Highway route selection method and system based on integrated air-space-ground-indoor intelligence analysis

Abstract

This invention discloses a highway route selection method and system based on integrated air-space-ground intelligent analysis, belonging to the field of highway route selection technology. The method includes: using InSAR and remote sensing image interpretation technology to initially identify and screen potential geological hazards in a corridor at a large scale; using airborne lidar technology to conduct detailed investigations of geological hazards in the corridor at a small scale; using comprehensive exploration methods including geological surveys, geophysical testing, and drilling verification to check geological hazards around the preliminary route; conducting risk assessments of potential geological hazard points within the preliminary route corridor and constructing a risk assessment model; and having geological engineers and route engineers optimize the route and provide multiple suggested routes, with the optimal planned route calculated using an intelligent expert analysis model. This invention alleviates the technical problem of limited scientific rigor and objectivity in route selection due to reliance on single geological hazard data in existing technologies.

Description

Technical Field

[0001] This invention relates to the field of highway route selection technology, and in particular to a highway route selection method and system based on integrated air-space-ground-indoor intelligent analysis. Background Technology

[0002] More and more highways in my country are extending into mountainous areas prone to geological disasters, and the focus of highway construction in Hubei Province is also shifting towards the geologically complex mountainous regions of western and northwestern Hubei. Due to the constraints of these mountainous areas' complex terrain and geological conditions, the variety of complex terrain and adverse geological phenomena that need to be considered in highway route selection will significantly increase. An unreasonable route will expose roadbed slopes, bridges, and tunnels to significant geological disaster risks and structural safety risks during construction, potentially leading to substantial economic losses.

[0003] Due to the complexity, diversity, and concealment of geological hazards, accurate identification is extremely difficult. Traditional identification methods mainly rely on manual on-site investigations and borehole exploration. These traditional single-hazard investigation methods fail to fully utilize the advantages of technologies such as remote sensing and drone aerial photography, resulting in huge investments of manpower and resources. Furthermore, they suffer from incomplete and insufficient investigations, making it difficult to meet the needs of geological hazard prevention and control. At the same time, existing route selection methods mostly depend on data from single geological hazards, and often suffer from independent decision-making and a lack of data complementarity. Route selection often depends on subjective human will, lacking objective scientific basis, leading to the underutilization of multi-source data and limiting the scientific rigor and rationality of route selection. Summary of the Invention

[0004] To address the aforementioned technical problems in existing technologies, this invention provides a highway route selection method and system based on integrated air-space-ground intelligent analysis. The technical solution is as follows:

[0005] On the one hand, a highway route selection method based on integrated air-space-ground-indoor intelligent analysis is provided. The method includes: preliminary zoning of the geological hazard susceptibility within the highway corridor based on the overall highway route planned during the engineering feasibility study phase, and preliminary marking based on historical geological hazard data to obtain a preliminary spatial distribution map of geological hazards along the highway; preliminary identification and screening of potential geological hazards in the corridor area based on InSAR and remote sensing image interpretation technology to obtain a large-scale spatial distribution map of potential geological hazards; detailed investigation of the large-scale spatial distribution map of potential geological hazards based on UAV-borne lidar and real-time dynamic positioning technology to obtain a small-scale spatial distribution map of potential geological hazards; and preliminary route design based on the small-scale spatial distribution map of potential geological hazards to obtain a preliminary... The design phase involves defining the local route corridor area; verifying surrounding geological hazards within the local route corridor area using comprehensive survey methods, and constructing a geological condition information database; these comprehensive survey methods include geological surveys, geophysical testing, and drilling verification; based on the geological condition information database, conducting local geological risk assessments of potential geological hazard points within the local route corridor area using qualitative methods, and obtaining a risk assessment model; based on the risk assessment model, making preliminary judgments on risk sources and risk zones along the local route corridor area, and adjusting and optimizing the route within the local route corridor area to obtain multiple routes to be planned; constructing an intelligent expert judgment model using a combination of qualitative and quantitative methods, and judging and comparing the multiple routes to be planned based on the intelligent expert judgment model to obtain the target planned route.

[0006] Optionally, based on the overall highway route planned during the feasibility study phase, the susceptibility to geological hazards within the highway corridor is preliminarily divided into zones, and preliminary marking is performed based on historical geological hazard data to obtain a preliminary spatial distribution map of geological hazards along the highway. This includes: classifying the susceptibility to geological hazards within the highway corridor into multiple regions according to the topographical features that easily induce geological hazards, based on the overall highway route planned during the feasibility study phase; the topographical features include: rivers, riverbanks, mountains, and karst areas; marking historical hazards in each region; the historical hazards include: landslides, debris flows, collapses, and unstable rock masses; generating image maps of the highway route within a predetermined range based on satellite data, and marking the historical hazards in the image maps to obtain a preliminary spatial distribution map of geological hazards along the highway.

[0007] Optionally, based on InSAR and remote sensing image interpretation technology, preliminary identification and screening of potential geological hazards in the corridor zone of the preliminary geological hazard spatial distribution map along the highway are performed to obtain a large-scale spatial distribution map of potential geological hazards. This includes: based on synthetic aperture radar interferometry, analyzing the interference effect between radar images of the target area acquired at different times to identify the displacement of the ground surface between two imaging sessions, obtaining multiple SAR images of the same area at different time points; the target area is the area corresponding to the corridor zone in the preliminary geological hazard spatial distribution map along the highway; registration, interferometry, filtering, and unwrapping calculations are performed on the multiple SAR images to obtain the deformation of the target area over the entire time period. The deformation time series is used to obtain surface deformation monitoring data; based on the surface deformation monitoring data, the three-dimensional coordinate information of the target area before and after deformation is obtained, and based on the three-dimensional coordinate information of the target area before and after deformation, the deformation characteristics, volume, and drop information of the unfavorable geological body are obtained; based on the deformation characteristics of the unfavorable geological body, the type of unfavorable geological body is identified; the types of unfavorable geological bodies include: landslides, debris flows, collapses, and unstable rock masses; based on the type of unfavorable geological body and the volume and drop information, the impact range of geological hazards is estimated; the impact range of geological hazards is marked in the multi-scene SAR imagery to obtain a large-scale spatial distribution map of geological hazard risks.

