A low-altitude integrated air traffic management system and method thereof

Abstract

The purpose of the present invention is to provide a low-altitude integrated air traffic management system and method thereof, the method comprising: detecting a second aircraft within a preset range of a first aircraft; classifying the type of the second aircraft according to the distance between the second aircraft and the first aircraft; and planning the flight path of the first aircraft according to the type of the second aircraft. The present invention can simulate the operating safety environment of the first aircraft, plan the flight path in real time according to the acquired environmental data, and can effectively drive the first aircraft to fly around the second aircraft, further improving the safety and reliability of the first aircraft's flight.

Description

Technical Field

[0001] The present invention relates to the technical field of air flight path control, and in particular to a low-altitude integrated air traffic management system and method thereof. Background Art

[0002] Air traffic management (ATM) is an information processing system used to manage air traffic. Air traffic management includes three parts: air traffic services, air traffic flow management and airspace management. With the continuous growth of air traffic demand, the number of manned and unmanned aircraft has increased dramatically. In particular, the airspace in metropolitan environments will be shared by traditional manned first aircraft and first aircraft, that is, air traffic management integrates low-altitude airspace. Integrating air traffic in low-altitude airspace, each first aircraft must avoid various obstacles, such as static objects (high-rise buildings, trees, lamp posts, no-fly zones, etc.) and dynamic objects (cranes, other first aircraft, manned aircraft, etc.). The dense operating environment in low-altitude airspace has made air traffic congestion more and more serious, greatly increasing the risk of potential conflicts between air traffic first aircraft, leading to an increase in air traffic control workload and endangering air traffic safety.

[0003] In recent years, a large number of studies have proposed conflict resolution technologies to resolve air traffic conflict crises. Conflict resolution aims to resolve potential conflicts of the first aircraft during operation according to the flight plan of the first aircraft, and is a key technology to ensure the safe operation of the first aircraft. The existing conflict resolution methods include adjusting the take-off time, flight speed, horizontal flight track, and altitude layer allocation of the first aircraft, and their combinations. However, they only resolve local conflicts within a limited range.

[0004] Due to the coupling relationship between the first aircraft and the complex environment of low-altitude airspace, the existing conflict resolution strategy is difficult to apply to the coordinated control between multiple first aircraft and the global obstacle avoidance strategy of multiple second aircraft. Therefore, the flight conflict resolution control strategy of multiple first aircraft and multiple second aircraft has become a key technology to be solved in the low-altitude integrated air traffic management system. Summary of the invention

[0005] The purpose of the present invention is to provide a low-altitude integrated air traffic management system and method thereof, which can simulate a complex low-altitude flight environment of aircraft, and judge whether the first aircraft needs to avoid obstacles based on the clustering coefficient of the second aircraft. When the clustering coefficient of the second aircraft reaches a preset value, it begins to judge the possibility of a conflict between the second aircraft and the first aircraft within a preset range, and then makes a path planning for the first aircraft based on the possibility of a conflict.

[0006] A low-altitude integrated air traffic management method, comprising:

[0007] Detecting a second aircraft within a preset range of the first aircraft;

[0008] classifying the second aircraft into types according to the distance between the second aircraft and the first aircraft;

[0009] A flight path of the first aircraft is planned according to the type of the second aircraft.

[0010] Preferably, detecting the second aircraft within a preset range of the first aircraft includes:

[0011] Acquire image data, millimeter wave radar data, satellite coordinate data, and laser radar data collected in the flight direction of the first aircraft;

[0012] calculating a profile of a second aircraft based on the image data;

[0013] Calculate the distance information between the first aircraft and the second aircraft according to the satellite coordinate data;

[0014] The distance information between the first aircraft and the second aircraft is calibrated according to the millimeter wave radar data and the laser radar data.

[0015] Preferably, the types of the second aircraft are classified according to the distance between the second aircraft and the first aircraft:

[0016] Calculate the clustering coefficient of the second aircraft within the preset range of the first aircraft:

[0017]

[0018] Among them, N represents the number of conflicting edges of K second aircraft with which the first aircraft node has conflicts, and Q is the clustering coefficient, which represents the degree of congestion of the second aircraft near the first aircraft.

