Method suitable for cooperative operation of civil aviation and general aviation

Abstract

The invention discloses a method suitable for cooperative operation of civil aviation and general aviation, which is applied to civil aviation air traffic control and general aviation flight service, and comprises the following steps: collecting multi-source data, carrying out data cleaning, standardized processing and real-time analysis, and sending the processed data to the civil aviation or the general aviation; based on the processed data, the real-time flight demand and the airspace use condition, the airspace of civil aviation and general aviation is dynamically allocated; based on the punctuality rate requirement of the civil aviation flight, the timeliness of the general aviation task and the airspace limitation, carrying out collaborative optimization on the flight plans of the civil aviation and the general aviation; and constructing a collaborative coping scheme according to the emergencies. According to the method, the flight safety of civil aviation and general aviation can be guaranteed, the comprehensive utilization rate of airspace resources is improved, and the efficiency of a whole aviation operation system is enhanced.

Description

Technical Field

[0001] This invention belongs to the field of air traffic management, and specifically relates to a method applicable to the coordinated operation of civil aviation and general aviation. Background Technology

[0002] Currently, a general aviation flight approval process has been established within the civil aviation system. General aviation flight plans are filled out and submitted manually in advance, and then coordinated and approved by the civil aviation authorities before being fed back to the general aviation flight operators. The above structure consists of two independent civil aviation systems and a general aviation system: a civil aviation command system and a general aviation flight plan system. This scheme is physically and logically separate.

[0003] In existing solutions, there is no unified, low-level real-time data sharing bus between the two systems, and the "connection" between them is usually loose. When general aviation needs to execute a flight plan, the plan needs to be manually filled in in advance, and when emergency rescue or special operations are involved, the response speed is often lagging. This fragmented operation mode is the core feature of the existing technical solution in terms of permissions and data flow, and it is also the source of its fundamental defects.

[0004] In summary, the essence of the existing technical solution is to use two independent systems with non-shared permissions and no real-time data exchange to complete a collaborative operation plan covering civil aviation and general aviation through external coordination and advance application. This results in a waste of human resources and low operational efficiency. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide a method applicable to the coordinated operation of civil aviation and general aviation, so as to solve the problems of lack of mutual knowledge of flight status and prominent flight conflict risks caused by the independent information systems and the inability to share data in real time between civil aviation systems and general aviation systems in the prior art; the method of this invention can ensure the flight safety of civil aviation and general aviation, improve the comprehensive utilization rate of airspace resources, and enhance the efficiency of the entire aviation operation system.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] The present invention provides a method for the coordinated operation of civil aviation and general aviation, applied to civil aviation air traffic control and general aviation flight services, comprising the following steps:

[0008] 1) Collect data from multiple sources, perform data cleaning, standardization, and real-time analysis, and send the processed data to civil aviation or general aviation;

[0009] 2) Based on the data processed in step 1), real-time flight demand, and airspace usage, dynamically allocate airspace for civil aviation and general aviation;

[0010] 3) Based on the on-time performance requirements of civil aviation flights, the timeliness of general aviation missions, and airspace restrictions, flight plans for civil aviation and general aviation are optimized in a coordinated manner.

[0011] 4) Depending on the emergency, repeat steps 1) to 3) to build a collaborative response plan.

[0012] Furthermore, the multi-source data in step 1) includes: civil aviation flight plan data, general aviation flight application data, real-time meteorological data, airspace congestion status data, and airport capacity data;

[0013] The civil aviation flight plan data PlanList includes the sub-variable Plan: Plan No., Flight No., CallSign, Airport Codes ADEP and ADES, Planned Departure Time ETD, Planned Arrival Time ETA, Flight Level CFL, Route ROUTE, Aircraft Type PlaneType, and Wake Turb.

[0014] The General Aviation Flight Application Data GeneralList includes the sub-variable General: Application Number No, Aircraft Number AircraftType, Mission Type Type, Requested Airspace Range Airspace, Requested Flight Time Period Time, and Flight Altitude Range AltRange;

[0015] The real-time meteorological data MetarList includes the sub-variable Metar: monitoring point coordinates M_loc, real-time wind speed M_wind, visibility M_vis, weather phenomena M_cond, and meteorological update frequency M_freq;

[0016] The airspace congestion status data S_congest_list includes the sub-variable S_congest: airspace partition number S_id, number of aircraft in the current airspace S_ac_num, airspace capacity limit S_cap, and congestion index S_index;

[0017] The airport capacity data C_airport_list includes the sub-variable C_airport: airport code C_ap, number of currently available runways C_runway, maximum number of takeoffs and landings per hour C_hourly, number of available parking stands C_park, and ground support capacity C_support.

[0018] Furthermore, the data cleaning and standardization process in step 1) specifically includes:

[0019] 11) Data cleaning includes: outlier removal and missing value completion;

[0020] 111) Outlier Removal: Based on the preset rule DEFAULT_RULE, outlier data is marked and removed, and an anomaly report R_err is generated, which includes the outlier data ID, anomaly type and processing suggestions;

[0021] 112) Missing value completion: For partially missing sub-variables, fill them with the mean of similar data or call the backup data source;

[0022] 12) Data standardization includes: standardizing data formats and standardizing data units;

[0023] 121) Standardized Format: Converts data from different sources into a system-wide format using preset standards;

[0024] 122) Store the raw data, cleaned and standardized data in a distributed database D_store, and set the data lifecycle D_life to clean up redundant data periodically.

[0025] Furthermore, the real-time analysis of the processed data in step 1) specifically includes: analysis of busy periods and busy airspaces for civil aviation, analysis of busy periods and busy airspaces for general aviation, and whether there are busy periods and airspaces for civil aviation that require priority protection.

[0026] Analysis of busy periods and busy airspaces in civil aviation, using 30-minute intervals, analyzes airspace and flight frequency, and marks them according to the level of busyness;

[0027] The analysis of busy periods and busy airspaces in general aviation is performed in 15-minute increments, analyzing airspace and flight operations and marking them according to their level of busyness.

[0028] Mark civil aviation flights that cannot be adjusted and require special protection or general aviation flight missions that must be performed.

