EP3892959A1 - Systèmes de gestion de trafic et procédés pour véhicules aériens sans pilote - Google Patents

Systèmes de gestion de trafic et procédés pour véhicules aériens sans pilote Download PDF

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Publication number
EP3892959A1
EP3892959A1 EP21166796.9A EP21166796A EP3892959A1 EP 3892959 A1 EP3892959 A1 EP 3892959A1 EP 21166796 A EP21166796 A EP 21166796A EP 3892959 A1 EP3892959 A1 EP 3892959A1
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EP
European Patent Office
Prior art keywords
waypoint
traffic
computing devices
uav
network
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
EP21166796.9A
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German (de)
English (en)
Other versions
EP3892959B1 (fr
Inventor
Navin Kadavil
Aswathy Praveena SUKUMARAN
Roshan Prasad
Amber Bhardwaj
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Honeywell International Inc
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Honeywell International Inc
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Publication date
Priority claimed from US16/894,126 external-priority patent/US11410561B2/en
Application filed by Honeywell International Inc filed Critical Honeywell International Inc
Publication of EP3892959A1 publication Critical patent/EP3892959A1/fr
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0004—Transmission of traffic-related information to or from an aircraft
    • G08G5/0013—Transmission of traffic-related information to or from an aircraft with a ground station
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0017—Arrangements for implementing traffic-related aircraft activities, e.g. arrangements for generating, displaying, acquiring or managing traffic information
    • G08G5/0026—Arrangements for implementing traffic-related aircraft activities, e.g. arrangements for generating, displaying, acquiring or managing traffic information located on the ground
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/003—Flight plan management
    • G08G5/0034—Assembly of a flight plan
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/003—Flight plan management
    • G08G5/0039—Modification of a flight plan
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047—Navigation or guidance aids for a single aircraft
    • G08G5/0056—Navigation or guidance aids for a single aircraft in an emergency situation, e.g. hijacking
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047—Navigation or guidance aids for a single aircraft
    • G08G5/006—Navigation or guidance aids for a single aircraft in accordance with predefined flight zones, e.g. to avoid prohibited zones
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047—Navigation or guidance aids for a single aircraft
    • G08G5/0069—Navigation or guidance aids for a single aircraft specially adapted for an unmanned aircraft
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0073—Surveillance aids
    • G08G5/0082—Surveillance aids for monitoring traffic from a ground station
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/02—Automatic approach or landing aids, i.e. systems in which flight data of incoming planes are processed to provide landing data
    • G08G5/025—Navigation or guidance aids
    • 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
    • G08G5/045—Navigation or guidance aids, e.g. determination of anti-collision manoeuvers

Definitions

  • the present disclosure generally relates to systems and methods for traffic management for unmanned aerial vehicles (UAVs).
  • UAVs unmanned aerial vehicles
  • the present disclosure more particularly relates to determining flight plans in response to requests from UAVs.
  • UAV traffic management (UTM) system for low-altitude airspace is necessary.
  • Systems and methods are disclosed for traffic management for unmanned aerial vehicles (UAVs).
  • the systems and methods define a network of waypoint computing devices having traffic corridors connecting the waypoint computing devices.
  • Systems and methods receive suspend calls and initiate calls from waypoint computing devices and dynamically update the network so as to include additional waypoint computing devices and traffic corridor connections based on the initiate calls and to remove from the network waypoint computing devices and associated traffic corridors based on the suspend calls.
  • the systems and methods determine a flight plan for the UAV in response to a request based on the updated network.
  • the flight plan includes a plurality of traffic corridors connecting source and destination global coordinates included in the request.
  • the systems and methods provide a response to the UAV including the flight plan.
  • an embodiment of a system or a component may employ various integrated circuit components, e.g., memory elements, digital signal processing elements, logic elements, look-up tables, or the like, which may carry out a variety of functions under the control of one or more microprocessors or other control devices.
  • integrated circuit components e.g., memory elements, digital signal processing elements, logic elements, look-up tables, or the like, which may carry out a variety of functions under the control of one or more microprocessors or other control devices.
