Heterogeneous aircraft intelligent examination and approval decision-making system and method based on dynamic performance envelope

Abstract

The invention discloses an intelligent examination and approval decision-making system and method for a heterogeneous aircraft based on a dynamic performance envelope, belongs to the technical field of heterogeneous aircrafts, and ensures that the aircraft safely and efficiently executes tasks by performing compliance verification, feasibility evaluation and task priority improvement by utilizing dynamically adjusted three-level hierarchical decision-making tree nodes. By constructing a four-dimensional dynamic airspace map superposed with multiple attributes in real time, the system can accurately perform path planning and conflict detection, evaluate aircraft conflict risks and dynamically adjust decision priorities, and when conflicts cannot be resolved, the system can re-plan paths according to aircraft performance envelopes or implement forced avoidance or delimit temporary isolation areas, so that the conflict resolution efficiency is improved. Therefore, task interruption and safety accidents are effectively avoided, and speed and precision bottlenecks in traditional manual examination and approval and path planning are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of heterogeneous aircraft, and in particular to a heterogeneous aircraft intelligent approval decision-making system and method based on a dynamic performance envelope. Background Art

[0002] With the continuous expansion of drone applications in various fields, the traditional aircraft approval system has gradually exposed many problems. The existing system fails to fully consider the significant differences in dynamic performance among different types of aircraft (such as fixed-wing, multi-rotor, eVTOL, etc.). Fixed-wing drones are suitable for high-speed cruising, but have poor flexibility when turning; multi-rotor drones are suitable for vertical take-off and landing and low-speed hovering, but have poor endurance; and eVTOL has the characteristics of both helicopters and fixed-wing aircraft, but its performance is also different from that of traditional aircraft. These differences have not been fully optimized by the system, resulting in approval results that may be overly conservative, limiting the performance of the aircraft and even failing to meet mission requirements, seriously affecting flight efficiency and safety.

[0003] The existing technology has the following shortcomings:

[0004] In complex flight environments, the problem of aircraft path conflicts is particularly prominent. Existing manually-led approval methods, due to limitations in processing speed and information acquisition, struggle to accurately coordinate the flight paths of multiple aircraft in real time. This is especially true when multiple drones are collaborating on a mission. Path conflicts can prevent successful mission completion and even lead to safety incidents. This situation is particularly severe in highly dynamic and complex airspace environments. Summary of the Invention

[0005] The purpose of the present invention is to provide a heterogeneous aircraft intelligent approval decision system and method based on dynamic performance envelope to address the shortcomings of the background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for intelligent approval decision-making of heterogeneous aircraft based on dynamic performance envelope, comprising:

[0007] Create a heterogeneous aircraft performance database, map different aircraft models and performance parameters, and formulate a dynamic data update strategy;

[0008] Based on real-time aircraft status data, an aircraft performance degradation model is established, and the performance envelope boundary is dynamically adjusted through the degradation model;

[0009] A three-level hierarchical decision tree is set up, including basic compliance verification, dynamic feasibility assessment, and mission priority improvement, to ensure that aircraft perform missions within compliance and safety ranges;

[0010] By fusing multi-source data, a four-dimensional dynamic airspace map with multiple attributes is constructed in real time for path planning and conflict detection.

[0011] Based on the aircraft's predicted trajectory, the space-time grid unit is calculated to assess the aircraft's collision risk, and the decision tree node priority is dynamically adjusted based on the assessment results.

[0012] During the conflict resolution process, the path is replanned based on the aircraft's performance envelope, and when the conflict cannot be resolved, forced avoidance is implemented or a temporary isolation zone is established.

[0013] Preferably, the performance parameters include dynamic performance parameters, power system parameters, environmental adaptability parameters and mission adaptability parameters.

[0014] Preferably, the aircraft performance is set to decay linearly with the change of time, environmental factors and aircraft state. The specific linear decay model is expressed as: P adjusted =P max ×(1-α1·t-α2·E); where: P adjusted is the adjusted aircraft performance; P max is the maximum performance of the aircraft; t is the aircraft usage time; E is the impact of environmental factors; α1 and α2 are constants of aircraft performance attenuation.

[0015] Preferably, based on the performance decay model of the aircraft, the model adopts a linear decay method to adjust the performance envelope boundary of the aircraft according to time and environmental changes, and updates its flight capability in real time according to the actual state of the aircraft.

[0016] Preferably, setting a three-level hierarchical decision tree node includes:

[0017] At the first level, basic compliance verification of the aircraft is conducted to determine whether the aircraft meets flight permit, qualification and airspace management requirements;

[0018] In the second-level node, dynamic feasibility assessment is performed to evaluate the flight path based on the real-time performance of the aircraft and environmental data to determine whether there are conflicts or flight restrictions;

[0019] In the third-level node, the urgency and priority of the task are evaluated, the processing priority of high-priority tasks is automatically increased, and the flight path is replanned according to the task requirements.

[0020] Preferably, the real-time construction of a four-dimensional dynamic airspace map through multi-source data fusion includes:

[0021] Collect aircraft status data, weather data, and airspace management data in real time;

[0022] Synchronize all data to a unified timestamp and perform spatial coordinate conversion to enable data fusion and construct a four-dimensional dynamic airspace map;

[0023] The airspace is divided into grids according to time and space coordinates, and aircraft status, airspace occupancy and meteorological parameter information are stored for each grid cell, and the airspace status is updated in real time.

[0024] Preferably, the space-time grid cells are calculated based on the predicted trajectory of the aircraft to assess the collision risk:

[0025] Based on the aircraft's initial position, speed, heading, and flight time, the aircraft's future trajectory is predicted and divided into multiple time periods.

[0026] In each time period, the space-time grid cell occupied by the aircraft is calculated based on its predicted trajectory and compared with the trajectory of other aircraft to determine whether there is a potential conflict;

[0027] Based on the relative steering capabilities and dynamic obstacle avoidance coefficients of the aircraft, the collision risk between aircraft is comprehensively assessed and the collision risk index is calculated;

[0028] If the conflict risk index exceeds the set threshold, it triggers dynamic adjustment of the decision tree node priority to enhance the execution rights of high-priority tasks.

