CN110634332A - Airport airspace flow control method for small and medium-sized vertical take-off and landing unmanned aerial vehicle - Google Patents

Airport airspace flow control method for small and medium-sized vertical take-off and landing unmanned aerial vehicle Download PDF

Info

Publication number
CN110634332A
CN110634332A CN201910938492.1A CN201910938492A CN110634332A CN 110634332 A CN110634332 A CN 110634332A CN 201910938492 A CN201910938492 A CN 201910938492A CN 110634332 A CN110634332 A CN 110634332A
Authority
CN
China
Prior art keywords
unmanned aerial
aerial vehicle
route
airport
node
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.)
Granted
Application number
CN201910938492.1A
Other languages
Chinese (zh)
Other versions
CN110634332B (en
Inventor
全权
崔恺
赵民强
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Flying Bull Intelligent Technology (nanjing) Co Ltd
Original Assignee
Flying Bull Intelligent Technology (nanjing) Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Flying Bull Intelligent Technology (nanjing) Co Ltd filed Critical Flying Bull Intelligent Technology (nanjing) Co Ltd
Priority to CN201910938492.1A priority Critical patent/CN110634332B/en
Publication of CN110634332A publication Critical patent/CN110634332A/en
Application granted granted Critical
Publication of CN110634332B publication Critical patent/CN110634332B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G5/00Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/003Flight plan management
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G5/00Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0043Traffic management of multiple aircrafts from the ground
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G5/00Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047Navigation or guidance aids for a single aircraft
    • G08G5/0069Navigation or guidance aids for a single aircraft specially adapted for an unmanned aircraft

Landscapes

  • Engineering & Computer Science (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Traffic Control Systems (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

The invention relates to the technical field of unmanned aerial vehicles, and discloses a flow control method for an airport airspace of a small and medium-sized vertical take-off and landing unmanned aerial vehicle, which comprises the following six parts: s1Unmanned aerial vehicle model design, S2Airport aeronautical road chart model design, S3Method design and S for planning air route4Flight delay strategy, S5Airport route map updating method design and S6And (4) emergency landing. The method for controlling the airport airspace flow of the small and medium-sized vertical take-off and landing unmanned aerial vehicle comprises the steps of adjusting the residual air routes of the airport in real time by using a graph theory method, ensuring the flight safety of the unmanned aerial vehicle in the airport airspace, well finishing the aim of controlling the airport airspace flow of the unmanned aerial vehicle, providing a safe and efficient interface for the unmanned aerial vehicle needing emergency landing, meeting the requirement of the airport airspace flow control under the actual condition, having small algorithm calculation amount, high robustness and good universality, and being suitable for similar airportsThe application is as follows.

