A method for detecting and quickly resolving aircraft route conflicts under a given road network structure

Abstract

The present invention discloses a method for detecting and quickly resolving aircraft route conflicts under a given road network structure. The method can be based on the given road network structure, through a consistent spatiotemporal analysis method, taking into account the constraints within the road network, and establishing a conflict detection model from several aspects such as same-direction pursuit, reverse intersection, and channel saturation, thereby achieving the qualitative detection of conflicts between multiple aircraft routes; and based on the conflict detection results, a conflict tree is constructed, and through a Monte Carlo tree search and focused branch reduction method, a feasible solution for the route conflict resolution adjustment scheme is searched, thereby achieving the generation of conflict-free route adjustments for multiple aircraft. The present invention detects the routes planned between aircraft, discovers possible collision risks in advance, and provides a fast and feasible route adjustment scheme to resolve conflict risks, thereby achieving conflict-free route planning for a large number of aerial aircraft under a given road network structure.

Description

Technical Field

[0001] The present invention relates to the technical field of air traffic control, and in particular to a method for detecting and quickly resolving aircraft route conflicts under a given road network structure. Background Art

[0002] In some air traffic control scenarios, aircraft flights must operate within fixed, prescribed routes, and air traffic controllers are responsible for maintaining aircraft separation. If flight paths need to be changed due to special circumstances such as conflicts, no-fly zones, danger zones, or extremely severe weather, the air traffic controller's instructions must be strictly followed. However, with the continued increase in air traffic volume, flight routes will become more congested, increasing the risk of aircraft conflicts, thereby reducing the operational efficiency of the air traffic system and threatening aviation safety. Currently, conflict detection in air traffic control uses the minimum safe separation method, which often relies on controllers' predictions of real-time routes. Conflict resolution also often relies on manual command mediation. These methods significantly reduce the efficiency of airspace control, especially as the number of aircraft in the route network increases, and the difficulty of detection and adjustment increases exponentially. Therefore, for pre-planned aircraft routes, it is particularly important to determine and resolve conflicts between them.

[0003] Currently, conflict detection and conflict resolution methods for route missions are difficult to decouple due to the complex, continuous, and mutually coupled characteristics of the time, space, and frequency domains. This can easily lead to a ripple effect across the entire system. When planning large quantities of routes, this chain reaction can lead to an "explosive" increase in the time required to resolve conflicts, making it impossible to form a conflict-free, large-scale aircraft planning solution within a limited timeframe. Summary of the Invention

[0004] Purpose of the invention: The purpose of the present invention is to provide a method for detecting and quickly resolving aircraft route conflicts under a given road network structure, so as to realize a route control method for the influx of a large number of aircraft in the airspace determined by the road network structure, realize rapid detection of conflicts between them and provide resolution solutions.

[0005] Technical solution: The present invention provides a method for detecting and quickly resolving aircraft route conflicts under a given route network structure, comprising the following steps:

[0006] Step 1: Define the elements of the established road network structure in the current spatial area, including channels, intersections and temporary channels;

[0007] Step 2: Build a conflict detection model based on consistent spatiotemporal analysis. Through spatiotemporal constraint modeling, quantitatively analyze the same-direction overtaking conflicts, opposite-direction intersection conflicts, and channel saturation conflicts between multiple aircraft routes.

[0008] Step 3: Build a conflict resolution experience knowledge base to store pairwise route conflict resolution solutions based on manual experience;

[0009] Step 4: Construct a conflict tree based on the conflict detection results of step 2. Combined with the conflict resolution experience knowledge base of step 3, a Monte Carlo tree search and focused branch reduction method are used to search for feasible solutions for route adjustment.

[0010] Step 5: Within a given time, select the optimal conflict-free route plan based on the total range and total flight time evaluation indicators of the conflict tree child nodes and adjust the aircraft route.

[0011] Furthermore, in step 1, a channel is defined as a straight horizontal area connecting two points at the same height, including the upper boundary height, lower boundary height, channel width, starting point longitude and latitude, end point longitude and latitude, and channel capacity attributes; an intersection is defined as a point in a channel, including the upper boundary height, lower boundary height, width, longitude, latitude, and safe passing time attributes, and each channel includes at least a starting intersection and an end intersection; a temporary channel is defined as a straight horizontal area connecting intersections at the same height between different channels, including the starting point longitude and latitude, end point longitude and latitude, height, and channel width attributes.

