CN117315998A - Method and device for detecting flight collision of aircraft - Google Patents

Method and device for detecting flight collision of aircraft Download PDF

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Publication number
CN117315998A
CN117315998A CN202210698958.7A CN202210698958A CN117315998A CN 117315998 A CN117315998 A CN 117315998A CN 202210698958 A CN202210698958 A CN 202210698958A CN 117315998 A CN117315998 A CN 117315998A
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aircraft
flight
main
conflict
state change
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隋东
涂诗晨
李倩
李雨露
杨威
韩卬学
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Nanjing University of Aeronautics and Astronautics
Boeing Co
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Nanjing University of Aeronautics and Astronautics
Boeing Co
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0043—Traffic management of multiple aircrafts from the ground
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2462—Approximate or statistical queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2474—Sequence data queries, e.g. querying versioned data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29—Geographical information databases

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  • Aviation & Aerospace Engineering (AREA)
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Abstract

The application discloses a method and a device for detecting flight conflict of an aircraft. A method of detecting a flight conflict of an aircraft, comprising: acquiring historical track data of a main aircraft, wherein the main aircraft refers to an aircraft with a changed flight state; determining a flight state change starting point of the main aircraft according to the historical track data of the main aircraft; acquiring flight state change start point information representing a flight state change start point of the main aircraft, and determining a plurality of potentially conflicting aircraft within a predetermined conflict range of the flight state change start point of the main aircraft based on the flight state change start point information of the main aircraft; predicting an original flight intent trajectory of a main aircraft and flight intent trajectories of a plurality of potentially conflicting aircraft; based on the primary flight intent trajectory of the primary aircraft and the flight intent trajectories of the plurality of potentially conflicting aircraft, a determination is made as to whether a flight conflict exists between the primary aircraft and the plurality of potentially conflicting aircraft.

Description

Method and device for detecting flight collision of aircraft
Technical Field
The present disclosure relates to the field of aerospace, and more particularly, to a method and apparatus for potential conflict detection and regulatory instruction speculation for aircraft based on real trajectory data.
Background
The controllers are very important operation units in the civil aviation transport system, the main tasks of the controllers are to monitor and command the aircrafts, prevent the aircrafts from colliding with the aircrafts and the aircrafts from colliding with ground obstacles, the normal work of the controllers can be influenced when the collision occurs in an air space, and the controllers need to distribute more energy to carry out collision resolution and allocation, so that the flight collision problems are researched, potential collisions in track data are analyzed, and a more perfect controller performance assessment mechanism is facilitated to be established; by analyzing the track data to establish a potential conflict scene and a corresponding release strategy of the controllers, the method can be helpful for researching an auxiliary decision-making system, better assist the work of the controllers and improve the operation efficiency of civil aviation transportation.
The flight conflict problem is mainly solved in two aspects of track prediction and a flight conflict model, wherein the track prediction refers to an estimation process of an aircraft future track by a certain prediction mode through analysis of the aircraft flight state, the prediction can be divided into long-term (1-24 h), medium-term (20 min) and short-term (5 min) predictions according to different detection time, various aspects of research are carried out on the prediction mode, and an aircraft kinematics model or a probability type prediction model based on various uncertain factor analysis in the flight process is established by utilizing the correlation theory of kinematics and aircraft aerodynamics. The flight conflict model is used for modeling the aircraft, abstracting a proper physical structure to represent the aircraft, and mainly comprises a particle motion model, a cube, an ellipse, a cylinder model and the like for building a protection area of the aircraft. Combining the step length and the prediction method of the track prediction with the physical structure of the aircraft established by the flight conflict model, establishing a flight conflict detection model, and detecting and judging whether conflicts exist between the aircraft and other aircraft.
The existing establishment of conflict scenes and research on conflict problems are mostly carried out based on simulation data or on the basis of control experience of first-line controllers, a great deal of time and personnel effort are required to be consumed in the modes, a certain gap exists between the experimental result and the actual running condition, and the actual control scenes are not objectively restored.
Disclosure of Invention
The technical problem to be solved by the present disclosure is to provide a method and apparatus for potential conflict detection and control instruction speculation of an aircraft based on real trajectory data, aiming at the above-mentioned deficiencies of the background art. The method and the device establish track prediction and conflict detection models aiming at different flight state change characteristics in a real track, and infer flight conflict resolution instructions possibly issued by a controller according to the change conditions of the flight states.
To achieve the above object, according to an aspect of the present disclosure, there is provided a method of detecting a flight collision of an aircraft, including the steps of: acquiring historical track data of a main aircraft, wherein the main aircraft refers to an aircraft with a changed flight state; determining a flight state change starting point of the main aircraft according to the historical track data of the main aircraft, and acquiring flight state change starting point information representing the flight state change starting point of the main aircraft; determining a plurality of potentially conflicting aircraft within a predetermined conflict range of a flight state change starting point of the main aircraft based on the flight state change starting point information of the main aircraft; predicting an original flight intent trajectory of a main aircraft and flight intent trajectories of a plurality of potentially conflicting aircraft; and detecting whether a flight conflict exists between the main aircraft and the plurality of potentially conflicting aircraft based on the original flight intent trajectory of the main aircraft and the flight intent trajectories of the plurality of potentially conflicting aircraft.
In one example according to this embodiment, acquiring historical trajectory data of a main aircraft includes the steps of: acquiring historical track data of a plurality of aircrafts; establishing a time sequence for historical track data of a plurality of aircrafts according to a time sequence; traversing a time sequence of historical trajectory data of the plurality of aircraft according to a predetermined time interval to obtain a flight state variation of the plurality of aircraft; and determining an aircraft having a change in flight status of equal to or greater than a predetermined threshold as a primary aircraft.
In one example according to this embodiment, the historical trajectory data for a plurality of aircraft may have been filtered and smoothed.
In one example according to the present embodiment, the flight state variation includes at least a flight altitude variation, a flight speed variation, and a flight heading variation, and an aircraft in which at least one of the flight altitude variation, the flight speed variation, and the flight heading variation is equal to or greater than a respective predetermined threshold value is determined as the main aircraft.
In one example according to this embodiment, predicting an original intent-to-fly trajectory of a primary aircraft and intent-to-fly trajectories of a plurality of potentially conflicting aircraft includes the steps of: acquiring flight state change information of a main aircraft, wherein the flight state change information at least comprises a flight state change starting point of the main aircraft and a flight state change quantity of the main aircraft; predicting the original flight intention track of the main aircraft according to the flight state change information of the main aircraft; the method comprises the steps of extracting flight information of a plurality of potentially conflicting aircraft from historical track data of the plurality of potentially conflicting aircraft to predict flight intent tracks of the plurality of potentially conflicting aircraft, the flight information of the plurality of potentially conflicting aircraft comprising at least a flight altitude, a flight speed and a flight heading of the plurality of potentially conflicting aircraft.
In one example according to this embodiment, predicting the primary flight intent trajectory of the main aircraft includes: according to the flight state change information of the main aircraft, establishing a flight state change scene of the main aircraft; setting a predicted time step; establishing a particle prediction model based on kinematics and mechanics by using a flight state change scene and a prediction time step of the main aircraft; and predicting the original flight intention track of the main aircraft by utilizing a kinematic and mechanical particle prediction model according to the flight state change starting point information of the main aircraft and the flight state change scene of the main aircraft.
In one example according to the present embodiment, when the flight state change scene is a climb-to-level flight scene, continuous climb prediction is performed based on flight state change start point information of the main aircraft, and an original flight intention trajectory of the main aircraft that maintains an original flight intention is predicted with a maximum cruising altitude of the main aircraft as an upper limit of climb; when the flight state change scene is a descent and leveling flight scene, continuously descending prediction is carried out based on the flight state change starting point information of the main aircraft, and the original flight intention track of the main aircraft is predicted based on the potential descending flight height of the main aircraft; when the flight state change scene is a flat flight change climbing and flat flight change descending scene, carrying out continuous flat flight prediction based on the flight state change starting point information of the main aircraft so as to predict the original flight intention track of the main aircraft; when the flight state change scene is a turning scene, continuously and directly predicting the original flight intention track of the main aircraft based on the flight state change starting point information of the main aircraft; when the flight state change scene is an acceleration/deceleration scene, carrying out continuous uniform flight prediction based on the flight state change starting point information of the main aircraft to predict the original flight intention track of the main aircraft; when the flight state change scene is an acceleration and deceleration change speed scene, continuously accelerating or decelerating flight prediction is performed based on the flight state change starting point information of the main aircraft so as to predict the original flight intention track of the main aircraft.
In one example according to this embodiment, detecting whether a flight conflict exists between the main aircraft and the plurality of potentially conflicting aircraft further comprises the steps of: and when the detection result is affirmative, acquiring conflict detection result information between the main aircraft and a conflict aircraft which conflicts with the main aircraft, wherein the conflict detection result information at least comprises flight state change starting point information of the conflict aircraft.
In one example according to this embodiment, detecting whether a flight conflict exists between a primary aircraft and a plurality of potentially conflicting aircraft includes: determining the conflict type of the potential conflict between the main aircraft and the plurality of potential conflict aircraft according to the original flight intention track of the main aircraft and the flight intention tracks of the plurality of potential conflict aircraft; establishing a corresponding safety interval threshold according to the conflict type of the potential conflict; determining a flight interval between the main aircraft and the plurality of potentially conflicting aircraft based on the primary flight intent trajectory of the main aircraft and the flight intent trajectories of the plurality of potentially conflicting aircraft; when the flight interval is less than the corresponding safety interval threshold, it is determined that a flight conflict exists between the primary aircraft and the plurality of potentially conflicting aircraft.
In one example according to this embodiment, the method further comprises: extracting respective flight state change end point information of the main aircraft and the conflict aircraft from the historical trajectory data according to the respective flight state change start point information of the main aircraft and the conflict aircraft, and calculating flight state changes of the main aircraft and the conflict aircraft according to the respective flight state change start point information and the flight state change end point information of the main aircraft and the conflict aircraft, thereby presuming a control instruction for conflict resolution of the main aircraft and the conflict aircraft.
In one example according to the present embodiment, the collision detection result information further includes: the predicted point time, the main aircraft call sign, the conflicting aircraft call sign, the time when the conflict occurs, the location of the conflict points, the number of conflicting aircraft, the conflict type, the interval status of the conflict points, and the control instructions include at least main aircraft control instructions for the main aircraft regarding altitude, speed and heading and conflicting aircraft control instructions for the conflicting aircraft regarding altitude, speed and heading.
In one example according to this embodiment, the method further comprises: analyzing and processing the conflict detection result information and the control instruction to delete the repeated information and output a final conflict detection and control instruction presumption result, wherein analyzing and processing the conflict detection result information and the control instruction comprises the following steps: deleting repeated conflict detection result information when the paired main aircraft and the conflict aircraft are identical and the conflict occurrence time difference is smaller than a first preset time interval; and when the conflict detection result information with the same conflict main aircraft number and the predicted point time difference smaller than the second preset time interval exists in the at least two conflicts in the deleted conflict detection result information, merging the at least two conflicts into a multi-aircraft conflict.
To achieve the object of the present disclosure, according to another aspect of the present disclosure, there is provided an apparatus for detecting a flight collision of an aircraft, comprising: the data acquisition module is configured to acquire historical track data of a main aircraft, wherein the main aircraft refers to an aircraft with a changed flight state; a flight state change determining module configured to determine a flight state change start point of the main aircraft from historical trajectory data of the main aircraft, and acquire flight state change start point information representing the flight state change start point of the main aircraft; a potentially conflicting aircraft determination module configured to determine a plurality of potentially conflicting aircraft within a predetermined conflict range of a flight state change start point of the main aircraft based on flight state change start point information of the main aircraft; a trajectory prediction module configured to predict an original flight intent trajectory of a main aircraft and flight intent trajectories of a plurality of potentially conflicting aircraft; and a collision detection module configured to detect whether a flight collision exists between the main aircraft and the plurality of potentially conflicting aircraft based on the original flight intent trajectory of the main aircraft and the flight intent trajectories of the plurality of potentially conflicting aircraft.
In another example according to this embodiment, the data acquisition module is further configured to: acquiring historical track data of a plurality of aircrafts; establishing a time sequence for historical track data of a plurality of aircrafts according to a time sequence; traversing a time sequence of historical trajectory data of the plurality of aircraft according to a predetermined time interval to obtain a flight state variation of the plurality of aircraft; and determining an aircraft having a change in flight status of equal to or greater than a predetermined threshold as a primary aircraft.
In another example according to this embodiment, the data acquisition module may further filter and smooth historical trajectory data of a plurality of aircraft and determine the main aircraft based on the filtered and smoothed historical trajectory data.
In another example according to the present embodiment, the flight state variation includes at least a flight altitude variation, a flight speed variation, and a flight heading variation, and an aircraft in which at least one of the flight altitude variation, the flight speed variation, and the flight heading variation is equal to or greater than a respective predetermined threshold value is determined as the main aircraft.
In another example according to this embodiment, the trajectory prediction module is further configured to: acquiring flight state change information representing a change in the flight state of the main aircraft, the flight state change information including at least a flight state change start point of the main aircraft and a flight state change amount of the main aircraft; predicting the original flight intention track of the main aircraft according to the flight state change information of the main aircraft; and extracting flight information of the plurality of potentially conflicting aircraft from historical trajectory data of the plurality of potentially conflicting aircraft to predict a flight intent trajectory of the plurality of potentially conflicting aircraft, the flight information of the plurality of potentially conflicting aircraft including at least a flight altitude, a flight speed, and a flight heading of the plurality of potentially conflicting aircraft.
In another example according to this embodiment, the trajectory prediction module is further configured to: according to the flight state change information of the main aircraft, establishing a flight state change scene of the main aircraft; setting a predicted time step; establishing a particle prediction model based on kinematics and mechanics by using a flight state change scene and a prediction time step of the main aircraft; and predicting the original flight intention track of the main aircraft by utilizing a kinematic and mechanical particle prediction model according to the flight state change starting point information of the main aircraft and the flight state change scene of the main aircraft.
In another example according to this embodiment, the collision detection module is further configured to acquire collision detection result information between the main aircraft and a collision aircraft that collides with the main aircraft, the collision detection result information including at least flight state change start point information of the collision aircraft, when the detection result is affirmative.
In another example according to this embodiment, the collision detection module is further configured to: determining the conflict type of the potential conflict between the main aircraft and the plurality of potential conflict aircraft according to the original flight intention track of the main aircraft and the flight intention tracks of the plurality of potential conflict aircraft; establishing a corresponding safety interval threshold according to the conflict type of the potential conflict; determining a flight interval between the main aircraft and the plurality of potentially conflicting aircraft based on the primary flight intent trajectory of the main aircraft and the flight intent trajectories of the plurality of potentially conflicting aircraft; and determining that there is a conflicting aircraft of the plurality of potentially conflicting aircraft that is in flight conflict with the primary aircraft when the flight interval is less than the corresponding safety interval threshold.
The apparatus further comprises: a policing instruction prediction module configured to: extracting respective flight state change end point information of the main aircraft and the conflict aircraft from the historical track data according to respective flight state change start point information of the main aircraft and the conflict aircraft, and calculating flight state changes of the main aircraft and the conflict aircraft according to the respective flight state change start point information and the flight state change end point information of the main aircraft and the conflict aircraft, thereby presuming control instructions for conflict resolution of the main aircraft and the conflict aircraft, wherein the control instructions at least comprise main aircraft control instructions for the relevant flight altitude, flight speed and flight heading of the main aircraft and conflict aircraft control instructions for the relevant flight altitude, flight speed and flight heading of the conflict aircraft; the arrangement output module receives the conflict detection result information from the conflict detection module and the control instruction from the control instruction presumption module, and analyzes and processes the conflict detection result information and the control instruction so as to delete repeated conflict detection result information when the paired main aircraft and the conflict aircraft are identical and the conflict occurrence time difference is smaller than a first preset time interval; and when the conflict detection result information with the same conflict main aircraft number and the predicted point time difference smaller than the second preset time interval exists in the at least two conflict detection result information, merging the at least two conflicts into a multi-aircraft conflict, deleting repeated information, and outputting a final conflict detection and control instruction estimation result.
According to yet another aspect of the present disclosure, there is also provided a computer readable storage medium storing a program which, when executed by a processor, is adapted to carry out the above-described method of detecting a flight conflict of an aircraft.
Drawings
Fig. 1 is a block diagram of an apparatus for aircraft potential flight conflict detection and release instruction speculation based on true trajectory data in accordance with an embodiment of the present disclosure.
Fig. 2 is a flowchart of a method of aircraft potential flight conflict detection and release instruction speculation based on real trajectory data in accordance with an embodiment of the present disclosure.
Fig. 3 is a schematic diagram illustrating a determination of a flight status change start point.
FIG. 4 is a schematic representation of a prediction of a climb-to-level fly scenario.
Fig. 5 is a schematic diagram of a prediction of a descent-corrected fly scene.
Fig. 6 is a table of statistically calculated falling height probabilities.
Fig. 7a shows a schematic view of scene prediction of a flat fly change climb, and fig. 7b shows a schematic view of scene prediction of a flat fly change descent.
Fig. 8 is a schematic diagram of prediction of a turning scene.
Fig. 9a, 9b and 9c are schematic diagrams of three collision types, respectively.
Fig. 10 is a schematic diagram illustrating the determination of the end point of the change in the flight status.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings. The embodiments described below by referring to the drawings are exemplary only for explaining the present invention and are not to be construed as limiting the present invention.
Fig. 1 is a block diagram of an apparatus for aircraft potential flight conflict detection and release instruction speculation based on true trajectory data in accordance with an embodiment of the present disclosure. As shown in fig. 1, an apparatus for aircraft potential flight collision detection and instruction speculation release (hereinafter referred to simply as detection and speculation apparatus) 100 may include: a data acquisition module 101, a flight status change determination module 102, a potential conflict aircraft determination module 103, a trajectory prediction module 104, a conflict detection module 105, a policing instruction speculation module 106, and a collation output module 107. The respective modules described above are specifically described below.
The data acquisition module 101 may acquire historical trajectory data main_track_d of the main aircraft, which refers to an aircraft whose flight state changes, and may provide the acquired historical trajectory data main_track_d of the main aircraft to the flight state change determination module 102.
As an example, the data acquisition module 101 may receive, via an interface (not shown) from a general call room of a civil aviation general office in a wired or wireless manner, historical track data track_d of a plurality of aircraft, for example, national historical track data, which is typically stored in XML format in a data format for a recording time interval of 8s, and may be historical track radar data.
Since the nationwide historical track data is formed by splicing radar data of all the regulatory regions of the whole country, partial data is not recorded or recorded in error when radar recording and data splicing are performed, so that noise data are filled in, noise data with larger phase difference with real data are generated in final data, and in order to ensure availability and integrity of the final data, the data acquisition module 101 can perform smooth average calculation on the historical track data track_D of a plurality of aircraft by using a filter in a "smoothdata" function in MATLAB after receiving the historical track data track_D of the plurality of aircraft, and eliminate data noise, thereby performing smooth filtering processing on the track. The function uses mainly various filters to calculate the average of the trace point values in steps.
Specifically, noise data in radar trajectory data exists mainly in the horizontal direction and the vertical direction. In the horizontal direction, a gaussian weighted moving average filter is used. Gaussian filtering smoothes data using a distribution of two-dimensional gaussian functions, sets the moving step size to 50, calculates a gaussian average from the step size, and replaces noise data with a gaussian weighted average, as shown in formula (1):
Wherein G is i (long, lat) Gaussian function value, σ of the locus point i 2 Representing variance, long i Longitude, lat representing track point i i Representing the latitude of the trajectory point i, and x represents the calculated weight. The reason for using the gaussian filter is that the gaussian function is symmetrical and the degree of smoothing in all directions is the same and the direction of the original data will not change when the smoothing process is performed.
In the vertical direction, there are two cases where the noise height difference is large and the noise height difference is small. For the case that the noise point height difference is large, setting the height value of the noise point as the height value of the normal track point, namely, the previous track point; for the case where the noise height difference is small, a moving average filter is used and the moving step is set to 10. Calculating an average value of the data according to the step length, and replacing noise data with the average value, as shown in formula (2):
wherein h is i Representing the flying height of the locus point i.
Further, after receiving the historical track data track_d of the plurality of aircraft and performing the smoothed average calculation on the historical track data track_d of the plurality of aircraft, the data acquisition module 101 may further establish a time series for the historical track data track_d of the plurality of aircraft in a time sequence, as described above, since the track data of each flight is constituted of, for example, 8 s-spaced track points and thus the nationwide historical track data are merged, all track points of all flights are ordered in time intervals of 8s, establishing a time series. The data acquisition module 101 may also traverse a time series of historical trajectory data track_d of a plurality of aircraft according to a predetermined time interval to acquire a flight state variation amount of the plurality of aircraft, and determine an aircraft whose flight state variation amount is equal to or greater than a predetermined threshold value as the main aircraft and thereby acquire the historical trajectory data track_d of the main aircraft. Optionally, the data acquisition module 101 may also acquire profile information of the main aircraft, such as a main aircraft call sign.
Further, the above-described flight state change amount may include a flight altitude change amount, a flight speed change amount, a flight heading change amount, and the like of the aircraft. Also, for example, an aircraft having at least one of a change in altitude, a change in flight speed, and a change in flight heading that is equal to or greater than a corresponding predetermined threshold may be determined as the main aircraft.
For example, in normal operation, when there is no conflict or other special conditions, the aircraft will run absolutely according to the flight plan route, and the trace represents that there is less state change in the trace data, and when there is a conflict, the controller intervenes in the operation of the aircraft to allocate the conflict, so that the state of the aircraft changes, so that the aircraft changes in the flight state as a trigger, and it is determined whether the flight state change is caused by the conflict allocation.
In addition, the change of the flight state is that the aircraft changes from a stable state to an unstable state or from an unstable state to a stable state, and mainly includes a change of the flight altitude, a change of the flight speed and a change of the heading, and the flight state is slightly fluctuated due to a certain degree of air disturbance during the flight of the aircraft, so that in order to determine whether the flight state is changed, a state change threshold value needs to be set, and the state change threshold value is determined according to relevant regulations in CCAR-93TM-R2 (86 order) and ICAO DOC4444, for example, the altitude change threshold value may be 300m, the speed change threshold value may be 20km/h, and the heading change threshold value may be 15 °. When one or more of the altitude, speed and heading of the track point changes and exceeds a threshold value, the flying state is judged to change, and in actual operation, when the flying height change is greater than or equal to 300m and/or the flying speed change is greater than or equal to 20km/h and/or the heading change is greater than or equal to 15 degrees, the flying state is judged to change, as shown in fig. 3, because the flying height change is equal to 300m, the flying state of the aircraft is judged to change. It should be noted that the data acquisition module 101 may iterate through the established time series to retrieve aircraft whose flight status changes and acquire historical trajectory data thereof.
Specifically, trajectory data of the current flight of the aircraft is refreshed and calculated in time series. When the flight of the aircraft occurs for the first time, recording the flight state change of the aircraft as 0; the flight state (speed, heading and altitude) of the aircraft is calculated when the aircraft is flying for a plurality of times, as shown in formula (3):
where k is the number of flushes for flight i, v is the flight speed for flight i, α is the heading for flight i, and h is the altitude for flight i.
When one or more of the cumulative changes exceeds a set threshold value, a change in the flight state of the flight is determined and initialized, and then the established time series is traversed to retrieve the aircraft whose flight state has changed and obtain historical trajectory data thereof.
The flight State change determination module 102 may receive the historical trajectory data track_d of the main aircraft from the data acquisition module 101, determine a flight State change start point of the main aircraft from the historical trajectory data track_d of the main aircraft, and acquire flight State change start point information state_in indicating the flight State change start point of the main aircraft.
Alternatively, the flight State change determination module 102 may also extract or determine a flight State change end point of the main aircraft based on the historical trajectory data track_d of the main aircraft received from the data acquisition module 101 and the acquired flight State change start point information state_in of the main aircraft, and acquire flight State change end point information indicating the flight State change end point of the main aircraft. The flight state change start point information and the flight state change end point information may be regarded as one type of flight state change information.
The potentially conflicting aircraft determination module 103 may receive the State of flight change start point information state_in of the main aircraft from the State of flight change determination module 102 and determine a plurality of potentially conflicting aircraft within a predetermined range of conflict of the State of flight change start point of the main aircraft based on the State of flight change start point information state_in of the main aircraft.
As an example, the potentially conflicting aircraft determination module 103 may construct a conflict range for the main aircraft, e.g., within 300km, centered around the flight state change start point for the main aircraft, and thereby determine all aircraft within the conflict range as potentially conflicting aircraft.
For example, when the flight state of the main aircraft changes, it is necessary to determine the aircraft that may collide with the main aircraft, determine the influence range of the main aircraft, calculate the range with the maximum range of collision, that is, the collision distance of head-to-head collision, calculate the aircraft speed with an average of 900km/h, and estimate the time within 5-10 min, and the distance of head-to-head collision is about 150-300 km, so that the square influence range of 300km is established with the starting point of the state change of the main aircraft as the center, and information of all potentially colliding aircraft in the range is obtained.
After the historical trajectory data for the main aircraft is acquired by the data acquisition module 102 determining that there is a main aircraft with a change in flight status, it is determined that a flight conflict may exist in practice and that a controller may issue a regulatory instruction to avoid a conflict between aircraft. Therefore, in this case, it is advantageous to predict the primary flight intent trajectory of the main aircraft and the flight intent trajectories of potentially conflicting aircraft to infer whether and what control instructions are issued by the controllers. The primary flight intention refers to that when no conflict or special situation occurs, the primary aircraft should keep the primary flight state to continue to fly, so the primary flight intention is mainly "keep the primary flight state to continue to fly", and the prediction of the flight trajectory is performed, where the primary flight intention trajectory of the primary aircraft and the flight intention trajectory of the potentially conflicting aircraft may be predicted by the trajectory prediction module 104.
As an example, the trajectory prediction module 104 may receive historical trajectory data of the main aircraft from the data acquisition module 101 according to the call sign of the main aircraft and historical trajectory data of the plurality of potentially conflicting aircraft determined according to the potentially conflicting aircraft determination module 103 from the data acquisition module 101, and obtain, from the historical trajectory data of the main aircraft, flight state change information representing a change in flight state of the main aircraft, which may include flight state change start point information representing a flight state change start point of the main aircraft and a flight state change amount of the main aircraft, which may include a flight altitude change amount, a flight speed change amount, and a flight heading change amount, as described above.
The track prediction module 104 may predict an original flight intent track of the main aircraft according to flight state change information of the main aircraft; and extracting flight information for the plurality of potentially conflicting aircraft from historical trajectory data for the plurality of potentially conflicting aircraft to predict flight intent trajectories for the plurality of potentially conflicting aircraft. The flight information for the plurality of potentially conflicting aircraft may include the altitude, speed, heading, etc. of the plurality of potentially conflicting aircraft. Wherein the primary flight intent trajectory of the main aircraft and the flight intent trajectories of the plurality of potentially conflicting aircraft may be represented by the same symbol o_track.
As an example, the trajectory prediction module 104 may establish a flight state change scene of the main aircraft according to the acquired flight state change start point information of the main aircraft and the flight state change amount of the main aircraft, where the flight state change scene may include: climbing and leveling off scene, descending and leveling off scene, turning scene, acceleration and deceleration and leveling scene; setting a predicted time step, which may be, for example, 5 minutes; establishing a particle prediction model based on kinematics and mechanics by using a flight state change scene and a prediction time step of the main aircraft; and predicting the original flight intention track of the main aircraft by utilizing a kinematic and mechanical particle prediction model according to the flight state change starting point information of the main aircraft and the flight state change scene of the main aircraft. The different flight state change scenarios will be described one by one.
In particular, kinematic and mechanical particle prediction models ignore factors such as the mass, shape, and size of the aircraft itself, and treat it as a moving particle. The flight characteristics of an aircraft are considered to be the motion characteristics of moving particles, including longitude, latitude, altitude, heading, speed, acceleration, climb or descent gradients, and the like. Finally, the future motion trajectories and positions of the particles are calculated from time using a kinematic model. As shown in equation (4), the time step may be 1s.
Wherein long is 0 、lat 0 、h 0 、v 0 For the initial longitude, latitude, altitude, and speed of the state change starting point, a is the acceleration of the state change starting point, α is the heading of the state change starting point, and θ is the climbing or falling gradient of the state change starting point.
When the flight state change scenario is a climb-leveling flight scenario, the trajectory prediction module 104 may perform continuous climb prediction based on flight state change start point information of the main aircraft, and predict an original flight intent trajectory of the main aircraft to maintain an original flight intent with a maximum cruising altitude of the main aircraft as an upper limit of climb, as shown in fig. 4.
When the flight state change scene is a descent-to-level flight scene, the trajectory prediction module 104 may perform continuous descent prediction based on the flight state change start point information of the main aircraft, and predict the original flight intent trajectory of the main aircraft based on the potential descent flight altitude of the main aircraft, as shown in fig. 5.
In this case, the flying heights of the aircraft at different distances from the landing airport can be counted, a descent height probability table is established, and the predicted potential descent flying heights are obtained from the probability table. Specifically, the nationwide historical track data is analyzed, a distance interval with 100km as an interval is established, the flying height of each flight when landing at different distance intervals from an airport is counted, an airport landing distance-descent height statistical table is obtained, and then a descent height probability table is established by using a Gaussian kernel probability density function (shown in fig. 6). The calculation method is shown in the formula (5),
wherein,indicating when the distance from the airport is d i Flying height FL at km j Probability of->And->When the distance from the airport is d i Flying height FL at km j And FL (field effect transistor) k Number of flights/time->Is the distance d from the airport i Total number of flights, sigma 2 Representing the variance.
The descent height probability table is used to determine possible descent flying heights of the aircraft at different distances. The Gaussian kernel probability density function estimation is to use the number and the bandwidth of flights of each flight altitude under the same airport landing distance as parameters of the kernel function, then form a kernel density estimation function according to linear superposition, and finally determine that the flight altitude arrives at an airport with a standardized probability value of the landing distance.
The possible descent flying heights of the aircraft at different distances are determined in the above manner. The primary flight intent trajectory of the main aircraft can thus be predicted from the possible descent flight altitude of the main aircraft and the flight state change start point information.
When the flight state change scene is a flat flight change out scene such as a flat flight change climb and flat flight change descent scene, the trajectory prediction module 104 may perform continuous flat flight prediction based on the flight state change start point information of the main aircraft to predict the original flight intention trajectory of the main aircraft, as shown in fig. 7a and 7 b.
When the flight state change scene is a turning scene, the trajectory prediction module 104 may perform continuous direct flight prediction based on the flight state change start point information of the main aircraft to predict the original flight intent trajectory of the main aircraft, as shown in fig. 8.
When the flight state change scene is an acceleration/deceleration scene, the trajectory prediction module 104 may predict the original flight intent trajectory of the main aircraft by performing continuous uniform flight prediction based on the flight state change start point information of the main aircraft.
When the flight state change scene is an acceleration/deceleration change speed scene, the trajectory prediction module 104 may perform continuous acceleration or deceleration flight prediction based on the flight state change start point information of the main aircraft to predict the original flight intent trajectory of the main aircraft.
Further, the collision detection module 105 may receive the primary flight intent trajectory of the primary aircraft and the flight intent trajectories o_track of the plurality of potentially conflicting aircraft from the trajectory prediction module 104 and detect whether there is a flight collision between the primary aircraft and the plurality of potentially conflicting aircraft, i.e., whether there is a conflicting aircraft of the plurality of potentially conflicting aircraft that collides with the primary aircraft, based on the primary flight intent trajectory of the primary aircraft and the flight intent trajectories o_track of the plurality of potentially conflicting aircraft.
Specifically, the conflict detection module 105 may determine a conflict type of the potential conflict of the main aircraft with the plurality of potential conflicting aircraft based on the original flight intent trajectory of the main aircraft and the flight intent trajectories o_track of the plurality of potential conflicting aircraft. The flight conflict refers to the situation that the horizontal and vertical intervals between the aircrafts do not meet the requirements of the air traffic management rule, and because different control units have different control operation requirements, whether the flight conflict occurs needs to be judged according to the actual operation requirements. The types of collisions are classified into three types according to the angle of flight between aircraft: head-on conflicts, cross conflicts, and co-directional conflicts, as shown in fig. 9a, 9b, and 9 c.
The conflict detection module 105 may establish a corresponding safety interval threshold according to the conflict type of the potential conflict, specifically, different safety interval standards are set according to different conflict types, for example, the opposite-head conflict may be a horizontal interval of 50km, the cross conflict may be a horizontal interval of 30km, the equidirectional conflict may be a horizontal interval of 20km, and the vertical intervals of the three conflicts may be 280m. The collision detection module 105 may determine a flight interval between the main aircraft and the plurality of potentially conflicting aircraft based on the original flight intent trajectory of the main aircraft and the flight intent trajectories of the plurality of potentially conflicting aircraft, and determine that a conflicting aircraft of the plurality of potentially conflicting aircraft is in conflict with the main aircraft when the flight interval is less than a corresponding safety interval criterion.
Specifically, comparing each of the main aircraft and the plurality of potentially conflicting aircraft one by one, and calculating a distance between a predicted trajectory point of the main aircraft and the potentially conflicting aircraft, including a horizontal distance and a vertical distance, to obtain a distance matrix and a altitude matrix, as shown in formula (6):
wherein,representing a distance matrix between the predicted trajectory point of the main aircraft and the potentially conflicting aircraft i, and +. >Representing the altitude matrix between the predicted trajectory points of the main aircraft and the potentially conflicting aircraft i.
And then, judging whether track points exist in the distance matrix and the altitude matrix and do not meet the safety interval standard according to the relative flight state between the main aircraft and the potential conflict aircraft. If so, judging the potential conflict aircraft as the conflict aircraft which collides with the main aircraft, and acquiring the relevant information of conflict scenes such as the time of occurrence of the conflict, the conflict type, the interval state of the conflict points and the like, otherwise, no flight conflict exists between the main aircraft and the potential conflict aircraft.
Upon determining that there is a conflicting aircraft that conflicts with the main aircraft among the plurality of potentially conflicting aircraft, the conflict detection module 105 may extract or obtain conflict detection result information detect_in between the main aircraft and the conflicting aircraft based on the historical trajectory data of the main aircraft and the historical trajectory data of the conflicting aircraft. The collision detection result information detect_in may include, for example, flight state change start point information of the main aircraft and the collision aircraft, a predicted point time, a main aircraft call sign, a collision aircraft call sign, a time when a collision occurs, a position of a collision point, the number of collision aircraft, a collision type, an interval state of the collision point, and the like.
The control instruction presumption module 106 may acquire conflict detection result information detect_in from the conflict detection module 105, extract or determine respective flight state change end point information of the main aircraft and the conflict aircraft from the historical trajectory data based on the respective flight state change start point information of the main aircraft and the conflict aircraft, and calculate flight state changes of the main aircraft and the conflict aircraft based on the respective flight state change start point information and the flight state change end point information of the main aircraft and the conflict aircraft, thereby presuming control instructions for conflict resolution of the main aircraft and the conflict aircraft.
The control instructions may include, for example, main aircraft control instructions for a main aircraft regarding altitude, speed, and heading, conflicting aircraft control instructions for a conflicting aircraft regarding altitude, speed, and heading, and the like.
As an example, the regulatory instruction speculation module 106 may acquire the historical trajectory data of the main aircraft and the historical trajectory data of the conflicting aircraft from the data acquisition module 101 according to, for example, the call sign of the main aircraft and the call sign of the conflicting aircraft, and extract or determine the respective flight state change end point information of the main aircraft and the conflicting aircraft from the historical trajectory data according to the respective flight state change start point information of the main aircraft and the conflicting aircraft, as shown in fig. 10.
Alternatively, the data acquisition module 101 may receive the collision detection result information detect_in from the collision detection module 105 to extract or acquire the flight state change end point information of the collision aircraft from the historical trajectory number using the flight state change start point information of the collision aircraft and extract or acquire the flight state change end point information of the main aircraft from the historical trajectory number using the flight state change start point information of the main aircraft, and then supply the acquired flight state change end point information of the main aircraft and the collision aircraft to the regulatory instruction estimation module 106.
In addition, the control instruction estimation module 106 may compare the flight state of the main aircraft using the flight state change start point information and the flight state change end point information of the main aircraft, calculate the flight state change of the start point and the end point, estimate the instruction of the main aircraft based on the altitude, the speed, and the heading, and compare the flight state of the main aircraft using the flight state change start point information and the flight state change end point information of the conflicting aircraft, calculate the flight state change of the start point and the end point, and estimate the instruction of the conflicting aircraft based on the altitude, the speed, and the heading.
The collation output module 107 may receive the conflict detection result information detect_in from the conflict detection module 105 and the control instruction from the control instruction presumption module 106, and analyze and process the conflict detection result information and the control instruction to delete the repeated conflict detection result information when the paired main aircraft and the conflict aircraft are identical and the conflict occurrence time difference is smaller than the first predetermined time interval; and when the conflict detection result information with the same conflict main aircraft number and the predicted point time difference smaller than the second preset time interval exists in the at least two conflict detection result information, merging the at least two conflicts into a multi-aircraft conflict, deleting repeated information, and outputting a final conflict detection and control instruction estimation result.
Specifically, the sorting output module 107 may sort the conflict detection result information and the control instruction, and generate calculation result data, where the result data may include: the method comprises the steps of predicting point time, main aircraft call sign, conflict occurrence time, conflict point position, conflict aircraft number, conflict type, conflict point interval state, main aircraft control instruction and conflict aircraft control instruction.
In addition, the sorting output module 107 performs analysis and comparison on the result data according to the paired conflicting aircraft and the main aircraft, and when the two conflicting aircraft pairs (the main aircraft and the conflicting aircraft) are identical and the conflict occurrence time difference is less than 5min, one conflict result is deleted, and the repeated calculation data caused by the traversal calculation is deleted. And traversing the deleted result data according to the call signs and the predicted point time of the conflict aircraft pairs, and when one conflict aircraft call sign is the same as the conflict aircraft call signs in other conflicts and the predicted point time difference is less than 5min, considering that the two conflicts belong to the conflicts occurring at the same time, merging the conflicts into a multi-aircraft conflict, deleting repeated information, and then sorting and outputting final calculation result data.
Note that the detection and speculation apparatus 100 of the present disclosure may be implemented by hardware, software, and a combination of hardware and software, for example, the detection and speculation apparatus 100 may be implemented by a memory for storing a program for executing a corresponding process and data required for executing the process (e.g., history trace data, intermediate result data, and final result data), and a processor for executing the corresponding process based on the program of the corresponding process and the required data.
The various modules and data transfers and supplies between modules included in the detection and speculation apparatus 100 described above are merely exemplary, and the detection and speculation apparatus 100 may include more or fewer modules, as may be determined based on actual use and implementation.
The apparatus for detecting potential flight conflict of an aircraft based on real trajectory data and predicting a release instruction according to an embodiment of the present disclosure is described above, and a method implemented using the apparatus is described below, as shown in fig. 2, which is a flowchart illustrating a method for detecting potential flight conflict of an aircraft based on real trajectory data and predicting a release instruction according to an embodiment of the present disclosure.
The method starts in step S200, in which historical trajectory data of a main aircraft, which is an aircraft whose flight state has changed, is acquired. The acquisition of the historical trajectory data of the main aircraft in this step may be performed by the data acquisition module 101 as described above, and the specific procedure of acquisition may be the same as described above with respect to the data acquisition module 101.
Then, the method proceeds to step S201, in which a flight state change start point of the main aircraft is determined from the historical trajectory data of the main aircraft; and acquires flight state change start point information indicating a flight state change start point of the main aircraft. This step may be performed by the flight state change determination module 102 as described above, and the detailed process of this step may be the same as that described above with respect to the flight state change determination module 102.
Next, the method proceeds to step S202, in which a plurality of potentially conflicting aircraft within a predetermined conflict range of the flight state change start point of the main aircraft is determined based on the flight state change start point information of the main aircraft. This step may be performed by the potentially conflicting aircraft determination module 103 as described above, and the detailed process of this step may be the same as described above with respect to the potentially conflicting aircraft determination module 103.
Next, the method proceeds to step S203, in which the original flight intent trajectories of the main aircraft and the flight intent trajectories of the plurality of potentially conflicting aircraft are predicted. This step may be performed by the trajectory prediction module 104 as described above, and the specific details of this step may be the same as described above with respect to the trajectory prediction module 104.
Thereafter, the method proceeds to step S204, in which it is detected whether there is a flight conflict between the main aircraft and the plurality of potentially conflicting aircraft based on the original flight intent trajectory of the main aircraft and the flight intent trajectories of the plurality of potentially conflicting aircraft. This step may be performed by the conflict detection module 105 as described above, and the detailed process of this step may be the same as described above with respect to the conflict detection module 105.
When the detection result in step S204 is that there is no conflicting aircraft that conflicts with the main aircraft (i.e., no in step S204), then the method returns to step S200 to continue to acquire the historical track data of the main aircraft, for example, to continue traversing the time series of the historical track data track_d of the plurality of aircraft to acquire the flight state variation amounts of the plurality of aircraft, and to determine an aircraft whose flight state variation amount is equal to or greater than the predetermined threshold value as the main aircraft and thereby acquire the historical track data track_d of the main aircraft.
On the other hand, when the detection result in step S204 is that there is a conflicting aircraft that conflicts with the main aircraft (i.e., yes in step S204), conflict detection result information between the main aircraft and the conflicting aircraft is acquired.
As described above, the collision detection result information may include: the flight state change starting point information of the main aircraft and the conflict aircraft, the time of the predicted point, the call sign of the main aircraft, the call sign of the conflict aircraft, the time when the conflict occurs, the position of the conflict point, the number of the conflict aircraft, the conflict type and the interval state of the conflict point.
Then, the method proceeds to step S206, in which the respective flight state change end point information of the main aircraft and the conflict aircraft is extracted or determined from the historical trajectory data based on the respective flight state change start point information of the main aircraft and the conflict aircraft, and the flight state changes of the main aircraft and the conflict aircraft are calculated based on the respective flight state change start point information and the flight state change end point information of the main aircraft and the conflict aircraft, thereby presuming the control instruction for conflict resolution of the main aircraft and the conflict aircraft. This step may be performed by the policing instruction speculation module 106 as described above, and the specific details of this step may be the same as described above with respect to the policing instruction speculation module 106.
Thereafter, the method proceeds to step S207, where the conflict detection result information and the control instruction are analyzed to delete the duplicate information, and the final conflict detection and control instruction presumption result is output. This step may be performed by the sort output module 107 as described above, and the specific details of this step may be the same as described above with respect to the sort output module 107. The method then ends.
The invention adopts the technical scheme and has the following beneficial effects:
(1) By analyzing historical track data of the aircraft, possible flight conflicts in the running track are found out, corresponding conflict scenes are established, and a data basis can be provided for deep research of flight conflict problems;
(2) The flight conflict detection and release are the most important decision support tools in the auxiliary decision making system of the controller, and based on potential conflict detection and control instruction speculation of real historical track data, the behavior of the controller in control command can be analyzed, and the decision support more beneficial to the controller can be provided.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.

Claims (20)

1. A method of detecting a flight conflict of an aircraft, comprising the steps of:
acquiring historical track data of a main aircraft, wherein the main aircraft refers to an aircraft with a changed flight state;
determining a flight state change starting point of the main aircraft according to the historical track data of the main aircraft, and acquiring flight state change starting point information representing the flight state change starting point of the main aircraft;
determining a plurality of potentially conflicting aircraft within a predetermined conflict range of the flight state change starting point of the main aircraft based on the flight state change starting point information of the main aircraft;
predicting an original flight intent trajectory of the main aircraft and flight intent trajectories of the plurality of potentially conflicting aircraft; and
based on the primary flight intent trajectory of the primary aircraft and the flight intent trajectories of the plurality of potentially conflicting aircraft, detecting whether a flight conflict exists between the primary aircraft and the plurality of potentially conflicting aircraft.
2. The method of claim 1, wherein obtaining historical trajectory data for the main aircraft comprises:
Acquiring historical track data of a plurality of aircrafts;
establishing a time series of the historical trajectory data for the plurality of aircraft in a time sequence;
traversing the time series of the historical trajectory data of the plurality of aircraft according to a predetermined time interval to obtain a change in flight state of the plurality of aircraft; and
and determining the aircraft with the flight state variation value being greater than or equal to a preset threshold value as the main aircraft.
3. The method of claim 2, wherein the change in flight status includes at least a change in altitude, a change in speed, and a change in heading, and wherein an aircraft having at least one of the change in altitude, the change in speed, and the change in heading being greater than or equal to the respective predetermined threshold is determined to be the primary aircraft.
4. The method of claim 1, wherein predicting the primary intent-to-fly trajectory of the primary aircraft and the intent-to-fly trajectories of the plurality of potentially conflicting aircraft comprises:
acquiring flight state change information representing a change in the flight state of the main aircraft, the flight state change information including at least the flight state change start point of the main aircraft and a flight state change amount of the main aircraft;
Predicting an original flight intention track of the main aircraft according to the flight state change information of the main aircraft; and
flight information of the plurality of potentially conflicting aircraft is extracted from historical trajectory data of the plurality of potentially conflicting aircraft to predict flight intent trajectories of the plurality of potentially conflicting aircraft, the flight information of the plurality of potentially conflicting aircraft including at least a flight altitude, a flight speed, and a flight heading of the plurality of potentially conflicting aircraft.
5. The method of claim 4, wherein predicting an original intent-to-fly trajectory of the main aircraft comprises:
establishing a flight state change scene of the main aircraft according to the flight state change information of the main aircraft;
setting a predicted time step;
establishing a kinematic and mechanical particle prediction model based on the flight state change scene of the main aircraft and the prediction time step; and
and predicting the original flight intention track of the main aircraft by utilizing the kinematic and mechanical particle prediction model according to the flight state change starting point information of the main aircraft and the flight state change scene of the main aircraft.
6. The method according to claim 5, wherein:
when the flight state change scene is a climbing leveling flight scene, carrying out continuous climbing prediction based on the flight state change starting point information of the main aircraft, and predicting the original flight intention track of the main aircraft for keeping the original flight intention by taking the maximum cruising height of the main aircraft as a climbing upper limit;
when the flight state change scene is a descent and leveling flight scene, continuously descending prediction is performed based on the flight state change starting point information of the main aircraft, and the original flight intention track of the main aircraft is predicted based on the potential descending flight height of the main aircraft;
when the flight state change scene is a flat flight change climbing scene and a flat flight change descending scene, carrying out continuous flat flight prediction based on the flight state change starting point information of the main aircraft so as to predict the original flight intention track of the main aircraft;
when the flight state change scene is a turning scene, performing continuous direct flight prediction based on the flight state change start point information of the main aircraft to predict the original flight intention track of the main aircraft;
When the flight state change scene is an acceleration/deceleration scene, performing continuous uniform flight prediction based on the flight state change starting point information of the main aircraft to predict the original flight intention track of the main aircraft; or alternatively
And when the flight state change scene is an acceleration and deceleration change speed scene, continuously accelerating or decelerating flight prediction is performed based on the flight state change starting point information of the main aircraft so as to predict the original flight intention track of the main aircraft.
7. The method of claim 1, wherein detecting whether a flight conflict exists between the main aircraft and the plurality of potentially conflicting aircraft further comprises:
and when the detection result is affirmative, acquiring conflict detection result information between the main aircraft and a conflict aircraft which conflicts with the main aircraft, wherein the conflict detection result information at least comprises flight state change starting point information of the conflict aircraft.
8. The method of claim 1, wherein detecting whether a flight conflict exists between the primary aircraft and the plurality of potentially conflicting aircraft comprises:
Determining a conflict type of a potential conflict between the main aircraft and the plurality of potential conflict aircraft according to the original flight intention track of the main aircraft and the flight intention tracks of the plurality of potential conflict aircraft;
establishing a corresponding safety interval threshold according to the conflict type of the potential conflict;
determining a flight interval between the main aircraft and the plurality of potentially conflicting aircraft from an original flight intent trajectory of the main aircraft and flight intent trajectories of the plurality of potentially conflicting aircraft; and
when the flight interval is less than the corresponding safety interval threshold, determining that there is a conflicting aircraft of the plurality of potentially conflicting aircraft that is in flight conflict with the primary aircraft.
9. The method of claim 7, wherein the method further comprises:
extracting respective flight state change end point information of the main aircraft and the conflicting aircraft from the historical trajectory data according to the respective flight state change start point information of the main aircraft and the conflicting aircraft, and calculating flight state changes of the main aircraft and the conflicting aircraft according to the respective flight state change start point information and the flight state change end point information of the main aircraft and the conflicting aircraft, thereby presuming a control instruction for conflict resolution of the main aircraft and the conflicting aircraft.
10. The method of claim 9, wherein the step of determining the position of the substrate comprises,
the conflict detection result information further includes: prediction point time, main aircraft call sign, conflicting aircraft call sign, time of conflict occurrence, location of conflict point, number of conflicting aircraft, conflict type, interval status of conflict point, and
the control instructions include at least a primary aircraft control instruction for the primary aircraft regarding altitude, speed, and heading and a conflicting aircraft control instruction for the conflicting aircraft regarding altitude, speed, and heading.
11. The method according to claim 10, wherein the method further comprises:
analyzing the conflict detection result information and the control instruction to delete repeated information and output a final conflict detection and control instruction estimation result, wherein the analyzing the conflict detection result information and the control instruction comprises the following steps:
deleting the repeated conflict detection result information when the paired main aircraft and conflict aircraft are identical and the conflict occurrence time difference is smaller than a first predetermined time interval; and
And when the deleted conflict detection result information has conflict detection result information with the same number of the conflict main aircraft and a predicted point time difference smaller than a second preset time interval in at least two conflicts, merging the at least two conflicts into a multi-aircraft conflict.
12. An apparatus for detecting a flight conflict of an aircraft, the apparatus comprising:
the data acquisition module is configured to acquire historical track data of a main aircraft, wherein the main aircraft is an aircraft with a changed flight state;
a flight state change determination module configured to determine a flight state change start point of the main aircraft from the historical trajectory data of the main aircraft and obtain flight state change start point information representing the flight state change start point of the main aircraft;
a potentially conflicting aircraft determination module configured to determine a plurality of potentially conflicting aircraft within a predetermined conflict range of the flight state change starting point of the main aircraft based on the flight state change starting point information of the main aircraft;
a trajectory prediction module configured to predict an original flight intent trajectory of the main aircraft and flight intent trajectories of the plurality of potentially conflicting aircraft; and
A collision detection module configured to detect whether a flight collision exists between the main aircraft and the plurality of potentially conflicting aircraft based on an original flight intent trajectory of the main aircraft and flight intent trajectories of the plurality of potentially conflicting aircraft.