Description

Airport airspace flow control method for small and medium-sized vertical take-off and landing unmanned aerial vehicle
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a method for controlling the airport airspace flow of a small and medium-sized vertical take-off and landing unmanned aerial vehicle.
Background
Unmanned aerial vehicle is applied to city commodity circulation prospect wide, and VTOL and many rotor unmanned aerial vehicle all can realize hovering and VTOL, and the maneuverability is excellent, turns to in a flexible way, and it is lower to the airport condition requirement, is fit for being applied to city commodity circulation. The airport flow control method adopted by civil aviation is not suitable for small and medium-sized unmanned aerial vehicles capable of taking off and landing vertically, and an unmanned aerial vehicle airport on the current market can only realize the taking off and landing of a single unmanned aerial vehicle, and a subsequent unmanned aerial vehicle can enter after the previous unmanned aerial vehicle leaves the airport. In a real logistics scene, an 'airport' will be a material inventory area, a transfer station or a distribution station, and the capability of taking off and landing a plurality of unmanned aerial vehicles simultaneously is required. When the density of the unmanned aerial vehicle in the airport area is high, an airport and a reasonable flow control method applied to the urban logistics scene need to be designed, so that the flight safety of the unmanned aerial vehicle in the airport area is ensured, and the traffic efficiency is improved. Therefore, the application provides a flow control method of a small and medium-sized vertical take-off and landing fixed-wing unmanned aerial vehicle and a multi-rotor unmanned aerial vehicle in an airport airspace based on a graph theory.
Disclosure of Invention
Aiming at the defects of the background technology, the invention provides a method for controlling the airport airspace flow of a small and medium-sized vertical take-off and landing unmanned aerial vehicle, which has the advantages of route planning and safe travel and solves the problems provided by the background technology.
The invention provides the following technical scheme: a flow control method for an airport airspace of a small and medium-sized vertical take-off and landing unmanned aerial vehicle is divided into the following six parts: s1Unmanned aerial vehicle model design, S2Airport aeronautical road chart model design, S3Method design and S for planning air route4Flight delay strategy, S5Airport route map updating method design and S6And (4) emergency landing. (ii) a
S1And designing an unmanned aerial vehicle model, wherein the unmanned aerial vehicle model is a particle model. When unmanned aerial vehicle safety flight, can regard as a particle with each unmanned aerial vehicle, then unmanned aerial vehicle particle model is:
Figure BDA0002222235150000021
wherein li>0,pU,iIndicate the ith unmanned planePosition of (v)iIndicating the speed, v, of the ith droned,iRepresenting the desired speed of the ith drone.
S2Designing an airport rout graph model, wherein the airport rout graph model adopts a graph theory model, the airport rout graph model is represented by an undirected graph gamma (N, E), all airport nodes are represented by N, and the number of the airport nodes is NN
Figure BDA0002222235150000022
For a positive integer set, the Γ node of the graph may be enumerated as:
Figure BDA0002222235150000023
and E denotes all the routes of the airport, and
Figure BDA0002222235150000024
the number of airport flight segments is nEThen, the Γ -shaped navigation segment may be enumerated as:
Figure BDA0002222235150000025
any leg can be represented by its two side nodes as:
E(j)={N(j)s,N(j)e}∈E,N(j)s,N(j)e∈N
let the airport aeronautical road map theoretical model be gamma, then obtain gamma middle aeronautical road map as follows:
(1) acquiring coordinates of all airport nodes, and setting nNA node
Figure BDA0002222235150000026
The node with the number i is N (i) and the coordinate is
Figure BDA0002222235150000027
(2) Obtaining a adjacency matrix A of gamma, A being nNThe order symmetric square matrix has the following values:
Figure BDA0002222235150000028
(3) calculating to obtain an adjacency matrix G with distance weight according to the communication relation between the node coordinate position and the node by taking the distance as the weight of the airport route mapAThe values are as follows:
Figure BDA0002222235150000031
the matrix comprises the relative positions and the communication relation among all the nodes, and the flow control of the airport area can be realized by calculating the matrix.
S3The method comprises designing route planning method, wherein the route of unmanned aerial vehicle is composed of edges in undirected graph gamma, and unmanned aerial vehicle U is arrangedkDenoted as E in the ith leg of the flightk(i) Then the route is represented in the form of a leg in graph Γ as follows:
RE,k=[Ek(1),Ek(2),...,Ek(nr)] (6)
wherein n isrIndicating the number of edges in the course, for successive legs Ek(1),Ek(2) The starting point of the front navigation section is the terminal point of the rear navigation section, and the heading direction of the unmanned aerial vehicle is arranged to enable the navigation section Ek(j) Front is flight section Ek(j+1),Ek(j) Starting point of (2) is Ns(Ek(j) Endpoint is N)e(Ek(j) Then, then
Ne(Ek(j))=Ns(Ek(j+1)) (7)
Wherein the content of the first and second substances,
Figure BDA0002222235150000032
let U be represented by node numberkThe route is RN,k
Figure BDA0002222235150000033
When planning approach, the entrance n (i) is used as the starting point (n (i) in fig. 1)N (4)), calculating the shortest approach paths from the entrance N (i) to all the air aprons N (j) in the undirected graph gamma one by using Dijkstra algorithm according to the terminal points of the air aprons N (j) (the number of the air aprons is 21-26), and taking the shortest approach path as RN,kThat is, the approach path is the shortest one of the shortest paths from the entrance to each air park, and when no unmanned aerial vehicle exists in the airport, the U is used1Approach path RN,1=[N(4),N(1),N(5)],U2Approach path RN,2=[N(4),N(7),N(10)];
Similar to the approach, the departure route planning takes the current apron node N (i) as the starting point and the airport exit N (j) as the end point (N (j) ═ N (15)), and the departure path R can be directly calculated by the Dijkstra algorithmN,k
S4Flight delay strategy, set UkThe time for receiving the approach and departure instruction is ts,kAnd planning a path for the unmanned aerial vehicle at the time point, if no available path exists, taking off and landing are delayed, and U is adoptedkWaiting at the current position, planning the route again after a period of time until the route is available, and setting UkTotal delay at the present moment is Td,kEach time delay is increased by time tstep,kAnd respectively calculating the unmanned aerial vehicles entering the field and the unmanned aerial vehicles leaving the field by adopting a delay strategy from the beginning to the completion of the air route planning process, namely the delay calculation between the unmanned aerial vehicles entering the field and the unmanned aerial vehicles leaving the field is not influenced mutually.