[0008] Optionally, a detailed investigation of the large-scale geological hazard spatial distribution map is conducted based on UAV-borne LiDAR and real-time dynamic positioning technology to obtain a small-scale geological hazard spatial distribution map. This includes: using UAV-borne LiDAR and UAV-borne camera aerial photography technology, flying close to the geological hazard points in the large-scale geological hazard spatial distribution map to obtain image data of unfavorable geological bodies within the geological hazard and 3D point cloud data acquired based on LiDAR; using SFM 3D image reconstruction technology to generate a 3D model; based on the 3D model, obtaining the attitude information of exposed structural surfaces of unfavorable geological bodies in different geological hazard areas; embedding the 3D model into the image map of the large-scale geological hazard spatial distribution map, and marking the attitude information of exposed structural surfaces of unfavorable geological bodies in the 3D model to obtain the small-scale geological hazard spatial distribution map.

[0009] Optionally, a geological condition information database is constructed by verifying the surrounding geological hazards within the local railway corridor area based on comprehensive exploration methods. This includes: obtaining first geological information of the local railway corridor area using geological survey methods; the first geological information includes: stratigraphic lithology, landform type, hydrology and meteorology, geological structure, vegetation cover information, and information on the impact of human activities; obtaining second geological information by conducting ground tests on the local railway corridor area using geophysical testing methods such as high-density electrical resistivity tomography, CSATM magnetotelluric method, micro-motion surface wave method, and 3D seismic method; obtaining third geological information by conducting internal geological exploration of the soil and rock at potential geological hazard points within the local railway corridor area using drilling verification methods such as internal drilling, comprehensive well logging, and deep displacement monitoring; and constructing a geological condition information database based on the first, second, and third geological information.

[0010] Optionally, based on the geological condition information database, a qualitative method is used to conduct a local geological risk assessment of the geological hazard points within the local route corridor, resulting in a risk assessment model. This model includes: constructing multiple risk indicators based on the geological condition information database, and assigning corresponding weights to each risk indicator; the risk indicators include: topographic indicators, geological structure indicators, stratigraphic lithology indicators, hydrogeological condition indicators, and adverse geological body indicators; and conducting expert panel scoring of the geological hazard points within the local route corridor based on the multiple risk indicators to construct the risk assessment model.

[0011] Optionally, based on the risk assessment model, a preliminary judgment is made on the risk sources and risk zones along the local route corridor, and the routes within the local route corridor are adjusted and optimized to obtain multiple routes to be planned. This includes: based on the risk assessment model, a preliminary judgment is made on the risk sources and risk zones along the local route corridor to obtain the risk level of multiple risk zones; the multiple risk zones are ranked based on the risk level of each risk zone; the routes within the local route corridor are adjusted and optimized based on the ranking of the multiple risk zones to obtain multiple routes to be planned; wherein the optimization objective is to minimize the sum of the risk levels of the routes passing through the risk zones.

[0012] Optionally, an intelligent expert judgment model is constructed using a combination of qualitative and quantitative methods. Based on the intelligent expert judgment model, the multiple routes to be planned are evaluated and compared to obtain the target planned route. This includes: determining multiple impact indicators based on the risk assessment model; the multiple impact indicators include multiple technical indicators, multiple geological indicators, and multiple economic indicators; screening multiple sensitive indicators based on the multiple impact indicators; constructing an intelligent expert judgment model using a combination of qualitative and quantitative methods based on the multiple sensitive indicators; and evaluating and comparing the multiple routes to be planned based on the intelligent expert judgment model to obtain the target planned route.

[0013] Optionally, a combined qualitative and quantitative approach is used to construct an intelligent expert judgment model, including: constructing an initial model structure based on an optimal route layer, an influencing indicator layer, and a proposed route layer; establishing a first comparison matrix for the influencing indicator layer; the first comparison matrix includes... , Indicator Factors and Compared to the importance of what is obtained, The first factor influencing highway route selection is defined as: Based on the first comparison matrix, a first importance matrix is ​​constructed relative to the optimal route layer O, whereby the influencing index layer is the i-th factor. This first importance matrix includes:

[0014]

[0015] Based on the first importance matrix, the largest eigenvalue and the corresponding first eigenvector are obtained, and normalized to obtain a normalized first eigenvector. Based on the magnitude of the elements in the normalized first eigenvector, the importance ranking of each factor in the influence index layer is obtained; each element in the normalized first eigenvector represents the weight of the influence index layer relative to each factor in the optimal route layer; a second comparison matrix for the proposed route layer is established; the second comparison matrix includes... , Indicator Factors With factors Compared to the importance of what is obtained, For the proposed first i One alternative route; based on the second comparison matrix, the proposed route layer is obtained relative to the first influencing index layer. i The second importance matrix of the factors; the second importance matrix includes:

[0016]

[0017] Based on the second importance matrix, the largest eigenvalues ​​and corresponding second eigenvectors are obtained and normalized to obtain normalized second eigenvectors. Each element in the normalized second eigenvector represents the weight of the proposed route layer relative to each factor in the optimal route layer. Based on the magnitude of the elements in the normalized second eigenvector, the comprehensive weight of each factor in the proposed route layer to the optimal route layer is obtained. The comprehensive weight includes: In the formula, n i Let n be the comprehensive weight of the i-th factor in the proposed route layer to the optimal route layer, and n be the total number of factors in the proposed route layer. i,j m is an element in the normalized second eigenvector. j The elements are those in the normalized first feature vector; based on the comprehensive weight, the ranking of each candidate route in the proposed route layer is determined.

