Aircraft landing site selection method, apparatus, and program product

Abstract

The application discloses an aircraft landing site selection method, device and program product, and relates to the technical field of aircrafts. The aircraft landing site selection method comprises the following steps: acquiring soil topographic data of a landing candidate area and passability data of a mobile landing device; determining a device accessible area from the landing candidate area based on the passability data and the soil topographic data; and determining the landing site from the device accessible area. The application takes whether the walking ability of a mobile landing device carrier can reach as a site selection factor, and can provide reliable landing and operation service guarantee for temporary landing of an aircraft involving the mobile landing device.

Description

Technical Field

[0001] This application relates to the field of aircraft technology, and in particular to methods, equipment and procedures for aircraft take-off and landing site selection. Background Technology

[0002] If manned or unmanned aircraft such as helicopters, multirotor aircraft, and electric vertical take-off and landing (eVTOL) vehicles cannot return to their origin, a temporary alternate landing site that meets the aircraft's landing requirements must be selected using a temporary take-off and landing site selection algorithm. The temporary alternate landing site can be a mobile take-off and landing device. Mobile take-off and landing devices are rapidly deployable temporary take-off and landing sites, enabling them to provide timely take-off and landing support for helicopters, multirotor aircraft, and even eVTOLs.

[0003] However, the aircraft take-off and landing site selection methods in related technologies only consider the landing environment requirements of the aircraft, which leads to insufficient reliability of the selection methods in practical applications. Summary of the Invention

[0004] The main objective of this application is to provide a method, device, and program for selecting aircraft take-off and landing sites, aiming to solve the technical problem that the method for selecting aircraft take-off and landing sites considers only one factor and lacks reliability.

[0005] To achieve the above objectives, this application proposes a method for selecting aircraft take-off and landing sites, the method comprising: Acquire soil topography data and mobility data of the mobile take-off and landing device in the candidate landing area; Based on the passability data and the soil topography data, the reachable area of ​​the device is determined from the landing candidate area; The take-off and landing points are determined from the area accessible by the device.

[0006] In one embodiment, determining the reachable area of ​​the device from the landing candidate areas based on the passability data and the soil topography data includes: Based on the accessibility data, accessibility constraints are obtained; wherein, the accessibility constraints include at least one of road network accessibility constraints, slope constraints, and land carrying capacity constraints. Based on the passability constraints and the soil topography data, the reachable area of ​​the device is determined from the landing candidate area.

[0007] In one embodiment, acquiring soil topography data of the landing candidate area and passability data of the mobile take-off and landing device includes: Acquire remote sensing data on landing safety conditions, landing candidate areas, and passability data of mobile take-off and landing devices; wherein, the remote sensing data includes soil topography data and meteorological data, and the landing safety conditions include at least one of non-landing feasible areas, meteorological safety conditions, and airspace restriction conditions; The process of determining the reachable area of ​​the device from the candidate landing areas based on the passability constraints and the soil topography data includes: Based on the passability data and the landing safety conditions, hard constraints are generated; Based on the hard constraints and the remote sensing data, the reachable area of ​​the device that satisfies the device reachability and landing safety conditions is determined from the candidate landing area.

[0008] In one embodiment, determining the take-off and landing point from the reachable area of ​​the device includes: Based on a multi-objective optimization algorithm, the take-off and landing points are determined from each sub-region of the reachable area of ​​the device; the optimization objectives of the multi-objective optimization algorithm include at least one of minimizing the device arrival time, minimizing the flight path offset distance, and maximizing the suitability of the landing environment.

[0009] In one embodiment, determining the take-off and landing points from various sub-regions of the reachable area of ​​the device based on a multi-objective optimization algorithm includes: Based on all the sub-regions, determine the positive ideal solution and the negative ideal solution of the optimization objective; For each sub-region, the Euclidean distance between the sub-region and the positive ideal solution and the negative ideal solution is determined, and the relative proximity of the sub-region is determined based on the Euclidean distance. Based on the relative proximity, the take-off and landing points are determined from all the sub-regions.

[0010] In one embodiment, the method further includes: For each sub-region, a landing environment suitability score is determined for each node in the sub-region, and the average of the environmental suitability scores of all nodes is taken as the landing environment suitability of the sub-region.

[0011] In one embodiment, determining the landing environment suitability score for each node in the sub-region includes: Determine the correlation between each landing impact characteristic and the landability of the aircraft; Based on the correlation, the weights of each of the landing impact features are determined; For each node, the sum of the products of the feature values ​​of each landing impact feature and the corresponding weights is determined as the landing environment suitability score.

[0012] In one embodiment, after determining the take-off and landing points from the candidate landing area, the method further includes: The takeoff and landing points are visualized; and / or, Based on the on-site survey data of the mobile take-off and landing device, determine whether the take-off and landing point is a target take-off and landing point; wherein, the on-site survey data includes at least the local micro-meteorological data, surface micro-topography, and ground bearing capacity of the take-off and landing point; And / or, Before acquiring the soil topography data of the landing candidate area and the passability data of the mobile take-off and landing device, the method further includes: determining the landing candidate area based on the current mission route and range data of the aircraft; And / or, The mobile take-off and landing device includes an empty state without the aircraft and a loaded state with the aircraft; the passability data includes first passability data when the mobile take-off and landing device is in an empty state and / or second passability data when it is in a loaded state.

[0013] In addition, to achieve the above objectives, this application also proposes an aircraft take-off and landing point selection device, the device including: a memory, a processor and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the aircraft take-off and landing point selection method as described above.

[0014] In addition, to achieve the above objectives, this application also proposes a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the aircraft take-off and landing point selection method described above.

[0015] One or more technical solutions proposed in this application have at least the following technical effects: Compared to related technologies where aircraft take-off and landing point selection algorithms fail to consider whether mobile take-off and landing devices can reach temporary take-off and landing points, the take-off and landing points determined in this application are based on the passability data of mobile take-off and landing devices and the soil and terrain data of landing candidate areas. The reachable areas of the devices are determined from the landing candidate areas, thus incorporating the accessibility of the vehicle into the location selection factors. This can provide reliable take-off, landing and operation service guarantees for temporary take-off and landing of aircraft involving mobile take-off and landing devices, thereby expanding the operating scenarios of aircraft. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the first embodiment of the aircraft take-off and landing point selection method of this application; Figure 2 This is a flowchart illustrating the second embodiment of the aircraft take-off and landing point selection method of this application; Figure 3 This is a flowchart illustrating the third embodiment of the aircraft take-off and landing point selection method of this application; Figure 4 This is a flowchart illustrating the fourth embodiment of the aircraft take-off and landing point selection method of this application; Figure 5 This is a flowchart illustrating the fifth embodiment of the aircraft take-off and landing point selection method of this application.

[0019] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0021] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0022] With the development of low-altitude aircraft, the number of manned or unmanned aircraft such as helicopters, multi-rotor aircraft, and eVTOLs operating in urban and other environments will increase significantly in the future. Helicopters, multi-rotor aircraft, and eVTOLs typically need to reserve sufficient fuel / electricity to return to their original or nearby airports after completing their missions. If they cannot return normally, they need to use temporary take-off and landing point selection algorithms to choose a temporary alternate landing point that meets the aircraft's landing requirements. For eVTOLs, in particular, they may face challenges such as uneven distribution of take-off and landing sites, difficulties landing when performing temporary flight missions (such as emergency rescue, accident rescue, and material transfer) in remote areas or on uneven surfaces without available take-off and landing conditions.