S5The airport route map updating method is designed, the airport route map updating method interrupts or recovers a part of the route section in the airport according to the information of the flight state, the real-time position and the like of the unmanned aerial vehicle, and the route map GAThe updating is carried out to ensure the flight safety of the unmanned aerial vehicle in the airport area, improve the entering and leaving efficiency of the unmanned aerial vehicle on the premise of ensuring the safety and improve the airport capacity, and the rest airport route graph is G after the interrupted route is removed at the current momentA,rThe updating of the airport route map is essentially to GA,rThe value of the unmanned aerial vehicle is continuously reset to zero and restored to the original value, and only one unmanned aerial vehicle can fly in the same flight segment at any time in order to ensure the flight safety of the unmanned aerial vehicle;
if G isA(i, j) ═ 0, tableWhen updating the route, no new route is generated between N (i) and N (j) corresponding to A (i, j) ═ 0, and the route updating only means to change the original route;
unmanned plane UkHas a real-time position of pU,kAt a current speed vkIn order to ensure flight safety and prevent the common nodes from existing in the front route of the unmanned aerial vehicle flying at the same time, the route sections around all the nodes in the route are interrupted after the route is planned; when the unmanned aerial vehicle passes through a node, recovering a part of route around the node except a flight front section;
setting a flag bit matrix GFRecording the number of times the flight segment is interrupted, and GFTogether with the adjacency matrix A, determining whether each leg can be interrupted or resumed, GFInitial values of A, GFIf (i, j) ═ 1 indicates that the route between the nodes i and j is through, otherwise, the route does not exist or is interrupted, and during the whole airport operation process, when G is usedFWhen certain conditions are satisfied, for GA,rUpdating is carried out, the condition is as follows, after the unmanned aerial vehicle plans the effective route, if GF(i, j) is less than or equal to 0 and an original path exists (A (i, j) ═ 1), the path is interrupted, and only G needs to be enabledF(i,j)=GF(i, j) -1; otherwise, the situation that no air route exists between the two points originally and the processing is not needed is shown, and when the unmanned aerial vehicle flies over one air point, if the G corresponding to the segment taking the node as the end point is used, the G corresponding to the segment takes the node as the end pointFIf (i, j) is 0 and there is an original route, then the route is restored and G is set toF(i, j) ═ 1; if G isF(i, j) < 0 and the original existence of the route, only need to make GF(i,j)=GF(i, j) +1, where recovery of the leg between the two points is not allowed. Note GFFor symmetric matrix, in updating GF(i, j) requires a synchronous update GF(j,i);
In order to prevent the unmanned aerial vehicle from passing through a waypoint above the apron on which the unmanned aerial vehicle has been parked, the apron area needs to be specially treated.
The method comprises the following steps of updating an approach unmanned aerial vehicle airway chart:
(1) unmanned plane UkApproach route RN,k=[N(i1),N(i2),...,N(ir)]Then, then
Figure BDA0002222235150000051
GA,rSymmetrical about GA,r(in,im) Modified together with GFUpdating, planning effective route, and adding RN,kThe segment with the middle node as the end point is interrupted;
(2) when the unmanned aerial vehicle flies to the front of the parking apron area and passes through one node, all the surrounding flight sections with the node as an end point are recovered, and the unmanned aerial vehicle passes through N (i)a) Time of flight
Figure BDA0002222235150000052
GA,rThe variation expression is as follows:
Figure BDA0002222235150000053
in the same way, GA,r(in,ia) Together modify and pair GFAnd (6) updating. Note that the restored route does not include N (i)a) To the leg between the next waypoint.
(3) When the unmanned aerial vehicle arrives at the parking apron area, in order to prevent the subsequent unmanned aerial vehicle from entering the occupied parking apron, the unmanned aerial vehicle is regulated to arrive at a parking apron node N (i)r-1) And N (i)r) The method does not recover the surrounding air routes, does not change the zone bit of the air section of the apron area, and always keeps the state of the interruption of the air routes of the apron area in the process that the unmanned aerial vehicle enters the airport and leaves the apron until the unmanned aerial vehicle takes off, and does not recover until the unmanned aerial vehicle takes off, and the updating of the off-site air route map is similar to that in the process of entering the airport. Before planning an off-site route, the route of the apron area where the unmanned aerial vehicle is located needs to be recovered, otherwise, an available route cannot be planned. If the planned route is invalid, all the flight sections of the apron area need to be interrupted again, and the planned route is recovered again when the next departure time point is reached. The update process needs to conform to GFAnd (6) updating. Updating the navigation chart and entering step (1) and (2)The same, but may fly away from the egress node all the time at step (2).
S6Emergency landing, the design of the unmanned aerial vehicle emergency route is as follows:
(1) the unmanned aerial vehicle which is in emergency landing enters from different entrances with other unmanned aerial vehicles, and the emergency entrance can be above the original entrance;
(2) adding a navigation point above all the parking aprons, wherein the navigation point is higher than the navigation point above the original parking aprons and is as high as the emergency entrance;
(3) the unmanned aerial vehicle enters from the emergency entrance, directly flies to a navigation point above the parking apron which is closest to the unmanned aerial vehicle and then lands;
(4) if the included angle of the direct route from the emergency entrance to the upper part of different parking aprons is extremely small, combining partial routes, namely, when the unmanned aerial vehicle needs to fly to the farther parking apron, the unmanned aerial vehicle firstly passes through the node above the closer parking apron;
with EkTo represent unmanned plane UkWhether an emergency landing is required, EkIndicates that the drone is flying normally when being 0, EkIndicate that the unmanned aerial vehicle needs emergency landing 1. The unmanned aerial vehicle for emergency landing has a route planning mode basically the same as that of the unmanned aerial vehicle for normal landing. However, the included angle between the multiple air routes may be small, the shortest distance from the unmanned aerial vehicle flying on one air route to the rest air routes in a short time after the approach may be smaller than the safe distance, and danger may be caused if other unmanned aerial vehicles are in emergency landing at the approaching moment. In order to ensure the flight safety of the unmanned aerial vehicle, all the emergency routes are interrupted for the subsequent unmanned aerial vehicle after the unmanned aerial vehicle enters the field until the unmanned aerial vehicle flies out for a certain distance and then the routes are recovered. In actual conditions, the density of the unmanned aerial vehicle which is in emergency landing is lower, and the delay time t increased every timestep,kBy using a fixed value
The invention has the following beneficial effects:
according to the airport airspace flow control method for the small and medium-sized vertical take-off and landing unmanned aerial vehicles, the residual air paths of the airport are adjusted in real time by using the graph theory method through the airport airspace flow control method for the small and medium-sized vertical take-off and landing fixed-wing unmanned aerial vehicles and multi-rotor unmanned aerial vehicles in the graph theory, so that the flight safety of the unmanned aerial vehicles in the airport airspace can be ensured, the aim of controlling the flow of the unmanned aerial vehicles in the airport area can be well fulfilled, and a safe and efficient. The method meets the requirement of airport area flow control under the actual condition. The algorithm has the advantages of small calculation amount, high robustness and good universality, and is suitable for similar airports.
Drawings
FIG. 1 is an airport route model;
FIG. 2 is an approach shortest path graph;
fig. 3 is a flow chart of unmanned aerial vehicle entering and leaving delay;
fig. 4 is a flow chart of determining the single delay time length of the unmanned aerial vehicle;
FIG. 5 is a schematic illustration of the remaining routes;
FIG. 6 is a flowchart of an update of an approach roadmap;
FIG. 7 is an off-site roadmap update flow chart;
FIG. 8 is an airport route model with the addition of an emergency landing route.
Detailed Description
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. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-8, a flow control method for an airport airspace of a small and medium sized vertical take-off and landing unmanned aerial vehicle is divided into the following six parts: s1Unmanned aerial vehicle model design, S2Airport aeronautical road chart model design, S3Method design and S for planning air route4Flight delay strategy, S5Airport route map updating method design and S6Emergency landing;
S1unmanned aerial vehicle model design, unmanned aerial vehicle model are the particle model, when unmanned aerial vehicle safety flight, can regard each unmanned aerial vehicle as a particle, then unmanned aerial vehicle particle model is:
Figure BDA0002222235150000081
wherein li>0,pU,iIndicating the position of the ith drone, viIndicating the speed, v, of the ith droned,iRepresenting the desired speed of the ith drone.
S2Designing an airport rout graph model, wherein the airport rout graph model adopts a graph theory model, the airport rout graph model is represented by an undirected graph gamma (N, E), all airport nodes are represented by N, and the number of the airport nodes is NN
Figure BDA0002222235150000082
For a positive integer set, the Γ node of the graph may be enumerated as:
and E denotes all the routes of the airport, and
Figure BDA0002222235150000084
the number of airport flight segments is nEThen, the Γ -shaped navigation segment may be enumerated as:
Figure BDA0002222235150000085
any leg can be represented by its two side nodes as:
E(j)={N(j)s,N(j)e}∈E,N(j)s,N(j)e∈N
let the airport aeronautical road map theoretical model be gamma, then obtain gamma middle aeronautical road map as follows:
(1) acquiring coordinates of all airport nodes, and setting nNA node
Figure BDA0002222235150000086
The node with the number i is N (i) and the coordinate is
(2) Obtaining a adjacency matrix A of gamma, A being nNThe order symmetric square matrix has the following values:
Figure BDA0002222235150000088
(3) calculating to obtain an adjacency matrix G with distance weight according to the communication relation between the node coordinate position and the node by taking the distance as the weight of the airport route mapAThe values are as follows:
Figure BDA0002222235150000089
the matrix comprises the relative positions and the communication relation among all the nodes, and the flow control of the airport area can be realized by calculating the matrix.
S3The method comprises designing route planning method, wherein the route of unmanned aerial vehicle is composed of edges in undirected graph gamma, and unmanned aerial vehicle U is arrangedkDenoted as E in the ith leg of the flightk(i) Then the route is represented in the form of a leg in graph Γ as follows:
RE,k=[Ek(1),Ek(2),...,Ek(nr)] (6)
wherein n isrIndicating the number of edges in the course, for successive legs Ek(1),Ek(2) The starting point of the front navigation section is the terminal point of the rear navigation section, and the heading direction of the unmanned aerial vehicle is arranged to enable the navigation section Ek(j) Front is flight section Ek(j+1),Ek(j) Starting point of (2) is Ns(Ek(j) Endpoint is N)e(Ek(j) Then, then
Ne(Ek(j))=Ns(Ek(j+1)) (7)
Wherein the content of the first and second substances,
Figure BDA0002222235150000091
let U be represented by node numberkThe route is RN,k
When planning approach, the shortest approach path from the entrance N (i) to any apron N (j) in the undirected graph F is calculated one by using Dijkstra algorithm with the entrance N (i) as a starting point (N (i) ═ N (4) in FIG. 1) and the number of each apron node N (j) as an end point (21-26), and the shortest one is taken as RN,kThat is, the approach path is the shortest one of the shortest paths from the entrance to each air park, and when no unmanned aerial vehicle exists in the airport, the U is used1Approach path RN,1=[N(4),N(1),N(5)],U2Approach path RN,2=[N(4),N(7),N(10)];
Similar to the approach, the departure route planning takes the current apron node N (i) as the starting point and the airport exit N (j) as the end point (N (j) ═ N (15)), and the departure path R can be directly calculated by the Dijkstra algorithmN,k
S4Flight delay strategy, set UkThe time for receiving the approach and departure instruction is ts,kAnd planning a path for the unmanned aerial vehicle at the time point, if no available path exists, taking off and landing are delayed, and U is adoptedkWaiting at the current position, planning the route again after a period of time until the route is available, and setting UkTotal delay at the present moment is Td,kEach time delay is increased by time tstep,kFrom the beginning of waiting to the completion of the route planning process, the unmanned aerial vehicles entering the field and leaving the field are separately calculated by adopting a delay strategy, namely, the delay calculation between the unmanned aerial vehicles entering the field and leaving the field is not influenced by each other;
the design delay strategy has two purposes: when the unmanned aerial vehicle enters the field, the rear unmanned aerial vehicle surpasses the unmanned aerial vehicle waiting in front; the unmanned aerial vehicle waiting for the longest time can enter or leave the field as early as possible. The purpose is realized by changing the time delay t of the unmanned aerial vehicle every timestep,kTo achieve this, a smaller t is setstep1A larger tstep2Let t bestep2≥2×tstep1When there are many unmanned aerial vehicles delayed, the unmanned aerial vehicle with the longest delay time adopts tstep1As tstep,kOther unmanned aerial vehicles adopt tstep2The number of unmanned aerial vehicles which are set at the time of approach delay or departure delay is nU,dAnd the number of all unmanned aerial vehicles in the airport is nU,ttl. Accessible judgment U for whether unmanned aerial vehicle is in-range delay or out-of-range delaykReal-time location of
Figure BDA0002222235150000101
And (6) obtaining. Judge unmanned aerial vehicle tstep,kThe strategy of (2) is shown in fig. 4.
