A city low-altitude air route network planning method combining demand attraction and danger prevention

Abstract

The application discloses a kind of urban low-altitude air route network planning methods combining demand attraction and danger prevention, comprising the following steps: (1) based on demand, land, etc. Data determine urban low-altitude airport site selection, draw and simplify complete graph, form the air route network based on demand attraction, i.e. demand air route network;(2) based on obstacle data extraction low-altitude danger point, draw Voronoi diagram, form the air route network based on danger prevention, i.e. safe air route network;(3) double network fusion is carried out to demand air route network and safe air route network, replace the initial planned flight leg in demand air route network with conflict with danger point with optimized actual flight air route in safe air route network, and then generate fusion air route network.The application can meet economy from demand attraction angle, and guarantee safety from danger prevention angle only by using flight plan order data, calculation is simple and fast, analysis effect is good, and provides effective decision support for urban low-altitude air route network planning.

Description

Technical Field

[0001] This invention relates to urban air traffic network planning, specifically to a method for planning urban low-altitude airway networks that combines demand attraction and hazard prevention. Background Technology

[0002] With the rapid development of vertical takeoff and landing (VTOL) aircraft, urban air traffic, as a new mode of transportation, has gradually attracted attention, thus promoting the vigorous development of new concepts and technologies related to urban air traffic. In particular, unmanned aerial vehicle (UAV) logistics within urban air traffic has a vast market and enormous potential, serving as an effective way to alleviate the pressure on ground logistics transportation. The low production and operating costs, high mobility and operability of UAVs, and the fact that they do not require human escort all contribute to their enormous development potential in many fields. However, the operating environment of UAV systems in low-altitude airspace is extremely complex. Therefore, with the gradual increase in the number of UAVs, the gradual opening of low-altitude airspace, and the rapid growth of the internet economy, the rapid development of UAV systems has brought new opportunities and challenges to future low-altitude airspace development. Currently, my country's low-altitude airspace is not yet fully open, and core issues such as urban low-altitude air route network planning and UAV operation modes are still in the exploratory stage.

[0003] Existing airway network planning methods, based on simple topology structures or simply adding routes one by one, are ill-suited for large-scale network planning. In particular, urban low-altitude airway network planning results are difficult to apply practically, failing to comprehensively analyze urban logistics needs and building obstacles from both economic and safety perspectives. In the future, low-altitude airspace may face a large demand for logistics drones. To avoid conflicts between drones, it is essential to plan drone operating routes in low-altitude airspace, thereby ensuring the safe, orderly, and efficient operation of low-altitude air traffic. Therefore, research on bottlenecks in low-altitude traffic operation is crucial. Summary of the Invention

[0004] Purpose of the invention: To address the shortcomings of existing technologies, this invention proposes a method for planning urban low-altitude airway networks that combines demand attraction and hazard prevention. In urban low-altitude airway planning, it satisfies both economic efficiency from the perspective of demand attraction and safety from the perspective of hazard prevention, and comprehensively analyzes the logistics needs and building obstacles of the city from both economic and safety perspectives.

[0005] Technical solution: A method for planning urban low-altitude airway networks that combines demand attraction and hazard prevention, comprising the following steps:

[0006] (1) Determine the location of urban low-altitude airports based on demand, land use and other data, draw and simplify the complete map, and form a demand-attracted airway network, i.e., the demand airway network.

[0007] (2) Extract low-altitude hazard points based on obstacle data, draw the Voronoi diagram, and form a route network based on hazard prevention, namely a safe route network;

[0008] (3) The demand route network and the safety route network are merged. The initial planned flight segments in the demand route network that conflict with the danger points are replaced with the optimized actual flight routes in the safety route network, thereby generating a merged route network.

[0009] Furthermore, in step (1), land use and actual order demand factors are fully considered, and these factors are comprehensively analyzed to determine the site selection for urban low-altitude airports and clarify the spatial distribution of airports. All determined airport points are then connected in pairs to create a complete map. The complete map is composed of all airport nodes and flight segments, and is represented as follows:

[0010] G = (N, S)

[0011] S={s|s ij :o i d j ,o i ,d j ∈N}

[0012] Where N = {O, D} consists of the set O of all departure airports (logistics delivery nodes) and the set D of arrival airports (user demand nodes) in the network, and S represents all flight segments in the network. ij To connect the departure airport i and arrival at the airport j The directed initial planned flight segment.

