Highway site selection result evaluation method considering influence of low-altitude aircrafts

Abstract

The application discloses a kind of expressway site selection result evaluation method considering low altitude aircraft influence, it is related to site selection result evaluation field, including: after generating expressway site selection evaluation index system based on low altitude aircraft flight influence factor, construction hierarchical structure evaluation model is obtained expressway site selection result according to hierarchical structure evaluation model;Three-dimensional airspace accessibility model is constructed using low altitude aircraft historical flight data, the flight route of low altitude aircraft is predicted, and the service satisfaction degree of low altitude aircraft is judged in combination with service requirement to expressway site selection result;Based on service satisfaction degree design emergency scenario, judge the strain capacity of expressway site selection result, and according to the rationality of strain capacity evaluation expressway site selection result, using rationality evaluation result determines the final expressway site selection result.The application can ensure that the service of aircraft in expressway site selection area is fully guaranteed.

Description

Technical Field

[0001] This invention relates to the field of site selection result evaluation, and more specifically, to a method for evaluating highway site selection results considering the influence of low-altitude aircraft. Background Technology

[0002] The low-altitude economy refers to a collection of industries that utilize low-altitude airspace (usually the area between the ground and approximately 1,000 meters in altitude) for various economic activities. With technological advancements, the development of drones and low-altitude aircraft, and the gradual liberalization of airspace management policies, the low-altitude economy has gradually become one of the emerging industrial sectors 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] Highway site selection considering the impact of low-altitude aircraft is a multi-dimensional and comprehensive issue, involving multiple factors such as the flight safety, flight path, charging needs, service support, and emergency response capabilities of low-altitude aircraft (such as drones and electric air taxis). With the increasing popularity of low-altitude aircraft applications, especially in logistics, air travel, agriculture, and emergency rescue, highway site selection must not only consider traditional factors such as traffic flow, land use, and environmental protection, but also the impact of low-altitude aircraft on highway site selection.

[0004] However, existing highway site selection methods that consider the impact of low-altitude aircraft lack a reasonable assessment of the magnitude of the influencing factors during application. Since different influencing factors have different effects on site selection, assessing whether the site selection is scientific and reasonable requires not only a comprehensive consideration of each influencing factor, but also assigning reasonable weights to each influencing factor, thereby obtaining a systematic quantitative evaluation.

[0005] No effective solutions have yet been proposed to address the problems in the relevant technologies. Summary of the Invention

[0006] In response to the problems in related technologies, this invention proposes a method for evaluating highway site selection results that takes into account the impact of low-altitude aircraft, so as to overcome the aforementioned technical problems existing in the existing related technologies.

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

[0008] A method for evaluating highway site selection results considering the impact of low-altitude aircraft includes:

[0009] After generating an evaluation index system for highway site selection based on the factors affecting low-altitude aircraft flight, a hierarchical evaluation model is constructed, and highway site selection results are obtained based on the hierarchical evaluation model.

[0010] A three-dimensional airspace accessibility model is constructed using historical flight data of low-altitude aircraft to predict the flight path of low-altitude aircraft, and the service satisfaction of highway site selection results with low-altitude aircraft is judged in combination with service requirements.

[0011] Based on service satisfaction, design emergency scenarios, assess the resilience of highway site selection results, evaluate the rationality of highway site selection results based on resilience, and use the rationality evaluation results to determine the final highway site selection results.

[0012] Preferably, after generating an evaluation index system for highway site selection based on the influencing factors of low-altitude aircraft flight, a hierarchical evaluation model is constructed, and the highway site selection results are obtained based on the hierarchical evaluation model, including:

[0013] Resource information at the location of the highway site selection scheme and the influencing factors of low-altitude aircraft are selected as evaluation indicators to construct a highway site selection evaluation index system.

[0014] Based on the highway site selection evaluation index system, a hierarchical evaluation model is constructed, with highway site selection schemes as the scheme layer, evaluation indicators as the criterion layer, and highway site selection results as the target layer.

[0015] The importance of each pair of different evaluation indicators in the criterion layer of the hierarchical evaluation model is compared using scaling theory. A judgment matrix is ​​generated based on the comparison results, and the weight matrix of the evaluation indicators is obtained.

[0016] 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 and weighted using game theory. The highway site selection results are obtained based on the weighting results.

[0017] Preferably, the subjective and objective weights of the scheme layer are determined based on the weight matrix and the entropy weight method, and game theory is used to combine and assign weights to the subjective and objective weights. The highway site selection results are obtained based on the weighting results, including:

[0018] The logical errors in the judgment matrix are verified based on the weight matrix of the evaluation index. The final weight matrix is ​​determined based on the verification results. The final weight matrix is ​​used to determine the composite weight of the scheme layer, and the composite weight is used as the subjective weight of the scheme layer.

[0019] An initial evaluation matrix is ​​constructed based on the scheme layer and evaluation indicators, and data normalization is performed on the initial evaluation matrix. The proportion of the evaluation indicators is calculated based on the processing results.

[0020] The entropy and coefficient of variation of the scheme layer are calculated using the proportional results. The objective weights of the scheme layer are calculated based on the coefficient of variation results. The objective weights and subjective weights are combined to construct a weight vector set.

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

[0022] Preferably, a three-dimensional airspace accessibility model is constructed using historical flight data of low-altitude aircraft to predict the flight path of low-altitude aircraft, and the service satisfaction of highway site selection results with low-altitude aircraft is determined in conjunction with service requirements, including:

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

[0024] The three-dimensional airspace is defined and divided into several grids. Each grid represents a reachable three-dimensional spatial unit. The flight capability of low-altitude aircraft is modeled within the three-dimensional spatial unit based on the flight trajectory, flight speed and flight altitude.

[0025] Obtain obstacle information within the highway site selection area, perform obstacle modeling within three-dimensional spatial units, and combine the flight capability modeling results to obtain a three-dimensional airspace accessibility model;

[0026] The flight path of low-altitude aircraft is predicted based on a three-dimensional airspace accessibility model and path planning algorithm, and the charging capacity of low-altitude aircraft is obtained by combining the location information of charging equipment in the area of ​​highway site selection results.

[0027] The charging capacity is compared with the charging service requirements of low-altitude aircraft, and the service satisfaction of the highway site selection results with low-altitude aircraft is judged based on the comparison results.

[0028] Preferably, the flight path of the low-altitude aircraft is predicted based on a three-dimensional airspace accessibility model and path planning algorithm, and the charging capacity of the low-altitude aircraft is obtained by combining the location information of charging equipment in the area of ​​highway site selection results.

[0029] The historical coordinate information of dynamic obstacles in three-dimensional spatial units is obtained based on the three-dimensional spatial accessibility model, and the dynamic obstacles are then expanded.

[0030] A motion trajectory model is generated using the dilated dynamic obstacle and the Lagrange interpolation method. The location points of the dynamic obstacle within the highway site selection result area are obtained based on the motion trajectory model.

[0031] The incremental path planning algorithm, the location of dynamic obstacles, and flight requirements are combined to predict the flight path of low-altitude aircraft and obtain the installation location of charging equipment in the area of ​​highway site selection results.

[0032] Analyze the distance between the route points corresponding to the flight path and the installation location of the charging equipment, and judge the suitability of the highway site selection results for the charging capacity of the low-altitude aircraft based on the distance information.

[0033] Preferably, a motion trajectory model is generated using the dilated dynamic obstacle and Lagrange interpolation method. The location points of the dynamic obstacle within the highway site selection area are obtained based on the motion trajectory model, including:

[0034] Set the initial position of the dynamic obstacle after the dilation process, and construct a polynomial based on the initial position using the Lagrange interpolation method to sample the state of the dynamic obstacle at any position.

[0035] Based on the polynomial analysis of the sequential positions of dynamic obstacles during their movement, a trajectory prediction model for the dynamic obstacles in the lateral and longitudinal directions is obtained based on the position results.