[0012] Furthermore, in step 2, the spatiotemporal constraint modeling is specifically as follows: Channel flow constraint model:

[0013] ;

[0014] in, The starting point of the route Arrive at a fixed intersection air traffic flow; For a fixed intersection To the end of the route Traffic volume; The starting point of the route Go directly to the end of the route Traffic volume; For intersection The maximum capacity value of the channel The maximum capacity value; is the total number of intersections; is the total number of route starting intersections; is the total number of route terminal intersections;

[0015] The safety constraint model includes: node flight interval constraint and route channel constraint;

[0016] Task condition constraint model: ;

[0017] Where, is the time of arrival at the route destination, Ask for time for tasks.

[0018] Furthermore, in step 2, the qualitative conflict analysis includes the following: same-direction overtaking conflict: two aircraft cross the same channel at the same altitude in the same direction, and the one that enters first exits last; opposite-direction crossing conflict: two aircraft cross the same channel at the same altitude in opposite directions; channel saturation conflict: the time interval between two aircraft passing the same intersection is less than the safe passage time.

[0019] Furthermore, in step 3, the conflict resolution experience knowledge base includes: same-direction pursuit conflict resolution solutions: speed adjustment, height adjustment or point adjustment for detour; reverse cross conflict resolution solutions: height adjustment, speed adjustment or point adjustment for detour; channel saturation conflict resolution solutions: speed adjustment or point adjustment for detour.

[0020] Furthermore, in step 4, the conflict tree node includes: conflict number, conflict cause, conflict aircraft number, and conflict channel number; the expansion process of the conflict tree is expressed as:

[0021] ;

[0022] in, Representative is located at layer Node No., which contains the aircraft Conflict between ; The representative randomly extracts a solution from the conflict resolution solution library in a Monte Carlo manner and obtains the layer Node .

[0023] Furthermore, the focused branch reduction method is as follows: Calculate the leaf node evaluation value:

[0024] ;

[0025] in, Represents the relevance of the conflict within the leaf node to all routes, Represents the impact of conflicts within leaf nodes on key tasks, Represents the airspace resources affected by the conflict within the leaf node; calculates the Q value for each leaf node and retains the node with the largest Q value in the current layer, and prunes the remaining nodes in the same layer.

[0026] Furthermore, step 5 is as follows: search for a conflict-free leaf node set T within time t; calculate the total range and total flight time evaluation values ​​of each solution , select the minimum value Corresponding solutions As the final adjustment plan.

[0027] An electronic device according to the present invention includes a processor and a memory, wherein the memory stores a computer program, and the processor implements any one of the methods when executing the computer program.

[0028] The computer-readable storage medium of the present invention stores a computer program, and when the computer program is executed by a processor, any one of the methods is implemented.

[0029] Beneficial effects: Compared with the existing technology, the present invention has the following significant advantages: (1) for a given road network structure, the element definition and the attributes contained in the element under the road network structure are clarified, laying the foundation for the subsequent solution of route conflict detection and conflict resolution problems; (2) a qualitative and quantitative detection method for the conflict relationship between routes based on consistent spatiotemporal modeling is proposed, which realizes the reasonable modeling of the spatiotemporal resources occupied by aircraft routes and quickly and efficiently analyzes the conflicts existing between all routes; (3) a conflict tree structure is constructed to describe the current route method conflict, and based on the Monte Carlo tree search method, the subtree of the lower layer conflict resolution is explored, and finally the leaf node without conflict between routes is obtained, which transforms the route conflict resolution problem into the problem of finding the optimal conflict tree subnode; (4) through the heuristic-based key conflict focusing method, the core conflict is quickly located to trim the conflict tree nodes, reduce the subsequent search scale while ensuring the optimality of the subsequent search results as much as possible. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flow chart of the consistent space-time flight conflict model algorithm of the present invention;

[0031] Figure 2 is a diagram of a multi-directional conflict detection implementation method of the present invention;

[0032] Figure 3 This is an example diagram of the same-direction pursuit relationship of the present invention;