[0023] Mobile takeoff and landing (MRT) systems are rapidly deployable temporary takeoff and landing sites developed for scenarios where landing is not possible. This allows them to provide timely takeoff and landing support for helicopters, multirotor aircraft, and even eVTOLs. MRT systems typically consist of a vehicle and a landing platform. The vehicle can be a ground vehicle such as a car or a waterborne vehicle such as a ship. The landing platform usually employs a modular design, allowing it to be transported to the required location like a container and deployed into a usable landing pad within minutes using automated systems or manually.

[0024] In related technologies, temporary take-off and landing site selection algorithms only support the selection of temporary take-off and landing points that meet the conditions of ground flatness and soil bearing capacity required for aircraft landing in complex terrain environments. However, they fail to fully consider whether mobile take-off and landing devices can reach the selected temporary take-off and landing points, nor do they consider whether mobile take-off and landing devices carrying aircraft can transfer aircraft from temporary take-off and landing points to fixed airports. Therefore, temporary take-off and landing site selection algorithms are difficult to apply to temporary site selection scenarios involving mobile take-off and landing devices.

[0025] To this end, this application provides a solution in which the determined take-off and landing point belongs to the area accessible to the device, that is, whether the vehicle's mobility is accessible is taken into account in the site selection factors. This can provide reliable take-off, landing and operation service guarantees for the temporary take-off and landing of aircraft involving mobile take-off and landing devices, thereby expanding the operating scenarios of aircraft.

[0026] The technical solution of this application and how it solves the above-mentioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0027] Before providing a further detailed description of the embodiments of this application, the nouns and terms used in the embodiments of this application will be explained. The nouns and terms used in the embodiments of this application shall be interpreted as follows: Remold Cone Index (RCI): The RCI measures the bearing capacity of soil and is determined based on the correlation between soil type and moisture index. The magnitude of the RCI directly affects the safety of mobile take-off and landing equipment deployment in the corresponding area and the safety of aircraft take-off and landing.

[0028] Furthermore, the solution provided in this application can be applied to emergency landing, relay flight, and other application scenarios of vertical takeoff and landing aircraft such as eVTOL. To better understand the solution provided in this application, the following explanation uses eVTOL as an example and combines it with a specific application scenario.

[0029] When eVTOL performs temporary and unconventional flight missions such as emergency rescue and medical care, the mission area usually does not have a fixed take-off and landing site, and the mission distance is greater than the maximum operating range of a single eVTOL flight. In this case, multiple temporary parking aprons are set up along the mission route through multiple mobile take-off and landing devices to obtain multiple take-off and landing points. This allows eVTOL to reach the mission destination by relaying flights between multiple temporary parking aprons, effectively expanding the eVTOL operation scenarios.

[0030] It is understood that the above is only one example, and this embodiment is not limited here.

[0031] Based on this, embodiments of this application provide a method for selecting aircraft take-off and landing points, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the aircraft take-off and landing point selection method of this application.

[0032] In this embodiment, the aircraft take-off and landing point selection method includes steps S10 to S20: Step S10: Obtain soil topography data and mobility data of the mobile take-off and landing device for the candidate landing area.

[0033] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a server, vehicle-mounted / airborne computer, cloud platform, etc., or a mobile terminal such as a tablet computer, personal computer, mobile phone, etc., or an electronic device capable of realizing the above functions, such as an aircraft take-off and landing point selection device, etc. The following uses an aircraft take-off and landing point selection device as an example to describe this embodiment and the following embodiments.

[0034] The landing candidate area is the region near the current mission flight path that the aircraft can choose to land in while flying its current mission flight path. Therefore, the landing candidate area extends along the aircraft's current mission flight path, with the current mission flight path as its central axis, and the distance between its boundary line and the central axis is no greater than a preset offset distance. In one example, for eVTOL, the preset offset distance could be 30 km.

[0035] It is understandable that the preset offset distance can be adjusted according to the type of aircraft, remaining range, and requirements for safe landing. In one specific embodiment, before step S10, the method further includes: determining a landing candidate area based on the aircraft's current mission route and range data.

[0036] It should be noted that the range data can be the aircraft's effective range, which is the maximum flight distance achievable under specific conditions. For relay flights, since the aircraft cannot reach the mission destination directly in one flight, the length of the landing candidate area along the current mission route is set according to the flight mission, the aircraft's effective range, and the corresponding safe landing requirements when implementing the method provided in this embodiment during the pre-flight planning phase. For example, in one example, the length of the landing candidate area along the current mission route is between 50-100 km.

[0037] Alternatively, the range data can also be the aircraft's remaining range, which is the distance the aircraft can fly from its current position after exhausting its remaining available fuel, electricity, or hydrogen fuel / other clean energy. In scenarios where an emergency landing is required due to weather changes at the destination or a temporary change in the aircraft's flight mission, when implementing the method provided in this embodiment, the length of the landing candidate area extending along the current mission route and / or the preset offset distance are set according to the flight mission, the aircraft's remaining range, and the corresponding safe landing requirements.

[0038] Soil topographic data includes at least topographic elevation data and soil mechanical strength data. The topographic elevation data describes the topographic relief variations of the landing candidate area, thus displaying its three-dimensional morphology. The soil mechanical strength data describes the soil mechanical strength of each plot within the landing candidate area. Therefore, soil topographic data is a digital map, and the environmental factors for each pixel in the map include at least elevation data and a soil mechanical strength value. Alternatively, soil topographic data can also be extracted from remote sensing data of the landing candidate area. It should be noted that the soil mechanical strength data can be the soil conic index.

[0039] Mobile takeoff and landing (MRT) systems provide ground air traffic control and operational support services for vertical takeoff and landing (VTOL) aircraft during operation. They enable the deployment and folding of mobile airports and guide the landing of eVTOL aircraft. MRT systems are rapidly deployable and highly mobile, bringing takeoff and landing capabilities to any location where needed. For small rotorcraft, the MRT system can be a mobile drone swarm. For helicopters or eVTOLs, the MRT system can include vehicle-mounted or seaplane-based mobile airports. It should be noted that the MRT system can be equipped with aircraft maintenance and repair components and / or aircraft securing components. The aircraft maintenance and repair components are used for fault detection, calibration, maintenance, and refueling / charging operations. Thus, the aircraft can temporarily land on the MRT system, and after necessary maintenance, repairs, or refueling, it can take off again to continue its flight mission. The aircraft securing components are used to secure the aircraft to the MRT system, allowing the MRT system to transport the aircraft to other airports. Therefore, depending on whether an aircraft is loaded, a mobile takeoff and landing device (MTD) includes an empty state without an aircraft and a loaded state with an aircraft. The empty state is the state without an aircraft, while the loaded state is the state where the aircraft is secured to the MTD by the aircraft fixing components. Of course, when there is no need to transfer the aircraft, the MTD's passability data is the passability data of the MTD itself, i.e., the first passability data in the empty state. However, when an aircraft needs to be transferred, the MTD's passability data is the second passability data of the MTD and the aircraft as a whole after the aircraft is loaded.

[0040] For mobile take-off and landing devices with vehicles as the vehicle body, the first passability data and the second passability data refer to the ability to traverse various types of roads and / or off-road areas and / or overcome ground obstacles under a certain vehicle load. Specifically, the first passability data and the second passability data include, but are not limited to, weight, overall dimensions, minimum ground clearance, approach angle, departure angle, longitudinal clearance angle, minimum turning radius, maximum gradeability, maximum wading depth, and maximum output horsepower.

[0041] For mobile take-off and landing devices whose vehicle is a ship, the mobility data of the mobile take-off and landing device is the ship's navigation performance data. Specifically, the first mobility data and the second mobility data include, but are not limited to, draft, ship length, maximum height above water, and turning diameter.

[0042] Step S20: Based on passability data and soil topography data, determine the reachable area of ​​the device from the landing candidate area.