[0018] On the other hand, a highway route selection system based on integrated air-space-ground-indoor intelligent analysis is also provided, applied to the highway route selection method based on integrated air-space-ground-indoor intelligent analysis provided in the embodiments of the present invention. The system includes: a preliminary zoning module, a first screening module, a second screening module, a preliminary design module, a construction module, an evaluation module, an optimization module, and an analysis module. The preliminary zoning module is used to perform preliminary zoning of the geological hazard susceptibility within the highway corridor based on the macro-route of the entire highway planned in the engineering feasibility study stage, and to perform preliminary marking based on historical geological hazard data to obtain a preliminary spatial distribution map of geological hazards along the highway. The first screening module is used to perform preliminary identification and screening of corridor geological hazard hazards in the preliminary spatial distribution map of geological hazards along the highway based on InSAR and remote sensing image interpretation technology to obtain a large-scale spatial distribution map of geological hazard hazards. The second screening module is used to conduct a detailed investigation of the large-scale spatial distribution map of geological hazard hazards based on UAV-borne lidar and real-time dynamic positioning technology to obtain a small-scale spatial distribution map of geological hazard hazards. The system comprises the following modules: a spatial distribution map of geological hazards; a preliminary design module for preliminary route design based on the small-scale spatial distribution map of geological hazards, resulting in a local route corridor range for the preliminary design stage; a construction module for verifying the surrounding geological hazards within the local route corridor range using comprehensive exploration methods, including geological surveys, geophysical testing, and drilling verification; an evaluation module for conducting local geological risk assessments of geological hazard points within the local route corridor range using qualitative methods based on the geological condition information database, resulting in a risk assessment model; an optimization module for making preliminary judgments on risk sources and risk zones along the local route corridor range based on the risk assessment model, and adjusting and optimizing the route within the local route corridor range to obtain multiple routes to be planned; and a judgment module for constructing an intelligent expert judgment model using a combination of qualitative and quantitative methods, and judging and comparing the multiple routes to be planned based on the intelligent expert judgment model to obtain the target planned route.

[0019] This invention provides a method and system for highway route selection based on integrated air-space-ground-indoor intelligent analysis. By integrating multi-source information such as InSAR data, airborne lidar data, geological surveys, geophysical tests, and drilling verification, a risk assessment model and an intelligent expert analysis model are constructed. This solves the problems of data bias and strong subjectivity when selecting routes based on a single factor. By comprehensively considering multiple influencing factors and comparing the importance of any two factors to calculate their weights, the scientific nature and timeliness of highway route selection are improved. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a highway route selection method based on integrated air-space-ground-indoor intelligence analysis provided by an embodiment of the present invention;

[0022] Figure 2 This is a preliminary spatial distribution map of geological hazards along a highway provided by an embodiment of the present invention;

[0023] Figure 3 This is a large-scale spatial distribution map of potential geological hazards provided by an embodiment of the present invention;

[0024] Figure 4 This is a small-scale spatial distribution map of potential geological hazards provided by an embodiment of the present invention;

[0025] Figure 5 This is a schematic diagram of the structure of an intelligent expert judgment model provided in an embodiment of the present invention;

[0026] Figure 6 This is a schematic diagram of a highway route selection system based on integrated air-space-ground-indoor intelligent analysis provided in an embodiment of the present invention. Detailed Implementation

[0027] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0028] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0029] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0030] Figure 1 This is a flowchart of a highway route selection method based on integrated air-space-ground-indoor intelligent analysis according to an embodiment of the present invention. Figure 1 As shown, the method specifically includes the following steps:

[0031] Step S102: Based on the overall highway route planned in the feasibility study stage, the geological hazard susceptibility within the highway corridor is preliminarily divided into zones, and preliminary marking is performed based on historical geological hazard data to obtain a preliminary spatial distribution map of geological hazards along the highway.

[0032] Step S104: Based on InSAR and remote sensing image interpretation technology, preliminary identification and screening of potential geological hazards in the corridor zone of the preliminary geological hazard spatial distribution map along the highway are carried out to obtain a large-scale spatial distribution map of potential geological hazards.

[0033] Step S106: Based on UAV-borne lidar and real-time dynamic positioning technology, a detailed investigation of the spatial distribution map of large-scale geological hazard risks is conducted to obtain a spatial distribution map of small-scale geological hazard risks.

[0034] Step S108: Based on the spatial distribution map of small-scale geological hazard risks, a preliminary route design is carried out to obtain the local route corridor range in the preliminary design stage.

[0035] Step S110: Verify the surrounding geological hazards within the local corridor area based on comprehensive exploration methods and construct a geological condition information database; the comprehensive exploration methods include geological survey, geophysical testing and drilling verification.

[0036] Step S112: Based on the geological condition information database, a qualitative method is used to conduct a local geological risk assessment of the geological hazard points within the local route corridor area, and a risk assessment model is obtained.

[0037] Step S114: Based on the risk assessment model, a preliminary judgment is made on the risk sources and risk zones along the local route corridor, and the routes within the local route corridor are adjusted and optimized to obtain multiple routes to be planned.

[0038] Step S116: A smart expert judgment model is constructed using a combination of qualitative and quantitative methods. Based on the smart expert judgment model, multiple routes to be planned are judged and compared to obtain the target planned route.

[0039] Specifically, step S102 further includes the following steps:

[0040] Step S1021: Based on the overall highway route planned in the feasibility study stage, the terrain and geomorphological features that are prone to geological disasters are classified into multiple areas within the highway corridor. The terrain and geomorphological features include: rivers, riverbanks, mountains, and karst areas.

[0041] Step S1022: Mark historical disasters in each area; historical disasters include: landslides, debris flows, collapses, and unstable rock masses;

[0042] Step S1023: Generate an image map of the entire highway's macroscopic route within a predetermined range based on satellite data, and mark historical disasters on the image map to obtain a preliminary spatial distribution map of geological disasters along the highway, such as... Figure 2 As shown. Among them, Figure 2 This is a preliminary spatial distribution map of geological hazards along a highway, provided according to an embodiment of the present invention.

[0043] Among them, historical disasters refer to disasters that have occurred in the history of the highway corridor.

[0044] Specifically, step S104 further includes the following steps:

[0045] Step S1041: Based on the synthetic aperture radar interferometry (InSAR) technology, analyze the interference effect between radar images of the target area acquired at different times to identify the displacement of the ground surface between the two imaging, and obtain multiple SAR images of the same area at different time points; the target area is the area corresponding to the corridor zone in the preliminary spatial distribution map of geological hazards along the highway.