[0033] Figure 4 1 is an example diagram of the reverse intersection relationship of the present invention; wherein, (A) represents that aircraft 1, while descending, has a reverse intersection conflict with aircraft 2, which is flying level; (B) represents that aircraft 1, while ascending, has a reverse intersection conflict with aircraft 2, which is flying level; (C) represents that aircraft 1 and aircraft 2, while flying level at the same altitude, have a reverse intersection conflict; (D) represents that aircraft 1, while ascending, has a reverse intersection conflict with aircraft 2, which is descending; (E) represents that aircraft 1, while ascending, has a reverse intersection conflict with aircraft 2, which is ascending; (F) represents that aircraft 1, while descending, has a reverse intersection conflict with aircraft 2, which is descending;

[0034] Figure 5 It is a schematic diagram of conflict tree construction based on the conflict resolution solution library of the present invention;

[0035] Figure 6 It is a conflict tree search flow chart of the present invention. DETAILED DESCRIPTION

[0036] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0037] like Figure 1 As shown, an embodiment of the present invention provides a method for detecting and quickly resolving aircraft route conflicts under a given road network structure, and the specific steps are as follows:

[0038] S1, determine the definitions of various elements in the established road network structure within the current space that can be used for the safe passage of aircraft. The elements in the road network include channels, intersections, temporary channels, etc.

[0039] (11) Elements in the road network include channels, intersections, temporary channels, etc. The specific definition of a channel is a straight horizontal area connecting two points at the same height in space, which includes attributes such as upper boundary height, lower boundary height, channel width, starting point longitude and latitude, end point longitude and latitude, and channel capacity;

[0040] (12) The specific definition of an intersection is a point in a channel, including attributes such as upper bound height, lower bound height, width, longitude, latitude, and safe passing time. A channel includes at least two intersections, namely the starting intersection and the ending intersection;

[0041] (13) The specific definition of a temporary channel is a straight horizontal area between different channels that connects intersections at the same height. Its height is consistent with the intersection height and includes the latitude and longitude of the starting point, the longitude and longitude of the end point, the height, the channel width and other attributes.

[0042] S2, determine the type of airspace conflict under the current established road network structure, design a conflict detection model based on consistent spatiotemporal analysis, and through modeling the spatiotemporal constraints of the established road network structure, achieve rapid qualitative and quantitative analysis of conflicts such as same-direction overtaking and reverse intersection between the routes planned by multiple aircraft.

[0043] The algorithm flow of the consistent space-time flight conflict model is as follows Figure 1 First, the established road network structure is modeled as a directed graph Secondly, a spatiotemporal constraint model is established under the given road network structure, which includes channel flow constraints, two types of safety constraints, and mission condition constraints. The specific definitions are as follows:

[0044] Channel flow constraint model:

[0045] ;

[0046] Where, The starting point of the route Arrive at a fixed intersection air traffic flow; For a fixed intersection To the end of the route Traffic volume; The starting point of the route Go directly to the end of the route Traffic volume; For intersection The maximum capacity value; For channel The maximum capacity value; is the total number of intersections; is the total number of route starting intersections; is the total number of route terminal intersections.

[0047] Two types of security constraint models:

[0048] Category 1: Node flight interval constraints:

[0049] ;

[0050] Where, For the intersection aircraft and the The arrival time difference of the aircraft, Provide safe crossing time intervals at intersections;

[0051] Category 2: Route channel constraints:

[0052] ;

[0053] Where, For the The flow rate of the airway channel, For the The maximum capacity of each airway channel;

[0054] Task condition constraint model:

[0055] ;

[0056] Where, is the time of arrival at the route destination, Ask for time for tasks.

[0057] Finally, multi-directional conflict detection and classification of intersection conflicts and waterway conflicts are realized. The specific implementation method is as follows: Figure 2 shown.

[0058] Before conflict detection, all aircraft conflict scenarios are divided into the following 13 categories based on the heading relationship between aircraft routes and the motion status of aircraft on the routes, as shown in Table 1.

[0059] Table 1 Classification of two-aircraft conflict scenarios

[0060] ;

[0061] Flight aircraft conflict detection and resolution first determines the state relationship and position relationship of the aircraft, establishes a decision tree for conflict type judgment, and after determining the corresponding conflict type, selects the corresponding conflict resolution method from the established resolution rule library to resolve it.

[0062] (a) Overtaking in the same direction

[0063] Same-direction pursuit conflicts are a common type of aircraft conflict, often occurring during the en-route flight phase, or cruising phase. Same-track conflicts can be resolved by converting them into pursuit issues. These conflicts typically occur when the longitudinal separation between aircraft decreases due to the following aircraft's speed exceeding the leading aircraft's.

