A method, system, device, and storage medium for constructing a hierarchical topology for low-altitude routes for large-scale flight.

Abstract

This invention discloses a method, system, device, and storage medium for constructing a layered topology for low-altitude airways for large-scale flight operations. The method includes: acquiring the airworthiness space, mission requirement matrix, capacity evaluation results, and operational load constraints of a target area; converting the airworthiness space into a layered navigation map containing altitude layer attributes; generating candidate passage edges in the layered navigation map based on the mission requirement matrix; comparing the load parameters of the candidate passage edges with the operational load constraints based on the capacity evaluation results to identify bottleneck units and high-load units that exceed the constraint range; and performing addition, deletion, merging, diversion, or inter-layer transfer processing on the candidate passage edges corresponding to the identified bottleneck units and high-load units according to load balancing rules and bottleneck mitigation rules to generate a layered airway topology.

Description

Technical Field

[0001] This invention belongs to the technical fields of low-altitude traffic network organization, hierarchical navigation map construction, operational load balancing, and low-altitude air conditioning infrastructure. Specifically, it relates to a method, system, equipment, and storage medium for constructing a hierarchical topology of low-altitude airways for large-scale flights. Background Technology

[0002] As low-altitude operations shift from a limited number of demonstration flights to multi-mission, multi-schedule, and multi-time-period operations, single-path planning is difficult to distill into a reusable operational structure. If routes are generated solely based on static spatial morphology, problems such as local bottlenecks, path concentration, insufficient inter-level transitions, and increased conflicts during peak hours can easily arise. Summary of the Invention

[0003] To address the problems of existing low-altitude route construction methods, which rely on fixed layers, directions, or grid rules, making them ill-suited for the dynamically changing mission requirements of large-scale flights and prone to local bottlenecks, path congestion, and increased conflicts during peak hours, this invention provides a method for constructing a layered route topology based on airworthiness space, mission requirements, and capacity feedback. This method converts airworthiness space into a layered navigation map and missions into origin-destination demand matrices. Candidate edges are generated on the layered navigation map, bottleneck areas and high-load edges are identified based on capacity evaluation results, and topology updates such as additions, deletions, merging, diversions, or inter-layer transfers are performed according to load balancing rules. This achieves the goal of forming an adaptive layered route topology structure capable of supporting large-scale operations, improving airspace utilization efficiency, and enhancing flight safety.

[0004] According to one aspect of the present invention, a method for constructing a layered topology for low-altitude routes for large-scale flight is provided, comprising: acquiring the airworthiness space, mission requirement matrix, capacity evaluation results, and operational load constraints of a target area; converting the airworthiness space into a layered navigation map containing altitude layer attributes; generating candidate passage edges in the layered navigation map according to the mission requirement matrix; comparing the load parameters of the candidate passage edges with the operational load constraints based on the capacity evaluation results, and identifying bottleneck units and high-load units that exceed the constraint range; and performing addition, deletion, merging, diversion, or inter-layer transfer processing on the candidate passage edges corresponding to the identified bottleneck units and high-load units according to load balancing rules and bottleneck mitigation rules, thereby generating a layered route topology.

[0005] As a further technical solution, the hierarchical navigation map consists of flight-ready grid nodes, adjacent passage relationships, inter-layer transition relationships, and edge attributes; the edge attributes include length, risk cost, capacity margin, historical conflict frequency, and estimated passage time.

[0006] As a further technical solution, the task demand matrix is ​​generated based on origin-destination pairs, task type, time period demand intensity, and aircraft type, and is used to represent the expected traffic flow between different spatial units.

[0007] As a further technical solution, the bottleneck unit is identified by at least one of the following indicators: edge betweenness number, traffic flow, conflict frequency, resolution failure rate, or number of alternative paths; wherein, the resolution failure rate is the ratio of the number of conflict resolution failures to the scale of traffic demand during capacity assessment or simulation.

[0008] As a further technical solution, the load balancing rules include: adding alternative edges for high-load channels, guiding some tasks to adjacent height layers, increasing the passage weight of low-load layers, or limiting the task allocation ratio of bottleneck edges.

