Low altitude intelligent flight management system and method

Abstract

The application provides a low-altitude intelligent flight management system and method, and belongs to the technical field of low-altitude flight management. First, low-altitude flight application information (including flight task types and the like) and airspace basic state data (including approved flight plan trajectory information and the like) are integrated to obtain a flight demand information set. Then, based on the flight demand information set, flight conflict prediction is performed in combination with real-time dynamic data of the airspace to obtain a conflict prediction result containing information such as a conflict period. According to the conflict prediction result, low-altitude flight safety rules are applied to generate a flight path adjustment scheme containing adjusted flight trajectory coordinates and the like. Flight control instructions matching the control protocol are generated based on the flight path adjustment scheme. Instruction execution feedback of the flight target is received, which is compared with the flight path adjustment scheme and the airspace basic state data is updated, thereby effectively improving the safety and management efficiency of low-altitude flight.

Description

Technical Field

[0001] This invention relates to the field of low-altitude flight management technology, and more specifically, to a low-altitude intelligent flight management system and method. Background Technology

[0002] In the field of low-altitude flight, with the increasing frequency of low-altitude flight activities, such as drone logistics delivery, low-altitude tourism, and aerial photography, higher demands are being placed on the efficiency and safety of low-altitude flight management. Traditional low-altitude flight management methods mainly rely on manual scheduling and simple airspace planning. When processing flight applications, they often only review the legality and basic feasibility of each flight mission in isolation, without fully integrating low-altitude flight application information with basic airspace status data.

[0003] During flight, the assessment of flight conflicts is often delayed and cursory, typically involving manual intervention only after a conflict has occurred or is about to occur, lacking a proactive conflict prediction mechanism. Furthermore, when flight conflicts arise, the formulation of flight path adjustment plans lacks systematicity and scientific rigor, relying heavily on the experience of management personnel, making it difficult to guarantee that the adjusted paths meet both safety requirements and the actual needs of the flight mission. In addition, traditional management methods are not timely or accurate in tracking and providing feedback on the execution of flight commands, failing to update basic airspace status data in real time. This results in a lack of accurate data for the scheduling and management of subsequent flight missions, easily leading to new conflicts and safety hazards. Summary of the Invention

[0004] In view of the aforementioned problems, and in conjunction with the first aspect of the present invention, embodiments of the present invention provide a low-altitude intelligent flight management method, the method comprising: By integrating low-altitude flight application information with basic airspace status data, a flight demand information set is obtained. The low-altitude flight application information includes flight mission type, expected flight time period, initial take-off and landing coordinates, and flight altitude requirement. The basic airspace status data includes trajectory information of approved flight plans, distribution of fixed obstacles in the airspace, and temporary restricted airspace range. Based on the flight demand information set, and combined with real-time dynamic airspace data, flight conflict prediction is performed to obtain conflict prediction results. The conflict prediction results include conflict time periods, associated flight target identifiers, and conflict trajectory segments of the flight mission to be evaluated. Based on the conflict prediction results, a flight path adjustment plan is generated by applying low-altitude flight safety rules. The flight path adjustment plan includes the adjusted flight trajectory coordinates, flight altitude adjustment range, and flight speed control requirements. The low-altitude flight safety rules include conflict response rules for path adjustment, altitude adjustment, and speed adjustment. Based on the flight path adjustment scheme, flight control commands are generated. The flight control commands include trajectory execution content, altitude adjustment content, and speed control content. The flight control commands are matched with the control protocol corresponding to the flight mission type. The system receives instruction execution feedback from the flight target, compares the instruction execution feedback with the flight path adjustment plan, and updates the airspace basic state data based on the comparison results. The instruction execution feedback includes the flight target's real-time position execution record, real-time altitude execution record, and real-time speed execution record.

[0005] In another aspect, embodiments of the present invention also provide a low-altitude intelligent flight management system, including a processor and a machine-readable storage medium connected to the processor. The machine-readable storage medium is used to store programs, instructions, or code, and the processor is used to run the programs, instructions, or code in the machine-readable storage medium to implement the above-described method.

[0006] Based on the above, this invention integrates low-altitude flight application information with basic airspace status data to form a flight demand information set. Based on this set and combined with real-time dynamic airspace data, flight conflict prediction is performed, enabling the early detection of potential conflicts. Detailed information such as the conflict time period, associated flight target identifiers, and conflict trajectory segments of the flight mission to be evaluated is accurately provided. Based on the conflict prediction results, low-altitude flight safety rules are applied to generate flight path adjustment schemes, ensuring that the adjusted flight trajectory, altitude, and speed meet both safety requirements and the actual needs of the flight mission to the greatest extent possible, thus improving the scientific and rational nature of flight management. Flight control commands matching the flight mission type control protocol are generated based on the flight path adjustment scheme. By receiving and executing commands from flight targets and comparing them with the adjustment scheme, the basic airspace status data is updated in a timely manner, effectively improving the safety and management efficiency of low-altitude flights. Attached Figure Description

[0007] Figure 1 This is a schematic diagram of the execution flow of the low-altitude intelligent flight management method provided in an embodiment of the present invention.

[0008] Figure 2 This is a schematic diagram of the hardware architecture of the low-altitude intelligent flight management system provided in an embodiment of the present invention. Detailed Implementation

[0009] The present invention will now be described in detail with reference to the accompanying drawings. Figure 1 This is a flowchart illustrating a low-altitude intelligent flight management method according to an embodiment of the present invention. The low-altitude intelligent flight management method will be described in detail below.

[0010] Step S110: Integrate low-altitude flight application information with airspace basic status data to obtain a flight demand information set. The low-altitude flight application information includes flight mission type, expected flight time period, initial take-off and landing coordinates, and flight altitude requirement. The airspace basic status data includes trajectory information of approved flight plans, distribution of fixed obstacles in the airspace, and temporary restricted airspace range.

[0011] This embodiment uses a medical supply drone delivery mission within a city as an example. The system receives a low-altitude flight application for this mission, which is a type of cargo flight, specifically medical supply delivery. The expected flight time is from some time in the morning to some time around noon. The initial take-off and landing coordinates are as follows: the starting point is the take-off and landing point of a medical supply warehouse in the eastern part of the city, and the ending point is the take-off and landing point of a hospital in the western part of the city. The required flight altitude is within the medium altitude range, which is determined according to the recommended altitude range for medical supply delivery missions in the city's low-altitude flight management regulations.

[0012] The airspace basic status data was retrieved, including the trajectory information of approved flight plans, which included the flight trajectories of multiple drones within similar time periods. For example, the approved flight plan trajectory of a drone used for urban express delivery covered a coordinate sequence from the express sorting center in the north of the city to multiple delivery points in the south of the city, with each coordinate point corresponding to a specific time node. Another drone used for power line inspection had its approved flight trajectory distributed along power transmission lines in the east of the city. The distribution of fixed obstacles in the airspace included the location information of high-rise buildings, TV towers, communication base stations, etc., within the city. For example, the base coordinates and top height of a high-rise building in the city center were recorded in detail; the location coordinates and overall height of a TV tower on the city edge were also accurately marked. The temporarily restricted airspace area was a large event hosting area in the central part of the city. This large event hosting area was temporarily designated as restricted airspace during the expected flight period of the aforementioned medical supply delivery mission, and its boundary coordinates were clearly defined. The aforementioned low-altitude flight application information is integrated with the basic airspace status data to form a flight demand information set. This flight demand information set fully includes all application parameters for medical supply delivery missions, as well as information on existing flight plans, obstacles, and temporary restricted areas within the airspace.

[0013] Step S120: Based on the flight demand information set, and combined with real-time dynamic airspace data, perform flight conflict prediction to obtain conflict prediction results. The conflict prediction results include conflict time periods, associated flight target identifiers, and conflict trajectory segments of the flight mission to be evaluated.

[0014] Based on the aforementioned set of flight demand information, flight conflict prediction is initiated by combining real-time airspace dynamic data. This real-time airspace dynamic data is acquired in real-time through monitoring equipment deployed throughout the city, including the real-time location, speed, and altitude of all drones currently in flight within the airspace. For example, the drone used for urban express delivery is detected to be currently located over a street in the central part of the city, maintaining a stable speed, and flying at an altitude within its approved range. Another drone providing emergency communication support is located over a mountainous area in the western part of the city, with a slower speed and a relatively higher altitude.

[0015] By analyzing and comparing the aforementioned real-time data with relevant data in the flight demand information set, it is determined whether the expected flight trajectory of the medical supply delivery mission conflicts with the flight trajectories of other drones that are currently flying or have approved flight plans. This allows for the identification of conflict periods, associated flight targets, and conflict trajectory segments of the flight mission to be evaluated, thus forming a conflict prediction result.

[0016] Step S121: Extract the expected trajectory content of the flight mission to be evaluated from the flight demand information set. The expected trajectory content includes the expected flight path coordinates derived from the initial take-off and landing coordinates and the flight mission type, the expected flight speed determined by the flight mission type, and the expected flight altitude change determined by the flight altitude requirement.

[0017] The projected trajectory of the medical supply delivery mission to be evaluated was extracted from the aforementioned flight demand information set. Based on the initial takeoff and landing coordinates—that is, the coordinates of the takeoff and landing points from the medical supply warehouse in the eastern part of the city to the hospital in the western part of the city—and considering the mission type of medical supply delivery, the projected flight path coordinates were derived. Since the medical supply delivery mission requires a direct path to ensure timeliness and avoid known fixed obstacles, the projected flight path coordinate sequence starts from the starting coordinates, passes through multiple intermediate coordinate points avoiding obstacles, and finally reaches the destination coordinates. These coordinate points together constitute the projected flight path.

[0018] The projected flight speed is determined based on the type of flight mission: medical supply delivery. Considering the time-sensitive requirements of medical supplies and the payload capacity of the drone, and referencing the typical flight speeds of similar medical supply delivery drones, the projected flight speed for this mission is determined. This projected flight speed ensures both timely delivery of supplies and flight stability and safety.

