Danger avoiding path planning method based on flood disaster dynamic evolution

Abstract

The invention discloses a flood disaster dynamic evolution-based risk avoiding path planning method, belongs to the technical field of flood disaster risk avoiding, and aims to dynamically consider the failure influence of a flood disaster on a road network according to different influences of an urban flood process on road failure. The method comprises the following steps: constructing a dynamic road network model introduced with virtual nodes based on a time interval of numerical simulation calculation of a flood process, determining origin and destination, and updating information of the virtual nodes in real time according to different positions at each moment; according to the method, the position of a research object in each time period in dynamic change serves as a virtual node and is added into an original road network, information of the virtual node is updated according to different positions at each moment, and the original road network is reconstructed according to the virtual node; and then the virtual node is used as a new starting point, and the shortest path of each stage is dynamically calculated.

Description

Technical Field

[0001] The present invention belongs to the technical field of flood disaster avoidance, and in particular relates to a method for planning a risk avoidance path based on the dynamic evolution of flood disasters. Background Art

[0002] Due to the development of modern cities and the increase in population density and asset density, urban flood disasters have exposed a higher vulnerability. The disaster-bearing bodies, disaster-causing mechanisms, disaster patterns, and loss structures of flood disasters have all undergone significant changes compared to before. When excessive rainstorms occur and the defense capacity is insufficient to bear such a huge disaster, it is very likely that disaster losses will surge, and then the characteristics of the disaster will show new characteristics such as chain reaction, mutation, and transmission. In order to effectively respond to this challenge, it is particularly important to formulate and implement scientific, efficient, and operational flood emergency avoidance plans. In the complex system of emergency avoidance of flood disasters, the research and development and application of risk avoidance technology is undoubtedly the key to reducing disaster losses and ensuring public safety.

[0003] The temporal and spatial distribution of urban flooding changes with rainfall. When urban roads are affected by floods and their sections and nodes fail, the service capacity of the road network is reduced accordingly, and vehicles / pedestrians and other disaster-bearing objects exposed on the road will also face the impact and risk of floods. Therefore, according to the different impacts of urban flooding on road failure, it is necessary to dynamically consider the impact of floods on road networks, so as to achieve dynamic perception of flood risks and intelligent risk avoidance path planning tasks.

[0004] Therefore, a risk avoidance path planning method based on the dynamic evolution of flood disasters is needed to solve the problem in the existing technology that the failure impact of urban flood processes on road failures is different, and the failure impact caused by flood disasters on the road network needs to be dynamically considered, so as to realize the dynamic perception of flood risks and intelligent risk avoidance path planning tasks. Summary of the invention

[0005] The purpose of the present invention is to provide a risk avoidance path planning method based on the dynamic evolution of flood disasters to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a risk avoidance path planning method based on the dynamic evolution of flood disasters, comprising:

[0007] Based on the time interval of numerical simulation calculation of flood process, a dynamic road network model with virtual nodes is constructed;

[0008] Determine the starting and ending points, and update the virtual node information in real time according to the different positions at each moment;

[0009] Determine whether the path planning end point has been reached. If the judgment result is yes, end the calculation, output the path, distance, time and other information of the dynamic path planning, complete the dynamic path planning, and organize the relevant results;

[0010] If the judgment result is no, the position of Virtual_N is accurately calculated based on the time and moving speed, and the road section information is determined;

[0011] According to the location of Virtual_N, insert the road section where it is located and reconstruct the road network topology;

[0012] Taking Virtual_N as the starting point, find the shortest path to the end point in this stage;

[0013] Update time t=t+△t. According to the moving distance within △t, update the virtual node position and record the nodes that have been passed, and judge again whether the path planning end point has been reached.

[0014] It should be noted that the construction of a dynamic road network model introducing virtual nodes includes:

[0015] Initialize the model and complete the refined risk assessment of urban road flood disasters, especially quantify the traffic risk of roads;

[0016] According to the changing characteristics of flood disasters, the data interaction time △t between the dynamic programming algorithm and the numerical model is determined. When the flood disaster changes more drastically and the failure process of the road network changes faster, the △t value will be shorter. On the contrary, the △t value can be appropriately increased.

