Geohash-related location predictions

• US 10,285,014 B2
• Filed: 10/01/2018
• Issued: 05/07/2019
• Est. Priority Date: 04/04/2017
• Status: Active Grant

• Current Assignee: LYFT Incorporated
• Original Assignee: LYFT Incorporated
• Inventors: Pao, Yuanyuan, Kodesh, Snir, Chopra, Jatin, Fan, Kevin, Lin, Charlie, Shen, Limin, Levi, Dor, Haque, Asif, Baz, Zeynep Erkin
• Primary Examiner(s): Patel, Mahendra
• Application Number:
  US16/148,633
• Publication Number:
  US 20190037355A1
• Time in Patent Office: 218 Days
• Field of Search: 4554563, 4554141, 705 5, 705 13, 705 264, 705333
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/024 Guidance services
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/44 for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]

Abstract

Embodiments provide techniques, including systems and methods, for determining an estimated target pickup location for a corresponding transport request at a particular location, such as associated with a particular geohash. A requestor may send a request that is associated with a location that does not reflect the requestor'"'"'s intent regarding where they would like to be met by the provider (i.e., “picked up”). GPS inaccuracies may cause the request location to inaccurately indicate where the requestor will be; for example, the request location may be inside a building while the requestor is waiting on a curb around a far side of the building. The target pickup location allows for a requestor and a provider to meet more efficiently, reducing delay for the provider and improving the efficiency of the system by preventing provider system resources from being taken from other service areas and decreasing provider downtime upon matching.

Claims

1. A method of matching received transport requests utilizing a dynamic transportation matching system, the method comprising:

determining, based on a location associated with a computing device, prior transport data comprising at least one prior location;

weighting the at least one prior location based at least in part on a distance from the at least one prior location to the location associated with the computing device;

determining a target location based at least in part on the weighting of the at least one prior location; and

sending, by the dynamic transportation matching system, the target location to the computing device.

2. The method of claim 1, further comprising weighting the at least one prior location based at least in part on one or more additional factors.

3. The method of claim 2, wherein:

the prior transport data further includes prior weather data associated with the at least one prior location; and

weighting the at least one prior location based at least in part on the one or more additional factors comprises weighting based at least in part on the prior weather data associated with the least one prior location and current weather data associated with the location associated with the computing device.

4. The method of claim 2, wherein:

the prior transport data further includes prior time data associated with the at least one prior location; and

weighting the at least one prior location based at least in part on the one or more additional factors comprises weighting based at least in part on the prior time data associated with the at least one prior location and current time data associated with the location associated with the computing device.

5. The method of claim 2, wherein:

the prior transport data further includes prior traffic data associated with the at least one prior location; and

weighting the at least one prior location based at least in part on the one or more additional factors comprises weighting based at least in part on traffic data associated with the at least one prior location and current traffic data associated with the location associated with the computing device.

6. The method of claim 2, wherein:

the prior transport data further includes prior construction data associated with the at least one prior location; and

weighting the at least one prior location based at least in part on the one or more additional factors comprises weighting based at least in part on the prior construction data associated with the at least one prior location and current construction data associated with the location associated with the computing device.

7. The method of claim 2, wherein weighting the at least one prior location based at least in part on the one or more additional factors comprises weighting based at least in part on safety data associated with the at least one prior location.

8. The method of claim 2, further comprising:

identifying a prior target location for the at least one prior location;

determining that the prior target location is within a threshold distance of the target location; and

determining, for the prior target location within the threshold distance, that the prior target location was moved,

wherein weighting the at least one prior location based at least in part on the one or more additional factors comprises weighting the prior target location that was moved more heavily than prior locations that were not moved.

9. The method of claim 2, further comprising:

identifying, for the at least one prior location, a prior Wi-Fi network associated with the at least one prior location; and

determining, for the at least one prior location, whether the prior Wi-Fi network matches a current Wi-Fi network associated with the computing device,

wherein weighting the at least one prior location based at least in part on the one or more additional factors comprises weighting based at least in part on whether the prior Wi-Fi network matches the current Wi-Fi network associated with the computing device.