[0019] The expected flight altitude change is determined by the flight altitude requirements. The flight altitude requirement for this medical supply delivery mission is in the medium altitude range. In the expected flight trajectory, the flight altitude gradually increases from the initial altitude to the lower limit of this medium altitude range during the takeoff phase, and then remains within this range for most of the flight path. Near the destination, the flight altitude gradually decreases to the takeoff and landing altitude of the destination, forming a continuous expected flight altitude change curve.

[0020] Step S122: Collect the real-time position, real-time speed, and real-time flight altitude of each flying target in the airspace to form the real-time dynamic data of the airspace.

[0021] Monitoring equipment distributed across key locations throughout the city, such as low-altitude radar, drone detectors, and data interfaces connected to various drone operators, collects real-time data on all flying targets within the airspace. For the aforementioned drones used for urban express delivery, their real-time position coordinates are collected at short intervals. These coordinates are acquired through the drone's built-in positioning system and transmitted to the monitoring center. Simultaneously, their real-time speed is collected, calculated based on the drone's power system parameters and real-time motion status. Their real-time flight altitude is also collected, measured using devices such as barometric pressure sensors.

[0022] For drones providing emergency communication support, their real-time position, speed, and altitude are collected at the same time intervals. All collected data is then aggregated and processed, and outliers, such as those with excessively large position coordinate deviations due to signal interference, are removed. This process ultimately creates real-time dynamic airspace data, which is continuously updated over time to reflect the latest status of all flying targets within the airspace.

[0023] Step S123: Associate the real-time position of the flight target in the real-time dynamic data of the airspace with the coordinates of the expected flight path, and deduce the predicted flight trajectory of the flight target in the future time period by combining the real-time speed of the flight target.

[0024] The real-time positions of each flying target in the real-time dynamic airspace data are correlated with the coordinates of the expected flight path of the medical supply delivery mission. For example, the real-time position coordinates of the drone used for urban express delivery are compared with the coordinates of the expected flight path of the medical supply delivery mission to determine their relative spatial position.

[0025] By combining the real-time speed of the delivery drone, its predicted flight trajectory for future periods is derived. Based on the drone's real-time position and speed direction, its possible location at each subsequent time point is predicted. Connecting these locations sequentially forms the predicted flight trajectory for the drone's future periods. Similarly, other flying targets, such as emergency communication support drones, are processed in the same way to derive their predicted flight trajectories for future periods.

[0026] Step S1231: Extract the real-time position, real-time speed, and real-time flight altitude of the flight target from the real-time dynamic data of the airspace, and extract the current flight mission type of the flight target from the approved flight plan trajectory information.

[0027] Specific information about each flying target is extracted from real-time dynamic airspace data. For the aforementioned drone used for urban express delivery, its real-time position coordinates are extracted as a specific latitude, longitude, and altitude; its real-time speed is extracted as a specific value and direction; and its real-time flight altitude is extracted as a specific value. Simultaneously, the approved flight plan trajectory information reveals that the drone's current flight mission type is urban express delivery, which falls under the category of cargo flight missions.

[0028] For emergency communication support drones, their real-time location, real-time speed, and real-time flight altitude are extracted. From the approved flight plan trajectory information, it is known that their current flight mission type is emergency communication support, which falls under the category of operational flight missions.

[0029] Step S1232: Determine the motion law of the flight target based on its current flight mission type. If the current flight mission type of the flight target is a cargo flight mission or a passenger flight mission, determine its motion law as uniform linear motion; if the current flight mission type of the flight target is an operational flight mission, determine its motion law as variable speed curvilinear motion.

[0030] Based on the extracted current flight mission type of the flying target, its motion pattern is determined. The aforementioned drone used for urban express delivery has a current flight mission type of cargo flight, therefore its motion pattern is determined to be uniform linear motion, that is, the speed and direction of the drone are relatively stable during flight, and the flight path is approximately a straight line.

[0031] The current flight mission type of the emergency communication support drone is an operational flight mission. It needs to patrol back and forth in a specific area to ensure communication signals. Therefore, its motion law is determined to be variable speed curvilinear motion, that is, the speed and direction of the drone will change continuously according to the operational requirements, and the flight path will present a curvilinear shape.

[0032] Step S1233: If the motion pattern is uniform linear motion, determine the flight direction according to the real-time velocity direction of the flying target, deduce the flight position of each time node in the future period by combining the real-time position, sort the flight positions of each time node by time period, and form a predicted flight trajectory.

[0033] For urban delivery drones that move at a constant velocity in a straight line, their flight direction is determined by their real-time velocity direction. For example, if their real-time velocity direction is from the center of the city to the south, their flight direction is determined to be south.

[0034] Based on the drone's real-time location and following the principle of uniform linear motion, the flight position at each time point in the future is deduced. It is assumed that after the first time interval following the current time point, the drone will fly south for a distance to reach a new position; after the second time interval, it will continue flying south for the same distance to reach the next position, and so on. The derived flight positions at each time point are then ordered chronologically and connected sequentially to form the predicted flight trajectory of the drone for the future period.

[0035] Step S1234: If the motion pattern is a variable speed curve motion, extract the speed change pattern in the historical flight trajectory of the flight target, combine the real-time speed to deduce the flight speed and direction of each time node in the future period, and combine the real-time position to deduce the flight position of each time node. Sort the flight positions of each time node by time period to form a predicted flight trajectory.

[0036] For emergency communication support drones exhibiting variable-speed curvilinear motion, the speed variation patterns in their historical flight trajectories were extracted. Analysis of their historical flight data revealed that during communication support operations, the drone could decelerate in some areas and accelerate in others, depending on signal coverage requirements, and its flight direction would frequently adjust to cover a wider area, thus forming a specific speed variation pattern.

[0037] Based on the current real-time speed of the drone and the extracted speed change patterns, the flight speed and direction at each time point in the future can be deduced. For example, based on historical patterns, it is expected that in the first time interval, its speed will gradually decrease and its flight direction will deviate to the southeast; in the second time interval, its speed will gradually increase and its flight direction will deviate to the southwest, and so on.

[0038] By combining the drone's real-time location with the derived flight speed and direction at each time point, the flight position at each time point is calculated. These flight positions are then sorted chronologically and connected sequentially to form the predicted flight trajectory of the drone for future periods.

[0039] Step S1235: Associate the derived predicted flight trajectory with the distribution of fixed obstacles in the airspace, associate the predicted flight trajectory with the range of temporary restricted airspace, and associate the predicted flight trajectory with the corresponding time period to form a complete predicted flight trajectory of the flight target for the future time period.

[0040] The predicted flight trajectories of urban delivery drones and emergency communication support drones derived above are correlated with the distribution of fixed obstacles in the airspace. For example, it is checked whether the predicted flight trajectory of urban delivery drones passes through areas with tall buildings in the city center. If the trajectory overlaps with the location of a tall building, the location and corresponding time need to be marked in the predicted flight trajectory to indicate the potential collision risk.

[0041] Simultaneously, the predicted flight trajectory will be correlated with the temporary restricted airspace. For the predicted flight trajectory of urban delivery drones, it will be checked whether they enter the temporary restricted airspace of a large event area in the central part of the city. If the trajectory is expected to enter this area at a certain time, the time period and the corresponding location will be clearly marked in the predicted flight trajectory.

[0042] Furthermore, the predicted flight trajectory is correlated with the corresponding time period, that is, the specific time node corresponding to each location point on the predicted flight trajectory is determined. Through the above correlation operation, a complete predicted flight trajectory for the future time period of the flight target is formed. This predicted flight trajectory not only includes spatial location information, but also time information and correlation information with obstacles and restricted airspace.

[0043] Step S124: Compare the predicted flight path coordinates of the flight mission to be evaluated with the predicted flight trajectory of the flight target by time period, and mark the spatially overlapping trajectory segments in the same time period.

[0044] The coordinates of the predicted flight path of the medical supply delivery mission are compared with the predicted flight trajectories of each target according to time period. For example, the coordinates of the predicted flight path of the medical supply delivery mission during a certain time period in the morning are compared with the predicted flight trajectory of the urban express delivery drone during the same time period to check whether there is any overlap between the coordinates.

[0045] If, within a certain time period, a segment of coordinates on the predicted flight path of a medical supplies delivery mission completely overlaps with or is very close to a segment of coordinates on the predicted flight trajectory of an urban express delivery drone, then that time period and the corresponding two trajectory segments are marked and identified as spatially overlapping trajectory segments. Similarly, the predicted flight trajectories of other flight targets are compared and marked in a similar manner to identify all possible spatially overlapping trajectory segments.

[0046] Step S125: Correlate the expected flight altitude change of the flight mission to be evaluated with the real-time flight altitude of the flight target to deduce the predicted flight altitude of the flight target in the future time period. Then, compare the expected flight altitude change with the predicted flight altitude by time period and mark the time period in which the flight altitudes of the two overlap.

[0047] By correlating the predicted flight altitude changes of medical supply delivery missions with the real-time flight altitudes of various flight targets, the predicted flight altitudes of each target in future time periods can be derived. For example, for urban express delivery drones, their future flight altitudes in various time periods can be derived based on their current real-time flight altitude and the altitude change characteristics determined by the type of flight mission.

[0048] Then, the predicted flight altitude changes of the medical supply delivery mission are compared with the derived predicted flight altitudes of each flight target according to time periods. If the predicted flight altitude range of the medical supply delivery mission overlaps with the predicted flight altitude range of a certain flight target within a certain time period, then that time period is marked as a high-overlap period.

[0049] Step S1251: Extract the real-time flight altitude and real-time speed of the flight target from the real-time dynamic data of the airspace, and determine its altitude change pattern by combining the current flight mission type of the flight target.