[0029] Preferably, the relative steering capability calculation formula is: Among them, the turning radius and maximum speed are the dynamic parameters of the aircraft; the calculation formula of the dynamic obstacle avoidance coefficient is: Where AX is the dynamic collision avoidance coefficient, V avoid V is the maximum speed at which the aircraft can safely avoid obstacles. relative is the relative speed to other aircraft.

[0030] Preferably, during the conflict resolution process, the path is replanned based on the aircraft's performance envelope, and when the conflict cannot be resolved, forced avoidance is implemented or a temporary isolation zone is established:

[0031] After detecting an aircraft path conflict, the flight path is optimized according to the aircraft's dynamic performance envelope, and the flight altitude, speed or heading are adjusted to avoid the conflict;

[0032] If the path optimization cannot resolve the conflict, multiple alternative paths are generated and the optimal path is selected to replan the aircraft trajectory;

[0033] If the conflict cannot be resolved, a mandatory avoidance instruction will be issued based on the real-time airspace conditions, requiring the aircraft to perform vertical or horizontal avoidance maneuvers;

[0034] When a conflict cannot be avoided, a temporary isolation zone will be established to ensure the safety of the aircraft.

[0035] The present invention also provides a heterogeneous aircraft intelligent approval decision-making system based on dynamic performance envelope, including an aircraft performance management module, an aircraft status monitoring module, a mission management module, an airspace management module, a risk assessment module, and a conflict resolution module;

[0036] Aircraft performance management module: Create a heterogeneous aircraft performance database, map different aircraft models and performance parameters, and formulate a dynamic data update strategy;

[0037] Aircraft status monitoring module: Based on real-time aircraft status data, an aircraft performance degradation model is established and the performance envelope boundary is dynamically adjusted through the degradation model;

[0038] Mission Management Module: Set up a three-level hierarchical decision tree node, including basic compliance verification, dynamic feasibility assessment and mission priority improvement, to ensure that the aircraft performs the mission within the compliance and safety range;

[0039] Airspace management module: Through multi-source data fusion, a four-dimensional dynamic airspace map with multiple attributes is constructed in real time for path planning and conflict detection;

[0040] Risk Assessment Module: Calculates space-time grid cells based on the aircraft's predicted trajectory, assesses the aircraft's collision risk, and dynamically adjusts the decision tree node priority based on the assessment results;

[0041] Conflict resolution module: During the conflict resolution process, the path is replanned based on the aircraft's performance envelope, and when the conflict cannot be resolved, forced avoidance is implemented or a temporary isolation zone is established.

[0042] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0043] 1. This invention creates and dynamically updates a heterogeneous aircraft performance database, monitors aircraft status in real time, and integrates multi-source data to construct a four-dimensional dynamic airspace map. The system accurately performs path planning and conflict detection, assesses conflict risks between aircraft in real time, and intelligently adjusts decision tree node priorities. During conflict resolution, the system optimizes paths based on aircraft performance envelopes, ensuring safe and efficient mission execution in dynamic environments. This avoids the limitations of manual approval and information acquisition, reducing the probability of safety incidents.

[0044] 2. By establishing a three-level hierarchical decision tree node, combined with task priority management and aircraft dynamic performance adjustment, this system ensures that high-priority tasks are prioritized in emergency situations and automatically optimizes the allocation of airspace resources. Furthermore, by combining aircraft predicted trajectories with conflict risk assessment of space-time grid cells, this system further improves the efficiency of multi-aircraft collaborative missions. In particular, when multiple aircraft collaborate on complex missions, this system enables intelligent scheduling and path planning to minimize conflict and ensure the safe and timely completion of flight missions. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0046] Figure 1 This is a mind map of the method of the present invention.

[0047] Figure 2 This is a mind map of the system modules of the present invention. DETAILED DESCRIPTION

[0048] To make the objectives, 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 of 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. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0049] Example 1, please refer to Figure 1 As shown, the intelligent approval decision-making method for heterogeneous aircraft based on dynamic performance envelopes described in this embodiment includes:

[0050] Create a heterogeneous aircraft performance database, map different aircraft models and performance parameters, and formulate a dynamic data update strategy;

[0051] Based on real-time aircraft status data, an aircraft performance degradation model is established, and the performance envelope boundary is dynamically adjusted through the degradation model;

[0052] A three-level hierarchical decision tree is set up, including basic compliance verification, dynamic feasibility assessment, and mission priority improvement, to ensure that aircraft perform missions within compliance and safety ranges;

[0053] By fusing multi-source data, a four-dimensional dynamic airspace map with multiple attributes is constructed in real time for path planning and conflict detection.

[0054] Based on the aircraft's predicted trajectory, the space-time grid unit is calculated to assess the aircraft's collision risk, and the decision tree node priority is dynamically adjusted based on the assessment results.

[0055] During the conflict resolution process, the path is replanned based on the aircraft's performance envelope, and when the conflict cannot be resolved, forced avoidance is implemented or a temporary isolation zone is established.

[0056] The goal of creating a heterogeneous aircraft performance database is to collect and store detailed performance data of multiple types of aircraft, ensuring that the approval decision system can make accurate decisions based on the characteristics of specific aircraft, environmental conditions and mission requirements.

[0057] First, aircraft are categorized by type, which generally includes:

[0058] Fixed-wing aircraft: suitable for long-duration, high-speed cruising missions, such as aerial surveys, remote sensing mapping, etc.

[0059] Multirotor aircraft: Suitable for short-distance, low-altitude flight, with vertical take-off and landing capabilities, suitable for scenarios such as express delivery and low-altitude surveillance.

[0060] eVTOL (electric vertical take-off and landing aircraft): It combines the advantages of fixed-wing and helicopters and is suitable for urban air travel, emergency rescue and other tasks.

[0061] Each aircraft type is further subdivided into specific models. For example, fixed-wing drones can be further classified based on flight distance, cruising speed, take-off method, and other characteristics to ensure the accuracy of the database.

[0062] For each type of aircraft, the following performance parameters are collected based on actual application requirements and design specifications:

[0063] Dynamic performance parameters: including the aircraft's maximum flight speed, maximum flight altitude, maximum range, minimum turning radius, climb rate, glide speed, etc.

