Using aircraft trajectory data to infer aircraft intent

• US 8,977,484 B1
• Filed: 08/22/2013
• Issued: 03/10/2015
• Est. Priority Date: 08/22/2013
• Status: Active Grant

• Current Assignee: The Boeing Co.
• Original Assignee: The Boeing Co.
• Inventors: La Civita, Marco
• Primary Examiner(s): Black, Thomas G
• Assistant Examiner(s): HUYNH, LUAT T
• Application Number:
  US13/972,911
• Publication Number:
  US 20150057915A1
• Time in Patent Office: 565 Days
• Field of Search: 701/120, 701/3, 701/14, 701/301, 340/945, 340/947
• US Class Current: 701/120
• CPC Class Codes: G08G 5/0013 with a ground station
• CPC Class Codes: G08G 5/0021 located in the aircraft
• CPC Class Codes: G08G 5/0026 located on the ground
• 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 5/0078 for monitoring traffic from the aircraft radar or analogous systems specially adapted for traffic control G01S13/91
• CPC Class Codes: G08G 5/0082 for monitoring traffic from a ground station radar or analogous systems specially adapted for traffic control G01S13/91
• CPC Class Codes: G08G 5/0091 for monitoring atmospheric conditions radar or analogous systems specially adapted for meteorological use G01S13/95; meteorology G01W

Abstract

A method is provided for inferring the aircraft intent of an aircraft from an observed trajectory. Aircraft performance data relating to that type of aircraft is retrieved from memory, along with atmospheric conditions along the observed trajectory. An initial set of candidate aircraft intents is generated. Each aircraft intent provides an unambiguous description of how the aircraft may be flown that allows a determination of an unambiguous resulting trajectory. A computer system calculates a trajectory defined by each candidate aircraft intent and forms a cost function from a comparison of each calculated trajectory to the observed trajectory. An evolutionary algorithm evolves the initial candidate aircraft intents, wherein the evolutionary algorithm uses a multi-objective cost function to obtain a cost function value that measures the suitability of each candidate aircraft intent.

Claims

1. A computer-implemented method of inferring the aircraft intent of an aircraft from an observed trajectory of the aircraft, the method comprising:

obtaining the observed trajectory of the aircraft;

determining a type of the aircraft and retrieving from memory aircraft performance data relating to that type of aircraft;

retrieving data regarding atmospheric conditions along the observed trajectory;

generating an initial set of candidate aircraft intents that provide an unambiguous description of how the aircraft may be flown and that allows a determination of an unambiguous resulting trajectory;

providing as inputs to a computer system the initial set of candidate aircraft intents, the aircraft performance data, and the atmospheric conditions data;

calculating from the inputs a calculated trajectory defined by each candidate aircraft intent in the initial set of candidate aircraft intents;

forming a multi-objective cost function from a comparison of each calculated trajectory to the observed trajectory;

using an evolutionary algorithm to evolve the set of initial candidate aircraft intents into an evolved set of candidate aircraft intents and repeating iterations of the evolutionary algorithm to evolve further the candidate aircraft intents of the evolved set, wherein the evolutionary algorithm uses a multi-objective cost function to obtain a cost function value that measures a goodness of each candidate aircraft intent; and

providing one or more candidate aircraft intents with the best cost function value or values respectively.

2. The method of claim 1, wherein determining the trajectory of the aircraft comprises using radar data, ADS-B data or ADS-C data.

3. The method of claim 1 further comprising providing as a further input to the computer system initial conditions of the aircraft, and wherein the calculated trajectory defined by each candidate aircraft intent is calculated from the inputs and the further input.

4. The method of claim 3, further comprising generating a common set of initial conditions from the observed trajectory or generating different sets of initial conditions from the candidate aircraft intents.

5. The method of claim 1, further comprising retrieving a set of bounds, and randomly generating the initial set of candidate aircraft intents to include randomly generated values within the bounds.

