Low-altitude airspace refinement management method and system based on four-dimensional airspace grid

Abstract

The application relates to the technical field of airspace management, and provides a low-altitude airspace fine management method and system based on a four-dimensional airspace grid. According to a low-altitude airspace geographical boundary and a height level, three-dimensional space grid units are divided and a time dimension attribute is associated to form a four-dimensional airspace grid structure; candidate flight trajectories are generated in the structure; a conflict grid set is determined through traversal and matching; a grid unit sequence is adjusted in a conflict resolution search space, and a conflict-free flight path is generated; the grid units corresponding to the path are marked as occupied and are bound with aircraft identifiers, fine low-altitude airspace resource management is realized, and flight safety and airspace use efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of airspace management technology, and in particular to a method and system for refined management of low-altitude airspace based on a four-dimensional airspace grid. Background Technology

[0002] With the rapid development and widespread application of low-altitude aircraft such as drones and low-altitude flying vehicles, low-altitude airspace management faces unprecedented challenges. Low-altitude airspace refers to the airspace from the ground to a certain altitude, typically defined as airspace below 1000 meters or 3000 meters. This airspace, due to its complex terrain, dense buildings, and frequent flight activities, demands high precision and efficiency in airspace management. Traditional airspace management methods rely mainly on manual planning and monitoring, suitable for managing a limited number of large aircraft, but struggling to cope with the vast number and diverse types of low-altitude flying vehicles. With the increasing application scenarios of smart city construction and drone delivery, aerial photography, and emergency rescue, a refined management mechanism for low-altitude airspace is urgently needed.

[0003] Existing low-altitude airspace management technologies suffer from the following defects and shortcomings: First, they lack the ability to finely represent and manage low-altitude airspace resources. Traditional air traffic control systems primarily employ two-dimensional routes or simple three-dimensional hierarchical management methods, which cannot effectively represent the complex obstacles and dynamically changing airspace status in the low-altitude environment. This results in low airspace resource utilization and an inability to meet the ever-increasing demand for low-altitude flights. Second, existing conflict detection and avoidance technologies are mainly based on simple point-to-point or segment-to-segment comparisons, leading to high computational complexity and low efficiency. When the number of low-altitude aircraft surges, it becomes difficult to handle the massive conflict detection demands in real time, easily causing computational resource overload and affecting system response speed and safety. Third, existing technologies lack effective integration and management of the temporal dimension. Aircraft activities in low-altitude airspace are highly dynamic and time-sensitive, while existing systems focus primarily on spatial dimension management, lacking sufficient fine-grained management of the temporal dimension. This makes it difficult to achieve spatiotemporal joint scheduling and optimized allocation of airspace resources, failing to fully realize the potential of airspace capacity. Summary of the Invention

[0004] This invention provides a method and system for refined management of low-altitude airspace based on a four-dimensional airspace grid, which can solve the problems in the prior art.

[0005] A first aspect of this invention provides a method for refined management of low-altitude airspace based on a four-dimensional airspace grid, comprising:

[0006] Based on the geographical boundaries and altitude levels of the low-altitude airspace, the target airspace is divided into three-dimensional spatial grid units, and a four-dimensional airspace grid structure is obtained by associating a time dimension attribute with each spatial grid unit. Candidate flight trajectories are generated in the four-dimensional airspace grid structure based on the flight mission requirements of the aircraft.

[0007] Traverse the sequence of grid cells traversed by the candidate flight trajectory, associate and match each grid cell with the occupancy status of the allocated flight resources, and determine the set of conflicting grid cells that conflict with the occupied grid cells in the spatiotemporal dimension.

[0008] For the conflict grid set, a conflict resolution search space is determined in the four-dimensional airspace grid structure. By adjusting the time marker or spatial coordinate of the grid cell sequence in the conflict resolution search space, a conflict-free flight path that avoids the conflict grid set is generated.

[0009] The grid cell sequence corresponding to the conflict-free flight path is marked as occupied, and the occupied state is bound to the aircraft identifier to obtain an airspace resource allocation record. The airspace resource allocation record is used for conflict detection and airspace resource status query in subsequent flight missions.

[0010] Based on the geographical boundaries and altitude levels of the low-altitude airspace, the target airspace is divided into three-dimensional spatial grid cells. A four-dimensional airspace grid structure is obtained by associating a time dimension attribute with each spatial grid cell. Candidate flight trajectories are then generated within this four-dimensional airspace grid structure based on the aircraft's flight mission requirements. These trajectories include:

[0011] Geographic boundary data and altitude level parameters of low-altitude airspace are obtained. Based on the geographic boundary data, spatial discretization is performed in the horizontal direction, and based on the altitude level parameters, altitude layering is performed in the vertical direction to obtain three-dimensional spatial grid cells.

[0012] Associating each three-dimensional spatial grid cell with a time granularity identifier yields a four-dimensional spatial grid structure;

[0013] Analyze the flight mission requirements of the aircraft and extract the starting position coordinates, target position coordinates, and flight time window;

[0014] The starting position coordinates and the target position coordinates are respectively mapped to the four-dimensional spatial grid structure to determine the starting grid cell corresponding to the starting position coordinates and the target grid cell corresponding to the target position coordinates;

[0015] Based on the starting grid cell and the target grid cell, the grid cell connection path is determined in the four-dimensional spatial grid structure;

[0016] The time dimension constraint verification is performed on the connected paths of the grid cells to determine whether the time identifier of each grid cell in the connected paths of the grid cells meets the constraint conditions of the flight time window, and the grid cell sequence that meets the constraint conditions of the flight time window is retained as a candidate flight trajectory.

[0017] Traverse the sequence of grid cells traversed by the candidate flight trajectory, associate and match each grid cell with the occupancy status of allocated flight resources, and determine the set of conflicting grid cells that conflict with occupied grid cells in the spatiotemporal dimension, including:

[0018] Determine the sequence of grid cells traversed by the candidate flight trajectory, and query the occupancy status data of the allocated flight resources in the four-dimensional airspace grid structure;

[0019] Traverse each grid cell in the grid cell sequence, and match the spatial coordinates and time identifier of each grid cell with the occupied grid cells in the occupancy status data one by one to determine the grid cells in the grid cell sequence that coincide with the occupied grid cells in the occupancy status data in both spatial coordinates and time identifiers.

[0020] The simultaneously overlapping mesh cells are marked as conflicting mesh cells, and the conflicting mesh cells are sorted according to their position order in the mesh cell sequence to generate an ordered list of conflicting mesh cells;

[0021] Spatial continuity is determined for adjacent conflicting grid cells in the ordered list of conflicting grid cells to obtain the spatial continuity determination result;

[0022] Based on the spatial continuity determination result, the ordered list of conflict grid cells is divided into multiple spatially continuous conflict grid subsets, and the set of the conflict grid subsets is taken as the conflict grid set.

[0023] Determine the sequence of grid cells traversed by the candidate flight trajectory, and query the occupancy status data of allocated flight resources in the four-dimensional airspace grid structure, including:

[0024] The trajectory representation of the candidate flight trajectory is analyzed to obtain the set of discrete trajectory points of the candidate flight trajectory in the time dimension;

[0025] Interpolation processing is performed on the spatial interval between adjacent trajectory points in the discrete trajectory point set to generate supplementary trajectory points between adjacent trajectory points whose spatial interval exceeds the grid cell scale;

[0026] Map each trajectory point in the complete trajectory point sequence composed of the discrete trajectory point set and the supplementary trajectory points to the four-dimensional spatial grid structure to determine the grid cell corresponding to each trajectory point;

[0027] The grid cells are arranged according to the chronological order of the trajectory points in the candidate flight trajectory to generate a sequence of grid cells traversed by the candidate flight trajectory;

[0028] Access the resource occupancy state storage structure of the four-dimensional spatial grid structure;

[0029] Extract the grid cells marked as occupied from the resource occupancy status storage structure, obtain the binding data of the spatial coordinates, time identifier and aircraft identifier of the occupied grid cells, and generate the occupancy status data of the allocated flight resources.