  • the program or code segments or programming instructions are described as a computer program stored in a tangible processor-readable medium or memory, which may include any medium that can store or transfer information.
  • a non-transitory and processor-readable medium include an electronic circuit, a semiconductor memory device, a ROM, a flash memory, an erasable ROM (EROM), a floppy diskette, a CD-ROM, an optical disk, a hard disk, or the like.
  • UAVs may have random take off positions, varying payloads and distributed roof top landing pads. UAVs with passenger traffic may require take-off and landing at designated landing pads.
  • the present disclosure provides, in some embodiments, systems and methods to plan entry and exit to/from a traffic flow and to optimize the traffic flow.
  • Systems and methods described herein provide software that connects waypoints into a network. A flight path between any two waypoints in the network is determined based on network performance parameters. The network performance parameters can be used to optimize the flight path and traffic flow through the network. The network performance parameters from various pairs of waypoints can be connected and scaled into a flight plan.
  • one or more landing pads and a waypoint computing device is located on a building and form part of a network of waypoints.
  • Two waypoint computing devices make a software connection to build a traffic corridor.
  • a trajectory of any UAV is predictable along the traffic corridors.
  • a UAV registers with a nearby waypoint computing device located on a building (associated with a building ID) before take-off.
  • the UAV sends a flight plan request including source and destination coordinates and the traffic management system determines and allocates a flight plan with an optimized trajectory.
  • the trajectory is optimized based on network performance parameters to optimize traffic flow.
  • more than two waypoint computing devices are connected to define a network.
  • Waypoint computing devices can join the network and exit the network through initiate and suspend calls.
  • the traffic management system keeps an updated record of waypoint computing devices making up the network.
  • UAVs also utilize the network as needed. Landing pads may be available on or at commercial and/or residential buildings.
  • the waypoint computing devices can self-initiate onto the network through an initiate call to a traffic management computer.
  • the traffic management computer designates a location of the building associated with the waypoint computing device with a traffic waypoint.
  • the waypoint computing devices are connected by defined traffic corridors. Addition of waypoint computing devices and associated traffic corridors allow the network to grow exponentially across a city.
  • a routing algorithm provides a connected list of traffic corridors for the flight plan. Further, the routing algorithm re-computes the flight plan at each traffic corridor transition in order to maintain the optimal path based on network performance, thereby reducing travel times and efficiently utilizing the network.
  • the routing algorithm uses various network performance parameters for each traffic corridor and formulates cost vectors embodying the network performance parameters. The routing algorithm minimizes the sum of cost vectors in determining the flight plan.
  • the network performance parameters include number of hops (hop count), speed of the traffic corridor, congestion/conditions for the traffic corridor, latency (delay), traffic corridor bandwidth, and any emergency.
  • the routing algorithm places emphasis on traffic throughput when determining a flight plan.
  • a UAV is commanded to leave traffic corridors during any emergency for the UAV to allow other traffic to proceed. Hovering is not permitted in the traffic corridors.
  • FIG. 1 illustrates a block diagram of a traffic management system 10 including a traffic management computer 14, a UAV 12 and a network 16 of waypoint computing devices 18, in accordance with an embodiment.
  • FIG. 2 illustrates a block diagram of an exemplary traffic flow network 200 including waypoint computing devices 18 located on respective buildings 202 that have landing pads 206. Traffic corridors 208 are defined between buildings 202 by the traffic management system 10, as described further herein.
  • the waypoint computing devices 18 include a memory 36, a processor 34, and a global positioning system (GPS) receiver and a transceiver 38.
  • the memory 36 has one or more computer programs 42 stored thereon that are executed by the processor 34 in order to perform the various functions described herein with respect to the waypoint computing devices 18.
  • GPS global positioning system
  • the waypoint computing devices 18 send initiate calls to the traffic management computer 14 as part of a request to join the network 16 of waypoint computing devices 18.
  • the request is sent by the transceiver 38 through a cellular data connection or through a wired or wireless (e.g. wireless router such as WiFi) internet connection.
