A key damaged road section identification method, device, equipment and medium

Abstract

The application discloses a key damaged road section identification method and device, equipment and medium, relates to the field of complexity science, and the method comprises the following steps: constructing a damaged road network recovery scene according to to-be-processed information of a research area, calculating the road section importance of the damaged road section through three road section importance aspects of road section importance based on node degree, road section importance based on node betweenness and road section importance based on resilience ring, obtaining the corresponding damaged road section recovery sequence based on the three road section importance aspects respectively, then recovering the damaged road section based on each importance sequence, calculating the resilience representation value corresponding to each importance sequence, determining the best damaged road section recovery sequence according to the resilience representation values corresponding to all the importance sequences, and further determining a key damaged road section set, so that the problem that the existing method is difficult to be applied to a large-scale road network and ignores the improvement of overall resilience is solved, and the application has strong systematicness and high 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] Road transportation networks are essential infrastructure for the normal operation of modern society. Their safety and reliability are directly linked to social stability and economic development. However, road networks often suffer severe damage during emergencies such as natural disasters and accidents. How to quickly and effectively restore damaged sections of road to ensure the resilience and capacity of the transportation network is a critical scientific issue.

[0003] Current road segment restoration strategies that consider road network resilience mainly focus on quickly repairing damaged road segments 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 restoration 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 restoration strategies are required after disasters, which may cause the road segment restoration model for small-scale road networks to fail. For large-scale road networks, existing road segment restoration strategies mainly focus on how to identify and prioritize the repair of key road segments to ensure the connectivity and traffic capacity of the overall transportation network. However, the road segment restoration 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 critical 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 critical damaged road sections, comprising:

[0007] Obtaining information to be processed in the study area; the information to be processed includes geographic latitude and longitude 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 set of damaged road sections, a road network before damage, a road network after damage, and a set of traffic demands; the road network after damage is composed of road network nodes and undamaged road sections; the starting and ending points corresponding to the traffic demands 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 the 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 reachability between the starting point and the end point in the damaged road section and other nodes in the road network before the damage;

[0010] For each target section importance, sort the target section importances of all 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;

[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 resilience representation value corresponding to the importance order is calculated; the resilience representation value represents the change in the road network when the damaged road section is restored;

[0012] An optimal damaged road section restoration sequence is determined according to all the toughness characterization values ​​corresponding to the importance orders, and a critical 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 device for identifying a critical damaged road section, 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 latitude and longitude information and point of interest data;

[0015] A damaged road network restoration scenario construction module is configured to: construct a damaged road network restoration scenario based on the to-be-processed information of the study area; the damaged road network restoration scenario includes a set of damaged road sections, a road network before damage, a road network after damage, and a set of traffic demands; the damaged road network after damage is composed of road network nodes and undamaged road sections; and the starting and ending points corresponding to the traffic demands are road network nodes;

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

[0017] An importance order determination module is configured to: sort the importance of each target road section according to the target road section importances of all the damaged road sections to obtain an 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 configured 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 optimal 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 optimal damaged road section restoration order.

[0020] In a third aspect, the present application provides 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 above-mentioned method for identifying critical 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, apparatus, 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: 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. Then, the damaged road section is restored based on each of the above importance orders, and the resilience characterization value corresponding to each importance order is calculated. The optimal damaged section restoration order is determined based on 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 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 following briefly introduces the drawings required for use in the embodiments. 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 creative work.

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

[0028] Figure 4 A schematic diagram of the functional modules of a device for identifying a critical damaged road section 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 this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0031] In order to make the above-mentioned purposes, 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 information to be processed in the study area to the server 104. After the server 104 receives the information to be processed in the study area, for the information to be processed in the study area, the server 104 constructs a damaged road network recovery scenario based on the information to be processed in the study area, and calculates the section importance of the damaged section 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 respectively, and then the damaged section is restored based on each of the above importance orders, and the resilience characterization value corresponding to each importance order is calculated. The optimal damaged section recovery order is determined according to the resilience characterization values ​​corresponding to all importance orders, and then the key damaged section set is determined. The server 104 can feed back the obtained set of key damaged road sections for the study area to the terminal 102. Furthermore, in some embodiments, the key damaged road section identification method can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly identify key damaged road sections based on the pending information of the study area, or the server 104 can obtain the pending information of the study area from a data storage system and identify key damaged road sections based on the pending information of the study area.