[0030] For the conflict grid set, a conflict resolution search space is determined in a four-dimensional spatial grid structure. By adjusting the time stamp or spatial coordinates of the grid cell sequence in the conflict resolution search space, a conflict-free flight path that avoids the conflict grid set is generated, including:

[0031] Based on the spatial coordinates and temporal identifiers of each conflicting grid cell in the conflicting grid set, the spatiotemporal distribution characteristics of the conflicting grid set in the four-dimensional spatial grid structure are determined;

[0032] For each conflict grid cell in the conflict grid set, the conflict resolution search space is determined in the four-dimensional spatial grid structure;

[0033] Based on the dynamic performance constraints of the aircraft, reachability filtering is performed on the available neighborhood grid cells in the conflict resolution search space to generate a dynamically reachable conflict resolution search space;

[0034] In the dynamically reachable resolution search space, determine the bypass grid path from the pre-conflict grid cell to the post-conflict grid cell of the candidate flight trajectory;

[0035] The conflict segment located between the pre-conflict and post-conflict grid cells in the grid cell sequence of the candidate flight trajectory is replaced with the detour grid path to generate an adjusted grid cell sequence;

[0036] The adjusted grid cell sequence is subjected to spatiotemporal continuity verification, and the adjusted grid cell sequence that passes the spatiotemporal continuity verification is used as a conflict-free flight path.

[0037] Based on the dynamic performance constraints of the aircraft, reachability filtering is performed on the available neighborhood grid cells in the conflict resolution search space to generate a dynamically reachable conflict resolution search space, including:

[0038] For each available neighboring grid cell in the conflict resolution search space, determine the state transition trajectory from the pre-conflict grid cell to the available neighboring grid cell;

[0039] Based on the kinematic and dynamic characteristics of the state transition trajectory, determine the mapping relationship between the kinematic characteristics and the geometric motion constraints in the dynamic performance constraints;

[0040] Based on the kinematic and dynamic characteristics of the state transition trajectory, determine the mapping relationship between the dynamic characteristics and the dynamic output constraints in the dynamic performance constraints;

[0041] Based on the geometric motion constraints, the feasibility of the kinematic features is determined, and based on the dynamic output constraints, the feasibility of the dynamic features is determined, and the available neighborhood grid cells that pass both the feasibility determination of the geometric motion constraints and the feasibility determination of the dynamic output constraints are determined.

[0042] Available neighborhood grid cells that pass the dual feasibility determination are marked as dynamically reachable grid cells, and the set of all dynamically reachable grid cells in the conflict resolution search space is taken as the dynamically reachable resolution search space.

[0043] The grid cell sequence corresponding to the conflict-free flight path is marked as occupied, and the occupied state is bound to the aircraft identifier to obtain an airspace resource allocation record, including:

[0044] Extract the spatial coordinates and time signatures of each grid cell in the grid cell sequence corresponding to the conflict-free flight path to generate an airspace resource occupancy list;

[0045] For each grid cell in the airspace resource occupancy list, the corresponding grid node is determined in the four-dimensional airspace grid structure;

[0046] When the current occupancy status of the grid node is marked as unoccupied, the occupancy status of the grid node is changed to marked as occupied, thus completing the state transition of the grid node;

[0047] Write the grid node identifier of the grid node that has completed the state transition into the binding object field, and write the aircraft identifier into the binding attribute field to determine the association mapping relationship between the occupied state of the grid node and the aircraft identifier, thus obtaining the resource binding data structure;

[0048] Based on the resource binding data structure of all grid nodes, an airspace resource allocation record corresponding to the aircraft identifier is generated.

[0049] A second aspect of this invention provides a low-altitude airspace fine-grained management system based on a four-dimensional airspace grid, comprising:

[0050] The first unit is used to divide the target airspace into three-dimensional spatial grid units according to the geographical boundaries and altitude levels of the low-altitude airspace, and associate time dimension attributes with each spatial grid unit to obtain a four-dimensional airspace grid structure. Based on the flight mission requirements of the aircraft, candidate flight trajectories are generated in the four-dimensional airspace grid structure.

[0051] The second unit is used to traverse the sequence of grid cells passed by the candidate flight trajectory, associate and match each grid cell with the occupancy status of the allocated flight resources, and determine the set of conflicting grid cells that conflict with the occupied grid cells in the spatiotemporal dimension.

[0052] The third unit is used to determine the conflict resolution search space for the conflict grid set in the four-dimensional airspace grid structure, and to generate a conflict-free flight path that avoids the conflict grid set by adjusting the time marker or spatial coordinate of the grid cell sequence in the conflict resolution search space.

[0053] The fourth unit is used to mark the grid cell sequence corresponding to the conflict-free flight path as occupied, and bind the occupied state with the aircraft identifier to obtain an airspace resource allocation record. The airspace resource allocation record is used for conflict detection and airspace resource status query in subsequent flight missions.

[0054] A third aspect of the present invention provides an electronic device, comprising:

[0055] processor;

[0056] Memory used to store processor-executable instructions;

[0057] The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0058] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0059] This invention achieves refined management of airspace resources and improves their utilization efficiency by dividing low-altitude airspace into a four-dimensional airspace grid structure (three-dimensional space plus a time dimension). It can traverse the grid cell sequence traversed by candidate flight trajectories, automatically identify spatiotemporal conflicts, and generate conflict-free flight paths within a defined conflict resolution search space, effectively solving potential conflicts between aircraft in low-altitude airspace. By marking the grid cell sequence corresponding to conflict-free flight paths as occupied and binding it to aircraft identifiers, this invention establishes a dynamic airspace resource allocation record system, enabling airspace managers to monitor airspace resource usage in real time. Through accurate identification and resolution of spatiotemporal conflicts, this invention significantly improves the safety of low-altitude aircraft and reduces the risk of mid-air collisions. This invention adapts to the increasing flight demands of low-altitude aircraft such as UAVs, providing reliable airspace management technology support for future large-scale low-altitude flight activities. Attached Figure Description

[0060] Figure 1 This is a flowchart illustrating the low-altitude airspace refined management method based on a four-dimensional airspace grid, according to an embodiment of the present invention.

[0061] Figure 2 This is a schematic diagram illustrating the process of determining a conflict-free flight path according to an embodiment of the present invention. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] The technical solution of the present invention will be described in detail below with reference to 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.

[0064] Figure 1 This is a flowchart illustrating the low-altitude airspace refined management method based on a four-dimensional airspace grid, according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0065] Based on the geographical boundaries and altitude levels of the low-altitude airspace, the target airspace is divided into three-dimensional spatial grid units, and a four-dimensional airspace grid structure is obtained by associating a time dimension attribute with each spatial grid unit. Candidate flight trajectories are generated in the four-dimensional airspace grid structure based on the flight mission requirements of the aircraft.

[0066] Traverse the sequence of grid cells traversed by the candidate flight trajectory, associate and match each grid cell with the occupancy status of the allocated flight resources, and determine the set of conflicting grid cells that conflict with the occupied grid cells in the spatiotemporal dimension.

[0067] For the conflict grid set, a conflict resolution search space is determined in the four-dimensional airspace grid structure. By adjusting the time marker or spatial coordinate of the grid cell sequence in the conflict resolution search space, a conflict-free flight path that avoids the conflict grid set is generated.

