Method, device, electronic device and computer-readable storage medium for dividing airspace

Abstract

The present application relates to the field of flight management technology, and proposes a method, device, electronic device, and computer-readable storage medium for dividing airspace, wherein the method includes determining airspace data corresponding to the airspace division in response to an airspace division instruction, wherein the airspace division instruction includes the purpose of airspace use; dividing the airspace data according to the purpose of airspace use to obtain an airspace division result; wherein the airspace division result includes a first result set and a second result set, wherein the first result set includes three-dimensional geometric shapes corresponding to the airspace data, and the second result set includes the relationship between the three-dimensional geometric shapes corresponding to the airspace data. According to an embodiment of the present application, an airspace division standard is proposed by dividing the airspace into a set of universal three-dimensional geometric shapes and giving the positional relationship between the universal three-dimensional geometric shapes, thereby improving the interoperability of airspace management, simplifying airspace management and planning, and improving the efficiency of airspace division.

Description

Technical Field

[0001] The present application relates to the field of flight management technology, and more specifically, to a method, device, electronic device, and computer-readable storage medium for dividing airspace. Background Art

[0002] Currently, low-altitude airspace holds vast potential for applications and development. The booming low-altitude economy, driven by sectors like consumer drones, industrial drones, urban air mobility, and general aviation helicopters, presents new challenges for traffic management and planning in low-altitude airspace.

[0003] The continuous advancement of urbanization has led to an increasingly congested urban airspace. Low-altitude areas are filled with obstacles such as buildings and no-fly zones, and these obstacles are constantly changing. Furthermore, different urban areas have different characteristics. For example, residential areas are more sensitive to aircraft noise, while areas with high ground traffic have extremely high requirements for aircraft safety. In this context, precise and reasonable airspace demarcation must consider urban environmental information and its dynamic changes to ensure the coordinated operation of drones and other urban elements. However, existing rigid airspace demarcation methods cannot flexibly respond to changes in traffic flow, resulting in wasted airspace resources and congestion. Summary of the Invention

[0004] The present application proposes a method, device, electronic device and computer-readable storage medium for dividing airspace to solve the problem of low management efficiency caused by inconsistent airspace division standards in the prior art.

[0005] According to one aspect of the present application, a method for dividing airspace is proposed, comprising:

[0006] In response to an airspace partitioning instruction, determining airspace data corresponding to the airspace partitioning, the airspace partitioning instruction including a purpose of airspace use;

[0007] Dividing the airspace data according to the purpose of using the airspace to obtain an airspace division result;

[0008] The spatial domain division result includes a first result set and a second result set, the first result set includes three-dimensional geometric shapes corresponding to the spatial domain data, and the second result set includes the relationship between the three-dimensional geometric shapes corresponding to the spatial domain data.

[0009] According to some embodiments, the three-dimensional geometric shape includes a polyhedron, a sphere, a cylinder, a frustum and / or an ellipsoid.

[0010] According to some embodiments, the first result set includes geometric information of at least one three-dimensional geometric shape, and the geometric information includes:

[0011] The spatial position, pose, scale and / or spatial attribute values of each 3D geometric shape.

[0012] According to some embodiments, the second result set includes a relative position relationship between any two three-dimensional geometric shapes in the first result set, where the relative position relationship includes a containment relationship, an adjacent relationship, and / or a connected relationship.

[0013] According to some embodiments, the airspace is represented using a four-dimensional digital base.

[0014] According to some embodiments, dividing the airspace data according to the airspace usage purpose to obtain an airspace division result includes:

[0015] Selecting at least one three-dimensional geometric shape from a preset airspace general structure according to the purpose of using the airspace;

[0016] A relationship between at least one selected three-dimensional solid geometric shape is determined based on the spatial data of the four-dimensional digital base representation.

[0017] According to some embodiments, dividing the airspace data according to the airspace usage purpose to obtain an airspace division result includes:

[0018] Determining the conditions for dividing the airspace;

[0019] According to the division condition, the spatial domain data is divided by a preset evaluation function to obtain the spatial domain division result;

[0020] The division condition includes the purpose of airspace use, and also includes the airspace division range, the purpose of airspace use and / or the airspace attribute value.

[0021] According to some embodiments, dividing the spatial domain data according to the division condition and using a preset evaluation function to obtain the spatial domain division result includes:

[0022] The spatial domain data is divided according to the division condition and a preset evaluation function through a search algorithm or a Transformer algorithm to obtain the spatial domain division result.

[0023] According to some embodiments, the search algorithm includes an A* algorithm, a genetic algorithm, a simulated annealing algorithm and / or an ant colony algorithm.

[0024] According to some embodiments, dividing the spatial domain data according to the division condition and using a preset evaluation function to obtain the spatial domain division result includes:

[0025] Dividing the spatial domain data according to the division condition to obtain at least one spatial domain division result;

[0026] Calculate the evaluation value corresponding to each airspace division result through the preset evaluation function;

[0027] An optimal spatial domain division result is determined according to the evaluation value.

[0028] According to some embodiments, the airspace attribute value includes airspace usage rules and / or airspace usage preferences.

[0029] According to some embodiments, the relative positional relationship between any two three-dimensional geometric shapes in the first result set is determined by calculating the distance between the coordinate positions of the any two three-dimensional geometric shapes.

[0030] According to one aspect of the present application, a device for dividing airspace is proposed, comprising:

[0031] an airspace data determining unit, configured to determine airspace data corresponding to the airspace division in response to an airspace division instruction, wherein the airspace division instruction includes an airspace usage purpose;

[0032] an airspace division unit, configured to divide the airspace data according to the purpose of using the airspace to obtain an airspace division result;

[0033] The spatial domain division result includes a first result set and a second result set, the first result set includes three-dimensional geometric shapes corresponding to the spatial domain data, and the second result set includes the relationship between the three-dimensional geometric shapes corresponding to the spatial domain data.

[0034] According to one aspect of the present application, an electronic device is proposed, characterized in that it includes: a processor; a memory for storing a computer program; when the computer program is executed by the processor, the processor implements the method described in any of the previous embodiments.

[0035] According to one aspect of the present application, a non-transitory computer-readable storage medium is provided, on which computer-readable instructions are stored. When the instructions are executed by a processor, the processor executes the method as described in any of the above embodiments.

[0036] According to an example embodiment of the present application, an airspace division standard is proposed by dividing the airspace into a set of universal three-dimensional geometric shapes and giving the positional relationship between the universal three-dimensional geometric shapes, thereby improving the interoperability of airspace management, simplifying airspace management and planning work, and improving the efficiency of airspace division. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for describing the embodiments.

