CN111739347B - Autonomous flight path planning and conflict resolution method and device applied to free route airspace - Google Patents
Autonomous flight path planning and conflict resolution method and device applied to free route airspace Download PDFInfo
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Abstract
The embodiment of the invention discloses an autonomous flight path planning and conflict resolution method and device applied to a free route airspace, relates to the technical field of air traffic management and planning, and provides reasonable auxiliary measures for air traffic management personnel. The invention comprises the following steps: acquiring airspace state data and aircraft operation data; carrying out discretization processing on the airspace based on cells by utilizing the airspace state data; obtaining a pre-planning result by utilizing a space domain discrete state based on a cell, wherein the pre-planning result comprises the following steps: paths that satisfy the constraint of the bounding region; and acquiring potential conflict data by using the preplanning result and the aircraft operation data, and acquiring a track conflict resolution scheme according to the potential conflict data. The invention is suitable for air traffic management and planning.
Description
Technical Field
The invention relates to the technical field of air traffic management and planning, in particular to an autonomous flight path planning and conflict resolution method and device applied to a free route airspace.
Background
At present, air traffic systems worldwide are in a full transformation and upgrading stage to meet the increasing flight demands, complex and huge architectures and diversified operating environments. In order to alleviate the contradiction between the increasing transportation total amount and the increasingly saturated airspace capacity, the method is developed based on track operation and free route airspace concepts. China also released a track-based operation concept based on the air condition of China in 2019.
Applications running on a track basis benefit from the development of satellite-based navigation and monitoring technologies and the perfection of four-dimensional flight management systems, which simultaneously facilitate the sharing of situational awareness between controllers and pilots. However, in flight-path-based free-route operation under high-density conditions, the controller workload becomes a key factor that restricts further increases in airspace capacity. Particularly, under the condition that a part of airspace is limited, uncertainty of aircraft conflict often causes chain reaction, so that the workload of a controller is increased explosively, and the operation risk is increased greatly.
Therefore, how to reasonably improve the automation degree of the controller in the work and provide reasonable auxiliary measures becomes a main research direction in the industry at present.
Disclosure of Invention
The embodiment of the invention provides an autonomous flight path planning and conflict resolution method and device applied to a free route airspace, which provide reasonable auxiliary measures for air traffic control personnel and alleviate the problem of man-machine cognitive synchronization under autonomous flight path operation.
In order to achieve the above purpose, the embodiment of the invention adopts the following technical scheme:
in a first aspect, an embodiment of the present invention provides a method, including:
acquiring airspace state data and aircraft operation data; carrying out discretization processing on the airspace based on cells by utilizing the airspace state data; obtaining a pre-planning result by utilizing a space domain discrete state based on a cell, wherein the pre-planning result comprises the following steps: paths that satisfy the constraint of the bounding region; and acquiring potential conflict data by using the preplanning result and the aircraft operation data, and acquiring a track conflict resolution scheme according to the potential conflict data.
In a second aspect, an embodiment of the present invention provides an apparatus, including:
the flight path pre-planning module is used for carrying out discretization processing on the airspace based on cells by utilizing the airspace state data; and obtaining a pre-planning result by utilizing a space domain discrete state based on the cells, wherein the pre-planning result comprises the following steps: paths that satisfy the constraint of the bounding region;
and the track conflict processing module is used for acquiring potential conflict data by utilizing the preplanning result and the aircraft operation data and acquiring a track conflict resolution scheme according to the potential conflict data.
In the embodiment, by collecting airspace real-time state information containing restricted area information, discretizing the airspace based on cells, classifying the states of the cells in the airspace, constructing a preliminary track feasible network diagram based on a visual map according to the discretized airspace state, acquiring an optimal path meeting the restricted area constraint through a path search algorithm, and realizing rapid preliminary planning of the track; the method comprises the steps of collecting real-time operation parameters of the aircraft, predicting future tracks of the aircraft according to continuous flight dynamics and track plans, classifying relative positions of the aircraft, detecting local conflicts on the basis, searching for a re-voyage track meeting constraints for detected potential conflicts, delaying the controlled arrival time of a subsequent track point of the aircraft without feasible solution under current constraints, and finally realizing real-time autonomous track conflict detection and resolution. The method is suitable for air traffic management, provides reasonable auxiliary measures for air traffic management personnel, and alleviates the problem of human-computer cognitive synchronization under autonomous track operation.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a diagram of a spatial domain discretization model based on cell according to an embodiment of the present invention;
FIG. 2 is a diagram of a primary location point model of a cell according to an embodiment of the present invention;
FIG. 3 is a diagram of a pre-track feasible network model based on a visual representation according to an embodiment of the present invention;
FIG. 4 is a diagram of a real-time aircraft position update model according to an embodiment of the present invention;
FIG. 5 is a diagram of a local collision detection model according to an embodiment of the present invention;
FIG. 6 is a model diagram of a relative position relationship between two aircraft according to an embodiment of the present invention;
FIG. 7 is a diagram of a model for optimizing a re-voyage based on reachable time-space domain according to an embodiment of the present invention;
FIG. 8 is a diagram of a model of a potential range extension of a diversion area according to an embodiment of the present invention;
FIG. 9 is a flowchart of a re-voyage optimization model algorithm provided by an embodiment of the present invention;