[0019] Preferably, classifying the second aircraft into types according to the distance between the second aircraft and the first aircraft comprises:

[0020] Assume the motion model of the first aircraft is:

[0021] Wherein, P is the plane position of the first aircraft, V is the velocity of the first aircraft, a is the acceleration of the first aircraft, x is the horizontal coordinate of the first aircraft, and y is the vertical coordinate of the first aircraft. is the lateral velocity of the first aircraft, is the longitudinal velocity of the first aircraft, is the lateral acceleration of the first aircraft, is the longitudinal acceleration of the first aircraft;

[0022] The set of regions where the first aircraft and the second aircraft may collide is

[0023] The set of regions where the first aircraft and the second aircraft are bound to collide is

[0024] The set of regions where the first aircraft and the second aircraft will not collide is

[0025] in, is the center of the second aircraft, r is the radius of the first aircraft, R represents the detection radius of the first aircraft, Indicates the radius of the second aircraft.

[0026] Preferably, determining whether the second aircraft conflicts with the first aircraft includes:

[0027] Calculate the remaining time until the second aircraft collides with the first aircraft:

[0028]

[0029] in, is the speed of the second aircraft, is the speed of the first aircraft, is the plane position of the first aircraft, is the plane position of the second aircraft, is the length of the second aircraft;

[0030] Assume that the sample with conflict risk is = 1, the normal sample is = 0, and the probability of risk occurrence is P' and 1-P' respectively to establish a binary Logit model. The binary Logit model is used to express the risk of conflict between the second aircraft and the first aircraft as:

[0031]

[0032] in, is a constant term, e is an independent variable vector, i.e., the conflict influencing factors, including the remaining time for the second aircraft to conflict with the first aircraft, k is the number of influencing factors, is the coefficient vector corresponding to the independent variable.

[0033] Preferably, planning the flight path of the first aircraft according to the type of the second aircraft comprises:

[0034] If the second aircraft is within the set of possible collision areas, the acceleration of the first aircraft at this time is expressed as:

[0035]

[0036] Where n is the unit vector, k is the acceleration proportional coefficient, is the center of the i-th second aircraft, is the radius of the i-th second aircraft.

[0037] Preferably, planning the flight path of the first aircraft according to the type of the second aircraft comprises:

[0038] If the second aircraft is in a certain collision area set, and if the second aircraft is currently stationary;

[0039] Adjusting the flight altitude of the first aircraft until the plane where the first aircraft is located is offset from the plane where the second aircraft is located;

[0040] After the height of the first aircraft is adjusted, the acceleration of the first aircraft is changed to , where n is a unit vector, is the maximum acceleration of the first aircraft.

[0041] Preferably, planning the flight path of the first aircraft according to the type of the second aircraft comprises:

[0042] If the second aircraft is in a certain collision area set, and if the second aircraft is currently moving;

[0043] The first aircraft allowed movement time is expressed as:

[0044]

[0045] in, The latest movement time allowed for the first aircraft, is the current time;

[0046] The allowed movement path of the first aircraft is expressed as:

[0047]

[0048] in, is the maximum height to which the first aircraft can move, The current altitude of the first aircraft;

[0049] Calculate the path planning cost based on the allowed movement time and allowed movement path of the first aircraft:

[0050]

[0051] in, is the time required for the first aircraft to bypass the second aircraft, The flight altitude required for the first aircraft to bypass the second aircraft;

[0052] Choose the flight path with the lowest movement cost for obstacle avoidance.

[0053] A low-altitude integrated air traffic management system, comprising:

[0054] A flight information module, used to detect a second aircraft within a preset range of the first aircraft;

[0055] An operation status module, used for classifying the type of the second aircraft according to the distance between the second aircraft and the first aircraft;

[0056] An airspace management module is used to plan a flight path of the first aircraft according to the type of the second aircraft.

[0057] An electronic device comprises: a processor and a memory, wherein the memory is used to store computer program codes, and the computer program codes comprise computer instructions. When the processor executes the computer instructions, the electronic device executes a low-altitude integrated air traffic management method.

