Road traffic operation state assessment zoning method and system based on disaster conditions

Abstract

The invention discloses a road traffic operation state assessment zoning method and system based on disaster conditions, and the method comprises the steps: fusing road geological disaster data and meteorological disaster data for disaster risk assessment and zoning, and employing a disaster-pregnant geological and meteorological index system analysis and information amount model solving method. Traffic operation state risk assessment and zoning under the condition of highway disasters are carried out, the result is basically reliable, and the method is suitable for highway traffic operation state risk zoning work under the condition of the disasters.

Description

Technical Field

[0001] The present invention relates to the technical field of highway traffic, and in particular to a method and system for evaluating and zoning highway traffic operation status based on disaster conditions. Background Art

[0002] With the rapid development of my country's economy, the demand for transportation is increasing, and highway construction is advancing to mountainous areas and the west. The traffic volume of mountain trunk roads is gradually increasing, and the trunk road network is becoming denser. Although highway service facilities are constantly improving, transportation practitioners have summarized a series of experiences and scientific research results in practice. Due to the harsh natural environment and poor linear conditions of mountain roads, especially mountain roads in the western plateau, the traffic operation status is extremely susceptible to the great impact of geological disasters and meteorological disasters. Geological, meteorological and other natural disasters have a significant impact on the smoothness and safety of traffic operation. In particular, in recent years, extreme climate events have occurred frequently under the influence of the global climate change trend, which has aggravated the impact of geological disasters and climate disasters in extreme environments on the safe operation of highway traffic.

[0003] Based on the first national comprehensive natural disaster risk census, supplementary data on highway facilities and natural disaster risk point information were reported through the natural disaster risk highway disaster-prone body census collection system; natural disaster risk point risk assessments were conducted, and high-level risk point data verification was carried out. The basic number of natural disaster risk hazards in highway disaster-prone bodies was basically determined, and preliminary exploration of highway natural disaster risk zoning was conducted.

[0004] However, the highway natural disaster risk zoning is only a single zoning of natural disasters, without considering the factors of highway traffic safety operation status under disaster conditions. The analysis of road traffic operation risk often focuses on the analysis of factors such as road traffic safety accidents, vehicle accidents, highway alignment, and simple meteorology, and has not studied the risk assessment method of highway traffic operation status under disaster coupling. At present, the highway traffic operation status assessment and zoning method under disaster conditions has a single indicator and the results are poorly applicable. Summary of the invention

[0005] The present application provides a method and system for evaluating and zoning highway traffic operation status based on disaster conditions, so as to solve the problems that the traditional measurement method has simple considerations, large deviations in measurement results, and cannot meet the requirements of actual railway station design work.

[0006] According to the first aspect, an embodiment provides a method for evaluating and zoning highway traffic operation status based on disaster conditions, the method comprising:

[0007] Obtain data on natural disaster risk points along the highway, collect data on geological factors, topographic factors and meteorological factors that may lead to disasters on the highway, and collect data on highway traffic operation status under disaster conditions;

[0008] Each highway area is divided into evaluation units according to the main disaster-prone factors in the area, and different evaluation factor combinations are selected for each divided evaluation unit according to the characteristics of the evaluation unit;

[0009] Based on the combination of evaluation factors of each evaluation unit, the total information value of geological disasters under the corresponding combination of evaluation factors is solved by using the information model method to evaluate the possibility of geological disasters and obtain the disaster probability information of different evaluation factors.

[0010] Based on the acquired data of natural disaster risk points along the highway, the density information of highway disaster points is obtained, and the disaster probability information of different evaluation factors and the density information of highway disaster points are weighted superimposed to obtain the geological disaster susceptibility evaluation results of each evaluation unit;

[0011] The geological disaster susceptibility assessment results are weighted and superimposed with the probability information of the main disaster-inducing factors in the region and the geological disaster point information to obtain the geological disaster risk assessment results;

[0012] Based on the collected data on highway traffic operation status under disaster conditions, the road traffic impact index is obtained, and the disaster risk level matrix is ​​established by combining the geological disaster hazard assessment results with the road traffic impact index to obtain the disaster risk assessment results and form a highway traffic operation status risk level zoning map under disaster conditions.

[0013] Furthermore, we obtain data on natural disaster risk points along the highway, collect data on geological factors, topographic factors and meteorological factors that may cause disasters on the highway, and collect data on the operation status of highway traffic under disaster conditions, including:

[0014] Based on the comprehensive natural disaster risk survey results and the natural disaster risk highway disaster-prone body survey and collection system results, collect natural disaster risk point information, conduct natural disaster risk point risk assessment, verify high-level risk point data, and obtain the natural disaster risk hidden dangers of highway disaster-prone bodies;

[0015] Collect data on geological factors, topographic and geomorphic factors, and meteorological factors that may lead to highway disasters, including data on topography, geomorphology, engineering rock groups, geological structures, surface water systems, earthquake intensity, and precipitation; collect data on traffic operation status under disaster conditions, including data on the location, frequency, and duration of road blockages.

[0016] Furthermore, each highway area is divided into evaluation units according to the main disaster-prone factors in the area, and different evaluation factor combinations are selected for each divided evaluation unit according to the characteristics of the evaluation unit, including:

[0017] Analyze each highway area to determine the main disaster-prone factors in the area, and select the main disaster-prone factors as the division theme of the evaluation unit in each area;

[0018] Susceptibility evaluation factors include geological factors: engineering rock formations, hydrogeology, structural characteristics, topographic factors: elevation, slope, aspect, curvature, slope drop, landform, surface water system, as well as vegetation coverage factor, rainfall factor, and earthquake intensity factor;

[0019] During the evaluation, different evaluation factors are selected and combined based on the characteristics of the evaluation unit and the judgment of experts.