FIG. 10 is a schematic topology diagram of the solution logic provided by an embodiment of the present invention;
fig. 11 is a schematic diagram of a system architecture according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention. As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or coupled. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items. It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The main design idea of this embodiment lies in: the method comprises the steps of collecting airspace real-time state information containing limited area information, carrying out cellular-based discretization processing on the airspace, and carrying out state classification on the airspace cellular. The method comprises the steps of collecting real-time operation parameters of the aircraft, predicting future tracks of the aircraft according to continuous flight dynamics and track plans, classifying relative positions of the aircraft, detecting local conflicts on the basis, searching for a re-voyage track meeting constraints for detected potential conflicts, delaying the controlled arrival time of a subsequent track point of the aircraft without feasible solution under current constraints, and finally realizing real-time autonomous track conflict detection and resolution. The general logic design of the scheme of the embodiment is shown in fig. 10, and the flight path planning method based on the reachable time-space domain is mainly divided into two parts:
firstly, the method comprises the following steps: the autonomous track rapid preplanning part is implemented before the aircraft enters the airspace (namely, when the aircraft enters the airspace), wherein the model comprises a cell-based airspace discretization model, a cell main position point model and a visual-based advanced track feasible network model; II, secondly: and the real-time autonomous flight path conflict detection disengagement part is implemented in a real-time operation stage of the aircraft in the airspace, wherein the model comprises an aircraft real-time position updating model, a local conflict detection model, a relative position relation model of the two aircraft, a navigation optimization model based on reachable time-space domain and a potential navigation area range expansion model.
To facilitate understanding, the logic flow may be divided into links S1-S5:
s1, collecting airspace real-time state information containing restricted area information, carrying out cellular-based discretization processing on the airspace, and carrying out state classification on the airspace cells.
The method comprises the steps of classifying cells in an airspace area according to whether the airspace is limited (cannot fly due to the influence of severe weather, military activities and the like) by relying on airspace data shared by 'air-ground' through an air traffic control communication, navigation and monitoring system, particularly the position and geometric model of a limited area, constructing an airspace discretization model, and deducing a main position point model of the cells.
S2, constructing a pre-track feasible network graph based on a visual map, and obtaining an optimal path meeting the constraint of a restricted area through a path search algorithm to finish rapid pre-planning of the track.
The method comprises the steps of constructing a preliminary track feasible network model based on a visual view by taking an entry point, an exit point and a limited area outer boundary point of an aircraft in an airspace as alternative route points based on a cell main position point model, and obtaining an optimal re-navigation track by taking a shortest path as an optimization target through a Dijkstra path search algorithm on the basis.
And S3, acquiring the operation parameters of the aircraft at fixed time sampling intervals, including position coordinates, course, speed and the like, combining with a pre-planned flight path based on continuous flight dynamics, and constructing 2 types of aircraft real-time position updating models according to whether the aircraft is still in the current flight section after the position of the aircraft is updated.
And S4, constructing 4 relative position relation models of the two aircrafts according to different real-time position updating models of the aircrafts, and further solving the minimum distance between the two aircrafts in the current flight segment.
S5, controlled arrival time constraint, turning angle constraint, limit area constraint and potential conflict constraint are considered, a re-voyage optimization model based on a reachable time-space domain is constructed, a potential re-voyage path of the aircraft exists in an elliptical range formed by projection of a specific pyramid, and under the condition that no solution exists under the current controlled arrival time constraint, the controlled arrival time of a subsequent waypoint is delayed based on a potential re-voyage area range expansion model, and re-voyage optimization model solving is carried out.
Specifically, the autonomous flight path planning and conflict resolution method applied to the free route airspace provided by the embodiment of the present invention includes:
acquiring airspace state data and aircraft operation data, wherein the airspace state data comprises: boundary coordinates, occupancy altitude, occupancy time, etc. of a restricted area (such as military aviation activities, dangerous weather, etc.) within the airspace, the aircraft operation data including at least: position coordinates, heading, and speed of the aircraft. And carrying out discretization processing based on cells on the airspace by using the airspace state data. Obtaining a pre-planning result by utilizing a space domain discrete state based on a cell, wherein the pre-planning result comprises the following steps: paths that satisfy the constraints of the restricted area. And acquiring potential conflict data by using the preplanning result and the aircraft operation data, and acquiring a track conflict resolution scheme according to the potential conflict data.
In this embodiment, the performing a discretization process based on cells on a space domain by using the space domain state data includes: and classifying the space domain cells according to the limited condition of the space domain. And according to the classification result, constructing a space domain discretization model and acquiring a cell position point model. Wherein, the rapid pre-planning of the flight path relies on the airspace data shared by the 'air-ground', such as: by means of an air traffic control communication, navigation and monitoring system, air-ground shared airspace data, particularly the position and geometric model of a restricted area, and according to whether the airspace is restricted (the airspace is not flyable due to the influence of severe weather, military activities and the like), the airspace cells are classified, an airspace discretization model is built, and a cell main position point model is deduced. And constructing a previous track feasible network model based on a visual map, and acquiring the optimal re-navigation track through a Dijkstra path search algorithm on the basis.
The method for acquiring the pre-planning result by utilizing the airspace discrete state based on the cells comprises the following steps: and constructing a view-based advanced track feasible network diagram. And extracting the optimal path meeting the constraint of the restricted area from the pre-track feasible network graph through a path search algorithm, and taking the optimal path as the pre-planning result.
Wherein the constructing of the preliminary track feasible network map based on the view comprises the following steps: and constructing a preliminary track feasible network diagram based on a visual map by taking the entry point, the exit point and the outer boundary point of the restricted area of the aircraft in the airspace as alternative route points through the acquired cell position point model. Specifically, based on a cell main position point model, an entry point, an exit point and a limited area outer boundary point of an aircraft in an airspace are used as alternative route points, a previous flight path feasible network model based on a visual view is constructed, and on the basis, the shortest path is used as an optimization target, and the optimal re-navigation flight path is obtained through a Dijkstra path search algorithm.
Further, the extracting the optimal path satisfying the constraint of the restricted area includes: and weighting corresponding edges in the map according to the actual distance between each point in the map by using the pre-track feasible network map to generate a undirected weighted map, and searching the undirected weighted map by using a Dijkstra algorithm to obtain the shortest path.
In this embodiment, the obtaining potential conflict data by using the preplanning result and the aircraft operation data includes: and constructing an aircraft real-time position updating model according to the pre-planning result and the aircraft operation data. And constructing an aircraft relative position relation model by utilizing the aircraft real-time position updating model. And acquiring the minimum distance of the two aircrafts in the current flight section through the aircraft relative position relation model, comparing the minimum safety interval, acquiring the conflict relation of the two aircrafts, and communicating the detection aircraft number, the detected aircraft number, the detection time and the detection position to jointly form the potential conflict data.
The acquiring of the flight path conflict resolution scheme according to the potential conflict data comprises: and establishing a diversion optimization model according to the reachable time-space domain. Traversing all potential navigation change cells by using the conflict data and the navigation change optimization model, and extracting an optimal navigation change cell, wherein the optimal navigation change cell represents: the length of the re-navigation route formed by taking the central point of the cellular as the re-navigation route point is shortest.
The method comprises the steps of collecting real-time operation parameters of the aircraft, predicting future tracks of the aircraft according to continuous flight dynamics and a track plan, classifying relative positions of the aircraft, detecting local conflicts on the basis, searching a re-voyage track meeting constraints for detected potential conflicts, delaying controlled arrival time of a follow-up track point of the aircraft without feasible solution under current constraints, and finally realizing real-time autonomous track conflict detection and resolution. Specifically, the real-time autonomous flight path conflict detection is released, and the total number of the steps is 3, and the method comprises the following steps: the method comprises the steps of aircraft real-time track prediction based on continuous flight dynamics and advance tracks, local conflict detection based on the real-time track prediction, and real-time conflict resolution based on reachable time-space domains.
The real-time flight path prediction of the aircraft based on the continuous flight dynamics and the advance flight path can be understood as follows: in the real-time track prediction of the aircraft, the operation parameters of the aircraft, including position coordinates, course, speed and the like, are collected at fixed time sampling intervals, and based on continuous flight dynamics and combined with a pre-planned track, 2 types of aircraft real-time position updating models are constructed according to whether the aircraft is still in the current flight segment after the position updating.
Local conflict detection based on real-time track prediction can be understood as follows: in local conflict detection, 4 relative position relation models of the two aircrafts are constructed according to different real-time position updating models of the aircrafts, and then the minimum distance between the two aircrafts in the current flight segment is solved.
The real-time conflict resolution based on the reachable time-space domain can be understood as follows: in the real-time conflict resolution, controlled arrival time constraint, turning angle constraint, restricted area constraint and potential conflict constraint are considered, a re-navigation optimization model based on a reachable time-space domain is constructed, a potential re-navigation path of the aircraft exists in an elliptical range formed by projection of a specific pyramid, and under the condition that no solution exists under the current controlled arrival time constraint, the controlled arrival time of a subsequent waypoint is delayed based on a potential re-navigation area range expansion model, and re-navigation optimization model solution is carried out.
In the current technical field, a novel autonomous flight path conflict detection and release technology is urgently needed to be established so as to realize autonomous operation of an aircraft based on flight paths. Although it provides a potential direction for the development of air traffic control automation, air traffic control systems, and in particular control activities, are still in a so-called "person-oriented" mode, i.e. people are placed at the core of the control system. Even in a low-density air space, autonomous flight cannot be truly achieved. The breakthrough is that the air traffic control automation equipment needs to realize human-machine consciousness synchronization so as to increase the decision transparency among controllers, pilots and an automation system.
In the embodiment, by collecting airspace real-time state information containing restricted area information, discretizing the airspace based on cells, classifying the states of the cells in the airspace, constructing a preliminary track feasible network diagram based on a visual map according to the discretized airspace state, acquiring an optimal path meeting the restricted area constraint through a path search algorithm, and realizing rapid preliminary planning of the track; the method comprises the steps of collecting real-time operation parameters of the aircraft, predicting future tracks of the aircraft according to continuous flight dynamics and track plans, classifying relative positions of the aircraft, detecting local conflicts on the basis, searching for a re-voyage track meeting constraints for detected potential conflicts, delaying the controlled arrival time of a subsequent track point of the aircraft without feasible solution under current constraints, and finally realizing real-time autonomous track conflict detection and resolution. The invention is suitable for air traffic management.
The operation principle and mechanism of the present embodiment in practical application are described below by specific examples.
Firstly, the autonomous track rapid preplanning comprises:
1.1, establishing a spatial domain discretization model based on cells: based on the warp (X-axis) and weft (Y-axis) degrees, the airspace is divided into a number of cells, and C (X, Y) represents a cell whose cell coordinate is (X, Y). Each cell has its corresponding cell coordinate, and two basic types of cells, namely, usable cells and unusable cells, are defined according to whether the airspace is limited (the airspace is not flyable due to the influence of severe weather, military activities and the like). Based on safety considerations, a cell is defined as an available cell if and only if all of the available airspaces are available in the cell, and otherwise is defined as a restricted cell.
1.2, establishing a cell main position point model: for any cell, there are 5 main location points, namely, a center point, an upper left point, an upper right point, a lower left point, and a lower right point. Assuming that the cell side length is S, the actual coordinate of the origin of the coordinate system is (x)0,y0) Then the actual coordinates of the 5 main location points of the cell can be expressed as:
wherein, PC，PTL，PTR，PBLAnd PBRRespectively representing the actual coordinates of the center point, the upper left point, the upper right point, the lower left point and the lower right point.
1.3, establishing a visual-based advanced track feasible network model:
a visual diagram structure based on a restricted area is shown, wherein V represents a set of all points in the diagram, E represents a set of all edges in the diagram,
is the corresponding rule for points and edges. Based on the characteristics of visual diagram theory and spatial domain discretization, the order is as follows:
V2＝{v|Pv＝PI or PO}
V＝V1 UV2
C(X,Y)∈CR,i,i∈I
wherein V denotes a point in the diagram, V1Representing a set of outer boundary points of the restricted area, V2Representing the set of entry and exit points of the aircraft, V being V1And V2A union of (a), representing a set of all points of the visual map; x, Y, X ', Y', X ', Y', X ', Y' all indicate the horizontal and vertical coordinates of the cells, and the upper right-hand corner of the parameter symbols are distinguished from each other by the following conditions.
Meaning "presence",
meaning "unique to the presence", i.e. "there is and only one". PvRepresenting the actual coordinates of point v, CR,iDenotes the set of limiting cells in a limiting zone I, I being the set of all limiting zones, PIAnd POThe actual coordinates of the aircraft's entry and exit points in the airspace,erepresenting an edge, | v, in the diagramivj| represents a point viAnd point vjThe connecting line of (2). The edge of the visual image is a non-directional edge, and the weight value of the edge is the actual distance between two points connecting the edge. And searching out the shortest path in the generated undirected weighted graph based on the visual graph by using Dijkstra algorithm.
Specific examples are: as shown in fig. 1, the spatial domain discretization model based on the cells is a graph in which the spatial domain is divided into 10 × 10 cells based on the longitude (X axis) and latitude (Y axis) degrees. C (X, Y) represents a cell having cell coordinates (X, Y). Two basic types of cells, namely usable cells and unusable cells, are defined according to whether the airspace is limited (non-flyable due to the influence of severe weather, military activities and the like). A cell is defined as an available cell, such as C (1,4), if and only if all airspaces in the cell are available, and otherwise as a restricted cell, such as C (2,4) and C (3, 4).
As shown in fig. 2, a diagram of a primary position point model of a cell is shown, and assuming that the cell is C (3,4), the spatial origin coordinates are (0,0), and the cell size is 10, the 5 primary position point coordinates are respectively a center point (35,45), an upper left point (30,50), an upper right point (40,50), a lower left point (30,40), and a lower right point (40, 40).
FIG. 3 is a diagram of a pre-track feasible network model based on a visual map, where the limiting cells are C (2,3), C (3,2), C (3,3), C (5,7), C (6,6), C (6,7), C (7,6), and C (7,7), and the convex edge boundary points of the limiting cells are Pc(1,2)、Pc(1,4)、Pc(2,1)、Pc(4,1)、Pc(4,4)、Pc(4,6)、Pc(4,8)、Pc(5,5)、Pc(8,5)、Pc(8,8) aircraft entry point Pc(0,0) point of departure Pc(7,9). The entry point, the exit point and the convex boundary point of the limiting cell of the aircraft are connected in pairs, the lines which do not pass through the limiting cell are taken to form an undirected graph together, and the actual length of the edge is used for weighting the edge to form an undirected weighted graph. Solving the shortest path by Dijkstra algorithm, wherein the track points of the pre-track are P in sequencec(0,0)、Pc(1,4)、Pc(4,8)、Pc(7,9)。
Secondly, the real-time autonomous track conflict detection is released, including:
2.1, establishing an aircraft real-time position updating model: the aircraft flies along the expected track, and a certain continuous three way points of the way are respectively Wk、Wk+1、Wk+2The corresponding actual coordinates are (x)k,yk)、(xk+1,yk+1)、(xk+2,yk+2) Controlled arrival times are respectively Tk、Tk+1、Tk+2. FIG. Ai、Ai+1、Ai+2Respectively, the aircraft at ti、ti+1、ti+2The real-time location of the moment. Wherein, tiIndicating the moment at which the aircraft performs the ith collision detection. The time interval of each update is T, i.e. Ti+1＝ti+ T, where i and k are both positive integers, is a corner mark commonly used in mathematical formulas to represent different discrete values. Suppose the aircraft is at ti、ti+1、ti+2The actual coordinates of the positions at these three times are (x) respectivelyi,yi)、(xi+1,yi+1)、(xi+2,yi+2). And according to whether the aircraft is still in the current flight segment after the position of the aircraft is updated, two situations are total.
Case 1: suppose from tiConjecture to ti+1The aircraft is still in the current leg after the position update. At this time, the process of the present invention,
i.e. the actual coordinates of the aircraft can be expressed as:
in this case, assuming that the motion state of the aircraft is a uniform linear motion, the real-time position of the aircraft is represented as:
wherein x (t) and y (t) respectively represent the time t e [ t ]i,ti+1]The actual coordinates of the aircraft position.
Case 2: suppose from ti+1Conjecture to ti+2After the position update the aircraft is already in the next leg. At this time, the process of the present invention,
i.e. the actual coordinates of the aircraft can be expressed as:
similarly, in this case, assuming that the motion state of the aircraft is a uniform linear motion, the real-time position of the aircraft is calculated by the continuous flight dynamics model, and then:
2.2, establishing a local conflict detection model: firstly, defining: an aircraft that actively performs collision detection is referred to as a detection aircraft; an aircraft within the detection range is referred to as a detected aircraft; the outer aircraft is then referred to as the unexplored aircraft. Only potential conflicts between the detecting aircraft and the aircraft being detected are considered. Assume a minimum horizontal separation between aircraft of SS. If and only if the minimum horizontal separation between any two aircraft at a certain moment in flight is less than SSAnd then, the potential flight conflict between the aircrafts can be judged. If the minimum horizontal separation between the detecting aircraft and the aircraft to be detected is less than SSA collision is detected.
2.3, establishing a relative position relation model of the two aircrafts: as described above, there are 2 cases in each update of the aircraft position according to whether the updated position of the aircraft is still in the current leg, and there are 4 cases in the relative position expression of 2 aircraft after each position update. The model representation for the most complex case can cover the other 3 cases, i.e. both aircraft positions are in the next leg after updating. In this case, assume that
Is an aircraft m3 successive waypoints in the desired track, their actual coordinates being respectively
And the controlled arrival times are respectively
Suppose that
Is an aircraft n3 successive waypoints in the desired track, their actual coordinates being respectively
And the controlled arrival times are respectively
Aircraft m and n at tiAnd ti+1The actual coordinates of the position of the time of day are respectively
And
thus, the actual coordinates of the aircraft m and n may be expressed as:
wherein, Pm(t) and Pn(t) is the aircraft m and n respectively at t ∈ [ t ]i,ti+1]The actual position of the time.
The aircraft moves linearly at a constant speed in each flight segment, so that the position of the aircraft changes linearly with time. The square of the distance between the aircraft is a piecewise function with respect to t, each piecewise being a quadratic function.
The segment i piecewise function may be expressed as:
si 2(t)＝Ait2+Bit+Ci
wherein s (t) ═ Pm(t)Pn(t)|，Ai、Bi、CiAre all constant, and AiIs greater than 0. Since s (t) is not less than 0, si(t) and si 2(t) the minimum is taken at the same t, which represents time. Thus, siThe minimum value of (t) can be expressed as:
the minimum distance between two aircraft in the current flight segment is therefore:
mins(t)＝min{minsi(t)}
that is, if mins (t) < SSA collision is detected, otherwise no collision is detected.
2.4, establishing a model based on reachable time-space domain: suppose AiFor an aircraft at tiThe actual position of the time, is noted as (x)i,yi)；WkIs the next waypoint in the aircraft track, and the actual coordinates and the controlled arrival time are respectively marked as TkAnd (x)k,yk). At this time, let
Is a re-navigable point in C (X, Y) with actual coordinates (X, Y) as follows:
(x,y)＝PC(X,Y)
vmaxthe maximum speed of the aircraft. In view of the controlled arrival time constraint, the following constraints can be derived:
wherein the content of the first and second substances,
indicating a relocation point using C (X, Y) as a relocation unit cell, and
Δt＝Tk-ti
namely:
from the above formula, all feasible re-navigation route points (x, y) are within an ellipse, that is:
wherein the content of the first and second substances,
2.5, establishing a diversion optimization model and a solving algorithm thereof:
1) objective function
The flight path optimization takes the controlled arrival time into consideration, namely, when planning conflict and releasing the flight path, the control arrival time limit should be met through speed regulation as much as possible. Because the diversion points in the route reachable domain can meet the controlled arrival time requirement, the optimization goal in the text is that the diversion route is shortest and is recorded as:
minZ＝f(X,Y)
wherein f (X, Y) is when the aircraft is in PCAnd (X, Y) is the flight distance of the re-navigation section when the re-navigation waypoint is changed.
2) Constraint conditions
(1) The restricted area constrains. Based on the spatial domain discretization thought of the cells, whether the central point of the cell is in the ellipse or not is examined, if so, the cell is listed as a potential diversion cell, namely the diversion point is not in a limited area:
wherein, CR,jRepresenting the set of restricted cells in restricted area j, and I is the set of all restricted areas.
Meanwhile, the re-navigation track cannot pass through the restricted area, namely:
(2) the turning angle is restricted. Given aircraft performance limitations, potential re-voyage waypoints need to meet aircraft turn angle limitations. False maximum turning angle TAThen, there are:
αXY,βXY,γXY≤TA
wherein alpha isXY、βXY、γXYRespectively, the go-to-go angle, the return-to-go angle and the track recovery angle, as shown in fig. 8.
(3) A minimum safety interval constraint. Based on the collision detection method mentioned in the local collision detection, the re-navigation flight path should meet the minimum safety interval:
mins(X,Y)≥SS
wherein mins(X,Y)When the aircraft is at PCAnd (X, Y) is the shortest distance between the detected aircraft and the re-navigating route point.
In summary, the shortest conflict-free track planning model is:
minZ＝f(X,Y)
wherein I represents the set of all restricted zones, CR,j(R is subscript) denotes the limiting cell number j, where R is from restricted, CRIs a whole and j is a variable.
(R is superscript) indicating the relocation Point for a relocation cell with C (X, Y), R being from route, WRIs a whole, and XY is a variable.
3) Solving algorithm
And traversing all potential navigation change cells by adopting an enumeration method, screening feasible navigation change cells through the constraint conditions, and selecting the optimal navigation change cell from the feasible navigation change cells to obtain the optimal navigation change route point and the corresponding navigation change track.
Specific examples are:
FIG. 4 is a diagram of a real-time position update model of an aircraft with three consecutive track points W1、W2、W3Is divided into Pc(1,2)、Pc(2,6)、Pc(5,7) controlled arrival times of 100s, 280s, 420s, A, respectively1、A2、A 33 continuous position updating points of the aircraft, the aircraft speed is 826km/h, the sampling time is 100s (the actual sampling time is within 10s, the difference of position calculation under two position updating conditions is shown here), the cell size is 10km, the airspace origin coordinate is (0,0), and the 1 st position updating point A1The coordinates of (17.2,33.5) and the sampling time point was 140 s. The 2 nd position update point a2Is (21.5,51.0), the 3 rd position update point A2Has the coordinates of (37.9, 69.3).
FIG. 5 is a diagram of a local collision detection model for detecting an aircraft P1Has a detection range of 30 km. Aircraft P2、P3With aircraft P1Is less than 30km, the aircraft P2、P3Is a detected aircraft; aircraft P4、P5With aircraft P1Is greater than 30km, the aircraft P4、P5Are undetected aircraft.
Fig. 6 is a model diagram of the relative positional relationship between two aircraft, and 4 sub-diagrams in the diagram illustrate the relative positional relationship between 4 aircraft before and after updating. Sub-diagram 1 shows that the aircraft m and n are still in the current flight segment after being updated; FIG. 2 shows that the aircraft m is in the next flight segment after being updated, and the aircraft n is still in the current flight segment after being updated; FIG. 3 shows that the aircraft m is still in the current leg after being updated, and the aircraft n is in the next leg after being updated; and the sub-diagram 4 shows that the aircrafts m and n are in the next flight segment after being updated.
FIG. 7 is a diagram of a model for optimization of re-voyage based on reachable time-space domain, although the center point P of C (4,6) is in the potential re-voyage areac(4,6) is also within the potential re-voyage area, but since C (4,6) is a restricted area cell, it cannot be a potential re-voyage cell. Suppose in this example that the current aircraft position is (27.2,32.3), the next waypoint Pc(7,6), according to the constraint condition, the final feasible re-navigating unit cells are C (3,5), C (4,5) and C (5,6), the corresponding objective functions (shortest path lengths) are 65.2km, 60.5km and 63.0km respectively, and then the optimal re-navigating point is C (4, 5).
FIG. 8 is a diagram of a model for expanding the range of a potential diversion area, wherein if FIG. 7 shows that there are no feasible diversion cells according to the constraint conditions, the next waypoint P is postponedc(7,6) the CTA expands the potential re-navigation area by adding 14 new potential re-navigable cells in this example, and continuing to postpone the next waypoint P if there are still no feasible re-navigable cells in the current potential re-navigable cellscThe CTA of (7,6) expands the potential re-voyage area until there are viable re-voyage cells.
Specifically, a flowchart of a specific algorithm of the sailing optimization model is shown in fig. 9.
In this embodiment, an autonomous flight path planning and conflict resolution device applied to a free route airspace is further provided, including:
and the track pre-planning module is used for carrying out discretization processing on the airspace based on cells by utilizing the airspace state data. And obtaining a pre-planning result by utilizing a space domain discrete state based on the cells, wherein the pre-planning result comprises the following steps: paths that satisfy the constraints of the restricted area. The flight path rapid pre-planning module acquires airspace state information, carries out discretization processing on the airspace based on cells, solves the optimal path meeting the constraint of a restricted area and achieves rapid pre-planning of the flight path.