[0033] Terminal 102 may include, but is not limited to, various desktop computers, laptops, smartphones, tablet computers, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, and smart car devices. Portable wearable devices may include smart watches, smart bracelets, and head-mounted devices. Server 104 may be implemented as a standalone 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 critical damaged road sections is provided. The method is executed by a computer device, specifically a computer device such as a terminal or a server, or a terminal and a server. 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 process, including the following steps 201 to 206.

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

[0036] Step 202: Construct 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 traffic demand set; 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 reachability 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 importances 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 traffic demand set, 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 an optimal damaged section restoration sequence based on all the toughness characterization values ​​corresponding to the importance orders, and determining a critical damaged section set based on all the damaged sections corresponding to the optimal damaged section restoration sequence.

[0041] Implement the above steps 201 to 206, calculate the section importance of the damaged section through the three section importance aspects of 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 section importance aspects, 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 based on 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 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 being systematic, highly flexible and widely applicable. 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 proposed method. Specifically, a snowstorm paralyzed a road network consisting of tens of thousands of road sections, creating hundreds of humanitarian access needs that needed to be met within a short period of time. The goal was to identify the critical damaged sections of this large-scale road network and, after restoration, to meet as many humanitarian access needs 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 within 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 geographic boundaries of the large-scale road network are defined using the geographic latitude and longitude information of the study area. Next, all road segments within the study area are considered as the edge set E, the undamaged segments as the edge set E1, the damaged segments as the edge set E2, and the junctions or intersections between segments in the edge set E as the node set N. Based on complex network theory, the pre-damage road network G = (N, E) and the post-damage road network G1 = (N, E1) within the study area are constructed.

[0049] The method for determining damaged road sections is as follows: This application can determine damaged road sections through two levels: structural or functional. 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: POIs are locations or facilities within a specific geographic area that have a particular significance or value. These POIs can be natural or artificial and are commonly used in Geographic Information Systems (GIS) and navigation systems to help people find important or interesting locations. Examples include large residential areas, large stadiums, train stations, airports, energy facilities, schools, hospitals, and government offices.

[0051] The specific process in step 302 is as follows: for each point of interest within the boundary of the study area, the distance between it and each node in the node set N is calculated, and the longitude and latitude coordinates of the point of interest are replaced with the longitude and latitude of the nearest node to achieve 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 an optional solution of this embodiment, the distance between the point of interest and the road network node can be calculated using methods such as great circle distance. The formula for calculating 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, which is usually 6371.016371.01 (unit: kilometers); (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 demand for humanitarian rescue traffic 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. Among them, dispersed means that all traffic demands are relatively evenly distributed in space; dense means that all traffic demands are relatively densely distributed 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's important to note that the distribution of traffic demand is closely related to critical damaged sections. A dense traffic demand distribution often creates critical nodes within the road network. If these nodes are damaged, repairing them significantly increases traffic demand and improves network resilience, making them more likely to become critical 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 and global levels respectively; combined with the background of road damage, 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 to the same 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 road section are calculated in the road network G = (N, E) before the damage, and the sum of the out-degree of the starting point and the in-degree of the end point of the damaged road section is used as the section importance index based on the node degree of the damaged road section; at the global level, the betweenness of the starting point and the betweenness of the end point of a damaged road section are calculated in the road network G = (N, E) before the damage, and the sum of the betweenness of the starting point and the betweenness of the end point of the damaged road section is used as the section importance index based on the node betweenness of the damaged road 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 shortest paths passing through that node to the total number of shortest paths. The shortest path is the path with the fewest number of segments or the lowest path cost (such as distance or 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 segments. 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 segment) to the target node (end point of the segment) is calculated, and then the number of all shortest paths for all node pairs is summed. The formula for calculating the betweenness of a node is as follows:

[0065]

[0066] Where 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 endpoint j.

[0068] The specific process of step 402 is as follows: for each damaged road section, calculate the resilience ring at the start point and the resilience ring at the end point of the damaged road section in the road network G = (N, E) before damage; take the average of the resilience ring at the start point and the resilience ring at the end point of the damaged road section and normalize them to obtain the road section importance index based on the resilience ring of the damaged road section; the greater the importance of each damaged road section based on the resilience ring, the worse the mutual accessibility between the start 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 start point and end point, indicating that the damaged road section is likely to be a key link for restoring the road network connectivity. The calculation formula of the road section importance based on the resilience 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 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 road network node i to road network node i; G represents the road network before damage.