[0009] As a further technical solution, the bottleneck mitigation rules include: performing diversion connections for locally narrow connected areas, performing boundary connections for isolated flight-ready areas, or performing local detour reconfiguration for high-conflict areas.

[0010] As a further technical solution, the hierarchical route topology undergoes reachability verification, capacity verification, and risk verification before output. If the verification fails, the candidate travel edges are returned for adjustment.

[0011] According to one aspect of the present invention, a low-altitude route hierarchical topology construction system for large-scale flight is provided, comprising: a flightable space access module for acquiring flightable space in a target area; a hierarchical navigation map construction module for converting the flightable space into a hierarchical navigation map containing altitude layer attributes; a demand mapping module for generating candidate passage edges in the hierarchical navigation map according to a mission demand matrix; a bottleneck identification module for comparing the load parameters of the candidate passage edges with operational load constraints based on capacity evaluation results, and identifying bottleneck units and high-load units that exceed the constraint range; and a topology update module for performing addition, deletion, merging, diversion, or inter-layer transfer processing on the candidate passage edges corresponding to the identified bottleneck units and high-load units according to load balancing rules and bottleneck mitigation rules, thereby generating a hierarchical route topology structure.

[0012] According to one aspect of the present invention, an electronic device is provided, including a memory, a processor, and program instructions stored in the memory and executable by the processor, wherein the processor, when executing the program instructions, implements the aforementioned method for constructing a low-altitude route hierarchical topology for large-scale flight.

[0013] According to one aspect of the present invention, a non-transitory computer-readable storage medium is provided, storing computer instructions that, when executed by a processor, implement the aforementioned method for constructing a low-altitude route hierarchical topology for large-scale flight.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention can dynamically generate reusable hierarchical airway topology based on actual mission requirements and capacity assessment results, effectively overcoming the shortcomings of traditional fixed airway networks in adapting to traffic fluctuations. By identifying bottleneck units and high-load units in real time and performing targeted addition, deletion, merging, diversion, or inter-layer transfer processing, it can significantly reduce path congestion and flight conflicts caused by local bottlenecks. By introducing inter-layer transfer and alternative channel mechanisms, it can flexibly guide the balanced distribution of mission traffic across different altitude layers and paths, greatly improving the mission diversion capability and robustness of the airway network. In addition, this invention can seamlessly integrate with conflict detection, capacity simulation, and scheduling systems to form a closed-loop operation system of "identification-adjustment-verification-optimization," continuously improving the operational efficiency and safety assurance level of the low-altitude airway network.

[0015] Furthermore, by introducing operational load constraints and a task requirement matrix that includes aircraft type categories, this invention enables the hierarchical route topology construction to not only consider spatial reachability but also the capacity occupancy differences of different aircraft types on nodes, passage edges, and inter-layer transfer edges in different time slices. This allows for more accurate identification of high-load units and bottleneck units, thereby improving the safety and schedulability of route topology in large-scale operation scenarios. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating a method for constructing a low-altitude airway hierarchical topology for large-scale flight, provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the hierarchical navigation map and task requirement mapping provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of bottleneck identification and topology update provided for an embodiment of the present invention. Detailed Implementation

[0018] It should be noted that the terms mentioned in this invention specification are explained as follows: A layered navigation graph refers to a graph structure consisting of flight-ready nodes, same-layer edges, and inter-layer transition edges.

[0019] The task demand matrix refers to traffic demand in terms of origin and destination, time period, task type, and aircraft type.

[0020] Bottleneck units refer to nodes or edges with high capacity utilization, high frequency of conflicts, or insufficient alternative paths.

[0021] Layered route topology refers to the low-altitude route chart structure used for route planning, scheduling, and monitoring.

[0022] Capacity assessment results refer to feedback results obtained from capacity assessment or operational simulation, such as capacity margin, conflict frequency, resolution failure rate, delays, or bottleneck locations.