[0017] Set the initial evacuation / evacuation path planning scenario, determine the starting point and end point of the dynamic programming algorithm, and introduce a virtual node Virtual_N to store the position of the object under study in each stage;

[0018] After initialization is completed, dynamic planning of the risk avoidance path begins.

[0019] It is further worth noting that the determination of the starting and ending points and the real-time updating of the virtual node information according to the different positions at each moment include:

[0020] According to scenario planning, first determine its starting and ending points (i.e., the OD pair in path planning), define L as the connected path from the starting point to the destination in the OD pair, and <v 0 ,v 1 ,v 2 ,...,v d >Connected and combined;

[0021] Define δ(v i ,v i+1 ) are two nodes <vi ,v i+1 >The cost function (weight) of the connected line segments, which obviously changes over time and also changes depending on whether the road is invalid;

[0022] Then the total weight between the OD pairs and the path L can be expressed by the following formula:

[0023]

[0024] Where, t 0 ,t 1 ,t n is each sub-period of the time period T; v i is the node passed; n, m are the time step and the number of road sections respectively.

[0025] It should be further explained that the process of finding the shortest path to the end point in this stage with Virtual_N as the starting point includes:

[0026] When solving the dynamic shortest path, it is necessary to solve the shortest path in each sub-cycle as the optimal solution, which can be expressed by the following formula:

[0027]

[0028] In the formula, [] (t) is the road section passed within the time period t; l′ is a non-overlapping subsequence segment within the total road section L.

[0029] It is further necessary to explain that when urban roads are affected by heavy rain, combined with the location of flood disaster risk, the impact on the road network topology structure is mainly divided into two categories: one is section failure and the other is node failure. Section failure refers to the failure scenario in which the current section does not have normal traffic capacity due to excessive risk of one or several roads in the urban road; node failure refers to the failure scenario in which the disaster risk of a certain intersection of the urban road is high, thus affecting the normal traffic of vehicles and pedestrians.

[0030] The failure process of urban road networks caused by floods can be roughly described as follows: in flood disasters caused by rainfall or floodplains, as the rainfall or flood volume increases, the urban road network begins to suffer from the impact of flood risks, and some of its roads gradually fail; with the influence of runoff generation and convergence processes, the failed sections in the region also change in spatial scale; when the impact of floods in the region is most serious, it also indicates that the number of failed sections of roads in the region has reached the maximum value; as the rainfall / flood volume gradually decreases and the region absorbs floods, the flood risk in the region gradually decreases, and the road network also restores its traffic capacity.

[0031] It is understandable that in the dynamic evolution of disasters, as floods spread, existing roads may be submerged or closed, so the escape path needs to be updated in real time. At the end of each time step △t, the position of the virtual node is recalculated to evaluate whether the road section it is located on is passable.

[0032] For the status at each moment, the road network topology is reconstructed to ensure that the planned risk avoidance path is feasible by excluding inaccessible road nodes and sections.

[0033] Compared with the prior art, the method for planning a risk avoidance path based on the dynamic evolution of flood disasters provided by the present invention has at least the following beneficial effects:

[0034] By taking the location of the research object in each time period during dynamic changes as a virtual node and adding it to the original road network, the information of the virtual node is updated according to the different positions at each moment, and the original road network is reconstructed based on the virtual node; then the virtual node is used as a new starting point to dynamically calculate the shortest path in each stage. According to the characteristics of flood disasters in terms of temporal and spatial evolution, a risk avoidance path planning algorithm that considers the dynamic evolution of flood disasters is constructed, thereby ensuring the accuracy, effectiveness and reliability of risk avoidance path planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a flow chart of a method for planning a risk avoidance path based on the dynamic evolution of flood disasters according to the present invention;

[0036] Figure 2 A schematic diagram of a process for constructing a dynamic road network model introducing virtual nodes in the present invention;

[0037] Figure 3 The cycle t of the present invention 1 Schematic diagram of dynamic planning of road network taking flood disaster into consideration at all times;

[0038] Figure 4 The cycle t of the present invention 2 Schematic diagram of dynamic planning of road network taking flood disaster into consideration at all times;

[0039] Figure 5 The cycle t of the present invention 3 Schematic diagram of dynamic planning of road network taking flood disasters into consideration at all times. DETAILED DESCRIPTION

[0040] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0041] Reference Figure 1As shown, the present invention provides a risk avoidance path planning method based on the dynamic evolution of flood disasters, including:

[0042] S100, based on the time interval of numerical simulation calculation of flood process, a dynamic road network model with virtual nodes is constructed;

[0043] In this step, when considering the flood disaster scenario, the urban traffic network is a road network that changes dynamically over time, which can be mathematically defined as the network state within a time period.