[0013] Because the complete graph becomes too complex after connecting all airports in pairs, the generated complete graph is simplified by reducing S in the complete graph. all{O,D} Simplify to S' to simplify the complete graph. (The last part, "S", appears to be a typo and can be omitted.) all{O,D} Consider it as a set to be deleted, S0, where the number of all segment elements in S0 is n(n-1), and n is the total number of airports in the region.

[0014] Sort all segment elements within S0 by length:

[0015] S0={s1,s2,...,s n(n-1)},(s i ≤s i+1 )

[0016] For the longest segment s within S0 q Find the origin and destination points that are the same as the straight segment and whose total length is less than or equal to e·s. qIf a broken line segment can be found, it is used to replace the longest straight line segment, that is, the longest straight line segment is deleted from the set to be deleted S0, where the non-straight line coefficient e ranges from [1,5]. If no corresponding broken line segment is found, the longest straight line segment is moved from the set to be deleted S0 to the simplified segment set S'. The first two steps are repeated until the number of segment elements in S' is equal to k·n, where the network simplification coefficient k ranges from [1,n-1].

[0017] Using the above method, while ensuring connectivity between any two airports, the remaining redundant flight segments are simplified to form a demand-attractive route network, i.e., a demand-based route network, which can be represented as:

[0018] G'=(N,S')

[0019] Furthermore, in step (2), the height and location information of all obstacles such as buildings, mountains, and power facilities within the coverage area of ​​the low-altitude airway network that may affect the operation of aircraft in urban low-altitude areas are statistically analyzed to form low-altitude hazard points. The location of the center of each low-altitude hazard point is regarded as a discrete point p. w Where w is the obstacle number. For building obstacles, the center point of any building or the center point of a cluster of nearby buildings is considered a discrete point. The obstacle avoidance distance for a single obstacle is:

[0020] R max =a max +c

[0021] For clusters of similar obstacles, the obstacle avoidance distance is:

[0022] R max =b max +c

[0023] Where R max a is the maximum obstacle avoidance distance. max b is the length of any single obstacle from its center point. max Let c be the distance from the center of the obstacle group to the farthest point, and let c be the minimum safe distance for the UAV, where 5m ≤ c ≤ 50m.

[0024] Using a spatial segmentation algorithm, the Delaunay triangulation algorithm is employed to generate flight segment connectivity. Let P = p1, p2, ..., p be a set of discrete points in space that are not co-located. n any point p n Let T be a convex polygon i The center of the convex polygon, any point within the polygon, and other points p. j The distances (j≠i) are all greater than the distances to p inside the convex polygon. j The distance, the Voronoi polygon is:

[0025]

[0026] L={l|l ij :p i p j ,p i ,p j ∈P}

[0027] Where d (t,p) Let L be the distance between point t and subset p, and let L be the set of all optimized actual flight paths. ij For p i and p j The route formed by the perpendicular bisector.

[0028] Voronoi diagram, i.e., primitive cell T i The tuples (i∈w) connect the cell points to form several triangles. The pericenters are found using the perpendicular bisector. The line segment connecting all the pericenters is the optimized actual flight path, and finally a route network based on hazard prevention, namely the safe route network, is formed.

[0029] Furthermore, in step (3), for all initially planned flight segments connecting each pair of airports in the demand route network, all segments that conflict with low-altitude hazard points are identified and extracted. The expression for the flight altitude constraint is:

[0030] H max ≤z u

[0031] Among them, z u H represents the altitude of the u-th waypoint node on the flight segment; max Indicates the maximum height of the obstacle.

[0032] The expression for the safety separation constraint between the flight segment and the low-altitude danger point is:

[0033]

[0034] Among them, R max x represents the maximum obstacle avoidance distance for any single obstacle. u ,y u ,z u Let x and x represent the coordinates of the u-th waypoint node on the initial planned flight segment. v ,y v ,z v These represent the coordinates of the v-th low-altitude hazard point in the airway network.

[0035] For the initial planned segments in the aforementioned demand route network that do not meet the constraints, find and extract the Voronoi polygon edge segments in the safe route network that coincide with the origin and destination of these segments.

[0036] Using the safe route network, the overlapping Voronoi polygon edge segments are extracted and considered as optimized actual flight routes, replacing the initial planned flight segments that overlap with them and conflict with low-altitude hazard points. mn Replace the corresponding s ij l mn The corresponding start and end points are o m and o n s ij The corresponding start and end points are o i and o j And o m o n with o i o j The following constraints must be met:

[0037]

[0038]

[0039] Where, d o-o' This represents the distance between two points, o and o', i.e., o m It should be the distance o in the safe airway network node. i The nearest point, o n It should be the distance o in the safe airway network node. j The nearest point.