  • the request may include a location (e.g. latitude and longitude) of a building 202 on which the waypoint computing device 18 is located.
  • the location of the building 202 can be determined through the GPS receiver 40 or through other geolocation systems such as a WiFi positioning system.
  • the location of the building 202 is preset in the waypoint computing device 18. When more accurate location is required, differential GPS technology may be used.
  • a combination of one or more map databases and detected location data is utilized to accurately determine the location of the building 202.
  • the request may further include an identification of a number of landing pads 206 on the building 202 and optionally also a location of each landing pad in terms of altitude, latitude and longitude (or relative location with respect to each other and with respect to the building location), which may be retrieved from the memory 36.
  • the traffic management computer 14 responds with a building identifier that is stored by the waypoint computing device 18 in memory 36 and which is used to identify the waypoint computing device 18 in further communications with the traffic management computer 14.
  • the waypoint computing devices 18 send suspend calls when a waypoint computing device 18 (and its associated building 202) is to drop off the network 16.
  • the waypoint computing devices 18 may send the suspend call to the traffic management computer 14 when all of the landing pads 206 for the building 202 associated with the waypoint computing device 18 are occupied or when there is an emergency at the building 202 such as a medical emergency (e.g. a passenger taken ill), a traffic emergency (e.g. a UAV crash) or a building emergency (e.g. a fire alarm).
  • a medical emergency e.g. a passenger taken ill
  • a traffic emergency e.g. a UAV crash
  • a building emergency e.g. a fire alarm
  • the waypoint computing devices 18 each store and update a routing table 44.
  • the routing table 44 is a database that keeps track of paths, like a map, and uses these to respond to requests from UAVs to determine a flight plan.
  • the waypoint computing devices 18 compute cost vectors for each traffic corridor 208 connecting a waypoint computing device 18 to a neighboring waypoint computing device 18.
  • the cost vectors include a measure of throughput for the traffic corridor.
  • the cost vectors include at least one of the following metrics (or network performance parameters): length of the traffic corridor (in distance), average time to traverse the traffic corridor or traffic corridor delay, inverse of path bandwidth, and traffic congestion.
  • the waypoint computing devices 18 monitor such network performance parameters through each UAV communicating, via its transceiver 24, with the waypoint computing device 18 when entering and exiting its one or more traffic corridors 208.
  • Each waypoint computing device 18 updates its own routing table 44 based on changes to the network performance parameters affecting the cost vectors for any traffic corridors 208 connecting to its neighbors. Further, each waypoint computing device 18 receives routing tables 44 from its neighboring waypoint computing devices 18 and sends its own routing table 44 to neighboring waypoint computing devices 18. In this way, the routing tables 44 of each waypoint computing device 18 are updated by calculating cost vector changes based on changing network performance parameters with respect to traffic corridors connecting to neighboring waypoint computing devices 18 and by receiving further afield information from updated routing tables received from neighboring waypoint computing devices 18.
  • the waypoint computing device 18 of building A1 can update cost vectors in its own routing table 44 by monitoring network performance parameters for traffic corridors A1A2 and A1B1 and can receive updated cost vectors based on routing tables 44 received from waypoint computing devices 18 of buildings A2, B2 and B1.
  • the cost vectors for the whole network 16 are updated by propagation of updated routing tables 44 sent to each neighbor. This propagation algorithm allows each routing table 44 of each waypoint computing device 18 to, eventually, have updated status information for the cost vectors for each traffic corridor 208.
  • FIG. 4 illustrates a simplified network 16 of waypoint computing devices A to D that are connected by traffic corridors AB, AC, BC and CD.
  • Each traffic corridor is associated with a cost vector, which is represented by a single real number.
  • traffic corridor AB has a cost vector of 3
  • traffic corridor AC has a cost vector of 23
  • traffic corridor BC has a cost vector of 2
  • traffic corridor CD has a cost vector of 5.
  • cost matrices are created for each waypoint computing device 18 to its immediate neighbors based on network performance parameters. In this way, the cost vectors shown in FIG. 4 are established.