[0038] Figure 1 A flow chart of a method for dividing airspace according to an exemplary embodiment of the present application is shown.

[0039] Figure 2 A schematic diagram of a method for dividing airspace data according to airspace usage purposes according to an exemplary embodiment of the present application is shown.

[0040] Figure 3 A schematic diagram of another method for dividing airspace data according to airspace usage purposes according to an exemplary embodiment of the present application is shown.

[0041] Figure 4 A block diagram of a device for dividing airspace according to an exemplary embodiment of the present application is shown.

[0042] Figure 5 An electronic device according to an exemplary embodiment of the present application is shown. DETAILED DESCRIPTION

[0043] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. Like reference numerals in the drawings represent like or similar parts, and thus repetitive description thereof will be omitted.

[0044] The described features, structures or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of these specific details, or other modes, components, materials, devices or operations may be employed. In these cases, well-known structures, methods, devices, implementations, materials or operations will not be shown or described in detail.

[0045] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0046] The terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0047] The existing rigid division method cannot flexibly respond to changes in traffic flow, resulting in waste of airspace resources or congestion. In order to effectively manage the airspace, it is necessary to divide the airspace according to unified standards to improve the interoperability of airspace management, simplify airspace management and planning, and improve the efficiency of airspace division.

[0048] This application combines real-time data from a low-altitude four-dimensional digital base with a library of airspace design rules to dynamically adjust airspace divisions based on actual flight demands. During peak drone logistics periods, automated planning algorithms can rapidly optimize flight paths and airspace allocations, increasing airspace capacity in busy areas and improving airspace utilization. By evaluating the rationality of airspace division results, airspace conflicts can be promptly identified and resolved, further ensuring efficient airspace operations.

[0049] In addition, with the continuous emergence of new aircraft such as drones and eVTOL (electric Vertical Take-off and Landing), traditional high-altitude airspace management methods are difficult to adapt to their diverse flight needs. This application provides a flexible and intelligent way to divide and manage airspace. The design of the universal three-dimensional geometric shape of the airspace enables different types of aircraft to find suitable flight space. By reasonably setting the properties and parameters of the basic configuration corresponding to the universal three-dimensional geometric shape, the special requirements of new aircraft in terms of speed, altitude, maneuverability, etc. can be met. In addition, this application also has good scalability and can be continuously updated and optimized with the development of technology, providing guarantees for the application of more new aircraft in the future.

[0050] This application uses universal three-dimensional geometric shapes to divide the airspace, which has the following technical effects:

[0051] 1) Achieve interoperability of global aviation systems: Universal three-dimensional geometric shapes provide a unified standard and language for airspace management worldwide. Interoperability ensures that air traffic management systems in different countries and regions can be seamlessly connected, promoting the smooth operation of international aviation.

[0052] For example, shared design standards: The use of common three-dimensional geometric shapes provides a unified standard for airspace design, helping to ensure that airspace management around the world follows the same guidelines and requirements, thereby improving global aviation safety and operational efficiency.

[0053] Another example is simplifying international collaboration: standardized three-dimensional airspace geometry promotes international collaboration and information sharing in aviation safety and airspace management, which is particularly important for cross-border flights and international route planning.

[0054] 2) Simplify airspace management and planning, reducing complexity: Universal 3D geometries reduce the complexity of designing airspace from scratch by providing a set of predefined spatial models. Airspace planners can select appropriate 3D geometries and adapt them to their specific needs without having to perform complex geometric calculations. This makes it easier for airspace planners to identify, evaluate, and implement airspace configurations, whether creating new airspace or adjusting existing airspace.

[0055] 3) Accelerate decision-making and improve efficiency: In emergencies or rapidly changing air traffic environments, common airspace configurations can expedite decision-making. Managers can quickly select the appropriate configuration template and make necessary adjustments to respond to emergencies or optimize airspace use without having to design from scratch.

[0056] 4) Enhanced predictability, transparency, and predictability in airspace planning: The common configuration provides both pilots and regulators with a clear and predictable flight environment, helping them better plan flight paths and comply with airspace use rules. This predictability is crucial for improving flight safety and reducing air traffic delays.

[0057] 5) Improve the efficiency of airspace division

[0058] For example, rapid response to changing demands: As aviation activity increases and air traffic flows change, the airspace needs to be quickly adjusted and reconfigured. Common geometry makes the adjustment process faster and more flexible, improving the efficiency of responding to changing demands.

[0059] For example, it simplifies management work: standardized configuration simplifies the monitoring, maintenance and updating of airspace, reduces the workload of air traffic management agencies, and improves overall work efficiency.

[0060] It should be noted that the embodiments of the present application are applicable to the evaluation of high-altitude airspace division results, as well as the evaluation of low-altitude airspace division results, or the evaluation of ocean space division results. However, since low-altitude airspace involves more complex terrain and requires more space, the embodiments of the present application are particularly suitable for the evaluation of low-altitude airspace division results.

[0061] For the sake of simplicity, the specific embodiments of the present application are described in detail below with reference to the accompanying drawings, taking the evaluation of the division results of low-altitude airspace as an example.

[0062] Figure 1 A flow chart of a method for dividing airspace according to an exemplary embodiment of the present application is shown. Figure 1 The method shown includes step S101 and step S103. Figure 1 Taking as an example, a method for dividing airspace according to an exemplary embodiment of the present application is described in detail.

[0063] In step S101, in response to an airspace division instruction, airspace data corresponding to the airspace division is determined, where the airspace division instruction includes an airspace usage purpose.

[0064] It should be noted here that this application does not limit the specific representation of the airspace division instruction. As long as the airspace data operation corresponding to the airspace division can be initiated, it falls within the scope of protection of this application.

[0065] In the embodiments of the present application, the spatial data is represented by the four-dimensional digital base in application number 202410781151.9. The four-dimensional digital base takes standardized four-dimensional spatial data as input, uses different function calculation functions to describe the specified function information on the four-dimensional space-time coordinates according to the function category to be calculated, and outputs the fusion information corresponding to the position of the four-dimensional space-time coordinates based on the input four-dimensional space-time coordinates and the calculation results of the specified function to generate the four-dimensional digital base.

[0066] In some embodiments, the function calculation function is expressed using f_{function}(x, y, z, t). At each four-dimensional space-time coordinate position (x, y, z, t), multiple types of function calculation functions f_{function}(x, y, z, t) are used to represent the various specified function information of this four-dimensional space-time coordinate position, thereby enabling fusion calculation of the four-dimensional spatial domain data. The four-dimensional space-time coordinate position (x, y, z, t) can be represented using a discrete method or a continuous coordinate representation method. (x, y, z, t) represents the spatial coordinate position (x, y, z) at time t.

