CN106875755B - A kind of air traffic conflict management method and device based on complexity - Google Patents
A kind of air traffic conflict management method and device based on complexity Download PDFInfo
- Publication number
- CN106875755B CN106875755B CN201710113182.7A CN201710113182A CN106875755B CN 106875755 B CN106875755 B CN 106875755B CN 201710113182 A CN201710113182 A CN 201710113182A CN 106875755 B CN106875755 B CN 106875755B
- Authority
- CN
- China
- Prior art keywords
- aircraft
- complexity
- target sector
- airplane
- conflict
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000007726 management method Methods 0.000 title abstract description 29
- 230000000694 effects Effects 0.000 claims abstract description 36
- 238000004364 calculation method Methods 0.000 claims description 71
- 238000000034 method Methods 0.000 claims description 63
- 230000008859 change Effects 0.000 claims description 43
- 238000004422 calculation algorithm Methods 0.000 claims description 35
- 238000013459 approach Methods 0.000 claims description 19
- 230000001105 regulatory effect Effects 0.000 claims description 14
- 238000013507 mapping Methods 0.000 claims description 12
- 230000014509 gene expression Effects 0.000 claims description 5
- 239000004576 sand Substances 0.000 claims description 5
- 230000006870 function Effects 0.000 description 25
- 238000010586 diagram Methods 0.000 description 16
- 238000011160 research Methods 0.000 description 8
- 238000005457 optimization Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 6
- 238000004891 communication Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 238000009877 rendering Methods 0.000 description 3
- 230000005653 Brownian motion process Effects 0.000 description 2
- 238000000342 Monte Carlo simulation Methods 0.000 description 2
- 238000005537 brownian motion Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 238000000926 separation method Methods 0.000 description 2
- 240000006829 Ficus sundaica Species 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009194 climbing Effects 0.000 description 1
- 238000010225 co-occurrence analysis Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- 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
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/04—Anti-collision systems
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
Abstract
The present invention provides a kind of air traffic conflict management method and device based on complexity, including：When detecting that target sector has into aircraft, enter behind target sector the corresponding control activity of original aircraft in target sector according into aircraft, draw the calculating figure of the corresponding complexity in target sector；For the conflict area calculated in figure of complexity, the minimum optimal path of conflict is calculated；Select optimal inlet point of the corresponding inlet point of optimal path to enter target sector into aircraft；The present invention makes to enter target sector according to optimal inlet point into aircraft, and the optimal inlet point into aircraft is found according to complicated dynamic behaviour figure, how the air traffic provided with complexity is to entering the details in terms of aircraft is reacted, aircraft inlet point is with regard to that can be corrected, the conflict in sector can utmostly be reduced, to ensure to enter the personal distance between aircraft, while utmostly reduce the live load of sector controller.
Description
Technical Field
The invention relates to the technical field of air traffic, in particular to a complexity-based air traffic conflict management method and device.
Background
the collision detection means that collision tracks which violate minimum interval standards are predicted according to information such as position, altitude, speed, heading, flight mode and the like of the airplane provided by a monitoring system, wherein the standard distance of horizontal intervals in the airway space is usually 5 nautical miles, the vertical interval is 1000 feet, the collision resolution and the collision resolution track optimization are ideal flight tracks planned according to a general principle and a method.
Researchers in various countries around the world have done a great deal of research work on the detection and resolution of flight conflicts in free flight situations. The aircraft collision risk model of Reich is an early research effort in the field. In order to simplify mathematical calculation, each aircraft is assumed to be a cuboid with the same size, the average length, width and height of the aircraft are respectively represented by parameters, and the probability of collision between two aircrafts, namely the collision risk between two cuboids, is mathematically equivalent to the probability of collision risk between a certain mass point and the cuboid. Similar studies have been conducted by many scholars on the basis of the Reich model, which integrate various uncertainty factors affecting flight safety. Hu et al take the influence of uncertain factors such as wind on flight into a kinetic equation, and an airplane motion model is a determined trajectory equation plus a certain proportion of Brownian motion disturbance, and under the form, the probability of collision is changed into the probability of the Brownian motion escaping from a time-varying safe region, so that approximate expression applicable to a limited infinite range is obtained. Yang adopts a probability estimation method including airplane intention information in a trajectory model, mainly uses Monte Carlo simulation to estimate a future flight trajectory according to airplane flight intentions and various interferences, performs conflict detection and resolution, and focuses on the influence of intentions on the trajectory. The Mondoloni conflict resolution algorithm is also based on a genetic algorithm, can obtain a conflict-free flight scheme under the conditions of shortest time, minimum oil consumption or total cost, is applied to conflict prediction in the future 6-25 minutes of climbing, turning and descending stages of flight, can solve conflicts (such as fixed arrival time) containing certain flight planning constraints, and is proved by examples to enable a consumption function to reach the optimum, can be simply combined with a flight plan optimum function into a whole, but is complex in calculation, consumes more time and cannot predict conflicts in a short period (within 5 minutes). Alloot et al propose a priority-based optimization algorithm, give different priorities to each aircraft, and an aircraft with a high weight selects a route which is considered to be optimal by itself without considering an aircraft with a low weight, and so on, the basic method is to find the shortest path of a tree. Lucia Pallottino et al propose an algorithm for mixed integer programming, i.e. establish constraints for collision avoidance on a general geometric construction method and formulate them into linear constraints, and then solve them with an optimization tool CPLEX. Tomlin et al applied the non-cooperative game theory to derive the differential equations of the unsafe set boundaries described by the optimal control rules and results, and employed a pre-set conflict resolution strategy. Menon et al apply the optimal control theory to flight conflict resolution, using two different approaches. The first method uses a linear model of total flight time and fuel consumption as a consumption function, and uses a single-target SQP (Sequential orthogonal Programming) method and a multi-target obtaining method to solve the problem. The second method uses closed-loop navigation method, and takes route deviation as the optimal function to solve the multi-machine conflict.
However, most previous research articles focus on the aircraft spacing within a sector, and less emphasis is placed on the aircraft trajectory from the multi-sector perspective. Current conflict resolution methods focus on traffic in only one sector, which is likely to adversely affect flight safety and may also cause inefficiencies as the numerous aircraft participating in conflict resolution may need to re-plan their trajectories in subsequent sectors. Itan et al (Idan et al) states that reducing the number of re-planned trajectories reduces the computational effort and the workload on the pilot, and ultimately improves safety.
The inventor finds in research that the traffic conflict control method in the prior art is limited to one sector, and the air traffic cannot be controlled more accurately.
Disclosure of Invention
In view of the above, an object of the embodiments of the present invention is to provide a method and an apparatus for managing air traffic conflicts based on complexity, so as to ensure a safe interval between entering airplanes, and at the same time, to reduce the workload of sector controllers to the greatest extent.
In a first aspect, an embodiment of the present invention provides a complexity-based air traffic conflict management method, where the method includes:
when the target sector is detected to enter the airplane, drawing a calculation graph of the complexity corresponding to the target sector according to the control activity amount corresponding to the original airplane in the target sector after the entering airplane enters the target sector; wherein, the control activity amount refers to the total course angle change amount made by the original airplane in the target sector to release any conflict caused by entering the airplane; the complexity calculation graph refers to a distribution graph of the air traffic complexity formed by all the airplanes entering the airplane in the target sector;
for a conflict region in a computational graph of complexity, calculating an optimal path with minimum conflict in the conflict region;
and selecting the entry point corresponding to the optimal path as the optimal entry point for entering the target sector of the airplane so as to facilitate the entering of the airplane into the target sector according to the optimal entry point.