  • the following routing tables 1 to 4 are established by each waypoint computing device 18. Shortest path or minimum cost vector routes are highlighted in bold. Table 1 From A Via A Via B Via C Via D To A To B 3 To C 23 To D Table 2 From B Via A Via B Via C Via D To A 3 To B To C 2 To D Table 3 From C Via A Via B Via C Via D To A 23 To B 2 To C To D 5 Table 4 From D Via A Via B Via C Via D To A To B To C 5 To D
  • all the waypoint computing devices broadcast, via transceiver 38, their cost vectors to all their neighbors: A to B and C, B to C and A, C to A, B, and D, and D to C.
  • routers A and D have new shortest-paths (minimum costs) for their cost vectors.
  • a and D broadcast their new cost vectors to their neighbors: A broadcasts to B and C, and D broadcasts to C. This causes each of the neighbors receiving the new cost vectors to re-calculate their shortest paths.
  • the information from the cost vectors does not yield any shorter paths than they already have in their routing tables 44, then there are no changes to the routing tables.
  • none of the waypoint computing devices 18 have any new shortest-paths to broadcast. Therefore, none of the waypoint computing devices 18 receive any new information that might change their routing tables 44.
  • the algorithm comes to a stop until new cost vector information is received (such as through a waypoint computing device 18 determining that its own traffic corridors 208 has a change in cost vector based on detected network performance parameters).
  • new cost vector information is obtained that results in a new minimum cost vector path
  • the new cost vector information is propagated throughout the network 16 by each waypoint computing device transmitting its routing table 44 (or affected part thereof) to neighboring waypoint computing devices 18.
  • the neighboring waypoint computing devices 18 re-compute minimum cost vector paths and send the updated routing tables to its neighbors and so on until all routing tables 44 in the network 16 are brought up to date.
  • the waypoint computing devices 18 receive information from the traffic management computer 14 reporting when waypoint computing devices 18 are to be added to the network 16 and when waypoint computing devices 18 are to be removed from the network 16.
  • the information may include a description of new traffic corridors and neighboring waypoint computing devices 18 for additional waypoint computing devices and a description of traffic corridors that are to be removed from the network 16 for removal of waypoint computing devices from the network 16.
  • the waypoint computing devices 18 will recalculate its cost vectors and update the routing tables 44 to reflect new and removed waypoint computing devices 18.
  • the updated cost vectors and routing tables 44 are propagated throughout the network 16 in the manner described above.
  • the waypoint computing devices 18 receive requests from UAVs 12 for a flight plan.
  • the requests include at least source and destination global coordinates.
  • the source and destination global coordinates may be absolute coordinates or a building or waypoint computing device identifier. Additional information included in each request includes at least one of: estimated start time, number of passengers, take-off weight, flight ID and UAV registration number.
  • the closest waypoint computing device 18 is engaged with the request.
  • the waypoint computing device 18 engaged with the request responds with a flight plan that has been selected using the routing tables, specifically so as to select the lowest cost path to the destination included in the routing table.
  • This lowest cost represents a measure at least one of speed of traffic throughput and is an accumulation of costs for each traffic corridor 208 on the route from the receiving waypoint computing device 18 to the destination waypoint computing device 18.
  • the waypoint computing device 18 receiving the request responds with at least a list of flight legs made up of traffic corridors (e.g. traffic corridor identifiers). Additional information included in the response includes at least one of: flight ID, source GPS, destination GPS, maximum altitude, minimum altitude, and number of flight legs. Additional information included with respect to each flight leg includes at least one of: altitude, source building ID (or global coordinates), end building ID (or global coordinates), estimated start time, estimated end time, en route traffic management computer ID (where there is more than one traffic management computer 14).
  • the traffic management computer 14 has a processor 29, a transceiver 32, a memory 28 and one or more computer programs 30 stored on the memory 28 that are executable by the processor 29 to perform the functions and method steps of the traffic management computer 14.
  • the traffic management computer 14 maintains and dynamically updates the network 16 of waypoint computing devices 18.
  • the traffic management computer 14 receives one or more initiate calls, via the transceiver 32, from one or more waypoint computing devices 18 requesting to join (or re-join) the network 16.