[0040] In addition, o m with o i Optimized actual flight routes that can avoid low-altitude danger points should be added between them. o n with o j Optimized flight paths that can avoid low-altitude danger zones should also be added between them. After all air routes are replaced, the two networks are merged to generate a unified air route network.

[0041] Beneficial Effects: This invention addresses both the economic benefits of urban low-altitude airway planning from a demand attraction perspective and the safety concerns of hazard prevention. By comprehensively analyzing urban logistics needs and building obstacles from both economic and safety standpoints, it solves large-scale network planning problems. In particular, the practical application of urban low-altitude airway network planning results ensures the safe, orderly, and efficient operation of low-altitude air traffic and helps alleviate operational bottlenecks in low-altitude transportation. Attached Figure Description

[0042] Figure 1 A flowchart illustrating a method for planning urban low-altitude airway networks that combines demand attraction and hazard prevention, according to the present invention.

[0043] Figure 2This refers to a demand-driven route network, also known as a demand route network.

[0044] Figure 3 This refers to a route network based on hazard prevention, also known as a safe route network.

[0045] Figure 4 To integrate the air route network. Detailed Implementation

[0046] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0047] Figure 1 A flowchart illustrating a method for planning urban low-altitude airway networks that combines demand attraction and hazard prevention, according to the present invention, mainly includes the following steps:

[0048] Step (1): Determine the location of urban low-altitude airports based on demand, land use and other data, draw and simplify the complete map, and form a demand-attracted airway network, i.e., the demand airway network.

[0049] Taking into full account land use and actual order demand, and comprehensively analyzing these factors, the site selection for urban low-altitude airports was determined, and the spatial distribution of airports was clarified. All determined airport points were then connected pairwise to create a complete map. This complete map, composed of all airport nodes and flight segments, is represented as follows:

[0050] G = (N, S)

[0051] S={s|s ij :o i d j ,o i ,d j ∈N}

[0052] Where N = {O, D} consists of the set O of all departure airports (logistics delivery nodes) and the set D of arrival airports (user demand nodes) in the network, and S represents all flight segments in the network. ij To connect the departure airport i and arrival at the airport j The directed initial planned flight segment.

[0053] Because the complete graph becomes too complex after connecting all airports in pairs, the generated complete graph is simplified by reducing S in the complete graph. all{O,D} Simplify to S' to simplify the complete graph. (The last part, "S", appears to be a typo and can be omitted.) all{O,D} Consider it as a set to be deleted, S0, where the number of all segment elements in S0 is n(n-1), and n is the total number of airports in the region.

[0054] Sort all segment elements within S0 by length:

[0055] S0={s1,s2,...,s n(n-1)},(s i ≤s i+1 )

[0056] For the longest segment s within S0 q Find the origin and destination points that are the same as the straight segment and whose total length is less than or equal to e·s. q If a broken line segment can be found, it is used to replace the longest straight line segment, that is, the longest straight line segment is deleted from the set to be deleted S0, where the non-straight line coefficient e ranges from [1,5]. If no corresponding broken line segment is found, the longest straight line segment is moved from the set to be deleted S0 to the simplified segment set S'. The first two steps are repeated until the number of segment elements in S' is equal to k·n, where the network simplification coefficient k ranges from [1,n-1].

[0057] Using the above method, while ensuring connectivity between any two airports, the remaining redundant flight segments are simplified to form a demand-attractive route network, i.e., a demand-based route network, which can be represented as:

[0058] G'=(N,S')

[0059] Step (2) Extract low-altitude hazard points based on obstacle data, draw the Voronoi diagram, and form a hazard prevention-based airway network, namely a safe airway network.

[0060] The height and location information of all obstacles such as buildings, mountains, and power facilities within the coverage area of ​​the low-altitude airway network that may affect aircraft operations in urban low-altitude airspace are used to form low-altitude hazard points. The center location of each low-altitude hazard point is considered as a discrete point p. w Where n is the obstacle number. For building obstacles, the center point of any building or the center points of a cluster of nearby buildings are considered discrete points. The obstacle avoidance distance for a single obstacle is:

[0061] R max =a max +c

[0062] For clusters of similar obstacles, the obstacle avoidance distance is:

[0063] R max =b max +c

[0064] Where R max a is the maximum obstacle avoidance distance. max b is the length of any single obstacle from its center point. max Let c be the distance from the center of the obstacle group to the farthest point, and let c be the minimum safe distance for the UAV, where 5m ≤ c ≤ 50m.