[0036] The motion trajectory prediction model is used to analyze the predicted position of dynamic obstacles at any time, and the subsequent trajectory of the dynamic obstacles is analyzed based on the predicted position of the dynamic obstacles, and the trajectory curve is output.

[0037] The trajectory curve is mapped onto a three-dimensional spatial unit to obtain the location point of the dynamic obstacle trajectory curve within the highway site selection result area.

[0038] Preferably, the method of combining incremental path planning algorithms, the location of dynamic obstacles, and flight requirements to predict the flight path of low-altitude aircraft includes:

[0039] The starting point is defined based on the flight requirements of the low-altitude aircraft, and key points are selected from the flight requirements using bitwise operation instructions and added to the open list of the incremental path planning algorithm.

[0040] Analyze the keypoint with the lowest value in the open list, use it as an extended parent node, and check whether the path from the keypoint and its extended parent node to the starting point intersects with the location point of the dynamic obstacle.

[0041] If they do not intersect, the extended parent node will be used as the flight path point of the low-altitude aircraft. If they intersect, the extended parent node will be deleted, and a new key point will be selected from the open list as the extended parent node.

[0042] Connect the final flight path points to obtain the flight control polygon curve, and smooth the flight control polygon curve based on the Bézier curve to generate the flight path of the low-altitude aircraft.

[0043] Preferably, based on service satisfaction, emergency scenarios are designed to assess the resilience of the highway site selection results, and the rationality of the highway site selection results is evaluated based on the resilience. The final highway site selection results are then determined using the rationality evaluation results, including:

[0044] Based on the rules for setting meteorological changes, a disaster emergency scenario is designed within the area of ​​the highway site selection result; and the operating status of charging equipment within the area of ​​the highway site selection result is defined according to the design results.

[0045] The feasibility of charging low-altitude aircraft in the highway site selection area is assessed based on the operating status and service satisfaction of the charging equipment, and the adaptability of the charging equipment is analyzed based on the charging feasibility.

[0046] The ability to guarantee the charging needs of low-altitude aircraft within the area selected for highway relocation is assessed by utilizing the ability to guarantee charging needs, and the rationality of the highway relocation results is evaluated based on the guarantee capability.

[0047] After the rationality results meet the preset requirements, the weight correction technology is used to correct and feed back the highway site selection results, and the final highway site selection results are determined based on the feedback results.

[0048] Preferably, the method of using weight correction technology to correct and feedback the highway site selection results, and determining the final highway site selection results based on the feedback results, includes:

[0049] Based on the highway site selection evaluation index system, random combinations of influencing factor parameters are generated, and the site selection scheme score for each combination of influencing factor parameters is calculated. The average comprehensive score is obtained based on the score results.

[0050] The scores are combined with the mean of the comprehensive scores to evaluate the standard deviation of the highway site selection results, the probability of failure, and the sensitivity of the parameters. Based on the probability of failure and the sensitivity of the parameters, a modified triggering condition is established.

[0051] The weight values ​​of the highway site selection evaluation index system are adjusted proportionally based on the modified trigger conditions and parameter sensitivity, and the final highway site selection result is determined based on the adjustment results.

[0052] Preferably, the formula for calculating the site selection score is:

[0053] ;

[0054] ;

[0055] ;

[0056] In the formula, C (k) D represents the score of the k-th location selection scheme. -(k)D represents the negative score of the k-th group of solutions. +(k) ω represents the positive score of the k-th group of solutions. j This represents the weight of the j-th indicator. σ represents the standardized value of the k-th scheme on the j-th index. j This represents the historical standard deviation of the j-th indicator. This represents the positive ideal solution for the j-th index. Let j represent the negative ideal solution of the j-th index.

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

[0058] 1. This invention constructs a hierarchical evaluation model to comprehensively assess multiple influencing factors, taking into account different flight-related factors. This not only provides a clear evaluation framework but also ensures that the evaluation process is scientific and orderly, avoiding the omission of key factors. Furthermore, by constructing a model using historical flight data, it can more accurately simulate the flight path and flight requirements of low-altitude aircraft. Finally, it designs different emergency scenarios to simulate and test the adaptability of the site selection results under emergency conditions, thereby helping to determine whether the site selection can continue to provide necessary services under various unexpected circumstances, ensuring the safety of low-altitude aircraft.

[0059] 2. This invention, by constructing a three-dimensional airspace accessibility model and path planning algorithm, can help aircraft select the optimal flight path, while ensuring that the layout of charging stations meets the charging needs of the aircraft, thereby optimizing the execution efficiency of flight missions. Furthermore, by comprehensively analyzing the aircraft's flight capabilities, the impact of obstacles, and the layout of charging facilities, it ensures that the aircraft's service within the highway site selection area is fully guaranteed, avoiding mission failures caused by insufficient facilities or path problems.

[0060] 3. This invention, through scenario simulation of sudden weather changes and other emergencies, accurately analyzes the charging needs of aircraft and the operational status of charging equipment, ensuring that aircraft can receive timely and efficient charging services within the highway site selection area, improving the sustainability and reliability of the service. Furthermore, by utilizing weight correction technology and feedback mechanisms, it ensures that flexibility and adaptability are maintained throughout the evaluation and correction process of highway site selection results, further enhancing the scientific validity and feasibility of the site selection results. Attached Figure Description

[0061] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the 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.

[0062] Figure 1 This is a flowchart of a method for evaluating highway site selection results considering the impact of low-altitude aircraft, according to an embodiment of the present invention.

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

[0064] Figure 3 This is a flowchart of a game theory-based combinatorial weighting process in a highway site selection result evaluation method considering the impact of low-altitude aircraft, according to an embodiment of the present invention. Detailed Implementation

[0065] To further illustrate the various embodiments, the present invention provides accompanying drawings, which are part of the disclosure of the present invention. These drawings are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these drawings, those skilled in the art should be able to understand other possible implementation methods and the advantages of the present invention.

[0066] According to an embodiment of the present invention, a method for evaluating highway site selection results that takes into account the influence of low-altitude aircraft is provided.

[0067] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments, such as... Figure 1 As shown, the method for evaluating highway site selection considering the impact of low-altitude aircraft according to an embodiment of the present invention includes:

[0068] Step S1: After generating the highway site selection evaluation index system based on the flight influencing factors of low-altitude aircraft, construct a hierarchical evaluation model and obtain the highway site selection results based on the hierarchical evaluation model.

[0069] In one embodiment, after generating a highway site selection evaluation index system based on the influencing factors of low-altitude aircraft flight, a hierarchical evaluation model is constructed. When obtaining highway site selection results based on the hierarchical evaluation model, resource information at the location of the highway site selection scheme and the influencing factors of low-altitude aircraft can be selected as evaluation indicators to construct the highway site selection evaluation index system. Based on the highway site selection evaluation index system, a hierarchical evaluation model is constructed with the highway site selection scheme as the scheme layer, the evaluation indicators as the criterion layer, and the highway site selection results as the target layer. The importance of each pair of different evaluation indicators in the criterion layer of the hierarchical evaluation model is compared using scaling theory. A judgment matrix is ​​generated based on the comparison results to obtain the weight matrix of the evaluation indicators. The subjective and objective weights of the scheme layer are determined based on the weight matrix and the entropy weight method. Game theory is used to combine and assign weights to the subjective and objective weights, and the highway site selection results are obtained based on the weighting results.

[0070] In one embodiment, when determining the subjective and objective weights of the scheme layer based on the weight matrix and 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 based on the weighting result, the logical errors of the judgment matrix can be verified based on the weight matrix of the evaluation index. Based on the verification result, the final weight matrix can be determined, and the composite weight of the scheme layer can be determined using the final weight matrix. The composite weight is then used as the subjective weight of the scheme layer. An initial evaluation matrix is ​​constructed based on the scheme layer and the evaluation index, and data normalization processing is performed on the initial evaluation matrix. The proportion of the evaluation index is calculated based on the processing result. The entropy value and coefficient of variation of the scheme layer are calculated using the proportion result. The objective weight of the scheme layer is calculated based on the coefficient of variation result, and the objective weight and subjective weight are combined to construct a weight vector set. The optimal weight vector of the weight vector set is obtained, and linear coefficients are generated based on the optimal weight vector to solve the combined weight of the scheme layer. The combined weights are sorted, and the highway site selection result is determined based on the sorting result.