[0043] Step S30: Determine the take-off and landing points from the area accessible to the device.

[0044] The reachable area of ​​the device refers to the area that the mobile take-off and landing device can reach based on the mobility of the vehicle. If the take-off and landing point is within the reachable area, then it is feasible for the mobile take-off and landing device to travel from its initial location to the take-off and landing point in a real-world environment. In this embodiment, the initial location is the departure point or current location of the mobile take-off and landing device.

[0045] Understandably, in multi-objective optimization location selection algorithms, whether the take-off and landing point belongs to the reachable area of ​​the device can be used as a constraint. However, verifying the location after selection reduces overall efficiency, and using it as a constraint increases the computational load of the multi-objective optimization location selection algorithm. Therefore, in this embodiment, after obtaining the mobility data and soil topography data of the mobile take-off and landing device, mobility analysis is first performed through calculation, simulation, or modeling to determine the reachable areas that meet the accessibility requirements from the landing candidate areas. That is, areas inaccessible to the mobile take-off and landing device due to the vehicle's mobility are removed from the landing candidate areas. Then, the location selection algorithm is used to select the take-off and landing points from the reachable areas.

[0046] Passability analysis can specifically involve simulation or modeling operations, or it can be filtered through hard constraints. For example, for a mobile take-off and landing device with a vehicle as the vehicle, step S20 specifically includes steps S21 to S22: Step S21: Based on the passability data, obtain the passability constraints.

[0047] Step S22: Based on passability constraints and soil topography data, determine the reachable area of ​​the device from the landing candidate area.

[0048] Specifically, for mobile take-off and landing devices with vehicles as the vehicle body, corresponding passability constraints can be constructed based on the vehicle's first passability data and / or second passability data. For example, specific passability constraints can be constructed based on various indicators in the passability data, such as dimensional constraints, minimum turning radius constraints, maximum gradeability constraints, and maximum wading depth constraints. Among these, dimensional constraints can limit the width and height of the roads the vehicle can pass through; minimum turning radius constraints can limit the curvature of curves the vehicle can navigate, filtering out narrow roads or intersections with insufficient turning space; maximum gradeability constraints directly define the maximum gradient the vehicle can travel on, filtering out overly steep mountain roads or slopes; and maximum wading depth constraints define the maximum water depth the vehicle can pass through, used to eliminate flooded sections or shallow areas.

[0049] Then, these accessibility constraints are applied to the soil topography data, and all areas that meet the accessibility constraints are selected through spatial analysis or filtering algorithms, thereby determining the reachability range of the mobile take-off and landing device and obtaining the reachable area of ​​the device.

[0050] For landing candidate areas with road systems, device accessibility includes accessibility via the road system. This measures the feasibility of the mobile take-off and landing device (MRT) reaching its destination and deploying from its initial location using the road system. In this case, the aforementioned dimensional constraints, minimum turning radius constraints, and maximum gradeability constraints can be represented by road network accessibility constraints. Road network accessibility measures which areas within the landing candidate areas can be effectively covered by MRT deployed on the road network. The road network accessibility of each site can be specifically filtered using road network accessibility constraints.

[0051] In one specific implementation, in the digital map, buffer zones are created on both sides of the landing candidate area along paved or unpaved road lines based on the road network vector and the minimum turning radius of the mobile take-off and landing device. The radius of the buffer zone is R, and R satisfies: ;in, The minimum turning radius of the mobile take-off and landing device. For safety margin. In one example, The value of is 5, or for roads in flat, open terrain such as the Gobi Desert, then The value of can be increased accordingly. Understandably, the minimum turning radius is the minimum spatial diameter required for a vehicle to make a U-turn on the spot or on a narrow road, enter the work site, and be deployed and retrieved. It is the spatial threshold for the mobile take-off and landing device to maneuver and deploy within space. In actual operation, a safety buffer space must be reserved to prevent collisions between the mobile take-off and landing device and road edges or other obstacles due to operational errors or uneven ground conditions.

[0052] The buffer zone represents the geographical space within which the mobile take-off and landing device (MRT) can theoretically be safely operated directly from the road. Deployable areas with sufficient operational space near the road are selected based on the buffer zone, thereby generating the first binary mask. : ; The system spatially categorizes candidate landing areas into two types: areas with a value of 1 indicate that the mobile take-off and landing system (MRT) can be reached along the network and operations can be conducted within this area. These areas will be reserved for further evaluation in subsequent site selection analysis. Areas with a value of 0 indicate that the MRT cannot be safely reached directly along the network, or cannot be deployed there.

[0053] Alternatively, for aircraft such as eVTOLs, their landing candidate areas may lack road systems and rely on the vehicle's off-road capabilities. In this case, slope accessibility can be used to measure whether a certain area exceeds the maximum climbing ability of the mobile takeoff and landing device, thus allowing for screening based on slope constraints. Of course, in some special cases, the slope of specific road sections may exceed the vehicle's maximum climbing gradient, so both road network accessibility and slope accessibility can be considered simultaneously.

[0054] In one specific embodiment, the maximum climbing angle of the mobile take-off and landing device is used. Using a threshold value, the digital map is filtered to generate a second binary mask. : ; Clearly, the area with a slope less than or equal to the maximum climbing ability of the mobile take-off and landing device is 1, otherwise it is 0. In one example, Clearly, it spatially divides the candidate landing areas into two categories: areas with a value of 1 represent those that do not exceed the maximum climbing capacity of the mobile take-off and landing device (MTD), and are passable by the MTD. These areas will be retained for further evaluation in subsequent site selection analysis. Areas with a value of 0 represent those that have exceeded the maximum climbing capacity of the MTD, and are difficult for the MTD to pass.

[0055] Furthermore, the vehicle's ability to traverse soft terrain (such as sand, mud, and snow) differs from its ability to traverse hard surfaces. Additionally, mobile take-off and landing systems (MTLS) impose minimum ground pressure requirements during aircraft take-off and landing operations. Therefore, it is necessary to assess whether a given area meets the MLS's passability requirements and / or minimum ground pressure requirements during operation. This can be achieved through land bearing capacity constraints.

[0056] In one specific implementation, taking eVTOL as an example, the sum of the self-weight of the mobile take-off and landing device and the dynamic load during eVTOL take-off and landing is taken as the minimum total weight of the temporary take-off and landing point. Combined with the ground contact area of ​​the mobile take-off and landing device during operation, the minimum pressure requirement of the mobile take-off and landing device on the ground is calculated: ; in, To meet minimum pressure requirements, Minimum gross weight for temporary take-off and landing points. This represents the ground contact area during the operation of the mobile take-off and landing device. Based on the soil cone index (RCI) map in the digital map of the landing candidate area, the minimum required soil cone index value is calculated: ; in, The minimum required soil conic index value is then used to filter the digital map, generating a third binary mask. : ; It spatially divides the landing candidate area into two categories: a value of 1 indicates that the area meets the minimum pressure requirements for the mobile take-off and landing device (MTD), and the MTD can operate in this area. A value of 0 indicates that the area does not meet the minimum pressure requirements for the MTD, and the MTD can hardly operate in this area.

[0057] Understandably, after obtaining the first, second, and third binary masks, logical multiplication can be performed on these masks to generate a passability mask for the landing candidate region. This passability mask is then used to process the aforementioned digital map to eliminate unreachable areas and thus determine the reachable areas for the device.

[0058] After determining the accessible area of ​​the device, a suitable sub-area can be selected as the take-off and landing point using aircraft take-off and landing point selection methods. The mobile take-off and landing device can be deployed at the take-off and landing point for temporary aircraft take-off and landing operations. Specifically, after obtaining the accessible area of ​​the device, it can be divided into... Sub-regions Then, take-off and landing points are determined from each sub-region of the area accessible by the device.