[0064] Power system parameters: such as engine power, battery life, battery charge and discharge capacity, power-to-weight ratio, etc.

[0065] Environmental adaptability parameters: For example, the aircraft's ability to adapt to environmental factors such as wind speed, temperature, and air pressure, its anti-interference ability, and whether it can fly normally in severe weather.

[0066] Mission adaptability parameters: such as the aircraft's payload, mission execution time, operational flexibility, etc. in different mission scenarios.

[0067] Record the technical specifications of the aircraft (such as weight, size, load capacity, flight mode, etc.) in detail, clarify its operating limitations and optimal application environment, and ensure that the system can generate mission plans that meet the characteristics of different types of aircraft.

[0068] During actual operation, aircraft performance is affected by factors such as the environment, operating conditions, and aging. To ensure the timeliness of data in the database, a real-time monitoring mechanism is required. Aircraft continuously transmit flight status data to the system via sensors such as GPS, accelerometers, and barometers. This data includes the aircraft's real-time position, speed, altitude, battery status, and powertrain status.

[0069] Based on these real-time data, the performance envelope of the aircraft can be dynamically adjusted, that is, its maximum flight capability and safe operating range can be adjusted according to real-time environmental factors and the actual operating conditions of the aircraft.

[0070] For each aircraft, historical operational data (such as past mission performance, fault records, and maintenance history) is collected and machine learning and other methods are used to continuously optimize the aircraft performance model. For example, historical flight data can be used to analyze the changes in an aircraft's flight capabilities under different weather conditions and predict its performance under similar conditions, providing a reference for future mission decisions.

[0071] The frequency of updating data is determined by the intensity of aircraft usage and mission requirements. Aircraft that are used intensively or have malfunctions may require more frequent updates.

[0072] The system dynamically assesses the aircraft's adaptability based on its real-time status and external environment. For example, in windy weather, the aircraft's flight stability may decrease. In this case, the system will automatically adjust the aircraft's performance data (such as maximum flight speed and allowable flight altitude) to dynamically match the current mission requirements.

[0073] When the aircraft encounters performance degradation during mission execution, the system will adjust the aircraft's performance envelope boundaries through real-time data updates to prevent the aircraft's actual performance from exceeding its safe operating range.

[0074] In addition to the aircraft's own status data, it also incorporates external data from multiple sources (such as weather forecasts, airspace usage, and air traffic data). This data provides real-time updates to the aircraft's operating conditions, and the system adjusts the aircraft's dynamic performance based on this integrated data. This dynamic update mechanism ensures that the aircraft's performance data in the database always reflects its current true performance, allowing for timely adjustments to aircraft usage strategies based on changing environmental conditions.

[0075] During database updates, ensuring data integrity and security is crucial. We utilize blockchain technology and encrypted transmission to ensure the security of aircraft performance data during collection, storage, and transmission, preventing data tampering or loss and ensuring the reliability of system decisions.

[0076] By building and dynamically updating a heterogeneous aircraft performance database, the system comprehensively analyzes the performance, environmental adaptability, and mission requirements of different aircraft, intelligently planning optimal routes, mission priorities, and flight strategies for each aircraft, ensuring the accuracy and safety of approval decisions. Furthermore, the dynamic update strategy ensures that the aircraft database remains accurate as technology evolves and the environment changes, improving the efficiency and safety of aircraft mission execution.

[0077] The aircraft performance degradation model is designed to monitor the real-time status data of the aircraft and dynamically adjust its performance envelope boundaries according to the aircraft's current health status, environmental factors and usage conditions, thereby ensuring that the aircraft flies within a safe range and maximizes its mission execution capability.

[0078] In order to simplify and efficiently analyze, a linear attenuation model is selected, assuming that the aircraft performance decays linearly with the changes of time, environmental factors (such as wind speed, temperature) and aircraft status (such as battery power, engine temperature, etc.). The specific linear attenuation model can be expressed as: P adjusted =P max ×(1-α1·t-α2·E); where: P adjusted is the adjusted aircraft performance; P max is the maximum performance of the aircraft (the upper limit of performance when not attenuated); t is the aircraft usage time (or flight time); E is the influence of environmental factors (such as wind speed, temperature, etc.); α1 and α2 are constants of aircraft performance attenuation (adjusted according to the aircraft type and environmental factors).

[0079] The steps for dynamically adjusting the aircraft performance degradation model include:

[0080] Step 1: Collect aircraft status data in real time:

[0081] Aircraft status data: including aircraft flight time, flight altitude, speed, battery level, engine temperature, load status, etc.

[0082] Environmental data: such as current weather conditions (wind speed, temperature, humidity, etc.) and changes in flight airspace (airspace congestion, no-fly zones, etc.).

[0083] These data are monitored in real time through the aircraft's own sensors and transmitted to the system.

[0084] Step 2: Based on the collected real-time data, the system calculates the degree of attenuation of each influencing factor on the aircraft performance through the preset attenuation coefficient model. For example:

[0085] Usage Time (t): Based on the aircraft's accumulated flight time or current flight time, the system calculates the attenuation effect of this factor on the aircraft's maximum performance.

[0086] Environmental factors (E): For example, strong winds and low temperatures can cause aircraft performance to degrade. In this step, the system uses historical data and real-time weather forecasts to calculate the impact of environmental factors and further determine the attenuation coefficient.

[0087] The attenuation coefficients (α1, α2) are dynamically adjusted based on the aircraft type and usage conditions.

[0088] Step 3: Use the attenuation coefficient and linear attenuation formula to adjust the aircraft's performance envelope. The boundaries of the performance envelope change dynamically based on the aircraft's actual state and external environment data.

[0089] For example, under strong wind conditions, the maximum flight speed and flight altitude of the aircraft will be limited, and the boundaries of the performance envelope will be lowered accordingly; under normal environmental conditions, the aircraft's performance envelope will return to its original value.

[0090] The adjusted performance envelope represents the maximum safe flight capability of the aircraft in its current state. Any operation beyond this boundary will be considered beyond the safe range and require avoidance.

[0091] Step 4: Whenever the aircraft's status data or environmental conditions change, the system recalculates the attenuation coefficient in real time and updates the aircraft's performance envelope based on the new performance adjustment formula. The system dynamically feeds back the adjusted performance data to ensure the aircraft remains within safe performance limits during all phases (takeoff, cruise, landing, etc.).

