Departure sequencing systems and methods

• US 10,210,766 B2
• Filed: 08/04/2016
• Issued: 02/19/2019
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: American Airlines Incorporated (American Airlines Group Incorporated)
• Original Assignee: American Airlines Incorporated (American Airlines Group Incorporated)
• Inventors: Ince, Ilhan, Gumireddy, Lourdmareddy, Ergan, Hakan, Zhang, Bo
• Primary Examiner(s): Nguyen, Nga X
• Application Number:
  US15/228,184
• Publication Number:
  US 20160343259A1
• Time in Patent Office: 929 Days
• Field of Search: 703 22, 703 8, 701120, 701117, 705 6
• CPC Class Codes: G08G 5/0043 Traffic management of multiple aircrafts from the ground G08G5/003 takes precedence; data processing specially designed for resource management, e.g. scheduling or allocating time, human or machine resources G06Q10/06
• CPC Class Codes: G08G 5/0065 for taking-off

Abstract

A departure sequencing system models airport operations and provides suggested gate pushback times for aircraft. In various embodiments, a departure sequencing system includes an airport state analyzer, a taxi-out predictor, and a pushback optimizer. The departure sequencing system may utilize stochastic models, and resolve aircraft conflicts using a business rules engine. Via use of the departure sequencing system, taxi times may be reduced, taxi fuel burn may be reduced, and airport throughput may be increased.

Claims

1. A computer-implemented method for departure sequencing of a plurality of aircraft at an airport, the method comprising:

creating, by a computer, a graph network model representing the airport,

wherein the graph network model comprises a plurality of nodes and a plurality of links,

wherein the plurality of nodes include a gate node, airlinks, a runway with an entrance node and an exit node, and a runway crossing with a crossing node and ground links, and

wherein the graph network model is a directed graph;

scheduling, by the computer, a departure time for a first aircraft of the plurality of aircraft that is modeled on gate node business rules to model a taxi procedure for the first aircraft;

initializing, by the computer, a status of the first aircraft flight that is modeled on gate node business rules to further model the taxi procedure for the first aircraft;

allowing, by the computer, the first aircraft to occupy a node on a ground link, in response to the first aircraft approaching the node, a next ground link having available capacity and the node not being occupied by a second aircraft;

checking, by the computer, potential future directional head-to-head aircraft conflicts with the second aircraft to avoid gridlock;

triggering, by the computer and in response to the second aircraft waiting on the last ground link, movement of the second aircraft forward to wait on the next ground link as more space is made available on the next ground link;

releasing, by the computer, the node of the currently occupying aircraft;

creating, by the computer and in response to the second aircraft waiting for the node, a trigger to enter the node for the second aircraft;

implementing, by the computer, business rules for checking runway blockage by arrivals or crossings;

triggering, by the computer and after a take-off event, another take-off event in response to the first aircraft waiting on the runway entrance node and no blockage is applied;

scheduling, by the computer, multiple times for the first aircraft to pass the current runway node to model the runway crossing for the first aircraft in the graph network model;

assessing, by the computer, connection information associated with an item of luggage associated with an aircraft in the plurality of aircraft;

repeatedly executing, by the computer, the graph network model to obtain the suggested gate pushback time for the first aircraft at the airport based on the assessing of the connection information;

calibrating, by the computer, a parameter of the graph network model utilizing historical aircraft flight information for the airport; and

creating, by the computer, calibrated parameters based on different operating characteristics of the airport.

2. The method of claim 1, further comprising calibrating, by the computer, a parameter of the graph network model utilizing historical aircraft flight information for the airport.

3. The method of claim 2, further comprising associating, by the computer, business rules to at least one of a sequence of events, state transitions or an aircraft in the graph network model.

4. The method of claim 3, wherein the gate node business rules utilize real-time airport characteristics including rates and configuration to drive simulation parameters, and wherein the business rules are associated with aircraft path, pushback time, taxi speed and runway procedures.

5. The method of claim 1, further comprising:

calculating, by the computer, a time for the first aircraft to pass a ground link distance that is retrieved from historical speed table business rules for the ground link;

removing, by the computer, the first aircraft from a last ground link; and

adding, by the computer, the first aircraft to the next ground link.

6. The method of claim 1, wherein the calculating, by the computer, a suggested gate pushback time is repeated for the plurality of aircraft to minimize overall taxi time for the plurality of aircraft.

7. The method of claim 1, further comprising calculating and recording statistics of taxi time for each of the plurality of aircraft.

8. The method of claim 1, wherein the suggested gate pushback time is configured to ensure the hold time of each aircraft in the plurality of aircraft does not exceed a hold time threshold.

9. The method of claim 2, wherein the calibrating comprises revising, by the computer and in the graph network model, at least one of a speed zone distribution for a ground link or a business rule associated with a state transition.

10. The method of claim 1, further comprising executing, by the computer, an airport state analyzer, a taxi-out predictor, and a pushback optimizer.

11. The method of claim 1, further comprising communicating, by the computer and to an air traffic controller, a request for at least one of a ground stop program or a ground delay program responsive to the suggested gate pushback time.

12. The method of claim 1, further comprising:

calculating, by the computer, taxi path and taxi time for each of the plurality of aircraft;

determining, by the computer, ground congestion at the airport; and

resolving, by the computer and using a business rules engine, taxi conflicts and gate conflicts among the plurality of aircraft to model airport ground traffic.