With reference to the first aspect, an embodiment of the present invention provides a first possible implementation manner of the first aspect, where drawing a calculation graph of complexity corresponding to a target sector according to a control activity amount corresponding to an original airplane in the target sector after an airplane enters the target sector includes:
the angle of approach E and the azimuth angle B into the aircraft are calculated according to the following formulas:wherein, the binary variable n1And n2Maintaining the entry point field into the aircraft at-pi ≦ B ≦ pi and 0 ≦ E<2 pi; e represents an entrance angle; b represents an azimuth; superscript E indicates entry into the aircraft;
calculating a flight path change curve of the incoming airplane according to the following formula:wherein,the abscissa representing the curve of the course of the flight trajectory,the ordinate represents the change curve of the sailing track; v represents the flying speed of the entering airplane, and the speed is a constant value; superscript I represents the incoming aircraft in the target sector; k represents any aircraft in the target sector; t represents an arbitrary time within the target sector;
calculating a drawing function phi according to an entering angle E and an azimuth angle B of an entering airplane and a sailing track change curve of the entering airplane:wherein Φ represents a drawing function;
and drawing a calculation chart of the complexity corresponding to the target sector according to the calculated drawing function.
With reference to the first possible implementation manner of the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where, for a collision region in a computation graph of complexity, computing an optimal path with a minimum collision in the collision region includes:
for a conflict area in a complexity calculation graph, calculating a course angle change quantity delta theta of an original airplane in a target sector according to a calculation formula corresponding to mixed integer linear programming:for k＝2,…N；
and calculating the optimal path with the minimum conflict in the conflict area according to the course angle change delta theta of the original airplane.
With reference to the second possible implementation manner of the first aspect, an embodiment of the present invention provides a third possible implementation manner of the first aspect, where drawing a computation graph of complexity corresponding to a target sector according to a computed mapping function includes:
and solving the drawing function by adopting a variance quadtree drawing algorithm so as to draw a calculation graph of the complexity corresponding to the target sector according to the solving result.
With reference to the third possible implementation manner of the first aspect, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where a variance quadtree mapping algorithm is used to solve the mapping function, so as to map a computation graph of complexity corresponding to a target sector according to a result of the solution, where the method includes:
step 1: converting an arc in the X-Y coordinate system representing an entry point into the aircraft into a square in the E-B coordinate system;
step 2: dividing a search space S according to the grid size delta of a square;
and 3, step 3: calculating a regulatory activity quantity C at each discrete point (E, B) and plotting a corresponding complexity;
and 4, step 4: converting the complexity into a binary lattice, wherein each point has two expressions: c ═ 0 or ≠ 0 (i.e., C ═ 1);
and 5, step 5: calculating a variance Q for each square in space S; the method for calculating the variance Q comprises the following steps:
and 6, step 6: repeating steps 3-5 until all Q's in the subdivision are zero, or until the grid size is reduced to a minimum grid size set to 1 degreeUntil the end;
and 6, the drawn complexity corresponding to the step 6 is a final calculation graph of the complexity corresponding to the target sector.
With reference to the third possible implementation manner or the fourth possible implementation manner of the first aspect, an embodiment of the present invention provides a fifth possible implementation manner of the first aspect, where the arc representing the entry point into the aircraft is obtained by:
obtaining an entry point P that can be reached by an incoming aircraft on the boundary of a target sector1And P2；
Determining an entry point P1And P2The corresponding arc is the arc representing the entry point into the aircraft; wherein, PsAnd PfThe position of the incoming aircraft at time T-0 and T-T, respectively; the range of entry angles E for the arcs is: EP1≤E≤EP2。
In combination with the first aspectThe embodiment of the present invention provides a sixth possible implementation manner of the first aspect, and mixes a calculation formula corresponding to integer linear programmingA method for calculating for 2, … N, comprising:
calculating the course angle theta of each airplane with all conflicts in the target sector released according to the following formulai：WhereinAnd Δ θiRespectively representing the initial course angle and the course angle variation of each airplane;
the relative heading angle of each aircraft in the target sector is calculated according to the following formula: q. q.sa/b＝θa-ψab+2πsgn(ψab)bab，qb/a＝θb-ψab+2πsgn(ψab)bba(ii) a Wherein psiabIs the angle of the line between the plane and the transverse axis, babAnd bbaIs a binary variable that normalizes the following domains: -pi ≦ qa/b≤π,-π≤qb/a≤π；
Calculating the minimum safety angle theta necessary for the conflict between every two airplanes in the target sector according to the following formulam：Wherein D isabThe distance between two airplanes is indicated, and r is the safe radius between the two airplanes;
according to the relative course angle theta of each airplane in the target sectoriRelative heading angle of each aircraft and minimum safety angle thetamObtaining a calculation formula corresponding to the mixed integer linear programmingfor k＝2,…N。
In a second aspect, an embodiment of the present invention further provides a complexity-based air traffic conflict management apparatus, where the apparatus includes:
the complexity graph drawing module is used for drawing a calculation graph of the complexity corresponding to the target sector according to the control activity amount corresponding to the original airplane in the target sector after the airplane enters the target sector when the airplane entering the target sector is detected; wherein, the control activity amount refers to the total course angle change amount made by the original airplane in the target sector to release any conflict caused by entering the airplane; the complexity calculation graph refers to a distribution graph of the air traffic complexity formed by all the airplanes entering the airplane in the target sector;
the optimal path calculation module is used for calculating the optimal path with the minimum conflict in the conflict area for the conflict area in the complexity calculation graph;
and the optimal entry point selection module is used for selecting an entry point corresponding to the optimal path as an optimal entry point for entering the target sector by the airplane so as to facilitate the entrance of the airplane into the target sector according to the optimal entry point.
With reference to the second aspect, an embodiment of the present invention provides a first possible implementation manner of the second aspect, where the complexity map drawing module includes:
a first calculation unit for calculating an angle of approach E and an azimuth angle B into the aircraft according to the following formulas:wherein, the binary variable n1And n2Maintaining the entry point field into the aircraft at-pi ≦ B ≦ pi and 0 ≦ E<2 pi; e represents an entrance angle; b represents an azimuth; superscript E indicates entry into the aircraft;
a second calculation unit for calculating a flight path of the incoming aircraft according to the following formulaChange curve:wherein,the abscissa representing the curve of the course of the flight trajectory,the ordinate represents the change curve of the sailing track; v represents the flying speed of the entering airplane, and the speed is a constant value; superscript I represents the incoming aircraft in the target sector; k represents any aircraft in the target sector; t represents an arbitrary time within the target sector;
the third calculating unit is used for calculating a drawing function phi according to the entering angle E and the azimuth angle B of the entering airplane and the change curve of the sailing track of the entering airplane:wherein Φ represents a drawing function;
and the complexity map drawing unit is used for drawing a calculation map of the complexity corresponding to the target sector according to the calculated drawing function.
With reference to the first possible implementation manner of the second aspect, an embodiment of the present invention provides a second possible implementation manner of the second aspect, where the optimal path calculating module includes:
and the fourth calculating unit is used for calculating the course angle change quantity delta theta of the original airplane in the target sector according to a calculation formula corresponding to the mixed integer linear programming for the conflict area in the complexity calculation graph:for k＝2,…N；
and the fifth calculating unit is used for calculating the optimal path with the minimum conflict in the conflict area according to the course angle change delta theta of the original airplane.