  • the traffic management computer 14 determines neighboring waypoint computing devices 18 in the network 16 based on global coordinates included in the initiate call and global coordinates of waypoint computing devices 18.
  • the traffic management computer 14 retrieves three-dimensional (latitude, longitude and altitude) map data from a map database 46 that describes airspace with respect to buildings in a geographic location of relevance to the network 16 (e.g. a city).
  • the traffic management computer 14 defines one or more traffic corridors 208 connecting the new waypoint computing device with at least one neighboring waypoint computing device 18 already in the network 16 using airspace information from the map database 46.
  • the traffic corridors 208 should be defined so as to avoid obstacles including buildings and to include a safety buffer from the buildings.
  • the traffic management computer 14 defines, in embodiments, a traffic corridor 208 using a lateral range (minimum and maximum) and an altitude range (minimum and maximum) and a longitudinal range (maximum and minimum - defined from a position adjacent to the new waypoint computing device 18 (and its associated building 202) to a position adjacent to a neighboring waypoint computing device 18 already in the network 16).
  • the traffic management computer 14 provides the new waypoint computing device 18 with an identifier for use in communicating with the traffic management computer 14.
  • the identifier may be a building ID or a waypoint computing device ID.
  • the traffic management computer 14 or the new waypoint computing device 18 itself propagates data (waypoint computing device identifier, neighboring waypoint computing devices, etc.) concerning the new waypoint computing device 18 by updating the routing tables 44 throughout the network 16 using the propagation scheme described above.
  • the traffic management computer 14 receives one or more suspend calls from one or more waypoint computing devices 18.
  • the traffic management computer 14 maintains a dynamically updated record of network 16 including locations of all waypoint computing devices 18 and all locations and dimensions of traffic corridors 208 connecting the waypoint computing devices 18.
  • the suspend call includes the identifier of the waypoint computing device 18 or building 202 to be removed from the network 16.
  • the traffic management computer 14 removes the waypoint computing device 18 and traffic corridors 208 emanating therefrom to neighboring waypoint computing devices 18 from the network 16.
  • the traffic management computer 14 or neighboring waypoint computing devices 18 propagate data (waypoint computing device identifier, neighboring waypoint computing devices, etc.) concerning the removed waypoint computing device 18 by updating the routing tables 44 throughout the network 16 using the propagation scheme described above.
  • the UAV 12 includes a memory 20, one or more computer programs 22, a transceiver 24 and a GPS receiver 26.
  • the UAV 12 is an aircraft without a human pilot on board, although passengers may be onboard.
  • the UAV 12 may have a ground-based controller, and a system of communications between the controller and the UAV 12. In other embodiments, the UAV 12 is autonomous using onboard computers to control flight.
  • the UAV 12 may be a rotorcraft.
  • the UAV 12 may be electrically powered, combustible fuel powered or a hybrid thereof.
  • the processor 27 of UAV executes one or more computer programs 22 stored on the memory 20 to perform the functions and methods described herein.
  • the UAV 12 communicates with the waypoint computing devices 18 via the transceiver 24.
  • the UAVs 12 send, via transceivers 24, flight plan requests to proximal waypoint computing devices 18.
  • the transceivers 24 may operate through radiofrequency or microwave frequency broadcasts and/or through cellular or router-based internet connectivity.
  • the UAV 12 transmits its location, obtained from the GPS receiver 26, to traffic management computer 14 and requests a location of a nearest waypoint computing device 18. The location may be determined by other sensors such as Wifi location sensing, ground based location beacons, image-based localization and combinations thereof.
  • the traffic management computer 14 responds with the location of a nearest waypoint computing device 18 based on its current record of the network 16.
  • the UAV 12 is regularly updated with the record of the network 16 by the traffic management computer and selects a nearest waypoint computing device 12.
  • the UAV 12 transmits, as part of the request for a flight plan, the start location (which is usually the current location obtained via the GPS receiver 26) and a destination location, which is mission dependent, to the proximal waypoint computing device 18.