[0058] The beneficial effects of the present invention are: 1. The present invention can divide the second aircraft into different threat levels according to the distance between the first aircraft and the second aircraft, and make different flight path planning schemes according to the threat level of the second aircraft, and can cope with various flight environments; 2. The present invention can adjust the obstacle avoidance route of the first aircraft in real time according to the motion state of the second aircraft, breaking the limitation that the current first aircraft path planning only plans for the stationary second aircraft; 3. The present invention can adjust the flight altitude and flight speed at the same time, can select the optimal obstacle avoidance path from multiple obstacle avoidance paths, can enable the first aircraft to reach the destination faster, and can also adaptively adjust the flight path evaluation parameters according to user needs, and is suitable for different types of first aircraft. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0060] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0061] Figure 1 A schematic diagram of a low-altitude integrated air traffic management method of the present invention;

[0062] Figure 2A schematic diagram of a distance calculation process between a first aircraft and a second aircraft according to the present invention;

[0063] Figure 3 The figure is a schematic diagram of the hardware structure of an electronic device of the present invention. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0065] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0066] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0067] In recent years, a large number of studies have proposed conflict resolution technologies to resolve air traffic conflict crises. Conflict resolution aims to resolve potential conflicts of the first aircraft during operation according to the flight plan of the first aircraft, and is a key technology to ensure the safe operation of the first aircraft. The existing conflict resolution methods include adjusting the take-off time, flight speed, horizontal flight track, and altitude layer allocation of the first aircraft, and their combinations. However, they only resolve local conflicts within a limited range.

[0068] Due to the coupling relationship between the first aircraft and the complex environment of low-altitude airspace, the existing conflict resolution strategy is difficult to apply to the coordinated control between multiple first aircraft and the global obstacle avoidance strategy of multiple second aircraft. Therefore, the flight conflict resolution control strategy of multiple first aircraft and multiple second aircraft has become a key technology to be solved in the low-altitude integrated air traffic management system.

[0069] The present invention can classify different threat levels of the second aircraft according to the distance between the first aircraft and the second aircraft, and make different flight path planning schemes according to the threat level of the second aircraft, and can cope with various flight environments; the present invention can adjust the obstacle avoidance route of the first aircraft in real time according to the motion state of the second aircraft, breaking the limitation that the current first aircraft path planning only plans for the stationary second aircraft; the present invention can adjust the flight altitude and the flight speed at the same time, can select the optimal obstacle avoidance path from multiple obstacle avoidance paths, can enable the first aircraft to reach the destination faster, and can also adaptively adjust the flight path evaluation parameters according to user needs, and is suitable for different types of first aircraft.

[0070] Example 1

[0071] A low-altitude fusion air traffic management method, reference Figure 1 , including the steps of:

[0072] Step S100, detecting a second aircraft within a preset range of the first aircraft;

[0073] In the embodiment of the present invention, the first aircraft includes our drone, and the second aircraft is another drone. The other drone can be in a hovering state or in a moving state.

[0074] The ways in which aircraft detect obstacles include image recognition and radar detection. Radar detection is suitable for obstacle detection at a longer distance. In this embodiment, the radar detection distance is a preset range of obstacles, and image recognition is used to identify the details of detected objects at a closer distance to obstacles. For example, radar detection detects the presence of a second aircraft 500m ahead, and then when the first aircraft approaches the second aircraft, the shape of the second aircraft can be recognized. When there is a gap between the two second aircraft that can be passed through, the first aircraft can pass through between the two second aircraft.

[0075] Aircraft image recognition is the use of images collected by airborne cameras to identify and classify specific objects. At present, aircraft image recognition is mainly used for target reconnaissance, enemy surveillance and reporting in the military field, as well as geological surveys and hydrological monitoring in the civilian field. In aircraft image recognition technology, the first thing to achieve is image acquisition. With the development of multispectral sensor technology, aircraft can be equipped with a variety of cameras to obtain multispectral information and high-precision three-dimensional images. These high-quality data provide a broad space for subsequent image processing and recognition. There are mainly two aspects of image processing in aircraft image recognition technology. The first aspect is image segmentation, that is, to segment the target in the image from the background. The methods used include traditional threshold segmentation, supervised learning and unsupervised learning methods, as well as emerging deep learning methods. The second aspect is feature extraction, that is, extracting useful features from the segmented targets. The current mainstream method is a deep learning method based on convolutional neural network (CNN). By using CNN, features can be automatically learned to identify various targets in the image. Aircraft obstacle detection is mainly based on radar and visual methods. Among them, radar technology can analyze the shape, size, etc. of the object by detecting the echo signal of the object, and provide the depth information of the object. This method is more suitable for drone flights at night or in some harsh environments. However, radar technology also has its limitations because it cannot provide information such as the texture and color of the object. Unlike radar technology, the visual method mainly uses the camera of the drone to detect the surrounding environment. This method is mainly divided into two categories: based on monocular cameras and based on multi-cameras. In a monocular camera, only one camera obtains environmental information. This method is simple, but the detection range for obstacles is small. In a multi-camera, more abundant environmental information can be obtained through the method of camera combination. This method has greatly improved the detection distance and accuracy.