[0020] Furthermore, each highway area is divided into evaluation units according to the main disaster-prone factors in the area, and different evaluation factor combinations are selected for each divided evaluation unit according to the characteristics of the evaluation unit, including:

[0021] Based on the multi-source and multi-period data of optical remote sensing and DEM covering the highway disaster risk assessment area, comprehensive interpretation of various typical geological disaster evaluation factors is carried out, and different algorithms are used to extract information on various typical geological disaster evaluation factors;

[0022] A sample library is established based on the interpreted information of typical geological disaster evaluation factors. The constructed deep learning model is trained multiple times through classification supervision based on the sample library, and various types of atypical geological disaster evaluation factor information are obtained through the trained deep learning model.

[0023] Furthermore, the information volume model method is used to solve the total information volume value of geological disasters under the corresponding evaluation factor combination to evaluate the possibility of geological disasters, including:

[0024] The formula of disaster information is expressed as:

[0025]

[0026] Among them, A is a certain disaster-pregnant condition factor; J is the state classification or interval under the disaster-pregnant condition A; I Aj→B is the amount of information on the occurrence of geological disaster B under the corresponding factor A and j state or interval; N j is the number of points of geological disaster distribution under the corresponding factor A, j state or interval; N is the total number of known geological disaster risk points in the evaluation area; S j is the number of grid cells of the state or interval distribution of factor A, j; S is the total number of grid cells in the evaluation area;

[0027] When I Aj→B >0, it reflects that the amount of information on the occurrence tendency of geological disasters under the corresponding factor A, j state or interval is large, and the possibility of geological disasters is high, or it is conducive to the occurrence of geological disasters; when I Aj→B <0, it indicates that the factors A and j are not conducive to the occurrence of geological disasters under the state or interval conditions; Aj→B=0, it indicates that the state or interval of factors A and j does not provide any information about whether geological disasters occur or not, that is, the state or interval of factors A and j can be eliminated and excluded as geological disaster prediction factors;

[0028] Each evaluation unit is affected by many factors, and each factor has several states. The total information of geological disasters under the combination of various state factors is used to express the possibility of geological disasters, which is used as the geological disaster susceptibility index. The specific formula is as follows:

[0029]

[0030] Among them, I is the total amount of information corresponding to the occurrence of geological disasters in a specific unit, indicating the possibility of geological disasters, which serves as the geological disaster susceptibility index; N i is the geological disaster area or number of geological disaster points corresponding to specific factors, the i-th state or interval conditions; S i is the number of grid cells corresponding to a specific factor, the i-th state or interval; N is the total area of ​​geological hazards or the total number of geological hazard points in the assessment area; S is the total number of grid cells in the assessment area.

[0031] Furthermore, based on the acquired data of natural disaster risk points along the highway, the density information of highway disaster points is obtained, and the disaster probability information of different evaluation factors and the density information of highway disaster points are weighted superimposed to obtain the geological disaster susceptibility evaluation results of each evaluation unit, including:

[0032] Based on the acquired data of natural disaster risk points along the highway, the density analysis module in the SpatialAnalyst tool under the ARCGIS platform is used. The density analysis module provides three calculation methods: kernel density analysis, point density analysis, and line density analysis. The calculation method of kernel density analysis is selected to obtain the kernel density map of highway disaster points.

[0033] Utilize the ARCGIS spatial analysis overlay function, specifically call the overlay analysis module in the Spatial Analyst tool under the ARCGIS platform, select the weighted overlay calculation method, input the disaster probability layer and the kernel density layer, obtain the geological disaster susceptibility evaluation index of each evaluation unit through calculation, and form the susceptibility evaluation result.

[0034] Furthermore, the geological disaster susceptibility assessment results are weighted and superimposed with the probability information of the main disaster-inducing factors and the geological disaster point information in the region to obtain the geological disaster risk assessment results, which specifically include:

[0035] The weighted overlay calculation method provided by the ARCGIS software platform is selected to input the geological disaster susceptibility layer, the probability layer of the main disaster-inducing factors, and the geological disaster point information. The geological disaster point information includes the coordinates of the disaster point, the degree of hazard, the disaster level, the disaster type, the shadow length, and the frequency of occurrence information, and the geological disaster risk assessment results are obtained, thereby evaluating the possibility of the spatial location, scale or intensity, and frequency of occurrence of a certain scale of disasters in a certain area within a certain period of time.

[0036] Furthermore, based on the collected highway traffic operation status data under disaster conditions, the road traffic impact index is obtained, and the geological disaster risk assessment results and the road traffic impact index are used to establish a disaster risk level matrix to obtain the disaster risk assessment results, including:

[0037] The highway traffic operation status data collected under disaster conditions include the location, frequency, duration and length of highway traffic blockages. The data are normalized by grading and assigning values ​​to the highway traffic operation status indicator data to obtain the road traffic impact index, thereby establishing a disaster hazard and road traffic impact level matrix, and defining and coloring the disaster risk level into four levels: extremely high, high, medium and low risk.