[0029] Further, step 2) specifically includes:

[0030] 21) Flight demand and airspace usage analysis: Calculate the flight plans and airspace carrying capacity for civil aviation and general aviation;

[0031] 211) Based on the civil aviation flight plan data PlanList, the airspace congestion status data S_congest_list, and the civil aviation airspace demand parameter D_civil, calculate the civil aviation demand saturation S_civil; D_civil = {demand airspace partition D_civil_id, demand time period D_civil_time, demand number of aircraft D_civil_ac, and core mission priority P_civil}, the expression is as follows:

[0032] S_civil=D_civil_ac / (S_cap_total×P_civil);

[0033] Among them, S_cap_total is the upper limit of airspace capacity; the civil aviation demand saturation S_civil ranges from 0 to 1.5, and when S_civil ≥ 1.2, it is judged as high demand;

[0034] 212) Based on the general aviation flight application data GeneralList, mission type A_type, and general aviation airspace demand parameter D_general, calculate the general aviation demand saturation S_general; D_general = {demand airspace partition D_general_id, demand time period D_general_time, demand number of aircraft D_general_ac, and mission urgency P_general}; the expression is as follows:

[0035] S_general=D_general_ac / (S_cap_total×P_general);

[0036] The value of S_general ranges from 0 to 1.5. When S_general ≥ 1.2, it is considered to be in high demand.

[0037] 213) Every 15 minutes, retrieve the latest civil aviation flight plan data PlanList, general aviation flight application data GeneralList, airspace congestion status data S_congest_list, civil aviation airspace demand parameter D_civil, and general aviation airspace demand parameter D_general from the distributed database D_store. Calculate the civil aviation demand saturation S_civil and general aviation demand saturation S_general based on steps 211) and 212).

[0038] 22) Real-time allocation calculation;

[0039] 221) With the goal of maximizing airspace utilization and balancing the needs of both parties, the objective function F_obj is constructed as follows:

[0040] ;

[0041] Where α and β are weighting coefficients; S_civil_ac_num is the number of aircraft allocated to civil aviation, S_general_ac_num is the number of aircraft allocated to general aviation, and S_cap_total is the upper limit of airspace capacity; |S_civil-S_general| is the absolute value of the difference between the demand saturation of civil aviation and general aviation, and the smaller the difference, the better the balance.

[0042] 222) Set constraints;

[0043] Core mission guarantee constraints: If the core mission priority P_civil is international flights, then the airspace capacity allocated to civil aviation shall be greater than or equal to the number of aircraft required, D_civil_ac × 1.1; if the mission urgency P_general is emergency rescue, then its airspace requirements shall be prioritized and the allocated capacity shall be greater than or equal to the number of aircraft required, D_general_ac.

[0044] Adjustment range constraints: The adjusted airspace range ≤ airspace height A_air_alt × (1 + airspace adjustable ratio A_air_adjust), and the adjusted usage time ≤ original time period × (1 + A_air_adjust);

[0045] Safety separation constraints: The airspace allocated to civil aviation and general aviation must maintain a height difference of greater than or equal to 600 meters in space, or a time interval of greater than or equal to 10 minutes;

[0046] 223) Allocation Result Output: Through multiple rounds of iteration, the optimal allocation scheme R_optim is found to maximize airspace utilization, balance the demands of civil aviation and general aviation, and meet safety constraints; details are as follows:

[0047] 2231) Based on historical operational data, generate multiple initial allocation schemes, each scheme including:

[0048] Airspace scope: divided into non-overlapping airspace for civil aviation and airspace for general aviation, based on latitude and longitude coordinates, which also meet the requirements of safe spacing.

[0049] Time allocation: Based on peak hours and general aviation mission hours, civil aviation priority use time periods and general aviation priority use time periods are divided;

[0050] Capacity allocation: Based on airspace type, set the maximum number of civil aviation aircraft and the maximum number of general aviation aircraft allowed;

[0051] A multi-objective optimization algorithm optimized using spatial domain operation characteristics is used to calculate the fitness of each initial scheme. :

[0052] ;

[0053] Simultaneously verify the security constraints, and eliminate schemes that do not meet the constraints;

[0054] 2232) Retain the top 30% of solutions with high fitness, and select the parent cooperative solution probabilistically through a roulette wheel mechanism. The higher the fitness of the solution, the greater the probability of it being selected. Perform single-point crossover on the selected parent cooperative solutions. Randomly fine-tune some parameters to avoid the algorithm getting stuck in local optima.

[0055] 2233) Repeat the iterative process until the optimal fitness calculation method converges, then output the optimal solution;

[0056] 23) Compliance check of the allocation plan;

[0057] 231) Verification indicators:

[0058] Core mission fulfillment rate: Civil aviation core mission fulfillment rate C_civil = maximum permissible number of civil aviation aircraft R_civil_cap / required number of civil aviation aircraft D_civil_ac;

[0059] Adjustment compliance rate: Adjustment compliance rate C_adjust = actual adjustment range / airspace adjustable ratio A_air_adjust;

[0060] Safety interval compliance rate C_safe: Calculated based on existing radar safety interval requirements, that is, if the allocated scheme time and space intervals meet the current safety interval regulations, then there is no safety interval violation;

[0061] 232) Verification result processing: If all indicators are ≥ preset thresholds, the scheme passes the verification and is published in real time; if any indicators fail to meet the standards, return to step 223) for a second iteration, adjust the constraints, recalculate the allocation scheme, until the verification is passed.

[0062] Furthermore, step 3) specifically includes:

[0063] 31) Set optimization parameters, including: civil aviation plan optimization parameters, general aviation plan optimization parameters, and airspace restrictions and safety parameters;

[0064] The civil aviation planning optimization parameter Plan_opt is defined as follows: Plan_opt = {No, ETD, ETA, P_on_time, W_on_time, R_peak, T_civil_win}, where No is the plan number, ETD is the planned departure time, ETA is the planned arrival time, P_on_time is the on-time performance requirement, R_peak is the peak route identifier, and T_civil_win is the acceptable adjustment window for civil aviation.

[0065] The general aviation plan optimization parameter is General_opt, which is defined as follows: General_opt = {Gno, T_general_ori, T_urgent, Gairspace, Galtrange, T_general_deadline, A_takeoff_opt}, where GNo is the application number, T_general_ori is the flight duration, T_urgent is the mission urgency, Gairspace is the original flight area, Galtrange is the original flight range, T_general_deadline is the latest mission completion time, and A_takeoff_opt is the adjusted start time.