[0050] The real-time flight altitude and speed of each flying target are extracted from real-time dynamic airspace data. For urban express delivery drones, the current real-time flight altitude is extracted as a specific value, and the real-time speed is a stable value. Considering its cargo flight mission type, drones of this type typically maintain a relatively stable altitude during flight to improve flight efficiency and safety; therefore, its altitude change pattern is determined to be maintaining a constant altitude.

[0051] For emergency communication support drones, their real-time flight altitude and speed are extracted and combined with their operational flight mission type. Drones of this operational flight mission type need to adjust their flight altitude according to the terrain and communication requirements of the operational area. Therefore, their altitude change pattern is determined to be adjusting the altitude according to a preset rhythm. For example, when flying over mountainous areas, the altitude can be adjusted according to the undulations of the terrain to maintain a suitable signal coverage range.

[0052] Step S1252: If the altitude change pattern of the flight target is to maintain a constant altitude, the predicted flight altitude at each time point in the future period is the current real-time flight altitude.

[0053] For urban delivery drones that maintain a constant altitude, since their altitude does not change significantly during flight, the predicted flight altitude at each time point in the future will be equal to the current real-time flight altitude. For example, if the current real-time flight altitude is a certain value, then the predicted flight altitude at the first time point, the second time point, and so on, will all be that value.

[0054] Step S1253: If the altitude change pattern of the flight target is to adjust the altitude according to a preset rhythm, extract the altitude adjustment rhythm from the historical flight trajectory of the flight target, and combine it with the real-time flight altitude to deduce the predicted flight altitude at each time node in the future period.

[0055] For emergency communication support drones whose altitude change pattern follows a preset rhythm, the altitude adjustment rhythm was extracted from their historical flight trajectories. Analysis of historical data revealed that in similar past operations, the drone's altitude would rise or fall at certain intervals, forming a specific adjustment rhythm. For example, it would rise a certain altitude every five minutes, repeat this three times, and then descend a certain altitude every five minutes.

[0056] Based on the drone's current real-time flight altitude and the altitude adjustment rhythm extracted above, the predicted flight altitude for each time point in the future period is derived. For example, if the current real-time flight altitude is a certain value, according to the historical rhythm, it is expected that the altitude will increase by a certain amount at the first time point, continue to increase by a certain amount at the second time point, remain at the same altitude at the third time point, and decrease by a certain amount at the fourth time point, and so on.

[0057] Step S1254: Sort the predicted flight altitudes of each time point according to the time period to form a sequence of predicted flight altitudes of the flight target for future time periods.

[0058] The predicted flight altitudes of each flight target at various future time points, derived above, are sorted according to their corresponding time periods. For urban express delivery drones, the predicted flight altitudes at each time point are the same, forming a sequence with unchanged values ​​after sorting. For emergency communication support drones, the predicted flight altitudes at each time point are arranged sequentially according to the derived results, forming a sequence containing different altitude values. This sequence is the predicted flight altitude sequence of the flight targets for future time periods.

[0059] Step S1255: Extract the expected flight altitude change from the expected trajectory content of the flight mission to be evaluated, and determine the altitude range corresponding to the expected flight altitude change in each future time period.

[0060] The projected flight altitude changes are extracted from the predicted trajectory of the medical supply delivery mission. These changes show a trend of gradually increasing altitude from the takeoff point, stabilizing after reaching a certain altitude, and then gradually decreasing again near the destination. Based on this trend, the corresponding altitude ranges for each future time period are determined. For example, in the first time period after takeoff, the altitude range is from the initial takeoff altitude to the lower limit of the intermediate altitude range; in the main flight period, the altitude range is within the intermediate altitude range; and in the last time period near the destination, the altitude range is from the lower limit of the intermediate altitude range to the final takeoff and landing altitude.

[0061] Step S1256: Compare the predicted flight altitude sequence with the altitude range of each time period of the expected flight altitude change according to the corresponding time period.

[0062] The predicted flight altitude sequence of each flight target is compared with the predicted flight altitude range of the medical supply delivery mission for each time period. For example, the predicted flight altitude of urban express delivery drones during a certain time period in the morning is compared with the predicted flight altitude range of the medical supply delivery mission during the same time period; the corresponding values ​​in the predicted flight altitude sequence of emergency communication support drones during the same time period are compared with the predicted flight altitude range of that time period.

[0063] Step S1257: If the altitude value in the predicted flight altitude sequence within any time period is within the altitude range of the expected flight altitude change for that time period, mark that time period as an altitude overlap period.

[0064] During the comparison process, if it is found that the altitude value of a certain flight target in the predicted flight altitude sequence falls within the altitude range of the predicted flight altitude change of the medical supply delivery mission during that time period, then that time period is marked as an altitude overlap period. For example, if the predicted flight altitude of a city express delivery drone is a certain value during a certain time period in the morning, and the predicted flight altitude range of the medical supply delivery mission during that time period includes that value, then that time period is marked as an altitude overlap period.

[0065] Step S1258: Statistically analyze all overlapping time periods, associate the predicted flight altitude value and expected flight altitude range corresponding to each overlapping time period, and form a record of overlapping time periods.

[0066] All marked high-altitude overlapping time periods are statistically analyzed, and each overlapping time period is associated with the predicted flight altitude of the corresponding flight target and the expected flight altitude range of the medical supply delivery mission. For example, the high-altitude overlapping time period of an urban express delivery drone in a certain morning is associated with its predicted flight altitude for that time period and the expected flight altitude range of the medical supply delivery mission during that time period; similarly, the high-altitude overlapping time period of an emergency communication support drone is associated with its corresponding predicted flight altitude and expected flight altitude range. This association information is compiled and summarized to form a high-altitude overlapping time period record, which clearly presents the specific details of each high-altitude overlap.

[0067] Step S126: Associate the spatially overlapping trajectory segments with the highly overlapping time periods to determine the conflict time periods in which the flight mission to be evaluated and each flight target simultaneously have spatial and high-altitude overlap, and the conflict trajectory segments corresponding to the conflict time periods.

[0068] By performing correlation analysis between the spatially overlapping trajectory segments obtained above and the highly overlapping time periods, we can identify situations where both spatially overlapping trajectory segments and highly overlapping time periods exist. For example, if a medical supply delivery mission and an urban express delivery drone not only have spatially overlapping trajectory segments within a certain time period, but this time period is also a highly overlapping time period, then this time period is identified as the conflict time period between the two, and the corresponding spatially overlapping trajectory segment is the conflict trajectory segment.

[0069] Similarly, the spatial overlap and high overlap periods between medical supply delivery missions and other flight targets were correlated to identify all conflict periods and corresponding conflict trajectory segments.

[0070] Step S127: Associate the conflict period, the conflict trajectory segment with the identifier of the corresponding flight target, the operating entity, and the current flight mission type to form the conflict prediction result.

[0071] The identified conflict time periods and trajectory segments are associated with the corresponding flight target's identification information (such as the drone's unique serial number), operating entity (such as the name of the courier company or the name of the communications support company), and current flight mission type (such as express delivery or emergency communications support). For example, conflict time periods and trajectory segments related to urban express delivery drones are associated with the drone's serial number, the courier company it belongs to, and the urban express delivery mission type; conflict information related to emergency communications support drones is associated with their corresponding identification, operating entity, and mission type. Through this association, a complete conflict prediction result is formed, which includes detailed information on all conflicts.

[0072] Step S130: Based on the conflict prediction result, a flight path adjustment plan is generated by applying the low-altitude flight safety rules. The flight path adjustment plan includes the adjusted flight trajectory coordinates, flight altitude adjustment range, and flight speed control requirements. The low-altitude flight safety rules include conflict response path adjustment rules, altitude adjustment rules, and speed adjustment rules.

[0073] Based on the aforementioned conflict predictions, flight path adjustment plans were generated using the Low-Altitude Flight Safety Rules. These rules are formulated based on national and local regulations governing low-altitude flight management. The conflict response path adjustment rules specify how to adjust flight paths to avoid conflict under different circumstances; the altitude adjustment rules clarify the scope and methods of altitude adjustment; and the speed adjustment rules regulate speed control requirements.

[0074] Based on the specific circumstances of each conflict in the conflict prediction results, such as the length of the conflict period, the location of the conflict trajectory segment, and the mission type of the associated flight targets, and in accordance with the various rules in the low-altitude flight safety rules, the adjusted flight trajectory coordinates, flight altitude adjustment range, and flight speed control requirements are formulated to jointly constitute the flight path adjustment plan.

[0075] Step S131: Extract the conflict time period, conflict trajectory segment and corresponding flight target information from the conflict prediction result. The corresponding flight target information includes the flight target identifier, the current flight mission type and the historical flight trajectory pattern.

[0076] Extract the key information needed from the conflict prediction results, including the conflict time period, such as the specific time period of conflict with urban express delivery drones and the specific time period of conflict with emergency communication support drones; the conflict trajectory segment, that is, the trajectory segment of the medical supply delivery mission within the conflict time period; and the corresponding flight target information, such as the identification of the urban express delivery drone, the current flight mission type is urban express delivery, and its historical flight trajectory pattern is uniform straight flight with stable altitude; and the identification of the emergency communication support drone, the current flight mission type is emergency communication support, and its historical flight trajectory pattern is variable speed curve flight with altitude adjusted according to a preset rhythm.

[0077] Step S132: Retrieve the low-altitude flight safety rules, which include path adjustment priority rules corresponding to different conflict period lengths, avoidance direction rules for different flight mission types, flight altitude adjustment range rules, and flight speed adjustment interval rules.

[0078] The system retrieves pre-defined low-altitude flight safety rules. These rules specify priority rules for path adjustments based on the length of conflict periods. For longer conflict periods, priority is given to adjusting the path to completely avoid the conflict; for shorter conflict periods, speed or altitude can be adjusted appropriately to avoid conflict. Avoidance direction rules are clearly defined for different flight mission types. Medical supply delivery missions, being high-priority missions, can request delivery drones to avoid conflict in a specific direction when conflicting with express delivery drones, while the drone itself can choose the optimal avoidance direction. When conflicting with emergency communication support drones, the avoidance direction must be determined based on the urgency of both missions. Altitude adjustment range rules define the upper and lower limits for different types of drones when adjusting altitude to ensure a safe altitude difference with other flight targets. Speed ​​adjustment range rules specify the speed adjustment range for various types of drones under different conditions, ensuring effective avoidance without affecting the overall flight plan.