[0068] The grid cell sequence corresponding to the conflict-free flight path is marked as occupied, and the occupied state is bound to the aircraft identifier to obtain an airspace resource allocation record. The airspace resource allocation record is used for conflict detection and airspace resource status query in subsequent flight missions.

[0069] In one optional implementation, the target airspace is divided into three-dimensional spatial grid cells based on the geographical boundaries and altitude levels of the low-altitude airspace. A four-dimensional airspace grid structure is obtained by associating a time dimension attribute with each spatial grid cell. Candidate flight trajectories are then generated within the four-dimensional airspace grid structure based on the aircraft's flight mission requirements, including:

[0070] Geographic boundary data and altitude level parameters of low-altitude airspace are obtained. Based on the geographic boundary data, spatial discretization is performed in the horizontal direction, and based on the altitude level parameters, altitude layering is performed in the vertical direction to obtain three-dimensional spatial grid cells.

[0071] Associating each three-dimensional spatial grid cell with a time granularity identifier yields a four-dimensional spatial grid structure;

[0072] Analyze the flight mission requirements of the aircraft and extract the starting position coordinates, target position coordinates, and flight time window;

[0073] The starting position coordinates and the target position coordinates are respectively mapped to the four-dimensional spatial grid structure to determine the starting grid cell corresponding to the starting position coordinates and the target grid cell corresponding to the target position coordinates;

[0074] Based on the starting grid cell and the target grid cell, the grid cell connection path is determined in the four-dimensional spatial grid structure;

[0075] The time dimension constraint verification is performed on the connected paths of the grid cells to determine whether the time identifier of each grid cell in the connected paths of the grid cells meets the constraint conditions of the flight time window, and the grid cell sequence that meets the constraint conditions of the flight time window is retained as a candidate flight trajectory.

[0076] In the technical field of low-altitude aircraft flight planning, to meet the requirements of safe flight and mission execution, it is necessary to accurately divide the low-altitude airspace and plan reasonable flight trajectories. This implementation method generates candidate flight trajectories that meet the flight mission requirements by dividing the airspace into a three-dimensional spatial grid and combining it with a time dimension.

[0077] First, obtain the geographic boundary data and altitude layer parameters of the low-altitude airspace. The geographic boundary data typically includes latitude and longitude ranges; for example, the boundary of a city's low-altitude airspace is from 116.0° to 117.0° east longitude and from 39.5° to 40.5° north latitude. The altitude layer parameters define the vertical stratification; for example, the low-altitude airspace from 0 meters to 1000 meters can be divided into 10 altitude layers, each spaced 100 meters apart.

[0078] Based on the acquired geographic boundary data, spatial discretization is performed in the horizontal direction. This discretization can be achieved using an equidistant grid division method, dividing the area within the geographic boundary into several grid units according to a preset grid size (e.g., 500 meters × 500 meters). For example, for an area covering 100 square kilometers, if a grid size of 500 meters is selected, 400 horizontal grid units can be divided.

[0079] Simultaneously, based on the height hierarchy parameter, vertical height stratification is performed. Following the previous example, the airspace from 0 to 1000 meters is divided into 10 height layers: 0-100 meters, 101-200 meters, and so on up to 901-1000 meters. Combining the horizontal grid with the vertical stratification forms a three-dimensional spatial grid unit. In the above example, a total of 4000 three-dimensional spatial grid units are obtained.

[0080] By associating a time granularity identifier with each three-dimensional spatial grid cell, a four-dimensional spatial grid structure is obtained. The time granularity can be set according to the aircraft's speed characteristics and mission requirements. For example, a day can be divided into 24 hours, with each hour as a time unit, or a more refined 10-minute unit can be used. In this way, each three-dimensional spatial grid cell has a time attribute, forming a four-dimensional spatial grid structure. For example, a three-dimensional grid cell with coordinates (10, 15, 3) can be represented as a four-dimensional grid cell (10, 15, 3, 8) at time point t=8.

[0081] Next, we analyze the flight mission requirements of the aircraft and extract the starting position coordinates, target position coordinates, and flight time window. Assume the flight mission is from position A (longitude 116.2°, latitude 39.8°, altitude 50 meters) to position B (longitude 116.8°, latitude 40.2°, altitude 200 meters), and the flight time window is from 8:00 AM to 9:00 AM.

[0082] The starting and target position coordinates are mapped to a four-dimensional airspace grid structure, determining the starting and target grid cells. This mapping process requires converting geographic coordinates into corresponding grid indices. For example, starting position A is mapped to grid cell (4, 6, 0), while target position B is mapped to grid cell (16, 14, 2). Considering the flight start time is 8:00 AM, the four-dimensional representation of the starting grid cell is (4, 6, 0, 8).

[0083] Based on the starting and target grid cells, the connectivity paths between grid cells are determined in the four-dimensional spatial grid structure. Path search can employ either the A* algorithm or Dijkstra's algorithm to find the optimal path from the starting grid cell to the target grid cell. During the path search process, the connectivity between grid cells is considered; for example, adjacent grid cells can be directly connected, while non-adjacent grid cells need to be connected through intermediate grid cells.

[0084] During the search, for each movable direction (east, west, south, north, up, down), the next reachable grid cell is calculated. Assuming the current location is grid cell (5, 7, 1, 8.1), the next grid cells for the aircraft include (6, 7, 1, 8.2), (5, 8, 1, 8.2), (5, 7, 2, 8.2), and so on. Through iterative search, a grid cell sequence from (4, 6, 0, 8.0) to (16, 14, 2, 8.5) is finally obtained, representing a possible path from the starting position to the target position.

[0085] Finally, a time-dimensional constraint check is performed on the connected paths of the grid cells to determine whether the time identifier of each grid cell in the connected path meets the constraints of the flight time window. For example, it is checked whether the time identifiers of all grid cells in the path are between 8:00 and 9:00. If the time identifier of a certain grid cell is found to be outside the specified time window, the path does not meet the constraints and needs to be removed or adjusted.

[0086] Grid cell sequences that satisfy the flight time window constraints are retained as candidate flight trajectories. In the example above, if the time stamps of all grid cells in the generated path are between 8:00 and 9:00, and the total path time is 30 minutes (i.e., starting at 8:00 and arriving at the destination at 8:30), then this path can be considered a candidate flight trajectory. Multiple candidate flight trajectories that satisfy the constraints are generated based on different path search strategies and parameter settings, providing a foundation for subsequent trajectory optimization and selection.

[0087] Through the above, low-altitude flight trajectory planning based on a four-dimensional airspace grid structure was realized, which can effectively cope with complex low-altitude airspace environments, meet the flight mission requirements of aircraft, and provide technical support for the safe operation of low-altitude aircraft.

[0088] In one optional implementation, the sequence of grid cells traversed by the candidate flight trajectory is traversed, and each grid cell is associated with the occupancy status of allocated flight resources to determine the set of conflicting grid cells that conflict with the occupied grid cells in the spatiotemporal dimension, including:

[0089] Determine the sequence of grid cells traversed by the candidate flight trajectory, and query the occupancy status data of the allocated flight resources in the four-dimensional airspace grid structure;

[0090] Traverse each grid cell in the grid cell sequence, and match the spatial coordinates and time identifier of each grid cell with the occupied grid cells in the occupancy status data one by one to determine the grid cells in the grid cell sequence that coincide with the occupied grid cells in the occupancy status data in both spatial coordinates and time identifiers.

