Expressway site selection result evaluation method considering influence of low-altitude aircraft

Abstract

The invention discloses an expressway site selection result evaluation method considering the influence of a low-altitude aircraft, and relates to the field of site selection result evaluation, and the method comprises the steps: building a hierarchical structure evaluation model after generating an expressway site selection evaluation index system based on the flight influence factors of the low-altitude aircraft, obtaining a highway site selection result according to the hierarchical structure evaluation model; constructing a three-dimensional airspace reachability model by using historical flight data of the low-altitude aircraft, predicting a flight route of the low-altitude aircraft, and judging the service satisfaction degree of the highway site selection result to the low-altitude aircraft in combination with service requirements; and designing an emergency scene based on the service satisfaction degree, judging the strain capacity of an expressway site selection result, evaluating the reasonability of the expressway site selection result according to the strain capacity, and determining a final expressway site selection result by utilizing a reasonability evaluation result. According to the invention, the service of the aircraft in the site selection area of the expressway can be fully guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of site selection result evaluation, and more particularly, to a method for evaluating the site selection result of a highway considering the influence of low-altitude aircraft. Background Art

[0002] The low-altitude economy refers to the industrial aggregation that utilizes the low-altitude airspace (usually referring to the range from the ground to about 1000 meters in height) for various economic activities. With technological progress, the development of unmanned aerial vehicles and low-altitude aircraft, and the gradual liberalization of airspace management policies, the low-altitude economy has gradually become one of the emerging industrial fields globally. The core of the low-altitude economy is the efficient utilization of low-altitude airspace resources to promote economic development and innovation in social services.

[0003] The site selection of a highway considering the influence of low-altitude aircraft is a multi-dimensional comprehensive issue, involving multiple factors such as the flight safety, flight path, charging requirements, service guarantee, and emergency response ability of low-altitude aircraft (such as unmanned aerial vehicles, electric air taxis, etc.). With the gradual popularization of the application of low-altitude aircraft, especially in the fields of logistics transportation, air travel, agriculture, and emergency rescue, the site selection of a highway not only needs to consider traditional factors such as traffic flow, land use, and environmental protection, but also needs to consider the influence of low-altitude aircraft on the highway site selection.

[0004] However, the existing methods for highway site selection considering the influence of low-altitude aircraft lack a reasonable assessment of the magnitude of the influence of factors in the application process. Since different influencing factors have different magnitudes of influence on the site selection, evaluating whether the site selection is scientific and reasonable not only requires comprehensively considering each influencing factor, but also requires assigning reasonable weights to each influencing factor to obtain a systematic quantitative evaluation.

[0005] No effective solution has been proposed for the problems in the related art. Summary of the Invention

[0006] In view of the problems in the related art, the present invention proposes a method for evaluating the site selection result of a highway considering the influence of low-altitude aircraft to overcome the above-mentioned technical problems existing in the existing related art.

[0007] To this end, the specific technical solution adopted by the present invention is as follows:

[0008] A method for evaluating the site selection result of a highway considering the influence of low-altitude aircraft, comprising:

[0009] After generating a highway site selection evaluation index system based on the flight influencing factors of low-altitude aircraft, constructing a hierarchical structure evaluation model, and obtaining the highway site selection result according to the hierarchical structure evaluation model;

[0010] Construct a three-dimensional airspace accessibility model using the historical flight data of low-altitude aircraft, predict the flight routes of low-altitude aircraft, and combine service requirements to judge the service satisfaction of the highway location selection result for low-altitude aircraft;

[0011] Design an emergency scenario based on service satisfaction, judge the emergency response ability of the highway location selection result, and evaluate the rationality of the highway location selection result according to the emergency response ability. Use the rationality evaluation result to determine the final highway location selection result.

[0012] Preferably, after generating a highway location selection evaluation index system based on the influencing factors of low-altitude aircraft flight, construct a hierarchical structure evaluation model, and obtain the highway location selection result according to the hierarchical structure evaluation model, including:

[0013] Select the resource information at the highway location selection plan position and the influencing factors of low-altitude aircraft as evaluation indicators to construct a highway location selection evaluation index system;

[0014] Construct a hierarchical structure evaluation model with the highway location selection plan as the plan layer, evaluation indicators as the criterion layer, and the highway location selection result as the target layer according to the highway location selection evaluation index system;

[0015] Use the scale method theory to compare the importance of pairwise different evaluation indicators in the criterion layer of the hierarchical structure evaluation model, generate a judgment matrix according to the comparison result, and obtain the weight matrix of the evaluation indicators;

[0016] Determine the subjective and objective weights of the plan layer based on the weight matrix and entropy weight method, and use game theory to combine and weight the subjective and objective weights. Obtain the highway location selection result according to the weighting result.

[0017] Preferably, determine the subjective and objective weights of the plan layer based on the weight matrix and entropy weight method, and use game theory to combine and weight the subjective and objective weights. Obtain the highway location selection result according to the weighting result, including:

[0018] Verify the logical error of the judgment matrix according to the weight matrix of the evaluation indicators, determine the final weight matrix based on the verification result, use the final weight matrix to judge the composite weight of the plan layer, and use the composite weight as the subjective weight of the plan layer;

[0019] Construct an initial evaluation matrix according to the plan layer and evaluation indicators, and perform data normalization processing on the initial evaluation matrix. Calculate the ratio of the evaluation indicators based on the processing result;

[0020] Use the ratio result to calculate the entropy value and coefficient of variation of the plan layer, calculate the objective weight of the plan layer based on the coefficient of variation result, and combine the objective weight and subjective weight to construct a weight vector set;

[0021] Obtain the optimal weight vector of the weight vector set, generate the combined weight of the linear coefficient solution layer based on the optimal weight vector, sort the combined weights, and determine the highway site selection result according to the sorting result.

[0022] Preferably, use the historical flight data of low-altitude aircraft to construct a three-dimensional airspace accessibility model, predict the flight route of the low-altitude aircraft, and combine the service requirements to judge the service satisfaction of the highway site selection result for the low-altitude aircraft, including:

[0023] Collect historical flight data including the charging requirements, flight trajectories, flight speeds, and flight altitudes of low-altitude aircraft, and clean and remove abnormal data from the historical flight data;

[0024] Determine the three-dimensional airspace range, divide the three-dimensional airspace into several grids, define each grid to represent an accessible three-dimensional space unit, and model the flight capabilities of low-altitude aircraft within the three-dimensional space unit according to the flight trajectories, flight speeds, and flight altitudes;

[0025] Obtain the obstacle information within the highway site selection result area, model the obstacles within the three-dimensional space unit according to the obstacles, and combine the flight capability modeling results to obtain the three-dimensional airspace accessibility model;

[0026] Predict the flight route of the low-altitude aircraft based on the three-dimensional airspace accessibility model and the path planning algorithm, and combine the charging equipment location information within the highway site selection result area to obtain the charging capability of the low-altitude aircraft;

[0027] Compare the charging capability with the charging service requirements of the low-altitude aircraft, and judge the service satisfaction of the highway site selection result for the low-altitude aircraft according to the comparison result.

[0028] Preferably, predict the flight route of the low-altitude aircraft based on the three-dimensional airspace accessibility model and the path planning algorithm, and combine the charging equipment location information within the highway site selection result area to obtain the charging capability of the low-altitude aircraft, including:

[0029] Obtain the historical coordinate information of the dynamic obstacles within the three-dimensional space unit according to the three-dimensional airspace accessibility model, and perform dilation processing on the dynamic obstacles;

[0030] Use the dilated dynamic obstacles and the Lagrange interpolation method to generate a motion trajectory model, and obtain the position points of the dynamic obstacles within the highway site selection result area according to the motion trajectory model;

[0031] Combine the incremental path planning algorithm, the position points of the dynamic obstacles, and the flight requirements to predict the flight route of the low-altitude aircraft, and obtain the installation positions of the charging equipment within the highway site selection result area;

[0032] Analyze the distances between the route points corresponding to the flight route and the installation positions of the charging devices, and judge the compatibility of the freeway site selection result with the charging ability of low-altitude aircraft based on the distance information.

[0033] Preferably, a motion trajectory model is generated by using the dynamic obstacles after dilation processing and the Lagrange interpolation method. The position points of the dynamic obstacles within the freeway site selection result area obtained according to the motion trajectory model include:

[0034] Set the initial position points of the dynamic obstacles after dilation processing, construct a polynomial according to the initial position points by using the Lagrange interpolation method, and sample the states of the dynamic obstacles at any position points.