[0059] It is easy to see that the take-off and landing points determined in this embodiment are based on the passability data of the mobile take-off and landing device and the soil and topography data of the landing candidate area. The reachable area of ​​the device is determined from the landing candidate area, thus incorporating the accessibility of the vehicle into the site selection factors. This can provide reliable take-off, landing and operation service guarantees for the temporary take-off and landing of aircraft involving mobile take-off and landing devices, thereby expanding the operational scenarios of aircraft. Furthermore, this embodiment uses the mobility data of the mobile take-off and landing device and the soil and topography data of the landing candidate area to determine the reachable area of ​​the mobile take-off and landing device from the landing candidate area, and then determines the take-off and landing point from the reachable area. This will eliminate the inaccessible area of ​​the device from the site selection process, thereby improving the efficiency of site selection.

[0060] Furthermore, this embodiment addresses the needs of eVTOL and other aircraft performing temporary take-off and landing missions in areas lacking fixed take-off and landing sites, or requiring mid-flight charging / refueling / addition of fuel en route to their final destination. Considering the accessibility of mobile take-off and landing devices for eVTOLs and other aircraft, it provides a method for selecting aircraft take-off and landing points. This method solves the inefficiency and low flexibility of relying on pre-set stop points based on human experience when using mobile take-off and landing devices to support temporary take-off and landing missions in the field. It also addresses the issues of refueling and ground support for eVTOLs and other aircraft during long-distance relay flights. Particularly for eVTOLs, this embodiment effectively improves their take-off and landing flexibility and operational efficiency, reduces their dependence on fixed take-off and landing sites, and provides comprehensive take-off, landing, and operational service guarantees for customized travel in areas lacking fixed take-off and landing sites, thus expanding the operational scenarios for eVTOLs.

[0061] In addition, for the aircraft take-off and landing site selection method, factors such as airspace clearance and meteorological conditions also need to be considered. As one option in this embodiment, airspace clearance and meteorological conditions can be considered as factors in step S30. Alternatively, based on the above embodiments, a second embodiment of the aircraft take-off and landing site selection method of this application is proposed. In the second embodiment of this application, the content that is the same as or similar to the first embodiment described above can be referred to the above description and will not be repeated hereafter. Please refer to... Figure 2 , Figure 2 A flowchart illustrating a second embodiment of the aircraft take-off and landing point selection method is shown.

[0062] In this embodiment, the method for selecting the take-off and landing point of an aircraft includes the following steps: Step S10': Obtain remote sensing data on landing safety conditions, landing candidate areas, and passability data of the mobile take-off and landing device.

[0063] The remote sensing data includes soil topography data and meteorological data, and the landing safety conditions include at least one of non-landing feasible areas, meteorological safety conditions, and airspace restriction conditions.

[0064] Step S21': Based on the passability data and landing safety conditions, generate hard constraints; Step S22': Based on hard constraints and remote sensing data, determine the device reachable area that meets the device reachability and landing safety conditions from the landing candidate area.

[0065] Step S30: Determine the take-off and landing points from the area accessible to the device.

[0066] Specifically, remote sensing data refers to images formed by detecting and recording electromagnetic wave information reflected or radiated by objects at a distance using remote sensing technology. It should be noted that remote sensing data includes not only the images themselves but also a large amount of descriptive data. Remote sensing data includes soil topography data and meteorological data. Specifically, in this embodiment, remote sensing data includes, but is not limited to, 3D reality models, land cover types, geological hazard risks, soil conic index, road network vector files, and meteorological data.

[0067] Land cover types include, but are not limited to, categories such as water bodies, forests, buildings, and grasslands. Road network vector files include, but are not limited to, attribute data such as road grade and width. The 3D reality model utilizes high-precision satellite stereo imaging technology to generate a model that visually reflects the location, geometry, surface texture, and attribute information of geographic elements. Traditional digital elevation models and digital surface models can only evaluate basic terrain parameters such as slope and elevation, while the 3D reality model can evaluate detailed information such as surrounding obstacles (e.g., power lines, elevated structures), spacing, and surface features in various parts of the landing candidate area. In one example, the 3D reality model in this embodiment uses a spatial resolution of 2 meters to ensure the precision of terrain analysis. Land cover types are derived from multispectral and hyperspectral remote sensing image data provided by integrated communication, navigation, and remote sensing satellites, which can identify different types of land cover information such as forests, farmland, cities, water bodies, and bare land. Geological hazard data directly affects the safety of mobile take-off and landing equipment operations. The location and type of geological hazard points within the candidate area, including land subsidence, landslides, and debris flows, can be determined through terrain features (slope, aspect, fissures, landslide traces, etc.) in the remote sensing data. Of course, in some specific implementations, the mobile take-off and landing device is equipped with components such as vehicle-mounted radar, which can also conduct on-site surveys and supplements of geological hazard data by monitoring ground micro-topography. RCI infers soil type and moisture status based on remote sensing images provided by the integrated communication, navigation, and remote sensing satellite, and estimates these based on topography, vegetation cover, precipitation, and hydrological information. The integrated communication, navigation, and remote sensing satellite employs active and passive observation methods to acquire meteorological elements such as the atmosphere, clouds, precipitation, and wind field. Specifically, the satellite, equipped with payloads such as infrared radiometers, microwave radiometers, and multispectral sensors, acquires meteorological data such as cloud height, precipitation intensity, cloud cover, and surface temperature; the satellite, equipped with synthetic aperture radar and lidar, acquires wind field information, cloud information, visibility, water accumulation range, and ground moisture changes in the landing candidate area; in addition, it can also achieve all-weather, all-time integrated detection through integrated detection of "global navigation satellite inversion signals, atmospheric occultation, and ionizing occultation," acquiring real-time meteorological data such as ground wind field, soil moisture, atmospheric temperature, and humidity, and can collaborate with ground stations to improve data accuracy and real-time performance. Therefore, meteorological data includes wind speed, wind direction, cloud distribution, rainfall intensity, visibility, cloud base height, lightning activity, temperature, and humidity in the candidate landing areas. Wind speed data for the candidate landing areas includes, but is not limited to, annual average wind speed, monthly average wind speed, and daily average wind speed.

[0068] Understandably, after acquiring the raw remote sensing data, in order to eliminate the influence of different data units and magnitudes and make them comparable, the data needs to be normalized (standardized) to obtain remote sensing data, ensuring that these data can be identified and processed by the aircraft take-off and landing point selection equipment.

[0069] Specifically, for remote sensing data, the following data preprocessing can be performed: 1) Spatial Data Preparation: Create a regular raster grid model covering the entire landing candidate area. Transform all attribute data from the remote sensing data to the same projected coordinate system, such as the Universal Transverse Mercator Grid System (UTM). The spatial resolution is normalized to 2 meters. Based on the flight path buffer and geographic boundaries, integrate the various attribute data from the remote sensing data as landing impact feature layers into the regular raster grid model, thus obtaining the landing candidate area model for data processing. In subsequent data processing, the landing candidate area model is used to represent the landing candidate area.

[0070] 2) Data abstraction and reorganization: The various attribute data in remote sensing data can be divided into continuous numerical data, discrete categorical variables and binary variables.

[0071] The continuous numerical data includes elevation-related data (such as slope, undulation, etc.), soil conic index, wind speed, temperature / humidity, cloud base height, visibility, and rainfall intensity, forming an original continuous numerical feature matrix that can be subsequently standardized.