[0044] R=(G,T)

[0045] Where R is the network state; T is the time change period; G is the static road network within each time period T. As the time period increases, the static road network will be replaced by a time snapshot G that changes with time. 1 , G 2 , ..., G T .

[0046] S200, determining the starting and ending points, and updating the information of the virtual nodes in real time according to the different positions at each moment;

[0047] In this step, according to the scenario planning, first determine its starting and ending points (i.e., the OD pairs in the path planning, Figure 2 , Figure 3 , Figure 4 In the example, S is the starting point and D is the destination point), L is defined as the connected path from the starting point to the destination in the OD pair, consisting of two adjacent nodes. <v 0 ,v 1 ,v 2 ,...,v d >Connect and combine.

[0048] Define δ(v i ,v i+1 ) are two nodes <v i ,v i+1 >The cost function (weight) of the connected line segments, which obviously changes over time and whose weights will also change depending on whether the road is invalid.

[0049] Then the total weight between the OD pairs and the path L can be expressed by the following formula:

[0050]

[0051] Where, t 0 ,t 1 ,t n is each sub-period of the time period T; v i is the node passed; n, m are the time step and the number of road sections respectively.

[0052] S300, determining whether the planned path has been reached;

[0053] S400, if the judgment result is yes, then the calculation is terminated, the path, distance, time and other information of the dynamic path planning are output, the dynamic path planning is completed, and the relevant results are sorted;

[0054] S500, if the judgment result is no, accurately calculating the position of Virtual_N according to the time and the moving speed, and determining the road section information;

[0055] S600, inserting the road section according to the position of Virtual_N to reconstruct the road network topology;

[0056] S700, taking Virtual_N as the starting point, finding the shortest path to the end point in this stage;

[0057] In this step, when solving the dynamic shortest path, it is necessary to solve the shortest path in each sub-cycle as the optimal solution, which can be expressed by the following formula:

[0058]

[0059] In the formula, [] (t) is the road section passed within the time period t; l′ is a non-overlapping subsequence segment within the total road section L.

[0060] S800, update time t=t+Δt, update the virtual node position and record the nodes that have been passed according to the moving distance within time Δt, and determine again whether the path planning end point has been reached.

[0061] Reference Figure 2 As shown, in step S100, constructing a dynamic road network model introducing virtual nodes specifically includes the following steps:

[0062] S110, model initialization, completing the refined risk assessment of urban road flood disasters, especially quantitative characterization of road traffic risks;

[0063] In this step, a comprehensive assessment of the capacity of urban roads is required, including their possible failure in disasters, post-disaster recovery capabilities, and a quantitative description of different road conditions and types.

[0064] First, it is necessary to collect the city's infrastructure data and historical disaster data. Infrastructure data includes road networks, road grades, traffic flow, road slopes, drainage system capacity, etc. The main data sources include: Geographic Information System (GIS) data: road location, width, road surface type, traffic flow, road grade, etc.; remote sensing data and meteorological data: historical flood disaster data, weather forecasts (precipitation, wind speed, etc.), real-time satellite remote sensing images; urban drainage system data: including the design capacity of drainage pipes, sewage treatment plants, and reservoirs; historical disaster data includes the use of historical flood disaster records in the city to obtain information such as water levels, flood spread, and road damage under different circumstances;

[0065] Then the road traffic risk is quantified, including:

[0066] Flood depth and road flooding risk assessment, including calculation of flood depth for each road through hydrological models and flood forecast data, assessment of whether the road will be completely submerged or only partially affected when the water level exceeds a certain threshold; stratified risk assessment of water levels at different depths;

[0067] Drainage capacity and drainage status analysis, including evaluating the designed drainage capacity and actual operation status of drainage systems in various regions to determine their efficiency in flood relief; combining urban drainage networks and historical data to simulate water accumulation in various regions under different precipitation intensities, especially the drainage difficulties in low-lying areas;

[0068] The geographical features and structural strength of the road, such as the elevation and slope of the road, affect the distribution and accumulation of water flow. Low-lying areas are prone to water accumulation, affecting traffic. For example, asphalt, concrete and other road materials behave differently under water flow and water pressure. Some materials may be washed away or damaged by floods, affecting the availability of road sections.