[0038] Furthermore, obtaining disaster risk assessment results specifically includes:

[0039] Based on the principles of similarity and proximity, the disaster risk assessment results are generalized and converted from raster to vector. The specific method is to input the disaster risk assessment results in the ENVI software platform, call the Classification tool, select the PostClassification module, perform Sieve classes calculation to remove scattered patches, and then input parameters for Clumpclasses calculation to complete the patch generalization and cluster analysis, thereby realizing the generalized raster processing of disaster risk assessment information; then use the Raster to Surface submodule under the Raster to Surface module of the conversion tool in the ARCGIS platform to realize the vectorization of raster data.

[0040] According to the second aspect, in one embodiment, a highway traffic operation status assessment zoning system based on disaster conditions is provided, the system comprising:

[0041] The data collection module is used to obtain data on natural disaster risk points along the highway, collect data on geological factors, topographic factors and meteorological factors that may cause disasters on the highway, and collect data on the operation status of highway traffic under disaster conditions;

[0042] The evaluation factor determination module is used to divide each area of ​​the highway into evaluation units according to the main disaster-prone factors in the area, and select different evaluation factor combinations for each divided evaluation unit according to the characteristics of the evaluation unit;

[0043] The information volume calculation module is used to calculate the total information volume value of geological disasters under the corresponding evaluation factor combination based on the evaluation factor combination of each evaluation unit by using the information volume model method to evaluate the possibility of geological disasters and obtain the disaster probability information of different evaluation factors;

[0044] The susceptibility assessment module is used to obtain the density information of highway disaster points based on the acquired natural disaster risk point data along the highway, and obtain the geological disaster susceptibility assessment results of each assessment unit by weighted superposition of the disaster probability information of different assessment factors and the highway disaster point density information;

[0045] The hazard assessment module is used to perform weighted superposition of the geological disaster susceptibility assessment results with the probability information of the main disaster-inducing factors in the region and the geological disaster point information to obtain the geological disaster hazard assessment results;

[0046] The risk assessment module is used to obtain the road traffic impact index based on the collected highway traffic operation status data under disaster conditions, establish a disaster risk level matrix with the geological disaster hazard assessment results and the road traffic impact index, obtain the disaster risk assessment results, and form a highway traffic operation status risk level zoning map under disaster conditions.

[0047] The present application provides a method and system for evaluating and zoning highway traffic operation status based on disaster conditions, which integrates highway geological disaster data with meteorological disaster data for disaster risk assessment and zoning, and adopts disaster-prone geological and meteorological indicator system analysis and information volume model solution method to conduct risk assessment and zoning of traffic operation status under highway disaster conditions. The results are basically reliable and suitable for risk zoning of highway traffic operation status under disaster conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A flowchart of a method for evaluating and zoning highway traffic operation status based on disaster conditions provided by one embodiment of the present invention;

[0049] Figure 2 A specific implementation flow chart of a method for evaluating and zoning highway traffic operation status based on disaster conditions provided by one embodiment of the present invention;

[0050] Figure 3 A kernel density map of disaster points along a highway in a method for evaluating and zoning highway traffic operation status based on disaster conditions provided by an embodiment of the present invention;

[0051] Figure 4 A disaster probability layer in a method for evaluating and zoning highway traffic operation status based on disaster conditions provided by an embodiment of the present invention;

[0052] Figure 5 A risk evaluation level matrix diagram in a highway traffic operation status assessment zoning method based on disaster conditions provided by an embodiment of the present invention;

[0053] Figure 6 A comprehensive risk level zoning map of highway traffic operation status under disaster conditions in a highway traffic operation status assessment zoning method based on disaster conditions provided by one embodiment of the present invention;

[0054] Figure 7 A schematic diagram of the logical structure of a highway traffic operation status assessment zoning system based on disaster conditions provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0055] The present invention is further described in detail below by specific embodiments in conjunction with the accompanying drawings. Wherein similar elements in different embodiments adopt associated similar element numbers. In the following embodiments, many detailed descriptions are for making the present application better understood. However, those skilled in the art can easily recognize that some features can be omitted in different situations, or can be replaced by other elements, materials, methods. In some cases, some operations related to the present application are not shown or described in the specification, this is to avoid the core part of the present application being overwhelmed by too much description, and for those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations according to the description in the specification and the general technical knowledge in the art.

[0056] In addition, the features, operations or characteristics described in the specification can be combined in any appropriate manner to form various implementations. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for the purpose of clearly describing a certain embodiment and are not meant to be a required sequence, unless otherwise specified that a certain sequence must be followed.

[0057] The first embodiment of the present invention provides a method for evaluating and zoning highway traffic operation status based on disaster conditions. Figure 1 and Figure 2 Provide detailed explanation.

[0058] like Figure 1 As shown, in step S100, data on natural disaster risk points along the highway are obtained, data on geological factors, topographic factors and meteorological factors that may cause disasters on the highway are collected, and data on highway traffic operation status under disaster conditions are collected.

[0059] Specifically, the results of the first national comprehensive natural disaster risk survey and the natural disaster risk highway disaster-prone body survey and collection system are integrated to collect natural disaster risk point information; and a natural disaster risk point risk assessment is conducted, and high-level risk point data is verified to obtain the natural disaster risk hazard base of highway disaster-prone bodies, which is used to form the geological disaster development kernel density factor information in the highway disaster susceptibility assessment.

[0060] Collect data on geological and meteorological factors that may lead to highway disasters, including topography, landforms, engineering rock formations, geological structures, surface water systems (for conducting highway disaster susceptibility assessments), earthquake intensity, precipitation (for conducting highway disaster susceptibility assessments), and collect data on traffic operation status under disaster conditions, including data on the location, frequency, and duration of road blockages (for conducting highway disaster risk assessments and zoning).