[0023] Inter-layer transition relationship refers to the passage relationship connecting nodes at different heights, used to indicate the spatial location and constraints that allow layer switching, climbing or descending.

[0024] The conflict resolution failure rate refers to the ratio between the number of conflict resolution failures and the scale of traffic demand during capacity assessment or simulation, and is used to identify bottleneck units.

[0025] The terms “comprising” and “having”, and any variations thereof, in the specification, claims, and accompanying drawings of this invention are intended to cover a non-exclusive inclusion, such as a process, method, system, product, or apparatus that includes a series of steps or units, not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] The core of the method provided by this invention lies in using operational data feedback for adaptive topology organization of hierarchical routes, rather than employing fixed layers, fixed directions, or fixed grid rules. To reduce overlap with fixed-rule hierarchical expressions in published fundamental theories, the scope of protection of this invention is not limited to specific layer heights, specific direction rules, or fixed geometric paradigms. Instead, it focuses its innovation on the adaptive construction of hierarchical topology driven by task requirements and capacity feedback. To make the objectives, technical solutions, and advantages of the embodiments of this invention clearer, the technical solutions in the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention. Furthermore, the technical features of the various embodiments or individual embodiments provided by this invention can be arbitrarily combined to form new technical solutions. Such combinations are not constrained by the order of steps and / or structural composition patterns, but must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0027] Example 1

[0028] This embodiment provides a method for constructing a hierarchical topology for low-altitude routes oriented towards large-scale flight. (Refer to...) Figure 1 The method includes the following steps.

[0029] Step 1: Obtain input data.

[0030] The system acquires the flight-ready space, mission requirement matrix, capacity evaluation results, and operational load constraints of the target area.

[0031] Among them, the space suitable for flight is represented as It contains three-dimensional spatial information of the flyable area.

[0032] The task demand matrix is ​​used to describe the projected traffic demand under different origin and destination points, task types, aircraft types, and time periods. For example, the task demand matrix can be represented as follows: In this matrix, o represents the task start-point spatial unit, d represents the task end-point spatial unit, q represents the task type (e.g., order, inspection, cultural tourism, or emergency), k represents the aircraft type, and t represents the task time period. The aircraft type can include at least one of small multi-rotor drones, medium-sized heavy-duty drones, fixed-wing drones, compound-wing drones, or eVTOLs. If only the total task volume is available in the actual system, the aircraft type can be used as an attribute field in the task requirement record, or an aircraft type distribution can be generated based on the task type and historical operational data. This matrix can be generated from order data, inspection plans, scenic area visitor flow, hospital sample transfer requirements, or emergency task plans.

[0033] The capacity assessment results are obtained from capacity assessment or operational simulation, including feedback results such as capacity margin, collision frequency, resolution failure rate, delay and bottleneck location for each airspace unit.

[0034] Operational load constraints are used to limit the maximum acceptable operational load of nodes, passage edges, inter-layer transition edges, and altitude layers in a hierarchical route topology within a given time slice. Specifically, the operational load constraints include at least one of the following: capacity utilization constraints, conflict frequency constraints, resolution failure rate constraints, operational delay constraints, inter-layer transition constraints, aircraft type throughput constraints, and task priority and time window constraints.

[0035] Capacity utilization constraint: Used to limit the maximum traffic load of nodes, access edges, or height layers per unit time. For example, the capacity utilization of edge e in time period t shall not exceed Umax (e.g., 0.8).

[0036] Conflict frequency constraint: used to limit the number of prediction conflicts or conflict density, such as the maximum number of prediction conflicts allowed per unit time (confmax, e.g., 10 times / hour).

[0037] Failure rate constraint: Used to limit the proportion of the number of failed conflict resolutions to the number of tasks or the number of conflicts, such as the upper limit of the failure rate (failmax, e.g., 0.05).

[0038] Runtime delay constraints: used to limit average delay, maximum delay, or queuing time, such as the maximum tolerable delay delaymax.

[0039] Inter-layer transition constraints: These are used to limit the number of layer transitions allowed per unit of time, the occupancy rate of transition edges, and the transition time window, such as the upper limit of the occupancy rate of inter-layer transition edges.