[0065] Using a spatial segmentation algorithm, the Delaunay triangulation algorithm is employed to generate flight segment connectivity. Let P = p1, p2, ..., p be a set of discrete points in space that are not co-located. w any point p w Let T be a convex polygon i The center of the convex polygon, any point within the polygon, and other points p. j The distances (j≠i) are all greater than the distances to p inside the convex polygon. j The distance, the Voronoi polygon is:

[0066]

[0067] L={l|l ij :p i p j ,p i ,p j ∈P}

[0068] Where d (t,p) Let L be the distance between point t and subset p, and let L be the set of all optimized actual flight paths. ij For p i and p j The route formed by the perpendicular bisector.

[0069] Voronoi diagram, i.e., primitive cell T i The tuples (i∈w) connect the cell points to form several triangles. The pericenters are found using the perpendicular bisector. The line segment connecting all the pericenters is the optimized actual flight path, and finally a route network based on hazard prevention, namely the safe route network, is formed.

[0070] Step (3) involves merging the demand route network and the safety route network, replacing the initial planned flight segments in the demand route network that conflict with the hazard points with the optimized actual flight routes in the safety route network, thereby generating the merged route network.

[0071] For all initially planned flight segments connecting each pair of airports in the demand route network, identify and extract all segments that conflict with low-altitude hazard points. The expression for flight altitude constraints is:

[0072] H max ≤z u

[0073] Among them, z u H represents the altitude of the u-th waypoint node on the flight segment; max Indicates the maximum height of the obstacle.

[0074] The expression for the safety separation constraint between the flight segment and the low-altitude danger point is:

[0075]

[0076] Among them, R max x represents the maximum obstacle avoidance distance for any single obstacle. u ,y u ,z u Let x and x represent the coordinates of the u-th waypoint node on the initial planned flight segment. v ,y v ,z v These represent the coordinates of the v-th low-altitude hazard point in the airway network.

[0077] For the initial planned segments in the aforementioned demand route network that do not meet the constraints, find and extract the Voronoi polygon edge segments in the safe route network that coincide with the origin and destination of these segments.

[0078] Using the safe route network, the overlapping Voronoi polygon edge segments are extracted and considered as optimized actual flight routes, replacing the initial planned flight segments that overlap with them and conflict with low-altitude hazard points. mn Replace the corresponding s ij l mn The corresponding start and end points are o m and o n s ij The corresponding start and end points are o i and o j And o m o n with o i o j The following constraints must be met:

[0079]

[0080]

[0081] Where, d o-o' This represents the distance between two points, o and o', i.e., o m It should be the distance o in the safe airway network node. i The nearest point, o n It should be the distance o in the safe airway network node. j The nearest point.

[0082] In addition, o m with o i Optimized actual flight routes that can avoid low-altitude danger points should be added between them. o n with o j Optimized flight paths that can avoid low-altitude danger zones should also be added between them. After all air routes are replaced, the two networks are merged to generate a unified air route network.

[0083] The technical solution of the present invention will be further illustrated below with specific embodiments.

[0084] The research period T is one day (i.e., 24 hours), and the number of orders is 20 (corresponding to 20 start and end points). Taking Nanjing University of Aeronautics and Astronautics' Jiangjunlu Campus as an example, four low-altitude airports were set up after statistically analyzing the main service distribution points. Buildings in the area that could affect urban low-altitude operations were statistically analyzed, and eight low-altitude hazard points were extracted. The case study focuses on drone orders, totaling 20 flights, and the obtained order data is shown in Table 1.

[0085] Table 1. Case order data for the study period up to May 4, 2023

[0086]

[0087]

[0088] 1. Based on a comprehensive analysis of factors such as land use and actual order demand, and combining these factors with a case study, the site selection for low-altitude airports in four cities within the case area was determined. The determined latitude and longitude coordinates of the selected low-altitude airport sites are N1: 118.8001°, 32.0002°; N2: 118.8101°, 32.0102°; N3: 118.8011°, 32.0011°; N4: 118.8111°, 32.0111°. All airport points are connected pairwise to draw a complete graph, G = (N, S). Since the complete graph becomes too complex after connecting all airports pairwise, the following is obtained:

[0089] S0={s 24 ,s 31 ,s 43 ,s 12 ,s 23 ,s 14}

[0090] In this specific embodiment, e = 2 and k = 1. For the longest straight segment s within S0... 14 Find the origin and destination phases that are the same as the straight segment and whose total length is less than or equal to 2 seconds. 14 The broken line segment can be formed by the broken line segment s. 12 s 24 Replace this longest straight segment, that is, delete s from the set S0 to be deleted. 14 Repeat this step until the number of elements in the inner segment of S' is k·n = 4, then S' = {s 12 ,s 24 ,s 43 ,s 31}

[0091] While ensuring connectivity between any two airports, the remaining redundant flight segments are simplified to obtain a demand-attractive route network, namely the demand route network G' = (N, S'), where N = {N1, N2, N3, N4} and S' = {s 12 ,s 24 ,s 43 ,s 31},like Figure 2 As shown.

[0092] 2. After collecting the height and location information of all buildings within the low-altitude airway network coverage area that may affect aircraft operations in urban low-altitude airspace, eight low-altitude hazard points P are established based on the building height data, where P = p1, p2, ..., p8. A perpendicular bisector is drawn for each pair of hazard points, and this perpendicular bisector is used as the side length of a polygon to draw a Voronoi polygon, thus forming a Voronoi diagram. The Voronoi diagram is then simplified to form a hazard-based airway network, i.e., a safe airway network, such as... Figure 3 As shown.

[0093] 3. For all initially planned flight segments connecting each pair of airports in the demand route network, identify and extract all segments that conflict with low-altitude hazard points. For the initially planned flight segments that conflict with low-altitude hazard points extracted from the demand route network, identify and extract the routes in the safe route network that coincide with the origin and destination of these segments; these are represented by s. 12 s 43 The overlapping flight segments are extracted using the safe route network, and the initially planned flight segments that overlap with these segments and conflict with low-altitude hazard points are replaced. The replacement process is as follows:

[0094] Where s 12 The departure airport is N1, and the arrival airport is N2; for N1 and N2 respectively:

[0095]

[0096]

[0097] The nearest safe route network node to N1 is o1, and the nearest safe route network node to N2 is o4. Therefore, the broken line segment l is used. 14 l 24 l 26 For straight flight segment s 12 The replacement is performed, and the start and end points of the broken line segment are adjusted to avoid low-altitude danger points, forming routes from o1 to N1 and from o4 to N2, thereby generating the optimized actual flight route s′ between N1 and N2. 12 :

[0098] S' 12 ={l 14,l 24 ,s 12}

[0099] s 43 The departure airport is N4, and the arrival airport is N3; for N4 and N3 respectively:

[0100]

[0101]

[0102] The nearest safe route network node to N4 is o6, and the nearest safe route network node to N3 is o5. Therefore, a broken line segment l is used. 78 l 26 l 46 For straight flight segment s 43 The replacement was performed, and the start and end points of the broken line segment were adjusted to avoid low-altitude danger points, forming routes from o6 to N4 and from o5 to N3, thereby generating the optimized actual flight route s′ between N4 and N3. 43 :

[0103] s' 43 ={l 46 ,l 26 ,l 78 ,s 43}

[0104] Ultimately, after the dual-network integration, a fused route network for low-altitude route planning is obtained, such as... Figure 4 As shown.

[0105] The above description is merely a further detailed explanation of the present invention through a specific embodiment and should not be construed as limiting the invention to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the inventive concept, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A method for planning urban low-altitude airway networks that combines demand attraction and hazard prevention, characterized in that, The method includes the following steps: (1) Determine the location of urban low-altitude airports based on demand and land use data, draw and simplify the complete map, and form a demand-attractive airway network, i.e., the demand airway network: (2) Extract low-altitude hazard points based on obstacle data, draw a Voronoi diagram, and form a route network based on hazard prevention, namely a safe route network; (3) The demand route network and the safety route network are integrated, and the initial planned flight segments in the demand route network that conflict with the danger points are replaced with the optimized actual flight routes in the safety route network, thereby generating a fused route network; In step (3), for all initially planned flight segments connecting each pair of airports in the demand route network, find and extract all segments that conflict with low-altitude hazard points; the expression for flight altitude constraints is: in, Indicates the first segment of the flight. The elevation of each waypoint node; Indicates the maximum height of the obstacle; The expression for the safety separation constraint between the flight segment and the low-altitude danger point is: in, This represents the maximum obstacle avoidance distance for any single obstacle. These represent the first segment of the initial planned flight segment. The coordinates of each waypoint node They represent the first in the route network. Coordinates of a low-altitude hazard point; For the initial planned segments in the above-mentioned demand route network that do not meet the constraints, find and extract the Voronoi polygon edge segments in the safe route network that coincide with the origin and destination of these segments; In step (3), the overlapping Voronoi polygon edge segments extracted from the safe route network are used as the optimized actual flight routes, replacing the initial planned flight segments that overlap with them and conflict with low-altitude hazard points. Replace the corresponding ; The corresponding start and end points are respectively and , The corresponding start and end points are respectively and ,and , and , The following constraints must be met: in, express and The distance between two points, i.e. It should be the distance between nodes in the safe airway network. The nearest point, It should be the distance between nodes in the safe airway network. The nearest point; To connect the departure airport and arriving at the airport The directed initial planned flight segment; in addition, and Optimized actual flight routes that can avoid low-altitude danger points should be added between them. , and Optimized flight paths that can avoid low-altitude danger zones should also be added between them. After all routes are replaced, the two networks are integrated to generate a unified route network.