[0071] It should be explained that in determining the site selection results of highways, local conditions can be taken into account, 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 indicators to construct a scientific, comprehensive, accurate, and effective evaluation indicator system for the site selection of low-altitude aircraft highway service stations.

[0072] like Figure 2 and Figure 3 As shown, based on the obtained evaluation index system, a hierarchical evaluation model is constructed. The hierarchical model contains three levels: the target level (selecting a reasonable location), the criteria level (various influencing factors), and the scheme level (options available). The target level is to select a reasonable location for the construction of low-altitude aircraft highway service stations. The criteria level includes influencing factors related to service station location selection, such as population size, traffic conditions, airspace resources, economic development, application scenarios, radiation range, and urban planning. In practical applications, these factors can be reasonably adjusted according to specific circumstances to ensure they better suit the actual situation. The scheme level contains the available locations for low-altitude aircraft service station construction. The purpose of the hierarchical analysis is to select the most scientific and reasonable scheme from these options.

[0073] Applying the 1-9 scaling method, the importance of each pair of distinct elements in the criterion layer of the hierarchical evaluation model is compared. The results are then arranged into a judgment matrix, which is then used to obtain the following matrix:

[0074] ;

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

[0076] Table 1: Scaling Results

[0077]

[0078] For each factor in the criterion layer—population size, transportation conditions, airspace resources, economic development, application scenarios, radiation range, and urban planning—a 7*7 judgment matrix can be constructed using the 1-9 scaling method, as shown in Table 2.

[0079] Table 2: Judgment Matrix

[0080]

[0081] Based on the constructed judgment matrix, the weights of each indicator are calculated to obtain the weight matrix. Then, the maximum eigenvalue and the consistency index are calculated. The average random consistency index corresponding to the number of factors in the criterion layer is found by looking up a table. The consistency ratio is obtained by using the ratio of the consistency index and the average random consistency index. Based on this, it is determined whether there is a logical error in the constructed judgment matrix. If there is, it is adjusted. If not, the weights of each indicator are obtained. Based on the weights of each indicator in the criterion layer, the composite weights of the scheme layer are calculated and sorted.

[0082] Construct an initial evaluation matrix based on the available options and evaluation indicators, determine the objective weights using the entropy weight method, and define... x ij For the first j The indicator in the first i The evaluation indicators for each evaluation object (site selection scheme) are used to obtain the initial evaluation matrix: X =( x ij ) m*n ,(in m Indicates the number of evaluation objects. i =1,2,..., m ; n Indicates the number of evaluation indicators. j =1,2,..., n Since different types of indicators can significantly affect the results, it is necessary to remove the influence of dimensions and standardize the data during the calculation process. The process is as follows:

[0083] For positive indicators:

[0084] ;

[0085] For negative indicators:

[0086] ;

[0087] Appropriateness indicators:

[0088] ;

[0089] In the formula, x best,j This represents the optimal value of the appropriateness index. To ensure the validity of the values, each normalized value is incremented by 0.00000001.

[0090] Calculate the proportion P of each indicator ij :

[0091] ;

[0092] Calculate the entropy value e j :

[0093] ;

[0094] Calculate the coefficient of variation d j :

[0095] ;

[0096] Calculate the weight of the indicator w j :

[0097] ;

[0098] Simultaneously, game theory is applied to combine and assign weights to the subjective and objective weight calculation results. In the evaluation of multi-level indicators, assuming that g weighting methods are used to obtain g weight vectors, a weight vector set can be constructed. j represents the j-th index, j=1,2,......n, where u kj Let g represent the j-th level weight vector under the k-th scheme. Then, the linear combination of g weight vectors at each level constitutes a possible set of weights. , where a k U represents the coefficients of the linear combination. k Let T represent the composite weight vector, and T denote the transpose.

[0099] Find the optimal weight vector by minimizing u to the maximum extent. j With each u k deviation, that is:

[0100] ;

[0101] Using the differential properties of matrices, we obtain the first-order optimal derivative:

[0102] ;

[0103] a can be calculated using the above formula. k Normalization process:

[0104] ;

[0105] Obtain linear coefficients :

[0106] ;

[0107] Finally, the final combined weights are calculated as follows:

[0108] ;

[0109] After determining the combined weight vector of the j-th layer indicators, the combined weight of the (j-1)-th layer indicators can be calculated by superimposing the weight values ​​of the j-th layer indicators. The combined weights are then sorted, and the highway site selection result is determined based on the sorting result.

[0110] Step S2: Construct a three-dimensional airspace accessibility model using historical flight data of low-altitude aircraft, predict the flight path of low-altitude aircraft, and determine the service satisfaction of the highway site selection results with low-altitude aircraft based on service requirements.

[0111] In one embodiment, when constructing a three-dimensional airspace accessibility model using historical flight data of low-altitude aircraft, predicting the flight path of low-altitude aircraft, and judging the service satisfaction of highway site selection results for low-altitude aircraft based on service requirements, historical flight data including charging needs, flight trajectory, flight speed, and flight altitude of low-altitude aircraft can be collected, and the historical flight data can be cleaned and anomaly data removed; the three-dimensional airspace range can be determined and divided into several grids, with each grid representing an accessible three-dimensional spatial unit; the flight capability of low-altitude aircraft can be modeled within the three-dimensional spatial unit based on flight trajectory, flight speed, and flight altitude; obstacle information within the highway site selection result area can be obtained, and obstacle modeling can be performed within the three-dimensional spatial unit based on the obstacles, combined with the flight capability modeling results to obtain the three-dimensional airspace accessibility model; the flight path of low-altitude aircraft can be predicted based on the three-dimensional airspace accessibility model and path planning algorithm, and the charging capability of low-altitude aircraft can be obtained by combining the location information of charging equipment within the highway site selection result area; the charging capability can be compared with the charging service requirements of low-altitude aircraft, and the service satisfaction of highway site selection results for low-altitude aircraft can be judged based on the comparison results.

[0112] It should be explained that in the process of constructing a three-dimensional airspace accessibility model, it is necessary to collect historical flight data of low-altitude aircraft. The data includes the following aspects:

[0113] Aircraft charging requirements: The amount of charging required by an aircraft during flight, including charging frequency and charging duration;

[0114] Flight trajectory: The actual flight path of an aircraft, which can be recorded using GPS positioning data, radar data, or sensors;

[0115] Flight speed: Records the speed of the aircraft at various points in time during flight;

[0116] Flight altitude: Records the flight altitude of the aircraft at different points in time.

[0117] Statistical methods (such as mean, standard deviation, etc.) can be used to identify and remove extreme outliers. For example, the speed or altitude of an aircraft cannot exceed a certain range, and data that exceeds this range may be erroneous and needs to be removed. 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.

[0118] Based on practical application requirements and the flight capabilities of the aircraft, the three-dimensional airspace range that the low-altitude aircraft can cover is defined. For example, the spatial range of the airspace can be determined based on factors such as the aircraft's maximum flight altitude, flight speed, and geographical location. The defined three-dimensional airspace is then divided into several smaller spatial units, typically represented by a three-dimensional mesh. Mesh generation can be performed in several ways:

[0119] (1) Regular mesh division: The three-dimensional spatial domain is uniformly divided into several small cubes (e.g., each mesh is a small cube with equal length, width and height).

[0120] (2) Adaptive mesh generation: Based on the flight trajectory and flight requirements of the aircraft, some areas are selected for more refined mesh generation, while other areas are coarsely divided, thereby improving computational efficiency and refining the modeling of the aircraft's activity area.

