IP Library Patent Application 17662091
Patent Application
App. No. 17/662,091

VALIDATION OF COST-OPTIMAL MINIMUM TURN TIMES

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Quick Facts
Patent No.
US None
App. No.
17/662,091
Abstract

A computer-implemented method for determining a cost-optimal minimum turn time of a subject vehicle at a station includes receiving historical data via a processor, including actual past turn times and available turn times of the subject vehicle at the station. The method also includes creating a two-dimensional (2D) scatter plot of the historical data from a plurality of data points, identifying an inflection point on the 2D scatter plot as a point of intersection of two straight lines, and determining the cost-optimal minimum turn time using the inflection point. A scheduling action of the subject vehicle is executed via the processor using the cost-optimal minimum turn time. A system for performing the method includes the processor, a database of the actual past turn times and available turn times, and instructions recorded in memory. Execution of the instructions causes the processor to perform the method.

Claims (38)

1 . A method for determining a cost-optimal minimum turn time of a subject vehicle at a station, comprising:

receiving historical data via a processor, the historical data including a set of actual past turn times of the subject vehicle at the station and available turn times of the subject vehicle at the station;

creating a two-dimensional (2D) scatter plot of the historical data via the processor, wherein the 2D scatter plot is comprised of a plurality of data points;

identifying an inflection point on the 2D scatter plot as a point of intersection of two straight lines on the 2D scatter plot;

determining the cost-optimal minimum turn time via the processor using the inflection point; and

executing a scheduling action of the subject vehicle via the processor using the cost-optimal minimum turn time.

2 . The method of claim 1 , further comprising performing a Hough transform on the plurality of data points via the processor to thereby derive the two straight lines.

3 . The method of claim 1 , further comprising deriving the two straight lines using an iterative procedure, including applying a predetermined static slope parameter and a dynamic intercept parameter.

4 . The method of claim 3 , wherein the predetermined static slope parameter is 0.41.

5 . The method of claim 1 , wherein executing the scheduling action of the subject vehicle includes displaying the cost-optimal minimum turn time on a heatmap chart, the heatmap chart including a color-coded background indicative of a relative difference between the cost-optimal minimum turn time and an expected minimum turn time provided by a manufacturer of the subject vehicle.

6 . The method of claim 1 , the subject vehicle is an aircraft, and the station is an airport or a terminal thereof.

7 . The method of claim 6 , wherein executing the scheduling action using the cost-optimal minimum turn time includes modeling flight delay propagation through a plurality of airports.

8 . The method of claim 7 , wherein modeling the flight delay propagation through the plurality of airports includes performing a Gumbel approximation.

9 . The method of claim 5 , wherein executing the scheduling action includes using the cost-optimal minimum turn time to determine a future impact on a predicted reliability level of the expected minimum turn time.

10 . The method of claim 1 , wherein executing the scheduling action includes rescheduling a departure of the subject vehicle from the station.

11 . A scheduling system comprising:

a processor;

a database on which is recorded historical data, including a set of actual turn times of a subject vehicle at a station and available turn times of the subject vehicle at the station; and

instructions for determining a cost-optimal minimum turn time of the subject vehicle at the station, wherein execution of the instructions by the processor causes the processor to:

retrieve the historical data from the database;

create a two-dimensional (2D) scatter plot of the historical data, wherein the 2D scatter plot is comprised of a plurality of data points;

identify an inflection point on the 2D scatter plot as a point of intersection of two straight lines on the 2D scatter plot;

determine the cost-optimal minimum turn time using the inflection point; and

execute a scheduling action of the subject vehicle using the cost-optimal minimum turn time.

12 . The system of claim 11 , wherein the execution of the instructions by the processor causes the processor to perform a Hough transform on the plurality of data points to thereby derive the two straight lines.

13 . The system of claim 11 , wherein the execution of the instructions by the processor causes the processor to derive the two straight lines using an iterative procedure, including applying a predetermined static slope parameter and a dynamic intercept parameter.

14 . The system of claim 13 , wherein the static slope parameter is 0.41.

15 . The system of claim 11 , further comprising a display screen, wherein executing the scheduling action of the subject vehicle using the cost-optimal minimum turn time includes displaying the cost-optimal minimum turn time on a heatmap chart via the display screen, the heatmap chart having a color-coded background indicative of a relative difference between the cost-optimal minimum turn time and an expected minimum turn time of the subject vehicle at the station.

16 . The system of claim 11 , the subject vehicle is an aircraft, and the station is an airport or a terminal thereof.

17 . The system of claim 16 , wherein the scheduling action includes modeling propagation of a flight delay at the airport through a plurality of airports.

18 . A method for determining a cost-optimal minimum turn time of an aircraft at an airport, comprising:

receiving historical data via a processor, the historical data including a set of actual turn times at the airport and available turn times at the airport;

creating a two-dimensional (2D) scatter plot of the historical data via the processor, wherein the 2D scatter plot is comprised of a plurality of data points;

identifying an inflection point on the 2D scatter plot as a point of intersection of two straight lines on the 2D scatterplot, including deriving the two straight lines using an iterative procedure by applying a static slope parameter of 0.41 and a dynamic intercept parameter;

determining the cost-optimal minimum turn time via the processor using the inflection point; and

executing a scheduling action of the aircraft using the cost-optimal minimum turn time, including rescheduling a departure of the aircraft based on the cost-optimal minimum turn time.

19 . The method of claim 18 , wherein executing the scheduling action of the aircraft using the cost-optimal minimum turn time includes displaying the cost-optimal minimum turn time on a heatmap chart via a display screen, the heatmap chart having a color-coded background indicative of a relative difference between the cost-optimal minimum turn time and an expected minimum turn time provided by a manufacturer of the aircraft.

20 . The method of claim 18 , wherein executing the scheduling action includes using the cost-optimal minimum turn time to schedule a crew pairing of the aircraft.

Assignments (5)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 3, 2026
From: THE BOEING COMPANY
To: BOEING DIGITAL SOLUTIONS, INC.
Reel/Frame 075426/0001 →
CHANGE OF NAME Recorded Apr 3, 2026
From: BOEING DIGITAL SOLUTIONS, INC.
To: JEPPESEN FOREFLIGHT, INC.
Reel/Frame 075339/0227 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 25, 2026
From: THE BOEING COMPANY
To: JEPPESEN FOREFLIGHT, INC. (F/K/A BOEING DIGITAL SOLUTIONS, INC.)
Reel/Frame 074967/0544 →
SECURITY INTEREST Recorded Nov 17, 2025
From: FOREFLIGHT LLC; JEPPESEN FOREFLIGHT, INC.
To: APOLLO ADMINISTRATIVE AGENCY LLC, AS COLLATERAL AGENT
Reel/Frame 073622/0920 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 5, 2022
From: BASANETS, OLEKSANDR; SHARMA, DHRUV R.
To: THE BOEING COMPANY
Reel/Frame 059823/0700 →