[0046] Step S1042: Register, interferometrically, filter, and unwrap calculations are performed on multiple SAR images to obtain the deformation time series of the target area for the entire time period, and surface deformation monitoring data are obtained based on the deformation time series.

[0047] Step S1043: Based on the surface deformation monitoring data, obtain the three-dimensional coordinate information of the target area before and after deformation, and based on the three-dimensional coordinate information of the target area before and after deformation, obtain the deformation characteristics, volume and drop information of the unfavorable geological body.

[0048] Step S1044: Based on the deformation characteristics of the unfavorable geological body, identify the type of unfavorable geological body; the types of unfavorable geological bodies include: landslides, debris flows, collapses, and unstable rock masses;

[0049] Step S1045: Based on the type, volume, and elevation information of the adverse geological body, estimate the impact range of the geological hazard;

[0050] Step S1046: Mark the area affected by geological disasters in multiple SAR images to obtain a large-scale spatial distribution map of potential geological disaster hazards.

[0051] Figure 3 This is a large-scale spatial distribution map of potential geological hazards provided by an embodiment of the present invention.

[0052] Specifically, step S106 further includes the following steps:

[0053] Step S1061: Based on UAV-borne LiDAR and UAV-borne camera aerial photography technology, fly close to the geological hazard points in the large-scale geological hazard spatial distribution map to obtain image data of unfavorable geological bodies in the geological hazard and three-dimensional point cloud data based on LiDAR. Use SFM three-dimensional image reconstruction technology to generate a three-dimensional model.

[0054] Step S1062: Based on the three-dimensional model, obtain the attitude information of exposed structural surfaces of unfavorable geological bodies in different geological hazard risks;

[0055] Step S1063: The three-dimensional model is embedded into the image map of the large-scale spatial distribution map of geological hazards, and the occurrence information of exposed structural surfaces of adverse geological bodies is marked in the three-dimensional model to obtain the small-scale spatial distribution map of geological hazards.

[0056] Figure 4 This is a small-scale spatial distribution map of potential geological hazards provided by an embodiment of the present invention.

[0057] Specifically, step S110 further includes the following steps:

[0058] Step S1101: Using geological survey methods, obtain the first geological information of the local route corridor zone; the first geological information includes: stratigraphic lithology, landform type, hydrology and meteorology, geological structure, vegetation cover information and information on the impact of human activities;

[0059] Step S1102: Using geophysical testing methods, ground tests are conducted on the local corridor area using high-density electrical resistivity tomography, CSATM magnetotelluric method, micro-motion surface wave method, and three-dimensional seismic method to obtain second geological information.

[0060] Step S1103: Using the drilling verification method, internal geological exploration of the soil and rock is carried out by means of internal drilling, comprehensive logging and deep displacement monitoring of potential geological disaster points in the local line corridor area to obtain third geological information.

[0061] Step S1104: Based on the first geological information, the second geological information, and the third geological information, construct a geological condition information database containing multi-source heterogeneous information from the ground and interior.

[0062] Specifically, step S112 further includes the following steps:

[0063] Step S1121: Based on the geological condition information database, construct multiple risk indicators and assign corresponding weights to each risk indicator; the risk indicators include: topographic and geomorphological indicators, geological structure indicators, stratigraphic and lithological indicators, hydrogeological condition indicators, and adverse geological body indicators.

[0064] Preferably, the topographic and geomorphological indicators include: altitude, relative elevation, and slope.

[0065] Geological structural indicators include: active faults, dead faults, and tectonic stress;

[0066] Stratigraphic lithological indicators include: loose deposits, fractured rock masses, and intact rock masses;

[0067] Hydrogeological indicators include: the distribution range of groundwater, the distribution range of surface water, and the corrosivity of water to structures;

[0068] Unfavorable geological indicators include: landslides, debris flows, collapses, and unstable rock masses;

[0069] Step S1122: Based on multiple risk indicators, an expert panel scores the geological hazard points within the local corridor area and constructs a risk assessment model.

[0070] Specifically, the risk assessment model includes:

[0071] Based on expert experience, the weights of topographic and geomorphological indicators, geological structure indicators, stratigraphic lithology indicators, hydrogeological condition indicators, and adverse geological body indicators were obtained respectively, and they conform to the relationship formula (1):

[0072] (1)

[0073] In the formula: Weights for topographic and geomorphological indicators Weights of geological structural indicators Weights of stratigraphic lithology indicators The weights of hydrogeological condition indicators The weights of the indicators for unfavorable geological bodies;

[0074] Then, based on expert experience, the weights of altitude, relative elevation, and slope gradient are obtained, and they conform to the relationship formula (2):

[0075] (2)

[0076] In the formula: Weighting for altitude Weighting relative elevation The weight of the slope gradient;

[0077] Based on expert experience, the weights of active faults, dead faults, and tectonic stresses are obtained, and they conform to the relationship formula (3):

[0078] (3)

[0079] In the formula: Weight of active faults, Weights of dead faults The weight of the structural stress;

[0080] Based on expert experience, the weights of loose sedimentary layers, fractured rock masses, and intact rock masses are obtained, and they conform to the relationship formula (4):

[0081] (4)

[0082] In the formula: For the weight of loosely packed layers, For the weight of the fractured rock mass, The weight of the intact rock mass;

[0083] Based on expert experience, the weights of groundwater distribution range, surface water distribution range, and water corrosivity to structures were obtained, and they conformed to the relationship formula (5):

[0084] (5)

[0085] In the formula: Weights for groundwater distribution range Weights for the distribution range of surface water The weight of the corrosiveness of water to a structure;

[0086] Based on expert experience, the weights of landslides, debris flows, collapses, and unstable rock masses are obtained, and they conform to the relationship formula (6):

[0087] (6)

[0088] In the formula: For the weight of landslides, Weight of debris flow For the collapse of weight, The weight of the unstable rock mass;

[0089] Experts scored the altitude, relative elevation, and slope gradient to obtain scores for topographic indicators.

