Driver supply control

Patent metadata

Field	Value
Publication number	US-2023385978-A1
Application number	US-202318446273-A
Country	US
Kind code	A1
Filing date	Aug 8, 2023
Priority date	Dec 21, 2015
Publication date	Nov 30, 2023
Grant date	—

Abstract

A system for supply control includes an input interface and a processor. The input interface is to receive an indication of an expected event. The processor is to determine a historic event similar to the expected event, determine an expected driver demand for the expected event based at least in part on the similar historic event, and determine one or more incentives to meet the expected driver demand.

First claim

What is claimed is:

1 . A computer-implemented method comprising:
receiving, via an input interface of a driver dispatch server system, an indication of an expected event corresponding to a target region; analyzing a historical event database to select a plurality of similar historical events that satisfy a similarity threshold relative to the expected event; combining historical event data from the historical event database for the plurality of similar historical events to generate an expected number of requests from requestor mobile devices for driver mobile devices corresponding to the expected event; selecting, based on the expected number of requests from requestor mobile devices for driver mobile devices corresponding to the expected event and an incentive yield data model, a number of digital incentive notifications; transmitting, via an output interface of the driver dispatch server system for display via user interfaces of a plurality of provider mobile computing devices, the number of digital incentive notifications; based on monitoring user interactions with the number of digital incentive notifications via the plurality of provider mobile computing devices, modifying the number of digital incentive notifications transmitted by the driver dispatch server system; monitoring, via the input interface of the driver dispatch server system, a number of driver mobile computing devices during the expected event to determine a driver yield; and updating the incentive yield data model based on the number of driver mobile computing devices during the expected event reflected in the driver yield.

2 . The computer-implemented method of claim 1 , wherein selecting the plurality of similar historical events comprises:
determining similarity metrics by comparing at least one of event type, event size, or event time between the historical events and the expected event to determine similarity metric; and applying the similarity threshold to the similarity metrics to select the plurality of similar historical events.

3 . The computer-implemented method of claim 1 , wherein combining the historical event data comprises averaging the historical event data across the plurality of similar historical events to determine the expected number of requests from requestor mobile devices for driver mobile devices corresponding to the expected event.

4 . The computer-implemented method of claim 1 , further comprising generating the incentive yield model utilizing a nonlinear incentive yield function and historical yield data.

5 . The computer-implemented method of claim 1 , wherein transmitting the number of digital incentive notifications comprises:
selecting an incentive transmission time based on at least one of the target region or historical event times; and transmitting the number of digital incentive notifications according to the incentive transmission time.

6 . The computer-implemented method of claim 1 m wherein transmitting the number of digital incentive notifications comprises selecting the plurality of provider mobile computing devices based on historical driving patterns corresponding to the incentive transmission time.

7 . The computer-implemented method of claim 1 , wherein modifying the number of digital incentive notifications comprises:
determining a number of responding provider mobile computing devices of the plurality of provider mobile computing devices based on the user interactions with the plurality of digital incentive notifications; and rescinding one or more digital incentive notifications from one or more of the plurality of provider mobile computing devices based on the number of responding provider mobile computing devices.

8 . The computer-implemented method of claim 1 , wherein modifying the number of digital incentive notifications comprises transmitting an additional set of digital incentive notifications to an additional set of provider mobile computing devices based a number of responding provider mobile computing devices of the plurality of provider mobile computing devices.

9 . A system comprising:
at least one processor; and a non-transitory computer readable storage medium comprising instructions that, when executed by the at least one processor, cause the system to:
receive, via an input interface of the system, an indication of an expected event corresponding to a target region;
analyze a historical event database to select a plurality of similar historical events that satisfy a similarity threshold relative to the expected event;
combine historical event data from the historical event database for the plurality of similar historical events to generate an expected number of requests from requestor mobile devices for driver mobile devices corresponding to the expected event;
select, based on the expected number of requests from requestor mobile devices for driver mobile devices corresponding to the expected event and an incentive yield data model, a number of digital incentive notifications;
transmit, via an output interface of the system for display via user interfaces of a plurality of provider mobile computing devices, the number of digital incentive notifications;
based on monitoring user interactions with the number of digital incentive notifications via the plurality of provider mobile computing devices, modify the number of digital incentive notifications transmitted by system;
monitor, via the input interface of the system, a number of driver mobile computing devices during the expected event to determine a driver yield; and
update the incentive yield data model based on the number of driver mobile computing devices during the expected event reflected in the driver yield.

10 . The system of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the system to select the plurality of similar historical events by:
determining similarity metrics by comparing at least one of event type, event size, or event time between the historical events and the expected event to determine similarity metric; and applying the similarity threshold to the similarity metrics to select the plurality of similar historical events.

11 . The system of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the system to combine the historical event data by averaging the historical event data across the plurality of similar historical events to determine the expected number of requests from requestor mobile devices for driver mobile devices corresponding to the expected event.

12 . The system of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the system to generate the incentive yield model utilizing a nonlinear incentive yield function and historical yield data.

13 . The system of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the system to transmit the number of digital incentive notifications by:
selecting an incentive transmission time based on at least one of the target region or historical event times; and transmitting the number of digital incentive notifications according to the incentive transmission time.

14 . The system of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the system to transmit the number of digital incentive notifications by selecting the plurality of provider mobile computing devices based on historical driving patterns corresponding to the incentive transmission time.

15 . The system of

Assignees

• Lyft Inc

Inventors

• Fan Kevin
• Lauzier Ben

Classifications

• G06Q10/40

  Business processes related to social networking or social networking services · CPC title

• G06Q50/30 Primary

  Physics · mapped topic

• G06Q50/01

  Physics · mapped topic

• G06Q10/06315

  Needs-based resource requirements planning or analysis · CPC title

• G06Q30/0208

  Trade or exchange of goods or services in exchange for incentives or rewards · CPC title