METHOD, SYSTEM AND PROCESSOR-READABLE MEDIA FOR ESTIMATING AIRPORT USAGE DEMAND

• US 20160350770A1
• Filed: 06/01/2015
• Published: 12/01/2016
• Est. Priority Date: 06/01/2015
• Status: Active Grant

• Current Assignee: Conduent Business Services, LLC (Conduent, Inc.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: de Souza, Cesar Roberto, Ulloa Paredes, Luis Rafael, Chidlovskii, Boris, Ciriza, Victor
• Granted Patent: US 9,715,695 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

Methods and systems for estimating airport usage demand. Airport parking traffic usage data and flight-time table data can be compiled with respect to an airport (or more than one airport). The airport parking traffic usage data and flight-time table data can be analyzed using an efficient time matching approach (e.g., a time segment matching algorithm). An efficient method to match passengers and flights is introduced. Passenger behavior can be estimated with respect to the airport based on the airport parking traffic usage data and flight-time table data.

Claims

1. A method for estimating airport usage demand, comprising:

compiling in an electronic database airport parking traffic usage data and flight-time table data with respect to at least one airport, wherein said airport parking traffic usage data includes a distribution of parking events associated with said at least one airport and wherein said flight-time table data includes flight data comprising arrival flight information including a total number of arriving flights, flight arrival times, departure flight information including a total number of departing flights, flight departure times, and departure flight maximum capacities including a total number of passengers for each departing flight;

analyzing said airport parking traffic usage data and said flight-time table data contained in said electronic database using a time matching approach comprising processing an efficient time matching algorithm comprising a segment matching algorithm with said flight-time table data and said traffic usage data utilizing a processor of a data-processing system that is operably connected to said electronic database; and

estimating with a processor of a data-processing system, passenger behavior with respect to said at least one airport based on said airport parking traffic usage data and said flight-time table data, in response to analyzing said airport parking traffic usage data and said flight-time data contained in said electronic database, wherein said estimating includes inferring an amount of passengers that took a parking flight in response to analyzing said distribution of parking events.

2. The method of claim 1 further comprising determining an alignment of said flight data and parking data comprising said distribution of parking events in response to analyzing said airport parking traffic usage data and said flight-time table data using said time matching approach.

3. The method of claim 2 further comprising estimating said passenger behavior with respect to said at least one airport based on said alignment of said flight data and said parking data.

4. The method of claim 1 further comprising:

determining an alignment of said flight data and said parking data in response to analyzing said airport parking traffic usage data and flight-time table data using said time matching approach; and

estimating said passenger behavior with respect to said at least one airport based on said alignment of said flight data and said parking data.

6. The method of claim 1 wherein said efficient time matching algorithm comprises said segment matching algorithm with linearithmic average time complexity.

5. (canceled)

7. (canceled)

8. A method of modeling airport usage demand, comprising:

providing an electronic database of past and future departing and arriving flights from at least one airport and an electronic database of historical parking data with respect to said at least one airport, wherein said historic parking data includes a distribution of parking events associated with said at least one airport and said past and future departing and arriving flights includes information comprising a total number of arriving flight, flight arrival times, departure flight information including a total number of departing flights, flight departure times, and departure flight maximum capacities including a total number of passengers for each departing flight;

storing said electronic database in a memory of a computer; and

generating a model of airport usage demand with respect to said at least one airport by processing information contained in said database of past and future departing and arriving flights and in said database of historical parking data and based on a processed match between said historical parking data and said past and future departing and arriving flights using a time matching algorithm comprising a segment matching algorithm.

9. The method of claim 8 wherein said model after being processed by a processor infers how many passengers took a particular flight by analyzing a distribution of parking events with respect to said at least one airport and based on said information contained in said database of past and future departing and arriving flights and said database of historical parking data.

10. The method of claim 8 further comprising estimating for a particular flight with respect to said at least one airport, and based on said model, a percentage of users who likely parked cars in airport parking at said at least one airport and a percentage of users who did not.

11. The method of claim 8 further comprising developing said match based on viewing a flux of passengers within said at least one airport as a mixture distribution wherein each component of said mixture distribution represents at least one flight with respect to said at least one airport and wherein said at least one flight is either an arrival, a departure, or both.

12. The method of claim 8 wherein said historical parking data is derived from an off-street parking lot composed of distinct parking zones with different pricing strategies and physical characteristics, surrounding said at least one airport.

13. The method of claim 8 wherein data associated with said match is employed to create a generative model of parking events that is queried to generate new parking event samples, wherein said model comprises a generative model.

14. (canceled)

15. (canceled)

16. (canceled)

17. (canceled)

18. (canceled)

19. (canceled)

20. (canceled)

21. A system for estimating airport usage demand, said system comprising:

at least one processor; and

a non-transitory computer-usable medium embodying computer program code, said computer-usable medium capable of communicating with said at least one processor, said non-transitory computer program code comprising instructions executable by said at least one processor and configured for;

compiling in an electronic database airport parking traffic usage data and flight-time table data with respect to at least one airport, wherein said airport parking traffic usage data includes a distribution of parking events associated with said at least one airport and wherein said flight-time table data includes flight data comprising arrival flight information including a total number of arriving flights, flight arrival times, departure flight information including a total number of departing flights, flight departure times, and departure flight maximum capacities including a total number of passengers for each departing flight;

analyzing said airport parking traffic usage data and said night-time table data contained in said electronic database using a time matching approach comprising processing an efficient time matching algorithm comprising a segment matching algorithm with said flight-time table data and said traffic usage data utilizing a processor of a data-processing system that is operably connected to said electronic database; and

estimating with a processor of a data-processing system, passenger behavior with respect to said at least one airport based on said airport parking traffic usage data and said flight-time table data, in response to analyzing said airport parking traffic usage data and said flight-time data contained in said electronic database, wherein said estimating includes inferring an amount of passengers that took a parking flight in response to analyzing said distribution of parking events.

22. The system of claim 21 wherein said instructions are further configured for determining an alignment of said flight data and parking data comprising said distribution of parking events in response to analyzing said airport parking traffic usage data and said flight-time table data using said time matching approach.

23. The system of claim 22 further comprising estimating said passenger behavior with respect to said at least one airport based on said alignment of said flight data and said parking data.

24. The system of claim 21 wherein said instructions are further configured for:

determining an alignment of said flight data and said parking data in response to analyzing said airport parking traffic usage data and flight-time table data using said time matching approach; and

estimating said passenger behavior with respect to said at least one airport based on said alignment of said flight data and said parking data.

25. The system of claim 21 wherein said efficient time matching algorithm comprises said segment matching algorithm with linearithmic average time complexity.

26. The system of claim 21 wherein said airport parking traffic usage data includes historical parking data derived from an off-street parking lot composed of distinct parking zones with different pricing strategies and physical characteristics, surrounding said at least one airport.

27. The system of claim 24 wherein said efficient time matching algorithm comprises said segment matching algorithm with linearithmic average time complexity.

28. The system of claim 26 wherein said efficient time matching algorithm comprises said segment matching algorithm with linearithmic average time complexity.

29. The system of claim 28 further comprising estimating said passenger behavior with respect to said at least one airport based on said alignment of said flight data and said parking data.