[0090] (7)

[0091] In the formula: Fractions of altitude Fractions for relative elevation It represents the fraction of the slope.

[0092] By having experts score active faults, dead faults, and tectonic stress, scores for geological structural indicators are obtained:

[0093] (8)

[0094] In the formula: For active faults, The fraction of dead faults, This represents the fraction of structural stress.

[0095] By having experts score the loose sedimentary layers, fractured rock masses, and intact rock masses, scores for the stratigraphic lithology indicators are obtained:

[0096] (9)

[0097] In the formula: For the fraction of loosely packed layers, The fraction of the fractured rock mass The fraction of intact rock mass;

[0098] By having experts score the distribution range of groundwater, the distribution range of surface water, and the corrosiveness of water to structures, scores for hydrogeological conditions are obtained:

[0099] (10)

[0100] In the formula: Fractions of the distribution range of groundwater Fractions representing the distribution range of surface water The score representing the corrosiveness of water to the structure;

[0101] Experts scored landslides, debris flows, collapses, and unstable rock masses to obtain scores for unfavorable geological indicators:

[0102] (11)

[0103] In the formula: For the landslide score, For the fraction of debris flow, For the collapsed score, The fraction representing the unstable rock mass;

[0104] Based on the scores of topographic and geomorphological indicators, geological structure indicators, stratigraphic lithology indicators, hydrogeological condition indicators, and adverse geological body indicators, and their respective weights, a risk assessment model for a specific area is obtained:

[0105] (12)

[0106] Specifically, step S114 further includes the following steps:

[0107] Step S1141: Based on the risk assessment model, make a preliminary judgment on the risk sources and risk zones along the local line corridor and obtain the risk level of multiple risk zones.

[0108] Step S1142: Sort multiple risk partitions based on the risk level of each risk partition;

[0109] Step S1143: Based on the ranking of multiple risk zones, the routes within the local route corridor are adjusted and optimized to obtain multiple routes to be planned; the optimization objective is to minimize the sum of the risk levels of the routes passing through the risk zones.

[0110] Specifically, step S116 further includes the following steps:

[0111] Step S1161: Based on the risk assessment model, determine multiple impact indicators; these multiple impact indicators include: multiple technical indicators, multiple geological indicators, and multiple economic indicators.

[0112] Preferably, the technical specifications include: mileage, horizontal alignment, longitudinal profile, cross profile, burial depth, and slope;

[0113] Geological indicators include: topographic and geomorphological indicators, geological structure indicators, stratigraphic and lithological indicators, hydrogeological condition indicators, and indicators of unfavorable geological bodies;

[0114] Economic indicators include: project cost, demolition cost, and environmental impact losses;

[0115] Step S1162: Based on multiple influencing indicators, screen multiple sensitive indicators;

[0116] Step S1163: Based on multiple sensitive indicators, construct an intelligent expert judgment model using a combination of qualitative and quantitative methods;

[0117] Step S1164: Based on the intelligent expert judgment model, multiple routes to be planned are judged and compared to obtain the target planned route.

[0118] Figure 5 This is a schematic diagram of the structure of an intelligent expert judgment model provided according to an embodiment of the present invention. Figure 5 As shown, step S1163 further includes the following steps:

[0119] Step S1: Construct the initial model structure based on the optimal route layer, the influencing index layer, and the proposed route layer;

[0120] Specifically, the optimal route layer, using This indicates the final selected highway route;

[0121] Influence indicator layer ,use This indicates the factors that influence highway route selection;

[0122] Proposed route layer ,use This indicates the initial list of n alternative routes.

[0123] Step S2, establish the first comparison matrix affecting the indicator layer; the first comparison matrix includes , Indicator Factors and Compared to the importance of what is obtained, This is the i-th factor influencing highway route selection;

[0124] Specifically, M is a positively reciprocal matrix. The degree of importance follows these rules:

[0125] When factors and When equally important, ;

[0126] When factors Compare When it is slightly important, ;

[0127] When factors Compare When it is obviously important, ;

[0128] When factors Compare When it is extremely important, ;

[0129] When factors Compare When extremely important and strong, ;

[0130] When factors Compare Compared to when it is in the middle of the above adjacent importance levels, they are respectively , , , ;

[0131] When factors With factors The importance of the comparison is At that time, then factors With factors The importance of the comparison is ;

[0132] Step S3: Based on the first comparison matrix, construct the first importance matrix of the influence index layer relative to the optimal route layer O; the first importance matrix includes:

[0133]

[0134] Step S4: Based on the first importance matrix, obtain the largest eigenvalue and the corresponding first eigenvector, and normalize them to obtain the normalized first eigenvector. Based on the weights in the normalized first eigenvector, obtain the importance ranking of each factor influencing the indicator layer; where the first eigenvector... The elements in the index layer are the influencing factors. Relative to the optimal route layer Various factors Corresponding weights .

[0135] Step S5: Establish the second comparison matrix for the proposed route layer; the second comparison matrix includes... , Indicator Factors With factors Compared to the importance of what is obtained, This is the proposed i-th alternative route;

[0136] Wherein, the second comparison matrix N is a positive reciprocal matrix. The importance of satisfying the rules and The rules for determining their importance are the same;

[0137] Step S6: Based on the second comparison matrix, obtain the second importance matrix of the proposed route layer relative to the i-th factor in the influencing indicator layer; the second importance matrix (a total of m matrices) includes:

[0138]

[0139]

[0140]

[0141]

[0142] It should be noted that the elements at the same position within different matrices are different, such as b in M1. 1,2 and b in M2 1,2 They are not necessarily equal. i,j It represents any two elements in a random combination.

[0143] Step S7: Based on the second importance matrix, obtain each maximum eigenvalue and the corresponding second eigenvector, and normalize them to obtain the normalized second eigenvector. Based on the weights in the normalized second eigenvector, obtain the comprehensive weights of each factor in the proposed route layer on the optimal route layer.