  • the proximal waypoint computing device 18 is responsive to the request to determine the flight plan based on the combination of traffic corridors 208 having the lowest total cost vectors from the source to the destination, which is determined by looking up the routing table 44, which has been described in more detail above. Other factors may be taken into consideration when drawing up the flight plan.
  • network performance parameters such as throughput (e.g.
  • minimizing time for each journey and maximizing quantity of journeys) are favored in determining the flight plan such that shortest distance is not always the selected flight plan since the shortest distance may not factor in traffic corridor bandwidth, traffic corridor congestion, traffic corridor speed, etc..
  • Other factors included as part of flight plan determination are remaining fuel, maximum permissible time for journey and space requirements of the UAV 12. These additional factors may be transmitted by UAV 12 to proximal waypoint computing device 18.
  • the proximal waypoint computing device 18 may respond with a list of flight legs, which correspond to traffic corridor identifiers.
  • the UAV 12 may retrieve the geography of each listed traffic corridor 208 from an updated record of the network 16 from onboard memory 20 (which has been obtained from traffic management computer 14) or from the traffic management computer 14 in response to a request for traffic corridor data.
  • the geography of each traffic corridor 208 includes permissible lateral range, permissible altitude range and longitudinal range.
  • the UAV 12 retrieves the traffic corridor geography before commencing the flight.
  • the UAV 12 retrieves the traffic corridor geography from the traffic computer 14 at each traffic corridor transition along the flight.
  • the UAV 12 transmits the flight plan to the traffic management computer 14 when the flight plan is initiated and transmits a completion message when the flight plan is finished. In this way, the traffic management computer 14 is able to track in memory all flight plans in the network 16.
  • the UAV 12 may transmit a current flight plan to a new proximal waypoint computing device 18 at the end of each traffic corridor (or flight leg) 208 so that the new proximal waypoint computing device 18 validates or modifies the flight plan based on potentially changed network performance parameters, which are reflected in update cost vectors in routing tables 44. The UAV 12 will then switch traffic corridors 208 based on the changed flight plan.
  • the flight plan will include altitude and latitude commands within the traffic corridor 208.
  • the waypoint computing device 18 can monitor traffic in its own traffic corridor(s) 208 and select altitude and latitude parameters for new traffic to ensure that minimum spacing requirements and throughput are maintained.
  • the waypoint computing device 18 monitors plural latitude and altitude channels within its own traffic corridor(s) 208 and issues altitude and/or latitude switching instructions to UAVs 12 traversing the traffic corridor 208 to optimize traffic throughput. This monitoring can be performed by receiving global position coordinate broadcasts from each UAV 12 in the traffic corridor 208 and monitoring speed of each UAV with respect to latitude and/or latitude channels of the traffic corridor 208.
  • the UAVs 12 each broadcast their positions, speeds and possibly other motion parameters (like direction of movement) to all other UAVs in the same traffic corridor 208.
  • the UAVs 12 can freely switch latitude and altitude within the traffic corridor 208 in order to get moving longitudinally within the traffic corridor 208 with the constraint of maintaining a safety buffer from other UAVs 12 within the traffic corridor 208, which is determined based on motion parameters sent from other UAVs 12.
  • the known in-trail procedure algorithm is used by the UAVs 12 when selecting and switching between altitude and latitude channels within a traffic corridor 208.
  • FIG. 2 illustrates, by way of example, a traffic flow network 200 for an example city having a grid pattern of buildings 202 each having a waypoint computing device 18. More common would be arrangements of buildings 202 in a city (or other urban environment) that do not follow a grid pattern and wherein only some of the buildings 202 have waypoint computing devices 18.
  • each waypoint computing device 18 has registered with the traffic management computer 14 through an initiate call, as described herein.
  • the traffic management computer 14 maintains a record of all active waypoint computing devices 18 in the network 16 including a description of their locations, the traffic corridors 208 connecting to neighbors and the dimensions of the traffic corridors 208.
  • the UAV 12 sends a request to the proximal waypoint computing device 18 A1 for a flight plan.