[0091] The simultaneously overlapping mesh cells are marked as conflicting mesh cells, and the conflicting mesh cells are sorted according to their position order in the mesh cell sequence to generate an ordered list of conflicting mesh cells;

[0092] Spatial continuity is determined for adjacent conflicting grid cells in the ordered list of conflicting grid cells to obtain the spatial continuity determination result;

[0093] Based on the spatial continuity determination result, the ordered list of conflict grid cells is divided into multiple spatially continuous conflict grid subsets, and the set of the conflict grid subsets is taken as the conflict grid set.

[0094] In four-dimensional airspace route planning, to ensure flight safety, conflict detection between candidate flight trajectories and allocated flight resources is required. The following describes in detail the method for traversing the grid cell sequence of candidate flight trajectories and determining the set of conflicting grid cells.

[0095] First, the sequence of grid cells traversed by the candidate flight trajectory is obtained. The candidate flight trajectory is typically represented as a series of three-dimensional coordinate points with time stamps. These coordinate points need to be mapped onto a four-dimensional spatial grid structure. By sampling the trajectory, a series of trajectory points can be obtained, each containing spatial coordinates (x, y, z) and a time stamp t. For each trajectory point, its grid cell number is determined according to a preset grid division standard, thus forming a sequence of grid cells. , where g represents the grid cell and n represents the sequence length.

[0096] Next, the occupancy status data of allocated flight resources in the four-dimensional airspace grid structure is queried. This occupancy status data is typically stored in the database of the airspace resource management system and contains information on all grid cells occupied by allocated flight resources. Each record includes the spatial coordinates of the grid cell, a time identifier, and the identifier of the flight resource occupying that grid cell. Through a database query operation, the set of all currently occupied grid cells is obtained. , where o represents the occupied grid cell and m represents the number of occupied grid cells.

[0097] Iterate through each grid cell in the grid cell sequence and match it with the occupancy status data. For each grid cell in sequence G... Check whether it coincides with any occupied grid cell in the occupied state data O in the spatiotemporal dimension. The specific matching process is as follows: For Iterate through each occupied grid cell in O. ,Compare and Spatial coordinates and time signatures. If Spatial coordinates and Their spatial coordinates are the same, and Time stamp and If the time markers overlap, then it is considered and A conflict occurs in the spacetime dimension.

[0098] Mesh cells that coincide simultaneously in the spatiotemporal dimensions are marked as conflicting mesh cells. For each mesh cell identified as conflicting with an already occupied mesh cell... These conflicting mesh elements are then added to the list of conflicting mesh elements C. Next, they are sorted according to their position in the original mesh element sequence G, generating an ordered list C' of conflicting mesh elements. This sorting ensures that the list of conflicting mesh elements maintains the order of the original trajectory, facilitating subsequent analysis.

[0099] Spatial continuity is determined for adjacent conflicting mesh cells in an ordered list of conflicting mesh cells. The purpose of spatial continuity determination is to identify spatially continuous conflict regions. For each pair of adjacent conflicting mesh cells C'[k] and C'[k+1] (k=1,2,...,|C'|-1) in C', the spatial distance d between them is calculated. If d is less than a preset threshold... If the two conflicting grid cells are found to be contiguous in space, they are considered to belong to different conflict regions; otherwise, they are considered to belong to different conflict regions. The preset threshold can be determined based on factors such as grid size and flight speed, and is usually set to the diagonal length of a grid cell.

[0100] Based on the spatial continuity determination results, the ordered list of conflicting mesh cells is divided into multiple spatially continuous conflicting mesh subsets. Starting from the first element of list C', continuous conflicting mesh cells are grouped into the same subset according to the spatial continuity determination results. When a mesh cell that is not continuous with the previous mesh cell is encountered, a new subset is started. The final set of conflicting mesh subsets is obtained. , where S represents a spatially continuous subset of conflict grids, and p represents the number of subsets.

[0101] For example, suppose a drone plans to fly from airport A to destination B, and its candidate flight path passes through a sequence of grid cells. The search revealed that... and These are grid cells already occupied by other flight resources, therefore, an ordered list of conflicting grid cells. By determining spatial continuity, This creates a continuous conflict zone. This creates another continuous conflict zone. This forms a third consecutive conflict zone. Therefore, the set of conflict grid subsets... .

[0102] This conflict detection method can accurately identify conflict areas between candidate flight trajectories and allocated flight resources in the spatiotemporal dimension, providing an important basis for subsequent trajectory adjustments and route planning, and ensuring flight safety and efficient use of airspace resources.

[0103] In one optional implementation, the sequence of grid cells traversed by the candidate flight trajectory is determined, and the occupancy status data of allocated flight resources in the four-dimensional airspace grid structure is queried, including:

[0104] The trajectory representation of the candidate flight trajectory is analyzed to obtain the set of discrete trajectory points of the candidate flight trajectory in the time dimension;

[0105] Interpolation processing is performed on the spatial interval between adjacent trajectory points in the discrete trajectory point set to generate supplementary trajectory points between adjacent trajectory points whose spatial interval exceeds the grid cell scale;

[0106] Map each trajectory point in the complete trajectory point sequence composed of the discrete trajectory point set and the supplementary trajectory points to the four-dimensional spatial grid structure to determine the grid cell corresponding to each trajectory point;

[0107] The grid cells are arranged according to the chronological order of the trajectory points in the candidate flight trajectory to generate a sequence of grid cells traversed by the candidate flight trajectory;

[0108] Access the resource occupancy state storage structure of the four-dimensional spatial grid structure;

[0109] Extract the grid cells marked as occupied from the resource occupancy status storage structure, obtain the binding data of the spatial coordinates, time identifier and aircraft identifier of the occupied grid cells, and generate the occupancy status data of the allocated flight resources.

[0110] When planning flight trajectories, it is necessary to determine the sequence of grid cells traversed by the candidate flight trajectories and query the occupancy status data of allocated flight resources in the four-dimensional airspace grid structure. The specific implementation process is as follows:

[0111] First, the trajectory representation of the candidate flight trajectory is analyzed to obtain the discrete trajectory point set of the candidate flight trajectory in the time dimension. The candidate flight trajectory can be expressed in various forms, such as Bézier curves, B-spline curves, piecewise linear interpolation, and other mathematical models. In practical applications, a time series format can be used. Denotes the set of trajectory points, where Represents the three-dimensional spatial coordinates of the i-th trajectory point. This represents the timestamp corresponding to the trajectory point. For example, during the process of a drone flying from the takeoff point (100,200,0) to the destination (500,700,100), multiple discrete trajectory points can be sampled.

[0112] Next, interpolation is performed on the spatial interval between adjacent trajectory points in the discrete trajectory point set. Supplementary trajectory points are generated between adjacent trajectory points whose spatial interval exceeds the grid cell scale. Specifically, adjacent trajectory points are calculated. and The Euclidean distance d between them. If d is greater than the grid cell size δ (for example, when the grid cell size is 10 meters, if the distance between adjacent trajectory points is 25 meters, interpolation is required), then interpolation is needed. and Supplementary trajectory points are inserted between them. The number of interpolations, n, can be determined according to the formula. Confirmed, among which This indicates rounding up. Subsequently, linear interpolation can be used to generate supplementary trajectory points. For the k-th supplementary point (k=1,2,...,n), its coordinates and timestamp are calculated as follows:

[0113] x-coordinate of the interpolation point = ;

[0114] The y-coordinate of the interpolation point = ;

[0115] z-coordinate of the interpolation point = ;

[0116] Interpolation point timestamp = .

[0117] In this way, the distance between any adjacent points is ensured to be less than the grid cell scale, guaranteeing that no grid cell passed by the candidate flight trajectory will be missed.