6. The method of claim 1, further comprising randomly generating the initial set of aircraft intents while being guided to provide a broad range of candidate aircraft intents.

7. The method of claim 1, wherein the cost function is based upon the combination of (a) a point-by-point score derived from summing a deviation of the respective calculated trajectory from the observed trajectory at each of a number of points sampled along the observed trajectory, and (b) an overall consistency score derived from a length of the respective calculated trajectory that deviates from the observed trajectory by less than a threshold value.

8. The method of claim 1, wherein the candidate aircraft intents comprise threads, each thread defining a degree of freedom of the aircraft, and each thread extends from the start of the trajectory to the end of the trajectory, and wherein generating the initial set of candidate aircraft intents comprises, for each candidate aircraft intent, filling each thread with one or more instructions thereby closing all degrees of freedom of the aircraft throughout the trajectory.

9. The method of claim 8, wherein generating the initial set of candidate aircraft intents comprises, for each candidate aircraft intent, filling each thread with an instruction such that each thread contains only a single instruction spanning the entire trajectory.

10. The method of claim 9, wherein the calculated trajectories are divided into flight segments, a start and end of the flight segments being defined by starts and ends of the instructions, and wherein the method further comprises using the evolutionary algorithm to evolve a set of evolved candidate aircraft intents in a stepwise manner, each step comprising optimizing one flight segment at a time starting with the first flight segment and proceeding chronologically through the observed trajectory.

11. The method of claim 10, further comprising:

evolving the initial set of candidate aircraft intents iteratively to form the evolved set of candidate aircraft intents while allowing the length of the instructions to vary while keeping the start of each instruction tied to the start of the observed trajectory, and wherein the evolutionary algorithm uses the multi-objective cost function to obtain a cost function value that measures the goodness of each candidate aircraft intent based upon a comparison of the calculated trajectory calculated for the flight segment with the corresponding portion of the observed trajectory;

retaining the candidate aircraft intents with the best cost function values;

performing outer loops of iterations and inner loops of iterations, wherein;

the outer loop of iterations comprises;

generating a further initial set of candidate aircraft intents by generating multiple copies of the retained aircraft intents and adding an instruction to each thread of the copies of the retained candidate aircraft intents to extend from the end of the last flight segment to the end of the trajectory such that each thread is again filled by instructions spanning the entire trajectory,

repeated iterations of the inner loop comprising evolving the further initial set of candidate aircraft intents to form further evolved sets of candidate aircraft intents while allowing the length of the instructions occupying the final flight segment to vary while keeping the start of each instruction tied to the end of the previous instruction, while the evolutionary algorithm uses the multi-objective cost function to obtain a cost function value that measures the goodness of each candidate aircraft intent based upon a comparison of the calculated trajectory calculated from the start of the observed trajectory to the end of the final flight segment with the corresponding portion of the observed trajectory, and

retaining the candidate aircraft intents with the best cost function values;

wherein the outer loop of iterations are repeated until an evolved set of candidate solutions is produced that includes candidate aircraft intents with threads that are filled with instructions to span the entire observed trajectory.

12. The method of claim 1, further comprising providing multiple candidate aircraft intents with the best cost function values to a user for the user to select a preferred candidate aircraft intent.

13. The method of claim 1, further comprising ranking the provided candidate aircraft intents and the step of providing one or more candidate aircraft intents with the best cost function value or values respectively comprises either (a) providing a ranked list of candidate aircraft intents or (b) providing the highest ranked candidate aircraft intent.

14. The method of claim 13, wherein ranking the provided candidate aircraft intents comprises at least one of:

ranking according to the cost function values, ranking according to number of flight segments, and ranking according to the frequency with which that candidate aircraft intent appears in the evolved set.