[0079] Step S133: Determine the priority order of path adjustment based on the length of the conflict period using the path adjustment priority rule.

[0080] Based on the length of the extracted conflict period, a path adjustment priority rule is applied to determine the order of path adjustments. For example, if the conflict period with urban express delivery drones is relatively long, the rule dictates that the path involved in that conflict should be adjusted first; if the conflict period with emergency communication support drones is relatively short, the adjustment priority is relatively low. This method clarifies which conflicts require priority handling when generating flight path adjustment plans.

[0081] Step S134: Based on the current flight mission type of the corresponding flight target, apply the avoidance direction rule to determine the avoidance direction of the flight mission to be evaluated.

[0082] Based on the current flight mission type of the corresponding flight target, the avoidance direction rules are applied to determine the avoidance direction for medical supply delivery missions. For urban express delivery drones, whose mission type is general freight and has lower priority than medical supply delivery missions, the rules allow medical supply delivery missions to choose to avoid obstacles to the left or right. Considering the airspace conditions, avoiding obstacles to the right is more reasonable and can avoid more obstacles. For emergency communication support drones, whose missions are urgent, the rules require medical supply delivery missions to choose to avoid obstacles in a direction away from their operating area, such as to the north, to avoid interfering with their communication support work.

[0083] Step S135: Based on the avoidance direction, select an avoidance inflection point region between the starting coordinates and the ending coordinates of the conflict trajectory segment. The avoidance inflection point region is far from the spatial overlap region of the predicted flight trajectory of the flight target.

[0084] Based on the determined avoidance direction, an avoidance inflection point area is selected between the starting and ending coordinates of the conflict trajectory segment. For example, if the starting coordinates of a conflict trajectory segment with an urban delivery drone are at one location and the ending coordinates are at another location, with the avoidance direction to the right, a range far from the area overlapping with the predicted flight trajectory of the urban delivery drone is selected near the middle of this trajectory segment as the avoidance inflection point area. This avoidance inflection point area should ensure that the medical supply delivery drone can avoid the conflict after turning. Similarly, for conflict trajectory segments with emergency communication support drones, a corresponding avoidance inflection point area is selected according to the avoidance direction.

[0085] Step S136: Select candidate inflection points within the avoidance inflection point area. The candidate inflection points must satisfy the condition that the lines connecting the candidate inflection point to the starting point coordinates of the conflict trajectory segment and the lines connecting the candidate inflection point to the ending point coordinates of the conflict trajectory segment do not pass through the area where fixed obstacles are distributed in the airspace.

[0086] Candidate inflection points are selected within the chosen avoidance inflection point area, and these candidate inflection points must meet specific conditions. Taking the avoidance inflection point area for a conflict with an urban delivery drone as an example, several possible inflection point locations are initially selected within this area. Then, each candidate inflection point is checked by drawing a line from the candidate inflection point to the coordinates of the starting point of the conflict trajectory segment, and checking whether this line passes through areas with fixed obstacles in the airspace, such as high-rise buildings in the city center. If the line passes through an obstacle area, the candidate inflection point does not meet the requirements; if it does not, the candidate inflection point is retained. Next, a line is drawn from the candidate inflection point to the coordinates of the ending point of the conflict trajectory segment, and the same check is performed. Only candidate inflection points that do not pass through obstacle areas are ultimately retained.

[0087] Step S1361: Extract the distribution of fixed obstacles in the airspace from the basic airspace status data, and determine the location coordinates and coverage of each fixed obstacle.

[0088] Extract the distribution information of fixed obstacles in the airspace from the basic airspace status data. For high-rise buildings in the city center, determine the location coordinates (including longitude and latitude) of their bases and their coverage area, which includes the building's footprint and height. For communication base stations, determine the location coordinates of their tower bases and the height coverage area of ​​the tower. Using this information, clarify the specific location and impact range of each fixed obstacle in the airspace.

[0089] Step S1362: Select multiple initial candidate inflection points within the avoidance inflection point area, wherein the initial candidate inflection points are evenly distributed within the avoidance inflection point area.

[0090] Within the avoidance inflection point area, multiple initial candidate inflection points are selected according to the principle of uniform distribution. For example, the avoidance inflection point area is divided into several small squares, and an initial candidate inflection point is selected at the center of each small square to ensure that these inflection points are relatively evenly distributed within the area, thereby increasing the probability of finding a suitable inflection point.

[0091] Step S1363: For each initial candidate inflection point, draw a line connecting the initial candidate inflection point to the coordinates of the starting point of the conflict trajectory segment, and check whether the line passes through the coverage area of ​​any fixed obstacle.

[0092] For each initial candidate inflection point, a line is drawn from that initial candidate inflection point to the starting coordinates of the conflict trajectory segment using drawing tools or coordinate calculations. Then, this line is compared with the coverage area of ​​each fixed obstacle to check whether the line passes through the coverage area of ​​any fixed obstacle. For example, it checks whether the line passes through the height range and horizontal area of ​​a tall building.

[0093] Step S1364: If the line passes through the coverage area of ​​the fixed obstacle, the initial candidate inflection point is eliminated; if the line does not pass through the coverage area of ​​the fixed obstacle, the initial candidate inflection point is retained as the first stage candidate inflection point.

[0094] During the inspection process, if the line connecting an initial candidate inflection point to the starting point of the conflict trajectory segment passes through the coverage area of ​​a fixed obstacle, the initial candidate inflection point will be eliminated and will no longer be considered as a subsequent candidate. If the line does not pass through the coverage area of ​​any fixed obstacle, the initial candidate inflection point will be retained as a first-stage candidate inflection point.

[0095] Step S1365: For each candidate inflection point in the first stage, draw a line connecting the candidate inflection point in the first stage to the coordinates of the end point of the conflict trajectory segment, and check whether the line passes through the coverage area of ​​any fixed obstacle.

[0096] For the remaining candidate inflection points of the first stage, continue to draw a line connecting each candidate inflection point to the coordinates of the end point of the conflict trajectory segment. Similarly, compare this line with the coverage area of ​​each fixed obstacle to check whether it passes through the coverage area of ​​any fixed obstacle.

[0097] Step S1366: If the line passes through the coverage area of ​​the fixed obstacle, the candidate inflection point of the first stage is eliminated; if the line does not pass through the coverage area of ​​the fixed obstacle, the candidate inflection point of the first stage is retained as the candidate inflection point of the second stage.

[0098] If the line connecting the candidate inflection point in the first stage to the end point of the conflict trajectory segment passes through the coverage area of ​​a fixed obstacle, then the candidate inflection point in the first stage is eliminated. If the line does not pass through the coverage area of ​​any fixed obstacle, then the candidate inflection point in the first stage is retained as a candidate inflection point in the second stage.

[0099] Step S1367: Count the number of candidate inflection points in the second stage. If the number meets the path planning requirements, the candidate inflection points in the second stage are used as the final candidate inflection points. If the number does not meet the path planning requirements, expand the area of ​​the avoidance inflection point, reselect the initial candidate inflection points and repeat the above checking steps until candidate inflection points that meet the number requirements are obtained.

[0100] The number of candidate inflection points in the second stage is counted. Depending on the path planning requirements, multiple candidate inflection points are typically needed for optimization. If the current number of candidate inflection points in the second stage reaches or exceeds the required number, these candidate inflection points are used as the final candidate inflection points. If the number is insufficient, the area to avoid inflection points is expanded, and initial candidate inflection points are reselected within the new area. The checking process from steps S1363 to S1366 is then followed until a sufficient number of candidate inflection points are obtained.

[0101] Step S137: Replan the flight path of the conflict trajectory segment using the candidate inflection point as the intermediate node to form the adjusted flight trajectory coordinates.

[0102] Using the finalized candidate inflection points as intermediate nodes, the flight paths of conflicting trajectory segments are replanned. For example, for a trajectory segment that conflicts with an urban delivery drone, the starting coordinates, candidate inflection points, and ending coordinates of the original trajectory segment are connected sequentially to form a new flight path that avoids the spatial overlap with the urban delivery drone. The coordinates of each point on the new path are then compiled and recorded to form the adjusted flight trajectory coordinates.

[0103] Step S138: Based on the historical flight trajectory patterns of the corresponding flight target, apply the flight altitude adjustment range rules to determine the flight altitude adjustment range of the flight mission to be evaluated. The flight altitude adjustment range is far from the overlapping range of the predicted flight altitude of the flight target.

[0104] Based on the historical flight trajectory patterns of the corresponding flight targets, the flight altitude adjustment range rules are applied to determine the flight altitude adjustment interval for medical supply delivery missions. For example, the historical flight trajectory pattern of urban express delivery drones shows that their altitude is stable within a certain range, and their predicted flight altitude is also within that range. According to the flight altitude adjustment range rules, the flight altitude adjustment interval for medical supply delivery missions is determined to be an interval higher than this range by a certain value, to avoid overlapping altitude ranges. The historical flight trajectory pattern of emergency communication support drones shows that their altitude is adjusted within a certain range according to a preset rhythm, and their predicted flight altitude is also within this range. Therefore, the flight altitude adjustment interval for medical supply delivery missions is determined to be an interval lower than this range by a certain value, to avoid overlapping altitudes.

[0105] Step S139: Based on the length of the adjusted flight trajectory coordinates and the expected flight period, the flight speed adjustment interval rule is applied to determine the flight speed control requirements, which enable the flight mission to be evaluated to complete the adjusted flight path within the expected flight period.