[0035] Analyze the successive positions of the dynamic obstacles during the movement process according to the polynomial, and obtain the motion trajectory prediction models of the dynamic obstacles in the transverse and longitudinal directions based on the position results.

[0036] Analyze the predicted positions of the dynamic obstacles at any moment by using the motion trajectory prediction model, analyze the subsequent running trajectories of the dynamic obstacles according to the predicted positions of the dynamic obstacles, and output the trajectory curves.

[0037] Map the trajectory curves into the three-dimensional space cells to obtain the position points of the dynamic obstacle trajectory curves within the freeway site selection result area.

[0038] Preferably, combining the incremental path planning algorithm, the position points of the dynamic obstacles and the flight requirements to predict the flight route of the low-altitude aircraft includes:

[0039] Define the starting point based on the flight requirements of the low-altitude aircraft, and use bitwise operation instructions to filter out the key points from the flight requirements, and add the key points to the open list of the incremental path planning algorithm.

[0040] Analyze the key point with the smallest value in the open list as the extended parent node, and check whether the paths from the key point and its extended parent node to the starting point intersect with the position points of the dynamic obstacles.

[0041] If they do not intersect, use the extended parent node as the flight path point of the low-altitude aircraft. If they intersect, delete the extended parent node and reselect a key point from the open list as the extended parent node.

[0042] Connect the finally obtained flight path points to obtain a flight control polygonal curve, and smooth the flight control polygonal curve based on the Bezier curve to generate the flight route of the low-altitude aircraft.

[0043] Preferably, design emergency scenarios based on service satisfaction, judge the emergency response ability of the highway site selection result, evaluate the rationality of the highway site selection result according to the emergency response ability, and determine the final highway site selection result using the rationality evaluation result, including:

[0044] Design disaster emergency scenarios generated within the highway site selection result area based on meteorological mutation setting rules, and define the operation status of charging equipment within the highway site selection result area according to the design result;

[0045] Evaluate the charging feasibility of low-altitude aircraft within the highway site selection result area based on the operation status of charging equipment and service satisfaction, and analyze the emergency response ability of charging equipment based on the charging feasibility;

[0046] Use the emergency response ability to judge the charging demand guarantee ability of low-altitude aircraft within the highway site selection result area, and evaluate the rationality of the highway site selection result according to the guarantee ability;

[0047] After the rationality result meets the preset requirements, use the weight correction technology to correct and feedback the highway site selection result, and determine the final highway site selection result according to the feedback result.

[0048] Preferably, use the weight correction technology to correct and feedback the highway site selection result, and determine the final highway site selection result including:

[0049] Randomly generate parameter combinations of influencing factors based on the highway site selection evaluation index system, calculate the scores of the site selection schemes for each group of influencing factor parameter combinations, and obtain the average comprehensive score according to the score results;

[0050] Combine the score results with the average comprehensive score to evaluate the score standard deviation, failure probability, and parameter sensitivity of the highway site selection result, and establish a correction trigger condition based on the failure probability and parameter sensitivity;

[0051] Based on the correction trigger condition and parameter sensitivity, adjust the weight values of the highway site selection evaluation index system proportionally, and re-determine the final highway site selection result according to the adjustment results.

[0052] Preferably, the calculation formula for the score of the site selection scheme is:

[0053] ;

[0054] ;

[0055] ;

[0056] In the formula, C (k) represents the score value of the k-th group of site selection schemes, D -(k)Denote the negative score of the k-th group of solutions, D +(k) Denote the positive score of the k-th group of solutions, ω j Denote the weight of the j-th index, Denote the normalized value of the k-th group of solutions on the j-th index, σ j Denote the historical standard deviation of the j-th index, Denote the positive ideal solution of the j-th index, Denote the negative ideal solution of the j-th index.

[0057] The beneficial effects of the present invention are as follows:

[0058] 1. By constructing a hierarchical structure evaluation model, the present invention can comprehensively evaluate multiple influencing factors, taking into account different flight influencing factors, not only providing a clear evaluation framework, but also ensuring that the evaluation process is scientific and orderly, avoiding missing key factors. At the same time, by constructing a model with historical flight data, it can more accurately simulate the flight path and flight requirements of low-altitude aircraft, and finally design different emergency scenario simulations and test the response ability of the selected site in case of emergencies, thereby helping to determine whether the selected site can continuously provide necessary services in various unexpected situations and ensuring the safety of low-altitude aircraft.

[0059] 2. By constructing a three-dimensional airspace accessibility model and a path planning algorithm, the present invention can help the aircraft select the best flight path, and at the same time ensure that the layout of the charging stations meets the charging requirements of the aircraft, thereby optimizing the execution efficiency of the flight mission. And by comprehensively analyzing the flight ability of the aircraft, the influence of obstacles and the layout of charging facilities, it ensures that the services of the aircraft in the highway selected site area are fully guaranteed, avoiding the failure of the aircraft mission caused by insufficient facilities or path problems.

[0060] 3. By simulating scenarios of sudden weather changes and other emergencies, the present invention accurately analyzes the charging requirements of the aircraft and the operating status of the charging equipment, and can ensure that the aircraft obtains timely and efficient charging services in the highway selected site area, improving the sustainability and reliability of the services. And by using the weight correction technology and feedback mechanism, it can ensure that the evaluation and correction process of the highway selected site result always maintains flexibility and adaptability, further improving the scientificity and feasibility of the selected site result. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0062] Figure 1 It is a flowchart of a method for evaluating the result of highway site selection considering the influence of low-altitude aircraft according to an embodiment of the present invention;

[0063] Figure 2 It is a schematic diagram of a hierarchical evaluation model of a method for evaluating the result of highway site selection considering the influence of low-altitude aircraft according to an embodiment of the present invention;

[0064] Figure 3 It is a flowchart of combination weighting based on game theory in a method for evaluating the result of highway site selection considering the influence of low-altitude aircraft according to an embodiment of the present invention. Specific embodiments

[0065] To further illustrate each embodiment, the present invention provides drawings. These drawings are part of the disclosure of the present invention, mainly used to illustrate the embodiments, and can be combined with the relevant descriptions in the specification to explain the operating principle of the embodiments. With reference to these contents, those of ordinary skill in the art should be able to understand other possible embodiments and the advantages of the present invention.

[0066] According to an embodiment of the present invention, a method for evaluating the result of highway site selection considering the influence of low-altitude aircraft is provided.

[0067] Now, the present invention will be further described in combination with the drawings and specific embodiments. As Figure 1 shown, the method for evaluating the result of highway site selection considering the influence of low-altitude aircraft according to an embodiment of the present invention includes:

[0068] Step S1, after generating a highway site selection evaluation index system based on the flight influence factors of low-altitude aircraft, constructing a hierarchical evaluation model, and obtaining the highway site selection result according to the hierarchical evaluation model.

[0069] In one embodiment, when generating a highway site selection evaluation index system based on the flight influence factors of low-altitude aircraft, constructing a hierarchical evaluation model, and obtaining the highway site selection result according to the hierarchical evaluation model, the resource information at the location of the highway site selection scheme and the influence factors of low-altitude aircraft can be selected as evaluation indexes to construct a highway site selection evaluation index system; a hierarchical evaluation model with the highway site selection scheme as the scheme layer, the evaluation indexes as the criterion layer, and the highway site selection result as the target layer is constructed according to the highway site selection evaluation index system; the scale method theory is used to compare the importance of two different evaluation indexes in the criterion layer of the hierarchical evaluation model, a judgment matrix is generated according to the comparison result, and the weight matrix of the evaluation indexes is obtained; the subjective and objective weights of the scheme layer are determined based on the weight matrix and the entropy weight method, and the subjective and objective weights are combined weighted using game theory, and the highway site selection result is obtained according to the weighted result.