[0076] Step S200, classifying the second aircraft into types according to the distance between the second aircraft and the first aircraft;

[0077] The airspace of metropolitan environments will be shared by traditional manned aircraft and drones, and the dense operating environment of low-altitude airspace greatly increases the risk of conflict. In low-altitude urban areas, each drone must avoid various obstacles, such as static objects (high-rise buildings, trees, lamp posts, no-fly zones, etc.) and dynamic objects (cranes, other drones, manned aircraft, etc.). To this end, an advanced unmanned air traffic management system is needed to effectively handle flight conflicts in complex environments and ensure safety in a timely manner. Air traffic management mainly focuses on pre-planned flights between airports, and the schedules of these flights can be known in advance. In contrast, drone systems have high uncertainty in time and space. Drones can fly at any time and have no fixed waypoints. In addition, the current air traffic management system is a "man-in-the-loop" decision-making system, and human errors cannot be avoided, which is not conducive to the resolution of flight conflicts. In the field of unmanned aviation, drones will make multiple short flights, requiring a higher level of automation to resolve conflicts. Therefore, advanced conflict resolution tools and decision-making methods are needed to manage the large number of drone systems that are pouring in under unmanned air traffic management.

[0078] Step S300: planning a flight path of the first aircraft according to the type of the second aircraft.

[0079] A conflict refers to a state in which the distance between two aircraft is less than a specific interval, threatening the safety of the aircraft. Conflict detection and resolution is one of the core tasks of an aircraft control system. After the aircraft detects a possible conflict, it resolves the existing conflict threat through safe collision avoidance operations. Collision avoidance capability is an important factor in determining whether a drone can share airspace with other aircraft and whether it can perform tasks in a dynamic and uncertain environment. The obstacle avoidance algorithm proposed in the prior art takes into account the spatial position of the first aircraft and the second aircraft, and the calculation is simple, but it usually cannot obtain a smooth flight path, or there is a problem of local optimal points, and it cannot accurately reach the target.

[0080] The low-altitude fusion air traffic management method proposed in the present invention has the characteristics of simplicity, efficiency, safety and practicality. The interaction between aircraft can be mathematically described by calculating important air traffic characteristics (such as relative position and relative speed). In order to avoid collision, this valve adopts two ways to achieve the separation of aircraft, namely altitude change and speed change. Assuming that the first aircraft flies at a fixed altitude, the current position, speed and heading information of the first aircraft is used to deal with the plane airspace conflict problem based on the concept of relative motion. It can also have a small computational overhead when avoiding the second aircraft, ensuring real-time performance. An error bound is given during extraction so that the allowable error of the reachable set boundary has a limit, thereby completing the air traffic collision avoidance task.

[0081] Preferably, step S100, detecting a second aircraft within a preset range of the first aircraft includes:

[0082] Step S110, acquiring image data, millimeter wave radar data, satellite coordinate data and laser radar data collected in the flight direction of the first aircraft;

[0083] The equipment carried by the first aircraft includes a binocular camera, a millimeter-wave radar and a laser radar. The binocular camera is arranged at the end consistent with the forward direction of the drone, the millimeter-wave radar is arranged at the front, rear, left, right and bottom of the drone, and the laser radar is arranged at the end consistent with the forward direction of the drone.

[0084] Obtain left front image data and right front image data taken by the binocular camera along the flight direction of the UAV;

[0085] generating a depth map based on the left front image data and the right front image data;

[0086] Acquire forward laser radar data collected by the millimeter-wave radar along the flight direction of the UAV with the central area of ​​the depth map as the collection range, wherein the central area is a square in the depth map with the set coordinate point as the center and the set length as the side length;

[0087] Acquire forward laser radar data collected by the laser radar along the flight direction of the UAV with the central area as the collection range.

[0088] Step S120, calculating the profile of the second aircraft according to the image data;

[0089] Using an edge extraction algorithm to determine edge pixel points of the second aircraft in the forward image data;

[0090] Select each second aircraft included in the forward image data in the form of a rectangular frame according to the edge pixel points, and use the rectangular frame corresponding to the second aircraft as the corresponding second aircraft outline;

[0091] Step S130, calculating the distance information between the first aircraft and the second aircraft according to the satellite coordinate data;

[0092] Step S140: calibrate the distance information between the first aircraft and the second aircraft according to the millimeter wave radar data and the laser radar data.

