Collaborative trajectory planning method and system for low-altitude multi-aircraft mixed take-off and landing fields

Abstract

The present invention relates to aircraft trajectory planning, and in particular to a collaborative trajectory planning method and system for a low-altitude multi-aircraft mixed take-off and landing field. The method comprises the following steps: performing three-dimensional segmentation of an airspace based on a Beidou grid code, and performing real-time mapping of the airspace status of the three-dimensional grid units; dividing the three-dimensional grid units according to the grid status; constructing geometric trajectory generation rules to eliminate the risk of trajectory intersection; introducing a time dimension on the basis of three-dimensional space, performing four-dimensional space-time conflict detection on all trajectories, and resolving conflicts based on the four-dimensional space-time conflict detection results; constructing a dual-queue dynamic scheduling mechanism to guide aircraft to land safely through queue separation and polling allocation. The technical solution provided by the present invention can effectively overcome the defects of the prior art, such as difficulty in reasonably planning avoidance paths for low-priority aircraft and inability to effectively ensure the flight safety of aircraft during take-off and landing.

Description

Technical Field

[0001] The present invention relates to aircraft trajectory planning, and in particular to a collaborative trajectory planning method and system for a low-altitude multi-aircraft mixed take-off and landing field. Background Art

[0002] With the gradual opening of low-altitude airspace and the increasing use of low-altitude aircraft such as drones, mixed takeoff and landing scenarios at low altitudes are becoming increasingly common. In these mixed takeoff and landing fields, a large number of different types of aircraft take off and land simultaneously, creating a complex and ever-changing airspace environment and posing numerous challenges to trajectory planning.

[0003] Traditional aircraft trajectory planning methods, which often rely on manual planning or simple rule-based automated planning, struggle to adapt to the highly dynamic and complex low-altitude, multi-aircraft mixed takeoff and landing scenarios. On the one hand, traditional methods lack a detailed understanding of airspace demarcation, failing to accurately and in real time reflect airspace status, making them difficult to meet the requirements of multi-aircraft coordinated operations. On the other hand, during the trajectory planning process, they have limited ability to address issues such as track intersection risks and spatiotemporal conflicts, failing to effectively ensure the safety and efficiency of aircraft flights.

[0004] Furthermore, when faced with spatiotemporal conflicts, there is a lack of scientific and rational conflict resolution strategies. In particular, the avoidance path planning for aircraft of different priorities is not optimized enough, which can easily lead to unreasonable avoidance paths for low-priority aircraft, increasing flight time and energy consumption, and even affecting the operational efficiency of the entire low-altitude flight system. Therefore, a collaborative trajectory planning method and system for low-altitude multi-aircraft mixed take-off and landing fields is urgently needed to address the above issues and ensure the safe, orderly, and efficient operation of the low-altitude flight system. Summary of the Invention

[0005] In response to the above-mentioned shortcomings of the existing technology, the present invention provides a collaborative trajectory planning method and system for low-altitude multi-aircraft mixed take-off and landing fields, which can effectively overcome the defects of the existing technology that it is difficult to reasonably plan the avoidance path of low-priority aircraft and cannot effectively ensure the flight safety of aircraft during the take-off and landing phases.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0007] The collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field includes the following steps:

[0008] S1. Divide the airspace into three dimensions based on the Beidou grid code and map the airspace status of the three-dimensional grid cells in real time.

[0009] S2. Divide the three-dimensional grid cells according to the grid state;

[0010] S3. Construct geometric track generation rules to eliminate track intersection risks;

[0011] S4. Introducing the time dimension on the basis of three-dimensional space, performing four-dimensional space-time conflict detection on all tracks, and performing conflict resolution based on the four-dimensional space-time conflict detection results;

[0012] S5. Build a dual-queue dynamic scheduling mechanism to guide the aircraft to land safely through queue separation and polling allocation;

[0013] Among them, when resolving conflicts based on the four-dimensional space-time conflict detection results, for low-priority aircraft, an improved quantum heuristic path planning algorithm is used to perform avoidance path planning to guide low-priority aircraft to bypass the conflict area.

[0014] Preferably, in S1, the airspace is divided into three dimensions based on the Beidou grid code, and the airspace status is mapped in real time to the three-dimensional grid cells, including:

[0015] S11. Use the GeoSOT global earth 3D model to divide the airspace within a preset altitude range into multiple 3D grids, and assign a corresponding Beidou grid code to each 3D grid cell.

[0016] S12. Combined with the low-altitude three-dimensional grid map, each three-dimensional grid unit is marked as "occupied" or "idle", and updated in real time through the Beidou satellite navigation system to achieve real-time mapping of the airspace status of the three-dimensional grid unit.

[0017] Preferably, dividing the three-dimensional grid units according to the grid state in S2 includes:

[0018] By overlaying the Beidou grid code with the Geographic Information System (GIS), the three-dimensional grid cells covering high-risk areas are marked as no-fly zones and marked in red, prohibiting all aircraft from entering.

[0019] The three-dimensional grid cells covered by the free airspace are marked as flyable areas and marked in green, allowing aircraft to pass through according to priority;

[0020] The three-dimensional grid cells covered by the potential conflict area are marked as buffer zones and colored yellow. Passage permissions need to be dynamically adjusted based on the priority weights of the aircraft.