[0070] In one embodiment, when determining the subjective and objective weights of the solution layer based on the weight matrix and the entropy weight method, and using game theory to combine and assign weights to the subjective and objective weights, and obtaining the highway site selection result according to the weighted result, the logical error of the judgment matrix can be verified according to the weight matrix of the evaluation index, and the final weight matrix can be determined based on the verification result. The synthetic weight of the solution layer is judged using the final weight matrix, and the synthetic weight is used as the subjective weight of the solution layer; an initial evaluation matrix is constructed according to the solution layer and the evaluation index, and data normalization processing is performed on the initial evaluation matrix, and the ratio of the evaluation index is calculated based on the processing result; the entropy value and the coefficient of variation of the solution layer are calculated using the ratio result, the objective weight of the solution layer is calculated based on the coefficient of variation result, and the objective weight and the subjective weight are combined to construct a weight vector set; the optimal weight vector of the weight vector set is obtained, the combined weight of the solution layer is solved by generating a linear coefficient based on the optimal weight vector, and the combined weight is sorted, and the highway site selection result is determined according to the sorting result.

[0071] It should be noted that in the process of determining the highway site selection result, the local reality can be combined, and influencing factors such as population size, traffic conditions, airspace resources, economic development, application scenarios, radiation range, and urban planning can be selected as evaluation indexes to construct a scientific, comprehensive, accurate, and effective evaluation index system for the site selection of low-altitude aircraft highway service stations.

[0072] As Figure 2 shown in Figure 3 Based on the obtained evaluation index system, a hierarchical evaluation model is constructed. The hierarchical model contains 3 levels, namely the target level (select a reasonable address), the criterion level (each influencing factor), and the solution level (the options to be selected). The target level is to select a reasonable construction address for the low-altitude aircraft highway service station, the criterion level is the influencing factors related to the site selection of the service station such as population size, traffic conditions, airspace resources, economic development, application scenarios, radiation range, and urban planning. In practical applications, reasonable adjustments can be made according to specific situations to ensure better compliance with the actual situation. The solution level is the construction addresses of the low-altitude aircraft service stations to be selected. The purpose of the hierarchical analysis is to select the most scientific and reasonable solution from them.

[0073] Applying the 1-9 scale method theory, the importance between two different elements in the criterion level of the hierarchical evaluation model is compared, and the comparison results are arranged to form a judgment matrix and sorted to obtain the matrix:

[0074] ;

[0075] The specific scale results are shown in Table 1:

[0076] Table 1: Scale Results

[0077] For each factor at the criterion level, namely population size, traffic conditions, airspace resources, economic development, application scenarios, radiation range, and urban planning, a 7×7 judgment matrix can be constructed according to the 1-9 scale method, as shown in Table 2:

[0078] Table 2: Judgment Matrix

[0079] Based on the constructed judgment matrix, solve the weights of each index to obtain the weight matrix, then calculate the maximum eigenvalue and the consistency index. Find the average random consistency index corresponding to the number of factors at the criterion level by looking up the table, and obtain the consistency ratio using the ratio of the consistency index to the average random consistency index. Based on this, judge whether there are logical errors in the constructed judgment matrix. If there are, make adjustments; if not, obtain the weights of each index, and calculate the combined weights of the alternative layer according to the weights of each index at the criterion level and perform ranking.

[0080] Construct an initial evaluation matrix according to the alternative solutions and evaluation indexes, and use the entropy weight method to determine the objective weights. Define x ij as the evaluation index of the j th index for the i th evaluation object (site selection plan), and obtain the initial evaluation matrix: X =( x ij ) m*n , (where m represents the number of evaluation objects, i = 1, 2,..., m ; n represents the number of evaluation indexes, j = 1, 2,..., n ) Since indexes of different natures will have a great impact on the results, the influence of dimensions should be removed during the calculation process, and the data should be normalized. The processing process is as follows:

[0081] For positive indexes:

[0082] ;

[0083] For negative indexes:

[0084] ;

[0085] Moderate indexes:

[0086] ;

[0087] In the formula, x best,jRepresents the optimal value of the moderation index. To ensure the effectiveness of the value, each normalized value is added with a valid value of 0.00000001.

[0088] Calculate the proportion P of each index ij :

[0089] ;

[0090] Calculate the entropy value e j :

[0091] ;

[0092] Calculate the coefficient of variation d j :

[0093] ;

[0094] Calculate the index weight w j :

[0095] ;

[0096] At the same time, apply game theory to combine and assign weights to the calculation results of subjective and objective weights. In the multi-level index evaluation, assume that g weight assignment methods are used to obtain g weight vectors, and thus a weight vector set can be constructed , j represents the j-th index, j = 1, 2,..., n. In the formula, u kj represents the j-level weight vector under the k-th scheme. Then, the linear combination of g weight vectors at each level is a possible set of weight values , where a k represents the linear combination coefficient, u k represents the comprehensive weight vector, and T represents the transpose.

[0097] Find the optimal weight vector by minimizing the deviation between u j and each u k , that is:

[0098] ;

[0099] Using the differentiability of the matrix, obtain the first-order optimal derivative:

[0100] ;

[0101] According to the above formula, a k can be obtained and normalized:

[0102] ;

[0103] Obtain the linear coefficient :

[0104] ;

[0105] Finally, the final combined weight is obtained as:

[0106] ;

[0107] After determining the combined weight vector of the indicators at the j-th layer, the weights of the indicators at the j-th layer can be superimposed to calculate the combined weight of the indicators at the (j - 1)-th layer, and the combined weights are sorted. According to the sorting results, the highway site selection result is determined.

[0108] Step S2: Use the historical flight data of low-altitude aircraft to construct a three-dimensional airspace accessibility model, predict the flight routes of low-altitude aircraft, and combine service requirements to judge the service satisfaction of the highway site selection result for low-altitude aircraft.

[0109] In one embodiment, when using the historical flight data of low-altitude aircraft to construct a three-dimensional airspace accessibility model, predict the flight routes of low-altitude aircraft, and combine service requirements to judge the service satisfaction of the highway site selection result for low-altitude aircraft, historical flight data including the charging requirements, flight trajectories, flight speeds, and flight altitudes of low-altitude aircraft can be collected, and the historical flight data is cleaned and abnormal data is removed; determine the three-dimensional airspace range, divide the three-dimensional airspace into several grids, define each grid to represent an accessible three-dimensional space unit, and model the flight capabilities of low-altitude aircraft within the three-dimensional space unit according to the flight trajectories, flight speeds, and flight altitudes; obtain the obstacle information within the highway site selection result area, model the obstacles within the three-dimensional space unit according to the obstacles, and combine the flight capability modeling results to obtain the three-dimensional airspace accessibility model; predict the flight routes of low-altitude aircraft based on the three-dimensional airspace accessibility model and path planning algorithm, and combine the location information of charging facilities within the highway site selection result area to obtain the charging capabilities of low-altitude aircraft; compare the charging capabilities with the charging service requirements of low-altitude aircraft, and judge the service satisfaction of the highway site selection result for low-altitude aircraft according to the comparison results.

[0110] It should be explained that historical flight data of low-altitude aircraft needs to be collected in the process of constructing the three-dimensional airspace accessibility model, and the data includes the following aspects:

[0111] Aircraft charging requirements: The charging demand of the aircraft during flight, including charging frequency, charging duration, etc.;

[0112] Flight trajectory: The actual flight route of the aircraft, which can be recorded through GPS positioning data, radar data, or sensors;

[0113] Flight speed: Record the speed of the aircraft at each time point during flight;

[0114] Flight altitude: Record the flight altitude of the aircraft at different time points.

[0115] Use statistical methods (such as mean, standard deviation, etc.) to identify and eliminate extreme outliers. For example, the speed or altitude of the aircraft cannot exceed a certain specific range. Data outside this range may be incorrect and need to be eliminated. At the same time, if some data points are missing, interpolation algorithms (such as linear interpolation, spline interpolation, etc.) can be used to fill in the missing data.

[0116] According to the actual application requirements and the flight capabilities of the aircraft, define the three-dimensional airspace range that a low-altitude aircraft can cover. For example, the spatial range of the airspace can be determined based on factors such as the maximum flight altitude, flight speed, and geographical location of the aircraft. Divide the determined three-dimensional airspace into several small spatial units. Usually, a three-dimensional grid is used to represent each spatial position in the airspace. The grid division can be carried out in the following ways:

[0117] (1) Regular grid division: Uniformly divide the three-dimensional airspace into several small cubes (for example, each grid is a small cube with equal length, width, and height);

[0118] (2) Adaptive grid division: According to the flight trajectory and flight requirements of the aircraft, select some areas for finer grid division and perform rough division on other areas, thereby improving the calculation efficiency and refining the modeling of the aircraft's activity area.