[0093] Determine a ranging result corresponding to the second aircraft according to the second aircraft profile;

[0094] Determine a fused ranging result based on the forward image data, the forward millimeter-wave radar data, and the forward lidar data;

[0095] First, the first aircraft and the second aircraft are positioned and their approximate distances are calculated using satellite coordinate data, and then the smaller of the distance measurement result and the fused distance measurement result is used as the distance information between the first aircraft and the second aircraft.

[0096] Preferably, in step S200, the second aircraft is classified into types according to the distance between the second aircraft and the first aircraft:

[0097] Calculate the clustering coefficient of the second aircraft within the preset range of the first aircraft:

[0098]

[0099] Among them, N represents the number of conflicting edges of K second aircraft with which the first aircraft node has conflicts, and Q is the clustering coefficient, which represents the degree of congestion of the second aircraft near the first aircraft.

[0100] The clustering coefficient can reflect the degree of crowding of the second aircraft near the first aircraft. If the clustering coefficient is small, it means that the degree of crowding of the second aircraft is low, and the obstacle avoidance of the first aircraft is easier and can be completed without complex algorithms. If the clustering coefficient is high, it means that there are many second aircraft near the first aircraft and the degree of crowding is high. In this case, the flight path of the first aircraft needs to be reasonably planned to ensure the flight safety of the first aircraft.

[0101] Preferably, step S200, classifying the second aircraft into types according to the distance between the second aircraft and the first aircraft includes:

[0102] Assume the motion model of the first aircraft is:

[0103] Wherein, P is the plane position of the first aircraft, V is the velocity of the first aircraft, a is the acceleration of the first aircraft, x is the horizontal coordinate of the first aircraft, and y is the vertical coordinate of the first aircraft. is the lateral velocity of the first aircraft, is the longitudinal velocity of the first aircraft, is the lateral acceleration of the first aircraft, is the longitudinal acceleration of the first aircraft;

[0104] The set of regions where the first aircraft and the second aircraft may collide is

[0105] The possible collision area indicates that the first aircraft can avoid the second aircraft by accelerating, decelerating, or detouring, that is, the first aircraft can avoid obstacles without adjusting the flight altitude. Usually, the second aircraft that appears in the possible collision area is a static second aircraft, and the first aircraft can avoid collision by simply detouring.

[0106] The set of regions where the first aircraft and the second aircraft are bound to collide is

[0107] The area of ​​certain collision is an area where the first aircraft cannot avoid the second aircraft by accelerating, decelerating, or detouring, that is, the first aircraft needs to adjust not only the flight speed and flight direction, but also the flight altitude to avoid the obstacle. Usually, the second aircraft that appears in the area of ​​certain collision is a dynamic second aircraft. In this case, if the first aircraft wants to bypass the second aircraft, it needs to change the speed, flight direction, and flight altitude at the same time to avoid the dynamic second aircraft.

[0108] The set of regions where the first aircraft and the second aircraft will not collide is

[0109] in, is the center of the second aircraft, r is the radius of the first aircraft, R represents the detection radius of the first aircraft, Indicates the radius of the second aircraft.

[0110] The non-collision area indicates an area where the first aircraft only needs to travel along the original route and will not collide with the second aircraft.

[0111] Preferably, determining whether the second aircraft conflicts with the first aircraft includes:

[0112] Calculate the remaining time until the second aircraft collides with the first aircraft:

[0113]

[0114] in, is the speed of the second aircraft, is the speed of the first aircraft, is the plane position of the first aircraft, is the plane position of the second aircraft, is the length of the second aircraft;

[0115] Assume that the sample with conflict risk is = 1, the normal sample is = 0, and the probability of risk occurrence is P' and 1-P' respectively to establish a binary Logit model. The binary Logit model is used to express the risk of conflict between the second aircraft and the first aircraft as:

[0116]

[0117] in, is a constant term, e is an independent variable vector, i.e., the conflict influencing factors, including the remaining time for the second aircraft to conflict with the first aircraft, k is the number of influencing factors, is the coefficient vector corresponding to the independent variable.