The embodiment of the invention provides a method and a device for managing air traffic conflicts based on complexity, which comprises the following steps: when the target sector is detected to enter the airplane, drawing a calculation graph of the complexity corresponding to the target sector according to the control activity amount corresponding to the original airplane in the target sector after the entering airplane enters the target sector; for a conflict region in a computational graph of complexity, calculating an optimal path with minimum conflict in the conflict region; the method is characterized in that an entry point corresponding to an optimal path is selected as an optimal entry point for entering the target sector by the airplane, so that the airplane entering the target sector according to the optimal entry point.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flow chart illustrating a method for complexity-based air traffic conflict management according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating an operation concept in a complexity-based air traffic conflict management method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating the definition of an entry angle E and an azimuth angle B in a complexity-based air traffic conflict management method according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating a geometry of a conflict resolution approach provided by an embodiment of the present invention;
FIG. 5 is a diagram illustrating the accessible entry points in the X-Y coordinate system and the E-B coordinate system provided by an embodiment of the present invention;
FIG. 6 is a schematic diagram illustrating a grid and the definition of adjacent discrete points provided by an embodiment of the present invention;
FIG. 7 is a schematic diagram illustrating an example of level 2 refinement provided by an embodiment of the present invention;
FIG. 8 is a schematic illustration of a sampled air traffic situation provided by an embodiment of the present invention with 5 aircraft and a sector radius of 170 nautical miles;
FIG. 9 is a diagram illustrating an algorithm of complexity, with levels 0-3 refinement, according to an embodiment of the present invention;
fig. 10 is a schematic structural diagram illustrating a complexity-based air traffic conflict management apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
The air traffic conflict management method and device based on complexity provided by the embodiment of the invention enable an airplane (namely, a lower entering airplane) to change the entry point before reaching the next sector boundary. The entry point is determined on the condition that the conflict with other airplanes in the next sector is minimized according to the complexity. The complexity is an air traffic complexity assessment method that embodies the amount of work required to handle conflicts in sectors based on the situation of entering the aircraft. The complexity in embodiments of the present invention is to provide detailed information that is important to traffic flow management on how a known traffic flow within a sector (i.e., a target sector) will respond to an incoming aircraft. The embodiment of the invention provides a problem of reducing traffic complexity brought to the airplane in a sector as far as possible when an airplane is added in a certain sector, designs a flyable path for the airplane to enter according to a Dubins path, and expands the research into various practical applications.
Referring to fig. 1, an embodiment of the present invention provides a complexity-based air traffic conflict management method, where the method includes:
s101, when an entering airplane is detected in a target sector, drawing a calculation graph of complexity corresponding to the target sector according to the control activity amount corresponding to the original airplane in the target sector after the entering airplane enters the target sector; wherein the control activity amount refers to a total amount of course angle changes made by the original aircraft in the target sector to release any conflict brought by the entering aircraft; the computational graph of the complexity refers to a distribution graph of the air traffic complexity formed by all the airplanes in the target sector including the incoming airplane.
Specifically, to graphically illustrate the control activity amount C, the control activity amount C is defined as follows based on a complexity map to quantify a conflict-free maneuver of the aircraft within the sector.
Definition 1: regulatory activity C refers to the total amount of change in heading angle made by an aircraft in a sector to free any conflict caused by an entering aircraft.
And S102, for the conflict area in the calculation graph of the complexity, calculating the optimal path with the minimum conflict in the conflict area.
Specifically, the computational graph of complexity includes a conflict area and a conflict-free area caused by entering the airplane; in the embodiment of the invention, conflict-free areas are not considered; and aiming at the conflict area, calculating the control activity C after the current entering airplane enters the target sector, namely calculating the total course angle change amount of the airplane in the sector caused by any conflict after the current entering airplane enters the target sector.
S103, selecting an entry point corresponding to the optimal path as an optimal entry point for the entering airplane to enter the target sector, so that the entering airplane can enter the target sector according to the optimal entry point.
Compared with the prior art that the traffic conflict control method is limited in one sector and cannot accurately realize the control of air traffic, the air traffic conflict management method based on the complexity provided by the embodiment of the invention draws the complexity calculation chart of entering the target sector at each point of the sector entry point of the airplane when the airplane approaches a certain sector, finds the optimal entry point of entering the airplane according to the complexity calculation chart, and corrects the aircraft entry point by using the detailed information on how the air traffic reacts to the entering airplane provided by the complexity, so that the conflict in the sector can be reduced to the maximum extent, the safety interval between entering airplanes can be ensured, and the workload of a controller can be reduced to the maximum extent.
Specifically, in current air traffic control systems, the conflict resolution is for aircraft that are within a sector. If a new aircraft approaches the sector, the system will only try to ensure a minimum separation from other aircraft after it reaches the sector boundary. In fact, if approaching aircraft can take action proactively, which is a common method of adjusting approach times to a fixed point of entry, it is possible to improve the effectiveness of managing conflicts. Much research has been carried out on approach management, particularly by adjusting the speed of entering an aircraft, in an attempt to alleviate congestion in airport airspaces. Few have studied the possibility of changing the entry point. Embodiments of the present invention forego a predetermined entry point and dynamically determine an alternate entry point into the aircraft to minimize collisions. Studies have shown that the amount of change in heading angle required to maintain separation between aircraft is significantly reduced whenever a small change is made to the sector entry point of a new approaching aircraft.
The embodiment of the present invention illustrates the proposed operation concept in two spatial domains (named sector a and sector B, respectively) in fig. 2. There are N-1 airplanes flying in sector A, and the initial condition of traffic is conflict-free. When time T is 0, an airplane approaches sector a from sector B, and the estimated approach time is T. Suppose that this incoming aircraft would cause a conflict with other aircraft in sector a. According to conventional air traffic control methods, the control system only starts trying to release the conflict caused by entering the aircraft after time T ═ T. Controllers in adjacent sectors can also resolve conflicts through close coordination, but such coordination is limited to the tactical level and only occurs when a conflict with an incoming airplane is imminent. According to the method proposed by the embodiment of the invention, the entering airplane first foresees the air in the sector A when T is TTraffic conditions and determine an appropriate entry point before reaching the sector boundary. Furthermore, at time T ═ T2Moreover, after all conflicts have been resolved, the incoming aircraft is to perform a recovery maneuver to fly toward its original destination.
Further, the method for specifically drawing the computation graph of complexity in step 101 includes:
calculating the entry angle E and the azimuth angle B of the entering airplane according to the following formulas:wherein, the binary variable n1And n2Keeping the entry point field of the entering airplane at-pi ≦ B ≦ pi and 0 ≦ E<2 pi; e represents an entrance angle; b represents an azimuth; superscript E indicates entry into the aircraft;
calculating a sailing track change curve of the incoming airplane according to the following formula:wherein,the abscissa representing the curve of the course of the flight trajectory,the ordinate represents the change curve of the sailing track; v represents the flying speed of the entering airplane, and the speed is a constant value; superscript I represents the incoming aircraft within the target sector; k represents any aircraft within the target sector; t represents an arbitrary time within the target sector;
calculating a drawing function phi according to the entering angle E and the azimuth angle B of the entering airplane and the sailing track change curve of the entering airplane:wherein Φ represents a drawing function;
and drawing a calculation graph of the complexity corresponding to the target sector according to the calculated drawing function.