As can be seen from FIG. 3, the delay time returns to zero after the unmanned aerial vehicle plans to go out of the flight line, so if T is reachedd,k>0,UkIn a delayed state. T can then be specified according to the number of drones in the delayed state and their waiting timestep,kThe value of (c).
S5The airport route map updating method is designed, the airport route map updating method interrupts or recovers a part of the route section in the airport according to the information of the flight state, the real-time position and the like of the unmanned aerial vehicle, and the route map GAThe updating is carried out to ensure the flight safety of the unmanned aerial vehicle in the airport area, improve the entering and leaving efficiency of the unmanned aerial vehicle on the premise of ensuring the safety and improve the airport capacity, and the rest airport route graph is G after the interrupted route is removed at the current momentA,rThe updating of the airport route map is essentially to GA,rThe value of the unmanned aerial vehicle is continuously reset to zero and restored to the original value, and only one unmanned aerial vehicle can fly in the same flight segment at any time in order to ensure the flight safety of the unmanned aerial vehicle;
if G isA(i, j) ═ 0, which indicates that no route exists between the waypoints n (i) and n (j), and when updating the route, no new route is generated between n (i) and n (j) corresponding to a (i, j) ═ 0, and the route is updated only by changing the original route;
unmanned plane UkHas a real-time position of pU,kAt a current speed vkIn order to ensure flight safety and prevent the common nodes from existing in the front route of the unmanned aerial vehicle flying at the same time, the route sections around all the nodes in the route are interrupted after the route is planned; when the unmanned aerial vehicle passes through one node every time, the node cycle is recoveredEnclose partial air route, except flight the place ahead flight segment, but carry out the navigation route map according to above-mentioned method and update, when many unmanned aerial vehicles fly in the airport, probably partial flight segment is interrupted by repetition, if do not handle, arbitrary unmanned aerial vehicle can resume this air route after the endpoint node of this flight segment. But at this time, the route may not be recovered, and the potential safety hazard still exists.
Setting a flag bit matrix GFRecording the number of times the flight segment is interrupted, and GFTogether with the adjacency matrix A, determining whether each leg can be interrupted or resumed, GFInitial values of A, GFIf (i, j) ═ 1 indicates that the route between the nodes i and j is through, otherwise, the route does not exist or is interrupted, and during the whole airport operation process, when G is usedFWhen certain conditions are satisfied, for GA,rUpdating is carried out, the condition is as follows, after the unmanned aerial vehicle plans the effective route, if GF(i, j) is less than or equal to 0 and an original path exists (A (i, j) ═ 1), the path is interrupted, and only G needs to be enabledF(i,j)=GF(i, j) -1; otherwise, the situation that no air route exists between the two points originally and the processing is not needed is shown, and when the unmanned aerial vehicle flies over one air point, if the G corresponding to the segment taking the node as the end point is used, the G corresponding to the segment takes the node as the end pointFIf (i, j) is 0 and there is an original route, then the route is restored and G is set toF(i, j) ═ 1; if G isF(i, j) < 0 and the original existence of the route, only need to make GF(i,j)=GF(i, j) +1, where recovery of the leg between the two points is not allowed. Note GFFor symmetric matrix, in updating GF(i, j) requires a synchronous update GF(j,i);
In order to prevent the unmanned aerial vehicle from passing through a waypoint above the apron on which the unmanned aerial vehicle has been parked, the apron area needs to be specially treated.
The method comprises the following steps of updating an approach unmanned aerial vehicle airway chart:
(1) unmanned plane UkApproach route RN,k=[N(i1),N(i2),...,N(ir)]Then, then
Figure BDA0002222235150000111
GA,rSymmetrical about GA,r(in,im) Modified together with GFUpdating, planning effective route, and adding RN,kThe segment with the middle node as the end point is interrupted;
(2) when the unmanned aerial vehicle flies to the front of the parking apron area and passes through one node, all the surrounding flight sections with the node as an end point are recovered, and the unmanned aerial vehicle passes through N (i)a) Time of flight
Figure BDA0002222235150000112
GA,rThe variation expression is as follows:
Figure BDA0002222235150000121
in the same way, GA,r(in,ia) Together modify and pair GFAnd (6) updating. Note that the restored route does not include N (i)a) To the leg between the next waypoint.
(3) When the unmanned aerial vehicle arrives at the parking apron area, in order to prevent the subsequent unmanned aerial vehicle from entering the occupied parking apron, the unmanned aerial vehicle is regulated to arrive at a parking apron node N (i)r-1) And N (i)r) The method does not recover the surrounding air routes, does not change the zone bit of the air section of the apron area, and always keeps the state of the interruption of the air routes of the apron area in the process that the unmanned aerial vehicle enters the airport and leaves the apron until the unmanned aerial vehicle takes off, and does not recover until the unmanned aerial vehicle takes off, and the updating of the off-site air route map is similar to that in the process of entering the airport. Before planning an off-site route, the route of the apron area where the unmanned aerial vehicle is located needs to be recovered, otherwise, an available route cannot be planned. If the planned route is invalid, all the flight sections of the apron area need to be interrupted again, and the planned route is recovered again when the next departure time point is reached. The update process needs to be updated in compliance with GF. The step of updating the routing map is the same as the steps (1) and (2) in the approach, but the routing map can always fly away from the exit node in the step (2).
S6 emergency landing, the design of the unmanned aerial vehicle emergency route is as follows: a drone in flight may need to land immediately with certain emergencies, and for the dispatch of such a drone the following principles need to be followed:
(1) the flight safety of the unmanned aerial vehicle is ensured;
(2) make unmanned aerial vehicle descend as soon as possible.
Therefore, for an unmanned aerial vehicle requiring emergency landing, the route thereof needs to be separated from the route of the unmanned aerial vehicle flying normally, and the unmanned aerial vehicle needs to fly to the apron area at the shortest distance;
(1) the unmanned aerial vehicle which is in emergency landing enters from different entrances with other unmanned aerial vehicles, and the emergency entrance can be above the original entrance;
(2) adding a navigation point above all the parking aprons, wherein the navigation point is higher than the navigation point above the original parking aprons and is as high as the emergency entrance;
(3) the unmanned aerial vehicle enters from the emergency entrance, directly flies to a navigation point above the parking apron which is closest to the unmanned aerial vehicle and then lands;