[0106] Based on the total length of the adjusted flight path coordinates and the expected flight period, flight speed control requirements are determined using flight speed adjustment interval rules. The adjusted flight path length may be longer than the original path length; to ensure flight can be completed within the expected flight period, flight speed adjustments are necessary. For example, if the adjusted path length increases, according to the rules, flight speed can be appropriately increased during non-conflict periods, while maintaining a reasonable speed before and after conflict periods to ensure the total flight time does not exceed the expected flight period. These specific speed adjustment requirements are then clarified to form the flight speed control requirements.

[0107] Step S1310: Integrate the adjusted flight trajectory coordinates, the flight altitude adjustment range, and the flight speed control requirements, and mark the range and effective time period of the conflict trajectory segments corresponding to each adjustment content to form the flight path adjustment scheme.

[0108] The adjusted flight path coordinates, flight altitude adjustment ranges, and flight speed control requirements are integrated, and the conflicting trajectory segments and effective periods corresponding to each adjustment are marked. For example, the portion of the adjusted flight path coordinates related to conflicts with urban express delivery drones is marked with the corresponding conflicting trajectory segment range and effective period; the flight altitude adjustment range is marked within which conflicting period it takes effect; and the flight speed control requirements are marked within which trajectory segments and periods they are implemented. Through this integration and marking, a complete flight path adjustment plan is formed.

[0109] Step S140: Based on the flight path adjustment scheme, generate flight control commands. The flight control commands include trajectory execution content, altitude adjustment content, and speed control content. The flight control commands match the control protocol corresponding to the flight mission type.

[0110] Based on the flight path adjustment scheme generated above, flight control commands are generated. These commands must include trajectory execution, altitude adjustment, and speed control information, and must match the control protocol corresponding to the medical supplies delivery flight mission type to ensure the drone can accurately receive and execute commands.

[0111] Step S141: Analyze the adjusted flight trajectory coordinates, flight altitude adjustment range, flight speed control requirements, and the range and effective time of conflict trajectory segments corresponding to each adjustment in the flight path adjustment scheme.

[0112] The flight path adjustment plan is analyzed to extract the coordinates of the adjusted flight trajectory, clarifying the coordinates of each point the UAV needs to fly to; the flight altitude adjustment range is extracted to understand the altitude range to be maintained at different times; and the flight speed control requirements are extracted to understand the speed limits for different trajectory segments. Simultaneously, the conflicting trajectory segment ranges corresponding to each adjustment are clarified, i.e., which trajectory segments need to be adjusted, and the effective period of these adjustments, i.e., from when the adjustments begin to when they end.

[0113] Step S142: Decompose the adjusted flight trajectory coordinates into multiple consecutive waypoint coordinates, and determine the turning requirements between adjacent waypoint coordinates to form the trajectory execution content. The format of the waypoint coordinates matches the navigation system data format of the flight target.

[0114] The adjusted flight trajectory coordinates are broken down into multiple consecutive waypoint coordinates. These waypoint coordinates are key nodes on the flight trajectory, guiding the drone along the predetermined path. For example, the trajectory from the starting point to the first candidate inflection point is broken down into several waypoints, and the trajectory from the candidate inflection point to the destination is also broken down into several waypoints. Simultaneously, the turning requirements between adjacent waypoint coordinates, such as turning angle and turning speed, are determined to ensure a smooth transition between waypoints for the drone. The format of the waypoint coordinates needs to be consistent with the navigation system data format of the medical supply delivery drone, such as using a specific latitude and longitude format, to ensure that the navigation system can recognize and process them.

[0115] Step S143: Based on the flight altitude adjustment range and the effective time period, divide the altitude adjustment into the start time period, transition time period, and maintenance time period, and determine the altitude value and altitude change rhythm corresponding to each time period to form the altitude adjustment content. The altitude change rhythm matches the altitude change rules in the low-altitude flight safety rules.

[0116] Based on the altitude adjustment range and effective period, the altitude adjustment process is divided into three phases: the start phase, the transition phase, and the holding phase. The start phase is the initial part of the effective period, during which the drone begins preparing for altitude adjustment and maintains its current altitude. The transition phase follows the start phase, during which the drone adjusts its altitude to the target altitude at a certain pace. The holding phase follows the transition phase, during which the drone maintains its adjusted target altitude.

[0117] Determine the altitude values ​​for each time period. The altitude value for the initial time period is the altitude before adjustment. The altitude value for the transition period gradually changes from the altitude before adjustment to the target altitude, and the altitude value for the remaining time period is the target altitude. Simultaneously, determine the altitude change rhythm within the transition period, such as the altitude increase or decrease per second. This altitude change rhythm must match the altitude change rules in the low-altitude flight safety regulations to ensure a safe and smooth altitude adjustment process. Integrate the above information to form the altitude adjustment content.

[0118] Step S1431: Extract the flight altitude adjustment interval and the corresponding effective time period from the flight path adjustment plan. The flight altitude adjustment interval includes the starting altitude value and the target altitude value.

[0119] Extract the flight altitude adjustment range from the flight path adjustment plan. This range includes the initial altitude value and the target altitude value. The initial altitude value is the altitude of the UAV before the adjustment, and the target altitude value is the altitude to be reached after the adjustment. Simultaneously, extract the effective time period corresponding to this altitude adjustment, i.e., the time from which the altitude adjustment begins to the time from which it ends.

[0120] Step S1432: Divide the effective period into a start period, a transition period, and a maintenance period. The start period is the beginning part of the effective period, the maintenance period is the end part of the effective period, and the transition period is the part between the start period and the maintenance period.

[0121] For example, if the effective period for flight altitude adjustment is from a certain hour in the morning to ten minutes after that hour, then this effective period is divided into an initial period, a transition period, and a holding period. The initial period is from that hour to two minutes after that hour, serving as a preparation phase before altitude adjustment; the holding period is from seven minutes to ten minutes after that hour, used to stabilize and maintain the adjusted altitude; and the transition period is from two minutes to seven minutes after that hour, the stage for adjusting the altitude from the initial value to the target value.

[0122] Step S1433: Determine the altitude value corresponding to the start time period as the starting altitude value of the flight altitude adjustment range, and keep the altitude value corresponding to the time period as the target altitude value of the flight altitude adjustment range.

[0123] During the initial period, the altitude of the medical supply delivery drones will remain at the starting altitude value of the flight altitude adjustment range, i.e., the altitude before the adjustment. For example, if the starting altitude is a specific value, the drone will maintain this altitude throughout the initial period. During the maintenance period, the drone's altitude will stabilize at the target altitude value within the flight altitude adjustment range, i.e., the altitude to be reached after adjustment. If the target altitude is a certain amount higher than the starting altitude, this altitude will remain unchanged during the maintenance period.

[0124] Step S1434: Based on the length of the transition period and the difference between the initial height value and the target height value, determine the height change rhythm within the transition period, wherein the height change rhythm enables the height to smoothly transition from the initial height value to the target height value.

[0125] By combining the length of the transition period and the difference between the initial and target altitudes, the altitude change rhythm within the transition period is calculated. For example, if the transition period is five minutes long and the difference between the initial and target altitudes is a certain altitude difference, then the required altitude increase per minute can be determined to ensure a smooth transition from the initial altitude to the target altitude within five minutes. This altitude change rhythm must ensure that the drone does not experience drastic altitude changes during the adjustment process, meeting the requirements for stable flight.

[0126] Step S1435: Mark the start and end times of the start time period and determine the duration of maintaining the initial height value within the start time period.

[0127] Accurately mark the start and end times of the start period, such as starting at a specific hour in the morning and ending two minutes after that hour. Based on these two times, the duration of maintaining the initial altitude value within the start period can be determined to be two minutes. During these two minutes, the drone's altitude will not be adjusted, and it will maintain the initial altitude value during flight.

[0128] Step S1436: Mark the start and end times of the transition period and determine the duration of altitude adjustment according to the altitude change rhythm during the transition period.

[0129] The transition period begins at the end of the initial period, specifically two minutes after a certain hour in the morning, and ends seven minutes after that hour. Therefore, the duration of the altitude adjustment period within the transition period, following the established rhythm of altitude changes, is determined to be five minutes. During these five minutes, the drone gradually adjusts its altitude from the initial value to the target value according to the determined rhythm of altitude changes.

[0130] Step S1437: Mark the start and end times of the holding period and determine the duration of maintaining the target altitude value within the holding period.

[0131] The start time of the hold period is the end time of the transition period, which is seven minutes after a certain hour in the morning and ten minutes after that hour. Therefore, the duration of maintaining the target altitude value within the hold period is three minutes. During these three minutes, the drone flies stably at the target altitude value without making any altitude adjustments.

[0132] Step S1438: Integrate the time range of the start period, transition period, and maintenance period, as well as the corresponding altitude value and altitude change rhythm of each period, to form altitude adjustment content.

[0133] The time ranges of the start period, transition period, and hold period, along with the corresponding altitude values ​​for each period (the initial altitude value of the start period, the changing altitude value of the transition period, and the target altitude value of the hold period) and the altitude change rhythm of the transition period, are integrated to form a complete altitude adjustment content. This altitude adjustment content clearly indicates the altitude control requirements of the UAV at different times.

[0134] Step S144: Based on the flight speed control requirements and the range of the conflict trajectory segments, determine the target speed value and speed transition rhythm corresponding to each trajectory segment to form the speed control content. The target speed value matches the speed adjustment rules in the low-altitude flight safety rules.

[0135] Based on flight speed control requirements and the range of conflict trajectory segments, corresponding target speed values ​​are set for different trajectory segments. For example, in non-conflict trajectory segments, the target speed value can be set to the UAV's normal cruise speed; in areas approaching conflict trajectory segments, the target speed value is appropriately reduced to allow sufficient reaction time; on the adjusted path after a conflict trajectory segment, the target speed value is set according to the actual situation to ensure that conflict can be avoided. Simultaneously, the speed transition rhythm between adjacent trajectory segments is determined, such as the change in speed per second when transitioning from one target speed value to another, to ensure smooth speed adjustments. The aforementioned target speed values ​​must comply with the speed adjustment rules in low-altitude flight safety regulations and not exceed the prescribed speed limits. Integrating the above information forms the speed control content.