[0144] Specifically, the second feature vector The elements in the middle are the proposed route layers. n factors affect the indicator layer Factors in The weight is , ... ( ),in To influence the indicator layer The number of a certain factor;

[0145] Step S8: Based on the comprehensive weight, determine the ranking of each candidate route in the proposed route layer.

[0146] Specifically, according to weight and weight The proposed route layer is obtained. The i-th factor For the optimal route Overall weighting: ;

[0147] That is, the overall weight of each factor is:

[0148] according to Sort by size to obtain the proposed route layer The sorting, The corresponding route is the optimal route.

[0149] Optionally, this embodiment of the invention also provides a specific embodiment of an intelligent expert judgment model as follows:

[0150] To facilitate calculation and reduce the number of matrices and their elements, two factors were selected from each of the technical, geological, and economic indicators, for a total of six factors for calculation; the proposed routes were calculated as three routes.

[0151] Technical specifications include: planar alignment and burial depth;

[0152] Geological indicators include: geological structural indicators and indicators of unfavorable geological bodies;

[0153] Economic indicators include: project cost and demolition cost;

[0154] Optimal route layer, using This indicates the selection of the final highway route;

[0155] Influence indicator layer Including: planar linear ( ), burial depth ( ), geological structural indicators ( ), adverse geological indicators ( ), project cost ( ), demolition cost ( );

[0156] Proposed route layer ,include: , , ;

[0157] First comparison matrix ,use It is represented as a positively reciprocal matrix. Indicates any two factors and Compared to the importance of what is obtained, that is The degree of importance follows these rules:

[0158] When factors and When equally important, ;

[0159] When factors Compare When it is slightly important, ;

[0160] When factors Compare When it is obviously important, ;

[0161] When factors Compare When it is extremely important, ;

[0162] When factors Compare When extremely important and strong, ;

[0163] When factors Compare Compared to when it is in the middle of the above adjacent importance levels, they are respectively , , , ;

[0164] When factors With factors The importance of the comparison is At that time, then factors With factors The importance of the comparison is ;

[0165] Based on impact indicators and The importance rules determine the influence of the indicator layer. Relative to the optimal route layer Importance matrix:

[0166]

[0167] According to the matrix To obtain its largest eigenvalue and the corresponding normalized feature vector eigenvectors The elements in the index layer are the influencing factors. Relative to the optimal route layer Various factors Corresponding weights Based on the weights, the influencing indicator layer is obtained. Various factors Ranking by importance;

[0168] Second comparison matrix ,use It is represented as a positively reciprocal matrix. Indicates any two factors With factors Compared to the importance of what is obtained, The importance of satisfying the rules and The rules for determining their importance are the same;

[0169] Based on the proposed route, the proposed route layer is obtained. Compared to the influence indicator layer Importance matrix, including the proposed route layer Compared to the influence indicator layer Medium factors Importance matrix (6 matrices in total):

[0170] , ,

[0171] , , ;

[0172] Based on 6 matrices The largest eigenvalues ​​are obtained. and the corresponding normalized feature vector ,include:

[0173] , ;

[0174] , ;

[0175] , ;

[0176] , ;

[0177] , ;

[0178] , ;

[0179] According to each matrix The corresponding normalized feature vector The total eigenvector is obtained. :

[0180]

[0181] Feature vector The elements in the middle are the proposed route layers. n factors affect the indicator layer Factors in The weight is , , ( ), To influence the indicator layer The number of a certain factor;

[0182] According to weight and weight The proposed route layer is obtained. The i-th factor For the optimal route The weights are: ;

[0183] That is, the weight of each factor is:

[0184] according to Sort by size to obtain the proposed route layer The sorting, that is The corresponding route is the optimal route.

[0185] As described above, the embodiments of the present invention provide a highway route selection method based on integrated air-space-ground-indoor intelligent analysis. By integrating multi-source information such as InSAR data, airborne lidar data, geological surveys, geophysical tests, and drilling verification, a risk assessment model and an intelligent expert analysis model are constructed. This solves the problems of data bias and strong subjectivity when selecting routes based on a single factor. By comprehensively considering multiple influencing factors and comparing the importance of any two factors to calculate their weights, the scientificity and timeliness of highway route selection are improved.

[0186] Figure 6 This is a schematic diagram of a highway route selection system based on integrated air-space-ground-indoor intelligent analysis according to an embodiment of the present invention, applied to the highway route selection method based on integrated air-space-ground-indoor intelligent analysis provided in the embodiment of the present invention. Figure 6 As shown, the system includes: a preliminary partitioning module 10, a first screening module 20, a second screening module 30, a preliminary design module 40, a construction module 50, an evaluation module 60, an optimization module 70, and a judgment module 80.

[0187] Specifically, the preliminary zoning module 10 is used to perform preliminary zoning of the geological hazard susceptibility within the highway corridor based on the macro-route of the entire highway planned in the engineering feasibility study stage, and to perform preliminary marking based on historical geological hazard data to obtain a preliminary spatial distribution map of geological hazards along the highway.

[0188] The first screening module 20 is used to perform preliminary identification and screening of potential geological hazards in the corridor zone of the preliminary spatial distribution map of geological hazards along the highway based on InSAR and remote sensing image interpretation technology, so as to obtain a large-scale spatial distribution map of potential geological hazards.

[0189] The second screening module 30 is used to conduct a detailed investigation of the spatial distribution map of large-scale geological hazard hazards based on UAV-borne lidar and real-time dynamic positioning technology, and obtain a spatial distribution map of small-scale geological hazard hazards.

[0190] Preliminary design module 40 is used to conduct preliminary route design based on a small-scale spatial distribution map of geological hazard risks, and to obtain the local route corridor range in the preliminary design stage;

[0191] Module 50 is used to verify the surrounding geological hazards within the local corridor area based on comprehensive exploration methods and to build a geological condition information database; the comprehensive exploration methods include geological survey, geophysical testing and drilling verification;

[0192] Assessment module 60 is used to conduct local geological risk assessment of potential geological hazards within the local corridor area based on a geological condition information database and using qualitative methods to obtain a risk assessment model;

[0193] The optimization module 70 is used to make a preliminary judgment on the risk sources and risk zones along the local route corridor based on the risk assessment model, and to adjust and optimize the route within the local route corridor to obtain multiple routes to be planned.