[0069] Traffic flow and traffic interruption risk assessment, through historical traffic flow data combined with real-time traffic monitoring data, evaluate the traffic interruption risks of different roads under flood disasters; through the intelligent transportation system, dynamically adjust the road network to evaluate which sections should be reserved for evacuation and which sections can be temporarily closed.

[0070] Based on the above data, various risk factors are comprehensively evaluated to quantitatively characterize the traffic risk of each road.

[0071] S120, according to the changing characteristics of flood disasters, determining the data interaction time △t between the dynamic programming algorithm and the numerical model. When the flood disaster changes more drastically and the failure process of the road network changes faster, the value of △t will be shorter. Otherwise, the value of △t can be appropriately increased.

[0072] S130, setting the initial evacuation / evacuation path planning scenario, determining the starting point and end point of the dynamic programming algorithm, and introducing a virtual node Virtual_N to store the position of the studied object in each stage;

[0073] S140, initialization is completed, and dynamic planning of the risk avoidance path can begin.

[0074] It is understandable that when urban roads are affected by heavy rain, combined with the location of flood disaster risk, the impact on the road network topology structure can be divided into two categories: one is section failure and the other is node failure. Section failure refers to the failure scenario in which the current section does not have normal traffic capacity due to excessive risk of one or several roads in the city; node failure refers to the failure scenario in which the disaster risk of a certain intersection of the urban road is high, thus affecting the normal traffic of vehicles and pedestrians.

[0075] The failure process of urban road networks caused by floods can be roughly described as follows: in flood disasters caused by rainfall or floodplains, as the rainfall or flood volume increases, the urban road network begins to suffer from the impact of flood risks, and some of its roads gradually fail; with the influence of runoff generation and convergence processes, the failed sections in the region also change in spatial scale; when the impact of floods in the region is most serious, it also indicates that the number of failed sections of roads in the region has reached the maximum value; as the rainfall / flood volume gradually decreases and the region absorbs floods, the flood risk in the region gradually decreases, and the road network also restores its traffic capacity.

[0076] refer to Figure 3 , Figure 4 , Figure 5 As shown in the figure, in the dynamic evolution of the disaster, as the flood spreads, the original road may be submerged or closed, so the escape path needs to be updated in real time. At the end of each time step △t, the position of the virtual node is recalculated to evaluate whether the road section it is located on is passable.

[0077] For the status at each moment, the road network topology is reconstructed to ensure that the planned risk avoidance path is feasible by excluding inaccessible road nodes and sections.

[0078] The steps for using the above-mentioned risk avoidance path planning method based on the dynamic evolution of flood disasters are as follows:

[0079] Step 1: Initialize the model and complete the refined risk assessment of urban flooding, especially quantitatively characterize the traffic risk of roads;

[0080] Step 2: According to the changing characteristics of flood disasters, determine the data interaction time △t between the dynamic programming algorithm and the numerical model. When the flood disaster changes more drastically and the failure process of the road network changes faster, the △t value will be shorter. On the contrary, the △t value can be appropriately increased.