[0136] Step S145: Add a unified instruction identifier to the trajectory execution content, the altitude adjustment content, and the speed control content. The instruction identifier includes the instruction generation time period, the identifier of the flight target to be executed, and the instruction version information.

[0137] A unified command identifier is added to the trajectory execution, altitude adjustment, and speed control commands to facilitate drone identification and execution, and to enable the management system to track and record them. The command generation time is the specific time the command was generated, such as a specific hour, minute, and second in the morning; the target identifier is the unique number of the medical supply delivery drone; and the command version information is used to distinguish different command versions, such as the initial version, the first revised version, etc. By adding a unified command identifier, the uniqueness and traceability of commands are ensured.

[0138] Step S146: Integrate the trajectory execution content, altitude adjustment content, and speed control content according to the control protocol format corresponding to the flight mission type, and encapsulate them to form flight control commands.

[0139] Based on the control protocol format corresponding to the medical supply delivery flight mission, the trajectory execution, altitude adjustment, and speed control content are integrated. The control protocol format specifies the transmission method, data format, and verification method of the commands. Each element is encoded and organized according to this format, then encapsulated to form the final flight control commands. These encapsulated commands can be correctly parsed and executed by the control system of the medical supply delivery drone.

[0140] Step S150: Receive instruction execution feedback from the flight target, compare the instruction execution feedback with the flight path adjustment plan, and update the airspace basic state data based on the comparison result. The instruction execution feedback includes the real-time position execution record, real-time altitude execution record, and real-time speed execution record of the flight target.

[0141] During the execution of flight control commands, medical supply delivery drones can provide real-time feedback. This feedback includes the drone's real-time position execution record (i.e., actual flight position coordinates), real-time altitude execution record (actual flight altitude), and real-time speed execution record (actual flight speed). This feedback is compared with the adjusted flight trajectory coordinates, flight altitude adjustment range, and flight speed control requirements in the flight path adjustment plan to check if the drone's actual execution is consistent with the plan. Based on the comparison results, the basic airspace status data is updated, such as adding the drone's actual flight trajectory to the approved flight plan's trajectory information, or adjusting the temporary restricted airspace range according to the actual situation.

[0142] Step S151: Receive real-time command execution feedback from the flight target during the execution of flight control commands. The command execution feedback includes real-time position execution records, real-time altitude execution records, real-time speed execution records, and command execution status for each time period.

[0143] During the execution of flight control commands by the medical supply delivery drone, real-time feedback on command execution is received. The real-time position execution record for each time period is the actual position coordinates reached by the drone in each time interval; the real-time altitude execution record is the actual flight altitude in each time interval; the real-time speed execution record is the actual flight speed in each time interval; and the command execution status indicates whether the command was successfully received, whether it is being executed, whether it has been completed, or whether there has been an execution abnormality, such as status information like "executing", "execution normal", "altitude adjustment abnormality".

[0144] Step S152: Extract the adjusted flight trajectory coordinates, flight altitude adjustment range, and flight speed control requirements from the flight path adjustment plan as the comparison benchmark.

[0145] The baseline content for comparison is extracted from the flight path adjustment plan, including the adjusted flight trajectory coordinates (i.e., the desired position coordinate sequence of the UAV flight), the flight altitude adjustment range (the desired altitude range that the UAV will maintain), and the flight speed control requirements (the speed limits and change requirements that the UAV is expected to follow). The above baseline content is the standard for judging the execution of UAV commands.

[0146] Step S153: Compare the real-time position execution record in the command execution feedback with the adjusted flight trajectory coordinates according to the corresponding time period, and record the position difference between the two in each time period.

[0147] According to the corresponding time period, the real-time position records are compared with the adjusted flight trajectory coordinates. For example, the actual flight position coordinates of the drone within a certain time period are compared with the corresponding coordinates on the adjusted flight trajectory for that time period, and the distance difference between the two is calculated. The position difference for each time period is recorded; for example, in the first time period, the position difference is a certain distance; in the second time period, the position difference is another distance, and so on. By recording the position differences, the deviation between the drone's actual flight trajectory and the expected trajectory can be understood.

[0148] Step S154: Compare the real-time altitude execution record in the command execution feedback with the flight altitude adjustment range according to the corresponding time period, and record the time period when the real-time altitude execution record is outside the flight altitude adjustment range.

[0149] According to the corresponding time period, the real-time altitude execution record is compared with the flight altitude adjustment range to check whether the actual flight altitude of the drone is within the expected altitude range. If the real-time altitude execution record of a certain time period exceeds the flight altitude adjustment range, then that time period is recorded. For example, if the actual altitude of the drone is lower than the lower limit of the flight altitude adjustment range for a certain minute during the transition period, then that minute is recorded as an altitude abnormality period.

[0150] Step S155: Compare the real-time speed execution record in the command execution feedback with the flight speed control requirements according to the corresponding time period, and record the speed difference between the two in each time period.

[0151] According to the corresponding time period, the real-time speed execution records are compared with the flight speed control requirements. The flight speed control requirements may specify a target speed value or speed range for a certain time period. The actual speed is compared with the target speed value or speed range, and the speed difference is calculated. For example, if the target speed value for a certain time period is a certain value, while the actual speed is a different value, the difference between the two is recorded. By recording the speed difference, the speed execution status of the UAV can be understood.

[0152] Step S156: Integrate location differences, altitude differences, time periods, speed differences, and command execution status to form a comparison result.

[0153] The positional differences recorded in step S153, the altitude differences recorded in step S154, the speed differences recorded in step S155, and the command execution status are integrated. For example, if the positional difference is within the allowable range, there are no altitude difference periods, the speed difference is small, and the command execution status is "execution normal," the comparison result is "command execution conforms to the flight path adjustment plan." If there are large positional differences, multiple altitude difference periods, significant speed differences, or the command execution status is "execution abnormal," the comparison result is "command execution does not conform to the flight path adjustment plan." By integrating this information, a complete comparison result is formed.

[0154] Step S157: If the comparison result shows that the command execution conforms to the flight path adjustment plan, the actual flight trajectory of the flight target is integrated into the approved flight plan trajectory information in the airspace basic status data. The actual flight trajectory is formed by integrating the real-time position execution record, the real-time altitude execution record, and the real-time speed execution record.

[0155] When the comparison results show that the command execution conforms to the flight path adjustment plan, it indicates that the actual flight situation of the medical supply delivery drone is consistent with the flight path adjustment plan. At this point, the actual flight trajectory of the drone is integrated into the approved flight plan trajectory information in the airspace basic status data. The actual flight trajectory is formed by integrating real-time position execution records, real-time altitude execution records, and real-time speed execution records. That is, the position, altitude, and speed information of each time period are combined in chronological order to form a complete actual flight trajectory.

[0156] For example, step S1571: Extract the real-time position execution record, real-time altitude execution record, real-time speed execution record, and the corresponding flight time node for each time period from the actual flight trajectory.

[0157] From the integrated actual flight trajectory, extract the real-time position execution record (specific position coordinates), real-time altitude execution record (specific altitude value), and real-time speed execution record (specific speed value) for each time period. Simultaneously, extract the corresponding flight time node for each record (i.e., the specific time the record was generated). For example, extract the real-time position coordinates, altitude value, and speed value for the first minute after a certain hour in the morning, along with the corresponding time node as the first minute after that hour.

[0158] Step S1572: Sort the real-time position execution records, real-time altitude execution records, and real-time speed execution records for each time period according to the flight time node to form structured trajectory data.

[0159] The extracted real-time position, altitude, and speed records for each time period are sorted according to the chronological order of flight time. For example, starting from a certain hour in the morning, and sequentially for the first minute, second minute, and so on, the corresponding position, altitude, and speed information are arranged to form structured trajectory data. This structured trajectory data clearly reflects the UAV's flight status at different times.

[0160] Step S1573: Query the approved flight plan trajectory information corresponding to the flight mission to be evaluated in the basic airspace status data, and extract the planned trajectory content from the approved flight plan trajectory information.

[0161] In the basic airspace status data, query the approved flight plan trajectory information corresponding to the medical supplies delivery mission, and find the planned trajectory content in the information, namely the original planned flight trajectory coordinates, altitude range, speed requirements, etc.

[0162] Step S1574: Replace the planned trajectory content in the approved flight plan trajectory information with structured trajectory data, while retaining other content in the approved flight plan trajectory information, such as flight mission identifiers and operating entity information.

[0163] The planned trajectory content in the approved flight plan trajectory information is replaced with the structured trajectory data formed above, while other content in the information is retained, such as the flight mission identifier (a unique number for the medical supply delivery mission) and the operating entity information (the name of the logistics company responsible for the mission). Through this replacement, the approved flight plan trajectory information can reflect the actual flight situation of the drone.

[0164] Step S1575: Supplement the flight time nodes and actual total flight time in the structured trajectory data to the approved flight plan trajectory information.

[0165] The flight time nodes (the specific times corresponding to each record) and the actual total flight duration (the total time from takeoff to landing) from the structured trajectory data are supplemented into the approved flight plan trajectory information. For example, if the actual total flight duration is a specific duration, it is added to the information to make it more complete.

[0166] Step S1576: Check whether the updated approved flight plan trajectory information contains complete records of position, altitude, and speed for each time period. If any are missing, supplement the records for the corresponding time period from the instruction execution feedback.

[0167] The updated approved flight plan trajectory information is checked to see if it contains position, altitude, and speed records for all time periods. If any records for a particular time period are missing, such as the position coordinates for a specific minute not being included, the real-time position execution record, real-time altitude execution record, and real-time speed execution record for that time period are retrieved from the command execution feedback and added to the approved flight plan trajectory information to ensure the completeness of the information.