[0072] Discrete categorical variables include land cover type, wind direction, and cloud cover. For land cover type and cloud cover, the original classifications are recoded into adaptive scores. For example: bare soil = 1.0, grassland = 0.8, farmland = 0.6, forest = 0.3, water body = 0.0. Cloud cover rate is used to represent cloud cover; this score is based on prior knowledge and will be adjusted in subsequent weight calculations. For wind direction, east-west and north-south component rasteresms are used to preserve wind direction and speed information, and these are continuous values.

[0073] Binary variables include geological hazards, which are generated as 0 / 1 grids based on whether there are geological hazards or not.

[0074] 3) Standardization / Normalization: All abstracted continuous numerical data are transformed to the range [0,1] to eliminate the influence of dimensions. For categorical and binary variables, no further normalization is needed, as one-hot encoding or 0 / 1 values ​​already possess a unified scale. For continuous numerical data, this embodiment uses the Min-Max standardization method, with the specific formula as follows: ; in, For data The original direction. Then using The data undergoes orientation unification processing. For cost-related indicators such as slope, wind speed, and rainfall intensity, lower values ​​are desirable. Therefore, for any of these data points, their orientation is unified as follows: ; To ensure a unified direction after processing.

[0075] For benefit-oriented indicators such as soil conic index and visibility, higher values ​​are desirable; therefore, maintaining... Original direction, i.e.: After orientation unification processing, all raster layers with values ​​in the range [0,1] constitute a multidimensional dataset, where each spatial location (cell) corresponds to a feature vector, i.e. .

[0076] In this embodiment, hard constraints are generated based on accessibility data and landing safety conditions. All infeasible regions are then eliminated from the landing candidate regions, generating a "feasible region mask." It is understood that infeasible regions include areas that do not meet the device accessibility requirement and areas that do not meet either the landing safety condition requirement. Specifically, areas that do not meet device accessibility requirements are those that the device cannot reach using the vehicle's mobility, and areas that do not meet landing safety conditions are those where takeoff and landing operations are prohibited for aircraft landing safety. The hard constraints include landing safety constraints and accessibility constraints. For accessibility constraints, please refer to the first embodiment; they will not be repeated here.

[0077] Corresponding to landing safety conditions, landing safety constraints include at least one of non-landing feasible area constraints, meteorological safety constraints, and airspace restriction constraints.

[0078] Taking a vehicle as an example of a mobile take-off and landing device: For constraints on non-landing feasible areas: Based on the land cover classification map, categories such as water bodies, swamps, and dense forests are directly extracted, and areas of these categories are excluded from the landing candidate areas, thereby generating a fourth binary mask. The fourth binary mask is: ; Clearly, the areas with a value of 0 represent land cover categories such as water, swamp, and dense forest, where aircraft cannot land. Conversely, the areas with a value of 1 represent other land cover categories, which are suitable for aircraft landing.

[0079] Regarding meteorological safety constraints: To ensure the safe operation of aircraft, areas that meet the minimum meteorological standards for aircraft operation should be selected based on the capabilities and characteristics of the aircraft to be supported by the mobile take-off and landing system.

[0080] For a certain type of eVTOL, according to visual flight rules, visibility should be ≥5000 meters for flights with a mean sea level (MSL) below 3000 meters, and ≥8000 meters for flights with an MSL of 3000 meters and above, with a wind speed ≤65 knots. Therefore, by screening the landing candidate area model, a fifth binary mask can be generated. : ; Clearly, values ​​of 1 indicate that the aircraft meets the minimum meteorological standards for operation. Values ​​of 0 indicate that the aircraft does not meet the minimum meteorological requirements.

[0081] Regarding airspace restrictions, in order to ensure the safe operation of aircraft, the airspace near temporary take-off and landing points should meet the clearance requirements and meteorological safety requirements of the aircraft's take-off climb / approach surface, and avoid no-fly zones and temporary no-fly zones. Therefore, it includes clearance constraints and no-fly zone constraints.

[0082] Different aircraft operating with varying performance requirements have different clearance requirements for climb / approach obstacle limitation surfaces. For example, for a certain type of eVTOL, the obstacle limitation surface length is specified as 1220 meters and the slope as 12.5%. Using a landing candidate area model, regions meeting the eVTOL climb / approach obstacle limitation surface requirements are selected, generating a sixth binary mask. : ; Clearly, the part with a value of 1 satisfies the clearance constraint, while the part with a value of 0 does not.

[0083] Furthermore, aircraft are prohibited from operating within designated no-fly zones and temporarily designated no-fly zones. Therefore, the site selection for mobile take-off and landing (MTOD) devices should exclude no-fly zones and select areas that meet the operational airspace restrictions for electric vertical take-off and landing (eVTOL) aircraft, thereby generating a 72-value mask. : ; Clearly, the part with a value of 1 is outside the no-fly zone and can be used for aircraft take-off and landing, while the part with a value of 0 is inside the no-fly zone and therefore cannot be used for aircraft take-off and landing.

[0084] In this specific embodiment, a total feasible region mask can be generated: by performing logical multiplication on the aforementioned masks, a total feasible region mask within the landing candidate region is generated.

[0085] .

[0086] Then, the candidate landing region models are filtered using the total feasible region mask.

[0087] In this embodiment, hard constraints are generated using the mobility data and landing safety conditions of the mobile take-off and landing device to filter the candidate landing areas, resulting in reachable areas that meet both the device's reachability and landing safety conditions. Then, take-off and landing points are determined from each sub-region of the reachable area. It is clear that filtering by hard constraints first reduces the computational cost of subsequent steps in determining suitable take-off and landing points, thus improving the efficiency of take-off and landing point selection decisions.

[0088] Furthermore, for step S30, specifically, a model of the aircraft can be constructed, and a suitable take-off and landing point can be determined through simulation or modeling using a model of the reachable area of ​​the device. Alternatively, after setting the target, a suitable device loitering area can be obtained by using a weighted summation method, that is, by linearly combining multiple targets into a single target according to their weights, or by using the ɛ-constraint method.

[0089] Alternatively, the takeoff and landing points can be determined using a multi-objective optimization algorithm. Therefore, based on the above embodiments of this application, a third embodiment of this application is proposed. In the third embodiment of this application, content that is the same as or similar to the above embodiments can be referred to the above description, and will not be repeated hereafter.

[0090] In this embodiment, when the aircraft take-off and landing point selection device executes step S30, it specifically performs the following: based on a multi-objective optimization algorithm, it determines the take-off and landing points from each sub-region of the device's reachable area.

[0091] The optimization objectives of the multi-objective optimization algorithm include at least one of minimizing device arrival time, minimizing flight path offset distance, and maximizing landing environment suitability.

[0092] Specifically, for each sub-region, the device arrival time is the time it takes for the mobile take-off and landing device to travel from its initial location to the sub-region. The flight path offset distance is the distance the sub-region deviates from the aircraft's current mission flight path, measuring the degree of fit between the aircraft's landing trajectory and the current mission flight path. Landing environment suitability measures the impact of various attribute data in the remote sensing data for that sub-region on the aircraft's landing.

[0093] subregion For example, regarding the device arrival time Specifically, Geographic Information System (GIS) network analysis can be used to calculate the starting point from the mobile take-off and landing device. To sub-region The shortest travel time to the nearest road access point, i.e.: ; It is evident that the arrival time of the device measures the arrival time cost of the mobile take-off and landing device.

[0094] Regarding the distance of flight path deviation Specifically, sub-regions can be calculated. All nodes within the current mission's flight path The average distance, i.e. ; in, sub-region Inner 1 node sub-region The total number of internal nodes, Used to represent nodes To the current mission flight path The distance between them.