Specifically, the space within the circular boundary shown in fig. 3 is taken as an example. Complexity is a result of two parameters, the entry angle E and the azimuth angle B. As can be seen in fig. 3, the angle of approach E is specified in terms of the angular coordinate of the approach from north, while the azimuth angle B describes the relative trajectory of the incoming aircraft with respect to the radial line connecting the incoming aircraft with the center of the sector.
The embodiment of the invention adopts the following assumed conditions to explain the proposed method for drawing the calculation chart of complexity by defining the control activity C and carrying out air traffic conflict management according to the calculation chart. First, all aircraft move with a constant velocity V in a two-dimensional airspace. Secondly, when the safety ring zones (circular zones with a radius of 2.5 nautical miles) of each aircraft overlap, a conflict between the two aircraft can occur. Third, each aircraft may change course angle once to avoid a conflict. Fourth, the aircraft is represented in a kinematic model that can vary the heading angle instantaneously.
The policing activity C required to map the complexity for all combinations of entry angles E and azimuth angles B can be determined by the following two steps. Embodiments of the invention are described in (X)E(0),YE(0) For example, an incoming aircraft in a location. The first step is to determine from (X)E(T),YE(T)) an angle of approach E and an azimuth angle B starting at this position and a heading angle θ of the incoming aircraftE(T). Note that T represents the time at which the incoming aircraft reaches the sector boundary, and this time T depends on the entry point (E, B), since the incoming aircraft flies at a constant velocity V, which has been explained in the foregoing. If the sector center is at the initial position, then (E, B) and (X)E(T),YE(T)，θE(T)) can be expressed as the following equation:
in the above formulas (1) and (2), the superscript E indicates entering the aircraft, and in addition, the binary variable n is substituted1And n2To keep the domains-pi ≦ B ≦ pi and 0 ≦ E<2 pi. The second step is to determine the location and heading angle of the aircraft within the sector at time T-T. The kinematic model of the kth aircraft in a sector can be expressed as the following equation:
wherein the superscript I denotes the aircraft within the sector.
From this information, we can define the mapping function Φ as follows:
to obtain the management activity C, a conflict resolution algorithm needs to be formulated. The amount of regulatory activity C depends on which conflict resolution algorithm is selected and there are currently a number of different algorithms available for selection. For illustrative purposes, however, the present invention proposes a special conflict resolution algorithm, namely a sequential conflict resolution algorithm based on mixed integer linear programming.
The sequential algorithm is used to calculate the heading angle change delta theta of each aircraft so that all conflicts can pass through the new heading angle theta (theta-theta)0+ Δ θ), where θ0For each aircraftThe initial heading angle of (a). Geometric considerations can be made for the case of two aircraft in a sector, on the basis of which a collision-free condition is derived, which condition is then extended to the general case of N aircraft. In a sequential algorithm for resolving conflicts, a performance index is determined for minimizing the heading angle change Δ θ per aircraft. Furthermore, we derive constraints from the collision-free conditions. The detailed formulation of the in-order algorithm to resolve conflicts is described in detail below. It is to be noted here that the method proposed by the embodiments of the present invention does not exclude other types of conflict resolution algorithms.
Further, in step 102, for a collision region in the computation graph of complexity, a specific method for computing an optimal path with the minimum collision in the collision region includes:
for the conflict area in the calculation graph of the complexity, calculating the course angle change quantity delta theta of the original airplane in the target sector according to a calculation formula corresponding to the mixed integer linear programming:for k＝2,…N。
and calculating the optimal path with the minimum conflict in the conflict area according to the course angle change quantity delta theta of the original airplane.
The above-mentioned mixed integer linear programming corresponds to the calculation formulafor k 2, … N is calculated according to the following method:
calculating the course angle theta of each aircraft with all conflicts in the target sector released according to the following formulai：WhereinAnd Δ θiRespectively representing the initial course angle and the course angle variation of each airplane;
calculating the relative course angle of each aircraft in the target sector according to the following formula: q. q.sa/b＝θa-ψab+2πsgn(ψab)bab，qb/a＝θb-ψab+2πsgn(ψab)bba(ii) a Wherein psiabIs the angle of the line between the plane and the transverse axis, babAnd bbaIs a binary variable that normalizes the following domains: -pi ≦ qa/b≤π,-π≤qb/a≤π；
Calculating the minimum safety angle theta necessary for the conflict between every two airplanes in the target sector according to the following formulam：Wherein D isabThe distance between two airplanes is indicated, and r is the safe radius between the two airplanes;
according to the relative course angle theta of each airplane in the target sectoriThe relative heading angle of each aircraft and the minimum safety angle thetamObtaining a calculation formula corresponding to the mixed integer linear programmingfor k＝2,…N。
Specifically, the above process is a derivation process of a detailed formula of a sequential algorithm for resolving conflicts, that is, an optimization problem of determining the control activity C:
the conflict-free condition in terms of geometrical considerations is derived as follows. First we consider the case of two airplanes, followed by the general case of N airplanes. There is no conflict between aircraft a and b if one of the following conditions is met.
Condition 1:
qa/b≥0,qb/a≥0,qa/b≥qb/a(6)
condition 2:
qa/b≥0,qb/a≤0,qa/b≤qb/a(7)
condition 3:
qa/b≥0,qb/a≤0,qa/b≥-qb/a(9)
condition 4:
qa/b≥0，qb/a≤0，qa/b≤-qb/a(10)
condition 5:
qa/b≤0，qb/a≥0，-qa/b≥qb/a(12)
condition 6:
qa/b≤0，qb/a≥0，-qa/b≤qb/a(13)
condition 7:
qa/b≤0，qb/a≤0，-qa/b≥-qb/a(15)
condition 8:
qa/b≤0，qb/a≤0，-qa/b≤-qb/a(16)
wherein q isa/bAnd q isb/aIs the relative heading angle, θaAnd thetabIs the absolute heading angle. Attention is paid to the heading angle θ of each aircraft to free all conflictsiIs calculated according to the following formula:
wherein,and Δ θiRespectively representing the initial heading angle and the heading angle variation of each aircraft. The relative heading angle can be calculated as follows:
qa/b＝θa-ψab+2πsgn(ψab)bab(19)
qb/a＝θb-ψab+2πsgn(ψab)bba(20)
wherein psiabIs the angle of the line between the plane and the transverse axis, babAnd bbaThen it is a binary variable that normalizes the following domains:
-π≤qa/b≤π,-π≤qb/a≤π (21)
further, θmThe minimum safety angle necessary to avoid a conflict between two aircraft, embodiments of the present invention may calculate this angle by the following equation:
wherein DabRefers to the distance between the two aircraft, and r is the safe radius, as shown in fig. 4.