[0121] Simultaneously, in the process of modeling the flight capabilities of low-altitude aircraft, it is necessary to model the flight capabilities of each grid based on flight trajectory, speed, and altitude data. Flight capability modeling includes the following aspects:

[0122] Flight speed of an aircraft: Calculate the maximum flight speed that an aircraft can achieve in different grid cells; flight speed is affected by a variety of factors, such as aircraft type and weather conditions;

[0123] Aircraft flight altitude: Based on the aircraft's flight history data, establish the aircraft's accessibility within different altitude ranges; different altitudes correspond to different flight requirements, and the aircraft's maximum flight altitude is also limited by flight path, obstacles, and flight environment;

[0124] Flight path modeling: Combining flight trajectory data, the actual flight capability of the aircraft in three-dimensional space is established. These models determine whether the aircraft is reachable within a certain grid based on factors such as time, position, speed, and the aircraft's heading.

[0125] At this stage, obtaining obstacle information within the highway site selection area is essential. Obstacles typically include:

[0126] Natural obstacles: such as mountains, buildings, trees, etc., which can affect the flight path of low-altitude aircraft; man-made obstacles (dynamic obstacles).

[0127] Detailed information about obstacles is obtained and classified through remote sensing technology, geographic information systems (GIS), and obstacle data from actual measurements (such as databases and map data).

[0128] By acquiring obstacle information, obstacles in the three-dimensional airspace can be modeled. Specifically, based on the obstacle's coordinate position, size, shape, and other information, the specific location of the obstacle can be 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 based on factors such as the obstacle's height, range of expansion, and shape.

[0129] By combining the aircraft's flight capabilities and obstacle information, a three-dimensional airspace reachability model can be constructed. The specific process is as follows:

[0130] Within each grid, the aircraft's flight capabilities and obstacle models are combined to determine whether the aircraft can successfully pass through the grid. If the aircraft's flight capabilities (speed, altitude) cannot overcome the limitations of the obstacles, the aircraft cannot pass through the grid. For each grid cell, the aircraft's accessibility is calculated, and an accessibility matrix or graph model is generated to represent the three-dimensional spatial regions that the aircraft can access.

[0131] By combining the aircraft's charging needs and the location of charging facilities, the aircraft's flight path can be further optimized. Based on the distribution of charging facilities within the highway site selection area, it can be determined whether the aircraft can receive 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 aircraft's flight route and charging needs, the service satisfaction of the highway site selection results for low-altitude aircraft can be evaluated. The following steps can be used:

[0132] The analysis examines whether the aircraft can reach charging stations and service facilities within a reasonable time and space range; it assesses whether the service facilities in the highway site selection area can meet the aircraft's needs based on the aircraft's charging requirements, flight time, and speed; and it provides a service satisfaction score by combining service accessibility and aircraft charging requirements to determine whether the highway site selection is reasonable and whether further optimization is needed.

[0133] Through the above steps, a three-dimensional airspace accessibility model for low-altitude aircraft can be constructed. By combining historical flight data, flight capability modeling, obstacle modeling, and other factors, a comprehensive evaluation result can be obtained to determine the service satisfaction of the highway site selection results for low-altitude aircraft.

[0134] In one embodiment, when predicting the flight path of a low-altitude aircraft based on a three-dimensional airspace accessibility model and a path planning algorithm, and combining this with the location information of charging equipment within the highway site selection area to obtain the charging capacity of the low-altitude aircraft, the historical coordinate information of dynamic obstacles within a three-dimensional spatial unit can be obtained based on the three-dimensional airspace accessibility model, and the dynamic obstacles can be inflated. A motion trajectory model is generated using the inflated dynamic obstacles and the Lagrange interpolation method, and the location points of the dynamic obstacles within the highway site selection area are obtained based on the motion trajectory model. The incremental path planning algorithm, the location points of the dynamic obstacles, and the flight requirements are combined to predict the flight path of the low-altitude aircraft, and the installation locations of charging equipment within the highway site selection area are obtained. The distance between the route points corresponding to the flight path and the installation locations of the charging equipment is analyzed, and the suitability of the highway site selection results for the charging capacity of the low-altitude aircraft is determined based on the distance information.

[0135] It should be explained that the process of expanding obstacles first defines dynamic obstacles. Dynamic obstacles are usually objects that move over time, such as other aircraft, meteorological factors (such as airflow and wind speed), and flight areas that aircraft may avoid. Historical coordinate information is collected through remote sensing, aircraft sensors (such as GPS, radar, and lidar), and other dynamic monitoring technologies. For each dynamic obstacle, its position at different points in time is recorded, and its trajectory data is constructed. The movement trajectory of the dynamic obstacle is recorded through time-series data, and the data is supplemented by interpolation or smoothing methods. The trajectory information of each dynamic obstacle will serve as the basis for subsequent path planning and obstacle expansion processing.

[0136] In the three-dimensional airspace, dynamic obstacles may affect the safe flight path of an aircraft. Therefore, obstacles need to be expanded during path planning. Expansion refers to expanding the spatial range of the obstacle so that the expanded obstacle can more accurately simulate the obstacle avoidance requirements of the aircraft. The radius of expansion usually depends on the size of the aircraft (e.g., 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 larger, so the radius of expansion should also be increased accordingly.

[0137] Dynamic obstacles not only need to expand their current position but also need to consider their possible future trajectories. The expansion should take into account the possible positions of the obstacles within a certain time range in the future. By predicting the dynamic obstacles (e.g., using Kalman filtering or motion models), the future motion of the obstacles is predicted and expanded accordingly. For three-dimensional airspace, the expansion is not limited to the horizontal plane but also needs to be expanded in the vertical direction. The height information of the obstacles is also taken into account during the expansion process to ensure that the aircraft can safely pass over or under the obstacles when avoiding them. In the expanded obstacle model, the aircraft needs to avoid the expanded obstacle area. If the expanded obstacles overlap or contact the aircraft's flight path, the path planning algorithm will automatically adjust the flight route.

[0138] In one embodiment, when generating a motion trajectory model using a dilated dynamic obstacle and Lagrange interpolation, and obtaining the location points of the dynamic obstacle within the highway site selection result area based on the motion trajectory model, an initial location point of the dilated dynamic obstacle can be set. A polynomial is constructed using Lagrange interpolation based on the initial location point to sample the state of the dynamic obstacle at any location point. The polynomial is used to analyze the sequential positions of the dynamic obstacle during its movement, and a motion trajectory prediction model for the dynamic obstacle in the lateral and longitudinal directions is obtained based on the position results. The motion trajectory prediction model is used to analyze the predicted position of the dynamic obstacle at any time, and its subsequent trajectory is analyzed based on the predicted position, outputting a trajectory curve. The trajectory curve is mapped onto a three-dimensional spatial unit to obtain the location points of the dynamic obstacle's trajectory curve within the highway site selection result area.

[0139] In one embodiment, when combining incremental path planning algorithms, the location points of dynamic obstacles, and flight requirements to predict the flight path of a low-altitude aircraft, a starting point can be defined based on the flight requirements of the low-altitude aircraft. Bitwise operations are then used to filter key points from the flight requirements, and these key points are added to the open list of the incremental path planning algorithm. The key point with the lowest value in the open list is analyzed and used as an extended parent node. It is then checked whether the path from the key point and its extended parent node to the starting point intersects with the location points of the dynamic obstacles. If they do not intersect, the extended parent node is used as the flight path point of the low-altitude aircraft; if they intersect, the extended parent node is deleted, and a new key point is selected from the open list as the extended parent node. The final flight path points are connected to obtain a flight control polygon curve, which is then smoothed based on a Bézier curve to generate the flight path of the low-altitude aircraft.