[0095] It should be noted that nodes within a sub-region can be defined as each pixel in the GIS network. Alternatively, the sub-region can be divided into multiple non-overlapping triangles, with the vertices of the triangles serving as nodes. The following section will explain the concept of each pixel as a node.

[0096] Clearly, the deviation distance of the flight path The smaller the value, the smaller the sub-region. Current mission flight path The higher the fit, the better.

[0097] In one specific implementation, the suitability of the landing environment can be assessed by constructing a quantitative model, risk distribution map, and other methods to evaluate the characteristics of the impact on landing.

[0098] Alternatively, in another specific embodiment, the suitability of the landing environment for each sub-region can be determined in the following manner. In this case, the method further includes step A40: Step A40: For each sub-region, determine the landing environment suitability score for each node in the sub-region, and take the average of the environmental suitability scores of all nodes as the landing environment suitability.

[0099] As mentioned earlier, this embodiment treats each pixel in the GIS network as a node. For each pixel, the suitability of the landing environment can be determined in the following ways. Please refer to [link to relevant documentation]. Figure 3 Before step A40, the method further includes steps A10 to A30: Step A10: Determine the correlation between landing impact characteristics and aircraft landability.

[0100] Step A20: Based on the correlation, determine the weights of each landing impact feature.

[0101] Step A30: For each node, the sum of the products of the feature values ​​of each landing impact feature and the corresponding weights is determined as the landing environment suitability score.

[0102] Specifically, in this embodiment, the landing impact features are the attribute data in the remote sensing data. The weights of relevant landing impact features within a pixel are determined to characterize the relative importance of each landing impact feature to the landing environment, i.e., the correlation degree. Then, a comprehensive score for each pixel is calculated, i.e., the landing environment suitability score. Finally, the average of the landing environment suitability scores of all pixels is taken as the landing environment suitability score.

[0103] The weights of each landing impact feature on the landing impact can be calculated using methods including, but not limited to, the analytic hierarchy process (AHP), expert scoring, entropy weighting, and principal component analysis.

[0104] Alternatively, as an alternative, it can be determined using grey relational analysis: First, a sample set is constructed, comprising multiple sample regions and remote sensing data for each region. Based on the sample set, a multidimensional environmental and meteorological feature matrix is ​​then constructed. ;in, This represents the total number of sample regions. The total number of features.

[0105] Then construct a reference sequence to represent the ideal situation for each landing impact feature, i.e. Each landing impact feature is set to its theoretical optimal value of 1.

[0106] Then calculate the difference between each sample region and the ideal value. The difference matrix is ​​obtained. Difference matrix elements in satisfy: ; in, For the first The first sample One characteristic of the impact of landing. For the first Ideal values ​​for the characteristics of a landing effect.

[0107] Then calculate the global range. The global range includes the maximum range. and minimum range : ; ; Then the resolution coefficient is introduced. Calculate the correlation coefficient: ; in, For the first The first sample The correlation coefficients of the landing impact characteristics. Among them, =0.5. Of course, in other examples, Other values ​​are also possible.

[0108] After obtaining the correlation coefficients, the correlation coefficient matrix can be constructed. .

[0109] Then, for each landing impact feature, the mean of the correlation coefficients across all sample regions is calculated to obtain the overall correlation between that landing impact feature and the reference sequence. : ; Indicates landing impact characteristics The overall correlation with the reference sequence. The grey correlation consisting of all landing impact features is... , .

[0110] Finally, weight normalization calculations are performed to obtain the grey relational analysis weights corresponding to each landing impact feature. : ;in, This represents the sum of the overall correlation of all landing impact features.

[0111] In this selection, the grey relational analysis weights can be... As the weight of the corresponding landing impact characteristics.

[0112] Alternatively, as another option, a multidimensional environmental and meteorological feature matrix can be constructed from the aforementioned sample set. Furthermore, the weights can be determined using the random forest feature importance analysis method.

[0113] Specifically, the first step is to generate a comprehensive suitability score matrix. Comprehensive Suitability Score Matrix Each element : That is, the first The mean of all landing impact features of the nth sample is used as the nth sample. The initial overall score for each element.

[0114] Retrain the random forest model. Since the target variable is continuous, a regression random forest model can be used. The key parameters of the regression random forest model are: number of trees T = 500; maximum depth: Feature sampling ratio: 。

[0115] Then, feature importance is calculated: for each tree t, the prediction error of the out-of-bag samples is calculated. Characteristics of the impact on landing Random permutation, calculate the error after permutation. ; Calculate landing impact characteristics Importance Finally, regarding importance Normalization is performed to obtain random weights. .

[0116] in, ; .

[0117] In this selection, random weights can be used. As the weight of the corresponding landing impact characteristics.

[0118] Alternatively, as another option, the weights and random weights of the grey relational analysis method can be combined for calculation: ;in Let be the fusion coefficient, and .

[0119] for The overall score reconstruction error is minimized using a grid search method (step size 0.1): ; in, Multidimensional environmental and meteorological feature matrix The Middle The column containing each feature.

[0120] Finally, the final weights are obtained. , .

[0121] Then, through a weighted linear combination method, the sub-regions are processed. nodes Read the attribute value of the pixel on each landing impact feature layer. Each attribute value is associated with its corresponding weight. Multiply the results and sum all the products to obtain the landing environment suitability score for that pixel. : ; in, For the first The final combined weight of each landing impact feature.

[0122] After the above steps, a continuous raster layer of "Comprehensive Suitability Map" can be output. Continuous raster layer The value range is [0,1]. This layer can intuitively display the overall suitability score of each pixel within the reachable area of ​​the device.

[0123] Then, for the sub-region Suitable landing environment : .

[0124] in, It is a sub-region The total number of pixels within. Obviously. The larger the value, the larger the sub-region. The higher the overall quality of the site, the more suitable it is for aircraft landing.

[0125] In this embodiment, the optimization objectives of the multi-objective optimization algorithm include at least one of minimizing device arrival time, minimizing flight path offset distance, and maximizing landing environment suitability. Of course, in order to determine a better landing environment, the optimization objectives can be added, reduced, or modified to improve the accuracy of temporary take-off and landing point selection.

[0126] In one example, when the weather changes at the destination or the flight mission of the aircraft is temporarily changed, the remaining battery power of the aircraft can be used as a constraint in the multi-objective optimization algorithm to select a landing point in the landing candidate area and guide the aircraft to complete an emergency landing.

[0127] The following description uses the optimization objectives of minimizing device arrival time, minimizing flight path offset, and maximizing landing environment suitability as an example. The multi-objective optimization algorithm in this embodiment is used to sort sub-regions according to priority, including but not limited to multi-criteria compromise solution sorting method, elimination and selection transformation method, preference order structure evaluation method, weighted product method, and ideal solution approximation sorting method. Taking the ideal solution approximation sorting method as an example, in a specific implementation, step S30 specifically includes: Step S31: Based on all sub-regions, determine the positive ideal solution and negative ideal solution of the optimization objective.

[0128] Step S32: For each sub-region, determine the Euclidean distance between the sub-region and the positive ideal solution and the negative ideal solution respectively, and determine the relative proximity of the sub-region based on the Euclidean distance.

[0129] Step S33: Determine the take-off and landing points from all sub-regions based on relative proximity.

[0130] Specifically, the initial decision matrix is ​​first constructed. : ; Then, for the initial decision matrix Vector normalization is performed to eliminate the influence of dimensions. After vector normalization, the [number of vectors] is [number of vectors]. The first scheme is in the The normalized value on each target is : ; In this embodiment, 1≤ ≤3. Furthermore, since the reachable area of ​​the device comprises m sub-regions, there are a total of m solutions, i.e., 1 ≤ ≤m.