[0168] Step S1577: Replace the original approved flight plan trajectory information in the airspace basic status data with the updated approved flight plan trajectory information.

[0169] The updated and improved flight plan trajectory information will replace the original approved flight plan trajectory information in the airspace basic status data. This updates that portion of the airspace basic status data, ensuring it accurately reflects the actual flight trajectory of the medical supply delivery drones.

[0170] Step S158: If the comparison result shows that the command execution does not conform to the flight path adjustment plan, associate the flight target information with the current airspace basic status data, re-execute the flight conflict prediction step that combines the flight demand information set with the real-time dynamic airspace data, generate a new conflict prediction result, and formulate a new flight path adjustment plan based on the new conflict prediction result.

[0171] When the comparison results show that the command execution does not conform to the flight path adjustment plan, such as excessive deviation between the actual flight position and the adjusted trajectory of the UAV, altitude exceeding the adjustment range, or speed not meeting control requirements, further measures are required. The information of the medical supply delivery UAV (such as its identifier and current location) is correlated with the current basic airspace status data (such as the positions of other flying targets, obstacle distribution, and temporary restricted airspace). Then, the flight conflict prediction step in step S120, which combines the flight demand information set with real-time dynamic airspace data, is re-executed. This involves re-analyzing whether there are new conflicts between the UAV's current flight status and other flying targets, generating a new conflict prediction result. Based on the new conflict prediction result, a new flight path adjustment plan is formulated according to the method in step S130 to ensure that the UAV can safely complete its flight mission.

[0172] Step S159: Update the approved flight plan trajectory information and temporary restricted airspace range in the basic airspace status data.

[0173] Based on the comparison results and processing status, the approved flight plan trajectory information and temporary restricted airspace ranges in the airspace basic status data are updated. In addition to updating the approved flight plan trajectory information when the command execution conforms to the plan, if the temporary restricted airspace range needs adjustment during command execution (e.g., expansion or reduction of the restricted area due to changes in actual conditions), it also needs to be updated. For example, if activity in a temporarily restricted airspace ends early, its restricted period can be shortened and updated in the airspace basic status data to ensure that the planning of other flight missions is based on the latest airspace information.

[0174] Figure 2 The following is a schematic diagram of the hardware structure of a low-altitude intelligent flight management system 100 for implementing the above-described low-altitude intelligent flight management method, provided by an embodiment of the present invention. Figure 2 As shown, the low-altitude intelligent flight management system 100 may include a processor 110, a machine-readable storage medium 120, a bus 130, and a communication unit 140.

[0175] In one possible design, the low-altitude intelligent flight management system 100 can be a single server or a group of servers. The server group can be centralized or distributed (e.g., the low-altitude intelligent flight management system 100 can be a distributed system). In some embodiments, the low-altitude intelligent flight management system 100 can be local or remote. For example, the low-altitude intelligent flight management system 100 can access information and / or data stored in machine-readable storage medium 120 via a network. As another example, the low-altitude intelligent flight management system 100 can directly connect to machine-readable storage medium 120 to access the stored information and / or data.

[0176] Machine-readable storage medium 120 may store data and / or instructions. In some embodiments, machine-readable storage medium 120 may store data acquired from an external terminal. In some embodiments, machine-readable storage medium 120 may store data and / or instructions used by the low-altitude intelligent flight management system 100 to perform or use in order to accomplish the exemplary methods described in this invention.

[0177] In a specific implementation, one or more processors 110 execute computer-executable instructions stored in the machine-readable storage medium 120, enabling the processor 110 to execute the low-altitude intelligent flight management method as described in the above method embodiment. The processor 110, the machine-readable storage medium 120, and the communication unit 140 are connected via a bus 130. The processor 110 can be used to control the transmission and reception actions of the communication unit 140.

[0178] The specific implementation process of processor 110 can be found in the various method embodiments executed by the low-altitude intelligent flight management system 100 described above. The implementation principle and technical effect are similar, and will not be repeated here.

[0179] Furthermore, this embodiment of the invention also provides a readable storage medium containing computer-executable instructions. When the processor executes the computer-executable instructions, the above-mentioned low-altitude intelligent flight management method is implemented.

[0180] It should be noted that, in order to simplify the description of this invention and thus aid in the understanding of one or more embodiments, the foregoing description of the embodiments of this invention sometimes combines multiple features into a single embodiment, drawing, or description thereof. Similarly, it should be noted that, in order to simplify the description of this invention and thus aid in the understanding of one or more embodiments, the foregoing description of the embodiments of this invention sometimes combines multiple features into a single embodiment, drawing, or description thereof.

Claims

1. A low-altitude intelligent flight management method, characterized in that, The method includes: By integrating low-altitude flight application information with basic airspace status data, a flight demand information set is obtained. The low-altitude flight application information includes flight mission type, expected flight time period, initial take-off and landing coordinates, and flight altitude requirement. The basic airspace status data includes trajectory information of approved flight plans, distribution of fixed obstacles in the airspace, and temporary restricted airspace range. Based on the flight demand information set, and combined with real-time dynamic airspace data, flight conflict prediction is performed to obtain conflict prediction results. The conflict prediction results include conflict time periods, associated flight target identifiers, and conflict trajectory segments of the flight mission to be evaluated. Based on the conflict prediction results, a flight path adjustment plan is generated by applying low-altitude flight safety rules. The flight path adjustment plan includes the adjusted flight trajectory coordinates, flight altitude adjustment range, and flight speed control requirements. The low-altitude flight safety rules include conflict response rules for path adjustment, altitude adjustment, and speed adjustment. Based on the flight path adjustment scheme, flight control commands are generated. The flight control commands include trajectory execution content, altitude adjustment content, and speed control content. The flight control commands are matched with the control protocol corresponding to the flight mission type. The system receives instruction execution feedback from the flight target, compares the instruction execution feedback with the flight path adjustment plan, and updates the airspace basic state data based on the comparison results. The instruction execution feedback includes the real-time position execution record, real-time altitude execution record, and real-time speed execution record of the flight target. The process of performing flight conflict prediction based on the flight demand information set and combined with real-time dynamic airspace data to obtain conflict prediction results includes: Extract the expected trajectory content of the flight mission to be evaluated from the flight demand information set. The expected trajectory content includes the expected flight path coordinates derived from the initial take-off and landing coordinates and the flight mission type, the expected flight speed determined by the flight mission type, and the expected flight altitude change determined by the flight altitude requirements. The real-time position, real-time speed, and real-time flight altitude of each flying target within the airspace are collected to form real-time dynamic data of the airspace. The real-time position of the flight target in the real-time dynamic data of the airspace is associated with the coordinates of the expected flight path, and the predicted flight trajectory of the flight target in the future time period is derived by combining the real-time speed of the flight target. The predicted flight path coordinates of the flight mission to be evaluated are compared with the predicted flight trajectory of the flight target by time period, and the spatially overlapping trajectory segments in the same time period are marked. The predicted flight altitude change of the flight mission to be evaluated is correlated with the real-time flight altitude of the flight target to deduce the predicted flight altitude of the flight target in the future time period. Then, the predicted flight altitude change and the predicted flight altitude are compared by time period to mark the time period in which the flight altitudes of the two overlap. By associating the spatially overlapping trajectory segments with the highly overlapping time periods, conflict time periods in which the flight mission to be evaluated and each flight target simultaneously exhibit both spatial and high-altitude overlap are determined, as well as the conflict trajectory segments corresponding to the conflict time periods. The conflict prediction result is formed by associating the conflict period, the conflict trajectory segment with the corresponding flight target identifier, the operating entity, and the current flight mission type. The step of generating a flight path adjustment plan based on the conflict prediction results and applying low-altitude flight safety rules includes: From the conflict prediction results, the conflict time period, conflict trajectory segment and corresponding flight target information are extracted. The corresponding flight target information includes the flight target identifier, the current flight mission type and the historical flight trajectory pattern. The low-altitude flight safety rules are retrieved, which include path adjustment priority rules corresponding to different conflict period lengths, avoidance direction rules for different flight mission types, flight altitude adjustment range rules, and flight speed adjustment interval rules. Based on the length of the conflict period, the path adjustment priority rule is applied to determine the path adjustment priority order; Based on the current flight mission type of the corresponding flight target, the avoidance direction rule is applied to determine the avoidance direction of the flight mission to be evaluated; Based on the avoidance direction, an avoidance inflection point region is selected between the starting coordinates and the ending coordinates of the conflict trajectory segment. The avoidance inflection point region is far away from the spatial overlap region of the predicted flight trajectory of the flight target. Candidate inflection points are selected within the avoidance inflection point area. The candidate inflection points must satisfy the following conditions: the line connecting the candidate inflection point to the coordinates of the starting point of the conflict trajectory segment and the line connecting the candidate inflection point to the coordinates of the ending point of the conflict trajectory segment do not pass through the area where fixed obstacles are distributed in the airspace. The flight path of the conflict trajectory segment is replanned using the candidate inflection point as the intermediate node to form the adjusted flight trajectory coordinates; Based on the historical flight trajectory patterns of the corresponding flight targets, the flight altitude adjustment range rules are applied to determine the flight altitude adjustment range of the flight mission to be evaluated. The flight altitude adjustment range is far from the overlapping range of the predicted flight altitude of the flight targets. Based on the length of the adjusted flight trajectory coordinates and the expected flight period, the flight speed adjustment interval rule is applied to determine the flight speed control requirements, which enable the flight mission to be evaluated to complete the adjusted flight path within the expected flight period. The flight path adjustment scheme is formed by integrating the adjusted flight trajectory coordinates, the flight altitude adjustment range, and the flight speed control requirements, and marking the range and effective time period of the conflict trajectory segments corresponding to each adjustment.