[0092] Step 5: Based on the updated performance envelope, the flight plan or mission route will be replanned. If the aircraft's performance is significantly affected, the system will automatically adjust the flight path to avoid exceeding the aircraft's capabilities.

[0093] For example, in high wind conditions, the aircraft may need to choose a lower flight altitude. The system will adjust the flight path according to the new envelope boundary to ensure the safe flight of the aircraft.

[0094] Step 6: If the aircraft's performance degrades significantly (e.g., battery life is critically low, engine overheating, etc.), the system will issue a real-time warning and may require the aircraft to perform an emergency evasive maneuver or change its mission path. If normal flight performance cannot be restored, the system will issue a forced landing command or initiate other emergency measures to prevent the aircraft from entering a dangerous state.

[0095] In this invention, the linear decay model described above allows the aircraft's performance envelope to be dynamically adjusted based on its real-time state and environmental factors, ensuring that the aircraft remains within a safe operating range during actual flight. This method, through real-time monitoring and calculation, provides accurate dynamic performance predictions for the aircraft, optimizing flight decisions and enhancing flight safety.

[0096] In the intelligent aircraft approval decision-making system, the decision tree is a key mechanism for ensuring that aircraft can perform missions within compliance and safety. The three-level hierarchical decision tree nodes primarily evaluate various aircraft parameters in a phased manner, ultimately determining whether to approve the flight mission.

[0097] First-level node: basic compliance verification:

[0098] A basic compliance check verifies that an aircraft complies with all basic laws, regulations, airspace requirements, and flight qualification requirements before it can begin its mission. This step ensures that aircraft operations comply with legal regulations and airspace management regulations.

[0099] Aircraft compliance: Determine whether the aircraft complies with registration, inspection and certification requirements, whether it holds a valid flight permit, and whether it meets aircraft technical requirements (such as maximum take-off weight, flight performance, etc.).

[0100] Pilot qualifications: Verify whether the pilot has the necessary flight license and related qualifications, whether he has received sufficient training and meets the relevant operational requirements.

[0101] Airspace compliance: Determines whether the aircraft's planned route complies with current airspace management regulations to ensure the flight does not enter no-fly zones, restricted airspace, or other restricted areas.

[0102] Insurance and Legal Qualifications: Verify that the aircraft has the necessary flight insurance to ensure it meets the compensation liability requirements. In addition, verify that the aircraft operator complies with relevant legal requirements (such as airworthiness and maintenance specifications).

[0103] Compliance: If both the aircraft and the pilot meet all relevant requirements, proceed to the next step of the assessment (dynamic feasibility assessment).

[0104] Non-Compliance: If any compliance issues are found (such as the aircraft does not have valid certification, the pilot does not have a valid license, etc.), the mission will be rejected and the relevant information will be fed back to the operator for adjustment or correction.

[0105] Second level node: dynamic feasibility assessment:

[0106] After passing basic compliance, the dynamic feasibility assessment further evaluates whether the flight mission is feasible under current environmental conditions. This step focuses on the real-time performance of the aircraft and environmental changes to ensure the safety and feasibility of the flight mission.

[0107] Real-time performance evaluation of aircraft:

[0108] Real-time Performance Envelope Adjustment: Dynamically adjusts the aircraft's performance envelope based on its real-time status (e.g., battery charge, engine temperature, load, etc.). Aircraft parameters like maximum altitude, speed, and range are dynamically updated based on the aircraft's current health, environmental conditions (e.g., temperature, wind speed), and flight duration to ensure the aircraft remains within its safe performance range.

[0109] Environmental Adaptability: This step assesses whether the current flight's environmental conditions, such as wind speed, weather changes, and airspace congestion, will affect the aircraft's flight capabilities. For example, strong winds may affect aircraft stability, while cold temperatures may degrade battery performance. This step assesses the aircraft's ability to cope with these environmental factors and makes appropriate performance adjustments.

[0110] Feasibility assessment of flight paths:

[0111] Airspace Conflict Detection: Based on data from multiple sources (such as radar, ADS-B data, and airspace management data), the system detects potential conflicts between the aircraft's projected route and other aircraft, fixed obstacles, and no-fly zones. If a potential conflict is detected, the system will consider whether to replan the flight path or adjust the flight altitude.

[0112] Matching mission requirements with resources: Evaluate whether the mission requirements (such as flight altitude, duration, mission priority, etc.) match the actual capabilities of the aircraft, and consider whether the aircraft has sufficient power, endurance, and resources to complete the mission.

[0113] Feasible: If the aircraft can safely perform the mission under the current environmental conditions and the mission path is feasible, the mission enters the next decision level (task priority is increased).

[0114] Not feasible: If the aircraft cannot cope with the current environment or the mission requirements are beyond the aircraft's capabilities, the system will recommend modifying the flight plan or selecting another aircraft and re-evaluating.

[0115] Third-level node: Task priority improvement:

[0116] The mission priority boost node dynamically adjusts the priority of flight missions based on factors such as mission urgency and importance. For high-priority missions, the system will proactively adjust the flight path to ensure that the mission can be completed on time.

[0117] Mission urgency assessment: The system assesses the urgency of missions based on their nature (e.g., disaster relief missions, emergency medical transport, etc.). High-priority missions will be assigned higher priority to ensure they are handled first given limited airspace resources.

[0118] Task Priority Adjustment: For high-priority tasks, the system will automatically increase their priority and reroute them to avoid conflicts with other lower-priority tasks. The system may proactively adjust the flight paths of lower-priority tasks or suspend certain tasks to ensure the smooth completion of higher-priority tasks. Lower-priority tasks will be postponed or adjusted as appropriate to ensure they do not interfere with urgent tasks.

[0119] Task importance and resource allocation: The system also evaluates the resources required for the task (such as airspace occupancy, battery power, flight time, etc.) and ensures that resources are allocated first to high-priority tasks.

[0120] Mission priority has been successfully increased: For urgent missions, the system will automatically adjust the flight path and allocate priority airspace resources to ensure that the mission can be executed on time.