[0067] For example, when the designated function is to describe the flyability evaluation of the aircraft in the four-dimensional coordinate, the indicator evaluation value is calculated according to the flyability evaluation of the coordinate position corresponding to each three-dimensional geometric shape in the airspace division result.

[0068] In a specific embodiment, the flyability metric assessment includes multiple sub-indicators, such as whether the airspace is occupied, the distance between the airspace and the nearest obstacle, and / or the communication coverage or strength of the airspace.

[0069] The function calculation function for the coordinate position is shown in formula (1).

[0070] f{Flyability measure}(x, y, z, t)=(1−f{occupancy}(x, y, z, t))×normalized(W1⋅f{SDF}(x, y, z, t)+W2⋅f{communication}(x, y, z, t)+…+WN⋅f{N}(x, y, z, t)) (1);

[0071] Where f{occupancy}(x, y, z, t) indicates whether the airspace is occupied, f{SDF}(x, y, z, t) represents the distance between the airspace and the nearest obstacle, f{communication}(x, y, z, t) represents the communication coverage or strength of the airspace, WN⋅f{N}(x, y, z, t) represents the Nth flyability evaluation metric, W1, W2, …, WN represent the weights corresponding to each flyability evaluation metric, and (x, y, z, t) represents each spatial-temporal coordinate position corresponding to the airspace. f{flyability measure}(x, y, z, t) represents the flyability function calculation function at the coordinate position (x, y, z) at time t. normalized represents the normalization function.

[0072] According to an embodiment of the present application, before step S101, data required for the four-dimensional digital base needs to be prepared, for example, data on geographic information, buildings, transportation, weather, electromagnetic fields, and population included in the airspace.

[0073] In some embodiments, it is also necessary to identify no-fly zones, high-risk areas, and suitable flight zones. For example, no-fly zones can be determined based on building height and distribution, and areas unfavorable for flight due to strong winds, heavy rain, etc. can be identified based on meteorological data.

[0074] In this embodiment, airspace usage purposes include logistics, sightseeing, emergency rescue, urban development planning, and safety requirements. Different airspace usage purposes have different requirements, and the resulting airspace divisions are also different. For example, if the airspace is used for logistics services, then the focus should be on transportation efficiency and cargo safety; if the airspace is used for sightseeing, then the landscape and tourist safety should be considered.

[0075] In step S103, the airspace data is divided according to the purpose of airspace use to obtain an airspace division result.

[0076] According to an embodiment of the present application, the spatial domain division result obtained in step S103 includes a first result set and a second result set, the first result set includes the three-dimensional solid geometric shapes corresponding to the spatial domain data, and the second result set includes the relationship between the three-dimensional solid geometric shapes corresponding to the spatial domain data.

[0077] In an embodiment of the present application, the spatial domain division result includes the relationship between the three-dimensional geometric shape corresponding to the spatial domain and the three-dimensional geometric shape included in the spatial domain division result.

[0078] In a specific embodiment, the first result set includes common three-dimensional geometric shapes and combinations of these three-dimensional geometric shapes. The relationships between the three-dimensional geometric shapes are used to represent positional relationships between the multiple three-dimensional geometric shapes. The positional relationships between the multiple three-dimensional geometric shapes include, but are not limited to, containment relationships, adjacency relationships, and / or connectivity relationships.

[0079] In some embodiments, the general three-dimensional solid geometric shape is a solid geometric shape that can be expressed by a geometric expression in a specified coordinate system, including but not limited to a sphere, a cylinder, a cone, a frustum, an ellipsoid and / or various polyhedrons.

[0080] It should be noted here that general three-dimensional geometric shape representation methods include but are not limited to CSG (Constructive Solid Geometry) method, SDF (Signed Distance Field) method, mesh (also known as wireless mesh network) method, point cloud method and / or Bezier surface method, etc., and support multiple formats, for example, including but not limited to mesh or obj formats.

[0081] For example, in a specified coordinate system, the side and bottom surfaces of a cylinder are defined using the spatial geometric expression shown in formula (2), and the basic geometric expression of the cylinder is obtained using the CSG method.

[0082] (2)

[0083] Where the radius is R, the height is H, and the center of the bottom is at point (x0, y0, z0).

[0084] In some embodiments, the initial representation of a universal three-dimensional geometric shape is a basic configuration, that is, the size is a standard size, and the origin is (0, 0, 0). As mentioned above, when a universal three-dimensional geometric shape adopts different identification methods, the coordinate representation will be different.

[0085] In an embodiment of the present application, the first result set includes geometric information of at least one three-dimensional geometric shape, wherein the geometric information includes the spatial position, posture, scaling degree and / or spatial attribute value of each three-dimensional geometric shape.

[0086] In a specific embodiment, the initial expression of geometric information of a common three-dimensional geometric shape is a basic configuration expression in the form of (type, x, y, z, r, p, y, scale, connect_relationship, property). Among them, type represents the three-dimensional geometric shape, the attribute value of type is the shape name corresponding to its standard basic configuration, x, y, z represent the coordinate origin position of the basic configuration; connect_relationship indicates whether the configuration forms a connection relationship with its surrounding configurations.

[0087] For example, the basic configuration includes the coordinate points (x_min, y_min, z_min) within the range, and the structural center point of the basic configuration ((x_max-x_min) / 2, (y_max-y_min) / 2, (z_max-z_min) / 2). Here, x_min, y_min, and z_min are the minimum coordinate positions within the basic configuration coverage range, and x_max, y_max, and z_max are the maximum coordinate positions within the basic configuration coverage range.

[0088] In some embodiments, (r, p, y) corresponds to the roll angle Roll, pitch angle Pitch, and yaw angle Yaw, respectively, which are the spatial rotation of the basic configuration; scale indicates the degree of scaling of the basic configuration. In a specific embodiment, the size of the unit configuration scale can be defined, and the scale parameter can be used to represent the configuration of any size; property indicates the intrinsic airspace properties of the general geometric configuration, including but not limited to: whether it is a no-fly zone, airspace suitability conditions, etc.

[0089] It should be noted that the spatial domain division result may include a complete three-dimensional geometric shape or a partial shape within the three-dimensional geometric shape.