[0066] Airspace restrictions and safety parameters S_safe, S_safe={D_lateral, D_vertical, T_interval, T_peak}, where D_lateral is the lateral safety interval, D_vertical is the longitudinal safety interval, T_interval is the time interval threshold, and T_peak is the peak period for civil aviation routes;

[0067] 32) With the objectives of minimizing on-time performance loss in civil aviation, minimizing timeliness loss in general aviation, and minimizing conflict, a collaborative optimization scheme F_coordinate_opt is constructed, and the calculation formula is as follows:

[0068] F_coordinate_opt=A×(1-ΔT_civil / ETD)×W_on_time+B×(1-ΔT_general / T_general_ori)×K_urgent+γ×(1-C_total);

[0069] Where A is the on-time rate weight for civil aviation, A=0.4; B is the timeliness weight for general aviation, B=0.35; γ is the conflict degree weight, γ=0.25; ETD is the original departure time of civil aviation flights; 1-C_total is the conflict degree optimization index; K_urgent is the weight coefficient of mission timeliness urgency; W_on_time is the weight coefficient of on-time rate requirement;

[0070] The civil aviation on-time performance loss index ΔT_civil = |adjusted takeoff time F_takeoff_opt - original takeoff time ETD|, ΔT_civil ≤ T_civil_win;

[0071] The general aviation timeliness loss index ΔT_general = |adjusted mission duration T_general_opt - flight duration T_general_ori|, and the adjusted mission duration T_general_opt ≤ the latest mission completion time T_general_deadline - adjusted start time;

[0072] 321) Safety interval constraints;

[0073] Lateral constraint: The spatial distance D between civil aviation and general aviation aircraft at any given time, where D = ≥D_lateral, where (X1,Y1) are the coordinates of civil aviation flights, and (X2,Y2) are the coordinates of general aviation aircraft.

[0074] Vertical constraint: At any given time, the altitude distance H between civil aviation and general aviation aircraft, H = |F_alt_opt - A_alt_opt| ≥ D_vertical, where F_alt_opt is the adjusted altitude of the civil aviation flight and A_alt_opt is the adjusted altitude of the general aviation aircraft.

[0075] 322) Airspace capacity constraint: For any airspace partition S_id passed through by the optimized route, the total number of aircraft at any time is ≤ S_cap;

[0076] 323) Time window constraints, including: takeoff time window constraints for civil aviation flights and mission duration window constraints for general aviation aircraft;

[0077] The departure time window constraint for civil aviation flights is specifically as follows: the adjusted departure time must fall within the time interval between the original departure time minus the acceptable adjustment window duration and the original departure time plus the acceptable adjustment window duration, where F_takeoff_opt ∈ [F_takeoff_ori - T_civil_win, F_takeoff_ori + T_civil_win]. Here, the adjusted departure time F_takeoff_opt refers to the actual departure time of the optimized civil aviation flight; the original departure time ETD refers to the departure time initially set in the flight plan; and the acceptable adjustment window T_civil_win refers to the maximum allowable delay or advance time for the flight. Adjustments within this time range will not have a significant impact on the flight's on-time performance.

[0078] The mission duration window constraint for general aviation aircraft is as follows: the adjusted mission duration must be less than or equal to the mission's latest completion time minus the adjusted start time, T_general_opt ≤ T_general_deadline - A_takeoff_opt. Here, the adjusted mission duration T_general_opt refers to the total time required for the general aviation to complete the mission after optimization, including flight time and possible waiting time; the mission's latest completion time T_general_deadline refers to the deadline when the general aviation must complete the mission; and the adjusted start time A_takeoff_opt refers to the actual start time of the general aviation mission after optimization.

[0079] 324) Divide the airspace into 100×100 grid nodes, mark the nodes of civil aviation peak routes as high-cost nodes, and set the weight coefficient W_grid to 1.8, which is dynamically adjusted according to the busyness of peak routes, conflict risk, etc.

[0080] 325) Using general aviation take-off and landing points as the starting / ending points, search for alternative detour routes that avoid high-cost nodes, and calculate the spatial conflict degree C_space for each route;

[0081] 326) By adjusting the takeoff time of civil aviation, the flight time of general aviation, the flight altitude, and the detour routes for conflict avoidance, the civil aviation and general aviation plans can be coordinated and optimized.

[0082] Further, step 325) specifically involves: for each candidate detour route, traversing all its mapped grid nodes, retrieving the weight coefficient W_grid of each node from the database D_store to form the weight set W_route for that route, and summing the weights of all nodes in the weight set to obtain the total route weight Sum_W = Σ(W_grid), where The total number of grid nodes after route mapping is N_route. The total weight is divided by the total number of nodes to obtain the average node weight of the route, Avg_W = C_space = Sum_W / N_route. The average node weight of the route is the spatial conflict degree C_space. The spatial conflict degree C_space is a quantitative indicator that measures the degree of overlap or proximity between general aviation alternative detour routes and civil aviation flights in space. It is used to assess the conflict risk of the route. The higher the value, the more high-cost nodes the route passes through, and the higher the conflict risk.

[0083] Furthermore, step 4) specifically includes: adjusting the flight urgency level and airspace node weight in response to sudden weather, equipment failure, or emergency missions, repeating steps 1) to 3), constructing an emergency plan, prioritizing high-priority flight missions, and issuing an alarm if an emergency plan cannot be generated, and simultaneously activating the manual collaboration mode.

[0084] The beneficial effects of this invention are:

[0085] (1) This invention can flexibly allocate airspace according to real-time needs, predict airspace demand for the next 1-4 hours based on historical data, divide the fixed priority area (main civil aviation routes) and flexible sharing area (general aviation activity area), and can allocate more medium and high airspace to civil aviation, while general aviation mainly uses low airspace.

[0086] (2) Through real-time information sharing, this invention enables civil aviation control departments and general aviation operators to accurately grasp the dynamics of each other's aircraft, including real-time location, flight altitude, speed, and heading. It can provide early warnings of aircraft approaching busy civil aviation routes and issue avoidance prompts to prevent inadvertent incidents; civil aviation flights can also know the operating areas of general aviation in a timely manner and adjust their routes in advance to avoid them.

[0087] (3) This invention can reduce flight delays and obstruction of general aviation missions, improve the operational efficiency of civil aviation and general aviation, save travel time for civil aviation passengers, reduce operating costs for general aviation enterprises, shorten the response time of general aviation missions to within 10 minutes, and significantly improve emergency rescue efficiency. Attached Figure Description

[0088] Figure 1 This is a schematic diagram of the method of the present invention. Detailed Implementation

[0089] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to embodiments and accompanying drawings. The content mentioned in the embodiments is not intended to limit the present invention.

[0090] Reference Figure 1 As shown, the present invention provides a method for the coordinated operation of civil aviation and general aviation, applied to civil aviation air traffic control and general aviation flight services, comprising the following steps:

[0091] 1) Collect data from multiple sources, perform data cleaning, standardization, and real-time analysis, and send the processed data to civil aviation or general aviation;

[0092] The multi-source data in step 1) includes: civil aviation flight plan data, general aviation flight application data, real-time meteorological data, airspace congestion status data, and airport capacity data;

[0093] The civil aviation flight plan data PlanList includes the sub-variable Plan: Plan No., Flight No., CallSign, Airport Codes ADEP and ADES, Planned Departure Time ETD, Planned Arrival Time ETA, Flight Level CFL, Route ROUTE, Aircraft Type PlaneType, and Wake Turb.