10. The method of claim 2, further comprising:

identifying, for the at least one prior location, prior authentication credentials associated with a prior computing device; and

determining, for the prior computing device, whether the prior authentication credentials match current authentication credentials associated with the computing device,

wherein weighting the at least one prior location based at least in part on the one or more additional factors comprises weighting based at least in part on whether the prior authentication credentials match the current authentication credentials associated with the computing device.

11. The method of claim 2, further comprising:

identifying, for the at least one prior location, a prior stored address associated with a prior computing device; and

determining, for the prior computing device, whether the prior stored address matches a current stored address associated with the computing device,

wherein weighting the at least one prior location based at least in part on the one or more additional factors comprises weighting based at least in part on whether the prior stored address matches the current stored address associated with the computing device.

12. A dynamic transportation matching system for matching received transport requests, the dynamic transportation system comprising:

at least one processor; and

a non-transitory computer readable medium comprising instructions that, when executed by the at least one processor, cause the system to;

determine, based on transport request information indicating a location associated with a computing device, prior transport data comprising including at least one prior location;

weight the at least one prior location based at least in part on a distance from the at least one prior location to the location associated with the computing device;

determine a target location based at least in part on the weighting of the at least one prior location; and

send the target location to the computing device.

13. The system of claim 12, further comprising instructions that, when executed by the at least one processor, cause the system to weight the at least one prior location based at least in part on one or more additional factors.

14. The system of claim 13, wherein:

the prior transport data further includes prior weather data and prior time data associated with the at least one prior location; and

weighting the at least one prior location based at least in part on the one or more additional factors comprises weighting based at least in part on the prior weather data and prior time data associated with the least one prior location and current weather data and current time data associated with the location associated with the computing device.

15. The system of claim 13, further comprising instructions that, when executed by the at least one processor, cause the system to:

identify a prior target location for the at least one prior location;

determine that the prior target location is within a threshold distance of the target location; and

determine, for the prior target location within the threshold distance, that the prior target location was moved,

wherein weighting the at least one prior location based at least in part on the one or more additional factors comprises weighting the prior target location that was moved more heavily than prior locations that were not moved.

16. A non-transitory computer readable medium for matching received transport requests associated with a dynamic transportation matching system, the non-transitory computer readable medium comprising instructions that, when executed by at least one processor, cause a computer device to:

determine, based on transport request information indicating a location associated with a computing device, prior transport data comprising at least one prior location;

weight the at least one prior location based at least in part on a distance from the at least one prior location to the location associated with the computing device;

determine a target location based at least in part on the weighting of the at least one prior location; and

send the target location to the computing device.

17. The non-transitory computer readable medium of claim 16, further comprising instructions that, when executed by at least one processor, cause the computer device to:

identify, for the at least one prior location, a prior Wi-Fi network associated with the at least one prior location; and

determine, for the at least one prior location, whether the prior Wi-Fi network matches a current Wi-Fi network associated with the computing device,

wherein weighting the at least one prior location is further based at least in part on whether the prior Wi-Fi network matches the current Wi-Fi network associated with the computing device.

18. The non-transitory computer readable medium of claim 16, wherein:

the prior transport data further includes prior weather data associated with the at least one prior location; and

weighting the at least one prior location is further based at least in part on the prior weather data associated with the least one prior location and current weather data associated with the location associated with the computing device.

19. The non-transitory computer readable medium of claim 18, wherein:

the prior transport data further includes prior time data associated with the at least one prior location; and

weighting the at least one prior location is further based at least in part on the prior time data associated with the at least one prior location and current time data associated with the location associated with the computing device.

20. The non-transitory computer readable medium of claim 19, wherein:

the prior transport data further includes prior traffic data associated with the at least one prior location; and

weighting the at least one prior location is further based at least in part on the prior traffic data associated with the at least one prior location and current traffic data associated with the location associated with the computing device.