[0121] Mission priority adjustment failure: If the mission cannot be completed on time or the system fails to adjust the path smoothly, the system will issue a warning and remind the pilot to make corresponding adjustments.

[0122] By setting up a three-level hierarchical decision tree, the system ensures that the aircraft mission decision-making process meets multiple requirements, including compliance requirements, feasibility analysis, and emergency mission priorities. This hierarchical decision-making approach not only enhances the intelligence of the aircraft approval process but also effectively addresses dynamically changing environmental conditions, mission requirements, and priority conflicts, ensuring the safe and efficient execution of aircraft missions.

[0123] Building a four-dimensional dynamic airspace map based on multi-source data fusion is a key step in achieving intelligent aircraft approval decisions. By integrating multiple data sources (such as weather information, airspace occupancy, aircraft status, and real-time traffic flow) in real time, a dynamic map is generated that reflects the current airspace and aircraft status, as well as future changes. This map not only provides a foundation for aircraft path planning but also enables conflict detection and optimization during real-time flight.

[0124] A 4D dynamic airspace map is a data model that takes into account spatial location (X, Y, Z) and time (T). This 4D map combines the following important factors:

[0125] Spatial coordinates (X, Y, Z): Indicates the physical location in the airspace, including the lateral (X) and longitudinal (Y) coordinates, as well as the altitude (Z) of the aircraft.

[0126] Time (T): provides a time dimension for airspace changes, reflecting the status and resource allocation of the airspace at different time points.

[0127] Dynamic attributes: including aircraft status (such as speed, track, aircraft type, etc.), meteorological data (such as wind speed, temperature, air pressure, visibility), airspace occupancy (such as the location of other aircraft, no-fly zones, airspace restrictions, etc.).

[0128] With this information, the four-dimensional dynamic airspace map can provide aircraft with comprehensive, real-time airspace information for path planning and conflict detection.

[0129] In order to ensure that the 4D dynamic airspace map can accurately reflect the real-time status of the airspace, multi-source data fusion is necessary. The following are common data sources and their functions:

[0130] Aircraft status data: Aircraft's real-time position, speed, altitude, track, flight mode (such as automatic, manual, preset route, etc.). Aircraft health status (such as battery level, engine temperature, sensor status, etc.).

[0131] Weather data: Wind speed and direction: Affect the aircraft's flight stability and speed, especially at high altitudes. Air pressure and temperature: Affect the aircraft's lift, altitude, and control accuracy. Visibility and precipitation: Affect the aircraft's visual recognition capabilities, especially at low altitudes, affecting obstacle avoidance and navigation.

[0132] Airspace management data: Airspace division and no-fly zone information: Real-time updated airspace division, restricted areas and temporary no-fly zone information to ensure that aircraft avoid areas where flight is not allowed.

[0133] Airspace occupancy: the location, flight trajectory, and estimated arrival time of other aircraft.

[0134] Ground monitoring data: ADS-B (Automatic Dependent Surveillance-Broadcast) data: provides real-time position information, speed, altitude, etc. of the aircraft.

[0135] Radar data: Aircraft position, speed, and heading provided by ground-based radar complement other data sources, especially in blind spots or areas with weak signals.

[0136] The core task of building a real-time 4D dynamic airspace map is to synchronize the time and spatially fuse the above multi-source data. The specific steps are as follows:

[0137] Collect data in real time from various data sources, such as aircraft sensors, ground stations, weather stations, and air traffic control systems.

[0138] Clean and preprocess collected multi-source data to ensure accuracy and consistency. For example, weather data may require real-time prediction and correction, and aircraft position data may require filtering to remove noise.

[0139] All data is synchronized with real-time timestamps. Since aircraft are constantly moving, the temporal changes in airspace information are very important. Therefore, it is necessary to accurately record the timestamps of each data source in order to generate dynamic maps that are consistent with the actual flight time.

[0140] Perform coordinate transformation and fusion on spatial data to ensure that all data are unified into the same coordinate system.

[0141] The entire airspace is divided into multiple spatial grid cells, each containing aircraft information, weather data, and airspace occupancy information within the area. The grid can be created in three-dimensional space (X, Y, Z), and each grid cell is dynamically updated based on time (T).

[0142] The attributes recorded in each grid cell include information such as the presence of aircraft, airspace usage, and weather changes, forming a dynamic four-dimensional spatial model.

[0143] During each time period, an airspace map is generated based on information from various data sources. For example, meteorological data provides information about wind speed and temperature, which can affect an aircraft's flight capabilities; airspace occupancy data determines whether an aircraft can safely fly; and aircraft status data determines flight paths.

[0144] The fused four-dimensional dynamic airspace map provides instant decision support for each aircraft, ensuring that the aircraft can fly within a safe range and reflect airspace changes in real time.

[0145] Based on the real-time updated four-dimensional dynamic airspace map, the aircraft can perform accurate path planning and conflict detection.

[0146] The aircraft generates a path plan based on its current status (such as speed, altitude, and remaining battery power) and mission requirements (such as the shortest time to reach the destination and the minimum energy consumption). The system optimizes the path in real time based on a dynamic airspace map to avoid conflicts with other aircraft and adjusts flight altitude and speed based on weather and other environmental conditions.

[0147] The system compares the predicted trajectory of the aircraft with the trajectory of other aircraft, calculates the space-time grid cells it occupies, and evaluates the probability of conflict.

[0148] Based on this data, the system can identify potential path conflicts in real time, predict the time and place where conflicts may occur in advance, and generate conflict level reports.

[0149] If there is a conflict, the system will re-plan the trajectory based on the aircraft's performance envelope constraints to ensure that the aircraft can avoid the conflict area, or issue emergency avoidance instructions.

[0150] This invention uses multi-source data fusion to construct a four-dimensional dynamic airspace map in real time, providing aircraft with a precise airspace information framework. This framework considers spatial, temporal, environmental factors, and aircraft status at each point in time to generate the most optimal flight path for the aircraft, while also performing real-time conflict detection. This not only enhances aircraft autonomy and safety, but also significantly optimizes mission execution efficiency.

[0151] In order to achieve conflict detection and dynamic decision support between aircraft, combined with the aircraft's predicted trajectory, spatiotemporal grid cells, and the calculation of specific parameters, the following steps can be used to complete the assessment of conflict risk and the dynamic adjustment of decision tree node priorities.