[0140] In one embodiment, when analyzing the distance between route points corresponding to flight routes and the installation location of charging equipment, and determining the suitability of highway site selection results for the charging capacity of low-altitude aircraft based on distance information, a suitable distance calculation method needs to be defined to compare the relationship between flight route points and the installation location of charging equipment. Common distance calculation methods include:

[0141] Two-dimensional Euclidean distance: If only the horizontal plane (longitude and latitude) of the flight path is considered, the two-dimensional Euclidean distance can be used to calculate the horizontal distance between the flight path point and the charging station;

[0142] Three-dimensional distance: If the altitude difference of the aircraft is taken into account, the three-dimensional Euclidean distance can also be used to calculate the actual distance between the aircraft and the charging station;

[0143] If the altitude difference between the charging facility and the flight path is small, two-dimensional distance calculation is sufficient; if the altitude difference is large, three-dimensional distance calculation is more accurate.

[0144] Based on the aircraft's flight trajectory, 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 distance to all charging facilities (assuming there are M charging stations) is calculated separately. The distance from each flight route point to all charging facilities can be stored as a matrix, where each row represents a flight route point and the column represents the location of the charging facility.

[0145] Based on the above distance calculation results, it can be determined whether the aircraft can be charged smoothly, and then the matching degree of the highway site selection results with the aircraft's charging capacity can be evaluated. A maximum service distance threshold is set, that is, if the distance between the aircraft's waypoint 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 aircraft's charging needs and the aircraft's charging time constraints: D ij ≤D max D max This is the preset maximum service distance. If the distance between a flight route point and all charging facilities is greater than this threshold, it means that the flight route point cannot be charged smoothly in this area. All route points in the flight route are counted, and the proportion of them within the coverage area of ​​the charging facilities is calculated. If most flight route points are within the coverage area of ​​the charging facilities, it means that the highway site selection is highly compatible with the charging capacity of low-altitude aircraft.

[0146] Based on the service satisfaction of each flight route point, an overall matching score is calculated. A weighted average method can be used to comprehensively consider the matching degree of different route points.

[0147] ;

[0148] In the formula, G match O represents the overall match score. a S represents the importance weight of the a-th flight path point (this weight can be adjusted based on the length of the flight path, the flight requirements of the aircraft, etc.). a This indicates the service satisfaction level of the a-th flight route point (whether charging can be completed within the coverage area of ​​charging facilities).

[0149] Therefore, by calculating the distance between flight route points and charging facilities, it is possible to determine whether the aircraft can successfully obtain charging support, thereby assessing the compatibility of highway site selection with the charging capabilities of low-altitude aircraft.

[0150] To facilitate understanding of the above technical solutions of the present invention, the following describes in detail the operation method of judging the service satisfaction of low-altitude aircraft based on highway site selection results in practical applications.

[0151] Step 1: Construction of a 3D spatial reachability model;

[0152] Assume the following data is obtained based on historical data:

[0153] Aircraft charging requirements: The aircraft needs to be charged once every 50 kilometers of flight. The charging time is 15 minutes. After each charge, the aircraft can travel an additional 50 kilometers.

[0154] Flight trajectory: The historical trajectory of the aircraft is set as: [(r1, f1, z1), (r2, f2, z2), ..., (R1, f1, z1), (r2, f2, z2), ..., (R1, f1, z2), (r2, f2, z2), ..., (R1, f1, z2), (r2, f1 ... (r2, f A F A Z A Each data point contains longitude (r), latitude (f), and altitude (z).

[0155] For example:

[0156] (r1=40.7128°N, f1=74.0060°W, z1=200m);

[0157] (r2=40.7148°N, f2=74.0080°W, z2=220m);

[0158] Flight speed:

[0159] The aircraft's average flight speed is 60 km / h, its maximum flight speed is 100 km / h, and its minimum flight speed is 30 km / h.

[0160] Flight altitude:

[0161] When flying in urban areas, the flight altitude is generally around 200 meters, while it can reach 500 meters when flying in open areas.

[0162] Outlier removal of aircraft altitude: For example, if the flight altitude of a certain data point is 3000 meters, this is obviously an outlier and will be removed. At the same time, if there are missing position data in the flight trajectory, linear interpolation or spline interpolation is used to fill them.

[0163] The maximum flight altitude of the aircraft is set at 500 meters, the flight speed at 100 km / h, and its geographical location is within a specific area (e.g., a 10-kilometer area along a highway). The airspace range is as follows:

[0164] Longitude: 40.7°N to 40.8°N (within 10 km); Latitude: 73.9°W to 74.0°W (within 10 km); Altitude: 0 m (ground) to 500 m;

[0165] This area is divided into a 3D grid of 100m x 100m x 50m, for a total of 10,000 grids. Assuming each grid is a small cube with a length, width, and height of 100m, the flight capability model of the aircraft can be based on this grid unit, taking into account the flight requirements and obstacles of the aircraft.

[0166] Assume the following flight capability model already exists:

[0167] Maximum speed of the aircraft: 100km / h; maximum flight altitude of the aircraft: 500 meters; minimum flight altitude: 0 meters (ground).

[0168] Flight capability is modeled within each grid based on flight history data, using the following assumptions:

[0169] Flight speed modeling: Within these grids, the maximum flight speed of the aircraft is affected by weather and other aircraft, and is usually maintained at 60 km / h. If it encounters obstacles (such as buildings), the flight speed will decrease to 30 km / h.

[0170] Flight altitude modeling: Based on historical data, aircraft typically maintain an altitude of 200 to 300 meters, and will decrease altitude when flying in areas below 200 meters (such as urban areas).

[0171] Natural obstacles: such as mountains, forests, and undulating terrain, assuming these obstacles are 10 to 200 meters high; man-made obstacles: such as vehicles and other dynamic obstacles; in a three-dimensional airspace grid, these obstacles are modeled to generate the spatial range occupied by the obstacles, which in turn affects the reachability of the aircraft.

[0172] By combining flight capability and obstacle modeling, an reachability matrix is ​​generated, representing whether the aircraft can fly successfully within each grid. The following parameters are set:

[0173] If an aircraft's flight capability within a given grid is insufficient to overcome obstacles in that area, then that grid is unreachable. An reachability matrix is ​​generated based on a comparison of obstacles and the aircraft's flight capability. For example, if a grid contains a 150-meter-high building, and the aircraft's maximum flight altitude is 200 meters, then that grid may be unreachable.

[0174] Step 2: Service Satisfaction Analysis;

[0175] After obtaining the 3D spatial accessibility model, path planning is performed based on the location information of charging facilities. Assuming there is a charging station every 5 kilometers along the highway, the coordinates of the charging stations are:

[0176] (40.7100°N, 74.0055°W); (40.7150°N, 74.0100°W); (40.7200°N, 74.0150°W);

[0177] Assuming the aircraft needs to be charged every 50 kilometers, and the charging time is 15 minutes, the aircraft's charging requirement is to support 50 kilometers of flight per charge. Based on the path planning algorithm (such as incremental path planning), the distance between the flight path point and the charging device can be calculated based on the aircraft's flight path.

[0178] Assuming the aircraft takes off from (40.7100°N, 74.0050°W) and flies 100 kilometers, the distances between certain points along the flight path and the charging equipment are calculated as follows:

[0179] The route point (40.7110°N, 74.0060°W) is 200 meters away from the charging station (40.7100°N, 74.0055°W);

[0180] The route point (40.7150°N, 74.0080°W) is 100 meters away from the charging station (40.7150°N, 74.0100°W);

[0181] If the maximum service distance of the charging station is set to 500 meters, then both waypoints are within the service range, meaning that the aircraft can be charged successfully at these two locations.

[0182] For most waypoints, the aircraft can reach the charging facilities smoothly. The charging station coverage rate is calculated to be 80% (80 waypoints are within the service range of the charging station). Based on the charging demand and coverage rate, the service satisfaction rate is calculated to be 0.8. Therefore, the matching degree of highway site selection with the charging capacity of low-altitude aircraft is 80%.

[0183] Step S3: Design emergency scenarios based on service satisfaction, determine the resilience of the highway site selection results, evaluate the rationality of the highway site selection results based on the resilience, and determine the final highway site selection results using the rationality evaluation results.