[0118] Logit is a type of discrete choice model, often used for classification problems. Since the Logit model can represent the regression relationship between a dependent variable and multiple unrelated independent variables, it is often used to analyze the influencing factors of binary dependent variables. The characteristics of the Logit model include the explicit characteristics of its probability expression, fast solution speed, and convenient application. When the model selection set has not changed, but only the levels of each variable have changed, the probability of each selection branch being selected in the new environment can be easily solved. According to the IIA characteristics of the Logit model, the reduction or increase of the selection branch does not affect the size of the selection probability ratio between other selections. Therefore, the selection branch that needs to be removed can be directly removed from the model, and the newly added selection branch can be added to the model for direct prediction.

[0119] Preferably, step S300, planning the flight path of the first aircraft according to the type of the second aircraft includes:

[0120] If the second aircraft is within the set of possible collision areas, the acceleration of the first aircraft at this time is expressed as:

[0121]

[0122] Where n is the unit vector, k is the acceleration proportional coefficient, is the center of the i-th second aircraft, is the radius of the i-th second aircraft.

[0123] In the problem of aircraft conflict resolution, a finite set of aircraft sharing the same airspace is considered. When a collision risk is detected between any pair of aircraft, a conflict avoidance maneuver is performed. The initial position, speed, and heading of the aircraft in the plane airspace determine the trajectory of the aircraft. The purpose of the study is to provide a new collision avoidance strategy for each aircraft to resolve all possible conflicts without excessively affecting the original trajectory of the first aircraft. The second aircraft should be kept as far away from the first aircraft as possible, so that the first aircraft is in an absolutely safe state.

[0124] Preferably, step S300, planning the flight path of the first aircraft according to the type of the second aircraft includes:

[0125] If the second aircraft is in a certain collision area set, and if the second aircraft is currently stationary;

[0126] Adjusting the flight altitude of the first aircraft until the plane where the first aircraft is located is offset from the plane where the second aircraft is located;

[0127] After the height of the first aircraft is adjusted, the acceleration of the first aircraft is changed to , where n is a unit vector, is the maximum acceleration of the first aircraft.

[0128] The acceleration control amount is set according to the distance between the first aircraft and the second aircraft and the radius of the second aircraft; once the second aircraft enters a certain collision area of ​​the first aircraft, the maximum control amount should be set to ensure the safety of the first aircraft. This algorithm can ensure that the first aircraft can safely avoid all second aircraft on the path with a smaller turning curvature.

[0129] Preferably, step S300, planning the flight path of the first aircraft according to the type of the second aircraft includes:

[0130] If the second aircraft is in a certain collision area set, and if the second aircraft is currently moving;

[0131] The first aircraft allowed movement time is expressed as:

[0132]

[0133] in, The latest movement time allowed for the first aircraft, is the current time;

[0134] The allowed movement path of the first aircraft is expressed as:

[0135]

[0136] in, is the maximum height to which the first aircraft can move, The current altitude of the first aircraft;

[0137] Calculate the path planning cost based on the allowed movement time and allowed movement path of the first aircraft:

[0138]

[0139] in, is the time required for the first aircraft to bypass the second aircraft, The flight altitude required for the first aircraft to bypass the second aircraft;

[0140] Choose the flight path with the lowest movement cost for obstacle avoidance.

[0141] In actual operation, air traffic controllers often seek a good balance between the number of conflicts of the first aircraft and the amount of adjustment of the track of the first aircraft. The function of controlling the path cost of the first aircraft also includes minimizing the number and amplitude of the maneuvers of the first aircraft, minimizing the risk of conflicts of the first aircraft, and minimizing the delay time of the first aircraft. As a preferred embodiment, the present invention selects the delay time of the first aircraft and the moving path required by the first aircraft as the planning cost of the path of the first aircraft. Because the calculation of multiple objective functions is large, the time of path planning will be greatly increased, resulting in reduced efficiency of the first aircraft, and some objective functions have little effect on the actual flight process, so the present invention uses the delay time of the first aircraft and the moving path required by the first aircraft as the planning cost of the path of the first aircraft.

[0142] Example 2

[0143] A low-altitude integrated air traffic management system, comprising:

[0144] A flight information module, used to detect a second aircraft within a preset range of the first aircraft;

[0145] An operation status module, used for classifying the type of the second aircraft according to the distance between the second aircraft and the first aircraft;

[0146] The airspace management module is used to plan the flight path of the first aircraft according to the type of the second aircraft.