The numerical value of the control activity C is obtained by adopting the conflict resolution sequential algorithm provided by the embodiment of the invention. This is because in reality, the air traffic controller can only give an instruction to change the maneuver to one aircraft at a time, and then the air traffic controller can only give an instruction to another aircraft to change its maneuver after a certain time interval, so that the conflict resolution method is necessarily performed in sequence. Note that in the sequential conflict resolution algorithm, we sort the aircraft east and west. Furthermore, if the two planes are positioned perpendicular to each other, the south-most plane is assigned a lower numerical sequence number. The number with the minimum number of '1' is assigned to the entering airplane, and finally, the conflict resolution problem of the airplane in the k-th sector can be expressed according to mixed integer linear programming:
for the case of N aircraft, the above optimization problem for the aircraft in the k-th sector is solved by operating N-1 times. For example, for the problem of this conflict resolution, we first determine the lowest regulatory activity Δ θ for the aircraft in the first sector relative to the stationary incoming aircraft2. After the course angle of the airplane in the first frame sector is changed, the controlled activity delta theta of the airplane in the second frame sector is calculated3To satisfy the condition of no conflict with the fixed incoming aircraft and the aircraft in the first sector. Through the steps, the answer delta theta of each question is given2，Δθ3… and Δ θN. Next, the amount of regulated activity C in terms of the total amount of angular change of the heading, i.e., the amount of angular change of the heading, can be calculated
Complexity is introduced in determining new alternate entry points at sector boundaries. Complexity-i.e., how much regulatory activity is required to disengage the conflict from entering an aircraft, depending on all possible entry points into the aircraft (i.e., into the aircraft). From such information, we can determine the optimal entry point with minimal regulatory activity. The embodiment of the invention provides an entry point decision algorithm, and therefore, the entry point with the highest feasibility is determined instead of the initial entry point which is fixedly kept. In addition, the embodiment of the invention also provides a method for improving the computational efficiency during the complexity of drawing, wherein the variable grid structure of the aerograph and the maneuverability of the airplane are considered.
Further, the drawing function calculated in step 101 considers an ideal state, but the solving process corresponding to the ideal state is very complex, for this reason, the embodiment of the present invention provides a method for solving a drawing function, which reduces the calculation amount thereof and has good operability, and the specific method includes:
solving the drawing function by adopting a variance quadtree drawing algorithm so as to draw a calculation graph of the complexity corresponding to the target sector according to a solving result; the above-mentioned solving the mapping function by using the variance quadtree mapping algorithm to map the computation graph of the complexity corresponding to the target sector according to the solving result specifically includes:
step 1: converting an arc in the X-Y coordinate system representing an entry point into the aircraft into a square in the E-B coordinate system; the above-mentioned arc representing the entry point into the aircraft is obtained by: acquiring an access point P which can be reached by the entering airplane on the boundary of the target sector1And P2(ii) a Determining the entry point P1And P2The corresponding arc is the arc representing the entry point into the aircraft; wherein, PsAnd PfThe position of the incoming aircraft at time T-0 and T-T, respectively; the range of the entry angle E corresponding to the circular arc is: EP1≤E≤EP2。
Step 2: dividing a search space S according to the grid size delta of the square;
and 3, step 3: calculating a regulatory activity quantity C at each discrete point (E, B) and plotting a corresponding complexity;
and 4, step 4: converting the complexity into a binary lattice, wherein each point has two expressions: c ═ 0 or ≠ 0 (i.e., C ═ 1);
and 5, step 5: calculating a variance Q for each square in space S; the method for calculating the variance Q comprises the following steps:
and 6, step 6: repeating steps 3-5 until all Q's in the subdivision are zero, or until the grid size is reduced to a minimum grid size set to 1 degreeUntil the end;
and 6, the drawn complexity corresponding to the step 6 is a final calculation graph of the complexity corresponding to the target sector.
Specifically, the embodiment of the present invention describes an entry point decision algorithm. Such a decision algorithm is required when a new aircraft enters a certain sector. In the above we have explained that we consider an entry angle E from 0 to 360 degrees and an azimuth angle B from-90 to 90 degrees in the initial complexity. If the two angles are discretized by a grid size of 1 degree, the mixed integer linear programming model in equation (5) goes through 65,160 (181 × 360) solutions to map the complexity. Increasing the grid size in complexity reduces the required computations, but the complexity is less accurate because its accuracy is inversely proportional to the grid size. To address this problem, embodiments of the present invention focus on how quickly and accurately rendering complexity. This section is divided into three parts, each of which proposes a solution to this problem.
Accessible entry point at sector boundary
The method proposed by the embodiment of the invention does not need to consider the whole range of the entrance angle E so that E is more than or equal to 0<2 pi. The range of the entry angle E can be defined by considering only the accessible entry points on the sector boundaries corresponding to the initial position of entry into the aircraft. The entry points that can be reached at the sector boundary are limited to P1And P2The two contact points define an arc, as shown in the left diagram of FIG. 5, where PsAnd PfThe position of the incoming aircraft at time T-0 and T-T, respectively. The circular arc in the X-Y coordinate system can be transformed into a square in the E-B coordinate system as shown in the right diagram of fig. 5. It is noted here that by considering the entry points that can be reached, we can map only the complexity of EP1 ≦ E ≦ EP2 within the defined range, without having to consider 0 ≦ E<2 pi the entire range. Wherein, in FIG. 5, the left diagram shows a circle in the X-Y coordinate system; the right hand figure shows a square in the E-B coordinate system.
We can then make the following analysis of the magnitude of the reduction in the amount of computation required. Let us denote the sector radius by R and P in FIG. 3 by dsAnd PfThe distance between them. Then, the reduction ratio of the calculated amount can be calculated according to the following formula; in the left-hand picture of figure 5, the maximum number of calculations may be calculated. When the square in the E-B coordinate system is uniformly discretized by the minimum grid size, the maximum number of computations is the number of grid points. If the minimum grid size is specified to beThe maximum number of calculations can be calculated according to the following equation:for example, if R is specified to be 200 nautical miles and d is specified to be 30 nautical miles, the number of calculations can be reduced by 16.44%. Furthermore, if specifiedAt 1 degree, the maximum number of calculations is approximately 11,041.
Although the embodiments of the present invention primarily consider circular boundaries, the method proposed can be applied to sector boundaries of any shape with ease. However, in the case of an arbitrarily shaped sector boundary, two additional parameters are required instead of the entry angle E and the azimuth angle B. First, we define the entry point of the aircraft in terms of the amount of displacement along the sector boundary from the reference point. The orientation of the incoming aircraft is then specified relative to the north. By using these two parameters instead of E and B, the complexity of arbitrarily shaped sector boundaries can be determined. The schematic complexity of the non-circular sector boundaries will be given later.
(II) aerograph drawing algorithm based on variance quadtree
This section introduces a variance quadtree mapping algorithm for binary complexity. The initial variance quadtree algorithm was a spatial sampling method in which an image was divided into four equal quadrants until the variance within the hierarchy was reduced to some specified degree. In an embodiment of the present invention, entry points with a regulatory activity level C greater than 0 are considered unsuitable entry points. It is therefore stated whether C-0 contains sufficient information when drawing a binary chart. Now in a hierarchical manner, our algorithm starts first with a uniform coarse grid covering the search space where the entry point can be reached, but adds a finer secondary grid in some areas. By repeating this process from coarse to fine, we can map out the binary complexity and effectively retain the information in the original complexity.
In the following we take a single stage refinement approach as an example. Single level refinement may be extended to multiple levels of refinement. We denote the search space as S e R2, i.e. the boxed area in the left diagram of fig. 5. The region S is partitioned into grids of size δ to map complexity. The next step is to calculate a regulated activity level C for each point (E, B) in the area S. Fig. 6 illustrates a grid and its neighboring discrete points. The variance of the measure of activity Q at the vertices of the four squares is a criterion to determine whether further partitioning of the finer secondary mesh is required. The variance Q is calculated as follows:
whereinThe average number of movements is scaled for the square lattice vertices. If Q ≠ 0, then the quad-squares are divided into sizesThe four quadrants of (1); otherwise there is no need to divide the finer secondary mesh. Fig. 7 shows an example of level 2 refinement.