13. The method of claim 12, wherein the resolving comprises determining, by the computer, a departure sequence for the plurality of aircraft, wherein the departure sequence is configured to minimize overall taxi time for the plurality of aircraft.

14. The method of claim 1, wherein the suggested gate pushback time is configured to maintain a departing runway minimum queue size.

17. The method of claim 1, wherein the graph network model comprises a database, and wherein the repeatedly executing, by the computer, the graph network model comprises adjusting the database by:

(a) tuning, by the graph network model, the database to optimize database performance, wherein the tuning includes placing frequently used files as indexes on separate file systems to reduce in and out bottlenecks;

(b) designating, by the graph network model, a key field in data tables to speed searching for the plurality of nodes and the plurality of links; and

(c) sorting, by the graph network model, the plurality of nodes and the plurality of links according to a known order to simplify the lookup process.

18. The method of claim 1, further comprising, responsive to the suggested gate pushback time, pushing back the first aircraft from an associated airport gate.

15. An article of manufacture including a non-transitory, tangible computer readable storage medium having instructions stored thereon that, in response to execution by a computer, cause the computer to perform operations comprising:

creating, by the computer, a graph network model representing an airport,

wherein the graph network model comprises a plurality of nodes and a plurality of links,

wherein the plurality of nodes include a gate node, airlinks, a runway with an entrance node and an exit node, and a runway crossing with a crossing node and ground links, and

wherein the graph network model is a directed graph;

scheduling, by the computer, a departure time for a first aircraft of the plurality of aircraft that is modeled on gate node business rules to model a taxi procedure for the first aircraft;

initializing, by the computer, a status of the first aircraft flight that is modeled on gate node business rules to further model the taxi procedure for the first aircraft;

allowing, by the computer, the first aircraft to occupy a node on a ground link, in response to the first aircraft approaching the node, a next ground link having available capacity and the node not being occupied by a second aircraft;

checking, by the computer, potential future directional head-to-head aircraft conflicts with the second aircraft to avoid gridlock;

triggering, by the computer and in response to the second aircraft waiting on the last ground link, movement of the second aircraft forward to wait on the next ground link as more space is made available on the next ground link;

releasing, by the computer, the node of the currently occupying aircraft;

creating, by the computer and in response to the second aircraft waiting for the node, a trigger to enter the node for the second aircraft;

implementing, by the computer, business rules for checking runway blockage by arrivals or crossings;

triggering, by the computer and after a take-off event, another take-off event in response to the first aircraft waiting on the runway entrance node and no blockage is applied;

scheduling, by the computer, multiple times for the first aircraft to pass the current runway node to model the runway crossing for the first aircraft in the graph network model;

assessing, by the computer, connection information associated with an item of luggage associated with an aircraft in the plurality of aircraft

repeatedly executing, by the computer, the graph network model to obtain the suggested gate pushback time for the first aircraft at the airport based on the assessing of the connection information;

calibrating, by the computer, a parameter of the graph network model utilizing historical aircraft flight information for the airport; and

creating, by the computer, calibrated parameters based on different operating characteristics of the airport.

16. A system comprising:

a processor; and

a tangible, non-transitory memory configured to communicate with the processor,

the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations comprising;

creating, by the processor, a graph network model representing an airport,

wherein the graph network model comprises a plurality of nodes and a plurality of links,

wherein the plurality of nodes include a gate node, airlinks, a runway with an entrance node and an exit node, and a runway crossing with a crossing node and ground links, and

wherein the graph network model is a directed graph;

scheduling, by the processor, a departure time for a first aircraft of the plurality of aircraft that is modeled on gate node business rules to model a taxi procedure for the first aircraft;

initializing, by the processor, a status of the first aircraft flight that is modeled on gate node business rules to further model the taxi procedure for the first aircraft;

allowing, by the processor, the first aircraft to occupy a node on a ground link, in response to the first aircraft approaching the node, a next ground link having available capacity and the node not being occupied by a second aircraft;

checking, by the processor, potential future directional head-to-head aircraft conflicts with the second aircraft to avoid gridlock;

triggering, by the processor and in response to the second aircraft waiting on the last ground link, movement of the second aircraft forward to wait on the next ground link as more space is made available on the next ground link;

releasing, by the processor, the node of the currently occupying aircraft;

creating, by the processor and in response to the second aircraft waiting for the node, a trigger to enter the node for the second aircraft;

implementing, by the processor, business rules for checking runway blockage by arrivals or crossings;

triggering, by the processor and after a take-off event, another take-off event in response to the first aircraft waiting on the runway entrance node and no blockage is applied;

scheduling, by the processor, multiple times for the first aircraft to pass the current runway node to model the runway crossing for the first aircraft in the graph network model;

assessing, by the processor, connection information associated with an item of luggage associated with an aircraft in the plurality of aircraft

repeatedly executing, by the processor, the graph network model to obtain the suggested gate pushback time for the first aircraft at the airport based on the assessing of the connection information;

calibrating, by the processor, a parameter of the graph network model utilizing historical aircraft flight information for the airport; and

creating, by the processor, calibrated parameters based on different operating characteristics of the airport.