[0061] like Figure 1 As shown, in step S200, each area of ​​the highway is divided into evaluation units according to the main disaster-prone factors in the area, and different evaluation factor combinations are selected for each divided evaluation unit according to the characteristics of the evaluation unit.

[0062] Specifically, due to the large differences in climate, geography, geology and other conditions in the areas where the highway passes, it is impossible to conduct a unified zoning evaluation. In the specific evaluation, it is necessary to consider the areas involved in the highway as a whole, and divide different evaluation units according to the main disaster-pregnant or inducing factors of disasters in each area. The main disaster-pregnant or inducing factors can be determined artificially. On the basis of the classification of the main disaster types in each block, the main disaster-pregnant factors, such as geomorphic units, earthquake zoning, slope, etc., are selected as the evaluation unit division theme. For example, for the Sichuan-Tibet Highway section, the main controlling factor affecting the formation of disasters is the geomorphic unit. Therefore, it can be spatially cut according to the first-level geomorphic units such as high mountain canyons, lake basin valleys, and plains to form independent evaluation units, complete the evaluation unit division, and then select evaluation factors for each evaluation unit, substitute them into the evaluation model, and set the evaluation parameters.

[0063] The susceptibility assessment factors mainly include geological factors such as engineering rock groups, hydrogeology, and structural characteristics; topographic and geomorphological factors such as elevation, slope, aspect, curvature, slope drop, landform, and surface water system; and vegetation coverage factors, rainfall factors, and earthquake intensity factors. During the specific evaluation, different evaluation factors are selected and combined according to the characteristics of the evaluation unit. For example, in the high mountain canyon area, landform, slope, engineering rock group, vegetation coverage, etc. are selected to form an evaluation factor combination; in the lake basin valley area, landform, water system, vegetation coverage, etc. are selected to form an evaluation factor combination.

[0064] The above steps specifically include: based on the multi-source and multi-period data of optical remote sensing and DEM covering the highway disaster risk assessment area, comprehensive interpretation of various typical geological disaster evaluation factors is carried out, and various typical geological disaster evaluation factor information is extracted using different algorithms; a sample library is established based on the interpreted typical geological disaster evaluation factor information, and the constructed deep learning model is iteratively trained multiple times using classification supervision based on the sample library, and various atypical geological disaster evaluation factor information is obtained through the trained deep learning model.

[0065] Specifically, first, by purchasing multi-source and multi-period data such as optical remote sensing and DEM covering the highway disaster risk assessment area, various typical geological disaster evaluation factor information is extracted through different algorithms. Optical remote sensing data is used to carry out comprehensive interpretation of evaluation factors such as landforms, geological engineering rock groups, fault structures, and surface water systems, and the vegetation grade factor information is calculated using the vegetation index (NDVI) model; the slope shape is calculated using the SLOPE model using DEM data to extract terrain slope factor information, and the terrain aspect factor information is extracted using the Aspect model. Comprehensive interpretation of geological disasters is carried out through multi-period sub-meter optical remote sensing data to obtain information such as disaster type, spatial location, development scale, and disaster deformation development trend (long-term series optical remote sensing image comparison). Combined with the highway natural disaster risk point data obtained in step S100, the degree of disaster hazard and road disaster characteristics are analyzed, and finally the background data for highway disaster hazard assessment is obtained.

[0066] The calculation formulas for various evaluation factor information are as follows:

[0067] ① Vegetation index (NDVI) model:

[0068] NDVI = (NIR-R) / (NIR+R)

[0069] Where: NIR represents the reflectance value of the near-infrared band, and R represents the red light band.

[0070] ②Slope model

[0071]

[0072] Where Slope is the slope; Slopewe is the slope in the X direction; Slopesn is the slope in the Y direction; and the ground slope (slope) is the angle between the tangent plane passing through the point and the horizontal ground.

[0073] ③Aspect model

[0074] The equation of the tangent plane is:

[0075] Z=Ax+By+C=fx(x0,y0)x+fy(x0,y0)y+C

[0076] Slope direction:

[0077] β=arctan(A / B)

[0078] Where x and y are plane coordinates; z is the vertical coordinate; β is the slope azimuth.

[0079] In addition, in this embodiment, according to the typical geological hazard evaluation factor information interpreted above, a deep learning method is used to obtain atypical geological hazard factor information to supplement and improve the geological hazard factor information required for subsequent geological hazard susceptibility evaluation. Specifically, this embodiment collects various types of typical geological hazard evaluation factor information corresponding to the geological hazard development area, establishes a sample library, forms a deep learning model, and performs multiple iterative training under the ENVI software platform in a classified and supervised manner to obtain a multi-factor evaluation factor automatic identification optimization model (a training sample library identification model formed after multiple classified supervised iterative training of geological hazard samples, which is used to obtain atypical geological hazard factor information for disaster susceptibility evaluation).

[0080] In this embodiment, the evaluation factors are selected based on the characteristics of the evaluation unit area and on the basis of expert judgment, and the alternative model structure of multiple evaluation factor combinations is formed through weight superposition calculation. Based on the obtained typical and atypical geological hazard factor information values, the alternative models of multiple evaluation factor combinations are also used for weight calculation and normalization to obtain new information values ​​as the final data of each evaluation factor, so as to participate in the calculation of the following information value formula.