[0094] The General Aviation Flight Application Data GeneralList includes the sub-variable General: Application Number No, Aircraft Number AircraftType, Mission Type Type, Requested Airspace Range Airspace, Requested Flight Time Period Time, and Flight Altitude Range AltRange;

[0095] The real-time meteorological data MetarList includes the sub-variable Metar: monitoring point coordinates M_loc, real-time wind speed M_wind, visibility M_vis, weather phenomena M_cond, and meteorological update frequency M_freq;

[0096] The airspace congestion status data S_congest_list includes the sub-variable S_congest: airspace partition number S_id, number of aircraft in the current airspace S_ac_num, airspace capacity limit S_cap, and congestion index S_index;

[0097] The airport capacity data C_airport_list includes the sub-variable C_airport: airport code C_ap, number of currently available runways C_runway, maximum number of takeoffs and landings per hour C_hourly, number of available parking stands C_park, and ground support capacity C_support.

[0098] Specifically, the data cleaning and standardization process in step 1) includes:

[0099] 11) Data cleaning includes: outlier removal and missing value completion;

[0100] 111) Outlier Removal: Based on preset rules DEFAULT_RULE (such as data frame outlier rules, timestamp outlier rules, data rationality rules, etc.), outlier data is marked and removed, and an outlier report R_err is generated, which includes the outlier data ID, outlier type and processing suggestions (such as ETD earlier than the current time, Airspace exceeding the control range, M_vis<0, etc. are considered outliers).

[0101] 112) Missing value completion: For some missing sub-variables (such as CFL not filled), fill them with the mean of similar data (such as the average altitude of historical flights on the same route) or call the backup data source to fill them (such as obtaining CFL from the airline's operation and maintenance system).

[0102] 12) Data standardization includes: standardizing data formats and standardizing data units;

[0103] 121) Standardized format: Convert data from different sources into the system's universal format using the system's preset standards (e.g., time is standardized to "YYYY-MM-DD HH:MM:SS", and coordinates are standardized to the WGS84 coordinate system).

[0104] 122) Store the raw data, cleaned and standardized data in a distributed database D_store (using HBase architecture, supporting massive data storage and fast query), and set the data lifecycle D_life (e.g., retain the original flight plan for 1 year and real-time weather data for 7 days), and clean up redundant data regularly.

[0105] Specifically, the real-time analysis of the processed data in step 1) includes: analysis of busy periods and busy airspaces for civil aviation, analysis of busy periods and busy airspaces for general aviation, and whether there are busy periods and airspaces for civil aviation that require priority protection.

[0106] Analysis of busy periods and busy airspaces in civil aviation, using 30-minute intervals, analyzes airspace and flight frequency, and marks them according to the level of busyness;

[0107] The analysis of busy periods and busy airspaces in general aviation is performed in 15-minute increments, analyzing airspace and flight operations and marking them according to their level of busyness.

[0108] For civil aviation flights that cannot be adjusted and require special protection (such as special flights for VIPs) or general aviation flight missions that must be performed (such as emergency rescue), mark them.

[0109] 2) Based on the data processed in step 1), real-time flight demand, and airspace usage, dynamically allocate airspace for civil aviation and general aviation; specifically including:

[0110] 21) Flight demand and airspace usage analysis: Calculate the flight plans and airspace carrying capacity for civil aviation and general aviation;

[0111] 211) Based on the civil aviation flight plan data PlanList, the airspace congestion status data S_congest_list, and the civil aviation airspace demand parameter D_civil, calculate the civil aviation demand saturation S_civil; D_civil = {demand airspace partition D_civil_id, demand time period D_civil_time, demand number of aircraft D_civil_ac, and core mission priority P_civil}, the expression is as follows:

[0112] S_civil=D_civil_ac / (S_cap_total×P_civil);

[0113] Among them, S_cap_total is the upper limit of airspace capacity; the civil aviation demand saturation S_civil ranges from 0 to 1.5. When S_civil ≥ 1.2, it is judged as high demand (i.e., high airspace usage demand rate).

[0114] 212) Based on the general aviation flight application data GeneralList, mission type A_type, and general aviation airspace demand parameter D_general, calculate the general aviation demand saturation S_general; D_general = {demand airspace partition D_general_id, demand time period D_general_time, demand number of aircraft D_general_ac, and mission urgency P_general}; the expression is as follows:

[0115] S_general=D_general_ac / (S_cap_total×P_general);

[0116] The value of S_general ranges from 0 to 1.5. When S_general ≥ 1.2, it is considered to be in high demand (i.e., high airspace usage demand rate).

[0117] 213) Every 15 minutes, retrieve the latest civil aviation flight plan data PlanList, general aviation flight application data GeneralList, airspace congestion status data S_congest_list, civil aviation airspace demand parameter D_civil, and general aviation airspace demand parameter D_general from the distributed database D_store. Calculate the civil aviation demand saturation S_civil and general aviation demand saturation S_general based on steps 211) and 212).

[0118] 22) Real-time allocation calculation;

[0119] 221) With the goal of maximizing airspace utilization and balancing the needs of both parties, the objective function F_obj is constructed as follows:

[0120] ;

[0121] Where α and β are weighting coefficients (α=0.6, β=0.4, which can be adjusted according to policy); S_civil_ac_num is the number of aircraft allocated to civil aviation, S_general_ac_num is the number of aircraft allocated to general aviation, and S_cap_total is the upper limit of airspace capacity; |S_civil-S_general| is the absolute value of the difference between the demand saturation of civil aviation and general aviation, and the smaller the difference, the better the balance.

[0122] 222) Set constraints;

[0123] Core mission guarantee constraints: If the core mission priority P_civil is international flights (corresponding weight W_civil=1.0), then the airspace capacity allocated to civil aviation is ≥ the number of aircraft required D_civil_ac×1.1 (with 10% redundancy reserved); if the mission urgency P_general is emergency rescue (corresponding weight W_general=1.2), then its airspace requirements are prioritized, and the allocated capacity is ≥ the number of aircraft required D_general_ac.

