculated using the road network toughness characterization based on the shortest travel time, the importance order corresponding to the smallest toughness characterization value is determined as the optimal damaged road section restoration order.

7. The critical damaged road section identification method according to claim 1, characterized in that: Determining a set of key damaged road sections according to all damaged road sections corresponding to the optimal damaged road section restoration sequence specifically includes: The first set number of damaged road sections in the optimal damaged road section restoration sequence are determined as key damaged road sections; and all the key damaged road sections constitute a key damaged road section set.

8. A device for identifying critical damaged road sections, characterized in that: The key damaged road section identification device comprises: The module for obtaining information to be processed is used to obtain information to be processed in the research area; the information to be processed includes geographic longitude and latitude information and point of interest data; A damaged road network restoration scenario construction module is used to: construct a damaged road network restoration scenario according to the information to be processed in the study area; the damaged road network restoration scenario includes a damaged road section set, a road network before damage, a road network after damage, and a set of traffic demand; the damaged road network is composed of road network nodes and undamaged road sections; the starting point and end point corresponding to the traffic demand are road network nodes; The section importance calculation module is used to: for each damaged section in the damaged section set, calculate the section importance of the damaged section based on the road network before damage; the section importance includes the section importance based on node degree, the section importance based on node betweenness and the section importance based on toughness ring; the section importance based on node degree is determined by the out-degree of the starting point and the in-degree of the end point in the damaged section; the section importance based on node betweenness is determined by the betweenness of the starting point and the betweenness of the end point in the damaged section; the section importance based on toughness ring represents the mutual accessibility between the starting point and the end point in the damaged section and other nodes in the road network before damage; An importance order determination module is used to: for each target road section importance, sort the target road section importances of all the damaged road sections to obtain the importance order corresponding to the target road section importance; the target road section importance is any one of the road section importance based on node degree, the road section importance based on node betweenness, and the road section importance based on toughness ring; A toughness characterization value calculation module is used to: in response to a set of traffic demands, for each importance order, restore the damaged road section based on the importance order, and calculate a toughness characterization value corresponding to the importance order; the toughness characterization value represents a change in the road network when the damaged road section is restored; The critical damaged road section determination module is used to: determine the best damaged road section restoration order according to all the toughness characterization values ​​corresponding to the importance order, and determine the critical damaged road section set according to all the damaged road sections corresponding to the best damaged road section restoration order.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the critical damaged road section identification method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the critical damaged road section identification method described in any one of claims 1 to 7 is implemented.

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