[0040] Aircraft type constraints: These are used to limit the passage conditions for different aircraft types in terms of aisle width, safety interval, turning radius, speed range, and climbing and descending capabilities.

[0041] Task priority and time window constraints: These are used to limit the maximum detour and maximum delay requirements for high-priority tasks, time-limited tasks, and emergency tasks, so as to distinguish between ordinary congestion and obstruction of critical tasks when identifying bottlenecks.

[0042] Step 2: Convert the flight space into a hierarchical navigation map.

[0043] like Figure 2 As shown, the system converts the flyable space into a hierarchical navigation map that includes altitude layer attributes. Each flyable grid is combined with an altitude layer to form a graph node. If two nodes are located at the same altitude level and are spatially adjacent, the passage width meets the aircraft type requirements, and the risk cost is below the threshold, then a same-level passage edge is generated; if adjacent altitude levels are both flight-ready spaces in the allowed positions and meet the climb or descent performance requirements, then an inter-level transition edge is generated.

[0044] The resulting hierarchical navigation map It consists of flight-ready grid nodes, adjacent access relationships, inter-layer transition relationships, and edge attributes. Each edge stores the following attributes: length. Risk and cost Expected travel time , capacity margin Frequency of historical conflicts Dissolution failure rate and the number of alternative paths .

[0045] Step 3: Generate candidate access edges based on the task requirement matrix.

[0046] The system maps the task requirement matrix to a hierarchical navigation graph and uses shortest path, multi-path allocation, or capacity-constrained allocation methods for initial route allocation to obtain the expected throughput of each edge under different machine models. This generates candidate access edges in the hierarchical navigation graph.

[0047] For the task requirement matrix The system first generates candidate paths for each type of origin and destination, task type, machine type, and time period. If a certain edge If the request is used by the corresponding path, then the request is counted as an edge. The projected load can be expressed as:

[0048]

[0049] in, Representing an edge During the period Internal model The projected traffic volume generated Indicates whether the corresponding path passes through an edge. The value can be 0 or 1; if multi-path routing is used, the allocation ratio can also be between 0 and 1.

[0050] Considering the varying degrees to which different aircraft types occupy airway resources, the traffic flow of different aircraft types needs to be converted into equivalent load:

[0051]

[0052] in, Representing an edge During the period The equivalent operating load within, Indicates model Capacity occupancy factor. Small multi-rotor drones. It can be set to 1. Large, heavy-duty drones, high-speed drones, or models with greater safety distance requirements can be set to a value greater than 1.

[0053] When generating candidate passing edges, the edge cost can be calculated using the following formulas:

[0054]

[0055] in, This is a weighting coefficient that can be dynamically adjusted based on the task type.

[0056] Step 4: Identify bottleneck units and high-load units.

[0057] like Figure 3 As shown, based on the capacity evaluation results, the system compares the load parameters of the candidate access edges with the operating load constraints, and identifies bottleneck units and high-load units that exceed the constraint range.

[0058] First, based on operational load constraints, the system sets the maximum load-bearing capacity for each edge, node, or inter-layer transition edge. Capacity utilization rate is expressed as:

[0059]

[0060] when Greater than the preset capacity utilization threshold When this happens, the edge is marked as a high-load edge.

[0061] To avoid using only a single traffic metric to identify bottlenecks, this embodiment uses a comprehensive bottleneck scoring method:

[0062]

[0063] in, Representing an edge During the period Bottleneck score; For capacity utilization; To predict the frequency or density of conflicts; To reduce the failure rate of conflict resolution; This represents the average delay or waiting time. The pressure is due to the transition between floors; This refers to the number of alternative paths or the redundancy of alternative paths. to These are the weighting coefficients.

[0064] like Exceeding the capacity utilization threshold, or If the edge exceeds the bottleneck scoring threshold, it is identified as a bottleneck unit or a high-load unit. The same scoring method can be used for nodes, height layers, or inter-layer transition edges.