[0072] The specific process of step 204 is as follows: for each damaged road section in the damaged road section set E2, the road section importance based on node degree, the road section importance based on node betweenness, and the road section importance based on resilience ring are calculated respectively; for each target road section importance, all damaged roads are sorted in descending order of importance. Taking the road section importance based on resilience ring as an example, the importance order corresponding to the road 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] Where, e i is the damaged road section in the damaged road section set E2, and n is the number of damaged road sections.

[0076] Based on the importance index obtained in step 203, the damaged road sections are sorted. The damaged sections are restored from most important to least important, and the changes in the network resilience index are compared. The restoration order that maximizes network resilience is selected. Based on the actual restoration resource constraints, the top M damaged sections are selected as key damaged sections. 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, restoring the damaged road section based on each importance order, and calculating the resilience characterization value corresponding to each importance order of the traffic demand 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 based on the resilience characterization value corresponding to each importance order constitute 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 travel 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 for the resilience value of each traffic demand based on the road network resilience characterization of connectivity is as follows:

[0080]

[0081]

[0082] Among them, R C The resilience value calculated based on the road network resilience characterization of the connectivity level 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 and after restoration, respectively, to connect the starting point O and the end point D of the traffic demand. 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 is a 0 / 1 variable, indicating whether the road section (i, j) is in a damaged state in the road network before and after restoration, respectively. A value of 1 indicates that the road section (i, j) is not damaged, and a 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 for the resilience value of the road network resilience characterization calculated based on the shortest travel time for each traffic 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, representing 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 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, representing the travel time required to pass through the road section (i, j) in the road network before 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 order of restoring the damaged sections is determined based on the toughness characterization values ​​corresponding to all the importance orders, specifically including:

[0087] When calculating the resilience characterization value using the road network resilience characterization based on the degree of connectivity, the importance order corresponding to the resilience 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 importance order with the largest or fastest increase in toughness characterization value is selected as the best order for restoring damaged sections.

[0090] In step 206, a set of key damaged sections is determined based on 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; all the key damaged road sections constitute a key damaged road section set.

[0092] In actual restoration scenarios, limited human and material resources mean that the number of roads that can be restored within a specified restoration time cannot exceed a certain number. Therefore, this application considers actual restoration resource constraints, for example, the number of repaired roads cannot exceed M. From the optimal restoration order determined above, the first M damaged sections are selected as the critical 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 links of key damaged sections for the information to be processed in the study area, a damaged road network restoration scenario can be constructed based on the information to be processed in the study area. The section importance of the damaged section is 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. The corresponding damaged section restoration 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. The resilience representation value corresponding to each importance order is calculated, and the optimal damaged section restoration order is determined based on the resilience representation values ​​corresponding to all importance orders, thereby determining the set of key damaged sections.

[0094] like Figure 3 As shown, this application mainly proposes a set of systematic solutions for how to identify key damaged sections in large-scale road networks. First, by constructing a restoration scenario for a large-scale damaged road network, including modeling the road network before and after damage, matching points of interest within the road network area, and analyzing traffic demand, a preliminary damaged road network model is established; then, based on traffic demand, the road network resilience is defined, 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 key damaged sections is proposed, including section sorting under different importance indicators, optimal restoration order selection, and identification of key sections considering actual restoration resource constraints. The method for identifying key 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 information from all key elements of the road network by constructing a recovery scenario for a large-scale damaged road network, including pre- and post-disaster network modeling, point-of-interest matching, and traffic demand analysis. This comprehensive approach comprehensively reflects pre- and post-disaster changes and recovery needs, contributing to a comprehensive understanding and improvement of the overall resilience of large-scale road networks, thereby providing more precise recovery strategies.

[0097] 2. High Flexibility: This application uses connectivity and minimum travel time as resilience indicators, which can flexibly reflect different types of travel needs. Furthermore, a road segment importance index based on complex network theory and resilience rings is proposed. This allows for flexible adjustment of resilience representation and importance calculation methods based on actual conditions and needs, adapting to the road network recovery needs in different scenarios and providing a more adaptable solution.