[0119] At the same time, during the process of modeling the flight capabilities of a low-altitude aircraft, it is necessary to model the flight capabilities of each grid based on data such as flight trajectory, speed, and altitude. The flight capability modeling includes the following aspects:

[0120] Flight speed of the aircraft: Calculate the maximum flight speed that the aircraft can reach in different grid cells; The flight speed is affected by various factors, such as aircraft type, meteorological conditions, etc.;

[0121] Flight altitude of the aircraft: Based on the flight historical data of the aircraft, establish the accessibility of the aircraft within different altitude ranges; Different altitudes correspond to different flight requirements, and the maximum flight altitude of the aircraft is also restricted by the flight path, obstacles, and flight environment;

[0122] Flight path modeling: Combine the flight trajectory data to establish the actual flight capabilities of the aircraft in three-dimensional space. These models will determine whether the aircraft is reachable within a certain grid based on factors such as time, position, speed, and the heading of the aircraft.

[0123] At this stage, it is necessary to obtain the obstacle information within the highway site selection result area. Obstacles usually include:

[0124] Natural obstacles: such as mountains, buildings, trees, etc., which will affect the flight path of low-altitude aircraft; man-made obstacles (dynamic obstacles).

[0125] Through remote sensing technology, geographic information system (GIS), and obstacle data from actual measurements (such as databases, map data, etc.), detailed information of obstacles is obtained and classified.

[0126] Based on the obtained obstacle information, obstacles in the three-dimensional airspace can be modeled. Specifically, based on information such as the coordinate position, size, and shape of the obstacles, the specific positions of the obstacles are located in the three-dimensional airspace grid. Obstacles not only occupy space on the two-dimensional plane but also affect the aircraft in the vertical direction (height). Therefore, it is necessary to evaluate the impact of obstacles in the three-dimensional airspace according to factors such as the height, extension range, and shape of the obstacles.

[0127] By combining the flight capabilities of the aircraft and the obstacle information, a three-dimensional airspace accessibility model can be constructed. The specific process is as follows:

[0128] In each grid, combine the flight capabilities of the aircraft and the obstacle model to determine whether the aircraft can successfully pass through the grid. If the flight capabilities (speed, height) of the aircraft cannot overcome the limitations of the obstacles, then the grid cannot be passed. For each grid cell, calculate the accessibility of the aircraft to generate an accessibility matrix or graph model representing the three-dimensional space area that the aircraft can access.

[0129] Combined with the charging requirements of the aircraft and the locations of charging facilities, further optimize the flight path of the aircraft. According to the distribution of charging facilities within the highway site selection area, determine whether the aircraft can obtain charging support during flight. Finally, based on the service facilities (such as charging stations, maintenance stations, etc.) within the highway site selection area, as well as the flight route and charging requirements of the aircraft, evaluate the service satisfaction of the highway site selection result for low-altitude aircraft. The following steps can be used:

[0130] Analyze whether the aircraft can reach the charging station and service facilities within a reasonable time and space range; evaluate whether the service facilities in the highway site selection area can meet the needs of the aircraft according to the charging requirements, flight time, speed, etc. of the aircraft; combine service accessibility and aircraft charging requirements to give a service satisfaction score, and judge whether the highway site selection result is reasonable and whether further optimization is required.

[0131] Through the above steps, the construction of a three-dimensional airspace accessibility model for low-altitude aircraft can be achieved. Combining factors such as historical flight data, flight capability modeling, and obstacle modeling, a comprehensive evaluation result is finally obtained to judge the service satisfaction of the highway site selection result for low-altitude aircraft.

[0132] In one embodiment, when predicting the flight route of a low-altitude aircraft based on a three-dimensional airspace accessibility model and a path planning algorithm, and combining the position information of charging devices within the highway site selection result area to obtain the charging capacity of the low-altitude aircraft, the historical coordinate information of dynamic obstacles within the three-dimensional space unit can be obtained according to the three-dimensional airspace accessibility model, and the dynamic obstacles can be subjected to dilation processing; a motion trajectory model is generated using the dilated dynamic obstacles and the Lagrange interpolation method, and the position points of the dynamic obstacles within the highway site selection result area are obtained according to the motion trajectory model; the incremental path planning algorithm, the position points of the dynamic obstacles, and the flight requirements are combined to predict the flight route of the low-altitude aircraft, and the installation positions of the charging devices within the highway site selection result area are obtained; the distances between the route points corresponding to the flight route and the installation positions of the charging devices are analyzed, and the compatibility of the highway site selection result with the charging capacity of the low-altitude aircraft is judged based on the distance information.

[0133] It should be explained that during the process of dilating the obstacles, dynamic obstacles are first defined. Dynamic obstacles generally refer to objects that move with time, such as other aircraft, meteorological factors (such as air currents, wind speeds), flight areas that the aircraft may avoid, etc. Historical coordinate information is collected through remote sensing, aircraft sensors (such as GPS, radar, lidar, etc.), and other dynamic monitoring technologies. For each dynamic obstacle, its positions at different time points are recorded, and its trajectory data is constructed. Through time-series data, the motion trajectories of the dynamic obstacles are recorded, and the data is complemented through interpolation or smoothing methods; the trajectory information of each dynamic obstacle will serve as the basis for subsequent path planning and obstacle dilation processing.

[0134] In the three-dimensional airspace, dynamic obstacles may affect the safe flight path of the aircraft. Therefore, during path planning, it is necessary to dilate the obstacles. Dilation means expanding the spatial range of the obstacles so that the dilated obstacles can more accurately simulate the obstacle avoidance requirements of the aircraft. The radius of dilation usually depends on the size of the aircraft (for example, the minimum safe flight distance of the aircraft) and the flight speed of the aircraft. If the speed of the aircraft is faster, the safe distance required for obstacle avoidance is greater, so the radius of dilation should also be increased accordingly.

[0135] Dynamic obstacles not only need to expand their current positions but also consider their possible future movement trajectories. The expansion should take into account the possible positions of the obstacles within a certain future time range. By predicting the dynamic obstacles (such as using Kalman filtering or motion models), predict the future movement of the obstacles and perform expansion processing. For three-dimensional airspace, the expansion is not limited to the horizontal plane but also needs to be carried out in the vertical direction. The height information of the obstacles will also be considered in the expansion process to ensure that the aircraft can safely pass above or below when avoiding the obstacles. In the expanded obstacle model, the aircraft needs to avoid the expanded obstacle area. If the expanded obstacles overlap or touch the flight path of the aircraft, the path planning algorithm will automatically adjust the flight route.

[0136] In one embodiment, when generating a motion trajectory model using the expanded dynamic obstacles and Lagrange interpolation method and obtaining the position points of the dynamic obstacles within the highway site selection result area according to the motion trajectory model, the initial position points of the expanded dynamic obstacles can be set. Based on the initial position points, polynomials are constructed using Lagrange interpolation method to sample the states of the dynamic obstacles at any position points; analyze the successive positions of the dynamic obstacles during movement according to the polynomials, and obtain the motion trajectory prediction models of the dynamic obstacles in the lateral and longitudinal directions based on the position results; use the motion trajectory prediction models to analyze the predicted positions of the dynamic obstacles at any moment, and analyze their subsequent operation trajectories according to the predicted positions of the dynamic obstacles, and output the trajectory curves; map the trajectory curves into the three-dimensional space cells to obtain the position points of the dynamic obstacle trajectory curves within the highway site selection result area.

[0137] In one embodiment, when combining the incremental path planning algorithm, the position points of the dynamic obstacles and the flight requirements to predict the flight route of a low-altitude aircraft, the starting point can be defined based on the flight requirements of the low-altitude aircraft, and bitwise operation instructions are used to filter out the key points from the flight requirements and add the key points to the open list of the incremental path planning algorithm; analyze the key point with the smallest value in the open list as the expanded parent node, and check whether the paths from the key point and its expanded parent node to the starting point intersect with the position points of the dynamic obstacles; if they do not intersect, take the expanded parent node as the flight path point of the low-altitude aircraft, if they intersect, delete the expanded parent node and re-select the key point from the open list as the expanded parent node; connect the finally obtained flight path points to obtain a flight control polygon curve, and perform smoothing processing on the flight control polygon curve based on the Bezier curve to generate the flight route of the low-altitude aircraft.