[0090] Since the three-dimensional geometric shape can be a typical three-dimensional geometric shape or a combination of these three-dimensional geometric shapes. According to an embodiment of the present application, the second result set includes the relative position relationship between any two three-dimensional geometric shapes in the first result set, and the relative position relationship includes a containment relationship, an adjacent relationship, and / or a connected relationship. Among them, the containment relationship indicates that one three-dimensional geometric shape is located within the range of another three-dimensional geometric shape; the adjacent relationship includes that the two three-dimensional geometric shapes are adjacent but do not overlap in space; and the connected relationship indicates that the two three-dimensional geometric shapes partially overlap in space.

[0091] In a specific embodiment, the first result set is defined as set M, and the second result set is defined as A, and the spatial domain partition result can be expressed as R={M, A}.

[0092] In some embodiments, the set M is presented as a series of basic configuration instances, each of which contains detailed parameter information. The specific format is {basic configuration instance: (x, y, z, r, p, y, scale, basic configuration, other parameter settings), ...}. (x, y, z) represents the coordinate position of the basic configuration instance in space, determining its specific orientation in the airspace; (r, p, y) represents roll, pitch, and yaw, i.e., the spatial rotation of the basic configuration, used to accurately describe the configuration's posture; scale represents the scaling of the basic configuration, allowing the configuration's size to be adjusted to suit different needs. In this embodiment, the basic configuration specifies the configuration's geometric shape, such as typical three-dimensional geometric shapes like a sphere and cylinder; other parameter settings cover specific information related to the configuration, such as intrinsic airspace attributes such as whether it is prohibited from flying and airspace suitability conditions.

[0093] For example, suppose the base configuration instance is represented as (100, 200, 300, 0, 0, 0, 1, cylinder, {"no-fly": false, "suitable speed range": "5 - 10m / s"}), which means that the cylinder configuration is located at coordinates (100, 200, 300), has no rotation, a scale of 1, is not prohibited from flying, and has a suitable speed range of 5 - 10m / s.

[0094] In other embodiments, the set M includes multiple basic configurations, and each configuration instance can be represented as a tuple. The set M is represented as M={I1, I2, ..., I n}, n is the number of basic configurations included in the M set. For the i-th configuration instance, i , which is expressed as shown in formula (3).

[0095] I i =(x i ,y i , zi , r i , p i ,y i , scale i , basicshape i , otherParams i )(3);

[0096] Among them, x i ,y i , z i , represents the coordinate position of the i-th basic configuration in space, the unit is usually meter; r i , p i ,y i , respectively represents the i-th basic configuration roll, pitch, yaw, that is, the spatial rotation angle of the basic configuration, the unit is radian, scale i , representing the i-th basic configuration type.

[0097] In a specific embodiment, it can be defined as a set of discrete symbols, where the elements are the English names of the corresponding basic configuration types, as shown in formula (4).

[0098] (4);

[0099] In some embodiments, otherParams i Represents other parameter settings, which is a set of multiple attributes, as shown in formula (5).

[0100] otheParames i =(property i1 , property i2 , property i3 ,…,property in ) (5);

[0101] Among them, property ij Represents the j-th attribute, where j can be a positive integer greater than or equal to 1.

[0102] For example, property ij Indicates whether the flight is prohibited, property ij = {"nofly":true / false}.

[0103] For example, property ij Indicates airspace flight conditions, property ij = {"suitableSpeedRange":"5-10m / s"}.

[0104] The second result set, A, represents the relationships between the basic configurations included in the airspace partitioning results. This is represented by a scenegraph, a data structure used to organize and represent objects and their relationships within a scene, and to display the overall layout of each basic configuration instance within the airspace. The relationships between basic airspace configurations detail the relative position, inclusion, adjacency, and connectivity between different configurations, helping to understand the spatial connections between configurations within the airspace. For example, connectivity relationships clearly indicate which configurations are interconnected.

[0105] In a specific embodiment, the scenegraph (denoted as S) used to represent the set A can be defined as a directed graph structure S=(V, E). Where V is a node set, corresponding to the basic configuration included in the set M, which can be expressed as V={I1, I2, I3, ..., I n}. E is an edge set, which represents the relationship between basic configurations, E={(I i , I j ,attr ij )| , i≠j}, n is the number of basic configurations, and i is the i-th basic configuration.

[0106] In some embodiments, the relative positional relationship between any two three-dimensional geometric shapes in the first result set is determined by calculating the distance between the coordinate positions of the any two three-dimensional geometric shapes.

[0107] Assuming basic configuration I i , I j The coordinates of are (x i ,y i , z i )、(x j ,y j , z j ), I i , I j The distance between them can be calculated according to formula (6).

[0108] (6);

[0109] When d is less than the preset distance threshold, it is considered that the basic configuration I i , I j Closer in space.

[0110] In some embodiments, if I i , I j For inclusion relations, for example, I i All points in I j Inside, then attr ij= "contains"; otherwise, if I j in I i Internally, attr ij = "containedBy".

[0111] In other embodiments, if I i , I j is an adjacent relationship, that is, I i with I j When they have common boundaries in space and do not contain each other, attr ij = "adjacent".

[0112] In other embodiments, if I i , I j There is a path between the two, so that the aircraft can go from I i Fly to I without any obstacles in the area j The area where you are located is attr ij = "connected"; otherwise, attr ij = "notConnected".

[0113] according to Figure 1 The embodiment shown proposes an airspace division standard by dividing the airspace into a set of universal three-dimensional geometric shapes and giving the positional relationship between the universal three-dimensional geometric shapes, thereby improving the interoperability of airspace management, simplifying airspace management and planning, and improving the efficiency of airspace division.

[0114] Figure 2 A schematic diagram of a method for dividing airspace data according to airspace usage purposes according to an exemplary embodiment of the present application is shown. Figure 2 The method steps S201 and S203 are shown.

[0115] In step S201 , at least one three-dimensional geometric shape is selected from a preset general structure of the airspace according to the purpose of airspace use.

[0116] In a specific embodiment, a suitable configuration is selected from common three-dimensional geometric shapes of the airspace according to the purpose of airspace use and characteristics of airspace data.

[0117] For example, logistics transportation may choose a rectangular configuration to ensure a stable flight path.

[0118] For another example, a flexible polygonal configuration can be used for temporary activities.

[0119] In step S203, the relationship between the selected at least one three-dimensional geometric shape is determined based on the spatial data represented by the four-dimensional digital base.

[0120] According to the embodiments of the present application, the position, size, height and direction of the airspace are determined based on the selected three-dimensional geometric shape in combination with the four-dimensional digital base. While avoiding setting up low-altitude flight zones in densely populated areas, the spacing and connectivity between different three-dimensional geometric shapes are comprehensively considered to ensure safe and smooth flight.