[0081] like Figure 1 As shown, in step S300, based on the evaluation factor combination of each evaluation unit, the information quantity model method is used to solve the total information quantity value of the occurrence of geological disasters under the corresponding evaluation factor combination to evaluate the possibility of geological disasters, and obtain the disaster probability information of different evaluation factors.

[0082] Specifically, the embodiments of the present invention determine the main controlling factors for disasters based on the investigation and analysis of disaster-prone geological conditions, construct an index system and use the information model method to solve the corresponding information value; based on the hierarchical evaluation, the analysis results are comprehensively superimposed to divide the disaster susceptibility level; based on the susceptibility, the information of the main factors of the region such as rainfall, earthquakes, etc. is superimposed to calculate the disaster risk evaluation and zoning results.

[0083] The information value of geological disasters under specific conditions of certain factors is calculated by using the formula for geological disaster information under specific conditions. The specific formula is as follows:

[0084]

[0085] Wherein, A is a certain disaster-prone condition factor (factor information such as engineering rock formation, hydrogeology, structural characteristics, elevation, slope, slope aspect, curvature, slope drop, landform, surface water system and vegetation coverage obtained in step S200); J is the state classification or interval under the disaster-prone condition A; I Aj→B is the amount of information on the occurrence of geological disaster B under the corresponding factor A and j state or interval; N j is the number of points of geological disaster distribution under the corresponding factor A, j state or interval; N is the total number of known geological disaster risk points in the evaluation area; S j is the number of grid cells of the state or interval distribution of factor A, j (wherein the information of various evaluation factors is unified into a grid file, and different scales are set according to the accuracy requirements of different evaluation work, and then the grid cell size is unified in the grid processing / resampling tool under the data management module of ARCGIS software. For example, the 1:50000 accuracy requires the grid cell resampling pixel size to be 25*25m, and then the system symbol is called in the layer properties, and the grid cell count is queried in the classification statistics table, and finally the grid cells and their number can be obtained); S is the total number of grid cells in the evaluation area;

[0086] When I Aj→B >0, it reflects that the amount of information on the occurrence tendency of geological disasters under the corresponding factor A, j state or interval is large, and the possibility of geological disasters is high, or it is conducive to the occurrence of geological disasters; when I Aj→B <0, it indicates that the factors A and j are not conducive to the occurrence of geological disasters under the state or interval conditions; Aj→B =0, it indicates that the state or interval of factors A and j does not provide any information about whether geological disasters occur or not, that is, the state or interval of factors A and j can be eliminated and excluded as geological disaster prediction factors;

[0087] Each evaluation unit is affected by many factors, and each factor has several states. The total information of geological disasters under the combination of various state factors is used to express the possibility of geological disasters, which is used as the geological disaster susceptibility index. The specific formula is as follows:

[0088]

[0089] Among them, I is the total amount of information corresponding to the occurrence of geological disasters in a specific unit, indicating the possibility of geological disasters, which serves as the geological disaster susceptibility index; N i is the geological disaster area or number of geological disaster points corresponding to specific factors, the i-th state or interval conditions; S i is the number of grid cells corresponding to a specific factor, the i-th state or interval; N is the total area of ​​geological hazards or the total number of geological hazard points in the assessment area; S is the total number of grid cells in the assessment area.

[0090] like Figure 1 As shown, in step S400, based on the acquired natural disaster risk point data along the highway, the highway disaster point density information is obtained, and the disaster probability information of different evaluation factors and the highway disaster point density information are weighted superimposed to obtain the geological disaster susceptibility evaluation results of each evaluation unit.

[0091] Specifically, taking the highway line as the center, a buffer zone is set within 500m on both sides of the highway. Based on the background data of disaster points along the highway obtained in step S100, the density analysis module in the Spatial Analyst tool under the ARCGIS platform is used. The module provides three calculation methods: kernel density analysis, point density analysis, and line density analysis. This technology selects the calculation method of kernel density analysis to obtain the kernel density map of highway disaster points (such as Figure 3 shown).

[0092] The highway disaster point kernel density information is combined with the evaluation factors in the above-mentioned different evaluation units for weighted superposition calculation to obtain highway disaster susceptibility evaluation information. Specifically, the information value calculation formula for geological disasters under specific factors is used to evaluate the possibility of geological disasters controlled by disaster-prone geological conditions such as topographic and geomorphic characteristics, engineering geological rock groups, slope structure types, vegetation coverage, surface water and groundwater characteristics in a certain area. Using the aforementioned information value calculation model and the mathematical analysis module in the SpatialAnalyst tool under the ARCGIS platform, the above-mentioned evaluation factors are calculated to obtain disaster probability layers under different disaster-prone conditions (such as Figure 4 The probability of disasters under different disaster-prone conditions refers to the information value calculated according to the information value calculation formula under the corresponding disaster-prone conditions. Using the ARCGIS spatial analysis overlay function, specifically calling the overlay analysis module in the SpatialAnalyst tool under the ARCGIS platform, selecting the weighted overlay calculation method, inputting the disaster probability layer and the kernel density layer, and obtaining the geological disaster susceptibility evaluation index of each evaluation unit through computer calculation to form the susceptibility evaluation result.

[0093] like Figure 1 As shown, in step S500, the geological disaster susceptibility assessment result is weightedly superimposed with the probability information of the main disaster-inducing factors in the region and the geological disaster point information to obtain the geological disaster risk assessment result.