[0124] Adjustment range constraints: The adjusted airspace range ≤ airspace height A_air_alt × (1 + airspace adjustable ratio A_air_adjust), and the adjusted usage time ≤ original time period × (1 + A_air_adjust);

[0125] Safety separation constraints: The airspace allocated to civil aviation and general aviation must maintain a height difference of greater than or equal to 600 meters in space, or a time interval of greater than or equal to 10 minutes;

[0126] 223) Allocation Result Output: Through multiple rounds of iteration, the optimal allocation scheme R_optim is found to maximize airspace utilization, balance the demands of civil aviation and general aviation, and meet safety constraints; details are as follows:

[0127] 2231) Based on historical operational data, generate multiple initial allocation schemes, each scheme including:

[0128] Airspace range: divided into non-overlapping airspace for civil aviation that meets safety interval requirements (R_civil_air coordinate array type) and non-overlapping airspace for general aviation that meets safety interval requirements (R_general_air coordinate array type) according to latitude and longitude coordinates.

[0129] Time allocation: Based on peak hours and general aviation mission hours, civil aviation priority use time periods (R_civil_time time interval type) and general aviation priority use time periods (R_general_time time interval type) are divided.

[0130] Capacity allocation: Based on airspace type, set the maximum number of civil aviation aircraft allowed (R_civil_cap numerical type) and the maximum number of general aviation aircraft allowed (R_general_cap numerical type).

[0131] A multi-objective optimization algorithm optimized using spatial domain operation characteristics is used to calculate the fitness of each initial scheme. (Objective function F_obj):

[0132] ;

[0133] At the same time, safety constraints (such as lateral spacing ≥ 5km, capacity not exceeding the upper limit) are verified, and schemes that do not meet the constraints are eliminated;

[0134] 2232) Retain the top 30% of schemes with high fitness, and use a roulette wheel to probabilistically select the parent cooperative scheme (the basic airspace allocation scheme used to generate the next generation optimization scheme). The higher the fitness of the scheme, the greater the probability of it being selected. Perform single-point crossover on the selected parent cooperative schemes. Randomly fine-tune some parameters (such as capacity allocation ±1 flight, airspace coordinates ±0.1°) to avoid the algorithm getting trapped in local optima.

[0135] 2233) Repeat the iterative process until the optimal fitness calculation method converges, then output the optimal solution;

[0136] 23) Compliance check of the allocation plan;

[0137] 231) Verification indicators:

[0138] Core mission fulfillment rate: Civil aviation core mission fulfillment rate C_civil = maximum permissible number of civil aviation aircraft R_civil_cap / required number of civil aviation aircraft D_civil_ac;

[0139] Adjustment compliance rate: Adjustment compliance rate C_adjust = actual adjustment range / airspace adjustable ratio A_air_adjust;

[0140] Safety interval compliance rate C_safe: Calculated based on existing radar safety interval requirements, that is, if the allocated scheme time and space intervals meet the current safety interval regulations, then there is no safety interval violation;

[0141] 232) Verification result processing: If all indicators are ≥ preset thresholds (C_civil≥1.0, C_general≥1.0, C_adjust≤1.0, C_safe≥1.0), the scheme passes the verification and is published in real time; if any indicator fails to meet the standard (e.g., C_civil=0.9<1.0), return to step 223) for a second iteration, adjust the constraints, recalculate the allocation scheme, until the verification is passed (maximum 3 iterations, if it still fails, manual review is triggered).

[0142] 3) Based on the on-time performance requirements of civil aviation flights, the timeliness of general aviation missions, and airspace restrictions, flight plans for civil aviation and general aviation are optimized in a coordinated manner.

[0143] In step 3, under the premise of meeting the safety interval, avoidance paths are generated for general aviation aircraft and low-conflict routes are planned to reduce mutual interference.

[0144] Specifically, step 3) includes:

[0145] 31) Set optimization parameters, including: civil aviation plan optimization parameters, general aviation plan optimization parameters, and airspace restrictions and safety parameters;

[0146] The civil aviation flight schedule optimization parameter Plan_opt is defined as follows: Plan_opt = {No, ETD, ETA, P_on_time, W_on_time, R_peak, T_civil_win}. Here, No is the schedule number (consistent with the flight schedule number in the sub-variable Plan), ETD is the scheduled departure time (timestamp type), ETA is the scheduled arrival time (timestamp type), P_on_time is the on-time performance requirement (enumerated type: "extremely high / high / medium"), W_on_time is the corresponding weight (1.0 / 0.8 / 0.6, international flights default to "extremely high"), R_peak is the peak flight route identifier (Boolean type: True = passing through a peak civil aviation route, peak flight routes are defined as routes corresponding to airspace with S_index ≥ 0.8), and T_civil_win is the acceptable adjustment window for civil aviation.

[0147] The general aviation plan optimization parameter is General_opt, which is defined as follows: General_opt = {Gno, T_general_ori, T_urgent, Gairspace, Galtrange, T_general_deadline, A_takeoff_opt}. Here, GNo is the application number (string type, consistent with No in the sub-variable General), T_general_ori is the flight duration (time difference between the original planned flight time slots), T_urgent is the mission urgency level (enumerated type: "urgent / normal / lenient", corresponding coefficient K_urgent: 1.5 / 1.0 / 0.8, emergency rescue defaults to "urgent"), Gairspace is the original flight area, Galtrange is the original flight range, T_general_deadline is the latest mission completion time (timestamp type), and A_takeoff_opt is the adjusted start time.

[0148] Airspace restrictions and safety parameters S_safe, S_safe={D_lateral, D_vertical, T_interval, T_peak}, where D_lateral is the lateral safety interval, D_vertical is the longitudinal safety interval, T_interval is the time interval threshold, and T_peak is the peak period for civil aviation routes;

[0149] 32) With the objectives of minimizing on-time performance loss in civil aviation, minimizing timeliness loss in general aviation, and minimizing conflict, a collaborative optimization scheme F_coordinate_opt is constructed, and the calculation formula is as follows:

[0150] F_coordinate_opt=A×(1-ΔT_civil / ETD)×W_on_time+B×(1-ΔT_general / T_general_ori)×K_urgent+γ×(1-C_total);

[0151] Where A is the on-time performance weight for civil aviation, A=0.4; B is the timeliness weight for general aviation, B=0.35; γ is the conflict degree weight, γ=0.25; ETD is the original departure time of civil aviation flights; 1-C_total is the conflict degree optimization index (the closer to 1, the fewer the conflicts).