[0121] After step S203, Figure 2 The illustrated method also includes evaluating the resulting airspace divisions and adjusting them based on the evaluation results. By evaluating the rationality of the resulting airspace divisions, the airspace divisions are checked for compliance with regulations and design preferences. Based on the evaluation results, adjustments are made to increase the spacing between flight conflict zones and optimize the airspace structure in busy areas.

[0122] Figure 3 A schematic diagram of another method for dividing airspace data according to airspace usage purposes according to an exemplary embodiment of the present application is shown. Figure 3 The method steps S301 and S303 are shown.

[0123] In step S301, the conditions for dividing the airspace are determined.

[0124] According to an embodiment of the present application, the division condition includes the purpose of airspace use (or airspace use target), and also includes the airspace division range and / or airspace attribute value.

[0125] In a specific embodiment, the geographical scope for airspace division can be represented in various forms, including but not limited to multiple latitude and longitude coordinate points, AOI (Area of Interest) representation (for example, airspace division of a certain administrative area), polygon representation in GIS (Geographic Information System), etc.

[0126] In some embodiments, the geographical range to be spatially divided is represented using a four-dimensional digital base based on geographical information corresponding to a given range.

[0127] According to an embodiment of the present application, the purpose of airspace use includes feasibility, such as requiring no collision within the airspace and compliance with legal regulations.

[0128] According to other embodiments, the airspace usage purpose includes flight type requirements, such as speed limits, climb angles, turn angles, positioning accuracy, flight control accuracy, acceleration range, impact energy on the ground, and weight indication.

[0129] According to other embodiments, the purpose of airspace use includes multiple optimization indicators, for example, the higher the score / index, the better, for example, the more aircraft that can be in the air at the same time, the better, the higher the supportable start-end coverage, the better, the shorter the supportable flight distance, the shorter the flight time, the movement in the direction of gravity, the lowest acceleration speed, the farther away from residents, the less noise, etc.

[0130] According to other embodiments, it is also necessary to quantitatively evaluate the optimization indicators corresponding to the purpose of airspace use.

[0131] In some embodiments, the quantitative assessment includes a feasibility quantitative assessment and a preference quantitative assessment. The feasibility quantitative assessment includes a collision-free assessment, a compliance assessment, and / or a type requirement assessment; the preference quantitative assessment includes an efficiency assessment, a social factor assessment, and / or a comprehensive preference assessment.

[0132] In some embodiments, efficiency evaluation includes the number of aircraft in the air at the same time, start-end coverage, flight distance and time evaluation, gravity direction movement and acceleration evaluation; social factor evaluation includes distance from residents evaluation and noise evaluation.

[0133] For example, when performing a collision-free assessment, the number of possible collisions per unit time is calculated by calculating a potential collision risk index based on the number of aircraft within a divided airspace. Assuming n potential collisions are predicted within time period T, the potential collision risk index = T / n. A lower potential collision risk index indicates a higher collision-free feasibility. In some embodiments, for complex areas, the accuracy of collision risk calculations can be improved by determining whether aircraft trajectories intersect.

[0134] For example, during compliance assessments, a compliance score is constructed. Based on airspace regulations (such as no-fly zones and high-level tiering standards), a corresponding penalty weight is assigned to each violation. Assuming the penalty points for each violation are d1, …, dm, the compliance score = sum(d1, …, dm) / W, where W is the upper limit of the penalty points for all violations and sum is the summation function. The closer the compliance score is to 1, the better the compliance.

[0135] For example, when evaluating type requirements, the compliance rate is calculated for each type requirement, such as speed limit and climb angle. For speed limit, for example, the percentage of time the aircraft's speed is within the specified range over the total flight time is calculated. The calculated compliance rates for each type are then averaged. A higher value indicates a higher probability of meeting the type requirement.

[0136] For example, when counting the number of aircraft in the air, the maximum number of aircraft in flight at the same time in the airspace over a period of time is calculated. A larger value indicates a higher airspace utilization rate.

[0137] For example, when calculating origin-destination coverage, we calculate the proportion of origin-destination pairs within a given set of origins and destinations that can be connected by airspace partitioning. Assuming there are N origin-destination pairs, of which n can be connected by air, the origin-destination coverage = n / N. The closer the origin-destination coverage is to 1, the higher the supportable origin-destination coverage and the better the efficiency.

[0138] For example, when evaluating flight distance and time, the average flight distance AD and average flight time AT of aircraft completing missions within the designated airspace are calculated. These average flight distance AD and average flight time AT can be obtained through statistical analysis of flight data from multiple aircraft. The flight distance and time evaluation is defined as 1 / (AD + k1 * AT), where k1 is a weighting factor that can be adjusted based on needs to balance the importance of flight time and distance. The larger the calculated flight distance and time evaluation values, the higher the efficiency.

[0139] For example, when evaluating gravity-directed movement and acceleration, the aircraft's average acceleration AG and average travel distance DG in the gravity-directed direction are calculated. The estimated gravity-directed movement and acceleration value is calculated as 1 / (AG + k² * DG). k² is a weighting factor that can be adjusted as needed to balance the importance of gravity-directed movement and acceleration. A higher gravity-directed movement and acceleration value indicates lower energy efficiency in the gravity-directed direction and higher efficiency in the gravity-directed direction.

[0140] For example, the distance assessment from residents is calculated by calculating the average distance between airspace and residential areas. The distance assessment value from residents is defined as distance assessment from residents / Dmax, where Dmax is the set maximum reference distance. The larger the distance assessment value from residents, the farther away from residents, and the smaller the impact on residents.

[0141] For example, based on information such as aircraft type, altitude, and speed, combined with a noise propagation model, we calculate the noise intensity (NI) at residential areas. The noise assessment value is defined as 1-NI / NI standard, where NI standard represents the acceptable noise intensity level for residents. The closer the noise assessment value is to 1, the lesser the noise impact.

[0142] In some embodiments, a comprehensive score of social factors is obtained by averaging the distance assessment value and the noise assessment value. A higher comprehensive score of social factors indicates that the zoning scheme has a better priority in terms of social factors.

[0143] In some embodiments, the efficiency and social factor evaluations are weighted averaged according to preset weights to perform a comprehensive preference evaluation. A higher comprehensive preference evaluation value indicates a higher preference for the selected scheme. In specific embodiments, the weights corresponding to the efficiency and social factor evaluations can be adjusted as needed to highlight the importance of different preference objectives.