[0065] The conflict resolution failure rate is defined as the ratio between the number of conflict resolution failures and the scale of traffic demand during capacity assessment or simulation.

[0066] Step 5: Perform a topology update to generate a hierarchical route topology.

[0067] Based on load balancing and bottleneck mitigation rules, the system performs add, delete, merge, split, or inter-layer transfer processing on candidate access edges corresponding to identified bottleneck and high-load units.

[0068] For candidate access edges marked as bottleneck edges, the system prioritizes searching for alternative edges in adjacent height layers that have acceptable risk and sufficient capacity margin:

[0069] If an alternative edge exists, an inter-layer transfer relationship is established and task allocation weights are adjusted, transferring some tasks to the alternative edge. Specifically, traffic redistribution can be achieved by increasing the passage weight of low-load layers, guiding some tasks to adjacent height layers, or limiting the task allocation ratio of bottleneck edges.

[0070] If no suitable alternative edge exists, then bypass edge generation is performed on the locally connected region, or the demand allocation ratio through the bottleneck edge is restricted. Bypass edge generation includes performing diversion connections on locally narrow connected regions, performing boundary connections on isolated airworthy regions, or performing local bypass reconstruction on high-conflict regions.

[0071] The load balancing rules specifically include: adding alternative edges for high-load channels, guiding some tasks to adjacent height layers, increasing the passage weight of low-load layers, or limiting the task allocation ratio of bottleneck edges.

[0072] The bottleneck mitigation rules specifically include: implementing diversion connections for locally narrow connected areas, implementing boundary connections for isolated flight-ready areas, or implementing local detour reconfiguration for high-conflict areas.

[0073] Step 6: Verification and Output.

[0074] The generated hierarchical route topology undergoes reachability verification, capacity verification, and risk verification before output. Verification conditions include:

[0075] Reachability check: Check if there is a path between all origin-endpoint pairs that satisfies the runtime load constraint, i.e., Reach(o,d) = 1.

[0076] Capacity check: Check if the utilization rate of each edge meets the requirements. ,in The upper limit of capacity utilization defined in the running load constraints.

[0077] Risk verification: Check whether the total risk of each path meets the requirements. .

[0078] If the verification fails, the system returns to adjust the candidate travel edges and re-executes steps 4 and 5 until all verification conditions are met or the iteration limit is reached. Upon successful verification, the hierarchical route topology is output as a topology file for use by the scheduling platform.

[0079] Example 2

[0080] This embodiment provides a low-altitude route hierarchical topology construction system for large-scale flight, which is used to execute the above-described method. The system includes:

[0081] Flightable Space Access Module: Used to obtain the flightable space of the target area.

[0082] Layered navigation map building module: Used to convert flight space into a layered navigation map that includes altitude layer attributes.

[0083] Demand Mapping Module: Used to generate candidate access edges in the hierarchical navigation graph based on the task demand matrix.

[0084] Bottleneck identification module: Based on the capacity evaluation results, it compares the load parameters of candidate access edges with the operating load constraints to identify bottleneck units and high-load units that exceed the constraint range.

[0085] Topology update module: Based on load balancing rules and bottleneck mitigation rules, it performs add, delete, merge, split or inter-layer transfer processing on candidate access edges corresponding to identified bottleneck units and high-load units to generate a hierarchical route topology.

[0086] The above system can be deployed in city-level low-altitude operation management platforms, park low-altitude operation platforms, edge computing nodes, or regulatory assessment platforms. Each module can be implemented in the form of microservices, containerized services, or embedded services.

[0087] This embodiment provides an electronic device, including a memory, a processor, and program instructions stored in the memory and executable by the processor. When the processor executes the program instructions, it implements the steps described in the above method embodiments. This electronic device can be a server, workstation, cloud computing node, edge computing box, drone dispatch and control server, or low-altitude operation monitoring terminal.

[0088] This embodiment also provides a non-transitory computer-readable storage medium storing computer instructions thereon, which, when executed by a processor, implement the various steps in the above method embodiments.