2. The low-altitude intelligent flight management method according to claim 1, characterized in that, The step of associating the real-time position of the flight target in the real-time dynamic airspace data with the coordinates of the predicted flight path, and deriving the predicted flight trajectory of the flight target for future periods based on the real-time speed of the flight target, includes: Extract the real-time position, real-time speed, and real-time flight altitude of the flight target from real-time dynamic airspace data, and extract the current flight mission type of the flight target from the approved flight plan trajectory information; The motion pattern of the flight target is determined based on its current flight mission type. If the current flight mission type of the flight target is a cargo flight mission or a passenger flight mission, its motion pattern is determined to be uniform linear motion; if the current flight mission type of the flight target is an operational flight mission, its motion pattern is determined to be variable speed curvilinear motion. If the motion pattern is uniform linear motion, the flight direction is determined according to the real-time velocity direction of the flying target. The flight position at each time point in the future period is deduced by combining the real-time position. The flight positions at each time point are sorted by time period to form a predicted flight trajectory. If the motion pattern is a variable speed curve motion, extract the speed change pattern in the historical flight trajectory of the flight target, combine it with the real-time speed to deduce the flight speed and direction at each time node in the future period, and then combine it with the real-time position to deduce the flight position at each time node. Sort the flight positions of each extreme speed node by time period to form a predicted flight trajectory. The derived predicted flight trajectory is associated with the distribution of fixed obstacles in the airspace, the predicted flight trajectory is associated with the range of temporary restricted airspace, and the predicted flight trajectory is associated with the corresponding time period to form a complete predicted flight trajectory of the flight target for the future time period.

3. The low-altitude intelligent flight management method according to claim 1, characterized in that, The process involves correlating the expected flight altitude change of the flight mission to be evaluated with the real-time flight altitude of the flight target to deduce the predicted flight altitude of the flight target in future time periods. Then, the expected flight altitude change and the predicted flight altitude are compared by time period, and the time periods in which their flight altitudes overlap are marked, including: Extract the real-time flight altitude and speed of the flight target from real-time dynamic airspace data, and determine its altitude change pattern by combining the current flight mission type of the flight target. If the altitude of the flight target changes in a constant manner, the predicted flight altitude at each time point in the future period will be the current real-time flight altitude. If the altitude change pattern of the flight target is to adjust the altitude according to a preset rhythm, extract the altitude adjustment rhythm from the historical flight trajectory of the flight target, and combine it with the real-time flight altitude to deduce the predicted flight altitude at each time node in the future period; The predicted flight altitudes for each time point are sorted by time period to form a sequence of predicted flight altitudes for the target in future time periods. Extract the expected flight speed changes from the expected trajectory of the flight mission to be evaluated, and determine the altitude range corresponding to the expected flight altitude changes in various future time periods; The predicted flight altitude sequence is compared with the altitude range of each time period of the expected flight altitude change according to the corresponding time period; If the altitude value in the predicted flight altitude sequence falls within the altitude range of the predicted flight altitude change for any given time period, that time period is marked as an altitude overlap period. All highly overlapping time periods are statistically analyzed, and the predicted flight altitude values ​​and expected flight altitude ranges corresponding to each highly overlapping time period are correlated to form a record of highly overlapping time periods.

4. The low-altitude intelligent flight management method according to claim 1, characterized in that, The process of selecting candidate inflection points within the avoidance inflection point area requires that the lines connecting the candidate inflection point to the starting point coordinates of the conflict trajectory segment and the lines connecting the candidate inflection point to the ending point coordinates of the conflict trajectory segment do not pass through areas with fixed obstacles in the airspace, including: Extract the distribution of fixed obstacles in the airspace from the basic airspace status data, and determine the location coordinates and coverage of each fixed obstacle; Multiple initial candidate inflection points are selected within the avoidance inflection point area, and the initial candidate inflection points are evenly distributed within the avoidance inflection point area. For each initial candidate inflection point, draw a line from the initial candidate inflection point to the coordinates of the starting point of the conflict trajectory segment, and check whether the line passes through the coverage area of ​​any fixed obstacle. If the line passes through the coverage area of ​​a fixed obstacle, the initial candidate inflection point is eliminated; if the line does not pass through the coverage area of ​​a fixed obstacle, the initial candidate inflection point is retained as a first-stage candidate inflection point. For each candidate turning point in the first stage, draw a line connecting the candidate turning point in the first stage to the coordinates of the end point of the conflict trajectory segment, and check whether the line passes through the coverage area of ​​any fixed obstacle. If the line passes through the coverage area of ​​a fixed obstacle, the candidate inflection point for the first stage is eliminated; if the line does not pass through the coverage area of ​​a fixed obstacle, the candidate inflection point for the first stage is retained as a candidate inflection point for the second stage. Count the number of candidate inflection points in the second stage. If the number meets the path planning requirements, the candidate inflection points in the second stage are used as the final candidate inflection points. If the number does not meet the path planning requirements, expand the area to avoid inflection points, reselect the initial candidate inflection points, and repeat the above checking steps until candidate inflection points that meet the number requirements are obtained.

5. The low-altitude intelligent flight management method according to claim 1, characterized in that, The generation of flight control commands based on the flight path adjustment scheme includes: The analysis includes the adjusted flight trajectory coordinates, flight altitude adjustment range, flight speed control requirements, and the range and effective time of conflicting trajectory segments corresponding to each adjustment in the flight path adjustment plan. The adjusted flight trajectory coordinates are decomposed into multiple consecutive waypoint coordinates, and the turning requirements between adjacent waypoint coordinates are determined to form the trajectory execution content. The format of the waypoint coordinates matches the navigation system data format of the flight target. Based on the flight altitude adjustment range and the effective time period, the altitude adjustment is divided into a start time period, a transition time period, and a maintenance time period, and the altitude value and altitude change rhythm corresponding to each time period are determined to form the altitude adjustment content. The altitude change rhythm matches the altitude change rules in the low-altitude flight safety rules. Based on the flight speed control requirements and the range of conflict trajectory segments, the target speed value and speed transition rhythm corresponding to each trajectory segment are determined to form the speed control content. The target speed value matches the speed adjustment rules in the low-altitude flight safety rules. A unified instruction identifier is added to the trajectory execution content, the altitude adjustment content, and the speed control content. The instruction identifier includes the instruction generation time period, the identifier of the flight target to be executed, and the instruction version information. The trajectory execution content, altitude adjustment content, and speed control content are integrated according to the control protocol format corresponding to the flight mission type, and then encapsulated to form flight control commands.

6. The low-altitude intelligent flight management method according to claim 5, characterized in that, The altitude adjustment process, based on the flight altitude adjustment range and the effective time period, divides the altitude adjustment into a start period, a transition period, and a maintenance period, and determines the altitude value and altitude change rhythm corresponding to each period, thus forming the altitude adjustment content, including: Extract the flight altitude adjustment interval and its corresponding effective time period from the flight path adjustment plan. The flight altitude adjustment interval includes the initial altitude value and the target altitude value. The effective period is divided into a start period, a transition period, and a maintenance period. The start period is the beginning of the effective period, the maintenance period is the end of the effective period, and the transition period is the part between the start period and the maintenance period. The altitude value corresponding to the start time period is determined to be the starting altitude value of the flight altitude adjustment range, and the altitude value corresponding to the time period is maintained as the target maximum speed value of the flight altitude adjustment range; Based on the length of the transition period and the difference between the initial height value and the target height value, the rhythm of height change within the transition period is determined, and the rhythm of height change ensures a smooth transition of height from the initial height value to the target height value. Mark the start and end times of the start period, and determine the duration to which the initial height value is maintained within the start period; Mark the start and end times of the transition period, and determine the duration of the altitude adjustment according to the altitude change rhythm within the transition period; Mark the start and end times of the holding period, and determine the duration of maintaining the target altitude value within the holding period; The time ranges of the start period, transition period, and maintenance period, as well as the corresponding altitude values ​​and altitude change rhythms for each period, are integrated to form altitude adjustment content.

7. The low-altitude intelligent flight management method according to claim 1, characterized in that, The process of receiving instruction execution feedback from the flight target, comparing the instruction execution feedback with the flight path adjustment plan, and updating the airspace basic state data based on the comparison result includes: Receive real-time command execution feedback from the flight target during the execution of flight control commands. The command execution feedback includes real-time position execution records, real-time altitude execution records, real-time speed execution records, and command execution status for each time period. Extract the adjusted flight trajectory coordinates, flight altitude adjustment range, and flight speed control requirements from the flight path adjustment plan as the comparison benchmark. Compare the real-time position execution record in the command execution feedback with the adjusted flight trajectory coordinates according to the corresponding time period, and record the position difference between the two in each time period; Compare the real-time altitude execution record in the command execution feedback with the flight altitude adjustment range according to the corresponding time period, and record the time period when the real-time altitude execution record is outside the flight altitude adjustment range; Compare the real-time speed execution record in the instruction execution feedback with the flight speed control requirements according to the corresponding time period, and record the speed difference between the two in each time period; The comparison results are generated by integrating differences in location, altitude, time of day, speed, and command execution status. If the comparison results show that the command execution conforms to the flight path adjustment plan, the actual flight trajectory of the flight target will be integrated into the approved flight plan trajectory information in the airspace basic status data. The actual flight trajectory is formed by integrating the real-time position execution record, the real-time altitude execution record, and the real-time speed execution record. If the comparison results show that the command execution does not conform to the flight path adjustment plan, the flight target information is associated with the current airspace basic status data, and the flight conflict prediction step combining the flight demand information set and the real-time dynamic airspace data is re-executed to generate a new conflict prediction result. Based on the new conflict prediction result, a new flight path adjustment plan is formulated. Update the approved flight plan trajectory information and temporary restricted airspace range in the basic airspace status data.

8. A low-altitude intelligent flight management system, characterized in that, The low-altitude intelligent flight management system includes a processor and a memory, the memory and the processor being connected. The memory is used to store programs, instructions or code, and the processor is used to run the programs, instructions or code in the memory to implement the low-altitude intelligent flight management method according to any one of claims 1-7.

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