[0152] The civil aviation on-time performance loss index ΔT_civil = |adjusted takeoff time F_takeoff_opt - original takeoff time ETD|, ΔT_civil ≤ T_civil_win;

[0153] The general aviation timeliness loss index ΔT_general = |adjusted mission duration T_general_opt - flight duration T_general_ori|, and the adjusted mission duration T_general_opt ≤ the latest mission completion time T_general_deadline - adjusted start time;

[0154] 321) Safety interval constraints;

[0155] Lateral constraint: The spatial distance D between civil aviation and general aviation aircraft at any given time, where D = ≥D_lateral, where (X1,Y1) are the coordinates of civil aviation flights, and (X2,Y2) are the coordinates of general aviation aircraft.

[0156] Vertical constraint: At any given time, the altitude distance H between civil aviation and general aviation aircraft, H = |F_alt_opt - A_alt_opt| ≥ D_vertical, where F_alt_opt is the adjusted altitude of the civil aviation flight and A_alt_opt is the adjusted altitude of the general aviation aircraft.

[0157] 322) Airspace capacity constraint: For any airspace partition S_id passed through by the optimized route, the total number of aircraft at any time is ≤ S_cap;

[0158] 323) Time window constraints, including: takeoff time window constraints for civil aviation flights and mission duration window constraints for general aviation aircraft;

[0159] The departure time window constraint for civil aviation flights is specifically as follows: the adjusted departure time must fall within the time interval between the original departure time minus the acceptable adjustment window duration and the original departure time plus the acceptable adjustment window duration, where F_takeoff_opt ∈ [F_takeoff_ori - T_civil_win, F_takeoff_ori + T_civil_win]. Here, the adjusted departure time F_takeoff_opt refers to the actual departure time of the optimized civil aviation flight; the original departure time ETD refers to the departure time initially set in the flight plan; and the acceptable adjustment window T_civil_win refers to the maximum allowable delay or advance time for the flight. Adjustments within this time range will not have a significant impact on the flight's on-time performance.

[0160] The mission duration window constraint for general aviation aircraft is as follows: the adjusted mission duration must be less than or equal to the mission's latest completion time minus the adjusted start time, T_general_opt ≤ T_general_deadline - A_takeoff_opt. Here, the adjusted mission duration T_general_opt refers to the total time required for the general aviation to complete the mission after optimization, including flight time and possible waiting time; the mission's latest completion time T_general_deadline refers to the deadline when the general aviation must complete the mission; and the adjusted start time A_takeoff_opt refers to the actual start time of the general aviation mission after optimization.

[0161] 324) Divide the airspace into 100×100 grid nodes, mark the civil aviation peak route nodes (R_peak=True) as high-cost nodes, and set the weight coefficient W_grid to 1.8, which is dynamically adjusted according to the busyness of peak routes, conflict risk, etc.

[0162] The weighting coefficient of 1.8 is the baseline weight for high-cost nodes, ensuring that the algorithm has a clear direction for avoidance; while dynamic adjustment optimizes the weight value according to the risk changes in the actual operation scenario, balancing conflict avoidance and route efficiency, so that the path planning is more in line with the real airspace conditions.

[0163] 325) Using general aviation take-off and landing points as the starting / ending points, search for alternative detour routes (≥3 routes) that avoid high-cost nodes, and calculate the spatial conflict degree C_space for each route;

[0164] 326) By adjusting the takeoff time of civil aviation, the flight time of general aviation, the flight altitude, and the detour routes for conflict avoidance, the civil aviation and general aviation plans can be coordinated and optimized.

[0165] Specifically, step 325 involves: for each candidate detour route, traversing all its mapped grid nodes, retrieving the weight coefficient W_grid of each node from the database D_store to form the weight set W_route for that route, and summing the weights of all nodes in the weight set to obtain the total route weight Sum_W = Σ(W_grid), where... The total number of grid nodes after route mapping is N_route (i.e., the number of elements in the weight set). The total weight is divided by the total number of nodes to obtain the average node weight of the route, Avg_W = C_space = Sum_W / N_route. The value of the average node weight of the route is the spatial conflict degree C_space. The spatial conflict degree C_space is a quantitative indicator that measures the degree of overlap or proximity between general aviation alternative detour routes and civil aviation flights (especially peak routes) in space. It is used to assess the conflict risk of the route. The higher the value, the more high-cost nodes the route passes through, and the higher the conflict risk.

[0166] 4) Based on the emergency situation, repeat steps 1) to 3) to build a collaborative response plan; specifically, this includes: adjusting the flight urgency level and airspace node weight for sudden weather, equipment failure or emergency missions (such as medical rescue), repeating steps 1) to 3) to build an emergency plan, prioritizing high-priority flight missions, and issuing an alarm if an emergency plan cannot be generated, and simultaneously activating the manual collaboration mode.

[0167] This invention has many specific applications. The above description is only a preferred embodiment of this invention. It should be noted that for those skilled in the art, several improvements can be made without departing from the principle of this invention, and these improvements should also be considered within the scope of protection of this invention.

Claims

1. A method suitable for the coordinated operation of civil aviation and general aviation, applied to civil aviation air traffic control and general aviation flight services, characterized in that, The steps are as follows: 1) Collect data from multiple sources, perform data cleaning, standardization, and real-time analysis, and send the processed data to civil aviation or general aviation; 2) Based on the data processed in step 1), real-time flight demand, and airspace usage, dynamically allocate airspace for civil aviation and general aviation; 3) Based on the on-time performance requirements of civil aviation flights, the timeliness of general aviation missions, and airspace restrictions, flight plans for civil aviation and general aviation are optimized in a coordinated manner. 4) Depending on the emergency, repeat steps 1) to 3) to build a collaborative response plan.

2. The method for coordinated operation of civil aviation and general aviation according to claim 1, characterized in that, The multi-source data in step 1) includes: civil aviation flight plan data, general aviation flight application data, real-time meteorological data, airspace congestion status data, and airport capacity data; The civil aviation flight plan data PlanList includes the sub-variable Plan: Plan No., Flight No., CallSign, Airport Codes ADEP and ADES, Planned Departure Time ETD, Planned Arrival Time ETA, Flight Level CFL, Route ROUTE, Aircraft Type PlaneType, and Wake Turb. The General Aviation Flight Application Data GeneralList includes the sub-variable General: Application Number No, Aircraft Number AircraftType, Mission Type Type, Requested Airspace Range Airspace, Requested Flight Time Period Time, and Flight Altitude Range AltRange; The real-time meteorological data MetarList includes the sub-variable Metar: monitoring point coordinates M_loc, real-time wind speed M_wind, visibility M_vis, weather phenomena M_cond, and meteorological update frequency M_freq; The airspace congestion status data S_congest_list includes the sub-variable S_congest: airspace partition number S_id, number of aircraft in the current airspace S_ac_num, airspace capacity limit S_cap, and congestion index S_index; The airport capacity data C_airport_list includes the sub-variable C_airport: airport code C_ap, number of currently available runways C_runway, maximum number of takeoffs and landings per hour C_hourly, number of available parking stands C_park, and ground support capacity C_support.