[0098] 3. Wide application: The method for identifying critical damaged road sections 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 under different disaster and accident scenarios by sorting road sections under different importance indicators, selecting the optimal 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, embodiments of the present application also provide a device for identifying a critical damaged road section for implementing the aforementioned method for identifying a critical damaged road section. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the device for identifying a critical damaged road section provided below can be found in the aforementioned limitations of the method for identifying a critical damaged road section, and will not be further elaborated here.

[0100] In an exemplary embodiment, Figure 4 As shown, a device for identifying a key damaged road section 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 latitude and longitude information and point of interest data;

[0102] A damaged road network restoration scenario construction module T2 is configured to construct a damaged road network restoration scenario based on the to-be-processed information of the study area; the damaged road network restoration scenario includes a set of damaged road sections, a road network before damage, a road network after damage, and a set of traffic demands; the damaged road network after damage is composed of road network nodes and undamaged road sections; and the starting and ending points corresponding to the traffic demands are road network nodes;

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

[0104] The importance order determination module T4 is configured to: sort the importance of each target road section according to 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;

[0105] A toughness characterization value calculation module T5 is configured 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;

[0106] The critical damaged road section determination module T6 is used to determine the optimal 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 optimal damaged road section restoration order.

[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, abbreviated as I / O) and a communication interface. The processor, memory and 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 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 shown in the figure, or combine certain components, or have a different component arrangement.

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

[0110] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned 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 skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented 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 memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may 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 may 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 databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0114] The technical features of the above embodiments can 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 document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may 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 method for identifying key damaged road sections includes: Obtaining information to be processed in the study area; the information to be processed includes geographic latitude and longitude 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 set of damaged road sections, a road network before damage, a road network after damage, and a set of traffic demands; the road network after damage is composed of road network nodes and undamaged road sections; the starting and ending points corresponding to the traffic demands 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 the 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 reachability between the starting point and the end point in the damaged road section and other nodes in the road network before the damage; For each target section importance, sort the target section importances of all 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; 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 resilience representation value corresponding to the importance order is calculated; the resilience representation value represents the change in the road network when the damaged road section is restored; An optimal damaged road section restoration sequence is determined according to all the toughness characterization values ​​corresponding to the importance orders, and a critical 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, 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 resilience representation 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 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; 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, characterized in that: The calculation formula for the resilience value of each traffic demand based on the road network resilience characterization of connectivity is as follows: Among them, R C The resilience value calculated based on the road network resilience characterization of the connectivity level 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 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 method for identifying critical damaged road sections according to claim 2, characterized in that: The calculation formula for the resilience value of the road network resilience characterization calculated based on the shortest travel time for each traffic 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 segment (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 resilience 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 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 road network node i to road network node i; G represents the road network before damage.

6. The method for identifying critical damaged road sections according to claim 2, characterized in that: The optimal order of restoring damaged sections is determined based on the toughness characterization values ​​corresponding to all the importance orders, specifically including: When calculating the resilience characterization value using the road network resilience characterization based on the degree of connectivity, the importance order corresponding to the resilience 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 based on 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; all the key damaged road sections constitute a key damaged road section set.

8. A device for identifying key damaged road sections, characterized in that: The key damaged road section identification device includes: 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 latitude and longitude information and point of interest data; A damaged road network restoration scenario construction module is configured to: construct a damaged road network restoration scenario based on the to-be-processed information of the study area; the damaged road network restoration scenario includes a set of damaged road sections, a road network before damage, a road network after damage, and a set of traffic demands; the damaged road network after damage is composed of road network nodes and undamaged road sections; and the starting and ending points corresponding to the traffic demands are road network nodes; A link importance calculation module is used to: for each damaged link in the damaged link set, calculate the link importance of the damaged link based on the road network before the damage; the link importance includes link importance based on node degree, link importance based on node betweenness, and link importance based on toughness ring; the link 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 link; the link importance based on node betweenness is determined by the betweenness of the starting point and the betweenness of the end point in the damaged link; the link importance based on toughness ring represents the mutual reachability between the starting point and the end point in the damaged link and other nodes in the road network before the damage; An importance order determination module is configured to: sort the importance of each target road section according to the target road section importances of all the damaged road sections to obtain an 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 configured 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 optimal 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 optimal 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 according to any one of claims 1 to 7 is implemented.

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