[0131] Then construct the weighted normalization matrix. Introducing target preferences. Weighted normalization matrix. Each element : ; in It is the first The preference weights of each objective satisfy .

[0132] It's worth noting that preference weights are set based on the decision-maker's preferences. In one example: if the decision-maker prioritizes the suitability of the landing environment (i.e., high site quality) and the device's arrival time (i.e., rapid arrival), the weights can be set to... If the decision-maker requires the shortest possible route offset distance for a sub-region, it can be set to... .in, To maximize the preference weights for landing environment suitability; To minimize the preference weights for device arrival time, Preference weights are used to minimize the route offset distance.

[0133] Then, the positive and negative ideal solutions are determined. The positive ideal solution is the best-in-sight solution, composed of the optimal values ​​of each objective in the weighted matrix. Since in this embodiment 1 ≤ ≤3, therefore the ideal solution is... satisfy ; Negative ideal solution This is the worst-case scenario. satisfy: ; Then calculate the distance from each solution to the ideal solution.

[0134] Among them, the Euclidean distance to the ideal solution , satisfy:

[0135] Euclidean distance to the negative ideal solution , satisfy:

[0136] Then calculate the first... The relative similarity of the two schemes , satisfy: ; visible, The larger the value, the more significant the effect. The closer it is to the positive ideal solution and the farther it is from the negative ideal solution, the better the overall performance.

[0137] Finally, based on relative closeness The values ​​are sorted from largest to smallest for each sub-region. The one ranked first is the optimal solution. It should be noted that in this embodiment, the determined take-off and landing point can be the optimal solution ranked first, and the solutions ranked second to the other top preset positions can be alternative take-off and landing points. Alternatively, the determined take-off and landing point can also be a set of sub-regions ranked in the top preset position, such as the set of the top 5 sub-regions. This embodiment is not limited to this.

[0138] It is easy to see that in this embodiment, by first filtering the candidate landing areas through hard constraints and then determining the takeoff and landing points through a multi-objective optimization algorithm, computational efficiency can be improved. Furthermore, compared to manual site selection relying on expert scoring, this embodiment finds the optimal solution among multiple objectives through a multi-objective optimization algorithm, thus improving computational efficiency. Different optimization objectives can be configured to adapt to the aircraft's current mission. In addition, this embodiment uses grey relational analysis and / or random forest algorithms to calculate the weights of landing impact features, which has the advantages of not requiring subjective experience judgment, low computational resource consumption, rapid deployment, and rapid response. Therefore, it is suitable for deployment in places with limited computational resources, such as mobile airport devices, thereby expanding operational scenarios.

[0139] In addition, after determining the takeoff and landing points, it is necessary to output the takeoff and landing points to the pilot through various means. For example, the location of the takeoff and landing points can be output via voice announcement. Alternatively, when there is only one takeoff and landing point, i.e., the optimal solution, the takeoff and landing point can be set as the aircraft's destination so that the aircraft can automatically proceed there. Alternatively, the takeoff and landing points can be output for the pilot, control tower personnel, or operators to choose from. Therefore, based on the above embodiments of this application, a fourth embodiment of this application is proposed. In the fourth embodiment of this application, the same or similar content as the above embodiments can be referred to the above description, and will not be repeated hereafter. Please refer to... Figure 4 In this embodiment, after step S30, the method further includes: Step S40: Visualize the take-off and landing points.

[0140] Specifically, when the equipment for selecting aircraft take-off and landing points is a fixed airport control tower or a drone remote control center, in order to facilitate tower operators or drone operators in quickly making decisions about temporary take-off and landing points, it is also necessary to transform complex calculation and analysis results into intuitive information that decision-makers can quickly understand.

[0141] In one specific implementation, according to a preset rendering strategy, the image areas corresponding to the take-off and landing points and alternative take-off and landing points can be rendered on the satellite image map, and at least one of the following can be overlaid and displayed: the current mission route of the aircraft, the location information of the mobile take-off and landing device, and road network data.

[0142] Specifically, based on high-resolution satellite imagery, a gradient color from green through yellow to red can be used to render the top ten sub-regions, overlaying preset flight routes, mobile airport starting points, and road networks to provide tower operators or drone operators with visualized calculation results.

[0143] Alternatively, in another specific implementation, an interactive information panel can be configured on the control tower equipment at a fixed airport or on the drone remote control center to visually display the takeoff and landing points. This interactive information panel can at least include the following information: displaying the area, coordinates, device arrival time, and flight path offset distance of the top ten sub-regions. The values ​​and display effects are shown in Table 1.

[0144] Table 1 Sub-region sorting list

[0145] Alternatively, in another specific embodiment, when the aircraft's take-off and landing point selection device is the aircraft's own flight control calculator or the mobile take-off and landing device's onboard controller, the take-off and landing point can be displayed through the aircraft's navigation display or the mobile take-off and landing device's central control display. Of course, alternative take-off and landing points can also be displayed.

[0146] It is easy to see that this embodiment provides pilots, operators, or tower personnel with clear calculation results by visually outputting the takeoff and landing points, thus providing an intuitive basis for flight decisions and improving information transmission efficiency.

[0147] Furthermore, while remote sensing data can cover vast areas and thus obtain information on candidate landing areas in a single dataset, it is subject to errors and uncertainties. Therefore, based on the first embodiment described above, a fifth embodiment of this application is proposed. In this fifth embodiment, content that is the same as or similar to the above embodiments can be referred to the above description and will not be repeated hereafter. Please refer to... Figure 5 In this embodiment, after step S30, the method further includes: Step S50: Based on the on-site survey data of the mobile take-off and landing device, determine whether the take-off and landing point is to be used as the target take-off and landing point.

[0148] Specifically, after obtaining the takeoff and landing point, the mobile takeoff and landing device moves to the point. Upon arrival at the takeoff and landing point, the mobile takeoff and landing device completes on-site terrain and meteorological surveys of the takeoff and landing point, as well as pre-landing preparations, before the aircraft descends.

[0149] Specifically, the mobile takeoff and landing system utilizes onboard radar, camera modules, environmental pressure sensors, and other surveying equipment, along with on-site personnel, to collect data from actual surveys of the takeoff and landing points. This on-site survey data includes at least local micro-meteorological data, surface micro-topography, and ground bearing capacity. In other words, it involves surveying surface features, airspace conditions, and local micro-meteorological conditions—environmental factors that may affect aircraft takeoff and landing—to determine whether the calculated takeoff and landing point is suitable as a target location.

[0150] Once a suitable target take-off and landing point is identified, the roving take-off and landing system can be deployed within that point. After deployment, the roving take-off and landing system sends landing commands directly to the aircraft, or sends landing commands to the aircraft via a control tower. The roving take-off and landing system then guides the aircraft to a safe landing via wireless communication.

[0151] Of course, if a landing site is no longer a target landing site, the mobile landing device can proceed to an alternative landing site and report to the control tower and / or the aircraft that the landing site is not suitable as a target landing site, so that the aircraft can turn to the alternative landing site.

[0152] It is easy to see that this embodiment conducts on-site surveys of the calculated backup take-off and landing points to verify the accuracy of the results calculated using remote sensing data. This can effectively avoid misjudgments caused by factors such as weather and image resolution, thereby improving the safety of aircraft take-off and landing.

[0153] This application provides an aircraft take-off and landing point selection device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the aircraft take-off and landing point selection method in the above embodiment 1.

[0154] The aircraft take-off and landing point selection equipment in this application embodiment may include, but is not limited to, mobile terminals such as servers, cloud platforms, vehicle / airborne computers, mobile terminals, mobile phones, laptops, vehicle terminals (e.g., vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers.