[0138] In one embodiment, when analyzing the distance between the corresponding route points of the flight route and the installation positions of the charging devices, and judging the matching degree of the highway site selection result to the charging ability of the low-altitude aircraft according to the distance information, in order to compare the relationship between the flight route points and the installation positions of the charging devices, a suitable distance calculation method needs to be defined. Common distance calculation methods include:

[0139] Two-dimensional Euclidean distance: If only considering the horizontal plane (longitude, latitude) of the flight route, the two-dimensional Euclidean distance can be used to calculate the horizontal distance between the flight route points and the charging stations;

[0140] Three-dimensional distance: If considering the height difference of the aircraft, the three-dimensional Euclidean distance can also be used to calculate the actual distance between the aircraft and the charging stations;

[0141] If the height difference between the charging facilities and the flight route points is not large, the two-dimensional distance calculation can be adopted. If the height difference is large, the three-dimensional distance is more accurate.

[0142] According to the flight trajectory of the aircraft, the distance between each route point and the charging device is calculated one by one. For each flight route point (assuming there are L route points), the distances are calculated separately with all charging facilities (assuming there are M charging stations). Calculate the distances from each flight route point to all charging facilities, and these distances can be stored as a matrix, where each row represents a flight route point and the columns represent the positions of the charging facilities.

[0143] Based on the above distance calculation results, it can be judged whether the aircraft can be charged smoothly, and then the matching degree of the highway site selection result to the charging ability of the aircraft can be evaluated. Set a maximum service distance threshold, that is, if the distance between the route point of the aircraft and the nearest charging facility is less than this threshold, it is considered that the service is reachable. This threshold can be set according to the charging requirements of the aircraft and the charging time limit of the aircraft: D ij ≤D max ,D max is the preset maximum service distance. If the distances between a certain flight route point and all charging facilities are greater than this threshold, it means that this flight route point cannot be charged smoothly in this area. Count all the route points in the flight route and calculate the proportion of them within the coverage of the charging facilities. If most flight route points are within the coverage of the charging facilities, it means that the matching degree of the highway site selection to the charging ability of the low-altitude aircraft is relatively high.

[0144] According to the service satisfaction of each flight route point, calculate the overall matching degree score. The weighted average method can be used to comprehensively consider the matching degrees of different route points:

[0145] ;

[0146] Wherein, G match represents the overall matching degree score, O a represents the importance weight of the a-th flight route point (which can be adjusted according to the length of the flight route, the flight requirements of the aircraft, etc.), and S a represents the service satisfaction degree of the a-th flight route point (whether charging can be completed within the coverage of the charging facilities).

[0147] Therefore, by calculating the distance between the flight route point and the charging facility, it can be determined whether the aircraft can smoothly obtain charging support, thereby evaluating the matching degree of the highway location selection for the charging ability of low-altitude aircraft.

[0148] To facilitate the understanding of the above technical solution of the present invention, the following will detail the operation method for judging the service satisfaction degree of low-altitude aircraft by the highway location selection result during the actual application of the present invention.

[0149] Step 1: Construct a three-dimensional airspace accessibility model;

[0150] Assume the following data is obtained based on historical data:

[0151] Aircraft charging requirement: The aircraft needs to be charged once every 50 kilometers of flight, the charging time is 15 minutes, and after each charge, the aircraft can fly for another 50 kilometers;

[0152] Flight trajectory: Set the historical trajectory of the aircraft as: [(r1, f1, z1), (r2, f2, z2), …, (R A , F A , Z A ), where each data point includes longitude (r), latitude (f), and altitude (z);

[0153] Example:

[0154] (r1 = 40.7128°N, f1 = 74.0060°W, z1 = 200m);

[0155] (r2 = 40.7148°N, f2 = 74.0080°W, z2 = 220m);

[0156] Flight speed:

[0157] The average flight speed of the aircraft is 60 km / h, the maximum flight speed is 100 km / h, and the minimum flight speed is 30 km / h;

[0158] Flight altitude:

[0159] Generally, the flight altitude is about 200 meters when flying in urban areas, and can reach 500 meters when flying in open areas.

[0160] Removal of abnormal aircraft altitude values: For example, if the flight altitude of a certain data point is 3000 meters, which is obviously an abnormal value and will be removed. At the same time, if there is missing position data in the flight trajectory, linear interpolation or spline interpolation is used to fill it.

[0161] Set the maximum flight altitude of the aircraft to 500 meters, the flight speed to 100 km / h, and the geographical location is distributed in a specific area (such as a 10-kilometer area along a certain highway). The airspace range is:

[0162] Longitude: 40.7°N to 40.8°N (within 10 kilometers); Latitude: 73.9°W to 74.0°W (within 10 kilometers); Altitude: 0 meters (ground) to 500 meters;

[0163] Divide this area into three-dimensional grids of 100 meters × 100 meters × 50 meters. This area is divided into a total of 10,000 grids. Assuming each grid is a small cube with a length, width, and height of 100 meters each, considering the flight requirements and obstacles of the aircraft, the flight ability modeling of the aircraft can be based on this grid unit.

[0164] Assume there is already the following flight ability model:

[0165] Maximum aircraft speed: 100 km / h; The maximum flight altitude of the aircraft is 500 meters, and the minimum flight altitude is 0 meters (ground).

[0166] Based on flight historical data, conduct flight ability modeling within each grid, using the following assumptions:

[0167] Flight speed modeling: Within these grids, the maximum flight speed of the aircraft is affected by weather and other aircraft and usually remains at 60 km / h. If it encounters obstacles (such as buildings), the flight speed will be reduced to 30 km / h.

[0168] Flight altitude modeling: According to historical data, the aircraft usually maintains an altitude of 200 meters to 300 meters and will reduce its altitude when flying in areas below 200 meters (such as urban areas).

[0169] Natural obstacles: Such as mountains, forests, terrain undulations, etc. Assume the height of these obstacles is from 10 meters to 200 meters; Man-made obstacles: Such as some dynamic obstacles like vehicles; In the three-dimensional airspace grid, model these obstacles to generate the spatial range occupied by the obstacles, thereby affecting the accessibility of the aircraft.

[0170] Combine flight ability and obstacle modeling to generate an accessibility matrix, indicating whether the aircraft can fly smoothly within each grid. Set the following parameters:

[0171] If the flight ability of the aircraft in a certain grid is insufficient to overcome the obstacles in that area, then the grid is inaccessible; an accessibility matrix is generated based on the comparison between the obstacles and the flight ability of the aircraft. For example, if there is a building 150 meters high in a certain grid and the maximum flight height of the aircraft is 200 meters, then the grid may be inaccessible.

[0172] Step 2: Service satisfaction analysis;

[0173] After obtaining the three-dimensional airspace accessibility model, path planning is carried out in combination with the location information of the charging facilities. Assuming that there is a charging station every 5 kilometers along the highway, and the coordinates of the charging stations are:

[0174] (40.7100°N, 74.0055°W); (40.7150°N, 74.0100°W); (40.7200°N, 74.0150°W);

[0175] Assume that the aircraft needs to be charged once every 50 kilometers of flight, the charging time is 15 minutes, and the charging requirement of the aircraft is to support 50 kilometers of flight per charge. According to the path planning algorithm (such as incremental path planning), the distance between the flight route points and the charging facilities can be calculated based on the flight path of the aircraft.

[0176] Assume that the route of the aircraft takes off from (40.7100°N, 74.0050°W) and flies 100 kilometers. The distances between some route points of the calculated flight route and the charging facilities are as follows:

[0177] The route point (40.7110°N, 74.0060°W) is 200 meters away from the charging station (40.7100°N, 74.0055°W);

[0178] The route point (40.7150°N, 74.0080°W) is 100 meters away from the charging station (40.7150°N, 74.0100°W);

[0179] If the maximum service distance of the charging station is set to 500 meters, then both of these route points are within the service range, indicating that the aircraft can be successfully charged at these two positions.

[0180] For most route points, the aircraft can successfully reach the charging facilities. Calculate that the charging station coverage ratio is 80% (80 route points are within the service range of the charging station). According to the charging demand and the coverage ratio, calculate the service satisfaction as 0.8. Then the matching degree of the highway location selection for the charging ability of low-altitude aircraft is 80%.