[0144] In some embodiments, airspace attribute values include airspace usage rules and / or airspace usage preferences. Airspace design preferences refer to the primary uses and priorities of airspace within a given area. For example, the priority for airspace is to ensure efficient drone logistics while minimizing the impact on residents' lives.

[0145] In a specific embodiment, the airspace usage rule base is a systematic knowledge base that integrates rules, regulations, standards and best practices used to guide airspace design, providing a set of standardized and queryable airspace usage rules to support the effective management and planning of airspace and ensure the safety and efficiency of aviation activities.

[0146] In some embodiments, airspace usage rules include but are not limited to: controlled airspace and no-fly zone division conditions based on ground zoning information, for example: no-fly zones must be divided over hospitals, schools, nuclear power plants, high-speed rail stations, etc.; controlled airspace is divided over highways, specific parks, etc.; standard rules for the division of airspace altitude layers in accordance with the requirements of relevant national airspace regulations, for example, airspace below 120 meters above ground true altitude is Class G airspace, and airspace below 300 meters is Class W airspace, etc.; for take-off and landing fields and ground areas that may be planned as take-off and landing fields, the corresponding low-altitude airspace configuration should meet the various requirements of take-off and landing airspace; specific requirements for flight altitude, speed, route, no-fly zone, conditional flight zone, etc., as well as specific regulations for different types of aircraft (such as drones, commercial flights, etc.).

[0147] In step S303, the spatial data is divided according to the division conditions and by using a preset evaluation function to obtain a spatial division result.

[0148] According to an embodiment of the present application, in step S303, first, the spatial domain data is divided according to the division conditions to obtain at least one spatial domain division result; then, the evaluation value corresponding to each spatial domain division result is calculated through a preset evaluation function; finally, the optimal spatial domain division result is determined according to the evaluation value.

[0149] In a specific embodiment, the spatial domain data is divided according to the division conditions and a preset evaluation function through a search algorithm or a deep learning model Transformer algorithm based on the self-attention mechanism to obtain a spatial domain division result.

[0150] For example, first, a single generation process is looped until the first result set of the airspace division meets the purpose of airspace use; then, a second result set is obtained based on the first result set; finally, the airspace division result is evaluated and optimized. The single generation process includes roughly generating multiple three-dimensional geometric shapes, and then adjusting the generated multiple three-dimensional geometric shapes, for example, adjusting the parameters of the multiple three-dimensional geometric shapes (for example, the spatial rotation of the basic configuration corresponding to each three-dimensional geometric shape), the airspace rules corresponding to the three-dimensional geometric shapes (including the allowed flight speed, type / rotor, fixed wing, flight control accuracy, positioning accuracy and other body parameters), and the geometric body's occupied space range limit (for example, within the specified flight radius).

[0151] In an embodiment of the present application, the spatial data is divided by a preset evaluation function.

[0152] In a specific embodiment, the evaluation function comprehensively considers flyability metrics, rule base requirements, and design preferences to evaluate and score different airspace configuration combinations. During the search process, the optimal solution is selected from multiple airspace partitioning results, which initially meet the basic requirements of airspace partitioning.

[0153] The evaluation function can be designed in many different ways depending on the input conditions. For example, suppose FM represents the evaluation function; F fly (x, y, z, t) represents the flyable measurement function; R rule Represents the rule base constraint function, which is used to measure the degree of compliance of the partitioning scheme with the rule base. Compliance with the rules is positive, and non-compliance with the rules is negative. pref represents the design preference function, which is used to reflect the influence of design preferences. For example, if the preference is to improve airspace utilization efficiency, the scheme with large airspace capacity can be given extra points. For another example, if the preference is flight smoothness, the scheme with reduced conflicts can be given extra points. a, b, and c are weight coefficients, and a + b + c = 1. The evaluation function is shown in Formula (7).

[0154] FM = a F fly (x,y,z,t) + bR rule +cP pref (7);

[0155] Among them, the larger the FM value, the higher the flight suitability.

[0156] In the embodiments of the present application, the search algorithm includes an A* algorithm, a genetic algorithm, a simulated annealing algorithm, and / or an ant colony algorithm. In this embodiment, the ant colony algorithm is used as an example to describe in detail how to obtain a spatial partitioning result that meets the design requirements. Based on the same implementation process, those skilled in the art can easily use other search algorithms to obtain a spatial partitioning result that meets the design requirements, and the examples will not be repeated here.

[0157] The ant colony algorithm (ACO) simulates the foraging behavior of ants to gradually construct and optimize partitioning schemes in automated airspace structure design. The ACO search process includes problem modeling, parameter initialization, ant search, pheromone update, and determining termination conditions, ultimately resulting in an airspace partitioning solution that meets design requirements.

[0158] During the problem modeling phase, the airspace structure partitioning problem is transformed into a graph. Key locations in the airspace (such as takeoff and landing points, no-fly zone boundaries, and the centers of different functional zones) are set as nodes in the graph, and the connections between nodes are edges. The weight of the edges can be determined based on factors such as the distance between nodes and the flyability measure. For example, the weight of the edge between two nodes that are close and have a high flyability measure can be set larger, and vice versa.

[0159] During the parameter initialization phase, set parameters such as the number of ants, initial pheromone concentration, pheromone volatility coefficient, and heuristic factor. The initial pheromone concentration can be set to a uniform value, such as 0.1. The pheromone volatility coefficient is generally between 0 and 1, and a setting of 0.5, for example, controls the decay of pheromones over time. The heuristic factor is set based on the characteristics of the problem and measures the importance ants place on heuristic information (such as distance and flyability) when choosing a path.

[0160] During the ant search phase, each ant starts from a starting node and selects the next node according to specific rules. Ants calculate the probability of selection based on the pheromone concentration and heuristic information along the edges between nodes. The higher the pheromone concentration and the better the heuristic information (e.g., closer to the target node, higher flyability measure), the greater the probability of selection. As ants move, they construct their own paths, forming a local plan for airspace partitioning. For example, when choosing an area to pass through, ants comprehensively consider the flyability measure and the available pheromone concentration. When all ants complete their search, a set of candidate airspace partitioning plans is obtained.

[0161] During the pheromone update phase, pheromones are updated based on the quality of the ant-built paths (determined by an evaluation function that integrates factors such as flyability, compliance with airspace regulations, and airspace preferences). High-quality paths increase the amount of pheromones on them, while low-quality paths decrease the amount of pheromones on them.