And the track conflict processing module is used for acquiring potential conflict data by utilizing the preplanning result and the aircraft operation data and acquiring a track conflict resolution scheme according to the potential conflict data. The real-time autonomous flight path conflict detection and disengagement module predicts flight paths in real time, performs local conflict detection, and obtains the re-navigation flight paths through the conflict disengagement model for the detected potential conflicts so as to realize real-time autonomous flight path conflict detection and disengagement.
Specifically, the track conflict processing module includes:
and the track real-time prediction submodule is used for constructing an aircraft real-time position updating model according to the pre-planning result and the aircraft operation data. And constructing an aircraft relative position relation model by utilizing the aircraft real-time position updating model. The flight path real-time prediction submodule acquires the operation parameters of the aircraft, including position coordinates, course, speed and the like, and the flight path real-time prediction is realized through the aircraft real-time position update model.
And the local conflict detection submodule is used for acquiring the minimum distance of the two aircrafts in the current flight segment through the aircraft relative position relation model, comparing the minimum safety interval to acquire the conflict relation of the two aircrafts, and communicating the detection aircraft number, the detected aircraft number, the detection time and the detection position to jointly form the potential conflict data. The local conflict detection submodule analyzes the relative position relation between the aircrafts, determines a relative distance calculation expression, solves the minimum distance and realizes local conflict detection.
And the real-time conflict resolution submodule is used for establishing a navigation change optimization model according to the reachable time-space domain. And traversing all potential navigation change cells by using the conflict data and the navigation change optimization model, and extracting the optimal navigation change cells. The real-time conflict resolution submodule resolves the re-navigation track optimization model, delays the controlled arrival time of the subsequent waypoint based on the potential re-navigation area range expansion model under the condition that the current controlled arrival time is not constrained, and then resolves the re-navigation optimization model.
In this embodiment, the system mainly includes an autonomous flight path pre-planning module and a flight path conflict processing module. The autonomous track preplanning module aims at acquiring airspace real-time state information containing restricted area information, discretizing the airspace based on cells, classifying the state of the airspace cells, constructing a visible advanced track feasible network diagram according to the discretized airspace state, and acquiring an optimal path meeting the restricted area constraint through a path search algorithm to realize rapid preplanning of the track; the flight path conflict processing module aims to collect real-time operation parameters of the aircraft, predict the future flight path of the aircraft according to continuous flight dynamics and a flight path plan, classify the relative positions of the aircraft, detect local conflict on the basis, search the detected potential conflict for a re-voyage path meeting the constraint, delay the controlled arrival time of a subsequent flight path point of the aircraft without feasible solution under the current constraint, and finally realize the real-time autonomous flight path conflict detection and resolution.
The apparatus described in this embodiment may be specifically implemented in the current air traffic control system, and implement corresponding functions through each subsystem, as shown in fig. 11, including:
and the air traffic control monitoring subsystem is used for monitoring and acquiring the airspace state data and the aircraft operation data in real time.
And the track rapid pre-planning subsystem is used for acquiring airspace state data from the air traffic control monitoring subsystem, carrying out discretization processing on the airspace based on cells, acquiring an airspace discrete state model based on the cells, constructing a pre-track feasible network diagram based on the model, acquiring an optimal path meeting the constraint of a restricted area, and realizing rapid pre-planning of the track.
A real-time autonomous track collision detection and disengagement subsystem for acquiring from the air traffic control monitoring subsystemAircraftPre-planning the flight path data, performing real-time flight path prediction and local conflict detection, acquiring the re-navigation flight path through a conflict resolution model for the detected potential conflict,and the real-time autonomous track conflict detection is released.
And the display subsystem is used for displaying the elliptical projection based on the reachable time-space domain in the two-dimensional plane in the processes of airspace state, pre-planned flight path, real-time operation flight path, diversion flight path and diversion solving.