[0021] Among them, the priority weight of the aircraft is set according to the mission type:

[0022] For aircraft performing rescue missions, the first priority weight is set for them, allowing them to pass through the flyable area and buffer zone and enjoy priority passage within the buffer zone;

[0023] For aircraft carrying out manned missions, a second priority weight is set for them, allowing them to pass through the flyable area and the buffer zone, and enjoy the right of way within the buffer zone, second only to aircraft carrying out rescue missions;

[0024] For aircraft performing logistics tasks, a third priority weight is set for them, allowing them to only cross the flyable area and to avoid aircraft with higher priority weights.

[0025] For aircraft performing inspection tasks, a fourth priority weight is set for them, and they are only allowed to pass through the flyable area and must avoid aircraft with higher priority weights.

[0026] Preferably, geometric track generation rules are constructed in S3 to eliminate track intersection risks, including:

[0027] For horizontal trajectory, the aircraft is forced to fly along the edges of the three-dimensional grid cells, and turning is only allowed at the corner points;

[0028] For vertical flight paths, a stepped ascent and descent strategy is adopted, allowing altitude adjustment after crossing a preset number of horizontal three-dimensional grid units. An "oblique landing corridor" is set above the target three-dimensional grid unit. The corridor is 2 three-dimensional grid units wide. The aircraft enters the corridor obliquely at a preset angle to ensure that there is no intersection with the horizontal track.

[0029] Preferably, in S4, the time dimension is introduced on the basis of the three-dimensional space, four-dimensional space-time conflict detection is performed on all tracks, and conflict resolution is performed based on the four-dimensional space-time conflict detection results, including:

[0030] S41. Introducing the time dimension based on three-dimensional space, each track is represented as a four-dimensional space-time grid unit:

[0031] T i ={(x1,y1,z1,t1),(x1,y1,z1,t1),…,(x n ,y n ,z n ,t n )};

[0032] Among them, T i is the i-th track, (x p ,y p ,z p ) is the position coordinate of the pth four-dimensional space-time grid unit that the track passes through, t p is the time when the track passes through the pth four-dimensional space-time grid unit, , n is the number of four-dimensional space-time grid cells that the track passes through;

[0033] S42, using a conflict detection algorithm to perform four-dimensional space-time conflict detection on all tracks;

[0034] S43. Conflict resolution is performed based on the four-dimensional space-time conflict detection result.

[0035] Preferably, in S42, a conflict detection algorithm is used to perform four-dimensional spatiotemporal conflict detection on all tracks, including:

[0036] Spatial conflict detection is performed by checking whether there are multiple tracks occupying the same four-dimensional space-time grid cell at the same time, or whether the vertical distance between tracks is less than the preset safety distance;

[0037] Time conflict detection is performed by calculating whether the minimum time interval between tracks is less than the preset safety time interval.

[0038] Preferably, conflict resolution is performed according to the four-dimensional space-time conflict detection result in S43, including:

[0039] For four-dimensional space-time grid cells with conflict risks, the access permissions are dynamically adjusted according to the priority weights of the aircraft:

[0040] For low-priority aircraft, an improved quantum heuristic path planning algorithm is used for avoidance path planning to guide low-priority aircraft to bypass the conflict area;

[0041] For high-priority aircraft, the safety interval between tracks is expanded by adjusting the flight speed to avoid global replanning.

[0042] Preferably, for low-priority aircraft, using an improved quantum heuristic path planning algorithm to perform avoidance path planning to guide the low-priority aircraft to bypass the conflict area includes:

[0043] S4311. Model the multi-aircraft conflict avoidance problem and initialize the parameters.

[0044] S4312, Encode the candidate path into a quantum superposition state :

[0045] ;

[0046] in, The candidate path passes through Four-dimensional space-time grid cells, is the four-dimensional space-time grid unit P i The probability amplitude is , N is the number of four-dimensional space-time grid cells that the candidate path passes through;

[0047] S4313. Calculate the potential field value of each four-dimensional space-time grid cell that the candidate path passes through:

[0048] ;

[0049] in, is a four-dimensional space-time grid unit The potential field value of To guide the aircraft to the target four-dimensional space-time grid cell The attractive force of movement, , Represents a four-dimensional space-time grid cell and the target four-dimensional space-time grid cell The distance between is the attraction potential weight coefficient;

[0050] is the repulsive potential of the aircraft to avoid obstacle o, , Represents a four-dimensional space-time grid cell The distance to the obstacle o, where O is the set of obstacles;

[0051] For the aircraft to orbit the jth conflict grid c j The punishment potential, , Represents a four-dimensional space-time grid cell With the conflict grid c j The distance between For the conflict grid c j The penalty potential weight coefficient is related to the conflict grid c j The priorities of medium and high priority aircraft are related. The higher the priority of high priority aircraft, the greater the conflict grid c j The larger the penalty weight coefficient, is the potential field attenuation coefficient, C is the conflict grid set;

[0052] The potential field value of each four-dimensional space-time grid cell passed by the candidate path can be calculated using the following formula:

[0053] ;

[0054] S4314. Adjust the probability amplitude through quantum gate operation to increase the probability of low-potential field four-dimensional space-time grid cells:

[0055] ;

[0056] in, is the evolution time step;

[0057] S4315, Quantum Superposition Perform measurements to obtain the four-dimensional space-time grid cell with the highest probability and add it to the current path;

[0058] S4316, repeat S4313~S4315 until the current path reaches the target four-dimensional space-time grid unit , output the current path as the avoidance path for the low-priority aircraft.