The processing flow of the variance quadtree mapping algorithm is as follows:
step 1: the search space S is divided by the grid size δ.
Step 2: the amount of regulatory activity C at each discrete point (E, B) is calculated and the corresponding complexity is plotted.
And 3, step 3: converting the complexity into a binary lattice, wherein each point has two expressions: c ═ 0 or ≠ 0(C ═ 1). In other words, if the regulated activity amount C is not zero, the value is changed to 1.
And 4, step 4: the variance Q in equation (8) is calculated for each square in space S.
And 5, step 5: repeating steps 2-4 until all Q's in the subdivision are zero, or until the grid size is reduced to a minimum set to 1 degreeSize of the gridUntil now.
It is noted here that the amount of regulatory activity C at many entry points (E, B) ε S is zero. Of all these alternative entry points, the present embodiment treats the point closest to the original entry point as the most feasible entry point.
As shown in fig. 8, fig. 8 shows a sample air traffic situation, i.e., 5 aircraft in a sector at radius 170 nautical miles; in fig. 8, the left diagram represents the initial traffic situation and the right diagram represents the final destination; wherein, the Y axis (in nautical miles); x-axis (units are nautical miles). In the left diagram of fig. 8, the sector boundaries are depicted as one large circle, with small triangles representing the randomly assigned initial position and direction of the aircraft at time t-0. As previously mentioned, each aircraft is assigned a number in the order from west to east, and the word "AC" in the figure represents "aircraft". The five pointed star in the right hand diagram of fig. 8 represents the final destination of these aircraft within the sector. When time t is 0, we apply the proposed collision management method to resolve the collision brought by the airplane 1 entering the sector. Since the path to the aircraft deviates from its original destination for conflict resolution, the conflict resolution algorithm is re-run at each time step to calculate a new direction so that all aircraft can reach their final destination. In this scenario, if the incoming aircraft continues to fly forward, a 4.61 degree control activity is required. But the aircraft in the sector need not maneuver to resolve the conflict because of the alternative entry point determined by the complexity of having the incoming aircraft fly past. Fig. 9, left 1, shows the complexity of rendering according to a single uniform grid method, where the white areas indicate that the aircraft does not need control activities in them, while in the black areas there are conflicts caused by aircraft 1. Fig. 9 left 2 to 9 left 4 illustrate the complexity of rendering through levels 1-3 of refinement according to our proposed algorithm, where the small circles in black represent the initial predetermined entry point (entry angle, azimuth 267, 0), as determined by the initial position and direction of entry into the aircraft; the small black triangle then indicates the re-determined entry point (entry angle, azimuth 268, -7), where the control activity C from the nearest entry point to the original entry point is zero. In fig. 9, B (deg): azimuth angle (degrees); e (deg): the entry angle (degree).
Compared with the prior art that the traffic conflict control method is limited in one sector and cannot accurately realize the control of air traffic, the air traffic conflict management method based on the complexity provided by the embodiment of the invention draws the complexity calculation chart of entering the target sector at each point of the sector entry point of the airplane when the airplane approaches a certain sector, finds the optimal entry point of entering the airplane according to the complexity calculation chart, and corrects the aircraft entry point by using the detailed information on how the air traffic reacts to the entering airplane provided by the complexity, so that the conflict in the sector can be reduced to the maximum extent, the safety interval between entering airplanes can be ensured, and the workload of a controller can be reduced to the maximum extent.
The embodiment of the invention aims at the problem that the new airplane enters the sector to explore the feasible entry point which does not bring conflict resolution activity to the airplane in the sector. While conventional solutions to such conflicts focus on intra-sector optimal resolution, our proposed conflict management approach attempts to determine the best strategy across multiple sectors, which may be the basis for further research in the future. While a new conflict resolution method in the air traffic management field is proposed, we have re-interpreted and modified the original complexity concept. The entry point decision algorithm provided by the embodiment of the invention considers the maneuvering capability of entering the airplane and applies the variance quadtree algorithm so as to draw the complexity more efficiently. We also present the results of numerical simulations (including a monte carlo simulation) and apply the proposed method in real traffic scenarios to verify its effect. In future research, models used by the method should be expanded, and two-dimensional traffic models adopted by people are expanded into three-dimensional models. It may also be necessary to consider different conflict resolution maneuvers (e.g., a combination maneuver that changes both heading angle and speed). The extended models may require different optimization techniques, such as non-linear planning and geometric planning, to make them computationally easier to handle. The effect of our proposed method also needs to be further examined in a variety of traffic situations. This concept of conflict management should be further refined and examined. Furthermore, based on the results of this study, we must make a more practical air traffic management protocol and interface of the relevant decision support tools, and perform exhaustive co-occurrence analysis to further verify the applicability of the proposed method.
An embodiment of the present invention further provides a complexity-based air traffic conflict management apparatus, where the apparatus is configured to execute the complexity-based air traffic conflict management method, and with reference to fig. 10, the apparatus includes:
the complexity graph drawing module 11 is configured to, when it is detected that the target sector enters the airplane, draw a computation graph of complexity corresponding to the target sector according to the control activity amount corresponding to the original airplane in the target sector after the entering airplane enters the target sector; wherein, the control activity amount refers to the total course angle change amount made by the original airplane in the target sector to release any conflict caused by entering the airplane; the complexity calculation graph refers to a distribution graph of the air traffic complexity formed by all the airplanes entering the airplane in the target sector;
the optimal path calculation module 12 is configured to calculate, for a collision region in the computation graph of complexity, an optimal path with the minimum collision in the collision region;
and an optimal entry point selection module 13, configured to select an entry point corresponding to the optimal path as an optimal entry point for entering the aircraft into the target sector.
Further, the complexity map drawing module 11 of the air traffic conflict management apparatus based on complexity includes:
a first calculation unit for calculating an angle of approach E and an azimuth angle B into the aircraft according to the following formulas:wherein, the binary variable n1And n2Maintaining the entry point field into the aircraft at-pi ≦ B ≦ pi and 0 ≦ E<2 pi; e represents an entrance angle; b represents an azimuth; superscript E indicates entry into the aircraft;
the second calculating unit is used for calculating a sailing track change curve of the incoming airplane according to the following formula:wherein,the abscissa representing the curve of the course of the flight trajectory,the ordinate represents the change curve of the sailing track; v represents the flying speed of the entering airplane, and the speed is a constant value; superscript I represents the incoming aircraft in the target sector; k represents any aircraft in the target sector; t represents an arbitrary time within the target sector;
the third calculating unit is used for calculating a drawing function phi according to the entering angle E and the azimuth angle B of the entering airplane and the change curve of the sailing track of the entering airplane:wherein Φ represents a drawing function;
and the complexity map drawing unit is used for drawing a calculation map of the complexity corresponding to the target sector according to the calculated drawing function.