[0194] The analysis module 80 is used to construct an intelligent expert analysis model using a combination of qualitative and quantitative methods, and to analyze and compare multiple routes to be planned based on the intelligent expert analysis model to obtain the target planned route.

[0195] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A highway route selection method based on integrated air-space-ground-indoor intelligent analysis, characterized in that, The method includes: Step S102: Based on the overall highway route planned in the engineering feasibility study stage, the geological hazard susceptibility within the highway corridor is preliminarily divided into zones, and preliminary marking is performed based on historical geological hazard data to obtain a preliminary spatial distribution map of geological hazards along the highway. Step S104: Based on InSAR and remote sensing image interpretation technology, preliminary identification and screening of potential geological hazards in the corridor zone of the preliminary geological hazard spatial distribution map along the highway are carried out to obtain a large-scale spatial distribution map of potential geological hazards. Step S106: Based on UAV-borne lidar and real-time dynamic positioning technology, a detailed investigation is conducted on the large-scale geological hazard spatial distribution map to obtain a small-scale geological hazard spatial distribution map. Step S108: Based on the small-scale geological hazard spatial distribution map, a preliminary route design is carried out to obtain the local route corridor range in the preliminary design stage; Step S110: Verify the surrounding geological hazards within the local corridor area based on comprehensive exploration methods, and construct a geological condition information database; the comprehensive exploration methods include geological survey, geophysical testing, and drilling verification; Step S112: Based on the geological condition information database, a qualitative method is used to conduct a local geological risk assessment of the geological hazard points within the local line corridor area, and a risk assessment model is obtained. Step S114: Based on the risk assessment model, make a preliminary judgment on the risk sources and risk zones along the local route corridor, and adjust and optimize the routes within the local route corridor to obtain multiple routes to be planned. Step S116: A smart expert judgment model is constructed using a combination of qualitative and quantitative methods. Based on the smart expert judgment model, the multiple routes to be planned are judged and compared to obtain the target planned route.

2. The method according to claim 1, characterized in that, Based on the overall highway route planned during the feasibility study phase, preliminary zoning of the geological hazard susceptibility within the highway corridor was conducted, and preliminary marking was performed based on historical geological hazard data, resulting in a preliminary spatial distribution map of geological hazards along the highway, including: Based on the overall highway route planned during the feasibility study phase, the geological hazard susceptibility within the highway corridor is classified into multiple areas according to the topographical features that are prone to geological disasters. These topographical features include: rivers, riverbanks, mountains, and karst areas. Historical disasters within each area are marked; these historical disasters include: landslides, debris flows, collapses, and unstable rock masses. Based on satellite data, an image map of the entire highway's macroscopic route within a predetermined range is generated, and historical disasters are marked on the image map to obtain a preliminary spatial distribution map of geological disasters along the highway.

3. The method according to claim 1, characterized in that, Based on InSAR and remote sensing image interpretation technology, preliminary identification and screening of potential geological hazards in the corridor zone of the preliminary geological hazard spatial distribution map along the highway were conducted, resulting in a large-scale spatial distribution map of potential geological hazards, including: Based on synthetic aperture radar interferometry, the interference effect between radar images of the target area acquired at different times is analyzed to identify the displacement of the ground surface between the two imaging processes, thus obtaining multiple SAR images of the same area at different time points; the target area is the area corresponding to the corridor zone in the preliminary spatial distribution map of geological hazards along the highway. The multiple SAR images are registered, interferometric, filtered, and unwrapped respectively to obtain the deformation time series of the target area for the entire time period, and the surface deformation monitoring data are obtained based on the deformation time series. Based on the surface deformation monitoring data, the three-dimensional coordinate information of the target area before and after deformation is obtained, and based on the three-dimensional coordinate information of the target area before and after deformation, the deformation characteristics, volume and drop information of the unfavorable geological body are obtained. Based on the deformation characteristics of the adverse geological bodies, the types of adverse geological bodies are identified; the types of adverse geological bodies include: landslides, debris flows, collapses, and unstable rock masses; Based on the type of the adverse geological body and the information on its volume and elevation difference, the scope of the geological hazard impact is estimated; The affected area of ​​the geological disaster is marked in the multi-scene SAR imagery to obtain a large-scale spatial distribution map of potential geological disaster hazards.

4. The method according to claim 1, characterized in that, A detailed investigation of the large-scale geological hazard spatial distribution map was conducted using UAV-borne lidar and real-time dynamic positioning technology to obtain a small-scale geological hazard spatial distribution map, including: Based on UAV-borne LiDAR and UAV-borne camera aerial photography technology, the drone flies close to the geological hazard points in the large-scale geological hazard spatial distribution map to obtain image data of unfavorable geological bodies in the geological hazard and three-dimensional point cloud data based on LiDAR. The SFM three-dimensional image reconstruction technology is then used to generate a three-dimensional model. Based on the aforementioned three-dimensional model, information on the orientation of exposed structural surfaces of unfavorable geological bodies in different geological hazard risks is obtained; The three-dimensional model is embedded into the image of the large-scale geological hazard spatial distribution map, and the occurrence information of the exposed structural surfaces of the unfavorable geological bodies is marked in the three-dimensional model to obtain a small-scale geological hazard spatial distribution map.

5. The method according to claim 1, characterized in that, Based on comprehensive survey methods, the surrounding geological hazards within the aforementioned local railway corridor area were verified, and a geological condition information database was constructed, including: The geological survey method is used to obtain the first geological information of the local route corridor area; the first geological information includes: stratigraphic lithology, landform type, hydrology and meteorology, geological structure, vegetation cover information and information on the impact of human activities; Geophysical testing methods were employed, including high-density electrical resistivity tomography, CSATM magnetotelluric method, micro-motion surface wave method, and three-dimensional seismic method, to conduct ground tests on the local corridor area and obtain second geological information. The drilling verification method is used to conduct internal geological exploration of the soil and rock by means of internal drilling, comprehensive well logging and deep displacement monitoring in the local line corridor area to obtain third geological information; A geological condition information database is constructed based on the first geological information, the second geological information, and the third geological information.