15. A system for inferring the aircraft intent of an aircraft from an observed trajectory of the aircraft, the system comprising:

a computing system;

a tangible non-transitory computer readable medium comprising instructions stored thereon, that when executed by the computer system, causes the computer system to;

obtain the observed trajectory of the aircraft;

determine a type of the aircraft and retrieve from memory aircraft performance data relating to that type of aircraft;

retrieve data regarding atmospheric conditions along the observed trajectory;

generate an initial set of candidate aircraft intents that provide an unambiguous description of how the aircraft may be flown and that allows a determination of an unambiguous resulting trajectory;

provide as inputs, the initial set of candidate aircraft intents, the aircraft performance data, and the atmospheric conditions data;

calculate from the inputs a calculated trajectory defined by each candidate aircraft intent in the initial set of candidate aircraft intents;

form a multi-objective cost function from a comparison of each calculated trajectory to the observed trajectory;

use an evolutionary algorithm to evolve the set of initial candidate aircraft intents into an evolved set of candidate aircraft intents and repeat iterations of the evolutionary algorithm to evolve further the candidate aircraft intents of the evolved set, wherein the evolutionary algorithm uses a multi-objective cost function to obtain a cost function value that measures a goodness of each candidate aircraft intent; and

provide one or more candidate aircraft intents with the best cost function value or values respectively.

16. The system of claim 15, wherein the candidate aircraft intents comprise threads, each thread defining a degree of freedom of the aircraft, and each thread extends from the start of the trajectory to the end of the trajectory, and

wherein instructions for generating the initial set of candidate aircraft intents comprises instructions that when executed by the computer system, causes the computer system to, for each candidate aircraft intent, fill each thread with one or more instructions thereby closing all degrees of freedom of the aircraft throughout the trajectory.

17. The system of claim 16, wherein instructions for generating the initial set of candidate aircraft intents further comprises instructions that when executed by the computer system, causes the computer system to, for each candidate aircraft intent, fill each thread with an instruction such that each thread contains only a single instruction spanning the entire trajectory.

18. A tangible non-transitory computer readable medium having stored thereon a computer program for inferring the aircraft intent of an aircraft from an observed trajectory of the aircraft, the computer program comprising instructions, that when executed by a computer system, causes the computer system to:

obtain the observed trajectory of the aircraft;

determine a type of the aircraft and retrieve from memory aircraft performance data relating to that type of aircraft;

retrieve data regarding atmospheric conditions along the observed trajectory;

generate an initial set of candidate aircraft intents that provide an unambiguous description of how the aircraft may be flown and that allows a determination of a unambiguous resulting trajectory;

provide as inputs, the initial set of candidate aircraft intents, the aircraft performance data, and the atmospheric conditions data;

calculate from the inputs a calculated trajectory defined by each candidate aircraft intent in the initial set of candidate aircraft intents;

form a multi-objective cost function from a comparison of each calculated trajectory to the observed trajectory;

use an evolutionary algorithm to evolve the set of initial candidate aircraft intents into an evolved set of candidate aircraft intents and repeat iterations of the evolutionary algorithm to evolve further the candidate aircraft intents of the evolved set, wherein the evolutionary algorithm uses a multi-objective cost function to obtain a cost function value that measures a goodness of each candidate aircraft intent; and

provide one or more candidate aircraft intents with the best cost function value or values respectively.

19. The tangible non-transitory computer readable medium of claim 18, wherein the candidate aircraft intents comprise threads, each thread defining a degree of freedom of the aircraft, and each thread extends from the start of the trajectory to the end of the trajectory, and

wherein instructions for generating the initial set of candidate aircraft intents comprises instructions that when executed by the computer system, causes the computer system to, for each candidate aircraft intent, fill each thread with one or more instructions thereby closing all degrees of freedom of the aircraft throughout the trajectory.

20. The tangible non-transitory computer readable medium of claim 19, wherein instructions for generating the initial set of candidate aircraft intents further comprises instructions that when executed by the computer system, causes the computer system to, for each candidate aircraft intent, fill each thread with an instruction such that each thread contains only a single instruction spanning the entire trajectory.