Further, the above-mentioned air traffic collision management device based on complexity, the optimal path calculation module 12, includes:
fourth calculation sheetAnd the element is used for calculating the course angle change quantity delta theta of the original airplane in the target sector according to a calculation formula corresponding to the mixed integer linear programming for the conflict area in the calculation graph of the complexity:for k＝2,…N。
and the fifth calculating unit is used for calculating the optimal path with the minimum conflict in the conflict area according to the course angle change delta theta of the original airplane.
Compared with the prior art that the traffic conflict control method is limited in one sector and cannot accurately realize the control of air traffic, the air traffic conflict management device based on the complexity provided by the embodiment of the invention draws the complexity calculation chart of entering the target sector at each point of the sector entry point of the airplane when the airplane approaches a certain sector, finds the optimal entry point of entering the airplane according to the complexity calculation chart, and corrects the entry point of the airplane by using the detailed information on how the air traffic reacts to the entering airplane provided by the complexity, so that the conflict in the sector can be reduced to the greatest extent to ensure the safety interval between entering airplanes.
The complexity-based air traffic conflict management provided by embodiments of the present invention may be specific hardware on the device or software or firmware installed on the device, etc. The device provided by the embodiment of the present invention has the same implementation principle and technical effect as the method embodiments, and for the sake of brief description, reference may be made to the corresponding contents in the method embodiments without reference to the device embodiments. It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the foregoing systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments provided by the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus once an item is defined in one figure, it need not be further defined and explained in subsequent figures, and moreover, the terms "first", "second", "third", etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the present invention in its spirit and scope. Are intended to be covered by 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. A method for complexity-based air traffic conflict management, the method comprising:
when the target sector is detected to enter the airplane, drawing a calculation graph of the complexity corresponding to the target sector according to the control activity amount corresponding to the original airplane in the target sector after the airplane enters the target sector; wherein the control activity amount refers to a total amount of course angle changes made by the original aircraft in the target sector to release any conflict brought by the entering aircraft; the computation graph of the complexity refers to a distribution graph of air traffic complexity formed by all the airplanes which enter the airplane in the target sector;
for a conflict region in the computation graph of the complexity, computing an optimal path with the minimum conflict in the conflict region;
selecting an entry point corresponding to the optimal path as an optimal entry point for the entering airplane to enter the target sector, so that the entering airplane can enter the target sector according to the optimal entry point;
the drawing a calculation chart of the complexity corresponding to the target sector according to the control activity amount corresponding to the original airplane in the target sector after the entering airplane enters the target sector includes:
calculating the entry angle E and the azimuth angle B of the entering airplane according to the following formulas:wherein, the binary variable n1And n2Keeping the entry point field of the entering airplane at-pi ≦ B ≦ pi and 0 ≦ E<2 pi; e represents an entrance angle; b represents an azimuth; superscript E indicates entry into the aircraft;
calculating a sailing track change curve of the incoming airplane according to the following formula:wherein,the abscissa representing the curve of the course of the flight trajectory,the ordinate represents the change curve of the sailing track; v represents the flying speed of the entering airplane, and the speed is a constant value; superscript I represents the incoming aircraft within the target sector; k represents any aircraft within the target sector; t represents an arbitrary time within the target sector;
according to the entrance angle E of the entering airplane,Calculating a drawing function phi by the azimuth angle B and the change curve of the sailing track of the entering airplane:wherein Φ represents a drawing function;
drawing a calculation graph of the complexity corresponding to the target sector according to the calculated drawing function;
for the conflict region in the computation graph of the complexity, computing an optimal path with the minimum conflict in the conflict region, including:
for the conflict area in the calculation graph of the complexity, calculating the course angle change quantity delta theta of the original airplane in the target sector according to a calculation formula corresponding to the mixed integer linear programming:
and calculating the optimal path with the minimum conflict in the conflict area according to the course angle change quantity delta theta of the original airplane.
2. The method of claim 1, wherein said plotting the complexity corresponding to the target sector according to the calculated plot function comprises:
and solving the drawing function by adopting a variance quadtree drawing algorithm so as to draw a calculation graph of the complexity corresponding to the target sector according to a solving result.
3. The method of claim 2, wherein solving the mapping function using a variance quadtree mapping algorithm to map a computational graph of the complexity corresponding to the target sector according to the solution result comprises:
step 1: converting an arc in the X-Y coordinate system representing an entry point into the aircraft into a square in the E-B coordinate system;
step 2: dividing a search space S according to the grid size delta of the square;
and 3, step 3: calculating a regulatory activity quantity C at each discrete point (E, B) and plotting a corresponding complexity;
and 4, step 4: converting the complexity into a binary lattice, wherein each point has two expressions: c ═ 0 or C ═ 1;
and 5, step 5: calculating a variance Q for each square in space S; the method for calculating the variance Q comprises the following steps:
and 6, step 6: repeating steps 3-5 until all Q's in the subdivision are zero, or until the grid size is reduced to a minimum grid size set to 1 degreeUntil the end;
and 6, the drawn complexity corresponding to the step 6 is a final calculation graph of the complexity corresponding to the target sector.
4. A method according to claim 2 or 3, characterized in that the arc representing the entry point into the aircraft is obtained by:
acquiring an access point P which can be reached by the entering airplane on the boundary of the target sector1And P2；
Determining the entry point P1And P2The corresponding arc is the arc representing the entry point into the aircraft; wherein, PsAnd PfThe position of the incoming aircraft at time T-0 and T-T, respectively; the range of the entry angle E corresponding to the circular arc is: EP1≤E≤EP2。
5. The method of claim 1, wherein the mixed integer linear programming corresponds to a computational formulaThe calculation method of (2) comprises:
calculating the course angle theta of each aircraft with all conflicts in the target sector released according to the following formulai：WhereinAnd Δ θiRespectively representing the initial course angle and the course angle variation of each airplane;
calculating the relative course angle of each aircraft in the target sector according to the following formula: q. q.sa/b＝θa-ψab+2πsgn(ψab)bab，qb/a＝θb-ψab+2πsgn(ψab)bba(ii) a Wherein psiabIs the angle of the line between the plane and the transverse axis, babAnd bbaIs a binary variable that normalizes the following domains: -pi ≦ qa/b≤π,-π≤qb/a≤π；
Calculating the minimum safety angle theta necessary for the conflict between every two airplanes in the target sector according to the following formulam：Wherein D isabThe distance between two airplanes is indicated, and r is the safe radius between the two airplanes;
according to the relative course angle theta of each airplane in the target sectoriThe relative heading angle of each aircraft and the minimum safety angle thetamObtaining a calculation formula corresponding to the mixed integer linear programming
6. An apparatus for complexity-based air traffic conflict management, the apparatus comprising:
