Providing indicators of availability in a shared vehicle environment

Patent metadata

Field	Value
Publication number	US-11615710-B2
Application number	US-201816979556-A
Country	US
Kind code	B2
Filing date	Mar 16, 2018
Priority date	Mar 16, 2018
Publication date	Mar 28, 2023
Grant date	Mar 28, 2023

Abstract

An intelligent bicycle sharing system, or other vehicle sharing system, is able to provide helpful bicycle availability indications based on historical data and user proximity. Historical data can be collected over time as users use the bicycle sharing system. For example, the historical data may include how many bicycles are checked at out a given time and how many remain at a given location. In some embodiments, an indication may be provided to the user as the user approaches the vehicle sharing system. The indication may provide information regarding the availability of bicycles.

First claim

What is claimed is:

1. A system, comprising:
at least one computing device processor; and
a memory device including instructions that, when executed by the at least one computing device processor, cause the system to:
determine a user proximity to a vehicle sharing system, the vehicle sharing system comprising a plurality of resources, and the user proximity corresponding to a user distance from the vehicle sharing system;
obtain historical data collected from the vehicle sharing system, the historical data including a total number of resources available during a time period;
train a machine learning-based model using the historical data;
determine an availability of a resource of the plurality of resources based at least in part on the historical data and the machine learning-based model;
generate an availability response indicative of the availability of the resource; and
provide the availability response to an indicator, the indicator alerting the user as to the availability of the resource.

2. The system of claim 1 , wherein the instructions when executed further cause the system to:
obtain maintenance data collected from the vehicle sharing system, the maintenance data including at least one of past maintenance activity, present maintenance activity, or future maintenance activity for the plurality of resources;
train the machine learning-based model using the maintenance data; and
update the availability based at least in part on the maintenance data and the machine learning-based model.

3. The system of claim 1 , wherein the vehicle sharing system includes a docked bicycle sharing system comprising a plurality of docking stations and a plurality of bicycles, and wherein the user proximity is determined by receiving a signal from a user device of a user over a near field communication (NFC) protocol.

4. The system of claim 1 , wherein the user proximity is determined by:
obtaining an image from an area proximate the vehicle sharing station;
processing the image using one or more object detection algorithms to identify a human; and
upon detection of the human, determining the user distance from the vehicle sharing station.

5. A computer-implemented method, comprising:
determining a user proximity to a vehicle sharing system, the vehicle sharing system comprising a plurality of resources, and the user proximity comprising at least a distance of a user from the vehicle sharing system;
obtaining historical data collected from the vehicle sharing system, the historical data including a quantity of resources physically located at the vehicle sharing system;
training a machine learning-based model using the historical data;
determining an availability for a resource of the plurality of resources based at least in part on the historical data and the machine learning-based model; and
providing an indication to the user of the availability, the indication notifying the user of the availability from a notification distance, the notification distance being greater than a visual distance where the user could visually identify the availability.

6. The method of claim 5 , the method further comprising:
obtaining maintenance data collected from the vehicle sharing system, the maintenance data comprising information regarding future maintenance activity, past maintenance activity, or present maintenance activity for the plurality of resources; and
training the machine learning-based model using the maintenance data, wherein the availability is updated based at least in part on the maintenance data and the machine learning-based model.

7. The method of claim 5 , where determining the user proximity further comprises receiving a signal, by the vehicle sharing system, from a user device of the user, the signal being transmitted via a near field communication (NFC) protocol.

8. The method of claim 5 , wherein the plurality of resources includes a plurality of vehicle docking spots, an individual vehicle docking spot associated with one of the resources, the method further comprising:
recommending a resource of the plurality of resources to the user based on the availability and a recommendation model trained, via a neural network, using a number of input-output pairs; and
making the recommendation of the resource of the plurality of resources based at least in part on a proximity of the resource to another resource of the plurality of resources, wherein the resources is selected such that the resource has the greatest distance between the resource and the other resources of the plurality of resources.

9. The method of claim 5 , wherein determining the user proximity further comprises:
obtaining an image from an area proximate the vehicle sharing station;
processing the image using one or more object detection algorithms to identify a human; and
upon detection of the human, determining the distance of the user from the vehicle sharing station.

10. The method of claim 5 , wherein the indication comprises an auditory indication, a visual indication, a haptic indication, or a combination thereof.

11. The method of claim 5 , wherein the plurality of resources includes a plurality of vehicle docking spots, an individual vehicle docking spot associated with one of the resources, and the indication is mounted to at least one of the vehicle docking spots or the vehicle.

12. The method of claim 5 , wherein the indication is transmitted to a user device associated with the user.

13. The method of claim 5 , further comprising:
obtaining maintenance data collected from the vehicle sharing system, the maintenance data comprising a plurality of images of the plurality of resources and information regarding future maintenance activity, past maintenance activity, and present maintenance activity for the plurality of resources;
training the machine learning-based model using at least the maintenance data; and
predicting future maintenance activities using the machine learning-based model.

14. The method of claim 5 , further comprising:
authorizing a resource for check out to the user; and
updating the historical data based at least in part on the resource being checked out by the user.

Assignees

• Ford Motor Co

Inventors

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

Classifications

• H04W4/029

  Location-based management or tracking services · CPC title

• G06Q10/06315

  Needs-based resource requirements planning or analysis · CPC title

• G06Q10/06311

  Scheduling, planning or task assignment for a person or group · CPC title

• G08G1/205 Primary

  Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental · CPC title

• G06Q10/02

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