[0118] Subsequently, each trajectory point in the complete trajectory point sequence composed of the discrete trajectory point set and supplementary trajectory points is mapped to a four-dimensional spatial grid structure, determining the corresponding grid cell for each trajectory point. The four-dimensional spatial grid structure contains three-dimensional spatial coordinates and one-dimensional time coordinates, and can be represented as G(X,Y,Z,T). For a trajectory point P(x,y,z,t), the coordinates of the mapped grid cell can be calculated as follows:

[0119] Grid cell X coordinate = ;

[0120] Grid cell Y coordinate = ;

[0121] Z-coordinate of grid cell = ;

[0122] Grid cell T coordinate = .

[0123] Where δx, δy, and δz represent the grid cell scale in the three spatial dimensions X, Y, and Z, respectively, and δt represents the grid cell scale in the time dimension (e.g., 10 seconds). Indicates the starting point of time. This indicates rounding down. For example, when the spatial grid scale is 10m × 10m × 5m and the time grid scale is 10 seconds, the trajectory point (126.8, 235.4, 42.1, 1530) will be mapped to the grid cell (12, 23, 8, 153).

[0124] Then, the grid cells are arranged according to the chronological order of the trajectory points in the candidate flight trajectory to generate a sequence of grid cells traversed by the candidate flight trajectory. First, all trajectory points (including original discrete points and supplementary points) are sorted in ascending order by timestamp. Then, the grid cell coordinates corresponding to each trajectory point are extracted to form a grid cell sequence. Since multiple consecutive trajectory points may map to the same grid cell, deduplication is required to ensure that the final grid cell sequence does not contain duplicate adjacent grid cells.

[0125] Finally, the resource occupancy status storage structure of the four-dimensional airspace grid is accessed. Grid cells marked as occupied are extracted, and their spatial coordinates, time signatures, and aircraft identifiers are bound together to generate occupancy status data for allocated flight resources. This resource occupancy status storage structure can be implemented using data structures such as hash tables or spatial index trees (e.g., octtrees) to store the occupancy status of each grid cell. For each grid cell G(i,j,k,l), it is queried whether it is marked as "occupied." If occupied, the corresponding aircraft identifier ID and the occupied time period [t_start, t_end] are extracted to form an occupancy status data set {(i,j,k,l,ID,t_start,t_end)}. This data will be used for subsequent conflict detection and trajectory adjustment.

[0126] Through the above steps, the sequence of grid cells traversed by the candidate flight trajectory was determined, and the occupancy status data of the allocated flight resources in the four-dimensional airspace grid structure was queried, providing a foundation for subsequent flight resource allocation and conflict detection.

[0127] In one optional implementation, a conflict resolution search space is determined for the conflict grid set within a four-dimensional spatial grid structure. A conflict-free flight path avoiding the conflict grid set is generated by adjusting the time stamps or spatial coordinates of the grid cell sequence within the conflict resolution search space, including:

[0128] Based on the spatial coordinates and temporal identifiers of each conflicting grid cell in the conflicting grid set, the spatiotemporal distribution characteristics of the conflicting grid set in the four-dimensional spatial grid structure are determined;

[0129] For each conflict grid cell in the conflict grid set, the conflict resolution search space is determined in the four-dimensional spatial grid structure;

[0130] Based on the dynamic performance constraints of the aircraft, reachability filtering is performed on the available neighborhood grid cells in the conflict resolution search space to generate a dynamically reachable conflict resolution search space;

[0131] In the dynamically reachable resolution search space, determine the bypass grid path from the pre-conflict grid cell to the post-conflict grid cell of the candidate flight trajectory;

[0132] The conflict segment located between the pre-conflict and post-conflict grid cells in the grid cell sequence of the candidate flight trajectory is replaced with the detour grid path to generate an adjusted grid cell sequence;

[0133] The adjusted grid cell sequence is subjected to spatiotemporal continuity verification, and the adjusted grid cell sequence that passes the spatiotemporal continuity verification is used as a conflict-free flight path.

[0134] The process of determining the conflict resolution search space and generating conflict-free flight paths within a four-dimensional airspace grid structure first requires identifying the conflict grid set. This four-dimensional airspace grid structure consists of three-dimensional spatial coordinates and a one-dimensional time marker, which can accurately represent the aircraft's position information at a specific point in time.

[0135] Figure 2 This is a schematic diagram illustrating the process of determining a conflict-free flight path according to an embodiment of the present invention. Figure 2 As shown, firstly, based on the spatial coordinates and temporal markers of each conflict grid cell in the conflict grid set, the spatiotemporal distribution characteristics of the conflict grid set in the four-dimensional spatial grid structure are determined. Specifically, the temporal distribution patterns of the conflict grids are analyzed, such as whether the conflicts occur within a continuous time period or at discrete time points; the spatial distribution morphology is analyzed, such as the geometric shape, size, and directional characteristics of the conflict regions; the conflict density is assessed, the number of conflict grids per unit spacetime is calculated, and high-density conflict regions are identified. Through these characteristic analyses, a spatiotemporal distribution model of the conflict grid can be established, providing a basis for subsequent conflict resolution strategies.

[0136] For each conflict grid cell in the conflict grid set, a conflict resolution search space is determined within the four-dimensional spatial grid structure. This step is achieved by constructing search boundaries around the conflict grid cell. First, the temporal search range is determined, i.e., the interval from a certain point in time before the conflict to a certain point in time after the conflict. Then, the spatial search range is determined, and a three-dimensional spatial search boundary is set around the conflict grid cell based on the aircraft's maximum range and maneuverability. Finally, the temporal range and spatial boundary are combined to construct the four-dimensional search space.

[0137] Based on the aircraft's dynamic performance constraints, reachability filtering is performed on available neighborhood grid cells in the conflict resolution search space to generate a dynamically reachable conflict resolution search space. This process considers factors such as the aircraft's turning capability limitations, climb / descent rate limitations, and velocity variation range limitations. For each grid cell in the search space, the required turning angle, climb / descent rate, and velocity variation from the current position to that cell are calculated. If these parameters exceed the aircraft's performance parameters, the grid cell is removed from the search space. Thus, the final result is an reachable search space that satisfies the aircraft's dynamic performance constraints.

[0138] In a dynamically reachable resolution search space, a bypass grid path is determined from the pre-conflict grid cell to the post-conflict grid cell of the candidate flight trajectory. Specifically, the starting point is first marked as the safest grid cell preceding the conflicting grid cell in the candidate flight trajectory, and the ending point as the first safest grid cell after the conflict. Then, an improved A* search algorithm is applied to find the optimal bypass path in the dynamically reachable resolution search space. This algorithm uses a comprehensive cost function to evaluate the path, including factors such as path length, energy consumption, and flight time, and finds the lowest-cost bypass path through iterative search.

[0139] The conflict segments between pre-conflict and post-conflict grid cells in the candidate flight trajectory's grid cell sequence are replaced with detour grid paths, generating an adjusted grid cell sequence. In practice, the start and end positions of the segments to be replaced in the original trajectory are first determined, then that segment of the grid sequence is removed, and the detour grid path calculated in the previous step is inserted. To ensure a smooth trajectory transition, transition grid cells need to be added at connection points to reduce abrupt changes in heading or altitude.

[0140] The adjusted grid cell sequence undergoes a spatiotemporal continuity check. The adjusted grid cell sequence that passes the spatiotemporal continuity check is used as the conflict-free flight path. The spatiotemporal continuity check mainly examines whether the adjusted trajectory meets the following conditions: whether adjacent grid cells are spatially adjacent or continuous; whether the time signatures of adjacent grid cells conform to the aircraft's velocity constraints; and whether there are any time reversals or time jumps in the trajectory. If discontinuities are found, they need to be corrected by inserting transitional grid cells or adjusting the time signatures of grid cells. Only grid cell sequences that pass the spatiotemporal continuity check can ensure the aircraft's actual flight capability; therefore, they are determined as the final conflict-free flight path.