[0162] For example, for paths that meet all rules, have a high flyability measure, and satisfy design preferences, the pheromone concentration is significantly increased; for paths that violate regulations or have a low flyability measure, the pheromone concentration is reduced. The pheromone update formula is shown in Formula (8).

[0163] (8);

[0164] in, is the pheromone concentration on edge (i, j) at time t, is the pheromone volatility coefficient, is the pheromone increment on edge (i, j) in this iteration.

[0165] During the termination condition determination phase, the system checks whether the termination condition has been met, such as reaching the maximum number of iterations (e.g., 500) or the optimal solution showing no significant improvement after multiple iterations. If the termination condition is met, the optimal airspace partitioning solution is output. Otherwise, the system returns to step 3 and continues with the next round of ant search and pheromone update until a satisfactory solution is found.

[0166] According to an embodiment of the present application, the spatial domain partitioning result can also be generated based on Transformer. The steps of generating the spatial domain partitioning result based on Transformer include data preparation, Transformer model construction and training, generating a spatial domain partitioning sequence, and result optimization.

[0167] During the data preparation stage, various types of data used to generate the airspace division sequence are collected and organized.

[0168] For example, flyability measurements are obtained from a low-altitude four-dimensional digital base. These results reflect the flight suitability of different airspace locations and are an important basis for determining airspace division plans. Common airspace structure representations are organized, including the characteristics of various geometric configurations (such as the shape characteristics of spheres and cylinders) and properties (whether they are prohibited from flying, flight suitability conditions, etc.). The optimal solution obtained by the search algorithm is encoded and converted into an input format that the Transformer can understand. For example, parameters such as the position, rotation, and scale of the configuration instance are digitally encoded.

[0169] During the Transformer model construction and training phase, a Transformer model suitable for the spatial domain segmentation task is constructed.

[0170] For example, hyperparameters such as the number of layers, number of heads, and hidden layer dimensions are determined to balance the model's computational complexity and performance. The model is trained using the prepared data. During training, the model learns the relationship between feasible metrics, common structures, and optimal solutions, continuously adjusting model parameters to accurately generate a reasonable spatial partitioning sequence based on the input data. During training, the spatial partitioning scheme is used as a label, allowing the model to learn how to map the input data to the correct partitioning scheme.

[0171] During the spatial partitioning sequence generation phase, the trained Transformer model is fed with the encoded flyable measurement results, the general structure representation, and the optimal solution data. Using a self-attention mechanism, the model performs parallel processing and feature extraction on the input data, capturing correlations between different data.

[0172] For example, the model considers both the flyability of a region and the geometric configuration properties that are applicable to that region. Based on the extracted features, the Transformer model, in accordance with its internal architecture and patterns learned during training, generates a series of permutations and combinations of airspace partitioning configuration instances. These permutations and combinations form the preliminary framework of the partitioning scheme, determining the approximate distribution and combination of configuration instances in the airspace.

[0173] During the result optimization phase, the airspace partitioning sequence generated by the Transformer is evaluated and checked against the airspace design rule base to verify compliance with regulations such as no-fly zones and airspace stratification, while also taking into account design preferences. To address issues identified during the evaluation, the airspace partitioning sequence is corrected using search algorithms or manual intervention. Search algorithms can adjust the parameters of configuration instances within a certain range to identify optimal solutions. Manual intervention, based on actual experience and specific needs, allows for targeted optimization of the airspace partitioning sequence, ensuring that the final partitioning solution complies with both regulations and meets practical application requirements.

[0174] According to the embodiments of this application, after obtaining the airspace partitioning results, it is necessary to comprehensively consider factors such as flyability, rule compliance, and design preferences to evaluate the airspace partitioning results. By constructing a mathematical model, quantifying and weighting each factor, and calculating the evaluation function value, the merits of the partitioning scheme are judged, providing a basis for optimization and decision-making.

[0175] The embodiments of the present application are described above mainly from the perspective of methods. Those skilled in the art should readily appreciate that, in conjunction with the operations or steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Those skilled in the art may use different methods to implement the described functions for each specific operation or method, and such implementation should not be considered beyond the scope of this application.

[0176] The following describes the device embodiments of the present application. For details not described in the device embodiments of the present application, reference can be made to the method embodiments of the present application.

[0177] Figure 4 A block diagram of a device for dividing airspace according to an exemplary embodiment of the present application is shown. Figure 4 The illustrated apparatus includes an airspace data determination unit 401 and an airspace partitioning unit 403. The airspace data determination unit 401 is configured to determine airspace data corresponding to an airspace partition in response to an airspace partition instruction, wherein the airspace partition instruction includes an airspace usage purpose; and the airspace partitioning unit 403 is configured to partition the airspace data according to the airspace usage purpose to obtain an airspace partitioning result.

[0178] According to an embodiment of the present application, the spatial domain division result includes a first result set and a second result set. The first result set includes three-dimensional geometric shapes corresponding to the spatial domain data, and the second result set includes the relationship between the three-dimensional geometric shapes corresponding to the spatial domain data.

[0179] Figure 5 An electronic device according to an exemplary embodiment of the present application is shown. Figure 5 hereinafter, an electronic device 200 according to this embodiment of the present application is described. Figure 5 The electronic device 200 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0180] like Figure 5 As shown, electronic device 200 is implemented as a general-purpose computing device. Components of electronic device 200 may include, but are not limited to, at least one processing unit 210, at least one storage unit 220, a bus 230 connecting various system components (including storage unit 220 and processing unit 210), and a display unit 240.

[0181] The storage unit stores program codes, which can be executed by the processing unit 210, so that the processing unit 210 performs the methods described in this specification according to various exemplary embodiments of the present application. For example, the processing unit 210 can perform the method described above.

[0182] The storage unit 220 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 2201 and / or a cache memory unit 2202 , and may further include a read-only memory unit (ROM) 2203 .

[0183] The storage unit 220 may also include a program / utility 2204 having a set (at least one) of program modules 2205, such program modules 2205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0184] Bus 230 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0185] The electronic device 200 can also communicate with one or more external devices 300 (e.g., a keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 200, and / or any device that enables the electronic device 200 to communicate with one or more other computing devices (e.g., a router, modem, etc.). This communication can occur via an input / output (I / O) interface 250. Furthermore, the electronic device 200 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 260. The network adapter 260 can communicate with other modules of the electronic device 200 via the bus 230. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with the electronic device 200, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0186] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. The technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, or a network device, etc.) to execute the above-mentioned method according to the embodiments of the present application.