  • the request includes at least the destination address (e.g. a global coordinate, a waypoint computing device ID or a building ID) corresponding to building D4.
  • the waypoint computing device 18 A1 determines the lowest cost path from A1 to D4 based on cost vectors included in the routing table 44 for destination D4.
  • the routing table 44 identifies not only the lowest cost vectors from plural alternatives, but also identifies the list of via points in terms of traffic corridors. In the present case, there are many possibilities for travelling from A1 to D4.
  • One route 212 is illustrated in FIG. 2 , which, according to the routing table 44, has a higher total cost vector than route 210, which may mean that route 212 would be slower than route 210 despite the routes 210, 212 being equidistant. This may be because of a lack of bandwidth in one of the traffic corridors 208 along the route 212 as compared to the traffic corridors along the route 210. Accordingly, the waypoint computing device 18 A1 returns a flight plan including traffic corridors A1A2, A2A3, A3A4, A3B3, B3C3, C3D3, C3C4 corresponding to route 210.
  • the UAV 12 receives the flight plan from the waypoint computing device 18 A1 and determines dimensions of the traffic corridors either by looking up updated data from its own database concerning the network 16 (which has been provided and updated by traffic management computer 14) or by retrieving the data from using a request sent to the traffic management computer 14.
  • the dimensions of the traffic corridors 208 and the list of traffic corridors 208 in the flight plan allow the UAV 12 to generate flying commands for various onboard actuators (e.g. steering, lift and thrust) to fly along the designated flight corridors 208 from A1 to D4 along the route 210.
  • the flight is restricted to the dimensions (latitude, longitude and altitude) of each traffic corridor 208.
  • the UAV 12 may send a request (including the current flight plan) to the most proximal waypoint computing device 18 at each transition from one traffic corridor 208 to another (e.g. at the transition from A1A2 to A2A3) along the route 210 to confirm or update the flight plan based on changes to the network performance parameters that will be reflected in the continually updating cost vectors of the routing table 44.
  • the UAV 12 will send a completion message to the traffic management computer 14 to record the flight plan and its completion status in the memory 28.
  • FIG. 3 illustrates a flowchart of a method 300 for managing UAV traffic, in accordance with various exemplary embodiments.
  • the various tasks performed in connection with method 300 may be performed by software (e.g. program instructions executed by one or more of the processors 27, 29, 34), hardware, firmware, or any combination thereof. That is, method 300 may be executed by the processors 27, 29, 34 as described in the following or by any one or combination of the processors 27, 29, 34 executing computer programming instructions stored in one or more memories 20, 28, 36.
  • the following description of method 300 may refer to elements mentioned above in connection with FIG. 1 . It should be appreciated that method 300 may include any number of additional or alternative tasks, the tasks shown in FIG.
  • method 300 need not be performed in the illustrated order, and method 300 may be incorporated into a more comprehensive procedure or process having additional functionality not described in detail herein. Moreover, one or more of the tasks shown in FIG. 3 could be omitted from an embodiment of the method 300 as long as the intended overall functionality remains intact.
  • the method 300 includes a step 310 of maintaining the network 16 of waypoint computing devices 18.
  • the waypoint computing devices 18 are each located on a respective building 202.
  • the network 16 is maintained by the traffic management computer 14 including detailed information on the global location of each waypoint computing device 18 (or its associated building 202), the location of neighboring waypoint computing devices 18 and the dimensions and locations of the traffic corridors 208 connecting each waypoint computing device 18 to its neighbors.
  • the traffic corridors 208 are linear and are defined with respect to the ending longitudinal positions and have a constant crosssectional area between the ends.
  • the traffic corridors 208 may have plural lateral and/or altitude channels sized to fit respective UAVs.
  • the traffic corridors 208 may be one way or two-way paths.
  • the UAVs 12 are programmed to obey the dimensional constraints of each traffic corridor as well as any other rules such as directionality, permitted channels, speed, etc.
  • the method 300 includes a step 320 of receiving, at the traffic management computer 14, suspend calls and/or initiate calls from one or more waypoint computing devices 18.