[0141] In a practical application scenario, suppose a drone, while planning its flight path in urban airspace, detects a potential conflict with another drone 500 meters ahead. Rapid analysis of the two drones' trajectories identifies a conflict grid set containing five grid cells across three consecutive time points. Analysis of the conflict characteristics determines this to be a transient intersection conflict. A spherical search space with a 30-second time span and a 200-meter radius is constructed for the drone, centered on the conflict area. Considering the dynamic constraints of the drone's maximum turning rate of 15° per second and maximum climb rate of 5 meters per second, approximately 40% of the unreachable grid cells in the search space are filtered out. Within the dynamically reachable search space, a path is successfully found that bypasses the conflict area by temporarily climbing 30 meters and making a slight right turn, replacing the seven grid cells of the original conflict section. After spatiotemporal continuity verification, it is confirmed that this bypass path satisfies the aircraft dynamics constraints and will not generate new conflicts, ultimately generating a complete conflict-free flight path.

[0142] In one optional implementation, reachability filtering is performed on available neighborhood grid cells in the conflict resolution search space based on the aircraft's dynamic performance constraints to generate a dynamically reachable conflict resolution search space, including:

[0143] For each available neighboring grid cell in the conflict resolution search space, determine the state transition trajectory from the pre-conflict grid cell to the available neighboring grid cell;

[0144] Based on the kinematic and dynamic characteristics of the state transition trajectory, determine the mapping relationship between the kinematic characteristics and the geometric motion constraints in the dynamic performance constraints;

[0145] Based on the kinematic and dynamic characteristics of the state transition trajectory, determine the mapping relationship between the dynamic characteristics and the dynamic output constraints in the dynamic performance constraints;

[0146] Based on the geometric motion constraints, the feasibility of the kinematic features is determined, and based on the dynamic output constraints, the feasibility of the dynamic features is determined, and the available neighborhood grid cells that pass both the feasibility determination of the geometric motion constraints and the feasibility determination of the dynamic output constraints are determined.

[0147] Available neighborhood grid cells that pass the dual feasibility determination are marked as dynamically reachable grid cells, and the set of all dynamically reachable grid cells in the conflict resolution search space is taken as the dynamically reachable resolution search space.

[0148] In this embodiment, firstly, for each available neighboring grid cell in the conflict resolution search space, the state transition trajectory from the pre-conflict grid cell to the available neighboring grid cell is determined. Specifically, this can be achieved by constructing a polynomial trajectory function from the current grid cell to the target neighboring grid cell. This trajectory function includes a time parameter t and spatial position parameters (x, y, z). Based on the trajectory function, the path curve required for the aircraft to fly from the current grid cell to the target neighboring grid cell can be obtained. For example, a cubic Bézier curve can be used as the trajectory function. By setting the starting position, ending position, and two control points, a smooth state transition trajectory can be generated. This trajectory not only describes the change in the aircraft's spatial position but also includes time functions of parameters such as velocity and acceleration.

[0149] After trajectory generation, the mapping relationship between the kinematic and dynamic characteristics of the state transition trajectory and the geometric constraints in the dynamic performance constraints is determined based on these characteristics. The kinematic characteristics mainly include the aircraft's position, velocity, acceleration, attitude angles, and angular velocity during the state transition. The geometric constraints include maximum flight speed limits, maximum turning angle limits, and maximum climb / dive angle limits. The mapping relationship is established by calculating the kinematic parameters of discrete points on the trajectory and comparing them with the geometric constraints. For example, for a trajectory point at a certain time t, its velocity vector v(t) is calculated, and then it is determined whether |v(t)| is less than or equal to the aircraft's maximum speed limit Vmax. The trajectory curvature is calculated to determine whether the minimum turning radius requirement is met.

[0150] Simultaneously, based on the kinematic and dynamic characteristics of the state transition trajectory, the mapping relationship between the dynamic characteristics and the power output constraints in the dynamic performance constraints is determined. The dynamic characteristics mainly include parameters such as thrust and torque required by the aircraft during trajectory execution, while the power output constraints include maximum thrust limits, maximum acceleration limits, and energy consumption limits. For example, based on the acceleration components of the trajectory and the mass of the aircraft, the thrust F(t) required to execute the trajectory is calculated, and it is determined whether F(t) is less than or equal to the maximum available thrust Fmax of the aircraft; at the same time, it is considered whether the centrifugal force of the aircraft during the turn is within the structural bearing capacity.

[0151] Feasibility assessments are performed on kinematic features based on geometric motion constraints and on dynamic features based on dynamic output constraints. Usable neighborhood grid cells that pass both geometric motion and dynamic output constraint feasibility assessments are identified. The specific assessment process involves: for discrete time points on the trajectory... Calculate the corresponding kinematic characteristic quantities and dynamic characteristic quantities If the characteristic quantities at all time points satisfy the constraints, the trajectory is considered dynamically feasible. For example, if the velocity is always less than or equal to the maximum velocity limit and the required thrust is always less than or equal to the maximum thrust limit throughout the entire trajectory, then the neighborhood grid cells corresponding to the trajectory are determined to be dynamically reachable.

[0152] Available neighboring grid cells that pass the dual feasibility test are marked as dynamically reachable grid cells. The set of all dynamically reachable grid cells in the conflict resolution search space is taken as the dynamically reachable conflict resolution search space. In practice, a Boolean flag array can be used to record the reachability state of each grid cell. For all available neighboring grid cells in the search space, if the cell passes the dual feasibility test, its corresponding flag is set to true, indicating that the grid cell is dynamically reachable; otherwise, it is set to false, indicating that although the grid cell is geometrically feasible, it is actually unreachable after considering the dynamic performance constraints of the aircraft.

[0153] In practical applications, computational efficiency can be further optimized. For example, mesh cells that clearly violate constraints can be directly excluded without detailed trajectory generation and verification. For instance, if the straight-line distance between two mesh cells exceeds the maximum distance the aircraft can fly within a specified time, the neighboring mesh cell can be directly determined as unreachable. Furthermore, based on the aircraft's dynamic performance characteristics, reachability templates for typical scenarios can be pre-calculated to quickly filter out obviously unreachable mesh cells.

[0154] Through the above steps, dynamic reachability filtering of the conflict resolution search space is completed. Each grid cell in the obtained dynamic reachability resolution search space can ensure that the aircraft can safely reach the grid cell before the conflict under its dynamic performance constraints, providing a reasonable search range for subsequent conflict resolution path planning and improving the efficiency and feasibility of the planning.

[0155] In one optional implementation, the grid cell sequence corresponding to the conflict-free flight path is marked as occupied, and the occupied state is bound to the aircraft identifier to obtain an airspace resource allocation record, including:

[0156] Extract the spatial coordinates and time signatures of each grid cell in the grid cell sequence corresponding to the conflict-free flight path to generate an airspace resource occupancy list;

[0157] For each grid cell in the airspace resource occupancy list, the corresponding grid node is determined in the four-dimensional airspace grid structure;

[0158] When the current occupancy status of the grid node is marked as unoccupied, the occupancy status of the grid node is changed to marked as occupied, thus completing the state transition of the grid node;

[0159] Write the grid node identifier of the grid node that has completed the state transition into the binding object field, and write the aircraft identifier into the binding attribute field to determine the association mapping relationship between the occupied state of the grid node and the aircraft identifier, thus obtaining the resource binding data structure;

[0160] Based on the resource binding data structure of all grid nodes, an airspace resource allocation record corresponding to the aircraft identifier is generated.