3. The method for coordinated operation of civil aviation and general aviation according to claim 1, characterized in that, The data cleaning and standardization process in step 1) specifically includes: 11) Data cleaning includes: outlier removal and missing value completion; 111) Outlier Removal: Based on the preset rule DEFAULT_RULE, outlier data is marked and removed, and an anomaly report R_err is generated, which includes the outlier data ID, anomaly type and processing suggestions; 112) Missing value completion: For partially missing sub-variables, fill them with the mean of similar data or call the backup data source; 12) Data standardization includes: standardizing data formats and standardizing data units; 121) Standardized Format: Converts data from different sources into a system-wide format using preset standards; 122) Store the raw data, cleaned and standardized data in a distributed database D_store, and set the data lifecycle D_life to clean up redundant data periodically.

4. The method for coordinated operation of civil aviation and general aviation according to claim 1, characterized in that, The real-time analysis of the processed data in step 1) specifically includes: analysis of busy periods and busy airspaces for civil aviation, analysis of busy periods and busy airspaces for general aviation, and whether there are busy periods and airspaces for civil aviation that require special attention. Analysis of busy periods and busy airspaces in civil aviation, using 30-minute intervals, analyzes airspace and flight frequency, and marks them according to the level of busyness; The analysis of busy periods and busy airspaces in general aviation is performed in 15-minute increments, analyzing airspace and flight operations and marking them according to their level of busyness. Mark civil aviation flights that cannot be adjusted and require special protection or general aviation flight missions that must be performed.

5. The method for coordinated operation of civil aviation and general aviation according to claim 1, characterized in that, Step 2) specifically includes: 21) Flight demand and airspace usage analysis: Calculate the flight plans and airspace carrying capacity for civil aviation and general aviation; 211) Based on the civil aviation flight plan data PlanList, the airspace congestion status data S_congest_list, and the civil aviation airspace demand parameter D_civil, calculate the civil aviation demand saturation S_civil; D_civil = {demand airspace partition D_civil_id, demand time period D_civil_time, demand number of aircraft D_civil_ac, and core mission priority P_civil}, the expression is as follows: S_civil=D_civil_ac / (S_cap_total×P_civil); Among them, S_cap_total is the upper limit of airspace capacity; the civil aviation demand saturation S_civil ranges from 0 to 1.5, and when S_civil ≥ 1.2, it is judged as high demand; 212) Based on the general aviation flight application data GeneralList, mission type A_type, and general aviation airspace demand parameter D_general, calculate the general aviation demand saturation S_general; D_general = {demand airspace partition D_general_id, demand time period D_general_time, demand number of aircraft D_general_ac, and mission urgency P_general}; the expression is as follows: S_general=D_general_ac / (S_cap_total×P_general); The value of S_general ranges from 0 to 1.

5. When S_general ≥ 1.2, it is considered to be in high demand. 213) Every 15 minutes, retrieve the latest civil aviation flight plan data PlanList, general aviation flight application data GeneralList, airspace congestion status data S_congest_list, civil aviation airspace demand parameter D_civil, and general aviation airspace demand parameter D_general from the distributed database D_store. Calculate the civil aviation demand saturation S_civil and general aviation demand saturation S_general based on steps 211) and 212). 22) Real-time allocation calculation; 221) With the goal of maximizing airspace utilization and balancing the needs of both parties, the objective function F_obj is constructed as follows: ； Where α and β are weighting coefficients; S_civil_ac_num is the number of aircraft allocated to civil aviation, S_general_ac_num is the number of aircraft allocated to general aviation, and S_cap_total is the upper limit of airspace capacity; |S_civil-S_general| is the absolute value of the difference between the demand saturation of civil aviation and general aviation, and the smaller the difference, the better the balance. 222) Set constraints; Core mission guarantee constraints: If the core mission priority P_civil is international flights, then the airspace capacity allocated to civil aviation shall be greater than or equal to the number of aircraft required, D_civil_ac × 1.1; if the mission urgency P_general is emergency rescue, then its airspace requirements shall be prioritized and the allocated capacity shall be greater than or equal to the number of aircraft required, D_general_ac. Adjustment range constraints: The adjusted airspace range ≤ airspace height A_air_alt × (1 + airspace adjustable ratio A_air_adjust), and the adjusted usage time ≤ original time period × (1 + A_air_adjust); Safety separation constraints: The airspace allocated to civil aviation and general aviation must maintain a height difference of greater than or equal to 600 meters in space, or a time interval of greater than or equal to 10 minutes; 223) Allocation Result Output: Through multiple rounds of iteration, the optimal allocation scheme R_optim is found to maximize airspace utilization, balance the demands of civil aviation and general aviation, and meet safety constraints; details are as follows: 2231) Based on historical operational data, generate multiple initial allocation schemes, each scheme including: Airspace scope: divided into non-overlapping airspace for civil aviation and airspace for general aviation, based on latitude and longitude coordinates, which also meet the requirements of safe spacing. Time allocation: Based on peak hours and general aviation mission hours, civil aviation priority use time periods and general aviation priority use time periods are divided; Capacity allocation: Based on airspace type, set the maximum number of civil aviation aircraft and the maximum number of general aviation aircraft allowed; A multi-objective optimization algorithm optimized using spatial domain operation characteristics is used to calculate the fitness of each initial scheme. : ； Simultaneously verify the security constraints, and eliminate schemes that do not meet the constraints; 2232) Retain the top 30% of solutions with high fitness, and select the parent cooperative solution probabilistically through a roulette wheel mechanism. The higher the fitness of the solution, the greater the probability of it being selected. Perform single-point crossover on the selected parent cooperative solutions. Randomly fine-tune some parameters to avoid the algorithm getting stuck in local optima. 2233) Repeat the iterative process until the optimal fitness calculation method converges, then output the optimal solution; 23) Compliance check of the allocation plan; 231) Verification indicators: Core mission fulfillment rate: Civil aviation core mission fulfillment rate C_civil = maximum permissible number of civil aviation aircraft R_civil_cap / required number of civil aviation aircraft D_civil_ac; Adjustment compliance rate: Adjustment compliance rate C_adjust = actual adjustment range / airspace adjustable ratio A_air_adjust; Safety interval compliance rate C_safe: Calculated based on existing radar safety interval requirements, that is, if the allocated scheme time and space intervals meet the current safety interval regulations, then there is no safety interval violation; 232) Verification result processing: If all indicators are ≥ preset thresholds, the scheme passes the verification and is published in real time; if any indicators fail to meet the standards, return to step 223) for a second iteration, adjust the constraints, recalculate the allocation scheme, until the verification is passed.