  • the traffic management computer 14 dynamically updates the network 16 by adding the one or more waypoint computing devices 18 to the network 16 in response to the initiate calls and removing the one or more waypoint computing devices 18 from the network 16 in response to the suspend calls.
  • the traffic management computer 14 keeps a record of the network 16 (including traffic corridors 208) up to date. Accordingly, invalid traffic corridors 208 and waypoint computing devices 18 (e.g. as a result of no landing pad availability or an emergency at the building 202) are kept out of the network 16 to ensure relevancy of all flight plans generated.
  • the method 300 includes a step 340 of maintaining routing tables 44 at each of the waypoint computing devices.
  • the routing table 44 for any given waypoint computing device 18 includes a cost vector for each route alternative from the given waypoint computing device 18 to all other waypoint computing devices 18 in the network 16.
  • the routing tables 44 are updated accordingly based on add or remove commands sent from the traffic management computer 14.
  • the waypoint computing devices 18 determine network performance parameters for each of its connecting traffic corridors 208 based at least partly on motion data transmitted from UAVs 12 (e.g. at least position and optionally at least one of speed and acceleration) traversing the traffic corridors 208.
  • the motion data (which is based at least on GPS data from GPS receiver 26 and optionally also speed and other vehicle motion sensors like inertial measurement sensors and image based localization) may be transmitted by the UAVs 12 at periodic intervals during traversal of the traffic corridor 208 or at entry and exit of the traffic corridors 208.
  • the corresponding cost vectors in the routing table 44 are adjusted by the waypoint computing device 18.
  • the waypoint computing device 18 transmits its adjusted routing table 44 to its neighbors, which then adjust their own cost vectors based on the received routing table 44. In this way, the cost vectors (and the minimum cost values for each destination) are propagated by a routing table update propagation algorithm whereby each waypoint computing device 18 sends its changed routing table to each of its neighbors.
  • the method 300 includes a step 350 of a proximal waypoint computing device 18 receiving a request for a flight plan from a UAV 12.
  • the proximal waypoint computing device 18 is determined based on a detected location of the UAV 12 (e.g. through GPS coordinates obtained by GPS receiver 26 or through other localization techniques such as by comparing images from an onboard camera with mapped images or using ground based location beacons or a combination thereof) and information on the location of the waypoint computing devices 18 in the network 16 obtained from the traffic management computer 14.
  • the proximal waypoint computing device 18 determines a flight plan based on minimizing a total cost vector to the destination, which is obtainable based on the cost vectors included in the routing table 44.
  • the waypoint computing device 18 sends the flight plan to the UAV 12 including identification of each traffic corridor 208 in the flight plan (e.g. using traffic corridor identifiers).
  • the UAV 12 retrieves geography descriptions (e.g. longitudinal end locations, lateral range and altitude range) of the traffic corridors 208 included in the flight plan based on information received from the traffic management computer 14.
  • the UAV 12 flies the flight plan taking into account the traffic corridor dimensional constraints.
  • the UAV 12 receives from, and transmits to, other UAVs in the traffic corridor 208 motion data (e.g. three-dimensional location and speed).
  • the UAV 12 uses the information received from other UAVs 12 in the traffic corridor in order to maintain predetermined spacing from the other UAVs 12 including when deciding on whether to switch lateral and/or altitude position.
  • the lateral and/or altitude position occupied by the UAV 12 is set as part of the flight plan determined by, and received from, the waypoint computing device.
  • the UAV 12 sends the flight plan to the next waypoint computing device 18 en route when transitioning from one traffic corridor to another traffic corridor.
  • the next waypoint computing device 18 may adjust the flight plan depending on any changes to the network performance parameters reflected in cost vectors of the routing tables 44.
  • the UAVs 12 report completion of the flight plan to the traffic management computer 14 for flight tracking purposes.

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  • Engineering & Computer Science (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Business, Economics & Management (AREA)
  • Emergency Management (AREA)
  • Traffic Control Systems (AREA)
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US16/894,126 US11410561B2 (en) 2020-04-06 2020-06-05 Traffic management systems and methods for unmanned aerial vehicles

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