2. The urban low-altitude airway network planning method combining demand attraction and hazard prevention as described in claim 1, characterized in that, In step (1), land use and actual order demand factors are fully considered, and the above factors are comprehensively analyzed to determine the site selection of urban low-altitude airports and clarify the spatial distribution of airports; all the finally determined airport points are connected in pairs to draw a complete map; the complete map is a map composed of all airport nodes and flight segments, represented as: in, The set of all departure airports, i.e., logistics and distribution nodes in the network. and the set of user demand nodes upon arrival at the airport. composition, It represents all flight segments in the network.

3. The urban low-altitude airway network planning method combining demand attraction and hazard prevention as described in claim 2, characterized in that, The complete graph generated after connecting all airports pairwise in step (1) is too complex. Therefore, the generated complete graph is simplified by making the graph more concise. Simplified to To simplify the complete graph; Considered as a set to be deleted ,in The number of all segment elements is , where n is the total number of airports in the region; Will All segment elements within the flight are sorted by length: for Longest straight segment s q Find the origin and destination that are the same as the longest straight segment and whose total length is less than or equal to e·s. q If a broken line segment can be found, it will replace the longest straight line segment, i.e., it will be removed from the set to be deleted. Delete the longest straight segment, where the non-straightness coefficient e ranges from [1, 5]. If no corresponding broken line segment is found, remove the longest straight segment from the set to be deleted. Move to the simplified segment set Repeat the first two steps until... The number of elements in the domestic segment is equal to k· The network simplification coefficient k ranges from [1, n-1]; Using the above method, while ensuring connectivity between any two airports, the remaining redundant flight segments are simplified to form a demand-attractive route network, i.e., a demand-based route network, which can be represented as: 。 4. The urban low-altitude airway network planning method combining demand attraction and hazard prevention as described in claim 1, characterized in that, In step (2), the height and location information of all buildings, mountains, power facilities, and other obstacles within the coverage area of ​​the low-altitude airway network that may affect aircraft operations in urban low-altitude areas are collected to form low-altitude hazard points. The location of the center of each low-altitude hazard point is considered as a discrete point. ,in Obstacles are numbered; for building obstacles, the center point of any building or the center points of several nearby building clusters are considered discrete points; the obstacle avoidance distance for a single obstacle is: For clusters of similar obstacles, the obstacle avoidance distance is: in This is the maximum obstacle avoidance distance. The length of any single obstacle from its center point. The distance from the center point to the group of obstacles. To ensure the minimum safe distance for drones, there are ; Using spatial segmentation algorithms, the Delaunay triangulation algorithm is employed to generate flight segment connectivity relationships. This is based on a set of discrete points that are not co-located within the space. any point For a certain convex polygon The center of the convex polygon, any point inside the polygon, and other points. The distances are all greater than the distances to the interior of the convex polygon. The distance, the Voronoi polygon is: in For point and subsets distance, For the set of all optimized actual flight routes, for and The route formed by the perpendicular bisector.

5. The urban low-altitude airway network planning method combining demand attraction and hazard prevention as described in claim 4, characterized in that, In step (2), the Voronoi diagram is the primitive cell. The tuples connect the cell points to form several triangles. The pericenters are found using the perpendicular bisector. The line segment connecting all the pericenters is the optimized actual flight path, and finally a route network based on hazard prevention, namely the safe route network, is formed.

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