[0152] The predicted trajectory of an aircraft is to predict the movement path of the aircraft in the future based on the aircraft's initial position, speed, flight direction, flight time and other information. The predicted trajectory of the aircraft will be divided into multiple time periods, each time period corresponding to a spatial position (X, Y, Z) and time point (T). The calculation method of the trajectory prediction is: trajectory prediction = f (current position, speed, heading, time); in order to accurately manage the airspace and detect conflicts, the airspace is divided into multiple space-time grid cells. Each grid cell defines a spatial area within a time period, which is used to record the status of the aircraft and the risk of conflict in the area. The size and accuracy of each grid cell are adjusted according to the flight speed of the aircraft, environmental factors and mission requirements.

[0153] To ensure that the specific factors of different aircraft are taken into account when assessing the conflict risk, the relative steering capabilities and dynamic collision avoidance coefficients of the aircraft can be obtained for analysis to assess the conflict risk.

[0154] Relative turning capability describes the maximum angle an aircraft can turn within a specified timeframe and is related to its maneuverability. This parameter can be particularly effective in assessing whether an aircraft's maneuverability is sufficient to avoid collisions when paths intersect. Certain aircraft with poor maneuverability (such as large fixed-wing drones) have lower turning capabilities and may pose a higher risk of collision. The calculation formula is: Among them, the turning radius and maximum speed are the dynamic parameters of the aircraft.

[0155] The dynamic collision avoidance factor takes into account the aircraft's real-time flight status and environmental factors (such as wind speed, temperature, and air pressure) to assess whether the aircraft can make timely adjustments to avoid collisions. This parameter takes into account the aircraft's reaction speed when encountering obstacles and its practical obstacle avoidance capabilities. Calculation formula: Where AX is the dynamic collision avoidance coefficient, V avoid V is the maximum speed at which the aircraft can safely avoid obstacles. relative is the relative speed to other aircraft.

[0156] The relative steering capability and dynamic collision avoidance coefficient of the aircraft are combined with the predicted trajectory of other aircraft, airspace occupancy and environmental factors to form a comprehensive assessment model to calculate the collision risk. The specific calculation is as follows:

[0157] Calculate the relative speed V between the aircraft and other aircraft based on the aircraft's predicted trajectory relative This reflects the relative speed of the aircraft.

[0158] Calculate the space-time distance between aircraft to assess whether they will enter the same space-time grid cell. If the space-time distance between the two is less than a preset safety threshold, there may be a conflict.

[0159] Based on the aircraft's relative steering capability and dynamic collision avoidance coefficient, the system assesses whether it can adjust its trajectory to avoid collisions within the expected time. Specifically, when the aircraft's relative steering capability is low or the dynamic collision avoidance coefficient is small (i.e., the aircraft has poor obstacle avoidance capabilities), the risk of collision is higher.

[0160] Based on the above parameters, the conflict risk index CRI between aircraft is calculated using the following formula: Where qy is the relative steering capability. If the CRI value is greater than the set conflict risk threshold, it is considered that there is a potential conflict risk between the two aircraft.

[0161] If the calculated conflict risk index (CRI) exceeds a set threshold (e.g., 0.8), a conflict risk is considered to exist; otherwise, the aircraft can continue to fly along its current trajectory.

[0162] Based on the evaluation results, the system will dynamically adjust the priority nodes of the decision tree to adapt to the needs of different flight missions.

[0163] Specific adjustment steps:

[0164] Low conflict risk (CRI < 0.8): If the conflict risk is low, the system will maintain normal priority and continue to execute regular mission planning.

[0165] The priority of the corresponding decision tree node remains the basic priority (such as ordinary tasks).

[0166] High Conflict Risk (CRI ≥ 0.8): If the conflict risk is high, the system will increase the priority of the task. For example, if the task is high priority (such as an emergency rescue mission), the system will immediately adjust the flight path for the task to avoid conflict with lower-priority tasks. The system may assign a higher dynamic priority to the task at the first-level decision node.

[0167] For low-priority tasks, the system will proactively adjust their paths or suspend task execution to leave more space and resources for high-priority tasks.

[0168] Emergency avoidance: If the assessed conflict risk is irreconcilable (for example, the trajectories of the two aircraft cannot be adjusted to avoid conflict), the system will issue an emergency avoidance command, requiring the aircraft to immediately adjust their trajectory or make a forced landing.

[0169] In this invention, the collision risk between aircraft is assessed by comprehensively calculating the relative steering capabilities of the aircraft, the dynamic collision avoidance coefficient, and the temporal and spatial distance between the aircraft. Based on this assessment, the system dynamically adjusts the priority of the decision tree nodes, intelligently handling conflicts and ensuring the safety and efficiency of flight missions. When the conflict risk is high, the smooth execution of high-priority tasks is prioritized, and the paths of other aircraft are adjusted to avoid conflicts.

[0170] In airspace management and path planning for aircraft, conflict resolution is a critical step in ensuring flight safety. When the system detects a potential conflict between two or more aircraft, it must resolve the conflict based on the aircraft's performance envelope and real-time status information to ensure the aircraft can continue to perform their mission while avoiding the conflict. The following is a detailed conflict resolution process and corresponding steps:

[0171] The goal of conflict resolution is to ensure that aircraft can take reasonable measures within the collision risk area to avoid actual conflict, while ensuring the safety and efficiency of the aircraft's mission. When performing conflict resolution, the following principles must be followed:

[0172] Comply with the dynamic performance envelope limits of the aircraft to ensure that the aircraft flies within the safe performance range.

[0173] Minimize the impact on the timeliness of flight missions, especially in emergency situations.

[0174] Ensure that the aircraft can avoid conflicts as autonomously as possible without excessive human intervention.

[0175] An aircraft's performance envelope is the maximum range of performance within which it can safely fly under specific environmental conditions. This includes parameters such as maximum speed, maximum rate of climb, and minimum turn radius. The boundaries of this performance envelope are dynamically adjusted based on the aircraft's real-time status (e.g., battery charge, propulsion system status) and environmental factors (e.g., wind speed and air pressure).