[0155] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device, or installed from a read-only memory. When the computer program is executed by a processing device, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0156] The aircraft take-off and landing point selection device provided in this application, employing the aircraft take-off and landing point selection method in the above embodiments, can solve the technical problem that the aircraft take-off and landing point selection method is difficult to apply to temporary site selection scenarios involving mobile take-off and landing devices. Compared with the prior art, the beneficial effects of the aircraft take-off and landing point selection device provided in this application are the same as those of the aircraft take-off and landing point selection method provided in the above embodiments, and other technical features in this aircraft take-off and landing point selection device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0157] Among them, the aircraft take-off and landing site selection equipment can be a computing device configured in a mobile take-off and landing device.

[0158] In one embodiment, the mobile take-off and landing device includes a vehicle chassis, a central control unit, and a portable helipad. The vehicle chassis enables the mobile airport to operate on both paved and unpaved surfaces, while the portable helipad facilitates temporary take-off and landing, charging, and rapid maintenance of the eVTOL. The mobile take-off and landing device includes surveying equipment such as vehicle-mounted radar, camera modules, and environmental pressure sensors. This allows for the acquisition of centimeter-level terrain details, such as the height of surrounding small obstacles and surface hardness; and second-level meteorological data, including air pressure, wind shear, and short-duration heavy rainfall, ensuring the safety and reliability of the final site selection for the mobile take-off and landing device. The central control unit of the mobile take-off and landing device acquires remote sensing data from integrated communication, navigation, and telemetry satellites via the cloud and / or the control tower. Applying the aircraft take-off and landing point selection method provided in the aforementioned embodiments, and comprehensively considering constraints such as device passability data and landing safety conditions, it intelligently plans one or more take-off and landing points. Using surveying equipment such as vehicle-mounted radar, camera modules, and environmental pressure sensors, it precisely determines the optimal location for helipad deployment and safe aircraft take-off and landing. Understandably, the aircraft take-off and landing site selection equipment is configured on the mobile take-off and landing device to obtain more detailed data such as the height of ground obstacles, ground hardness, temporary obstacle intrusion, and ambient air pressure, thereby improving the quality of support.

[0159] In addition, portable landing pads can provide temporary take-off and landing, refueling and simple surface inspection services for aircraft such as eVTOL, reducing the selection criteria for natural terrain in the process of selecting take-off and landing sites, and providing strong support for the large-scale operation of electric vertical take-off and landing aircraft in a wider range of scenarios.

[0160] Alternatively, the aircraft take-off and landing site selection equipment can be configured in a control tower or in the cloud. In this case, the central control console includes a local controller, which connects to the aircraft, control tower equipment, or the cloud via a network interface and uploads the survey data of the mobile take-off and landing device. The cloud platform acquires remote sensing data, executes the aircraft take-off and landing site selection method provided in the aforementioned embodiments, and returns the results to the local controller. The central control console then displays the execution results.

[0161] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0162] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the aircraft take-off and landing point selection method described above.

[0163] The computer program product provided in this application can solve the technical problem that the aircraft take-off and landing point selection method is difficult to apply to temporary site selection scenarios involving mobile take-off and landing devices. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the aircraft take-off and landing point selection method provided in the above embodiments, and will not be repeated here.

[0164] The above are only some embodiments of this application and do not limit the scope of protection of this application. All equivalent structural transformations made under the technical concept of this application and using the content of this application specification and drawings, or direct / indirect applications in other related technical fields, are included in the scope of protection of this application.

Claims

1. A method for selecting take-off and landing points for aircraft, characterized in that, The method for selecting the take-off and landing points of the aircraft includes: Acquire soil topography data and mobility data of the mobile take-off and landing device in the candidate landing area; Based on the passability data and the soil topography data, the reachable area of ​​the device is determined from the landing candidate area; The take-off and landing points are determined from the area accessible by the device.

2. The aircraft take-off and landing point selection method as described in claim 1, characterized in that, The process of determining the reachable area of ​​the device from the candidate landing areas based on the passability data and the soil topography data includes: Based on the accessibility data, accessibility constraints are obtained; wherein, the accessibility constraints include at least one of road network accessibility constraints, slope constraints, and land carrying capacity constraints. Based on the passability constraints and the soil topography data, the reachable area of ​​the device is determined from the landing candidate area.

3. The method for selecting take-off and landing points for aircraft as described in claim 1, characterized in that, The acquisition of soil topography data and mobility data of the mobile take-off and landing device in the candidate landing area includes: Acquire remote sensing data on landing safety conditions, landing candidate areas, and passability data of mobile take-off and landing devices; wherein, the remote sensing data includes soil topography data and meteorological data, and the landing safety conditions include at least one of non-landing feasible areas, meteorological safety conditions, and airspace restriction conditions; The process of determining the reachable area of ​​the device from the candidate landing areas based on the passability constraints and the soil topography data includes: Based on the passability data and the landing safety conditions, hard constraints are generated; Based on the hard constraints and the remote sensing data, the reachable area of ​​the device that satisfies the device reachability and landing safety conditions is determined from the candidate landing area.

4. The method for selecting take-off and landing points for aircraft as described in claim 1, characterized in that, Determining the take-off and landing point from the reachable area of ​​the device includes: Based on a multi-objective optimization algorithm, the take-off and landing points are determined from each sub-region of the reachable area of ​​the device; the optimization objectives of the multi-objective optimization algorithm include at least one of minimizing the device arrival time, minimizing the flight path offset distance, and maximizing the suitability of the landing environment.

5. The method for selecting take-off and landing points for aircraft as described in claim 4, characterized in that, The multi-objective optimization algorithm determines the take-off and landing points from each sub-region of the reachable area of ​​the device, including: Based on all the sub-regions, determine the positive ideal solution and the negative ideal solution of the optimization objective; For each sub-region, the Euclidean distance between the sub-region and the positive ideal solution and the negative ideal solution is determined, and the relative proximity of the sub-region is determined based on the Euclidean distance. Based on the relative proximity, the take-off and landing points are determined from all the sub-regions.

6. The aircraft take-off and landing point selection method as described in claim 4, characterized in that, The method further includes: For each sub-region, a landing environment suitability score is determined for each node in the sub-region, and the average of the environmental suitability scores of all nodes is taken as the landing environment suitability of the sub-region.

7. The aircraft take-off and landing point selection method as described in claim 6, characterized in that, The determination of the landing environment suitability score for each node in the sub-region includes: Determine the correlation between each landing impact characteristic and the landability of the aircraft; Based on the correlation, the weights of each of the landing impact features are determined; For each node, the sum of the products of the feature values ​​of each landing impact feature and the corresponding weights is determined as the landing environment suitability score.

8. The method for selecting take-off and landing sites for aircraft as described in any one of claims 1 to 7, characterized in that, After determining the take-off and landing points from the candidate landing areas, the method further includes: The takeoff and landing points are visualized; and / or, Based on the on-site survey data of the mobile take-off and landing device, determine whether the take-off and landing point is a target take-off and landing point; wherein, the on-site survey data includes at least the local micro-meteorological data, surface micro-topography, and ground bearing capacity of the take-off and landing point; And / or, Before acquiring the soil topography data of the landing candidate area and the passability data of the mobile take-off and landing device, the method further includes: determining the landing candidate area based on the current mission route and range data of the aircraft; And / or, The mobile take-off and landing device includes an empty state without the aircraft and a loaded state with the aircraft; the passability data includes first passability data when the mobile take-off and landing device is in an empty state and / or second passability data when it is in a loaded state.

9. An aircraft take-off and landing point selection device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the aircraft take-off and landing site selection method as described in any one of claims 1 to 8.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the aircraft take-off and landing point selection method as described in any one of claims 1 to 8.

Images