[0147] Example 3

[0148] An electronic device includes: a processor and a memory, the memory is used to store computer program code, the computer program code includes computer instructions, when the processor executes the computer instructions, the electronic device executes a low-altitude integrated air traffic management method.

[0149] refer to Figure 3 , the electronic device 2 includes a processor 21, a memory 22, an input device 23, and an output device 24. The processor 21, the memory 22, the input device 23, and the output device 24 are coupled via a connector, and the connector includes various interfaces, transmission lines, or buses, etc., which are not limited in the embodiments of the present invention. It should be understood that in various embodiments of the present invention, coupling refers to mutual connection in a specific manner, including direct connection or indirect connection through other devices, for example, through various interfaces, transmission lines, buses, etc.

[0150] The processor 21 may be one or more graphics processing units (GPUs). When the processor 21 is a GPU, the GPU may be a single-core GPU or a multi-core GPU. Optionally, the processor 21 may be a processor group consisting of multiple GPUs, and the multiple processors are coupled to each other via one or more buses. Optionally, the processor may also be other types of processors, etc., which are not limited in the embodiments of the present invention.

[0151] The memory 22 can be used to store computer program instructions and various computer program codes including program codes for executing the scheme of the present invention. Optionally, the memory includes but is not limited to random access memory (RAM), read-only memory (ROM), erasable programmable read only memory (EPROM), or portable read only memory (CD-ROM), which is used for related instructions and data.

[0152] The input device 23 is used to input data and / or signals, and the output device 24 is used to output data and / or signals. The output device 24 and the input device 23 may be independent devices or an integrated device.

[0153] The present invention can classify different threat levels of the second aircraft according to the distance between the first aircraft and the second aircraft, and make different flight path planning schemes according to the threat level of the second aircraft, and can cope with various flight environments; the present invention can adjust the obstacle avoidance route of the first aircraft in real time according to the motion state of the second aircraft, breaking the limitation that the current first aircraft path planning only plans for the stationary second aircraft; the present invention can adjust the flight altitude and the flight speed at the same time, can select the optimal obstacle avoidance path from multiple obstacle avoidance paths, can enable the first aircraft to reach the destination faster, and can also adaptively adjust the flight path evaluation parameters according to user needs, and is suitable for different types of first aircraft.

[0154] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A low-altitude integrated air traffic management method, characterized in that: include: Detecting a second aircraft within a preset range of the first aircraft; classifying the second aircraft into types according to the distance between the second aircraft and the first aircraft; The classification of the second aircraft according to the distance between the second aircraft and the first aircraft is as follows: Calculate the clustering coefficient of the second aircraft within the preset range of the first aircraft: ； Where N represents the number of conflicting edges of K second aircrafts with which the first aircraft node has conflicts, Q is the clustering coefficient, which represents the degree of congestion of the second aircrafts near the first aircraft; The classification of the second aircraft according to the distance between the second aircraft and the first aircraft includes: Assume the motion model of the first aircraft is: ; Wherein, P is the plane position of the first aircraft, V is the velocity of the first aircraft, a is the acceleration of the first aircraft, x is the horizontal coordinate of the first aircraft, and y is the vertical coordinate of the first aircraft. is the lateral velocity of the first aircraft, is the longitudinal velocity of the first aircraft, is the lateral acceleration of the first aircraft, is the longitudinal acceleration of the first aircraft; The set of regions where the first aircraft and the second aircraft may collide is ; The set of regions where the first aircraft and the second aircraft are bound to collide is ； The set of regions where the first aircraft and the second aircraft will not collide is ; in, is the center of the second aircraft, r is the radius of the first aircraft, R represents the detection radius of the first aircraft, represents the radius of the second aircraft; planning a flight path of the first aircraft according to the type of the second aircraft; Planning the flight path of the first aircraft according to the type of the second aircraft comprises: If the second aircraft is within the set of possible collision areas, the acceleration of the first aircraft at this time is expressed as: ； Where n is the unit vector, k is the acceleration proportional coefficient, is the center of the i-th second aircraft, is the radius of the i-th second aircraft.

2. A low-altitude integrated air traffic management method according to claim 1, characterized in that: The detecting of a second aircraft within a preset range of the first aircraft comprises: Acquire image data, millimeter wave radar data, satellite coordinate data, and laser radar data collected in the flight direction of the first aircraft; calculating a profile of a second aircraft based on the image data; Calculate the distance information between the first aircraft and the second aircraft according to the satellite coordinate data; The distance information between the first aircraft and the second aircraft is calibrated according to the millimeter wave radar data and the laser radar data.

3. A low-altitude integrated air traffic management method according to claim 2, characterized in that: Determining whether the second aircraft conflicts with the first aircraft includes: Calculate the remaining time until the second aircraft collides with the first aircraft: ； in, is the speed of the second aircraft, is the speed of the first aircraft, is the plane position of the first aircraft, is the plane position of the second aircraft, is the length of the second aircraft; Assume that the sample with conflict risk is = 1, the normal sample is = 0, and the probability of risk occurrence is P' and 1-P' respectively to establish a binary Logit model. The binary Logit model is used to express the risk of conflict between the second aircraft and the first aircraft as: ； in, is a constant term, e is an independent variable vector, i.e., the conflict influencing factors, including the remaining time for the second aircraft to conflict with the first aircraft, k is the number of influencing factors, is the coefficient vector corresponding to the independent variable.

4. A low-altitude integrated air traffic management method according to claim 3, characterized in that: Planning the flight path of the first aircraft according to the type of the second aircraft comprises: If the second aircraft is in a certain collision area set, and if the second aircraft is currently stationary; Adjusting the flight altitude of the first aircraft until the plane where the first aircraft is located is offset from the plane where the second aircraft is located; After the height of the first aircraft is adjusted, the acceleration of the first aircraft is changed to , where n is a unit vector, is the maximum acceleration of the first aircraft.

5. A low-altitude integrated air traffic management method according to claim 4, characterized in that: Planning the flight path of the first aircraft according to the type of the second aircraft comprises: If the second aircraft is in a certain collision area set, and if the second aircraft is currently moving; The first aircraft allowed movement time is expressed as: ； in, The latest movement time allowed for the first aircraft, is the current time; The allowed movement path of the first aircraft is expressed as: ； in, is the maximum height to which the first aircraft can move, The current altitude of the first aircraft; Calculate the path planning cost based on the allowed movement time and allowed movement path of the first aircraft: ； in, is the time required for the first aircraft to bypass the second aircraft, The flight altitude required for the first aircraft to bypass the second aircraft; Choose the flight path with the lowest movement cost for obstacle avoidance.

6. A low-altitude integrated air traffic management system, characterized in that: include: A flight information module, used to detect a second aircraft within a preset range of the first aircraft; An operation status module, used for classifying the type of the second aircraft according to the distance between the second aircraft and the first aircraft; The classification of the second aircraft according to the distance between the second aircraft and the first aircraft is as follows: Calculate the clustering coefficient of the second aircraft within the preset range of the first aircraft: ； Where N represents the number of conflicting edges of K second aircrafts with which the first aircraft node has conflicts, Q is the clustering coefficient, which represents the degree of congestion of the second aircrafts near the first aircraft; The classification of the second aircraft according to the distance between the second aircraft and the first aircraft includes: Assume the motion model of the first aircraft is: ; Wherein, P is the plane position of the first aircraft, V is the velocity of the first aircraft, a is the acceleration of the first aircraft, x is the horizontal coordinate of the first aircraft, and y is the vertical coordinate of the first aircraft. is the lateral velocity of the first aircraft, is the longitudinal velocity of the first aircraft, is the lateral acceleration of the first aircraft, is the longitudinal acceleration of the first aircraft; The set of regions where the first aircraft and the second aircraft may collide is ; The set of regions where the first aircraft and the second aircraft are bound to collide is ； The set of regions where the first aircraft and the second aircraft will not collide is ; in, is the center of the second aircraft, r is the radius of the first aircraft, R represents the detection radius of the first aircraft, represents the radius of the second aircraft; an airspace management module, configured to plan a flight path of the first aircraft according to the type of the second aircraft; Planning the flight path of the first aircraft according to the type of the second aircraft comprises: If the second aircraft is within the set of possible collision areas, the acceleration of the first aircraft at this time is expressed as: ； Where n is the unit vector, k is the acceleration proportional coefficient, is the center of the i-th second aircraft, is the radius of the i-th second aircraft.

7. An electronic device, characterized in that: include: A processor and a memory, wherein the memory is used to store computer program codes, wherein the computer program codes include computer instructions. When the processor executes the computer instructions, the electronic device executes a low-altitude integrated air traffic management method as described in any one of claims 1 to 5.

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