[0161] The process of marking the grid cell sequence corresponding to the conflict-free flight path as occupied and binding the occupied state with the aircraft identifier to obtain the airspace resource allocation record can be specifically implemented through the following steps.

[0162] First, the spatial coordinates and time signatures of each grid cell in the grid cell sequence corresponding to the conflict-free flight path are extracted to generate an airspace resource occupancy list. Specifically, for a determined conflict-free flight path, the path is typically represented as a series of four-dimensional coordinate points, containing three-dimensional spatial coordinates and corresponding time information. The flight path planning module can obtain all the grid cells that the aircraft is expected to pass through. Each grid cell has a unique identifier, consisting of a spatial index (x, y, z) and a time index t. For example, the flight path can be represented as:

[0163] Each quadruple represents a complete identifier for a grid cell.

[0164] During the extraction process, these quadruple information are saved as structured data to form an airspace resource occupancy list, which records all airspace resources that the aircraft needs to occupy and their time windows.

[0165] Next, for each grid cell in the airspace resource occupancy list, the corresponding grid node is determined in the four-dimensional airspace grid structure. The four-dimensional airspace grid structure is a pre-constructed data structure used to manage the resource status of the entire airspace. By querying the index system of the four-dimensional airspace grid structure, the corresponding grid node for each grid cell in the data structure can be quickly located. In specific implementations, hash tables, quadtrees, octrees, or other data structures can be used for efficient indexing. For example, a combination of spatial coordinates and time identifiers can be used as the key to find the corresponding grid node object. This step maps each abstract grid cell in the airspace resource occupancy list to a specific grid node instance in the four-dimensional airspace grid structure.

[0166] When a grid node's current occupancy status is marked as unoccupied, the occupancy status is changed to occupied, completing the grid node's state transition. Specifically, the current status flag of the grid node is first checked. This flag is typically a boolean or enumeration type, such as 0 (unoccupied) or 1 (occupied). If the current status is detected as unoccupied (0), it is updated to occupied (1). This process requires atomic operations to ensure data consistency in high-concurrency environments and prevent conflicts when multiple aircraft simultaneously request the same grid resource. The state transition operation usually also records the transition timestamp for subsequent resource reclamation and state tracking.

[0167] The grid node identifier of the grid node that has completed its state transition is written to the binding object field, and the aircraft identifier is written to the binding attribute field. This determines the association mapping between the occupied state of the grid node and the aircraft identifier, resulting in a resource binding data structure. In this step, each occupied grid node needs to establish an association with the aircraft that occupies it. Specifically, a key-value pair structure can be used, where the grid node identifier is the binding object and the aircraft identifier is the binding attribute. For example, a resource binding record of the following form can be constructed:

[0168] The data structure, `aircraftId:UAV-2023001,status:occupied,timestamp:2023-06-01T10:30:45Z`, clearly represents the fact that a specific spatiotemporal grid is occupied by a specific aircraft, and can be supplemented with additional information such as the start time of occupation and the expected release time.

[0169] Finally, based on the resource binding data structure of all grid nodes, an airspace resource allocation record corresponding to the aircraft identifier is generated. This step aggregates all the previously created resource binding data to form a complete airspace resource allocation record. This record contains information such as the aircraft identifier, a list of all allocated grid resources, and the time range of resource occupation. The allocation record can be organized into a hierarchical structure, with the top layer being aircraft information and the lower layer being a list of grid resources arranged in chronological order. This structure facilitates quick retrieval of airspace resources occupied by a specific aircraft at a specific point in time, and also facilitates resource release and conflict detection. The allocation record can be serialized into formats such as JSON or XML for storage and transmission, or it can be stored in relational or non-relational databases to support efficient querying.

[0170] Through the above steps, the occupancy marking of the grid cells corresponding to the conflict-free flight path and the binding process with the aircraft identifier were completed, forming a structured airspace resource allocation record, which lays the data foundation for subsequent airspace monitoring, conflict early warning and resource recovery.

[0171] The low-altitude airspace fine-grained management system based on a four-dimensional airspace grid according to embodiments of the present invention includes:

[0172] The first unit is used to divide the target airspace into three-dimensional spatial grid units according to the geographical boundaries and altitude levels of the low-altitude airspace, and associate time dimension attributes with each spatial grid unit to obtain a four-dimensional airspace grid structure. Based on the flight mission requirements of the aircraft, candidate flight trajectories are generated in the four-dimensional airspace grid structure.

[0173] The second unit is used to traverse the sequence of grid cells passed by the candidate flight trajectory, associate and match each grid cell with the occupancy status of the allocated flight resources, and determine the set of conflicting grid cells that conflict with the occupied grid cells in the spatiotemporal dimension.

[0174] The third unit is used to determine the conflict resolution search space for the conflict grid set in the four-dimensional airspace grid structure, and to generate a conflict-free flight path that avoids the conflict grid set by adjusting the time marker or spatial coordinate of the grid cell sequence in the conflict resolution search space.

[0175] The fourth unit is used to mark the grid cell sequence corresponding to the conflict-free flight path as occupied, and bind the occupied state with the aircraft identifier to obtain an airspace resource allocation record. The airspace resource allocation record is used for conflict detection and airspace resource status query in subsequent flight missions.

[0176] A third aspect of the present invention provides an electronic device, comprising:

[0177] processor;

[0178] Memory used to store processor-executable instructions;

[0179] The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0180] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0181] This invention can be a method, apparatus, system, and / or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of the invention.

[0182] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for refined management of low-altitude airspace based on a four-dimensional airspace grid, characterized in that, include: Based on the geographical boundaries and altitude levels of the low-altitude airspace, the target airspace is divided into three-dimensional spatial grid units, and a four-dimensional airspace grid structure is obtained by associating a time dimension attribute with each spatial grid unit. Candidate flight trajectories are generated in the four-dimensional airspace grid structure based on the flight mission requirements of the aircraft. Traverse the sequence of grid cells traversed by the candidate flight trajectory, associate and match each grid cell with the occupancy status of the allocated flight resources, and determine the set of conflicting grid cells that conflict with the occupied grid cells in the spatiotemporal dimension. For the conflict grid set, a conflict resolution search space is determined in the four-dimensional airspace grid structure. By adjusting the time marker or spatial coordinate of the grid cell sequence in the conflict resolution search space, a conflict-free flight path that avoids the conflict grid set is generated. The grid cell sequence corresponding to the conflict-free flight path is marked as occupied, and the occupied state is bound to the aircraft identifier to obtain an airspace resource allocation record. The airspace resource allocation record is used for conflict detection and airspace resource status query in subsequent flight missions. The process of determining a conflict resolution search space for the conflict grid set within a four-dimensional spatial grid structure, and generating a conflict-free flight path to avoid the conflict grid set by adjusting the time markers or spatial coordinates of the grid cell sequence within the conflict resolution search space, includes: Based on the spatial coordinates and temporal identifiers of each conflicting grid cell in the conflicting grid set, the spatiotemporal distribution characteristics of the conflicting grid set in the four-dimensional spatial grid structure are determined; For each conflict grid cell in the conflict grid set, the conflict resolution search space is determined in the four-dimensional spatial grid structure; Based on the dynamic performance constraints of the aircraft, reachability filtering is performed on the available neighborhood grid cells in the conflict resolution search space to generate a dynamically reachable conflict resolution search space; In the dynamically reachable resolution search space, determine the bypass grid path from the pre-conflict grid cell to the post-conflict grid cell of the candidate flight trajectory; The conflict segment located between the pre-conflict and post-conflict grid cells in the grid cell sequence of the candidate flight trajectory is replaced with the detour grid path to generate an adjusted grid cell sequence; The adjusted grid cell sequence is subjected to spatiotemporal continuity verification, and the adjusted grid cell sequence that passes the spatiotemporal continuity verification is used as a conflict-free flight path. The dynamic performance constraints based on the aircraft perform reachability filtering on available neighborhood grid cells in the conflict resolution search space to generate a dynamically reachable conflict resolution search space, including: For each available neighboring grid cell in the conflict resolution search space, determine the state transition trajectory from the pre-conflict grid cell to the available neighboring grid cell; Based on the kinematic and dynamic characteristics of the state transition trajectory, determine the mapping relationship between the kinematic characteristics and the geometric motion constraints in the dynamic performance constraints; Based on the kinematic and dynamic characteristics of the state transition trajectory, determine the mapping relationship between the dynamic characteristics and the dynamic output constraints in the dynamic performance constraints; Based on the geometric motion constraints, the feasibility of the kinematic features is determined, and based on the dynamic output constraints, the feasibility of the dynamic features is determined, and the available neighborhood grid cells that pass both the feasibility determination of the geometric motion constraints and the feasibility determination of the dynamic output constraints are determined. Available neighborhood grid cells that pass the dual feasibility determination are marked as dynamically reachable grid cells, and the set of all dynamically reachable grid cells in the conflict resolution search space is taken as the dynamically reachable resolution search space.