[0181] Step S3: Design emergency scenarios based on service satisfaction, judge the resilience of the highway site selection result, evaluate the rationality of the highway site selection result according to the resilience, and use the rationality evaluation result to determine the final highway site selection result.

[0182] In one embodiment, when designing emergency scenarios based on service satisfaction, judging the resilience of the highway site selection result, evaluating the rationality of the highway site selection result according to the resilience, and using the rationality evaluation result to determine the final highway site selection result, disaster emergency scenarios generated within the highway site selection result area can be designed based on meteorological mutation setting rules, and the operation status of charging facilities within the highway site selection result area can be defined according to the design result; the charging feasibility of low-altitude aircraft within the highway site selection result area can be evaluated according to the operation status of the charging facilities and service satisfaction, and the resilience of the charging facilities can be analyzed based on the charging feasibility; the resilience can be used to judge the charging demand guarantee ability of low-altitude aircraft within the highway site selection result area, and the rationality of the highway site selection result can be evaluated according to the guarantee ability; after the rationality result meets the preset requirements, the highway site selection result can be corrected and fed back using the weight correction technology, and the final highway site selection result can be determined according to the feedback result.

[0183] It should be explained that meteorological mutation refers to the situation where weather conditions change violently within a short period of time, such as extreme weather conditions like heavy rain, lightning, hail, strong wind, etc. These mutation events may affect the operation of low-altitude aircraft and the safety of charging facilities. Therefore, when designing disaster emergency scenarios, the types of meteorological mutation events are first determined, including:

[0184] Heavy rain: Heavy precipitation may cause waterlogging or affect the flight visibility.

[0185] Lightning: Lightning strikes may endanger the safety of aircraft and ground facilities.

[0186] Strong wind: High wind speeds may affect the stability of aircraft and the safety of charging facilities.

[0187] Hail: Severe hail weather may cause damage to aircraft and external components of charging facilities.

[0188] Low-temperature extreme weather: Low temperature may affect the battery performance of aircraft and even cause charging facility failures.

[0189] Real-time meteorological data is obtained through tools such as meteorological satellites and weather radars to monitor the trend of meteorological mutations. Based on historical meteorological data, the occurrence probabilities of various mutation events are determined, a probability distribution model of different mutation events is constructed, and different disaster emergency scenarios are designed according to the occurrence rules of meteorological mutations and the impacts of mutation events to evaluate the safety of the highway site selection area and charging facilities.

[0190] Set emergency scenarios, for example:

[0191] In Scenario 1, heavy rain + strong wind: During heavy rain accompanied by strong wind, the aircraft may face navigation difficulties, and charging facilities may be damaged due to water accumulation or wind collapse;

[0192] In Scenario 2, lightning + hail: The aircraft may be struck by lightning or hail, and charging facilities may stop working due to lightning interference or physical damage;

[0193] In Scenario 3, strong temperature drop: Extremely cold weather may cause the aircraft battery to be unable to charge effectively, and charging facility equipment may freeze or fail due to low temperature;

[0194] The intensity of each disaster scenario should be quantified, for example: the precipitation intensity of heavy rain (mm / h); the wind speed of strong wind (m / s); the frequency and intensity of lightning; the rapid temperature change range. These parameters can be set based on meteorological warning systems or historical data.

[0195] Determine the time duration of the disaster event, for example, heavy rain lasts for 2 hours, strong wind lasts for 1 hour, etc., and define the geographical scope affected by the disaster, which may be a certain area along the highway (for example, within a radius of 10 kilometers).

[0196] According to the scenarios of disaster emergencies, the operating status of charging equipment can be defined under different disasters. The operating status of charging equipment will be affected by factors such as disaster type, intensity, and duration. According to the disaster scenarios, set the rules for the change of charging equipment status:

[0197] Heavy rain trigger rule: If the heavy rain intensity is greater than 50 mm / h and the duration exceeds 30 minutes, enter the deceleration mode; if the heavy rain intensity is greater than 100 mm / h and the duration exceeds 1 hour, the charging facility enters the suspended service state.

[0198] Strong wind trigger rule: If the wind speed exceeds 20 m / s (72 km / h), the charging facility enters the deceleration mode; if the wind speed exceeds 30 m / s (108 km / h), the charging facility enters the suspended service or fault mode.

[0199] Lightning trigger rule: If lightning activities occur frequently in the area of the charging facility, the charging facility automatically switches to the deceleration mode; if the charging equipment is struck by lightning, it enters the fault mode.

[0200] Hail trigger rule: If the diameter of hail is greater than 1 cm, the charging facility will enter the deceleration mode; if the diameter of hail is greater than 2 cm or the hail lasts for more than 30 minutes, the charging facility enters the suspended service state.

[0201] Low-temperature trigger rule: If the temperature drops below 0°C, the charging facility enters the deceleration mode and the output power decreases; if the temperature drops below -10°C, the charging facility suspends service.

[0202] After the disaster event has passed, the charging facility will resume normal service. The trigger rules for resumption can include:

[0203] Temperature recovery: When the temperature recovers to above 10°C, the charging facility resumes normal service;

[0204] Wind speed recovery: When the wind speed returns to a safe level (below 20 m / s), normal service is resumed;

[0205] Rainfall reduction: After the heavy rain stops and the facility inspection is completed, normal charging resumes.

[0206] Through the above design steps, the impact of different meteorological sudden disasters on the operating status of charging equipment in the highway site selection area can be simulated, ensuring that the charging requirements of aircraft under adverse meteorological conditions are reasonably evaluated and managed.

[0207] In one embodiment, when evaluating the charging feasibility of low-altitude aircraft in the highway site selection result area based on the operating status of the charging equipment and the service satisfaction, and analyzing the response ability of the charging equipment based on the charging feasibility, it is necessary to clarify the charging requirements of the low-altitude aircraft, which usually include: charging demand, charging time requirement, charging frequency; according to the disaster scenario and the status of the charging equipment, the service satisfaction of the charging facility can be defined. The core of the service satisfaction evaluation is whether the availability of the charging equipment matches the charging requirements of the aircraft. The specific analysis is as follows:

[0208] Service accessibility of the charging equipment: Calculate the distance from the takeoff point of the aircraft to the charging facility, considering factors such as path planning, obstacles, and meteorology, and determine whether the aircraft can reach the charging facility within the specified time; Service capacity of the charging equipment: Consider the operating status of the charging facility under extreme weather and evaluate whether the charging equipment can meet the charging requirements of the aircraft.

[0209] Combining the above factors, conduct a charging feasibility assessment based on the operating status of the charging equipment and the service satisfaction: According to the charging requirements of the aircraft and the operating status of the charging equipment, calculate whether the aircraft can complete charging on time in the selected area. If the service satisfaction of the charging facility is high (for example, the charging facility can provide charging services under normal conditions), the charging feasibility is high. If the charging facility is in a failure mode or suspended service due to extreme weather or other factors, the charging feasibility is low, and it is necessary to evaluate whether additional charging facilities are needed or the flight path needs to be adjusted.

[0210] The resilience of a charging device refers to whether the charging facility can resume or maintain its operation through certain measures in the face of emergencies (such as meteorological changes, equipment failures, etc.). The resilience of the charging device includes the following aspects:

[0211] Fault tolerance: Whether the charging facility has an automatic recovery function, such as whether it can automatically repair or switch to a backup system in the event of equipment failure or external disasters; Disaster adaptability: The adaptability of the charging device under extreme meteorological conditions, for example, whether it can prevent damage to the device caused by heavy rain, lightning, strong winds, etc.; Output power regulation ability: Whether the charging facility can adjust the output power under extreme weather or excessive load to ensure the continuity of the charging function, that is, whether it can maintain a certain charging capacity in the face of meteorological changes (such as storms, strong winds, etc.).

[0212] Finally, by combining the charging feasibility and the resilience of the charging device, comprehensively evaluate whether the charging facility can provide stable charging services in different disaster scenarios: High charging feasibility and high resilience: The charging facility can maintain normal services in extreme weather and emergencies, and the charging feasibility is relatively high. Low charging feasibility and low resilience: The charging facility cannot maintain the charging service during disasters, and the charging feasibility is relatively low. It is necessary to consider improving the facility or adding backup charging stations.