(4) if the included angle of the direct route from the emergency entrance to the upper part of different parking aprons is extremely small, combining partial routes, namely, when the unmanned aerial vehicle needs to fly to the farther parking apron, the unmanned aerial vehicle firstly passes through the node above the closer parking apron;
with EkTo represent unmanned plane UkWhether an emergency landing is required, EkIndicates that the drone is flying normally when being 0, EkIndicate that the unmanned aerial vehicle needs emergency landing 1. The unmanned aerial vehicle for emergency landing has a route planning mode basically the same as that of the unmanned aerial vehicle for normal landing. However, the included angle between the multiple air routes may be small, the shortest distance from the unmanned aerial vehicle flying on one air route to the rest air routes in a short time after the approach may be smaller than the safe distance, and danger may be caused if other unmanned aerial vehicles are in emergency landing at the approaching moment. In order to ensure the flight safety of the unmanned aerial vehicle, all the emergency routes are interrupted for the subsequent unmanned aerial vehicle after the unmanned aerial vehicle enters the field until the unmanned aerial vehicle flies out for a certain distance and then the routes are recovered. In actual conditions, the density of the unmanned aerial vehicle which is in emergency landing is lower, and the delay time t increased every timestep,kA fixed value may be used.
And acquiring the communication information between the coordinate position of the node in the airport and the node from the outside to generate an airport route map. Simulated airport routes as shown in FIG. 8, no airport at the initial moment of simulationAnd (4) man-machine. Obtaining unmanned aerial vehicle speed v from outsidekSelect entry information EkCalculating the time of entering and leaving the field of the unmanned aerial vehicle and calculating a zone bit matrix GFAnd simulating the flight of the unmanned aerial vehicle on the airport airway.
An entrance is required to be selected before the unmanned aerial vehicle enters the field: ekEntering from normal flight entrance N (4) when equal to 0, EkWhen the value is 1, the gas enters from an emergency entrance N (27). According to real time G upon arrival at the entranceA,rPlanning an air route by information, calculating the shortest landing route from an entrance to each air park by utilizing a Dijkstra algorithm, and selecting the shortest distance in each shortest route as the landing route R of the unmanned aerial vehicleE,k. If there is no valid route at the present time, the drone needs to wait for a period of time at the entrance, and then plan the route again until the route is valid, as shown in fig. 3. If there are many unmanned aerial vehicles delay waiting simultaneously, need to make the unmanned aerial vehicle of latency longest descend as early as possible, this unmanned aerial vehicle delay time that increases at every turn is less, and the delay time that all the other unmanned aerial vehicles increase at every turn is great, as shown in fig. 4. After the effective route is planned, the interruption meets GFConditional leg around route node, GA,rCorresponding to the position value of 0 and update GF
After the planning of the route is finished, the unmanned aerial vehicle follows RE,kUntil landing on the target apron. Influence of off-site factors is not considered during simulation, and the real-time position of the unmanned aerial vehicle can be estimated. In order to improve the passing efficiency of unmanned aerial vehicles at airports, UkEach time a waypoint is flown, divide the waypoint and RE,kIn the middle and next node, the requirement G is metFOther routes with the node as the end point of the condition are all recovered, GA,rRestoring the original value corresponding to the position data, and updating GF(ii) a To prevent UkSubsequent unmanned aerial vehicles pass through the nodes above the parking apron after landing, and the air routes taking the last two air points in the approach unmanned aerial vehicle route, namely the parking apron and the nodes above the parking apron as end points are specified not to recover the part of the route after the unmanned aerial vehicle passes through the nodes, as shown in figure 6, GFThe corresponding flag bit is not changed.
If the unmanned aerial vehicle needs emergency landing, the unmanned aerial vehicle enters the field from N (27), and emergency landing is plannedThe unmanned aerial vehicle can land on the shortest route under the condition of ensuring the safety of the unmanned aerial vehicle, and the route for emergency landing is shown in figure 8. U shapekWhen entering an airport, a position is on the side of a route starting from N (27) and close to N (27), and UkThe distance from the emergency air route to other emergency air routes is short, and potential safety hazards exist. In order to ensure the flight safety of the unmanned aerial vehicle, all emergency flight sections taking an emergency entrance as an end point are completely interrupted after the unmanned aerial vehicle enters a field, and all emergency flight paths are recovered after the unmanned aerial vehicle flies out for a certain distance. And under other conditions, updating the airway map is consistent with the normal landing of the unmanned aerial vehicle. Note that G is satisfied during interruption and resumption of the legFCondition and update G after the roadmap is updatedFAnd (4) matrix.
Before the unmanned aerial vehicle leaves the airport, the routes of the parking apron area are completely interrupted, and the available routes cannot be planned, so that the routes in the parking apron area meet GFIn terms of conditions, G needs to be restored and updated with course resources in the occupied apron area before planning the courseF. If the planned route is invalid, the part of route resources are required to be interrupted again after the route is planned, GA,rThe corresponding value is updated to 0 and G is updatedFAnd (4) matrix. If an invalid airway is planned, delayed takeoff is needed, and the delay strategy is the same as that of approach. After the effective route is planned, the updating method of the route map is basically the same as that of the route map during approach, and every time when a route node passes through, the condition that the periphery of the node meets G is recoveredFThe matrix condition of the way and no special treatment of several nodes at the end of the way is required, as shown in fig. 7.
The airport area can realize that many unmanned aerial vehicles advance simultaneously and leave the field, wherein, allows many unmanned aerial vehicles to advance simultaneously, nevertheless only allows to have an unmanned aerial vehicle to leave the field with the period. The safety performance of the flow control method can be evaluated through the shortest distance between unmanned aerial vehicles in an airport in the test simulation process, the delay time of the unmanned aerial vehicles is recorded through adjusting the approach interval of the unmanned aerial vehicles, the operation capacity [2] of the airport is obtained, namely the airport performance is evaluated through the maximum number of aircraft which can be served by an airspace system in unit time under the acceptable delay level.
Simulation results show that the method can realize the safe and ordered flight of the unmanned aerial vehicle in the airport airspace and better realize the flow control of the unmanned aerial vehicle in the airport area.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (1)