[0064] Taking the collision of two aircraft in the same direction while climbing as an example, the collision detection process can be described as first determining that the two aircraft are in the same direction based on the heading relationship of the two aircraft, and then taking the horizontal distance between the two aircraft after 5 minutes. and height difference ,Will and Compare with the conflict standard value, if and Are all less than the conflict standard value, indicating that a conflict has been detected. The relationship between the two aircraft with the same track conflict is as follows: Figure 3 shown.

[0065] (b) Reverse crossover

[0066] Like same-direction pursuit conflicts, reverse crossing conflicts often occur during the route cruise phase and are also prone to occur during the aircraft approach and departure phases. The conflict detection of reverse crossing can be summarized as an encounter problem.

[0067] Taking the conflict between two aircraft in opposite directions during climbing as an example, the conflict detection process can be described as first determining that the two aircraft are in opposite directions based on the heading relationship between the two aircraft, and then taking the horizontal distance between the two aircraft after 5 minutes. and height difference ,Will and Compare with the conflict standard value, if and Are all less than the conflict standard value, indicating that a conflict has been detected. The relationship between the two machines in the reverse cross conflict is as follows: Figure 4As shown; among them, (A) represents that aircraft 1 has a reverse crossing conflict with aircraft 2 in level flight when it is descending; (B) represents that aircraft 1 has a reverse crossing conflict with aircraft 2 in level flight when it is ascending; (C) represents that aircraft 1 and aircraft 2 have a conflict in reverse level flight at the same altitude; (D) represents that aircraft 1 has a reverse crossing conflict with aircraft 2 in descending when it is ascending; (E) represents that aircraft 1 has a reverse crossing conflict with aircraft 2 in ascending; (F) represents that aircraft 1 has a reverse crossing conflict with aircraft 2 in descending when it is descending.

[0068] (c) Congested intersection conflicts

[0069] For intersections If the aircraft passing and aircraft If the time interval is less than 5 minutes, it is considered that there is a congestion conflict at the intersection, that is: .

[0070] S3, based on manual experience, set up a conflict resolution plan between two routes and obtain a conflict resolution experience knowledge base.

[0071] For different conflict types, different resolution solution libraries are constructed for subsequent selection when resolving route conflicts.

[0072] (d) Same-direction pursuit and conflict resolution solutions

[0073] Option 1: Speed ​​control, speed up the path of the aircraft in front and slow down the path of the aircraft behind;

[0074] Option 2: Adjust the height, lower the path of the aircraft in front; raise the path of the aircraft in front; raise the path of the aircraft behind; lower the path of the aircraft behind;

[0075] Option three: Adjust the route and take another detour.

[0076] (e) Reverse cross-conflict resolution scheme

[0077] Option 1: Adjust the height, lower the route of the aircraft in front and raise the route of the aircraft behind; raise the route of the aircraft in front and lower the route of the aircraft behind;

[0078] Option 2: Speed ​​adjustment, accelerating the aircraft in one direction and decelerating the aircraft in another direction;

[0079] Option three: Adjust the route and take another detour.

[0080] (f) Channel saturation conflict

[0081] Option 1: Speed ​​control, speed up the path of the aircraft in front and slow down the path of the aircraft behind;

[0082] Option 2: Adjust the route and take another detour.

[0083] S4, based on the conflict results given in the second step, establish a conflict tree structure, and search for feasible solutions for the route adjustment plan based on the conflict resolution experience knowledge base set in the third step and the Monte Carlo tree search and focused branch reduction method.

[0084] Construct a conflict tree, in which each node describes the conflicts between multiple routes, such as cross-collision, same-direction overtaking, and channel saturation, in the form of numbers. The specific attributes include conflict sequence number, conflict cause, aircraft Serial number, aircraft Serial number, aircraft Channel number and aircraft number where the route conflicts The information of the channel number where the route conflicts occurs is used to build a conflict tree based on the conflict resolution solution library, such as Figure 5 As shown. Afterwards, Monte Carlo tree search is used to search and solve the conflict tree. The Monte Carlo tree search algorithm is a method that can take random sampling decision spaces in a specific field, and build a search tree based on the results to find the optimal decision. This algorithm has wide applicability in the problem of sequential decision trees. The basis of the Monte Carlo tree search algorithm is Monte Carlo simulation, which finds the "best" action in the current state by constructing an asymmetric optimal search tree. The advantage of the Monte Carlo tree search algorithm is that it does not require prior knowledge of the complete Markov decision process model, but only requires an underlying generative model-that is, a simulator or emulator. The idea of ​​the Monte Carlo tree search algorithm is mainly to evaluate the state based on the simulation data obtained from a state node. Specifically, for each state node, the Monte Carlo tree search algorithm selects an action based on the current action selection strategy; and executes this action through Monte Carlo simulation; observes the new state, and recursively evaluates this state if it is already on the tree; otherwise, inserts this state node into the tree and simulates the default strategy from this state until the termination condition is encountered; finally, updates the statistics of each state on the path through reverse backtracking.