[0213] Through this comprehensive analysis, the highway location selection plan can be further optimized to ensure that low-altitude aircraft can successfully complete the charging task under various meteorological conditions, and improve the reliability and safety of the system.

[0214] It should be explained that when evaluating the rationality of the highway location selection result, according to the charging requirements of the aircraft and the resilience of the charging facility, evaluate whether the charging facility can meet the charging needs of the aircraft in different environments. The specific steps are as follows:

[0215] Based on the aforementioned resilience, evaluate whether the charging facility can continuously provide charging for low-altitude aircraft in bad weather (such as heavy rain, strong wind, lightning, extremely cold weather, etc.), whether it can quickly recover when the charging facility is damaged, and whether it can provide charging services in a short time to prevent the aircraft from being unable to continue flying due to lack of charging.

[0216] Evaluate the ability of the charging facility to meet the charging needs of the aircraft: The availability of the charging facility in normal and extreme weather conditions, whether there are long-term service interruptions; Consider the power regulation ability of the charging device in disasters or emergencies, whether it can provide sufficient charging time in a timely manner to meet the endurance requirements of the aircraft.

[0217] Analyze whether the charging facilities cover the main flight paths of the aircraft, especially within the selected highway site area, and whether it can ensure that the aircraft can find a charging station in time to replenish power during flight. According to the charging requirements of the aircraft, judge whether the distribution of charging stations is reasonable. If the density of charging stations is low, it may affect the charging feasibility of the aircraft.

[0218] Evaluate the matching degree according to the charging requirements of low-altitude aircraft and the configuration of charging facilities within the selected area:

[0219] If the charging stations cover sufficient charging requirements within the flight range of the aircraft and can continuously provide charging services for the aircraft in bad weather, the site selection is considered reasonable; if the distribution of charging facilities cannot effectively cover the flight route of the aircraft, or the charging facilities cannot work properly in extreme weather, the site selection is considered unreasonable.

[0220] At the same time, evaluate whether the charging facilities within the selected highway site area can maintain charging services during sudden disasters. For example, when sudden events such as heavy rain and lightning occur, whether the charging facilities can continue to provide charging services. If the charging facilities encounter sudden events (such as lightning and strong winds), whether the system recovery time is fast enough and can resume charging services within a reasonable time to avoid affecting the aircraft.

[0221] Furthermore, the deployment and management of charging facilities can be optimized to ensure that the charging requirements of low-altitude aircraft within the selected highway site area can be reliably guaranteed.

[0222] In one embodiment, when using the weight correction technology to correct and feedback the highway site selection result and determining the final highway site selection result according to the feedback result, the influencing factor parameter combinations can be randomly generated based on the highway site selection evaluation index system, and the site selection plan scores of each group of influencing factor parameter combinations can be calculated. The comprehensive score mean value can be obtained according to the score results; the score results and the comprehensive score mean value are combined to evaluate the score standard deviation, failure probability and parameter sensitivity of the highway site selection result, and the correction trigger condition is established based on the failure probability and parameter sensitivity; the weight values of the highway site selection evaluation index system are adjusted proportionally according to the correction trigger condition and parameter sensitivity, and the final highway site selection result is re-determined according to the adjustment result.

[0223] It should be noted that during the process of simulating and evaluating the site selection results and feedback for weight correction, for the influencing factor indicators such as population scale (P), traffic conditions (T), airspace resources (A), economic development (E), application scenarios (S), radiation range (R), and urban planning (U), N = 10000 (determined according to actual needs) groups of parameter combinations are randomly generated to ensure uniform coverage of each parameter dimension, X(k)=[P(k),T(k),A(k),E(k),S(k),R(k),U(k)], k = 1, 2,......N; k represents the k-th group of site selection schemes randomly generated.

[0224] Calculate the score of each group of parameters:

[0225] ;

[0226] ;

[0227] ;

[0228] In the formula, C (k) represents the score value of the k-th group of site selection schemes, D -(k) represents the negative score of the k-th group of schemes, D +(k) represents the positive score of the k-th group of schemes, ω j represents the weight of the j-th index, represents the standardized value of the k-th group of schemes on the j-th index, σ j represents the historical standard deviation of the j-th index, represents the positive ideal solution of the j-th index, represents the negative ideal solution of the j-th index.

[0229] Quantitative analysis of site selection robustness:

[0230] (1) The key evaluation indicators are shown in Table 3:

[0231] Table 3: Key evaluation indicators

[0232] At the same time, based on the weight correction method of the evaluation results, specifically:

[0233] (1) When any of the following conditions is met, weight correction is initiated. The specific correction trigger conditions are:

[0234] ;

[0235] (2) Weight correction:

[0236] According to the sensitivity analysis results, adjust the weights proportionally:

[0237] ;

[0238] where η represents a constant, generally equal to 0.05, represents the partial differential symbol.

[0239] The weight update result is:

[0240] ;

[0241] represents the historical weight;

[0242] According to actual needs, set the constraint conditions:

[0243] The single-index weight range can be the minimum weight w min = 0.1, the maximum weight w max = 0.3, and the total weight sum is always 1:

[0244] ;

[0245] Therefore, using the weight correction technology and feedback mechanism can ensure that during the evaluation and correction process of the highway site selection results, flexibility and adaptability are always maintained, further improving the scientificity and feasibility of the site selection results.

[0246] In summary, by means of the above technical solutions of the present invention, the present invention can comprehensively evaluate multiple influencing factors by constructing a hierarchical structure evaluation model, taking into account different flight influencing factors, not only providing a clear evaluation framework, but also ensuring that the evaluation process is scientific and orderly, avoiding missing key factors. At the same time, by constructing a model with historical flight data, it can more accurately simulate the flight path and flight requirements of low-altitude aircraft. Finally, different emergency scenarios are designed to simulate and test the emergency response ability of the site selection result in case of emergencies, which helps to judge whether the site selection can continuously provide necessary services in various unexpected situations and ensure the safety of low-altitude aircraft. By constructing a three-dimensional airspace accessibility model and a path planning algorithm, the present invention can help the aircraft select the best flight path and ensure that the layout of the charging stations meets the charging requirements of the aircraft, thereby optimizing the execution efficiency of the flight mission. And by comprehensively analyzing the flight ability of the aircraft, the influence of obstacles and the layout of charging facilities, it ensures that the services of the aircraft in the highway site selection area are fully guaranteed, avoiding the failure of the aircraft mission caused by insufficient facilities or path problems. By simulating scenarios of sudden weather changes and other emergencies, the present invention accurately analyzes the charging requirements of the aircraft and the operation status of charging equipment, which can ensure that the aircraft can obtain timely and efficient charging services in the highway site selection area, improve the sustainability and reliability of the services. And by using the weight correction technology and feedback mechanism, it can ensure that flexibility and adaptability are always maintained in the evaluation and correction process of the highway site selection result, further improving the scientificity and feasibility of the site selection result.

[0247] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An evaluation method for the location selection results of expressways considering the influence of low-altitude aircraft, characterized in that Including: After generating a highway site selection evaluation index system based on the flight influencing factors of low-altitude aircraft, constructing a hierarchical structure evaluation model, and obtaining the highway site selection result according to the hierarchical structure evaluation model; Using the historical flight data of low-altitude aircraft to construct a three-dimensional airspace accessibility model, predicting the flight route of low-altitude aircraft, and judging the service satisfaction of the highway site selection result for low-altitude aircraft in combination with service requirements; Designing an emergency scenario based on service satisfaction, judging the emergency response ability of the highway site selection result, and evaluating the rationality of the highway site selection result according to the emergency response ability, and determining the final highway site selection result using the rationality evaluation result.

2. The evaluation method for the highway site selection result considering the influence of low-altitude aircraft according to claim 1, wherein The step of obtaining the highway site selection result after generating a highway site selection evaluation index system based on the flight influencing factors of low-altitude aircraft, constructing a hierarchical structure evaluation model, and according to the hierarchical structure evaluation model includes: Selecting the resource information at the highway site selection scheme location and the influencing factors of low-altitude aircraft as evaluation indexes to construct a highway site selection evaluation index system; Constructing a hierarchical structure evaluation model with the highway site selection scheme as the scheme layer, the evaluation indexes as the criterion layer, and the highway site selection result as the target layer according to the highway site selection evaluation index system; Using the scale method theory to compare the importance of pairwise different evaluation indexes in the criterion layer of the hierarchical structure evaluation model, generating a judgment matrix according to the comparison result, and obtaining the weight matrix of the evaluation indexes; Determining the subjective and objective weights of the scheme layer based on the weight matrix and the entropy weight method, and using game theory to perform combined weighting on the subjective and objective weights, and obtaining the highway site selection result according to the weighting result.