1. A flow control method for an airport airspace of a small and medium-sized vertical take-off and landing unmanned aerial vehicle is divided into the following six parts: s1Unmanned aerial vehicle model design, S2Airport aeronautical road chart model design, S3Method design and S for planning air route4Flight delay strategy, S5Airport route map updating method design and S6Emergency landing;
S1unmanned aerial vehicle model design, unmanned aerial vehicle model are the particle model, when unmanned aerial vehicle safety flight, can regard each unmanned aerial vehicle as a particle, then unmanned aerial vehicle particle model is:
Figure FDA0002222235140000011
wherein li>0,pU,iIndicating the position of the ith drone, viRepresenting the ith unmanned planeVelocity, vd,iRepresenting the desired speed of the ith drone.
S2Designing an airport rout graph model, wherein the airport rout graph model adopts a graph theory model, the airport rout graph model is represented by an undirected graph gamma (N, E), all airport nodes are represented by N, and the number of the airport nodes is NN
Figure FDA0002222235140000012
For a positive integer set, the Γ node of the graph may be enumerated as:
Figure FDA0002222235140000013
and E denotes all the routes of the airport, and
Figure FDA0002222235140000014
the number of airport flight segments is nEThen, the Γ -shaped navigation segment may be enumerated as:
Figure FDA0002222235140000015
any leg can be represented by its two side nodes as:
E(j)={N(j)s,N(j)e}∈E,N(j)s,N(j)e∈N
let the airport aeronautical road map theoretical model be gamma, then obtain gamma middle aeronautical road map as follows:
(1) acquiring coordinates of all airport nodes, and setting nNA node
Figure FDA0002222235140000016
The node with the number i is N (i) and the coordinate is
Figure FDA0002222235140000017
(2) Obtaining a adjacency matrix A of gamma, A being nNThe order symmetric square matrix has the following values:
Figure FDA0002222235140000018
(3) calculating to obtain an adjacency matrix G with distance weight according to the communication relation between the node coordinate position and the node by taking the distance as the weight of the airport route mapAThe values are as follows:
Figure FDA0002222235140000021
the matrix comprises the relative positions and the communication relation among all the nodes, and the flow control of the airport area can be realized by calculating the matrix.
S3The method comprises designing route planning method, wherein the route of unmanned aerial vehicle is composed of edges in undirected graph gamma, and unmanned aerial vehicle U is arrangedkDenoted as E in the ith leg of the flightk(i) Then the route is represented in the form of a leg in graph Γ as follows:
RE,k=[Ek(1),Ek(2),...,Ek(nr)] (6)
wherein n isrIndicating the number of edges in the course, for successive legs Ek(1),Ek(2) The starting point of the front navigation section is the terminal point of the rear navigation section, and the heading direction of the unmanned aerial vehicle is arranged to enable the navigation section Ek(j) Front is flight section Ek(j+1),Ek(j) Starting point of (2) is Ns(Ek(j) Endpoint is N)e(Ek(j) Then, then
Ne(Ek(j))=Ns(Ek(j+1)) (7)
Wherein the content of the first and second substances,
Figure FDA0002222235140000022
let U be represented by node numberkThe route is RN,k
Figure FDA0002222235140000023
When planning approach, the shortest approach path from the entrance N (i) to any apron N (j) in the undirected graph F is calculated one by using Dijkstra algorithm with the entrance N (i) as a starting point (N (i) ═ N (4) in FIG. 1) and the number of each apron node N (j) as an end point (21-26), and the shortest one is taken as RN,kThat is, the approach path is the shortest one of the shortest paths from the entrance to each air park, and when no unmanned aerial vehicle exists in the airport, the U is used1Approach path RN,1=[N(4),N(1),N(5)],U2Approach path RN,2=[N(4),N(7),N(10)];
Similar to the approach, the departure route planning takes the current apron node N (i) as the starting point and the airport exit N (j) as the end point (N (j) ═ N (15)), and the departure path R can be directly calculated by the Dijkstra algorithmN,k
S4Flight delay strategy, set UkThe time for receiving the approach and departure instruction is ts,kAnd planning a path for the unmanned aerial vehicle at the time point, if no available path exists, taking off and landing are delayed, and U is adoptedkWaiting at the current position, planning the route again after a period of time until the route is available, and setting UkTotal delay at the present moment is Td,kEach time delay is increased by time tstep,kAnd respectively calculating the unmanned aerial vehicles entering the field and the unmanned aerial vehicles leaving the field by adopting a delay strategy from the beginning to the completion of the air route planning process, namely the delay calculation between the unmanned aerial vehicles entering the field and the unmanned aerial vehicles leaving the field is not influenced mutually.
S5The airport route map updating method is designed, the airport route map updating method interrupts or recovers a part of the route section in the airport according to the information of the flight state, the real-time position and the like of the unmanned aerial vehicle, and the route map GAThe updating is carried out to ensure the flight safety of the unmanned aerial vehicle in the airport area, improve the entering and leaving efficiency of the unmanned aerial vehicle on the premise of ensuring the safety and improve the airport capacity, and the rest airport route graph is G after the interrupted route is removed at the current momentA,rThe updating of the airport route map is essentially to GA,rThe value of (2) continuously returns to zero and restores the original value, and in order to ensure the flight safety of the unmanned aerial vehicle, only one unmanned aerial vehicle can fly in the same flight segment at any moment;
If G isA(i, j) ═ 0, which indicates that no route exists between the waypoints n (i) and n (j), and when updating the route, no new route is generated between n (i) and n (j) corresponding to a (i, j) ═ 0, and the route is updated only by changing the original route;
unmanned plane UkHas a real-time position of pU,kAt a current speed vkIn order to ensure flight safety and prevent the common nodes from existing in the front route of the unmanned aerial vehicle flying at the same time, the route sections around all the nodes in the route are interrupted after the route is planned; when the unmanned aerial vehicle passes through a node, recovering a part of route around the node except a flight front section;
setting a flag bit matrix GFRecording the number of times the flight segment is interrupted, and GFTogether with the adjacency matrix A, determining whether each leg can be interrupted or resumed, GFInitial values of A, GFIf (i, j) ═ 1 indicates that the route between the nodes i and j is through, otherwise, the route does not exist or is interrupted, and during the whole airport operation process, when G is usedFWhen certain conditions are satisfied, for GA,rUpdating is carried out, the condition is as follows, after the unmanned aerial vehicle plans the effective route, if GF(i, j) is less than or equal to 0 and an original path exists (A (i, j) ═ 1), the path is interrupted, and only G needs to be enabledF(i,j)=GF(i, j) -1; otherwise, the situation that no air route exists between the two points originally and the processing is not needed is shown, and when the unmanned aerial vehicle flies over one air point, if the G corresponding to the segment taking the node as the end point is used, the G corresponding to the segment takes the node as the end pointFIf (i, j) is 0 and there is an original route, then the route is restored and G is set toF(i, j) ═ 1; if G isF(i, j) < 0 and the original existence of the route, only need to make GF(i,j)=GF(i, j) +1, where recovery of the leg between the two points is not allowed. Note GFFor symmetric matrix, in updating GF(i, j) requires a synchronous update GF(j,i);
In order to prevent the unmanned aerial vehicle from passing through a waypoint above the apron on which the unmanned aerial vehicle has been parked, the apron area needs to be specially treated.
The method comprises the following steps of updating an approach unmanned aerial vehicle airway chart:
(1) unmanned plane UkApproach route RN,k=[N(i1),N(i2),...,N(ir)]Then, then
Figure FDA0002222235140000041
GA,rSymmetrical about GA,r(in,im) Modified together with GFUpdating, planning effective route, and adding RN,kThe segment with the middle node as the end point is interrupted;
(2) when the unmanned aerial vehicle flies to the front of the parking apron area and passes through one node, all the surrounding flight sections with the node as an end point are recovered, and the unmanned aerial vehicle passes through N (i)a) Time of flight
Figure FDA0002222235140000042
GA,rThe variation expression is as follows:
Figure FDA0002222235140000043
in the same way, GA,r(in,ia) Together modify and pair GFAnd (6) updating. Note that the restored route does not include N (i)a) To the leg between the next waypoint.
(3) When the unmanned aerial vehicle arrives at the parking apron area, in order to prevent the subsequent unmanned aerial vehicle from entering the occupied parking apron, the unmanned aerial vehicle is regulated to arrive at a parking apron node N (i)r-1) And N (i)r) The method does not recover the surrounding air routes, does not change the zone bit of the air section of the apron area, and always keeps the state of the interruption of the air routes of the apron area in the process that the unmanned aerial vehicle enters the airport and leaves the apron until the unmanned aerial vehicle takes off, and does not recover until the unmanned aerial vehicle takes off, and the updating of the off-site air route map is similar to that in the process of entering the airport. Before planning an off-site route, the route of the apron area where the unmanned aerial vehicle is located needs to be recovered, otherwise, an available route cannot be planned. If the planned route is invalid, all the flight sections of the apron area need to be interrupted again, and the planned route is recovered again when the next departure time point is reached. Has been updatedProgram requirement conforms to GFAnd (6) updating. The step of updating the routing map is the same as the steps (1) and (2) in the approach, but the routing map can always fly away from the exit node in the step (2).
S6Emergency landing, the design of the unmanned aerial vehicle emergency route is as follows:
(1) the unmanned aerial vehicle which is in emergency landing enters from different entrances with other unmanned aerial vehicles, and the emergency entrance can be above the original entrance;
(2) adding a navigation point above all the parking aprons, wherein the navigation point is higher than the navigation point above the original parking aprons and is as high as the emergency entrance;
(3) the unmanned aerial vehicle enters from the emergency entrance, directly flies to a navigation point above the parking apron which is closest to the unmanned aerial vehicle and then lands;
(4) if the included angle of the direct route from the emergency entrance to the upper part of different parking aprons is extremely small, combining partial routes, namely, when the unmanned aerial vehicle needs to fly to the farther parking apron, the unmanned aerial vehicle firstly passes through the node above the closer parking apron;
with EkTo represent unmanned plane UkWhether an emergency landing is required, EkIndicates that the drone is flying normally when being 0, EkIndicate that the unmanned aerial vehicle needs emergency landing 1. The unmanned aerial vehicle for emergency landing has a route planning mode basically the same as that of the unmanned aerial vehicle for normal landing. However, the included angle between the multiple air routes may be small, the shortest distance from the unmanned aerial vehicle flying on one air route to the rest air routes in a short time after the approach may be smaller than the safe distance, and danger may be caused if other unmanned aerial vehicles are in emergency landing at the approaching moment. In order to ensure the flight safety of the unmanned aerial vehicle, all the emergency routes are interrupted for the subsequent unmanned aerial vehicle after the unmanned aerial vehicle enters the field until the unmanned aerial vehicle flies out for a certain distance and then the routes are recovered. In actual conditions, the density of the unmanned aerial vehicle which is in emergency landing is lower, and the delay time t increased every timestep,kA fixed value may be used.
CN201910938492.1A 2019-09-30 2019-09-30 Airport airspace flow control method for small and medium-sized vertical take-off and landing unmanned aerial vehicle Active CN110634332B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910938492.1A CN110634332B (en) 2019-09-30 2019-09-30 Airport airspace flow control method for small and medium-sized vertical take-off and landing unmanned aerial vehicle