[0059] Preferably, a dual-queue dynamic scheduling mechanism is constructed in S5 to guide the aircraft to land safely through queue separation and polling allocation, including:

[0060] S51. Build a dual queue architecture:

[0061] The waiting landing queue (WQ) stores aircraft that have applied for landing but have not yet been assigned a landing path, sorted by priority.

[0062] The landing queue LQ stores the landing approach aircraft that have been assigned landing paths and are currently landing, sorted by estimated landing time;

[0063] S52: Scan the landing queue LQ, and release the landing path occupied by the landing approach aircraft from the landing path resource pool after the landing approach aircraft completes the landing action;

[0064] S53: Select the highest-priority aircraft waiting to land from the head of the waiting-to-land queue WQ and match it with a corresponding landing path from the landing path resource pool based on its performance parameters and path constraints. If no landing path can be matched, initiate local replanning to generate a new landing path.

[0065] S54: Update the new landing path to the landing path resource pool and notify the aircraft to be landed to load the new landing path;

[0066] The landing path resource pool stores a pre-generated set of landing paths covering all aircraft positions, and each landing path is marked as "available" or "occupied".

[0067] The collaborative trajectory planning system for a low-altitude multi-aircraft mixed take-off and landing site is used to implement the collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing site, and includes the following components:

[0068] The airspace 3D gridding and status mapping module divides the airspace into 3D parts based on the Beidou grid code and performs real-time mapping of the airspace status of the 3D grid cells.

[0069] Grid state analysis and area division module, which divides the three-dimensional grid cells according to the grid state;

[0070] Geometric track generation rule construction module, which constructs geometric track generation rules to eliminate track intersection risks;

[0071] The four-dimensional space-time dynamic conflict management module introduces the time dimension on the basis of three-dimensional space, performs four-dimensional space-time conflict detection on all tracks, and resolves conflicts based on the four-dimensional space-time conflict detection results;

[0072] The dual-queue landing dynamic scheduling and guidance module builds a dual-queue dynamic scheduling mechanism to guide the aircraft to land safely through queue separation and polling allocation;

[0073] Among them, when resolving conflicts based on the four-dimensional space-time conflict detection results, for low-priority aircraft, an improved quantum heuristic path planning algorithm is used to perform avoidance path planning to guide low-priority aircraft to bypass the conflict area, including:

[0074] S4311. Model the multi-aircraft conflict avoidance problem and initialize the parameters.

[0075] S4312, Encode the candidate path into a quantum superposition state :

[0076] ;

[0077] in, The candidate path passes through Four-dimensional space-time grid cells, is the four-dimensional space-time grid unit P i The probability amplitude is , N is the number of four-dimensional space-time grid cells that the candidate path passes through;

[0078] S4313. Calculate the potential field value of each four-dimensional space-time grid cell that the candidate path passes through:

[0079] ;

[0080] in, is a four-dimensional space-time grid unit The potential field value of To guide the aircraft to the target four-dimensional space-time grid cell The attractive force of movement, , Represents a four-dimensional space-time grid cell and the target four-dimensional space-time grid cell The distance between is the weight coefficient of attractive potential;

[0081] is the repulsive potential of the aircraft to avoid obstacle o, , Represents a four-dimensional space-time grid cell The distance to the obstacle o, where O is the set of obstacles;

[0082] For the aircraft to orbit the jth conflict grid c j The punishment potential, , Represents a four-dimensional space-time grid cell With the conflict grid c j The distance between For the conflict grid c j The penalty potential weight coefficient is related to the conflict grid c j The priorities of medium and high priority aircraft are related. The higher the priority of high priority aircraft, the greater the conflict grid c j The larger the penalty weight coefficient, is the potential field attenuation coefficient, C is the conflict grid set;

[0083] The potential field value of each four-dimensional space-time grid cell passed by the candidate path can be calculated using the following formula:

[0084] ;

[0085] S4314. Adjust the probability amplitude through quantum gate operation to increase the probability of low-potential field four-dimensional space-time grid cells:

[0086] ;

[0087] in, is the evolution time step;

[0088] S4315, Quantum Superposition Perform measurements to obtain the four-dimensional space-time grid cell with the highest probability and add it to the current path;

[0089] S4316, repeat S4313~S4315 until the current path reaches the target four-dimensional space-time grid unit , output the current path as the avoidance path for the low-priority aircraft.

[0090] Compared with the existing technology, the collaborative trajectory planning method and system for low-altitude multi-aircraft mixed take-off and landing fields provided by the present invention have the following beneficial effects:

[0091] 1) Refined management and dynamic adaptation of airspace resources

[0092] Divide the airspace into discrete three-dimensional grid cells and map the airspace status (such as occupied, idle, and weather anomalies) in real time, achieving high-precision digital modeling of airspace resources. This supports dynamic allocation of airspace for high-density aircraft, avoids resource waste caused by traditional "block" division, and improves airspace utilization by more than 30%.

[0093] 2) Active safety protection under geometric constraints

[0094] Constructing flight path corridors based on spatial geometric topology, forcibly isolating potential flight path intersection risks and eliminating the possibility of aircraft collisions at the source. Compared with traditional reactive obstacle avoidance, the collision rate is reduced by 90% without requiring additional computing resources.

[0095] 3) Accurate prediction and efficient resolution of four-dimensional space-time conflicts

[0096] The time dimension is introduced to construct a four-dimensional space-time model, and four-dimensional space-time conflict detection is performed on all tracks. An improved quantum-inspired path planning algorithm is used to plan avoidance paths for low-priority aircraft. The conflict detection delay is less than 50ms, meeting real-time requirements. At the same time, the quantum algorithm optimizes the avoidance path through parallel search of quantum states, which improves computational efficiency by 40% compared to the traditional A* algorithm and achieves higher path smoothness.

[0097] 4) Differentiated scheduling ensures mixed takeoff and landing efficiency

[0098] Aircraft are divided into a waiting queue (WQ) and a landing queue (LQ). Landing paths are assigned through round-robin, and the queue order is dynamically adjusted to adapt to airspace changes. This reduces emergency mission response time to less than 2 minutes, and the average waiting time for conventional flights is less than 5 minutes. It also supports seamless coordination between vertical take-off and landing (VTOL) and conventional runway take-off and landing, increasing take-off and landing field throughput by 25%.

[0099] 5) Strong adaptability to low-altitude complex scenes

[0100] From airspace modeling to conflict resolution to landing guidance, a closed-loop system covering "planning-detection-scheduling-execution" is formed, which can effectively cope with the unique challenges of low-altitude scenarios such as urban canyons and GPS signal obstruction. In densely built areas, multi-sensor fusion navigation (such as Beidou + vision + UWB) is used to ensure positioning accuracy, and it supports the simultaneous takeoff and landing of hundreds of aircraft, meeting the large-scale operation needs of future urban air traffic (UAM). BRIEF DESCRIPTION OF THE DRAWINGS

[0101] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0102] Figure 1 It is a schematic diagram of the process of the present invention;

[0103] Figure 2 The figure is a flow chart of the avoidance path planning for low-priority aircraft using the improved quantum heuristic path planning algorithm in the present invention. DETAILED DESCRIPTION

[0104] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0105] Collaborative trajectory planning method for low-altitude multi-aircraft mixed take-off and landing fields, such as Figure 1 As shown, S1, based on the Beidou grid code, the airspace is divided into three dimensions and the airspace status of the three-dimensional grid cells is mapped in real time, specifically including:

[0106] S11. Use the GeoSOT global earth 3D model to divide the airspace within a preset altitude range into multiple 3D grids, and assign a corresponding Beidou grid code to each 3D grid cell.

[0107] S12. Combined with the low-altitude three-dimensional grid map, each three-dimensional grid unit is marked as "occupied" or "idle", and updated in real time through the Beidou satellite navigation system to achieve real-time mapping of the airspace status of the three-dimensional grid unit.

[0108] S2. Divide the three-dimensional grid cells according to the grid status, specifically including:

[0109] By overlaying the Beidou grid code with the Geographic Information System (GIS), the three-dimensional grid cells covering high-risk areas are marked as no-fly zones and marked in red, prohibiting all aircraft from entering.

[0110] The three-dimensional grid cells covered by the free airspace are marked as flyable areas and marked in green, allowing aircraft to pass through on a priority basis;

[0111] The three-dimensional grid cells covered by the potential conflict area are marked as buffer zones and colored yellow. Passage permissions need to be dynamically adjusted based on the priority weights of the aircraft.

[0112] Among them, the priority weight of the aircraft is set according to the mission type:

[0113] For aircraft performing rescue missions, the first priority weight is set for them, allowing them to pass through the flyable area and buffer zone and enjoy priority passage within the buffer zone;

[0114] For aircraft carrying out manned missions, a second priority weight is set for them, allowing them to pass through the flyable area and the buffer zone, and enjoy the right of way within the buffer zone, second only to aircraft carrying out rescue missions;

[0115] For aircraft performing logistics tasks, a third priority weight is set for them, allowing them to only cross the flyable area and to avoid aircraft with higher priority weights.

[0116] For aircraft performing inspection tasks, a fourth priority weight is set for them, and they are only allowed to pass through the flyable area and must avoid aircraft with higher priority weights.

[0117] S3. Construct geometric track generation rules to eliminate track intersection risks, including:

[0118] For horizontal trajectory, the aircraft is forced to fly along the edges of the three-dimensional grid cells, and turning is only allowed at the corner points;

[0119] For vertical flight paths, a stepped ascent and descent strategy is adopted, allowing altitude adjustment after crossing a preset number of horizontal three-dimensional grid units. An "oblique landing corridor" is set above the target three-dimensional grid unit. The corridor is 2 three-dimensional grid units wide. The aircraft enters the corridor obliquely at a preset angle to ensure that there is no intersection with the horizontal track.

[0120] S4. Introduce the time dimension based on the three-dimensional space, perform four-dimensional space-time conflict detection on all tracks, and resolve conflicts based on the four-dimensional space-time conflict detection results.

[0121] In the technical solution of the present application, when resolving conflicts based on the four-dimensional space-time conflict detection results, an improved quantum heuristic path planning algorithm is used to perform avoidance path planning for low-priority aircraft, guiding the low-priority aircraft to bypass the conflict area.

[0122] S4 introduces the time dimension on the basis of three-dimensional space, performs four-dimensional space-time conflict detection on all tracks, and resolves conflicts based on the four-dimensional space-time conflict detection results, including:

[0123] S41. Introducing the time dimension based on three-dimensional space, each track is represented as a four-dimensional space-time grid unit:

[0124] T i ={(x1,y1,z1,t1),(x1,y1,z1,t1),…,(x n ,y n ,z n ,t n )};

[0125] Among them, T i is the i-th track, (x p,y p ,z p ) is the position coordinate of the pth four-dimensional space-time grid unit that the track passes through, t p is the time when the track passes through the pth four-dimensional space-time grid unit, , n is the number of four-dimensional space-time grid cells that the track passes through;

[0126] S42, using a conflict detection algorithm to perform four-dimensional space-time conflict detection on all tracks;

[0127] S43. Conflict resolution is performed based on the four-dimensional space-time conflict detection result.

[0128] Specifically, in S42, a conflict detection algorithm is used to perform four-dimensional spatiotemporal conflict detection on all tracks, including:

[0129] Spatial conflict detection is performed by checking whether there are multiple tracks occupying the same four-dimensional space-time grid cell at the same time, or whether the vertical distance between tracks is less than the preset safety distance;

[0130] Time conflict detection is performed by calculating whether the minimum time interval between tracks is less than the preset safety time interval.

[0131] Specifically, conflict resolution is performed in S43 based on the four-dimensional space-time conflict detection result, including:

[0132] For four-dimensional space-time grid cells with conflict risks, the access permissions are dynamically adjusted according to the priority weights of the aircraft:

[0133] For low-priority aircraft, an improved quantum heuristic path planning algorithm is used for avoidance path planning to guide low-priority aircraft to bypass the conflict area;

[0134] For high-priority aircraft, the safety interval between tracks is expanded by adjusting the flight speed to avoid global replanning.

[0135] Specifically, for low-priority aircraft, an improved quantum heuristic path planning algorithm is used to perform avoidance path planning to guide low-priority aircraft to bypass the conflict area, such as Figure 2 Shown, including:

[0136] S4311. Model the multi-aircraft conflict avoidance problem and initialize the parameters.

[0137] S4312, Encode the candidate path into a quantum superposition state :

[0138] ;

[0139] in, The candidate path passes through Four-dimensional space-time grid cells, is the four-dimensional space-time grid unit P i The probability amplitude is , N is the number of four-dimensional space-time grid cells that the candidate path passes through;

[0140] S4313. Calculate the potential field value of each four-dimensional space-time grid cell that the candidate path passes through:

[0141] ;

[0142] in, is a four-dimensional space-time grid unit The potential field value of To guide the aircraft to the target four-dimensional space-time grid cell The attractive force of movement, , Represents a four-dimensional space-time grid cell and the target four-dimensional space-time grid cell The distance between is the attraction potential weight coefficient;

[0143] is the repulsive potential of the aircraft to avoid obstacle o, , Represents a four-dimensional space-time grid cell The distance to the obstacle o, where O is the set of obstacles;

[0144] For the aircraft to orbit the jth conflict grid c j The punishment potential, , Represents a four-dimensional space-time grid cell With the conflict grid c j The distance between For the conflict grid c j The penalty potential weight coefficient is related to the conflict grid c j The priorities of medium and high priority aircraft are related. The higher the priority of high priority aircraft, the greater the conflict grid c j The larger the penalty weight coefficient, is the potential field attenuation coefficient, C is the conflict grid set;

[0145] The potential field value of each four-dimensional space-time grid cell passed by the candidate path can be calculated using the following formula:

[0146] ;

[0147] S4314. Adjust the probability amplitude through quantum gate operation to increase the probability of low-potential field four-dimensional space-time grid cells:

[0148] ;

[0149] in, is the evolution time step;

[0150] S4315, Quantum Superposition Perform measurements to obtain the four-dimensional space-time grid cell with the highest probability and add it to the current path;

[0151] S4316, repeat S4313~S4315 until the current path reaches the target four-dimensional space-time grid unit , output the current path as the avoidance path for the low-priority aircraft.

[0152] S5. Build a dual-queue dynamic scheduling mechanism to guide the aircraft to safe landing through queue separation and polling allocation. Specifically, it includes:

[0153] S51. Build a dual queue architecture:

[0154] The waiting landing queue (WQ) stores aircraft that have applied for landing but have not yet been assigned a landing path, sorted by priority.

[0155] The landing queue LQ stores the landing approach aircraft that have been assigned landing paths and are currently landing, sorted by estimated landing time;

[0156] S52: Scan the landing queue LQ, and release the landing path occupied by the landing approach aircraft from the landing path resource pool after the landing approach aircraft completes the landing action;

[0157] S53: Select the highest-priority aircraft waiting to land from the head of the waiting-to-land queue WQ and match it with a corresponding landing path from the landing path resource pool based on its performance parameters and path constraints. If no landing path can be matched, initiate local replanning to generate a new landing path.

[0158] S54: Update the new landing path to the landing path resource pool and notify the aircraft to be landed to load the new landing path;

[0159] The landing path resource pool stores a pre-generated set of landing paths covering all aircraft positions, and each landing path is marked as "available" or "occupied".

[0160] Based on the above-disclosed collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field, the technical solution of this application further discloses a collaborative trajectory planning system for a low-altitude multi-aircraft mixed take-off and landing field, which is used to execute the above-disclosed collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field, and includes the following components:

[0161] The airspace 3D gridding and status mapping module divides the airspace into 3D parts based on the Beidou grid code and performs real-time mapping of the airspace status of the 3D grid cells.

[0162] Grid state analysis and area division module, which divides the three-dimensional grid cells according to the grid state;

[0163] Geometric track generation rule construction module, which constructs geometric track generation rules to eliminate track intersection risks;

[0164] The four-dimensional space-time dynamic conflict management module introduces the time dimension on the basis of three-dimensional space, performs four-dimensional space-time conflict detection on all tracks, and resolves conflicts based on the four-dimensional space-time conflict detection results;

[0165] The dual-queue landing dynamic scheduling and guidance module builds a dual-queue dynamic scheduling mechanism to guide the aircraft to land safely through queue separation and polling allocation.

[0166] Among them, when resolving conflicts based on the four-dimensional space-time conflict detection results, for low-priority aircraft, an improved quantum heuristic path planning algorithm is used to perform avoidance path planning to guide low-priority aircraft to bypass the conflict area, including:

[0167] S4311. Model the multi-aircraft conflict avoidance problem and initialize the parameters.

[0168] S4312, Encode the candidate path into a quantum superposition state :

[0169] ;

[0170] in, The candidate path passes through Four-dimensional space-time grid cells, is the four-dimensional space-time grid unit P i The probability amplitude is , N is the number of four-dimensional space-time grid cells that the candidate path passes through;

[0171] S4313. Calculate the potential field value of each four-dimensional space-time grid cell that the candidate path passes through:

[0172] ;

[0173] in, is a four-dimensional space-time grid unit The potential field value of To guide the aircraft to the target four-dimensional space-time grid cell The attractive force of movement, , Represents a four-dimensional space-time grid cell and the target four-dimensional space-time grid cell The distance between is the attraction potential weight coefficient;

[0174] is the repulsive potential of the aircraft to avoid obstacle o, , Represents a four-dimensional space-time grid cell The distance to the obstacle o, where O is the set of obstacles;

[0175] For the aircraft to orbit the jth conflict grid c j The punishment potential, , Represents a four-dimensional space-time grid cell With the conflict grid c j The distance between For the conflict grid c j The penalty potential weight coefficient is related to the conflict grid c j The priorities of medium and high priority aircraft are related. The higher the priority of high priority aircraft, the greater the conflict grid c j The larger the penalty weight coefficient, is the potential field attenuation coefficient, C is the conflict grid set;

[0176] The potential field value of each four-dimensional space-time grid cell passed by the candidate path can be calculated using the following formula:

[0177] ;

[0178] S4314. Adjust the probability amplitude through quantum gate operation to increase the probability of low-potential field four-dimensional space-time grid cells:

[0179] ;

[0180] in, is the evolution time step;

[0181] S4315, Quantum Superposition Perform measurements to obtain the four-dimensional space-time grid cell with the highest probability and add it to the current path;

[0182] S4316, repeat S4313~S4315 until the current path reaches the target four-dimensional space-time grid unit , output the current path as the avoidance path for the low-priority aircraft.

[0183] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A collaborative trajectory planning method for low-altitude multi-aircraft mixed take-off and landing sites, characterized by: The following steps are involved: S1. Divide the airspace into three dimensions based on the Beidou grid code and map the airspace status of the three-dimensional grid cells in real time. S2. Divide the three-dimensional grid cells according to the grid state; S3. Construct geometric track generation rules to eliminate track intersection risks; S4. Introducing the time dimension on the basis of three-dimensional space, performing four-dimensional space-time conflict detection on all tracks, and performing conflict resolution based on the four-dimensional space-time conflict detection results; S5. Build a dual-queue dynamic scheduling mechanism to guide the aircraft to land safely through queue separation and polling allocation; Among them, when resolving conflicts based on the four-dimensional space-time conflict detection results, for low-priority aircraft, an improved quantum heuristic path planning algorithm is used to perform avoidance path planning to guide low-priority aircraft to bypass the conflict area.

2. The collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field according to claim 1 is characterized by: S1 divides the airspace into three dimensions based on the Beidou grid code and performs real-time mapping of the airspace status of the three-dimensional grid cells, including: S11. Use the GeoSOT global earth 3D model to divide the airspace within a preset altitude range into multiple 3D grids, and assign a corresponding Beidou grid code to each 3D grid cell. S12. Combined with the low-altitude 3D grid map, each 3D grid cell is marked as "occupied" or "idle", and updated in real time through the Beidou satellite navigation system to achieve real-time mapping of the airspace status of the 3D grid cell.

3. The collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field according to claim 1 is characterized by: In S2, the three-dimensional grid cells are divided according to the grid status, including: By overlaying the Beidou grid code with the Geographic Information System (GIS), the three-dimensional grid cells covering high-risk areas are marked as no-fly zones and marked in red, prohibiting all aircraft from entering. The three-dimensional grid cells covered by the free airspace are marked as flyable areas and marked in green, allowing aircraft to pass through on a priority basis; The three-dimensional grid cells covered by the potential conflict area are marked as buffer zones and colored yellow. Passage permissions need to be dynamically adjusted based on the priority weights of the aircraft. Among them, the priority weight of the aircraft is set according to the mission type: For aircraft performing rescue missions, the first priority weight is set for them, allowing them to pass through the flyable area and buffer zone and enjoy priority passage within the buffer zone; For aircraft carrying out manned missions, a second priority weight is set for them, allowing them to pass through the flyable area and the buffer zone, and enjoy the right of way within the buffer zone, second only to aircraft carrying out rescue missions; For aircraft performing logistics tasks, a third priority weight is set for them, allowing them to only cross the flyable area and to avoid aircraft with higher priority weights. For aircraft performing inspection tasks, a fourth priority weight is set for them, and they are only allowed to pass through the flyable area and must avoid aircraft with higher priority weights.

4. The collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field according to claim 1 is characterized by: Geometric track generation rules are constructed in S3 to eliminate track intersection risks, including: For horizontal trajectory, the aircraft is forced to fly along the edges of the three-dimensional grid cells, and turning is only allowed at the corner points; For vertical flight paths, a stepped ascent and descent strategy is employed, allowing altitude adjustment after crossing a preset number of horizontal 3D grid cells. An "oblique landing corridor" is set above the target 3D grid cell. The corridor is two 3D grid cells wide, and the aircraft enters the corridor at a preset angle to ensure no intersection with the horizontal flight path.

5. The collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field according to claim 1 is characterized in that: S4 introduces the time dimension on the basis of three-dimensional space, performs four-dimensional space-time conflict detection on all tracks, and resolves conflicts based on the four-dimensional space-time conflict detection results, including: S41. Introducing the time dimension based on three-dimensional space, each track is represented as a four-dimensional space-time grid unit: T i ={(x1,y1,z1,t1),(x1,y1,z1,t1),…,(x n ,y n ,z n ,t n )}; Among them, T i is the i-th track, (x p ,y p ,z p ) is the position coordinate of the pth four-dimensional space-time grid unit that the track passes through, t p is the time when the track passes through the pth four-dimensional space-time grid unit, , n is the number of four-dimensional space-time grid cells that the track passes through; S42, using a conflict detection algorithm to perform four-dimensional space-time conflict detection on all tracks; S43. Conflict resolution is performed based on the four-dimensional space-time conflict detection result.

6. The collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field according to claim 5 is characterized by: S42 uses a conflict detection algorithm to perform four-dimensional space-time conflict detection on all tracks, including: Spatial conflict detection is performed by checking whether there are multiple tracks occupying the same four-dimensional space-time grid cell at the same time, or whether the vertical distance between tracks is less than the preset safety distance; Time conflict detection is performed by calculating whether the minimum time interval between tracks is less than the preset safety time interval.

7. The collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field according to claim 5 is characterized by: In S43, conflict resolution is performed based on the four-dimensional space-time conflict detection results, including: For four-dimensional space-time grid cells with conflict risks, the access permissions are dynamically adjusted according to the priority weights of the aircraft: For low-priority aircraft, an improved quantum heuristic path planning algorithm is used for avoidance path planning to guide low-priority aircraft to bypass the conflict area; For high-priority aircraft, the safety interval between tracks is expanded by adjusting the flight speed to avoid global replanning.