[0184] In one embodiment, when designing emergency scenarios based on service satisfaction, assessing the resilience of highway site selection results, evaluating the rationality of highway site selection results based on resilience, and determining the final highway site selection result using the rationality evaluation result, the following steps can be taken: Emergency disaster scenarios generated within the highway site selection result area can be designed based on meteorological change rules; the operational status of charging equipment within the highway site selection result area can be defined according to the design results; the charging feasibility of low-altitude aircraft within the highway site selection result area can be assessed based on the charging equipment operational status and service satisfaction, and the resilience of charging equipment can be analyzed based on charging feasibility; the resilience can be used to determine the charging demand guarantee capability of low-altitude aircraft within the highway site selection result area, and the rationality of the highway site selection result can be evaluated based on the guarantee capability; after the rationality result meets the preset requirements, the highway site selection result can be corrected and fed back using weight correction technology, and the final highway site selection result can be determined based on the feedback result.

[0185] It should be explained that meteorological abrupt changes refer to drastic changes in weather conditions within a short period of time, such as extreme weather events like heavy rain, thunderstorms, hail, and strong winds. These abrupt events can affect the operation of low-altitude aircraft and the safety of charging facilities. Therefore, when designing disaster emergency scenarios, the types of meteorological abrupt events should be determined first, including:

[0186] Heavy rain: Heavy precipitation may cause flooding or affect visual range for flight;

[0187] Lightning: Lightning strikes can endanger the safety of aircraft and ground facilities;

[0188] Strong winds: High wind speeds may affect the stability of aircraft and the safety of charging facilities;

[0189] Hail: Severe hail may damage aircraft and external components of charging facilities;

[0190] Extreme low temperatures: Low temperatures may affect the performance of aircraft batteries and even cause charging facilities to malfunction.

[0191] Real-time meteorological data is acquired through tools such as meteorological satellites and weather radar to monitor the trend of meteorological changes. Based on historical meteorological data, the probability of occurrence of various sudden events is determined, and probability distribution models of different sudden events are constructed. According to the occurrence pattern of meteorological changes and the impact of sudden events, different disaster emergency scenarios are designed to assess the safety of highway site selection areas and charging equipment.

[0192] Set up emergency scenarios, for example:

[0193] Scenario 1: Heavy rain and strong winds: During heavy rain, strong winds may cause navigation difficulties for aircraft, and charging facilities may be damaged due to water accumulation or wind collapse.

[0194] In scenario 2, lightning and hail: the aircraft may be struck by lightning or hail, and the charging facilities may stop working due to lightning interference or physical damage.

[0195] In scenario 3, a severe temperature drop occurs: extremely cold weather may prevent the aircraft battery from being charged effectively, and charging facilities and equipment may freeze or fail due to the low temperature.

[0196] The intensity of each disaster scenario needs to be quantified, such as: the rainfall intensity of heavy rain (mm / hour); the wind speed of strong winds (m / s); the frequency and intensity of lightning; and the range of rapid temperature changes. These parameters can be set based on meteorological early warning systems or historical data.

[0197] Determine the duration of the disaster event, such as heavy rain lasting 2 hours or strong winds lasting 1 hour, and define the geographical scope of the disaster's impact, which may be a certain area along a highway (e.g., within a 10-kilometer radius).

[0198] Based on the scenario of a disaster emergency, the operational status of charging equipment under different disaster conditions can be defined. The operational status of the charging equipment will be affected by factors such as the type, intensity, and duration of the disaster. According to the disaster scenario, the rules for the transition of the charging equipment status can be set:

[0199] Heavy rain trigger rules: If the intensity of the heavy rain is greater than 50 mm / hour and the duration exceeds 30 minutes, the system will enter deceleration mode; if the intensity of the heavy rain is greater than 100 mm / hour and the duration exceeds 1 hour, the charging facilities will enter a suspended service state.

[0200] Strong wind triggering rules: If the wind speed exceeds 20 m / s (72 km / h), the charging facility will enter deceleration mode; if the wind speed exceeds 30 m / s (108 km / h), the charging facility will enter a service suspension or malfunction mode.

[0201] Lightning triggering rules: If lightning activity occurs frequently within the charging facility area, the charging facility will automatically switch to deceleration mode; if lightning strikes the charging equipment, it will enter fault mode.

[0202] Hailstorm triggering rules: If the diameter of the hailstones is greater than 1 cm, the charging facility will enter a deceleration mode; if the diameter of the hailstones is greater than 2 cm or the hailstorm lasts for more than 30 minutes, the charging facility will enter a suspended service state.

[0203] Low temperature triggering rules: If the temperature drops below 0°C, the charging facility enters a deceleration mode and reduces its output power; if the temperature drops below -10°C, the charging facility suspends service.

[0204] Once the disaster has passed, the charging facilities will resume normal service. The triggering rules for this resumption may include:

[0205] Temperature recovery: Once the temperature returns to above 10℃, the charging facilities will resume normal service;

[0206] Wind speed recovery: Once the wind speed returns to a safe level (below 20 m / s), normal service will resume.

[0207] Rainfall decreases: After the heavy rain stops and the facilities are inspected, normal charging resumes.

[0208] Through the above design steps, the impact of different meteorological disasters on the operation of charging equipment in the highway site selection area can be simulated, ensuring that the charging needs of aircraft under severe weather conditions are reasonably assessed and managed.

[0209] In one embodiment, when assessing the charging feasibility of low-altitude aircraft within the highway site selection area based on the operational status and service satisfaction of charging equipment, and analyzing the resilience of charging equipment based on charging feasibility, it is necessary to clarify the charging requirements of the low-altitude aircraft, which typically include: charging quantity, charging time requirements, and charging frequency. Based on 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 assessment is whether the availability of the charging equipment matches the charging requirements of the aircraft, as analyzed in detail below:

[0210] Accessibility of charging equipment services: Calculate the distance from the aircraft's takeoff point to the charging facility, taking into account factors such as path planning, obstacles, and weather, to determine whether the aircraft can reach the charging facility within the specified time; Service capacity of charging equipment: Consider the operational status of the charging facility under extreme weather conditions, and assess whether the charging equipment can meet the aircraft's charging needs.

[0211] Taking into account the above factors, a charging feasibility assessment is conducted based on the operational status and service satisfaction of the charging equipment: Based on the aircraft's charging needs and the operational status of the charging equipment, it is calculated whether the aircraft can complete charging on time in the selected area. If the service satisfaction of the charging facilities is high (e.g., the charging facilities can provide charging services under normal conditions), the charging feasibility is high. If the charging facilities are in fault mode or suspended due to extreme weather or other factors, the charging feasibility is low, and it is necessary to assess whether additional charging facilities are needed or the flight path needs to be adjusted.

[0212] The resilience of charging equipment refers to whether charging facilities can restore or maintain their operation through certain measures when encountering emergencies (such as sudden weather changes, equipment failures, etc.). The resilience of charging equipment includes the following aspects:

[0213] Fault tolerance: Does the charging facility have 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 ability of the charging equipment to adapt to extreme weather conditions, such as whether it can prevent damage to the equipment from heavy rain, lightning, strong winds, etc. Output power regulation capability: Whether the charging facility can adjust the output power to ensure the continuity of the charging function in extreme weather or when the load is too high, that is, whether it can maintain a certain charging capacity when encountering sudden weather changes (such as storms, strong winds, etc.).

[0214] Finally, by combining charging feasibility with the resilience of charging equipment, a comprehensive assessment is made to determine whether charging facilities can provide stable charging services under different disaster scenarios: High charging feasibility and high resilience: Charging facilities can maintain normal service under extreme weather and emergencies, indicating high charging feasibility. Low charging feasibility and low resilience: Charging facilities cannot maintain charging service during disasters, indicating low charging feasibility, and improvements to the facilities or the addition of backup charging stations need to be considered.

[0215] This comprehensive analysis can further optimize highway site selection, ensure that low-altitude aircraft can successfully complete charging tasks under various weather conditions, and improve the reliability and safety of the system.