[0085] The Monte Carlo algorithm search process diagram of the entire route conflict tree is shown in Figure 6 The Monte Carlo tree search includes six steps: selection, expansion, simulation, focused search pruning, ending, and termination. The specific description is as follows:

[0086] (41) Selection

[0087] In the selection phase, starting from the root node, the initial situation is assigned to the spatial grid that needs to be decided. , then select the most urgent node to be expanded , and the situation It is the first node to be checked in each iteration. The check results include three possibilities: (411) All the possible actions in the node have been expanded; (412) The node has possible actions but has not been expanded; (413) The node has been expanded and has ended. For the above three possibilities, the following are handled respectively:

[0088] (i) If all possible actions have been expanded, calculate the performance index values ​​of all child nodes contained in the node, find the child node with the largest performance index value, and then continue to check the next child node. Repeat the iterative calculation for the next child node.

[0089] (ii) If the position being checked still has unexpanded child nodes (for example, a node contains 30 possible actions, but only 12 child nodes are created in the search tree), then this child node is considered to be the target node of this iteration. , and find out Actions that have not yet been expanded , and then perform the expansion step.

[0090] (iii) If the node being checked is a finished node, then the backpropagation step is performed directly from that node.

[0091] (42) Expansion

[0092] At the end of the selection phase, find a node that needs to be expanded , and an action that has not yet been expanded . At the same time, a new node is created in the search tree As A new child node of . The situation is the node After performing the action The situation after that. Actions in the expansion step Represents the use of different conflict resolution methods to resolve any pair of conflicts. The expansion process of the conflict tree is:

[0093] ;

[0094] in, Represents the jth node at the i-th layer, which contains the aircraft Conflict between , Represents randomly selecting a solution from the conflict resolution solution library in a Monte Carlo manner to obtain the kth node in the i+1th layer ;

[0095] (43) Simulation

[0096] To let Get an initial score. At the beginning, it will proceed randomly until it reaches an ending, and this ending will be used as Here, the digestion success / failure is generally used as the scoring standard for the result, that is, 1 or 0.

[0097] (44) Focused Search Pruning

[0098] Based on focused search heuristics, coupling the route correlation of a large number of actual aircraft routes , mission-critical impact , airspace crossing and other influencing factors, and obtain the focused search heuristic , to evaluate each leaf node and traverse all nodes in the current layer of the conflict tree Value, reserved The largest node cuts off all other nodes in the same layer and continues searching based on the current node.

[0099] (45) End

[0100] exist After the simulation ends, its parent node And from the root node to All nodes on the path will add their own cumulative scores based on the results of this simulation. If an outcome is found directly in the selection step, the score can be updated based on this outcome.

[0101] Each iteration expands the search tree, and as the number of iterations increases, the size of the search tree also increases. The search ends after a certain number of iterations or a certain time, and the best child node under the root node is selected as the result of this decision.

[0102] (46) Termination

[0103] The constructed tree is essentially a multi-branch search tree. Its expansion method is based on the elimination stack, so it is not complete. It may be impossible to reach the leaf node due to resource deadlock. When the search depth is greater than the set value , and the existing conflict is less than the set value When , the search terminates and the result of the current node is fed back.

[0104] S5, within a given time, based on the leaf nodes of the multiple conflict trees searched out, the better leaf node is determined based on the evaluation indicators of total route and total flight time as the solution for this conflict resolution process.

[0105] Determine the time , search the conflict tree using Monte Carlo tree search and focused branch reduction within the effective time to obtain a set of multiple leaf nodes , calculate each conflict-free route plan in the collection Total flight time and total distance , take the minimum value , get the conflict-free route plan with the minimum total flight time and total distance , determined that this plan was the final solution for resolving this conflict, and adjusted the routes of each aircraft.