2. The method according to claim 1, characterized in that, Based on the geographical boundaries and altitude levels of the low-altitude airspace, the target airspace is divided into three-dimensional spatial grid cells. A four-dimensional airspace grid structure is obtained by associating a time dimension attribute with each spatial grid cell. Candidate flight trajectories are then generated within this four-dimensional airspace grid structure based on the aircraft's flight mission requirements. These trajectories include: Geographic boundary data and altitude level parameters of low-altitude airspace are obtained. Based on the geographic boundary data, spatial discretization is performed in the horizontal direction, and based on the altitude level parameters, altitude layering is performed in the vertical direction to obtain three-dimensional spatial grid cells. Associating each three-dimensional spatial grid cell with a time granularity identifier yields a four-dimensional spatial grid structure; Analyze the flight mission requirements of the aircraft and extract the starting position coordinates, target position coordinates, and flight time window; The starting position coordinates and the target position coordinates are respectively mapped to the four-dimensional spatial grid structure to determine the starting grid cell corresponding to the starting position coordinates and the target grid cell corresponding to the target position coordinates; Based on the starting grid cell and the target grid cell, the grid cell connection path is determined in the four-dimensional spatial grid structure; The time dimension constraint verification is performed on the connected paths of the grid cells to determine whether the time identifier of each grid cell in the connected paths of the grid cells meets the constraint conditions of the flight time window, and the grid cell sequence that meets the constraint conditions of the flight time window is retained as a candidate flight trajectory.

3. The method according to claim 1, characterized in that, Traverse the sequence of grid cells traversed by the candidate flight trajectory, associate and match each grid cell with the occupancy status of allocated flight resources, and determine the set of conflicting grid cells that conflict with occupied grid cells in the spatiotemporal dimension, including: Determine the sequence of grid cells traversed by the candidate flight trajectory, and query the occupancy status data of the allocated flight resources in the four-dimensional airspace grid structure; Traverse each grid cell in the grid cell sequence, and match the spatial coordinates and time identifier of each grid cell with the occupied grid cells in the occupancy status data one by one to determine the grid cells in the grid cell sequence that coincide with the occupied grid cells in the occupancy status data in both spatial coordinates and time identifiers. The simultaneously overlapping mesh cells are marked as conflicting mesh cells, and the conflicting mesh cells are sorted according to their position order in the mesh cell sequence to generate an ordered list of conflicting mesh cells; Spatial continuity is determined for adjacent conflicting grid cells in the ordered list of conflicting grid cells to obtain the spatial continuity determination result; Based on the spatial continuity determination result, the ordered list of conflict grid cells is divided into multiple spatially continuous conflict grid subsets, and the set of the conflict grid subsets is taken as the conflict grid set.

4. The method according to claim 3, characterized in that, Determine the sequence of grid cells traversed by the candidate flight trajectory, and query the occupancy status data of allocated flight resources in the four-dimensional airspace grid structure, including: The trajectory representation of the candidate flight trajectory is analyzed to obtain the set of discrete trajectory points of the candidate flight trajectory in the time dimension; Interpolation processing is performed on the spatial interval between adjacent trajectory points in the discrete trajectory point set to generate supplementary trajectory points between adjacent trajectory points whose spatial interval exceeds the grid cell scale; Map each trajectory point in the complete trajectory point sequence composed of the discrete trajectory point set and the supplementary trajectory points to the four-dimensional spatial grid structure to determine the grid cell corresponding to each trajectory point; The grid cells are arranged according to the chronological order of the trajectory points in the candidate flight trajectory to generate a sequence of grid cells traversed by the candidate flight trajectory; Access the resource occupancy state storage structure of the four-dimensional spatial grid structure; Extract the grid cells marked as occupied from the resource occupancy status storage structure, obtain the binding data of the spatial coordinates, time identifier and aircraft identifier of the occupied grid cells, and generate the occupancy status data of the allocated flight resources.

5. The method according to claim 1, characterized in that, The grid cell sequence corresponding to the conflict-free flight path is marked as occupied, and the occupied state is bound to the aircraft identifier to obtain an airspace resource allocation record, including: Extract the spatial coordinates and time signatures of each grid cell in the grid cell sequence corresponding to the conflict-free flight path to generate an airspace resource occupancy list; For each grid cell in the airspace resource occupancy list, the corresponding grid node is determined in the four-dimensional airspace grid structure; When the current occupancy status of the grid node is marked as unoccupied, the occupancy status of the grid node is changed to marked as occupied, thus completing the state transition of the grid node; Write the grid node identifier of the grid node that has completed the state transition into the binding object field, and write the aircraft identifier into the binding attribute field to determine the association mapping relationship between the occupied state of the grid node and the aircraft identifier, thus obtaining the resource binding data structure; Based on the resource binding data structure of all grid nodes, an airspace resource allocation record corresponding to the aircraft identifier is generated.

6. A low-altitude airspace fine-grained management system based on a four-dimensional airspace grid, used to implement the method as described in any one of claims 1-5, characterized in that, include: The first unit is used to divide the target airspace into three-dimensional spatial grid units according to the geographical boundaries and altitude levels of the low-altitude airspace, and associate time dimension attributes with each spatial grid unit to obtain a four-dimensional airspace grid structure. Based on the flight mission requirements of the aircraft, candidate flight trajectories are generated in the four-dimensional airspace grid structure. The second unit is used to traverse the sequence of grid cells passed by the candidate flight trajectory, associate and match each grid cell with the occupancy status of the allocated flight resources, and determine the set of conflicting grid cells that conflict with the occupied grid cells in the spatiotemporal dimension. The third unit is used to determine the conflict resolution search space for the conflict grid set in the four-dimensional airspace grid structure, and to generate a conflict-free flight path that avoids the conflict grid set by adjusting the time marker or spatial coordinate of the grid cell sequence in the conflict resolution search space. The fourth unit is used to mark the grid cell sequence corresponding to the conflict-free flight path as occupied, and bind the occupied state with the aircraft identifier to obtain an airspace resource allocation record. The airspace resource allocation record is used for conflict detection and airspace resource status query in subsequent flight missions.

7. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 5.

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