[0094] Specifically, on the basis of geological disaster susceptibility assessment, the probability layer of major disaster-inducing factors in the region is superimposed (the information value calculated according to the information value calculation formula under the conditions of major disaster-inducing factors such as rainfall and earthquake). The specific method is to use the weighted overlay calculation method provided by the ARCGIS software platform, input the susceptibility assessment layer and the probability layer of major disaster-inducing factors such as rainfall and earthquake, and the geological disaster point information (including disaster point coordinates, degree of hazard, disaster level, disaster type, shadow length, occurrence frequency, etc.), and obtain the geological disaster risk assessment results, so as to evaluate the possibility of spatial location, scale (intensity), and frequency of occurrence of a certain scale of disasters in a certain area within a certain period of time.

[0095] like Figure 1 As shown, in step S600, based on the collected highway traffic operation status data under disaster conditions, a road traffic impact index is obtained, a disaster risk level matrix is ​​established by combining the geological disaster hazard assessment results with the road traffic impact index, the disaster risk assessment results are obtained, and a highway traffic operation status risk level zoning map under disaster conditions is formed.

[0096] Specifically, the geological disaster risk assessment results will be used to establish a grade matrix with the road traffic impact index to obtain the disaster risk assessment results. Using the data reflecting the traffic operation status such as the location, frequency, and duration of highway traffic blockage under disaster conditions collected in step S100, the road traffic impact index is obtained by normalizing the blockage frequency, blockage duration, and blockage length through a graded value assignment method, thereby establishing a disaster risk and road traffic impact grade matrix, and defining the disaster risk level and assigning colors in four levels of extremely high, high, medium, and low risks (such as Figure 5 shown).

[0097] Finally, based on the principle of similarity and proximity, the raster is generalized to vector. The specific method is to input the disaster risk assessment results in the ENVI software platform, call the Classification tool, select the Post Classification module, perform Sieve classes calculation to remove scattered spots, and then input parameters for Clump classes calculation to complete the spot generalization and cluster analysis, thereby realizing the generalized raster processing of disaster risk assessment information; then use the raster to surface submodule under the raster conversion module of the conversion tool under the ARCGIS platform to realize the vectorization of raster data. Finally, a risk zoning map of highway traffic operation status under disaster conditions is formed, such as Figure 6 shown.

[0098] Corresponding to the above-disclosed method for evaluating and zoning highway traffic operation status based on disaster conditions, the embodiment of the present invention further discloses a system for evaluating and zoning highway traffic operation status based on disaster conditions, such as Figure 7 As shown, it specifically includes:

[0099] The data collection module is used to obtain data on natural disaster risk points along the highway, collect data on geological factors, topographic factors and meteorological factors that may cause disasters on the highway, and collect data on the operation status of highway traffic under disaster conditions;

[0100] The evaluation factor determination module is used to divide each area of ​​the highway into evaluation units according to the main disaster-prone factors in the area, and select different evaluation factor combinations for each divided evaluation unit according to the characteristics of the evaluation unit;

[0101] The information volume calculation module is used to calculate the total information volume value of geological disasters under the corresponding evaluation factor combination based on the evaluation factor combination of each evaluation unit by using the information volume model method to evaluate the possibility of geological disasters and obtain the disaster probability information of different evaluation factors;

[0102] The susceptibility assessment module is used to obtain the density information of highway disaster points based on the acquired natural disaster risk point data along the highway, and obtain the geological disaster susceptibility assessment results of each assessment unit by weighted superposition of the disaster probability information of different assessment factors and the highway disaster point density information;

[0103] The hazard assessment module is used to perform weighted superposition of the geological disaster susceptibility assessment results with the probability information of the main disaster-inducing factors in the region and the geological disaster point information to obtain the geological disaster hazard assessment results;

[0104] The risk assessment module is used to obtain the road traffic impact index based on the collected highway traffic operation status data under disaster conditions, establish a disaster risk level matrix with the geological disaster hazard assessment results and the road traffic impact index, obtain the disaster risk assessment results, and form a highway traffic operation status risk level zoning map under disaster conditions.

[0105] It should be noted that for the detailed description of a highway traffic operation status assessment zoning system based on disaster conditions provided in an embodiment of the present invention, reference can be made to the relevant description of a highway traffic operation status assessment zoning method based on disaster conditions provided in an embodiment of the present application, which will not be repeated here.

[0106] In addition, an embodiment of the present invention also provides an electronic device, comprising: a processor and a memory; the memory is used to store one or more program instructions; the processor is used to run one or more program instructions to execute the steps of a method for assessing and zoning highway traffic operation status based on disaster conditions as described in any of the above items.

[0107] It should be noted that for the detailed description of an electronic device provided in an embodiment of the present invention, reference can be made to the relevant description of a highway traffic operation status assessment zoning method based on disaster conditions provided in an embodiment of the present application, which will not be repeated here.

[0108] In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of a method for evaluating and zoning highway traffic operation status based on disaster conditions as described in any of the above items are implemented.

[0109] It should be noted that, for a detailed description of a computer-readable storage medium provided in an embodiment of the present invention, reference can be made to the relevant description of a highway traffic operation status assessment zoning method based on disaster conditions provided in an embodiment of the present application, which will not be repeated here.

[0110] Those skilled in the art will appreciate that all or part of the functions of the various methods in the above-mentioned embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, and the storage medium can include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to implement the above-mentioned functions. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, all or part of the above-mentioned functions can be implemented. In addition, when all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can also be stored in a storage medium such as a server, another computer, disk, optical disk, flash disk or mobile hard disk, and can be downloaded or copied and saved in the memory of the local device, or the system of the local device is updated, and when the program in the memory is executed by the processor, all or part of the functions in the above-mentioned embodiments can be implemented.