Claims

1. A method for detecting and quickly resolving aircraft route conflicts under a given route network structure, characterized in that: The following steps are involved: Step 1: Define the elements of the established road network structure in the current spatial area, including channels, intersections and temporary channels; Step 2: Establish a conflict detection model based on consistent spatiotemporal analysis, and quantitatively analyze the same-direction pursuit conflicts, opposite-direction intersection conflicts, and channel saturation conflicts between multiple aircraft routes through spatiotemporal constraint modeling. The spatiotemporal constraint modeling is as follows: Channel flow constraint model: ； in, The starting point of the route Arrive at a fixed intersection air traffic flow; For a fixed intersection To the end of the route Traffic volume; The starting point of the route Go directly to the end of the route Traffic volume; For intersection The maximum capacity value of the channel The maximum capacity value; is the total number of intersections; is the total number of route starting intersections; is the total number of route terminal intersections; The safety constraint model includes: node flight interval constraint and route channel constraint; Task condition constraint model: ; Where, is the time of arrival at the route destination, Request time for tasks; Step 3: Build a conflict resolution experience knowledge base to store pairwise route conflict resolution solutions based on manual experience; Step 4: Construct a conflict tree based on the conflict detection results from step 2. Combined with the conflict resolution experience knowledge base from step 3, a Monte Carlo tree search and focused branch reduction method are used to search for feasible solutions for route adjustment. The conflict tree nodes include: conflict number, conflict cause, conflicting aircraft number, and conflicting channel number. The expansion process of the conflict tree is expressed as follows: ； in, Representative is located at layer Node No., which contains the aircraft Conflict between ; The representative randomly extracts a solution from the conflict resolution solution library in a Monte Carlo manner and obtains the layer Node ; The focused branch reduction method is as follows: Calculate the leaf node evaluation value: ； in, Represents the relevance of the conflict within the leaf node to all routes, Represents the impact of conflicts within leaf nodes on key tasks, Represents the airspace resources affected by the conflict within the leaf node; calculates the Q value for each leaf node and retains the node with the largest Q value in the current layer, and prunes the remaining nodes in the same layer; Step 5: Within a given time, select the optimal conflict-free route plan based on the total range and total flight time evaluation indicators of the conflict tree child nodes and adjust the aircraft route.

2. The method for detecting and quickly resolving aircraft route conflicts under a given route network structure according to claim 1, characterized in that: In step 1, a channel is defined as a straight horizontal area connecting two points at the same height, including the upper bound height, lower bound height, channel width, starting point longitude and latitude, end point longitude and latitude, and channel capacity attributes; an intersection is defined as a point in a channel, including the upper bound height, lower bound height, width, longitude, latitude, and safe passing time attributes. Each channel includes at least a starting intersection and an end intersection; a temporary channel is defined as a straight horizontal area connecting intersections at the same height between different channels, including the starting point longitude and latitude, end point longitude and latitude, height, and channel width attributes.

3. The method for detecting and quickly resolving aircraft route conflicts under a given route network structure according to claim 1, characterized in that: In step 2, the qualitative conflict analysis includes the following: same-direction overtaking conflict: two aircraft cross the same channel at the same altitude in the same direction, and the one that enters first exits last; opposite-direction crossing conflict: two aircraft cross the same channel at the same altitude in opposite directions; and channel saturation conflict: the time interval between two aircraft passing the same intersection is less than the safe passage time.

4. The method for detecting and quickly resolving aircraft route conflicts under a given route network structure according to claim 1, characterized in that: In step 3, the conflict resolution experience knowledge base includes: same-direction pursuit conflict resolution solutions: speed adjustment, height adjustment, or point adjustment for detour; reverse crossing conflict resolution solutions: height adjustment, speed adjustment, or point adjustment for detour; channel saturation conflict resolution solutions: speed adjustment, or point adjustment for detour.

5. The method for detecting and quickly resolving aircraft route conflicts under a given route network structure according to claim 1, characterized in that: Step 5 is as follows: Search for a conflict-free leaf node set T within time t; calculate the total range and total flight time evaluation values ​​of each plan , select the minimum value Corresponding solutions As the final adjustment plan.

6. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

7. A computer-readable storage medium, characterized in that A computer program is stored, and when the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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