[0216] It should be explained that when evaluating the rationality of highway site selection, the charging facilities can be assessed based on the aircraft's charging needs and the responsiveness of the charging infrastructure to determine whether the infrastructure can meet the aircraft's charging requirements under different environments. The specific steps are as follows:

[0217] Based on the aforementioned resilience, assess whether the charging facilities can continuously provide charging for low-altitude aircraft under severe weather conditions (such as heavy rain, strong winds, lightning, extreme cold, etc.), whether they can be quickly restored when damaged, and whether they can provide charging services in a short period of time to prevent aircraft from being unable to continue flying due to lack of charging.

[0218] Assess the ability of charging facilities to meet the charging needs of aircraft: the availability of charging facilities under normal and extreme weather conditions, and whether there are prolonged service interruptions; consider the power regulation capabilities of charging equipment in disasters or emergencies, and whether it can provide sufficient charging time in a timely manner to meet the aircraft's range requirements.

[0219] The analysis focuses on whether charging infrastructure covers the aircraft's main flight path, particularly within highway areas, and whether it can ensure the aircraft can find charging stations in a timely manner during flight. Based on the aircraft's charging needs, the distribution of charging stations is assessed for its rationality. Low charging station density may affect the feasibility of charging the aircraft.

[0220] Assess the compatibility between the charging needs of low-altitude aircraft and the availability of charging facilities in the selected area:

[0221] If the charging station covers sufficient charging needs within the aircraft's flight range and can continuously provide charging services to the aircraft in severe weather, the location is considered reasonable; if the distribution of charging facilities cannot effectively cover the aircraft's flight path, or if the charging facilities cannot function properly in extreme weather, the location is considered unreasonable.

[0222] At the same time, it is assessed whether the charging facilities in the highway site area can maintain charging services in the event of a sudden disaster, such as heavy rain or lightning. In the event of a sudden event (such as lightning or strong wind), can the charging facilities continue to provide charging services? If the charging facilities encounter a sudden event (such as lightning or strong wind), can the system recovery time be fast enough to restore charging services within a reasonable time and avoid affecting the aircraft?

[0223] This will optimize the deployment and management of charging facilities, ensuring that the charging needs of low-altitude aircraft in highway locations can be reliably guaranteed.

[0224] In one embodiment, when using weight correction technology to correct and feedback the highway site selection results, and determining the final highway site selection results based on the feedback results, a combination of influencing factor parameters can be randomly generated based on the highway site selection evaluation index system, and the site selection scheme score for each combination of influencing factor parameters can be calculated. The average comprehensive score is obtained based on the score results. The score results are combined with the average comprehensive score to evaluate the score standard deviation, failure probability, and parameter sensitivity of the highway site selection results, and correction triggering conditions are established based on the failure probability and parameter sensitivity. The weight values ​​of the highway site selection evaluation index system are adjusted proportionally based on the correction triggering conditions and parameter sensitivity, and the final highway site selection results are re-determined based on the adjustment results.

[0225] It should be explained that during the simulation evaluation and weight correction feedback of the site selection results, N=10000 sets of parameter combinations (determined according to actual needs) are randomly generated for influencing factors such as population size (P), traffic conditions (T), airspace resources (A), economic development (E), application scenario (S), radiation range (R), and urban planning (U) 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 kth randomly generated site selection scheme.

[0226] Calculate the score for each set of parameters:

[0227] ;

[0228] ;

[0229] ;

[0230] In the formula, C (k) D represents the score of the k-th location selection scheme. -(k) D represents the negative score of the k-th group of solutions. +(k) ω represents the positive score of the k-th group of solutions. j This represents the weight of the j-th indicator. σ represents the standardized value of the k-th scheme on the j-th index. j This represents the historical standard deviation of the j-th indicator. This represents the positive ideal solution for the j-th index. Let j represent the negative ideal solution of the j-th index.

[0231] Quantitative analysis of site selection robustness:

[0232] (1) Key evaluation indicators are shown in Table 3:

[0233] Table 3: Key Assessment Indicators

[0234]

[0235] Simultaneously, based on the evaluation results, a weight adjustment method is used, specifically:

[0236] (1) Weight adjustment is initiated when any of the following conditions are met. The specific adjustment trigger conditions are:

[0237] ;

[0238] (2) Weight adjustment:

[0239] Based on the sensitivity analysis results, the weights are adjusted proportionally:

[0240] ;

[0241] Where η represents a constant, typically equal to 0.05. Represents the partial differential symbol.

[0242] Weight update results for:

[0243] ;

[0244] Indicates historical weight;

[0245] Set constraints according to actual needs:

[0246] The weight range of a single indicator can be the minimum weight w min =0.1, maximum weight w max =0.3, the total weight sum is always 1:

[0247] ;

[0248] Therefore, by utilizing weight correction techniques and feedback mechanisms, flexibility and adaptability can be maintained throughout the evaluation and correction process of highway site selection results, thereby further improving the scientific validity and feasibility of the site selection results.

[0249] In summary, by utilizing the above-mentioned technical solutions of this invention, the present invention, through the construction of a hierarchical evaluation model, can comprehensively assess multiple influencing factors, taking into account different flight-related factors. This not only provides a clear evaluation framework but also ensures that the evaluation process is scientific and orderly, avoiding the omission of key factors. Furthermore, by constructing a model using historical flight data, it can more accurately simulate the flight paths and flight requirements of low-altitude aircraft. Finally, it designs simulations of different emergency scenarios and tests the adaptability of the site selection results under emergency conditions, thereby helping to determine whether the site selection can continuously provide necessary services under various unexpected circumstances, ensuring the safety of low-altitude aircraft. This invention, by constructing a three-dimensional airspace accessibility model and path planning algorithm, can help aircraft select the optimal flight path while ensuring that the layout of charging stations meets the aircraft's charging needs, thus optimizing the execution efficiency of flight missions. Moreover, by comprehensively analyzing the aircraft's flight capabilities, obstacle impacts, and the layout of charging facilities, it ensures that the service of aircraft within highway site selection areas is fully guaranteed, avoiding mission failures due to insufficient facilities or path problems. This invention, through scenario simulation of sudden weather changes and other emergencies, accurately analyzes the charging needs of aircraft and the operational status of charging equipment, ensuring that aircraft receive timely and efficient charging services within highway site selection areas, thereby improving the sustainability and reliability of the service. Furthermore, by utilizing weight correction technology and feedback mechanisms, it ensures that flexibility and adaptability are maintained throughout the evaluation and correction process of highway site selection results, further enhancing the scientific validity and feasibility of the site selection results.