[0111] The above specific examples are used to illustrate the present invention, which is only used to help understand the present invention and is not intended to limit the present invention. For those skilled in the art, according to the concept of the present invention, some simple deductions, modifications or substitutions can be made.

Claims

1. A method for evaluating and zoning highway traffic operation status based on disaster conditions, characterized in that: The method comprises: Obtain data on natural disaster risk points along the highway, collect data on geological factors, topographic factors and meteorological factors that may lead to disasters on the highway, and collect data on highway traffic operation status under disaster conditions; Each highway area is divided into evaluation units according to the main disaster-prone factors in the area, and different evaluation factor combinations are selected for each divided evaluation unit according to the characteristics of the evaluation unit; Based on the combination of evaluation factors of each evaluation unit, the total information value of geological disasters under the corresponding combination of evaluation factors is solved by using the information model method to evaluate the possibility of geological disasters and obtain the disaster probability information of different evaluation factors. Based on the acquired data of natural disaster risk points along the highway, the density information of highway disaster points is obtained, and the disaster probability information of different evaluation factors and the density information of highway disaster points are weighted superimposed to obtain the geological disaster susceptibility evaluation results of each evaluation unit; The geological disaster susceptibility assessment results are weighted and superimposed with the probability information of the main disaster-inducing factors in the region and the geological disaster point information to obtain the geological disaster risk assessment results; Based on the collected data on highway traffic operation status under disaster conditions, the road traffic impact index is obtained, and the disaster risk level matrix is ​​established by combining the geological disaster hazard assessment results with the road traffic impact index to obtain the disaster risk assessment results and form a highway traffic operation status risk level zoning map under disaster conditions.

2. A method for evaluating and zoning highway traffic operation status based on disaster conditions as claimed in claim 1, characterized in that: Obtain data on natural disaster risk points along the highway, collect data on geological factors, topographic factors and meteorological factors that may cause disasters on the highway, and collect data on highway traffic operation status under disaster conditions, including: Based on the comprehensive natural disaster risk survey results and the natural disaster risk highway disaster-prone body survey and collection system results, collect natural disaster risk point information, conduct natural disaster risk point risk assessment, verify high-level risk point data, and obtain the natural disaster risk hidden dangers of highway disaster-prone bodies; Collect data on geological factors, topographic and geomorphic factors, and meteorological factors that may lead to highway disasters, including data on topography, geomorphology, engineering rock groups, geological structures, surface water systems, earthquake intensity, and precipitation; collect data on traffic operation status under disaster conditions, including data on the location, frequency, and duration of road blockages.

3. A method for evaluating and zoning highway traffic operation status based on disaster conditions as claimed in claim 1, characterized in that: Each highway area is divided into evaluation units according to the main disaster-prone factors in the area, and different evaluation factor combinations are selected for each divided evaluation unit according to the characteristics of the evaluation unit, including: Analyze each highway area to determine the main disaster-prone factors in the area, and select the main disaster-prone factors as the division theme of the evaluation unit in each area; Susceptibility evaluation factors include geological factors: engineering rock formations, hydrogeology, structural characteristics, topographic factors: elevation, slope, aspect, curvature, slope drop, landform, surface water system, as well as vegetation coverage factor, rainfall factor, and earthquake intensity factor; During the evaluation, different evaluation factors are selected and combined based on the characteristics of the evaluation unit and the judgment of experts.

4. A method for evaluating and zoning highway traffic operation status based on disaster conditions as claimed in claim 1, characterized in that: Each highway area is divided into evaluation units according to the main disaster-prone factors in the area, and different evaluation factor combinations are selected for each divided evaluation unit according to the characteristics of the evaluation unit, including: Based on the multi-source and multi-period data of optical remote sensing and DEM covering the highway disaster risk assessment area, comprehensive interpretation of various typical geological disaster evaluation factors is carried out, and different algorithms are used to extract information on various typical geological disaster evaluation factors; A sample library is established based on the interpreted information of typical geological disaster evaluation factors. The constructed deep learning model is trained multiple times through classification supervision based on the sample library, and various types of atypical geological disaster evaluation factor information are obtained through the trained deep learning model.

5. The method for evaluating and zoning highway traffic operation status based on disaster conditions as claimed in claim 1, characterized in that: The information volume model method is used to solve the total information volume value of geological disasters under the corresponding evaluation factor combination to evaluate the possibility of geological disasters, including: The formula of disaster information is expressed as: Among them, A is a certain disaster-pregnant condition factor; J is the state classification or interval under the disaster-pregnant condition A; I Aj→B is the amount of information on the occurrence of geological disaster B under the corresponding factor A and j state or interval; N j is the number of points of geological disaster distribution under the corresponding factor A, j state or interval; N is the total number of known geological disaster risk points in the evaluation area; S j is the number of grid cells of the state or interval distribution of factor A, j; S is the total number of grid cells in the evaluation area; When I Aj→B >0, it reflects that the amount of information on the occurrence tendency of geological disasters under the corresponding factor A, j state or interval is large, and the possibility of geological disasters is high, or it is conducive to the occurrence of geological disasters; when I Aj→B <0, it indicates that the factors A and j are not conducive to the occurrence of geological disasters under the state or interval conditions; Aj→B =0, it indicates that the state or interval of factors A and j does not provide any information about whether geological disasters occur or not, that is, the state or interval of factors A and j can be eliminated and excluded as geological disaster prediction factors; Each evaluation unit is affected by many factors, and each factor has several states. The total information of geological disasters under the combination of various state factors is used to express the possibility of geological disasters, which is used as the geological disaster susceptibility index. The specific formula is as follows: Where I is the total amount of information on the occurrence of geological disasters in a specific unit, indicating the possibility of geological disasters, and serving as a geological disaster susceptibility index; N i is the geological disaster area or number of geological disaster points corresponding to specific factors, the i-th state or interval conditions; S i is the number of grid cells corresponding to a specific factor, the i-th state or interval; N is the total area of ​​geological hazards or the total number of geological hazard points in the assessment area; S is the total number of grid cells in the assessment area.