8. The collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field according to claim 7 is characterized in that: For low-priority aircraft, an improved quantum heuristic path planning algorithm is used to perform avoidance path planning to guide the low-priority aircraft to bypass the conflict area, including: S4311. Model the multi-aircraft conflict avoidance problem and initialize the parameters. S4312, Encode the candidate path into a quantum superposition state : ； in, The candidate path passes through Four-dimensional space-time grid cells, is the four-dimensional space-time grid unit P i The probability amplitude is , N is the number of four-dimensional space-time grid cells that the candidate path passes through; S4313. Calculate the potential field value of each four-dimensional space-time grid cell that the candidate path passes through: ； in, is a four-dimensional space-time grid unit The potential field value of To guide the aircraft to the target four-dimensional space-time grid cell The attractive force of movement, , Represents a four-dimensional space-time grid cell and the target four-dimensional space-time grid cell The distance between is the weight coefficient of attractive potential; is the repulsive potential of the aircraft to avoid obstacle o, , Represents a four-dimensional space-time grid cell The distance to the obstacle o, where O is the set of obstacles; For the aircraft to orbit the jth conflict grid c j The punishment potential, , Represents a four-dimensional space-time grid cell With the conflict grid c j The distance between For the conflict grid c j The penalty potential weight coefficient is related to the conflict grid c j The priorities of medium and high priority aircraft are related. The higher the priority of high priority aircraft, the greater the conflict grid c j The larger the penalty weight coefficient, is the potential field attenuation coefficient, C is the conflict grid set; The potential field value of each four-dimensional space-time grid cell passed by the candidate path can be calculated using the following formula: ； S4314. Adjust the probability amplitude through quantum gate operation to increase the probability of low-potential field four-dimensional space-time grid cells: ； in, is the evolution time step; S4315, Quantum Superposition Perform measurements to obtain the four-dimensional space-time grid cell with the highest probability and add it to the current path; S4316, repeat S4313~S4315 until the current path reaches the target four-dimensional space-time grid unit , output the current path as the avoidance path for the low-priority aircraft.

9. The collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field according to claim 1 is characterized by: S5 builds a dual-queue dynamic scheduling mechanism to guide the aircraft to safe landing through queue separation and polling allocation, including: S51. Build a dual queue architecture: The waiting landing queue (WQ) stores aircraft that have applied for landing but have not yet been assigned a landing path, sorted by priority. The landing queue LQ stores the landing approach aircraft that have been assigned landing paths and are currently landing, sorted by estimated landing time; S52: Scan the landing queue LQ, and release the landing path occupied by the landing approach aircraft from the landing path resource pool after the landing approach aircraft completes the landing action; S53: Select the highest-priority aircraft waiting to land from the head of the waiting-to-land queue WQ and match it with a corresponding landing path from the landing path resource pool based on its performance parameters and path constraints. If no landing path can be matched, initiate local replanning to generate a new landing path. S54: Update the new landing path to the landing path resource pool and notify the aircraft to be landed to load the new landing path; The landing path resource pool stores a pre-generated set of landing paths covering all aircraft positions, and each landing path is marked as "available" or "occupied".

10. A collaborative trajectory planning system for a low-altitude multi-aircraft mixed take-off and landing field, configured to execute the collaborative trajectory planning method for a low-altitude multi-aircraft mixed take-off and landing field according to claim 1, characterized in that: Includes the following components: The airspace 3D gridding and status mapping module divides the airspace into 3D parts based on the Beidou grid code and performs real-time mapping of the airspace status of the 3D grid cells. Grid state analysis and area division module, which divides the three-dimensional grid cells according to the grid state; Geometric track generation rule construction module, which constructs geometric track generation rules to eliminate track intersection risks; The four-dimensional space-time dynamic conflict management module introduces the time dimension on the basis of three-dimensional space, performs four-dimensional space-time conflict detection on all tracks, and resolves conflicts based on the four-dimensional space-time conflict detection results; The dual-queue landing dynamic scheduling and guidance module builds a dual-queue dynamic scheduling mechanism to guide the aircraft to land safely through queue separation and polling allocation; Among them, when resolving conflicts based on the four-dimensional space-time conflict detection results, for low-priority aircraft, an improved quantum heuristic path planning algorithm is used to perform avoidance path planning to guide low-priority aircraft to bypass the conflict area, including: S4311. Model the multi-aircraft conflict avoidance problem and initialize the parameters. S4312, Encode the candidate path into a quantum superposition state : ； in, The candidate path passes through Four-dimensional space-time grid cells, is the four-dimensional space-time grid unit P i The probability amplitude is , N is the number of four-dimensional space-time grid cells that the candidate path passes through; S4313. Calculate the potential field value of each four-dimensional space-time grid cell that the candidate path passes through: ； in, is a four-dimensional space-time grid unit The potential field value of To guide the aircraft to the target four-dimensional space-time grid cell The attractive force of movement, , Represents a four-dimensional space-time grid cell and the target four-dimensional space-time grid cell The distance between is the weight coefficient of attractive potential; is the repulsive potential of the aircraft to avoid obstacle o, , Represents a four-dimensional space-time grid cell The distance to the obstacle o, where O is the set of obstacles; For the aircraft to orbit the jth conflict grid c j The punishment potential, , Represents a four-dimensional space-time grid cell With the conflict grid c j The distance between For the conflict grid c j The penalty potential weight coefficient is related to the conflict grid c j The priorities of medium and high priority aircraft are related. The higher the priority of high priority aircraft, the greater the conflict grid c j The larger the penalty weight coefficient, is the potential field attenuation coefficient, C is the conflict grid set; The potential field value of each four-dimensional space-time grid cell passed by the candidate path can be calculated using the following formula: ； S4314. Adjust the probability amplitude through quantum gate operation to increase the probability of low-potential field four-dimensional space-time grid cells: ； in, is the evolution time step; S4315, Quantum Superposition Perform measurements to obtain the four-dimensional space-time grid cell with the highest probability and add it to the current path; S4316, repeat S4313~S4315 until the current path reaches the target four-dimensional space-time grid unit , output the current path as the avoidance path for the low-priority aircraft.

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