[0250] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for evaluating highway site selection results considering the impact of low-altitude aircraft, characterized in that, include: After generating an evaluation index system for highway site selection based on the factors affecting low-altitude aircraft flight, a hierarchical evaluation model is constructed, and highway site selection results are obtained based on the hierarchical evaluation model. A three-dimensional airspace accessibility model is constructed using historical flight data of low-altitude aircraft to predict the flight path of low-altitude aircraft, and the service satisfaction of highway site selection results with low-altitude aircraft is judged in combination with service requirements. Based on service satisfaction, design emergency scenarios, assess the resilience of highway site selection results, evaluate the rationality of highway site selection results based on resilience, and use the rationality evaluation results to determine the final highway site selection results. The process of constructing a three-dimensional airspace accessibility model using historical flight data of low-altitude aircraft, predicting the flight path of low-altitude aircraft, and judging the service satisfaction of highway site selection results for low-altitude aircraft in conjunction with service requirements includes: Collect historical flight data including charging requirements, flight trajectory, flight speed and flight altitude of low-altitude aircraft, and clean and remove abnormal data from the historical flight data; The three-dimensional airspace is defined and divided into several grids. Each grid represents a reachable three-dimensional spatial unit. The flight capability of low-altitude aircraft is modeled within the three-dimensional spatial unit based on the flight trajectory, flight speed and flight altitude. Obtain obstacle information within the highway site selection area, perform obstacle modeling within three-dimensional spatial units, and combine the flight capability modeling results to obtain a three-dimensional airspace accessibility model; The flight path of low-altitude aircraft is predicted based on a three-dimensional airspace accessibility model and path planning algorithm, and the charging capacity of low-altitude aircraft is obtained by combining the location information of charging equipment in the area of ​​highway site selection results. The charging capacity is compared with the charging service requirements of low-altitude aircraft, and the service satisfaction of the highway site selection results with low-altitude aircraft is judged based on the comparison results. The method of predicting the flight path of a low-altitude aircraft based on a three-dimensional airspace accessibility model and path planning algorithm, and combining this with the location information of charging equipment within the highway site selection area, to obtain the charging capacity of the low-altitude aircraft includes: The historical coordinate information of dynamic obstacles in three-dimensional spatial units is obtained based on the three-dimensional spatial accessibility model, and the dynamic obstacles are then expanded. A motion trajectory model is generated using the dilated dynamic obstacle and the Lagrange interpolation method. The location points of the dynamic obstacle within the highway site selection result area are obtained based on the motion trajectory model. The incremental path planning algorithm, the location of dynamic obstacles, and flight requirements are combined to predict the flight path of low-altitude aircraft and obtain the installation location of charging equipment in the area of ​​highway site selection results. Analyze the distance between the route points corresponding to the flight route and the installation location of the charging equipment, and judge the suitability of the highway site selection results for the charging capacity of the low-altitude aircraft based on the distance information; The process of generating a motion trajectory model using the dilated dynamic obstacle and Lagrange interpolation, and obtaining the location points of the dynamic obstacle within the highway site selection area based on the motion trajectory model, includes: Set the initial position of the dynamic obstacle after the dilation process, and construct a polynomial based on the initial position using the Lagrange interpolation method to sample the state of the dynamic obstacle at any position. Based on the polynomial analysis of the sequential positions of dynamic obstacles during their movement, a trajectory prediction model for the dynamic obstacles in the lateral and longitudinal directions is obtained based on the position results. The motion trajectory prediction model is used to analyze the predicted position of dynamic obstacles at any time, and the subsequent trajectory of the dynamic obstacles is analyzed based on the predicted position of the dynamic obstacles, and the trajectory curve is output. The trajectory curve is mapped onto a three-dimensional spatial unit to obtain the location point of the dynamic obstacle trajectory curve within the highway site selection result area.

2. The method for evaluating highway site selection results considering the impact of low-altitude aircraft according to claim 1, characterized in that, After generating the highway site selection evaluation index system based on the flight influencing factors of low-altitude aircraft, a hierarchical evaluation model is constructed, and the highway site selection results are obtained based on the hierarchical evaluation model, including: Resource information at the location of the highway site selection scheme and the influencing factors of low-altitude aircraft are selected as evaluation indicators to construct a highway site selection evaluation index system. Based on the highway site selection evaluation index system, a hierarchical evaluation model is constructed, with highway site selection schemes as the scheme layer, evaluation indicators as the criterion layer, and highway site selection results as the target layer. The importance of each pair of different evaluation indicators in the criterion layer of the hierarchical evaluation model is compared using scaling theory. A judgment matrix is ​​generated based on the comparison results, and the weight matrix of the evaluation indicators 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 and weighted using game theory. The highway site selection results are obtained based on the weighting results.

3. The method for evaluating highway site selection results considering the impact of low-altitude aircraft according to claim 2, characterized in that, The process of determining the subjective and objective weights of the scheme layer based on the weight matrix and entropy weight method, and using game theory to combine and assign weights to the subjective and objective weights, and obtaining the highway site selection results based on the weighting results includes: The logical errors in the judgment matrix are verified based on the weight matrix of the evaluation index. The final weight matrix is ​​determined based on the verification results. The final weight matrix is ​​used to determine the composite weight of the scheme layer, and the composite weight is used as the subjective weight of the scheme layer. An initial evaluation matrix is ​​constructed based on the scheme layer and evaluation indicators, and data normalization is performed on the initial evaluation matrix. The proportion of the evaluation indicators is calculated based on the processing results. The entropy and coefficient of variation of the scheme layer are calculated using the proportional results. The objective weights of the scheme layer are calculated based on the coefficient of variation results. The objective weights and subjective weights are combined to construct a weight vector set. Obtain the optimal weight vector of the weight vector set, generate linear coefficients based on the optimal weight vector to solve the combined weight of the scheme layer, sort the combined weights, and determine the highway site selection result based on the sorting result.

4. The method for evaluating highway site selection results considering the impact of low-altitude aircraft according to claim 3, characterized in that, The method of combining incremental path planning algorithms, the location of dynamic obstacles, and flight requirements to predict the flight path of low-altitude aircraft includes: The starting point is defined based on the flight requirements of the low-altitude aircraft, and key points are selected from the flight requirements using bitwise operation instructions and added to the open list of the incremental path planning algorithm. Analyze the keypoint with the lowest value in the open list, use it as an extended parent node, and check whether the path from the keypoint and its extended parent node to the starting point intersects with the location point of the dynamic obstacle. If they do not intersect, the extended parent node will be used as the flight path point of the low-altitude aircraft. If they intersect, the extended parent node will be deleted, and a new key point will be selected from the open list as the extended parent node. Connect the final flight path points to obtain the flight control polygon curve, and smooth the flight control polygon curve based on the Bézier curve to generate the flight path of the low-altitude aircraft.

5. The method for evaluating highway site selection results considering the impact of low-altitude aircraft according to claim 1, characterized in that, The process of designing contingency scenarios based on service satisfaction, assessing the resilience of highway site selection results, evaluating the rationality of highway site selection results based on resilience, and determining the final highway site selection results using the rationality evaluation results includes: Based on the rules for setting meteorological changes, a disaster emergency scenario is designed within the area of ​​the highway site selection result; and the operating status of charging equipment within the area of ​​the highway site selection result is defined according to the design results. The feasibility of charging low-altitude aircraft in the highway site selection area is assessed based on the operating status and service satisfaction of the charging equipment, and the adaptability of the charging equipment is analyzed based on the charging feasibility. The ability to guarantee the charging needs of low-altitude aircraft within the area selected for highway relocation is assessed by utilizing the ability to guarantee charging needs, and the rationality of the highway relocation results is evaluated based on the guarantee capability. After the rationality results meet the preset requirements, the weight correction technology is used to correct and feed back the highway site selection results, and the final highway site selection results are determined based on the feedback results.

6. The method for evaluating highway site selection results considering the impact of low-altitude aircraft according to claim 5, characterized in that, The process of using weighted correction techniques to correct and feedback the highway site selection results, and determining the final highway site selection results based on the feedback results, includes: Based on the highway site selection evaluation index system, random combinations of influencing factor parameters are generated, and the site selection scheme score for each combination of influencing factor parameters is calculated. The average comprehensive score is obtained based on the score results. The scores are combined with the mean of the comprehensive scores to evaluate the standard deviation of the highway site selection results, the probability of failure, and the sensitivity of the parameters. Based on the probability of failure and the sensitivity of the parameters, a modified triggering condition is established. The weight values ​​of the highway site selection evaluation index system are adjusted proportionally based on the modified trigger conditions and parameter sensitivity, and the final highway site selection result is determined based on the adjustment results.

7. The method for evaluating highway site selection results considering the impact of low-altitude aircraft according to claim 6, characterized in that, The formula for calculating the score of the location selection scheme is as follows: In the formula, C (k) D represents the score of the k-th location selection scheme. -(k) D represents the negative score of the k-th group of solutions. +(k) ω represents the positive score of the k-th group of solutions. j This represents the weight of the j-th indicator. σ represents the standardized value of the k-th scheme on the j-th index. j This represents the historical standard deviation of the j-th indicator. This represents the positive ideal solution for the j-th index. Let j represent the negative ideal solution of the j-th index.

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