Proximity-based shared transportation reservations

Patent metadata

Field	Value
Publication number	US-2021014678-A1
Application number	US-201816979949-A
Country	US
Kind code	A1
Filing date	Mar 19, 2018
Priority date	Mar 19, 2018
Publication date	Jan 14, 2021
Grant date	—

Abstract

Various approaches allow for shared transportation reservations and related actions to be made based on a user's proximity to a shared transportation station. Data is received concerning the user's computing device, such as a vehicle, a mobile device, an internet-connected device, or a cellular network-connected device. Approaches can use a variety of data formats, including image data, location coordinates, or wirelessly-transmitted data. Based on such data and a criterion such as a threshold proximity to the station, the user's account status is determined and access to same authorized. Via the account, numerous actions may be taken, including automatically triggering a transport mode reservation or return, prompting the user to reserve or return the shared transportation, or debiting the user per a fee associated with the transportation reservation. Further, neural network techniques may be applied to train a model for generating related recommendations.

First claim

What is claimed is:

1 . A computer-implemented method, comprising:
receiving location coordinates associated with a geographic location of a computing device; receiving user identification information; determining a registered user from the user identification information, the registered user associated with a user account of a service provider; authorizing access to the user account; determining that the geographic location is within a threshold distance to a transport station; and triggering a transport mode reservation event in the user account.

2 . The computer-implemented method of claim 1 , wherein the transport mode reservation event comprises at least one of: finalizing a transportation reservation, debiting the user account an amount associated with the transportation reservation event, or providing a notification to confirm a transport reservation or otherwise corresponding to the transport mode reservation event.

3 . The computer-implemented method of claim 2 , wherein the notification is a prompt concerning at least one transportation reservation opportunity.

4 . The computer-implemented method of claim 1 , wherein the location coordinates are Global Positioning System (GPS) navigation system data.

5 . A computer-implemented method, comprising:
receiving data associated with a user device; determining a registered user from the data, the registered user associated with a user account of a service provider; authorizing access to the user account; determining that the user device satisfies a transport reservation criterion; and triggering a transport mode reservation event in the user account.

6 . The computer-implemented method of claim 5 , wherein the transport reservation criterion is the user device being within a threshold distance to a transport station.

7 . The computer-implemented method of claim 6 , wherein the transport station is a bicycle station.

8 . The computer-implemented method of claim 5 , wherein the transport mode reservation event comprises at least one of: finalizing a transportation reservation, debiting the user account an amount associated with the transport mode reservation event, or providing a notification to confirm a transport reservation or otherwise corresponding to the transport mode reservation event.

9 . The computer-implemented method of claim 5 , wherein the data comprises at least one of: image data obtained from a camera, location coordinates, or Bluetooth or other wirelessly-transmitted data.

10 . The computer-implemented method of claim 5 , wherein the data is image data, the method further comprising:
analyzing the image data to determine a feature vector; comparing the feature vector to a plurality of stored feature vectors; and determining a stored feature vector from the plurality of stored feature vectors that matches the feature vector to at least a threshold deviation, the stored feature vector associated with the registered user.

11 . The computer-implemented method of claim 5 , wherein the user device is at least one of:
a vehicle, a mobile device, an internet-connected device, or a cellular network-connected device.

12 . The computer-implemented method of claim 5 , further comprising:
using a trained model to generate a recommendation for transport mode reservation events.

13 . A computing system, comprising:
at least one processor; and memory including instructions that, when executed by the at least one processor, cause the computing system to:
receive data concerning a user device;
determine a registered user from the data, the registered user associated with a user account of a service provider;
authorize access to the user account;
determine that the user device satisfies a transport reservation criterion; and
trigger a transport mode reservation event in the user account.

14 . The computing system of claim 13 , wherein the transport reservation criterion is the user device being within a threshold distance to a transport station.

15 . The computing system of claim 13 , wherein the transport mode reservation event comprises at least one of: finalizing a transportation reservation, debiting the user account an amount associated with the transport mode reservation event, or providing a notification to confirm a transport reservation or otherwise corresponding to the transport mode reservation event.

Assignees

• Ford Motor Co

Inventors

• Seagraves Jamel
• Tang Chih-Wei
• Aich Sudipto
• Kock Beaudry

Classifications

• H04W12/64 Primary

  using geofenced areas · CPC title

• G06Q10/06315

  Needs-based resource requirements planning or analysis · CPC title

• H04W4/40

  for vehicles, e.g. vehicle-to-pedestrians [V2P] · CPC title

• G06Q10/02

  Reservations, e.g. for tickets, services or events · CPC title

• H04W4/029

  Location-based management or tracking services · CPC title