6. The method according to claim 1, characterized in that, Based on the geological condition information database, a qualitative method is used to conduct a local geological risk assessment of potential geological hazards within the local railway corridor, resulting in a risk assessment model, including: Based on the geological condition information database, multiple risk indicators are constructed, and each risk indicator is assigned a corresponding weight; the risk indicators include: topographic and geomorphological indicators, geological structure indicators, stratigraphic and lithological indicators, hydrogeological condition indicators, and adverse geological body indicators. Based on the aforementioned multiple risk indicators, an expert panel scores the geological hazard points within the local railway corridor area, and a risk assessment model is constructed.

7. The method according to claim 1, characterized in that, Based on the aforementioned risk assessment model, a preliminary judgment is made on the risk sources and risk zones along the local route corridor, and the routes within the local route corridor are adjusted and optimized to obtain multiple routes to be planned, including: Based on the risk assessment model, a preliminary judgment is made on the risk sources and risk zones along the local line corridor, and the risk level of multiple risk zones is obtained. The multiple risk partitions are sorted based on the risk level of each risk partition; Based on the ranking of the multiple risk zones, the routes within the local route corridor are adjusted and optimized to obtain multiple routes to be planned; the optimization objective is to minimize the sum of the risk levels of the routes passing through the risk zones.

8. The method according to claim 1, characterized in that, A combined qualitative and quantitative approach is used to construct an intelligent expert evaluation model. Based on this model, multiple routes to be planned are evaluated and compared to obtain the target planned route, including: Based on the risk assessment model, multiple impact indicators are identified; these multiple impact indicators include: multiple technical indicators, multiple geological indicators, and multiple economic indicators. Based on the aforementioned multiple influencing indicators, several sensitive indicators were selected; Based on the aforementioned multiple sensitive indicators, an intelligent expert judgment model is constructed using a combination of qualitative and quantitative methods. Based on the intelligent expert judgment model, the multiple routes to be planned are judged and compared to obtain the target planned route.

9. The method according to claim 8, characterized in that, An intelligent expert judgment model is constructed using a combination of qualitative and quantitative methods, including: Based on the optimal route layer, the influencing indicator layer, and the proposed route layer, an initial model structure is constructed. Establish a first comparison matrix for the influence index layer; the first comparison matrix includes , Indicator Factors and Compared to the importance of what is obtained, The first factor affecting highway alignment i One factor; Based on the first comparison matrix, a first importance matrix is ​​constructed of the influence index layer relative to the optimal route layer O; the first importance matrix includes: ； Based on the first importance matrix, the largest eigenvalue and the corresponding first eigenvector are obtained, and normalized to obtain a normalized first eigenvector. Based on the size of the elements in the normalized first eigenvector, the importance ranking of each factor in the influence index layer is obtained; each element in the normalized first eigenvector is the weight of the influence index layer relative to each factor in the optimal route layer. Establish a second comparison matrix for the proposed route layer; the second comparison matrix includes , Indicator Factors With factors Compared to the importance of what is obtained, For the proposed first i 10 alternative routes; Based on the second comparison matrix, the proposed route layer is obtained relative to the first influencing index layer. i The second importance matrix of the factors; the second importance matrix includes: ； Based on the second importance matrix, the largest eigenvalues ​​and corresponding second eigenvectors are obtained and normalized to obtain normalized second eigenvectors. Each element in the normalized second eigenvector represents the weight of the proposed route layer relative to each factor in the optimal route layer. Based on the magnitude of the elements in the normalized second eigenvector, the comprehensive weight of each factor in the proposed route layer to the optimal route layer is obtained. The comprehensive weight includes: In the formula, n i Let n be the comprehensive weight of the i-th factor in the proposed route layer to the optimal route layer, and n be the total number of factors in the proposed route layer. i,j m is an element in the normalized second eigenvector. j The elements in the normalized first feature vector; Based on the comprehensive weights, the ranking of each candidate route in the proposed route layer is determined.

10. A highway route selection system based on integrated air-space-ground-indoor intelligent analysis, characterized in that, The method for highway route selection based on integrated air-space-ground-indoor intelligent analysis, as described in any one of claims 1-9, comprises: a preliminary zoning module, a first screening module, a second screening module, a preliminary design module, a construction module, an evaluation module, an optimization module, and an analysis module; wherein, The preliminary zoning module is used to perform preliminary zoning of the geological hazard susceptibility within the highway corridor based on the overall macro-route of the highway planned in the engineering feasibility study stage, and to perform preliminary marking based on historical geological hazard data to obtain a preliminary spatial distribution map of geological hazards along the highway. The first screening module is used to perform preliminary identification and screening of potential geological hazards in the corridor zone of the preliminary geological hazard spatial distribution map along the highway based on InSAR and remote sensing image interpretation technology, so as to obtain a large-scale geological hazard spatial distribution map. The second screening module is used to conduct a detailed investigation of the large-scale geological hazard spatial distribution map based on UAV-borne lidar and real-time dynamic positioning technology to obtain a small-scale geological hazard spatial distribution map. The preliminary design module is used to perform preliminary route design based on the small-scale geological hazard spatial distribution map to obtain the local route corridor range in the preliminary design stage; The construction module is used to verify the surrounding geological hazards within the local route corridor area based on comprehensive exploration methods, and to construct a geological condition information database; the comprehensive exploration methods include geological surveys, geophysical testing, and drilling verification; The assessment module is used to conduct a local geological risk assessment of geological hazard points within the local route corridor area based on the geological condition information database and using qualitative methods to obtain a risk assessment model; The optimization module is used to make a preliminary judgment on the risk sources and risk zones along the local route corridor based on the risk assessment model, and to adjust and optimize the routes within the local route corridor to obtain multiple routes to be planned. The judgment module is used to construct an intelligent expert judgment model using a combination of qualitative and quantitative methods, and to judge and compare the multiple routes to be planned based on the intelligent expert judgment model to obtain the target planned route.

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