3. The freeway site selection result evaluation method considering the influence of low-altitude aircraft according to claim 2, wherein The step of determining the subjective and objective weights of the scheme layer based on the weight matrix and the entropy weight method, and using game theory to perform combined weighting on the subjective and objective weights, and obtaining the highway site selection result according to the weighting result includes: Verifying the logical error of the judgment matrix according to the weight matrix of the evaluation indexes, determining the final weight matrix based on the verification result, judging the combined weight of the scheme layer using the final weight matrix, and taking the combined weight as the subjective weight of the scheme layer; Constructing an initial evaluation matrix according to the scheme layer and the evaluation indexes, performing data normalization processing on the initial evaluation matrix, and calculating the proportion of the evaluation indexes based on the processing result; Calculating the entropy value and coefficient of variation of the scheme layer using the proportion result, calculating the objective weight of the scheme layer based on the coefficient of variation result, and combining the objective weight and the subjective weight to construct a weight vector set; Obtaining the optimal weight vector of the weight vector set, generating a linear coefficient to solve the combined weight of the scheme layer based on the optimal weight vector, sorting the combined weights, and determining the highway site selection result according to the sorting result.

4. A method for evaluating the result of highway site selection considering the influence of low-altitude aircraft according to claim 1, characterized in that, The step of using the historical flight data of low-altitude aircraft to construct a three-dimensional airspace accessibility model, predicting the flight route of low-altitude aircraft, and judging the service satisfaction of the highway site selection result for low-altitude aircraft in combination with service requirements includes: Collecting historical flight data including the charging requirements, flight trajectories, flight speeds, and flight altitudes of low-altitude aircraft, and performing cleaning and abnormal data removal processing on the historical flight data; Determine the three-dimensional airspace range, divide the three-dimensional airspace into several grids, define each grid to represent an accessible three-dimensional space unit, and model the flight ability of low-altitude aircraft within the three-dimensional space unit according to the flight trajectory, flight speed, and flight altitude; Obtain the obstacle information within the highway site selection result area, model the obstacles within the three-dimensional space unit according to the obstacles, and combine the flight ability modeling results to obtain the three-dimensional airspace accessibility model; Predict the flight route of the low-altitude aircraft based on the three-dimensional airspace accessibility model and the path planning algorithm, and combine the charging equipment location information within the highway site selection result area to obtain the charging ability of the low-altitude aircraft; Compare the charging ability with the charging service requirements of the low-altitude aircraft, and judge the service satisfaction of the highway site selection result for the low-altitude aircraft according to the comparison result.

5. A method for evaluating the result of highway site selection considering the influence of low-altitude aircraft according to claim 4, characterized in that The predicting the flight route of the low-altitude aircraft based on the three-dimensional airspace accessibility model and the path planning algorithm, and combining the charging equipment location information within the highway site selection result area to obtain the charging ability of the low-altitude aircraft includes: Obtain the historical coordinate information of the dynamic obstacles within the three-dimensional space unit according to the three-dimensional airspace accessibility model, and perform dilation processing on the dynamic obstacles; Use the dilated dynamic obstacles and the Lagrange interpolation method to generate a motion trajectory model, and obtain the position points of the dynamic obstacles within the highway site selection result area according to the motion trajectory model; Combine the incremental path planning algorithm, the position points of the dynamic obstacles, and the flight requirements to predict the flight route of the low-altitude aircraft, and obtain the installation positions of the charging equipment within the highway site selection result area; Analyze the distance between the route points corresponding to the flight route and the installation positions of the charging equipment, and judge the matching degree of the highway site selection result for the charging ability of the low-altitude aircraft according to the distance information.

6. The freeway site selection result evaluation method considering the influence of low-altitude aircraft according to claim 5, characterized in that The using the dilated dynamic obstacles and the Lagrange interpolation method to generate a motion trajectory model, and obtaining the position points of the dynamic obstacles within the highway site selection result area according to the motion trajectory model includes: Set the initial position points of the dilated dynamic obstacles, construct a polynomial according to the initial position points using the Lagrange interpolation method, and sample the state of the dynamic obstacles at any position point; Analyze the successive positions of the dynamic obstacles during the movement process according to the polynomial, and obtain the motion trajectory prediction model of the dynamic obstacles in the horizontal and vertical directions based on the position results; Use the motion trajectory prediction model to analyze the predicted position of the dynamic obstacles at any moment, and analyze the subsequent running trajectory of the dynamic obstacles according to the predicted position of the dynamic obstacles, and output the trajectory curve; Map the trajectory curve into the three-dimensional space unit, and obtain the position points of the dynamic obstacle trajectory curve within the highway site selection result area.

7. A method for evaluating the result of highway site selection considering the influence of low-altitude aircraft according to claim 6, characterized in that, The combining the incremental path planning algorithm, the position points of the dynamic obstacles, and the flight requirements to predict the flight route of the low-altitude aircraft includes: Define the starting point based on the flight requirements of the low-altitude aircraft, and use bitwise operation instructions to select the key points from the flight requirements, and add the key points to the open list of the incremental path planning algorithm; Analyze the key point with the minimum value in the open list as the expanded parent node, and check whether the paths from the key point and its expanded parent node to the starting point intersect with the position points of the dynamic obstacles; If they do not intersect, take the expanded parent node as the flight path point of the low-altitude aircraft. If they intersect, delete the expanded parent node and re-select a key point from the open list as the expanded parent node; Connect the finally obtained flight path points to obtain a flight control polygonal curve, and smooth the flight control polygonal curve based on the Bezier curve to generate the flight route of the low-altitude aircraft.

8. A method for evaluating the result of selecting a highway location considering the influence of low-altitude aircraft, as claimed in claim 1, wherein The method of designing an emergency event scenario based on service satisfaction, judging the emergency response ability of the highway site selection result, and evaluating the rationality of the highway site selection result according to the emergency response ability, and determining the final highway site selection result using the rationality evaluation result includes: Design a disaster emergency event scenario generated in the highway site selection result area based on the rules of meteorological mutation, and define the operation status of the charging equipment in the highway site selection result area according to the design result; Evaluate the charging feasibility of the low-altitude aircraft in the highway site selection result area according to the operation status of the charging equipment and service satisfaction, and analyze the emergency response ability of the charging equipment based on the charging feasibility; Use the emergency response ability to judge the charging demand guarantee ability of the low-altitude aircraft in the highway site selection result area, and evaluate the rationality of the highway site selection result according to the guarantee ability; After the rationality result meets the preset requirements, use the weight correction technology to correct and feedback the highway site selection result, and determine the final highway site selection result according to the feedback result.

9. The evaluation method for the highway site selection result considering the influence of low-altitude aircraft according to claim 8, wherein, The method of using the weight correction technology to correct and feedback the highway site selection result, and determining the final highway site selection result according to the feedback result includes: Randomly generate a combination of influence factor parameters based on the highway site selection evaluation index system, calculate the score of the site selection scheme for each group of influence factor parameter combinations, and obtain the average comprehensive score according to the score result; Combine the score result with the average comprehensive score to evaluate the score standard deviation, failure probability and parameter sensitivity of the highway site selection result, and establish a correction trigger condition based on the failure probability and parameter sensitivity; Adjust the weight value of the highway site selection evaluation index system proportionally based on the correction trigger condition and parameter sensitivity, and re-determine the final highway site selection result according to the adjustment result.

10. The evaluation method for the highway site selection result considering the influence of low-altitude aircraft according to claim 9, characterized in that The calculation formula for the score of the site selection scheme is: ； ； ； Where C (k) represents the score value of the k-th group of site selection schemes, D -(k) represents the negative score of the k-th group of schemes, D +(k) represents the positive score of the k-th group of schemes, ω j represents the weight of the j-th indicator, represents the standardized value of the k-th group of schemes on the j-th indicator, σ j represents the historical standard deviation of the j-th indicator, represents the positive ideal solution of the j-th indicator, represents the negative ideal solution of the j-th indicator.

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