[0176] When the system detects a potential conflict, it will re-plan the flight path based on the aircraft's performance envelope. The following are the key steps in re-planning the path:

[0177] Path Optimization: The system uses the dynamic aircraft performance envelope to adjust the aircraft's trajectory. It adjusts parameters such as altitude, speed, and heading to avoid crossing paths with other aircraft. For example, if an aircraft has a low rate of climb, it might choose a lower altitude to avoid conflict with an aircraft at a higher altitude.

[0178] Alternative Path Generation: If the aircraft's current path cannot avoid collisions, the system calculates multiple alternative paths and selects the optimal one. This path must not only avoid other aircraft but also meet the aircraft's dynamic performance envelope requirements (such as maximum flight speed and minimum turning radius).

[0179] Path planning model: Path planning is usually based on algorithms such as A* or Dijkstra, combined with the performance envelope of the aircraft, to dynamically adjust the aircraft's trajectory to ensure that the aircraft can complete the mission within a safe time and space range.

[0180] Once the aircraft's path is replanned, the system will immediately send the new track information through the aircraft's navigation system. The aircraft will fly along the new path to avoid conflicts with other aircraft.

[0181] After the system attempts to replan the path and calculates multiple alternative paths, if the conflict cannot be effectively resolved (for example, the aircraft's performance envelope cannot support the avoidance maneuver), emergency avoidance measures must be taken. The forced avoidance operation process includes:

[0182] Automatic Avoidance Commands: The system automatically sends mandatory avoidance commands to the aircraft, requiring it to immediately adjust its flight path, typically by changing altitude or heading. These commands are calculated based on the aircraft's performance envelope and the current flight environment's constraints to ensure the aircraft safely avoids the conflict zone.

[0183] Avoidance Maneuver Type: Depending on the aircraft's current state and the conflict type, the avoidance can be horizontal (changing heading), vertical (changing altitude), or combined (changing both heading and altitude).

[0184] Emergency Response Monitoring: When the aircraft receives an avoidance command, the system monitors its execution in real time. If any anomalies occur during the avoidance process (such as the aircraft not adjusting its path as expected), the system will reassess the current conflict and issue a new avoidance command.

[0185] If the conflict cannot be resolved through path planning and forced avoidance, the system will demarcate a temporary isolation zone based on the real-time airspace conditions. The purpose of setting up a temporary isolation zone is to:

[0186] Ensure aircraft safety: By establishing temporary isolation zones, the system can ensure that other aircraft cannot enter the conflict area, avoiding possible collisions.

[0187] Minimize the risk of conflict: Through the exclusion zone, the system prevents all aircraft from flying within the time and space area, thereby eliminating the possibility of conflict, especially in complex or urgent flight missions.

[0188] Dynamically adjust the isolation zone: The temporary isolation zone is not fixed. The system will adjust the location, shape, and size of the isolation zone in real time based on the dynamic position of the aircraft and changes in the flight mission to ensure that the aircraft can safely pass through or avoid it.

[0189] The demarcation of temporary isolation zones not only needs to take into account the current conflict situation, but also needs to be dynamically adjusted based on the aircraft's performance envelope, environmental changes, and the flight paths of other aircraft. The following are the steps for dynamically adjusting isolation zones:

[0190] Conflict Zone Monitoring: The system monitors the position of aircraft and conflict zones in real time, assessing the severity of the conflict and its scope of impact.

[0191] Airspace Adjustment: When the system finds that the aircraft's avoidance path cannot resolve the conflict, it dynamically creates a new isolation zone and adjusts the size and shape of the isolation zone based on the aircraft's track and flight environment.

[0192] Collaborative decision-making: When multiple aircraft operate in coordination, the system will share conflict information with the navigation systems of other aircraft to avoid unnecessary waste of resources and coordination conflicts, ensuring safe flight.

[0193] In this invention, conflict resolution is a core task in aircraft path planning and airspace management. When conflicts cannot be completely avoided, rerouting based on the aircraft's performance envelope and implementing forced avoidance or temporary isolation zones when conflicts cannot be resolved effectively improves aircraft safety and reduces the likelihood of accidents. Key to this process is real-time monitoring of aircraft status, dynamic adjustment of path planning, and tailored emergency response to ensure the safe and successful completion of flight missions.

[0194] Example 2, please refer to Figure 2 As shown, the heterogeneous aircraft intelligent approval decision system based on the dynamic performance envelope described in this embodiment includes an aircraft performance management module, an aircraft status monitoring module, a mission management module, an airspace management module, a risk assessment module, and a conflict resolution module;

[0195] Aircraft performance management module: Create a heterogeneous aircraft performance database, map different aircraft models and performance parameters, and formulate a dynamic data update strategy;

[0196] Aircraft status monitoring module: Based on real-time aircraft status data, an aircraft performance degradation model is established and the performance envelope boundary is dynamically adjusted through the degradation model;

[0197] Mission Management Module: Set up a three-level hierarchical decision tree node, including basic compliance verification, dynamic feasibility assessment and mission priority improvement, to ensure that the aircraft performs the mission within the compliance and safety range;

[0198] Airspace management module: Through multi-source data fusion, a four-dimensional dynamic airspace map with multiple attributes is constructed in real time for path planning and conflict detection;

[0199] Risk Assessment Module: Calculates space-time grid cells based on the aircraft's predicted trajectory, assesses the aircraft's collision risk, and dynamically adjusts the decision tree node priority based on the assessment results;

[0200] Conflict resolution module: During the conflict resolution process, the path is replanned based on the aircraft's performance envelope, and when the conflict cannot be resolved, forced avoidance is implemented or a temporary isolation zone is established.

[0201] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0202] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0203] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0204] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. An intelligent decision-making method for heterogeneous aircraft approval based on dynamic performance envelopes, characterized by: include: Create a heterogeneous aircraft performance database, map different aircraft models and performance parameters, and formulate a dynamic data update strategy; Based on real-time aircraft status data, an aircraft performance degradation model is established, and the performance envelope boundary is dynamically adjusted through the degradation model; A three-level hierarchical decision tree is set up, including basic compliance verification, dynamic feasibility assessment, and mission priority improvement, to ensure that aircraft perform missions within compliance and safety ranges; By fusing multi-source data, a four-dimensional dynamic airspace map with multiple attributes is constructed in real time for path planning and conflict detection. Based on the aircraft's predicted trajectory, the space-time grid unit is calculated to assess the aircraft's collision risk, and the decision tree node priority is dynamically adjusted based on the assessment results. During the conflict resolution process, the path is replanned based on the aircraft's performance envelope, and when the conflict cannot be resolved, forced avoidance is implemented or a temporary isolation zone is established.