[0089] The above embodiments are only used to illustrate the technical solutions of the present invention and do not constitute a limitation on the scope of protection. Those skilled in the art can adjust the parameter range, data source type, calculation formula form, deployment environment, and module combination method without departing from the concept of the present invention. Any solution that uses the same or equivalent technical means to achieve the same technical effect should fall within the protection scope of the present invention.

[0090] 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 therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing a hierarchical topology for low-altitude routes for large-scale flight, characterized in that, include: Obtain the airworthiness space, mission requirement matrix, capacity evaluation results, and operational load constraints of the target area; The airworthiness space is converted into a hierarchical navigation map that includes altitude layer attributes; Candidate access edges are generated in the hierarchical navigation graph based on the task requirement matrix. Based on the capacity evaluation results, the load parameters of the candidate access edges are compared with the operating load constraints to identify bottleneck units and high-load units that exceed the constraint range. Based on load balancing and bottleneck mitigation rules, for the candidate access edges corresponding to the identified bottleneck units and high-load units, add, delete, merge, split, or transfer between layers are performed to generate a hierarchical route topology.

2. The method for constructing a hierarchical topology for low-altitude routes for large-scale flight as described in claim 1, characterized in that, The hierarchical navigation map consists of flight-ready grid nodes, adjacent passage relationships, inter-layer transition relationships, and edge attributes; the edge attributes include length, risk cost, capacity margin, historical conflict frequency, and estimated passage time.

3. The method for constructing a hierarchical topology for low-altitude routes oriented towards large-scale flight, as described in claim 1, is characterized in that... The task demand matrix is ​​generated based on origin-destination pairs, task type, time period demand intensity, and aircraft type, and is used to represent the expected traffic flow between different spatial units.

4. The method for constructing a hierarchical topology for low-altitude routes for large-scale flight as described in claim 1, characterized in that, The bottleneck unit is identified by at least one of the following indicators: edge betweenness number, traffic flow, conflict frequency, resolution failure rate, or number of alternative paths; wherein, the resolution failure rate is the ratio of the number of conflict resolution failures to the traffic demand during capacity assessment or simulation.

5. The method for constructing a hierarchical topology for low-altitude routes for large-scale flight as described in claim 1, characterized in that, The load balancing rules include: adding alternative edges for high-load channels, guiding some tasks to adjacent height layers, increasing the passage weight of low-load layers, or limiting the task allocation ratio of bottleneck edges.

6. The method for constructing a hierarchical topology for low-altitude routes for large-scale flight as described in claim 1, characterized in that, The bottleneck mitigation rules include: performing diversion connections for locally narrow connected areas, performing boundary connections for isolated flight-ready areas, or performing local detour reconfiguration for high-conflict areas.

7. The method for constructing a hierarchical topology for low-altitude routes for large-scale flight as described in claim 1, characterized in that, The hierarchical route topology undergoes reachability verification, capacity verification, and risk verification before output. If the verification fails, the candidate travel edges are returned for adjustment.

8. A low-altitude route hierarchical topology construction system for large-scale flight, characterized in that, include: The airspace access module is used to obtain the airspace in the target area; A layered navigation map construction module is used to convert the flight space into a layered navigation map containing altitude layer attributes; The requirement mapping module is used to generate candidate access edges in the hierarchical navigation graph based on the task requirement matrix. The bottleneck identification module is used to compare the load parameters of candidate access edges with the operating load constraints based on the capacity evaluation results, and identify bottleneck units and high-load units that exceed the constraint range. The topology update module is used to perform add, delete, merge, split or inter-layer transfer processing on candidate access edges corresponding to identified bottleneck units and high-load units according to load balancing rules and bottleneck mitigation rules, and generate a hierarchical route topology.

9. An electronic device, characterized in that, It includes a memory, a processor, and program instructions stored in the memory and executable by the processor, wherein the processor, when executing the program instructions, implements the method for constructing a low-altitude route hierarchical topology for large-scale flight as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that, The system stores computer instructions that, when executed by a processor, implement the low-altitude route hierarchical topology construction method for large-scale flight as described in any one of claims 1 to 7.

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