[0081] Step 3: Set the initial evacuation / evacuation path planning scenario, determine the starting point and end point of the dynamic programming algorithm, and introduce a virtual node Virtual_N to store the position of the object under study in each stage;

[0082] Step 4: Initialization is completed and dynamic planning of risk avoidance paths begins;

[0083] Step 5: Update the information of the virtual node in real time to determine whether the path planning destination has been reached;

[0084] Step 6: If the result of step 5 is yes, the calculation is terminated, and the path, distance, time and other information of the dynamic path planning are output, the dynamic path planning is completed, and the relevant results are sorted out;

[0085] Step 7: If the result of step 5 is no, the position of Virtual_N is accurately calculated based on the time and moving speed, and the road section information is determined;

[0086] Step 8: According to the location of Virtual_N, insert the road section where it is located and reconstruct the road network topology;

[0087] Step 9: Taking Virtual_N as the starting point, find the shortest path to the end point in this stage;

[0088] Step 10: Update time t=t+△t;

[0089] Step 11: Update the virtual node position and record the nodes that have been traveled according to the moving distance within the △t time, and return to step 5 for another judgment;

[0090] Step 12: Complete dynamic path planning and organize relevant results.

[0091] To sum up, the advantages of the present invention are: by taking the position of the research object in each time period in the dynamic change as a virtual node, adding it to the original road network, updating the information of the virtual node according to the different positions at each moment, and reconstructing the original road network according to the virtual node; and then taking the virtual node as the new starting point, the shortest path of each stage is dynamically calculated, and according to the characteristics of flood disasters in the temporal and spatial evolution, a risk avoidance path planning algorithm that considers the dynamic evolution of flood disasters is constructed, thereby ensuring the accuracy, effectiveness and reliability of risk avoidance path planning.

[0092] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A risk avoidance path planning method based on the dynamic evolution of flood disasters, characterized in that: include: Based on the time interval of numerical simulation calculation of flood process, a dynamic road network model with virtual nodes is constructed; Determine the starting and ending points, and update the virtual node information in real time according to the different positions at each moment; Determine whether the path planning end point has been reached. If the judgment result is yes, end the calculation, output the path, distance, time and other information of the dynamic path planning, complete the dynamic path planning, and organize the relevant results; If the judgment result is no, the position of Virtual_N is accurately calculated based on the time and moving speed, and the road section information is determined; According to the location of Virtual_N, insert the road section where it is located and reconstruct the road network topology; Taking Virtual_N as the starting point, find the shortest path to the end point in this stage; Update time t=t+△t. According to the moving distance within △t, update the virtual node position and record the nodes that have been passed, and judge again whether the path planning end point has been reached.

2. The method for planning a risk avoidance path based on the dynamic evolution of flood disasters according to claim 1 is characterized in that: The construction of a dynamic road network model introducing virtual nodes includes: Initialize the model and complete the refined risk assessment of urban road flood disasters, especially quantify the traffic risk of roads; According to the changing characteristics of flood disasters, the data interaction time △t between the dynamic programming algorithm and the numerical model is determined. When the flood disaster changes more drastically and the failure process of the road network changes faster, the △t value will be shorter. On the contrary, the △t value can be appropriately increased. Set the initial evacuation / evacuation path planning scenario, determine the starting point and end point of the dynamic programming algorithm, and introduce a virtual node Virtual_N to store the position of the object under study in each stage; After initialization is completed, dynamic planning of the risk avoidance path begins.

3. The method for planning a risk avoidance path based on the dynamic evolution of flood disasters according to claim 2 is characterized in that: Determining the starting and ending points, and updating the information of the virtual nodes in real time according to the different positions at each moment, includes: According to scenario planning, first determine its starting and ending points (i.e., the OD pair in path planning), define L as the connected path from the starting point to the destination in the OD pair, and < v0,v1,v2,...,v d> Connect and combine; Define δ(v i ,v i+1 ) are two nodes < v i ,v i+1> The cost function (weight) of the connected line segments obviously changes over time, and its weight will also change depending on whether the road is invalid; Then the total weight between the OD pairs and the path L can be expressed by the following formula: Where t0, t1, t n is each sub-period of the time period T; v i is the node passed; n, m are the time step and the number of road sections respectively.

4. The method for planning a risk avoidance path based on the dynamic evolution of flood disasters according to claim 3 is characterized in that: The process of taking Virtual_N as the starting point and finding the shortest path to the end point in this stage includes: When solving the dynamic shortest path, it is necessary to solve the shortest path in each sub-cycle as the optimal solution, which can be expressed by the following formula: In the formula, [] (t) is the road section passed within the time period t; l′ is a non-overlapping subsequence segment within the total road section L.

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