[0187] The software product may utilize any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0188] Computer-readable storage media may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0189] The program code used to perform the operations of the present application can be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0190] The computer-readable storage medium carries one or more programs (including computer-readable instructions stored thereon). When the one or more programs are executed by the device, the computer-readable storage medium implements the aforementioned functions.

[0191] Those skilled in the art will appreciate that the modules described above can be distributed in the device according to the description of the embodiment, or can be modified accordingly to be used in one or more devices that are different from the embodiment. The modules of the above embodiment can be combined into one module or further divided into multiple submodules.

[0192] According to an embodiment of the present application, a computer program is provided, including a computer program or instructions. When the computer program or instructions are executed by a processor, the method described above can be executed.

[0193] The embodiments of the present application are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only intended to help understand the method and core ideas of the present application. At the same time, changes or modifications made by those skilled in the art based on the ideas of the present application, the specific implementation methods, and the scope of application of the present application, all fall within the scope of protection of the present application. In summary, the contents of this specification should not be construed as limiting the present application.

[0194] Those skilled in the art will appreciate that the modules described above can be distributed in the device according to the description of the embodiment, or can be modified accordingly to be used in one or more devices that are different from the embodiment. The modules of the above embodiment can be combined into one module or further divided into multiple submodules.

[0195] Traditional airspace division methods lack a systematic evaluation mechanism, making it difficult to ensure the rationality of division schemes. This application proposes a comprehensive set of rationality assessment methods for airspace division and allocation, comprehensively considering factors such as flyability, rule compliance, and design preferences. Using mathematical models and multiple evaluation methods, it provides a comprehensive and objective evaluation of airspace division results. This allows for continuous optimization and improvement of division schemes during the development process, improving the scientific nature and accuracy of airspace division and reducing flight safety risks.

[0196] The embodiments of the present application are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only intended to help understand the method and core ideas of the present application. At the same time, changes or modifications made by those skilled in the art based on the ideas of the present application, the specific implementation methods, and the scope of application of the present application, all fall within the scope of protection of the present application. In summary, the contents of this specification should not be construed as limiting the present application.

Claims

1. A method for dividing airspace, characterized in that: The method of dividing airspace is applicable to low-altitude airspace, including: In response to an airspace partitioning instruction, determining airspace data corresponding to the airspace partitioning, the airspace partitioning instruction including a purpose of airspace use; Dividing the airspace data according to the purpose of using the airspace to obtain an airspace division result; Among them, the spatial domain division result includes a first result set and a second result set, the first result set includes the three-dimensional geometric shapes corresponding to the spatial domain data, and the second result set includes the relationship between the three-dimensional geometric shapes corresponding to the spatial domain data. The relationship between the three-dimensional geometric shapes is used to represent the positional relationship between multiple three-dimensional geometric shapes, and the positional relationship includes a connectivity relationship, and the connectivity relationship indicates that there is a spatial partial overlap between two three-dimensional geometric shapes.

2. The method according to claim 1, characterized in that The three-dimensional geometric shape includes a polyhedron, a sphere, a cylinder, a frustum and / or an ellipsoid.

3. The method according to claim 2, characterized in that The first result set includes geometric information of at least one three-dimensional geometric shape, and the geometric information includes: The spatial position, pose, scale and / or spatial attribute values of each 3D geometric shape.

4. The method according to claim 3, characterized in that The second result set includes the relative position relationship between any two three-dimensional geometric shapes in the first result set, and the relative position relationship includes a containment relationship, an adjacent relationship and / or a connected relationship.

5. The method according to claim 4, characterized in that The spatial domain is represented using a four-dimensional digital base.

6. The method according to claim 5, characterized in that The airspace data is divided according to the purpose of use of the airspace to obtain an airspace division result, including: Selecting at least one three-dimensional geometric shape from a preset airspace general structure according to the purpose of using the airspace; A relationship between at least two selected three-dimensional geometric shapes is determined based on the spatial data represented by the four-dimensional digital base.

7. The method according to claim 5, characterized in that The airspace data is divided according to the purpose of use of the airspace to obtain an airspace division result, including: Determining the conditions for dividing the airspace; According to the division condition, the spatial domain data is divided by a preset evaluation function to obtain the spatial domain division result; The division conditions include the purpose of airspace use, and also include the airspace division range and / or the airspace attribute value.

8. The method according to claim 7, characterized in that According to the division condition, the spatial domain data is divided by a preset evaluation function to obtain the spatial domain division result, including: The spatial domain data is divided according to the division condition and a preset evaluation function through a search algorithm or a Transformer algorithm to obtain the spatial domain division result.

9. The method according to claim 8, characterized in that The search algorithm includes A* algorithm, genetic algorithm, simulated annealing algorithm and / or ant colony algorithm.

10. The method according to claim 7, characterized in that According to the division condition, the spatial domain data is divided by a preset evaluation function to obtain the spatial domain division result, including: Dividing the spatial domain data according to the division condition to obtain at least one spatial domain division result; Calculate the evaluation value corresponding to each airspace division result through the preset evaluation function; An optimal spatial domain division result is determined according to the evaluation value.

11. The method according to claim 7, characterized in that The airspace attribute value includes airspace usage rules and / or airspace usage preferences.

12. The method according to claim 4, characterized in that The relative positional relationship between any two three-dimensional geometric shapes in the first result set is determined by calculating the distance between the coordinate positions of the any two three-dimensional geometric shapes.

13. A device for dividing airspace, characterized in that: The device for dividing airspace is applicable to low-altitude airspace and includes: an airspace data determining unit, configured to determine airspace data corresponding to the airspace division in response to an airspace division instruction, wherein the airspace division instruction includes an airspace usage purpose; an airspace division unit, configured to divide the airspace data according to the purpose of using the airspace to obtain an airspace division result; Among them, the spatial domain division result includes a first result set and a second result set, the first result set includes the three-dimensional geometric shapes corresponding to the spatial domain data, and the second result set includes the relationship between the three-dimensional geometric shapes corresponding to the spatial domain data. The relationship between the three-dimensional geometric shapes is used to represent the positional relationship between multiple three-dimensional geometric shapes, and the positional relationship includes a connectivity relationship, and the connectivity relationship indicates that there is a spatial partial overlap between two three-dimensional geometric shapes.

14. An electronic device, characterized in that: include: processor; memory for storing computer programs; When the computer program is executed by the processor, the processor is caused to implement the method according to any one of claims 1 to 12. 15 . A computer-readable storage medium having computer-readable instructions stored thereon, which, when executed by a processor, causes the processor to perform the method according to claim 1 .

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