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910938492.1A CN110634332B (en) 2019-09-30 2019-09-30 Airport airspace flow control method for small and medium-sized vertical take-off and landing unmanned aerial vehicle

Publications (2)

Publication Number Publication Date
CN110634332A true CN110634332A (en) 2019-12-31
CN110634332B CN110634332B (en) 2021-11-23

Family

ID=68973811

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910938492.1A Active CN110634332B (en) 2019-09-30 2019-09-30 Airport airspace flow control method for small and medium-sized vertical take-off and landing unmanned aerial vehicle

Country Status (1)

Country Link
CN (1) CN110634332B (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111477035A (en) * 2020-04-03 2020-07-31 飞牛智能科技(南京)有限公司 Low-altitude navigation network geometric structure generation method oriented to safety distance constraint
CN116151590A (en) * 2023-04-07 2023-05-23 中国民用航空飞行学院 Modularized unmanned aerial vehicle airport planning method for urban air traffic

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6282488B1 (en) * 1996-02-29 2001-08-28 Siemens Aktiengesellschaft Airport surface movement guidance and control system
CN101950493A (en) * 2010-09-10 2011-01-19 四川大学 Flow scheduling method of regional air traffic network
CN102222412A (en) * 2011-05-26 2011-10-19 北京航空航天大学 Method for optimizing layout of convergent points of air routes by introducing airspace capacity
CN103366605A (en) * 2013-07-23 2013-10-23 天津天航创力科技有限公司 Terminal section partition method based on graph theory and genetic algorithm
US20170263137A1 (en) * 2016-03-14 2017-09-14 Thales Method and system for managing a multi-destination flight plan
US20190012922A1 (en) * 2016-12-23 2019-01-10 Telefonaktiebolaget Lm Ericsson (Publ) Unmanned aerial vehicle in controlled airspace
CN109215399A (en) * 2018-11-07 2019-01-15 中国电子科技集团公司第二十八研究所 A kind of termination environment intelligence stream interface driver generation method
US20190096269A1 (en) * 2017-09-22 2019-03-28 Vianair Inc. Terminal and en-route airspace operations based on dynamic routes

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6282488B1 (en) * 1996-02-29 2001-08-28 Siemens Aktiengesellschaft Airport surface movement guidance and control system
CN101950493A (en) * 2010-09-10 2011-01-19 四川大学 Flow scheduling method of regional air traffic network
CN102222412A (en) * 2011-05-26 2011-10-19 北京航空航天大学 Method for optimizing layout of convergent points of air routes by introducing airspace capacity
CN103366605A (en) * 2013-07-23 2013-10-23 天津天航创力科技有限公司 Terminal section partition method based on graph theory and genetic algorithm
US20170263137A1 (en) * 2016-03-14 2017-09-14 Thales Method and system for managing a multi-destination flight plan
US20190012922A1 (en) * 2016-12-23 2019-01-10 Telefonaktiebolaget Lm Ericsson (Publ) Unmanned aerial vehicle in controlled airspace
US20190096269A1 (en) * 2017-09-22 2019-03-28 Vianair Inc. Terminal and en-route airspace operations based on dynamic routes
CN109215399A (en) * 2018-11-07 2019-01-15 中国电子科技集团公司第二十八研究所 A kind of termination environment intelligence stream interface driver generation method

Non-Patent Citations (7)

* Cited by examiner, † Cited by third party
Title
QUAN Q: "ntroduction to multicopter design and control", 《BERLIN: SPRINGER》 *
何寿昌: "基于图论的飞机飞行控制系统故障诊断方法研究", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 *
周雄飞,胡明华: "空域容量评估研究综述", 《中国民航飞行学院学报》 *
姚飞: "基于DSO的航路网络的飞行流量分配研究", 《滨州学院学报》 *
彭瑛: "空中交通流量统计、预测系统及容量评估问题研究", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 *
曹希: "基于复杂网络理论的航路网络生成及优化", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 *
杜光勋,全权: "考虑惯性积时多旋翼的可控性分析与度量方法", 《系统工程与电子技术》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111477035A (en) * 2020-04-03 2020-07-31 飞牛智能科技(南京)有限公司 Low-altitude navigation network geometric structure generation method oriented to safety distance constraint
CN111477035B (en) * 2020-04-03 2021-05-28 飞牛智能科技(南京)有限公司 Low-altitude navigation network geometric structure generation method oriented to safety distance constraint
CN116151590A (en) * 2023-04-07 2023-05-23 中国民用航空飞行学院 Modularized unmanned aerial vehicle airport planning method for urban air traffic

Also Published As

Publication number Publication date
CN110634332B (en) 2021-11-23

Similar Documents

Publication Publication Date Title
Sunil et al. Metropolis: Relating airspace structure and capacity for extreme traffic densities
US9513125B2 (en) Computing route plans for routing around obstacles having spatial and temporal dimensions
CN104991895A (en) Low-altitude rescue aircraft route planning method based on three dimensional airspace grids
US8082102B2 (en) Computing flight plans for UAVs while routing around obstacles having spatial and temporal dimensions
US11619953B2 (en) Three dimensional aircraft autonomous navigation under constraints
CN113379172B (en) Automatic operation scheduling system and scheduling method for multiple unmanned aerial vehicles
CN108961843A (en) A kind of analogue system and method based on track running technology
KR20170080354A (en) The virtual skyway and air traffic control system for the drone&#39;s safe flight or the drone navigation system or service
CN111192481B (en) Method for determining boundary of unmanned aerial vehicle control area of approach and departure procedure based on collision risk
CN110634332B (en) Airport airspace flow control method for small and medium-sized vertical take-off and landing unmanned aerial vehicle
CN103578299B (en) A kind of method simulating aircraft process
CN110322733B (en) Method for establishing arrival takeoff window of lateral runway protection area
US20230237917A1 (en) A Method and System for Controlling Flight Movements of Air Vehicles
Zhang et al. Intelligent amphibious ground-aerial vehicles: State of the art technology for future transportation
Bertram et al. An efficient algorithm for self-organized terminal arrival in urban air mobility
CN111142555A (en) Airport unmanned aerial vehicle control area planning method based on collision risk
CN113470438A (en) Logic time sequence deduction simulation-based conflict-free flight trajectory generation method
CN116564140A (en) Low-altitude real-time flight conflict detection and release method based on navigation rescue
Zeng et al. An airport airspace flow control method for drones
CN108229057B (en) Design method of overhead overpass structure
Zhou et al. Optimal design of SIDs/STARs in TMA using simulated annealing
Milošević et al. Time based separation model in high density U-space traffic environment
CN117935625B (en) Intelligent air traffic unmanned aerial vehicle route management system and method
CN115662198A (en) Method and system for passing through civil aviation route based on dynamic path planning field
Peters Applicability of extended arrival manager to assist ANSPs in determining an arrival sequence that accounts for en-route delays

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