13. The apparatus of claim 12, wherein the data acquisition module is further configured to:
acquiring historical track data of a plurality of aircrafts;
establishing a time series of the historical trajectory data for the plurality of aircraft in a time sequence;
traversing the time series of the historical trajectory data of the plurality of aircraft according to a predetermined time interval to obtain a change in flight state of the plurality of aircraft; and
determining an aircraft for which the flight state variation amount is equal to or greater than a predetermined threshold value as the main aircraft,
wherein the flight state variation includes at least a flight altitude variation, a flight speed variation, and a flight heading variation, and an aircraft in which at least one of the flight altitude variation, the flight speed variation, and the flight heading variation is equal to or greater than the respective predetermined threshold value is determined as the main aircraft.
14. The apparatus of claim 12, wherein the trajectory prediction module is further configured to:
acquiring flight state change information representing a change in the flight state of the main aircraft, the flight state change information including at least the flight state change start point information representing the flight state change start point of the main aircraft and a flight state change amount of the main aircraft;
predicting an original flight intention track of the main aircraft according to the flight state change information of the main aircraft;
flight information of the plurality of potentially conflicting aircraft is extracted from historical trajectory data of the plurality of potentially conflicting aircraft to predict flight intent trajectories of the plurality of potentially conflicting aircraft, the flight information of the plurality of potentially conflicting aircraft including at least flight altitude, flight speed, and flight heading of the plurality of potentially conflicting aircraft.
15. The apparatus of claim 14, wherein the trajectory prediction module is further configured to:
establishing a flight state change scene of the main aircraft according to the flight state change information of the main aircraft;
setting a predicted time step;
Establishing a kinematic and mechanical particle prediction model based on the flight state change scene of the main aircraft and the prediction time step; and
and predicting the original flight intention track of the main aircraft by utilizing the kinematic and mechanical particle prediction model according to the flight state change starting point information of the main aircraft and the flight state change scene of the main aircraft.
16. The apparatus of claim 15, wherein the device comprises a plurality of sensors,
when the flight state change scene is a climbing and leveling flight scene, the track prediction module predicts continuous climbing based on the flight state change starting point information of the main aircraft, and predicts the original flight intention track of the main aircraft for keeping the original flight intention by taking the maximum cruising height of the main aircraft as the climbing upper limit;
when the flight state change scene is a descent and leveling flight scene, the track prediction module predicts a continuous descent based on the flight state change starting point information of the main aircraft and predicts the original flight intention track of the main aircraft based on a potential descent flight height of the main aircraft;
When the flight state change scene is a flat flight change climb and flat flight change descent scene, the track prediction module performs continuous flat flight prediction based on the flight state change starting point information of the main aircraft to predict the original flight intention track of the main aircraft;
when the flight state change scene is a turning scene, the trajectory prediction module performs continuous direct flight prediction based on the flight state change start point information of the main aircraft to predict the original flight intent trajectory of the main aircraft;
when the flight state change scene is an acceleration/deceleration scene, the track prediction module predicts the original flight intention track of the main aircraft by performing continuous uniform speed flight prediction based on the flight state change starting point information of the main aircraft; or alternatively
When the flight state change scene is an acceleration/deceleration change speed scene, the trajectory prediction module performs continuous acceleration or deceleration flight prediction based on the flight state change start point information of the main aircraft to predict the original flight intention trajectory of the main aircraft.
17. The apparatus of claim 12, wherein the collision detection module is further configured to:
and when the detection result is affirmative, acquiring conflict detection result information between the main aircraft and a conflict aircraft which conflicts with the main aircraft, wherein the conflict detection result information at least comprises flight state change starting point information of the conflict aircraft.
18. The apparatus of claim 12, wherein the collision detection module is further configured to:
determining a conflict type of a potential conflict between the main aircraft and the plurality of potential conflict aircraft according to the original flight intention track of the main aircraft and the flight intention tracks of the plurality of potential conflict aircraft;
establishing a corresponding safety interval threshold according to the conflict type of the potential conflict;
determining a flight interval between the main aircraft and the plurality of potentially conflicting aircraft from an original flight intent trajectory of the main aircraft and flight intent trajectories of the plurality of potentially conflicting aircraft; and
when the flight interval is less than the corresponding safety interval threshold, determining that the plurality of potentially conflicting aircraft are conflicting aircraft that are in flight conflict with the primary aircraft.
19. The apparatus of claim 16, wherein the collision detection result information further comprises: the device comprises a prediction point time, a main aircraft call sign, a conflict aircraft call sign, a time when a conflict occurs, a position of a conflict point, the number of conflict aircraft, a conflict type and an interval state of the conflict point, and further comprises:
a policing instruction prediction module configured to: extracting respective flight state change end point information of the main aircraft and the conflicting aircraft from the historical trajectory data according to respective flight state change start point information of the main aircraft and the conflicting aircraft, and calculating flight state changes of the main aircraft and the conflicting aircraft according to respective flight state change start point information and flight state change end point information of the main aircraft and the conflicting aircraft, thereby presuming control instructions for conflict resolution of the main aircraft and the conflicting aircraft, the control instructions including at least main aircraft control instructions for the main aircraft regarding flight altitude, flight speed, and flight heading and conflicting aircraft control instructions for the conflicting aircraft regarding flight altitude, flight speed, and flight heading; and
A collation output module that receives the conflict detection result information from the conflict detection module and the control instruction from the control instruction presumption module, and analyzes and processes the conflict detection result information and the control instruction to delete the repeated conflict detection result information when the paired main aircraft and the conflict aircraft are identical and a conflict occurrence time difference is smaller than a first predetermined time interval; and when the conflict detection result information with the same conflict main aircraft number and the predicted point time difference smaller than the second preset time interval exists in the at least two conflicts in the deleted conflict detection result information, merging the at least two conflicts into a multi-aircraft conflict, deleting repeated information, and outputting a final conflict detection and control instruction estimation result.
20. A computer readable storage medium storing a program which, when executed by a processor, is adapted to carry out a method of detecting a flight conflict of an aircraft, the method comprising the steps of:
acquiring historical track data of a main aircraft, wherein the main aircraft refers to an aircraft with a changed flight state;
Determining a flight state change starting point of the main aircraft according to the historical track data of the main aircraft;
acquiring flight state change start point information indicating the flight state change start point of the main aircraft,
determining a plurality of potentially conflicting aircraft within a predetermined conflict range of the flight state change starting point of the main aircraft based on the flight state change starting point information of the main aircraft;
predicting an original flight intent trajectory of the main aircraft and flight intent trajectories of the plurality of potentially conflicting aircraft;
based on an original flight intent trajectory of the main aircraft and the flight intent trajectories of the plurality of potentially conflicting aircraft, detecting whether a flight conflict exists between the main aircraft and the plurality of potentially conflicting aircraft.
CN202210698958.7A 2022-06-20 2022-06-20 Method and device for detecting flight collision of aircraft Pending CN117315998A (en)

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CN117746693A (en) * 2024-02-20 2024-03-22 中国民用航空飞行学院 Method for discriminating air risk of specific unmanned aerial vehicle in airport terminal area

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117746693A (en) * 2024-02-20 2024-03-22 中国民用航空飞行学院 Method for discriminating air risk of specific unmanned aerial vehicle in airport terminal area
CN117746693B (en) * 2024-02-20 2024-05-14 中国民用航空飞行学院 Method for discriminating air risk of specific unmanned aerial vehicle in airport terminal area

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