6. The method for coordinated operation of civil aviation and general aviation according to claim 5, characterized in that, Step 3) specifically includes: 31) Set optimization parameters, including: civil aviation plan optimization parameters, general aviation plan optimization parameters, and airspace restrictions and safety parameters; The civil aviation planning optimization parameter Plan_opt is defined as follows: Plan_opt = {No, ETD, ETA, P_on_time, W_on_time, R_peak, T_civil_win}, where No is the plan number, ETD is the planned departure time, ETA is the planned arrival time, P_on_time is the on-time performance requirement, R_peak is the peak route identifier, and T_civil_win is the acceptable adjustment window for civil aviation. The general aviation plan optimization parameter is General_opt, which is defined as follows: General_opt = {Gno, T_general_ori, T_urgent, Gairspace, Galtrange, T_general_deadline, A_takeoff_opt}, where GNo is the application number, T_general_ori is the flight duration, T_urgent is the mission urgency, Gairspace is the original flight area, Galtrange is the original flight range, T_general_deadline is the latest mission completion time, and A_takeoff_opt is the adjusted start time. Airspace restrictions and safety parameters S_safe, S_safe={D_lateral, D_vertical, T_interval, T_peak}, where D_lateral is the lateral safety interval, D_vertical is the longitudinal safety interval, T_interval is the time interval threshold, and T_peak is the peak period for civil aviation routes; 32) With the objectives of minimizing on-time performance loss in civil aviation, minimizing timeliness loss in general aviation, and minimizing conflict, a collaborative optimization scheme F_coordinate_opt is constructed, and the calculation formula is as follows: F_coordinate_opt=A×(1-ΔT_civil / ETD)×W_on_time+B×(1-ΔT_general / T_general_ori)×K_urgent+γ×(1-C_total); Where A is the on-time rate weight for civil aviation, A=0.4; B is the timeliness weight for general aviation, B=0.35; γ is the conflict degree weight, γ=0.25; ETD is the original departure time of civil aviation flights; 1-C_total is the conflict degree optimization index; K_urgent is the weight coefficient of mission timeliness urgency; W_on_time is the weight coefficient of on-time rate requirement; The civil aviation on-time performance loss index ΔT_civil = |adjusted takeoff time F_takeoff_opt - original takeoff time ETD|, ΔT_civil ≤ T_civil_win; The general aviation timeliness loss index ΔT_general = |adjusted mission duration T_general_opt - flight duration T_general_ori|, and the adjusted mission duration T_general_opt ≤ the latest mission completion time T_general_deadline - adjusted start time; 321) Safety interval constraints; Lateral constraint: The spatial distance D between civil aviation and general aviation aircraft at any given time, where D = ≥D_lateral, where (X1,Y1) are the coordinates of civil aviation flights, and (X2,Y2) are the coordinates of general aviation aircraft. Vertical constraint: At any given time, the altitude distance H between civil aviation and general aviation aircraft, H = |F_alt_opt - A_alt_opt| ≥ D_vertical, where F_alt_opt is the adjusted altitude of the civil aviation flight and A_alt_opt is the adjusted altitude of the general aviation aircraft. 322) Airspace capacity constraint: For any airspace partition S_id passed through by the optimized route, the total number of aircraft at any time is ≤ S_cap; 323) Time window constraints, including: takeoff time window constraints for civil aviation flights and mission duration window constraints for general aviation aircraft; The departure time window constraint for civil aviation flights is specifically as follows: the adjusted departure time must fall within the time interval between the original departure time minus the acceptable adjustment window duration and the original departure time plus the acceptable adjustment window duration, where F_takeoff_opt ∈ [F_takeoff_ori - T_civil_win, F_takeoff_ori + T_civil_win]. Here, the adjusted departure time F_takeoff_opt refers to the actual departure time of the optimized civil aviation flight; the original departure time ETD refers to the departure time initially set in the flight plan; and the acceptable adjustment window T_civil_win refers to the maximum allowable delay or advance time for the flight. Adjustments within this time range will not have a significant impact on the flight's on-time performance. The mission duration window constraint for general aviation aircraft is as follows: the adjusted mission duration must be less than or equal to the mission's latest completion time minus the adjusted start time, T_general_opt ≤ T_general_deadline - A_takeoff_opt. Here, the adjusted mission duration T_general_opt refers to the total time required for the general aviation to complete the mission after optimization, including flight time and possible waiting time; the mission's latest completion time T_general_deadline refers to the deadline when the general aviation must complete the mission; and the adjusted start time A_takeoff_opt refers to the actual start time of the general aviation mission after optimization. 324) Divide the airspace into 100×100 grid nodes, mark the nodes of civil aviation peak routes as high-cost nodes, and set the weight coefficient W_grid to 1.8, which is dynamically adjusted according to the busyness of peak routes, conflict risk, etc. 325) Using general aviation take-off and landing points as the starting / ending points, search for alternative detour routes that avoid high-cost nodes, and calculate the spatial conflict degree C_space for each route; 326) By adjusting the takeoff time of civil aviation, the flight time of general aviation, the flight altitude, and the detour routes for conflict avoidance, the civil aviation and general aviation plans can be coordinated and optimized.

7. The method for coordinated operation of civil aviation and general aviation according to claim 6, characterized in that, Step 325) specifically involves: for each candidate detour route, traversing all its mapped grid nodes, retrieving the weight coefficient W_grid of each node from the database D_store to form the weight set W_route for that route, and summing the weights of all nodes in the weight set to obtain the total route weight Sum_W = Σ(W_grid), where... The total number of grid nodes after route mapping is N_route. The total weight is divided by the total number of nodes to obtain the average node weight of the route, Avg_W = C_space = Sum_W / N_route. The average node weight of the route is the spatial conflict degree C_space. The spatial conflict degree C_space is a quantitative indicator that measures the degree of overlap or proximity between general aviation alternative detour routes and civil aviation flights in space. It is used to assess the conflict risk of the route. The higher the value, the more high-cost nodes the route passes through, and the higher the conflict risk.

8. The method for coordinated operation of civil aviation and general aviation according to claim 1, characterized in that, Step 4) specifically includes: adjusting the flight urgency level and airspace node weight in response to sudden weather, equipment failure, or emergency missions, repeating steps 1) to 3), constructing an emergency plan, prioritizing high-priority flight missions, and issuing an alarm if an emergency plan cannot be generated, and simultaneously activating the manual collaboration mode.

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