6. A method for evaluating and zoning highway traffic operation status based on disaster conditions as claimed in claim 1, characterized in that: Based on the acquired data of natural disaster risk points along the highway, the density information of highway disaster points is obtained, and the disaster probability information of different evaluation factors and the density information of highway disaster points are weighted superimposed to obtain the geological disaster susceptibility evaluation results of each evaluation unit, including: Based on the acquired data of natural disaster risk points along the highway, the density analysis module in the Spatial Analyst tool under the ARCGIS platform is used. The density analysis module provides three calculation methods: kernel density analysis, point density analysis, and line density analysis. The calculation method of kernel density analysis is selected to obtain the kernel density map of highway disaster points. Utilize the ARCGIS spatial analysis overlay function, specifically call the overlay analysis module in the Spatial Analyst tool under the ARCGIS platform, select the weighted overlay calculation method, input the disaster probability layer and the kernel density layer, obtain the geological disaster susceptibility evaluation index of each evaluation unit through calculation, and form the susceptibility evaluation result.

7. A method for evaluating and zoning highway traffic operation status based on disaster conditions as claimed in claim 1, characterized in that: The geological disaster susceptibility assessment results are weighted and superimposed with the probability information of the main disaster-inducing factors in the region and the geological disaster point information to obtain the geological disaster risk assessment results, which specifically include: The weighted overlay calculation method provided by the ARCGIS software platform is selected to input the geological disaster susceptibility layer, the probability layer of the main disaster-inducing factors, and the geological disaster point information. The geological disaster point information includes the coordinates of the disaster point, the degree of hazard, the disaster level, the disaster type, the shadow length, and the frequency of occurrence information, and the geological disaster risk assessment results are obtained, thereby evaluating the possibility of the spatial location, scale or intensity, and frequency of occurrence of a certain scale of disasters in a certain area within a certain period of time.

8. A method for evaluating and zoning highway traffic operation status based on disaster conditions as claimed in claim 1, characterized in that: Based on the collected highway traffic operation status data under disaster conditions, the road traffic impact index is obtained, and the disaster risk level matrix is ​​established by combining the geological disaster risk assessment results with the road traffic impact index to obtain the disaster risk assessment results, including: The highway traffic operation status data collected under disaster conditions include the location, frequency, duration and length of highway traffic blockages. The data are normalized by grading and assigning values ​​to the highway traffic operation status indicator data to obtain the road traffic impact index, thereby establishing a disaster hazard and road traffic impact level matrix, and defining and coloring the disaster risk level into four levels: extremely high, high, medium and low risk.

9. A method for evaluating and zoning highway traffic operation status based on disaster conditions as claimed in claim 1, characterized in that: Obtain disaster risk assessment results, including: Based on the principles of similarity and proximity, the disaster risk assessment results are generalized and converted from raster to vector. The specific method is to input the disaster risk assessment results in the ENVI software platform, call the Classification tool, select the PostClassification module, perform Sieve classes calculation to remove scattered patches, and then input parameters for Clumpclasses calculation to complete the patch generalization and cluster analysis, thereby realizing the generalized raster processing of disaster risk assessment information; then use the Raster to Surface submodule under the Raster to Surface module of the conversion tool in the ARCGIS platform to realize the vectorization of raster data.

10. A highway traffic operation status assessment zoning system based on disaster conditions, characterized in that: The system comprises: The data collection module is used to obtain data on natural disaster risk points along the highway, collect data on geological factors, topographic factors and meteorological factors that may cause disasters on the highway, and collect data on the operation status of highway traffic under disaster conditions; The evaluation factor determination module is used to divide each area of ​​the highway into evaluation units according to the main disaster-prone factors in the area, and select different evaluation factor combinations for each divided evaluation unit according to the characteristics of the evaluation unit; The information volume calculation module is used to calculate the total information volume value of geological disasters under the corresponding evaluation factor combination based on the evaluation factor combination of each evaluation unit by using the information volume model method to evaluate the possibility of geological disasters and obtain the disaster probability information of different evaluation factors; The susceptibility assessment module is used to obtain the density information of highway disaster points based on the acquired natural disaster risk point data along the highway, and obtain the geological disaster susceptibility assessment results of each assessment unit by weighted superposition of the disaster probability information of different assessment factors and the highway disaster point density information; The hazard assessment module is used to perform weighted superposition of the geological disaster susceptibility assessment results with the probability information of the main disaster-inducing factors in the region and the geological disaster point information to obtain the geological disaster hazard assessment results; The risk assessment module is used to obtain the road traffic impact index based on the collected highway traffic operation status data under disaster conditions, establish a disaster risk level matrix with the geological disaster hazard assessment results and the road traffic impact index, obtain the disaster risk assessment results, and form a highway traffic operation status risk level zoning map under disaster conditions.

Images