2. The intelligent approval decision-making method for heterogeneous aircraft based on dynamic performance envelope according to claim 1 is characterized by: The performance parameters include dynamic performance parameters, power system parameters, environmental adaptability parameters and mission adaptability parameters.

3. The intelligent approval decision-making method for heterogeneous aircraft based on dynamic performance envelope according to claim 1 is characterized by: Assume that the aircraft performance decays linearly with the change of time, environmental factors and aircraft status. The specific linear decay model is expressed as: P adjusted =P max ×(1-α1·t-α2·E); where: P adjusted is the adjusted aircraft performance; P max is the maximum performance of the aircraft; t is the aircraft usage time; E is the impact of environmental factors; α1 and α2 are constants of aircraft performance attenuation.

4. The intelligent approval decision-making method for heterogeneous aircraft based on dynamic performance envelope according to claim 3 is characterized by: Based on the aircraft's performance degradation model, the model adopts a linear degradation method to adjust the aircraft's performance envelope boundary according to time and environmental changes, and updates its flight capability in real time according to the aircraft's actual status.

5. The intelligent approval decision-making method for heterogeneous aircraft based on dynamic performance envelope according to claim 1 is characterized by: Setting up a three-level hierarchical decision tree node includes: At the first level, basic compliance verification of the aircraft is conducted to determine whether the aircraft meets flight permit, qualification and airspace management requirements; In the second-level node, dynamic feasibility assessment is performed to evaluate the flight path based on the real-time performance of the aircraft and environmental data to determine whether there are conflicts or flight restrictions; In the third-level node, the urgency and priority of the task are evaluated, the processing priority of high-priority tasks is automatically increased, and the flight path is replanned according to the task requirements.

6. The intelligent approval decision-making method for heterogeneous aircraft based on dynamic performance envelope according to claim 5 is characterized by: By fusing multi-source data, a four-dimensional dynamic airspace map is constructed in real time, including: Collect aircraft status data, weather data, and airspace management data in real time; Synchronize all data to a unified timestamp and perform spatial coordinate conversion to enable data fusion and construct a four-dimensional dynamic airspace map; The airspace is divided into grids according to time and space coordinates, and aircraft status, airspace occupancy and meteorological parameter information are stored for each grid cell, and the airspace status is updated in real time.

7. The intelligent approval decision-making method for heterogeneous aircraft based on dynamic performance envelope according to claim 6 is characterized by: Calculate the space-time grid cells based on the aircraft's predicted trajectory to assess the risk of conflict: Based on the aircraft's initial position, speed, heading, and flight time, the aircraft's future trajectory is predicted and divided into multiple time periods. In each time period, the space-time grid cell occupied by the aircraft is calculated based on its predicted trajectory and compared with the trajectory of other aircraft to determine whether there is a potential conflict; Based on the relative steering capabilities and dynamic obstacle avoidance coefficients of the aircraft, the collision risk between aircraft is comprehensively assessed and the collision risk index is calculated; If the conflict risk index exceeds the set threshold, it triggers dynamic adjustment of the decision tree node priority to enhance the execution rights of high-priority tasks.

8. The intelligent approval decision-making method for heterogeneous aircraft based on dynamic performance envelope according to claim 7 is characterized by: The formula for calculating relative steering ability is: Among them, the turning radius and maximum speed are the dynamic parameters of the aircraft; the calculation formula of the dynamic obstacle avoidance coefficient is: Where AX is the dynamic collision avoidance coefficient, V avoid V is the maximum speed at which the aircraft can safely avoid obstacles. relative is the relative speed to other aircraft.

9. The intelligent approval decision-making method for heterogeneous aircraft based on dynamic performance envelope according to claim 8 is characterized by: During the conflict resolution process, the aircraft's path is replanned based on its performance envelope. If the conflict cannot be resolved, forced avoidance or temporary isolation zones are implemented. After detecting an aircraft path conflict, the flight path is optimized according to the aircraft's dynamic performance envelope, and the flight altitude, speed or heading are adjusted to avoid the conflict; If the path optimization cannot resolve the conflict, multiple alternative paths are generated and the optimal path is selected to replan the aircraft trajectory; If the conflict cannot be resolved, a mandatory avoidance instruction will be issued based on the real-time airspace conditions, requiring the aircraft to perform vertical or horizontal avoidance maneuvers; When a conflict cannot be avoided, a temporary isolation zone will be established to ensure the safety of the aircraft.

10. A heterogeneous aircraft intelligent approval decision system based on a dynamic performance envelope, used to implement the heterogeneous aircraft intelligent approval decision method based on a dynamic performance envelope according to any one of claims 1 to 9, characterized in that: It includes aircraft performance management module, aircraft status monitoring module, mission management module, airspace management module, risk assessment module and conflict resolution module; Aircraft performance management module: Create a heterogeneous aircraft performance database, map different aircraft models and performance parameters, and formulate a dynamic data update strategy; Aircraft status monitoring module: Based on real-time aircraft status data, an aircraft performance degradation model is established and the performance envelope boundary is dynamically adjusted through the degradation model; Mission Management Module: Set up a three-level hierarchical decision tree node, including basic compliance verification, dynamic feasibility assessment and mission priority improvement, to ensure that the aircraft performs the mission within the compliance and safety range; Airspace management module: Through multi-source data fusion, a four-dimensional dynamic airspace map with multiple attributes is constructed in real time for path planning and conflict detection; Risk Assessment Module: Calculates space-time grid cells based on the aircraft's predicted trajectory, assesses the aircraft's collision risk, and dynamically adjusts the decision tree node priority based on the assessment results; Conflict resolution module: During the conflict resolution process, the path is replanned based on the aircraft's performance envelope, and when the conflict cannot be resolved, forced avoidance is implemented or a temporary isolation zone is established.

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