This embodiment realizes 3 functions through the spatial domain discretization based on the cell: firstly, the aircraft can only fly in feasible cells through cell classification, so that the aircraft is ensured not to cause danger due to accidental intrusion into a restricted area; secondly, when the aircraft plans the expected track, the central point of the cellular of the boundary of the restricted area is used as an alternative route point of the diversion path; and thirdly, the flight change point of the aircraft for autonomous collision avoidance is also the center point of the cell. The aircraft realizes the rapid planning of the advance flight path under the limited information sharing support of the airspace, thereby being more concentrated on the conflict detection and the disengagement with other aircraft after entering the airspace, and further improving the real-time operation efficiency. The re-navigation optimization based on the reachable time-space domain not only can support the autonomous flight path operation in the free air route space, but also provides consistent situational awareness and a transparent and friendly man-machine interface, and particularly when special situations occur, a controller or a pilot can safely and seamlessly take over the operation of the space domain or the aircraft, so that the potential risk of autonomous operation is effectively reduced. In general, the method can support the autonomous flight path operation in a complex airspace high-density operation environment, and provides a new idea and a new method for promoting the development of an autonomous air traffic system.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus embodiment, since it is substantially similar to the method embodiment, it is relatively simple to describe, and reference may be made to some descriptions of the method embodiment for relevant points. The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. An autonomous flight path planning and conflict resolution method applied to a free-route airspace is characterized by comprising the following steps:
acquiring airspace state data and aircraft operation data, wherein the airspace state data comprises: boundary coordinates, an occupied height and an occupied time of a restricted area in the air, wherein the aircraft operation data at least comprises: position coordinates, heading and speed of the aircraft;
carrying out discretization processing on the airspace based on cells by utilizing the airspace state data;
obtaining a pre-planning result by utilizing a space domain discrete state based on a cell, wherein the pre-planning result comprises the following steps: paths that satisfy the constraint of the bounding region;
acquiring potential conflict data by using the preplanning result and the aircraft operation data, and acquiring a track conflict resolution scheme according to the potential conflict data;
the discretization processing based on the cells is carried out on the airspace by utilizing the airspace state data, and the discretization processing comprises the following steps:
classifying the space domain cells according to the limited condition of the space domain;
constructing a space domain discretization model according to the classification result, and acquiring a cell position point model;
the method for acquiring the pre-planning result by utilizing the airspace discrete state based on the cells comprises the following steps:
constructing a previous track feasible network diagram based on a visual map;
extracting an optimal path meeting the constraint of a restricted area from the pre-track feasible network graph through a path search algorithm, and taking the optimal path as a pre-planning result;
the constructing of the view-based advanced track feasible network graph comprises the following steps:
constructing a preliminary track feasible network diagram based on a visual map by taking an entry point, an exit point and a limited area outer boundary point of the aircraft in an airspace as alternative route points through the acquired cell position point model;
the extracting of the optimal path satisfying the constraint of the restricted area comprises the following steps:
and weighting corresponding edges in the map according to the actual distance between each point in the map by using the pre-track feasible network map to generate a undirected weighted map, and searching the undirected weighted map by using a Dijkstra algorithm to obtain the shortest path.
2. The method of claim 1, wherein the using the preplanning results and the aircraft operational data to obtain potentially conflicting data comprises:
constructing an aircraft real-time position updating model according to the pre-planning result and the aircraft operation data;
establishing an aircraft relative position relation model by utilizing the aircraft real-time position updating model;
and acquiring the minimum distance of the two aircrafts in the current flight section through the aircraft relative position relation model, comparing the minimum safety interval, acquiring the conflict relation of the two aircrafts, and communicating the detection aircraft number, the detected aircraft number, the detection time and the detection position to jointly form the potential conflict data.
3. The method of claim 2, wherein obtaining a trajectory conflict resolution scheme based on the potential conflict data comprises:
establishing a diversion optimization model according to the reachable time-space domain;
traversing all potential navigation change cells by using the conflict data and the navigation change optimization model, and extracting an optimal navigation change cell, wherein the optimal navigation change cell represents: the length of the re-navigation route formed by taking the central point of the cellular as the re-navigation route point is shortest.
4. An autonomous flight path planning and conflict resolution device applied to a free-route airspace, comprising:
the flight path pre-planning module is used for carrying out discretization processing on the airspace based on cells by utilizing the airspace state data; and obtaining a pre-planning result by utilizing a space domain discrete state based on the cells, wherein the pre-planning result comprises the following steps: paths that satisfy the constraint of the bounding region;
the flight path conflict processing module is used for acquiring potential conflict data by utilizing the preplanning result and the aircraft operation data and acquiring a flight path conflict resolution scheme according to the potential conflict data;
the method for carrying out discretization processing on the airspace based on the cells by utilizing the airspace state data comprises the following steps: classifying the space domain cells according to the limited condition of the space domain; constructing a space domain discretization model according to the classification result, and acquiring a cell position point model;
the method for acquiring the pre-planning result by utilizing the airspace discrete state based on the cells comprises the following steps: constructing a previous track feasible network diagram based on a visual map; extracting an optimal path meeting the constraint of a restricted area from the pre-track feasible network graph through a path search algorithm, and taking the optimal path as a pre-planning result;
the constructing of the view-based advanced track feasible network graph comprises the following steps: constructing a preliminary track feasible network diagram based on a visual map by taking an entry point, an exit point and a limited area outer boundary point of the aircraft in an airspace as alternative route points through the acquired cell position point model;
the extracting of the optimal path satisfying the constraint of the restricted area comprises the following steps: and weighting corresponding edges in the map according to the actual distance between each point in the map by using the pre-track feasible network map to generate a undirected weighted map, and searching the undirected weighted map by using a Dijkstra algorithm to obtain the shortest path.
5. The apparatus of claim 4, wherein the track collision processing module comprises:
the track real-time prediction submodule is used for constructing an aircraft real-time position updating model according to the pre-planning result and the aircraft operation data; establishing an aircraft relative position relation model by utilizing the aircraft real-time position updating model;
and the local conflict detection submodule is used for acquiring the minimum distance of the two aircrafts in the current flight segment through the aircraft relative position relation model, comparing the minimum safety interval to acquire the conflict relation of the two aircrafts, and communicating the detection aircraft number, the detected aircraft number, the detection time and the detection position to jointly form the potential conflict data.
6. The apparatus of claim 5, wherein the track collision processing module further comprises:
the real-time conflict resolution submodule is used for establishing a navigation improvement optimization model according to the reachable time-space domain; and traversing all potential navigation change cells by using the conflict data and the navigation change optimization model, and extracting the optimal navigation change cells.
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