the complexity graph drawing module is used for drawing a calculation graph of the complexity corresponding to a target sector according to the control activity amount corresponding to the original airplane in the target sector after the entering airplane enters the target sector when the entering airplane is detected to enter the airplane; wherein the control activity amount refers to a total amount of course angle changes made by the original aircraft in the target sector to release any conflict brought by the entering aircraft; the computation graph of the complexity refers to a distribution graph of air traffic complexity formed by all the airplanes which enter the airplane in the target sector;
the optimal path calculation module is used for calculating an optimal path with the minimum conflict in the conflict area for the conflict area in the complexity calculation graph;
an optimal entry point selection module, configured to select an entry point corresponding to the optimal path as an optimal entry point for the entering aircraft to enter the target sector, so that the entering aircraft enters the target sector according to the optimal entry point;
the complexity map drawing module comprises:
a first calculation unit for calculating the angle of approach E and the azimuth angle B of the incoming aircraft according to the following formulas:wherein, the binary variable n1And n2Keeping the entry point field of the entering airplane at-pi ≦ B ≦ pi and 0 ≦ E<2 pi; e represents an entrance angle; b represents an azimuth; superscript E indicates entry into the aircraft;
the second calculation unit is used for calculating the sailing track change curve of the incoming airplane according to the following formula:wherein,the abscissa representing the curve of the course of the flight trajectory,the ordinate represents the change curve of the sailing track; v represents the flying speed of the entering airplane, and the speed is a constant value; superscript I represents the incoming aircraft within the target sector; k represents any aircraft within the target sector; t represents an arbitrary time within the target sector;
a third calculating unit, configured to calculate a mapping function Φ according to the entering angle E and the azimuth angle B of the entering aircraft and the sailing trajectory variation curve of the entering aircraft:wherein Φ represents a drawing function;
a complexity map drawing unit, configured to draw a calculation map of complexity corresponding to the target sector according to the calculated mapping function;
the optimal path calculation module comprises:
a fourth calculating unit, configured to calculate, for a conflict area in the complexity calculation graph, a heading angle change Δ θ of the original aircraft in the target sector according to a calculation formula corresponding to a mixed integer linear programming:
and the fifth calculation unit is used for calculating the optimal path with the minimum conflict in the conflict area according to the course angle change quantity delta theta of the original airplane.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710113182.7A CN106875755B (en) | 2017-02-28 | 2017-02-28 | A kind of air traffic conflict management method and device based on complexity |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710113182.7A CN106875755B (en) | 2017-02-28 | 2017-02-28 | A kind of air traffic conflict management method and device based on complexity |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106875755A CN106875755A (en) | 2017-06-20 |
| CN106875755B true CN106875755B (en) | 2018-06-29 |
Family
ID=59168069
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710113182.7A Active CN106875755B (en) | 2017-02-28 | 2017-02-28 | A kind of air traffic conflict management method and device based on complexity |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106875755B (en) |
Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6618562B2 (en) * | 2018-03-22 | 2019-12-11 | 東京計器株式会社 | Ship navigation support device |
| WO2019212892A2 (en) * | 2018-05-04 | 2019-11-07 | Interdigital Patent Holdings, Inc. | Market based detect and avoid (daa) solutions |
| CN109979248B (en) * | 2019-04-25 | 2020-10-23 | 浙江工业大学 | Flight conflict resolution method based on dynamic planning |
| HRP20210018B1 (en) * | 2020-05-25 | 2022-06-24 | Sveučilište u Zagrebu FAKULTET PROMETNIH ZNANOSTI | Method for air traffic control system operation |
| CN112053333B (en) * | 2020-08-31 | 2023-04-07 | 中冶赛迪信息技术(重庆)有限公司 | Square billet detection method, system, equipment and medium based on machine vision |
| CN112164248B (en) * | 2020-11-12 | 2022-05-17 | 中国民航大学 | Air traffic complexity evaluation method based on flight intention interactive relation |
| CN112562421B (en) * | 2020-11-27 | 2022-04-12 | 大蓝洞(南京)科技有限公司 | Flight conflict evaluation method based on index system |
| CN113823125A (en) * | 2021-10-11 | 2021-12-21 | 北京瀚文智远信息技术有限公司 | Sector dynamic division method |
| CN114023111A (en) * | 2021-11-03 | 2022-02-08 | 中国民航大学 | Air traffic situation complexity evaluation method oriented to autonomous operation of aircraft |
| CN116312072B (en) * | 2023-03-21 | 2024-01-26 | 中国人民解放军93209部队 | Flight path operation conflict decoupling control method based on airspace grids |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101004861A (en) * | 2006-11-08 | 2007-07-25 | 北京航空航天大学 | System for monitoring moving target on place of aerodrome |
| CN102855778A (en) * | 2012-09-10 | 2013-01-02 | 南京航空航天大学 | Space-domain sector classification method based on complexity assessment |
| CN106297415A (en) * | 2016-08-16 | 2017-01-04 | 南京航空航天大学 | Movement area operation situation appraisal procedure |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8619669B2 (en) * | 2007-09-24 | 2013-12-31 | Qualcomm Incorporated | Multicast communications within a wireless communications network |
-
2017
- 2017-02-28 CN CN201710113182.7A patent/CN106875755B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101004861A (en) * | 2006-11-08 | 2007-07-25 | 北京航空航天大学 | System for monitoring moving target on place of aerodrome |
| CN102855778A (en) * | 2012-09-10 | 2013-01-02 | 南京航空航天大学 | Space-domain sector classification method based on complexity assessment |
| CN106297415A (en) * | 2016-08-16 | 2017-01-04 | 南京航空航天大学 | Movement area operation situation appraisal procedure |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106875755A (en) | 2017-06-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106875755B (en) | A kind of air traffic conflict management method and device based on complexity | |
| CN107145161B (en) | Flight path planning method and device for unmanned aerial vehicle to access multiple target points | |
| Chen et al. | Modified central force optimization (MCFO) algorithm for 3D UAV path planning | |
| Pehlivanoglu | A new vibrational genetic algorithm enhanced with a Voronoi diagram for path planning of autonomous UAV | |
| Turker et al. | 2D path planning for UAVs in radar threatening environment using simulated annealing algorithm | |
| CN110262563A (en) | Multiple no-manned plane collaboratively searching mesh calibration method waterborne | |
| Lauderdale | Probabilistic conflict detection for robust detection and resolution | |
| Fu et al. | An advanced sense and collision avoidance strategy for unmanned aerial vehicles in landing phase | |
| Haghighi et al. | Performance-based emergency landing trajectory planning applying meta-heuristic and Dubins paths | |
| EP0960413A1 (en) | Cooperative resolution of air traffic conflicts | |
| Zhao et al. | Multiple-aircraft-conflict resolution under uncertainties | |
| CN115686072B (en) | Automatic generation method of unmanned aerial vehicle group safe operation air line based on spatial grid | |
| Shi et al. | A distributed conflict detection and resolution method for unmanned aircraft systems operation in integrated airspace | |
| Emami et al. | Multi-agent based solution for free flight conflict detection and resolution using particle swarm optimization algorithm | |
| CN117170238A (en) | Heterogeneous unmanned aerial vehicle cluster search algorithm based on collaborative distributed MPC | |
| Zhang et al. | Bald eagle search algorithm for solving a three-dimensional path planning problem | |
| Neretin et al. | Optimal four-dimensional route searching methodology for civil aircrafts | |
| Kulida et al. | Methods for solving some problems of air traffic planning and regulation. PART I: Strategic Planning оf 4D Trajectories | |
| Sun et al. | Velocity obstacle–based conflict resolution and recovery method | |
| Yakovlev et al. | Analysis of the problem functioning modeling ergatic air traffic management information system | |
| Purwananto et al. | Collision avoidance modelling in airline traffic based on the change of airplane movements and dynamic clouds | |
| CN117250859B (en) | Multi-aircraft collaborative search algorithm under communication constraint | |
| Fanti et al. | Modeling and optimization of aircraft trajectories: a review | |
| Xiao et al. | An improved ant colony optimization approach for multi-aircraft horizontal escape maneuvers | |
| Wang et al. | An approximation path planning algorithm for fixed-wing UAVs in stationary obstacle environment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |