Crowd sourced optimization of vehicle performance based on cloud based data

• US 9,892,572 B2
• Filed: 10/27/2016
• Issued: 02/13/2018
• Est. Priority Date: 10/22/2013
• Status: Active Grant

• Current Assignee: LYFT Incorporated
• Original Assignee: AT&T Intellectual Property I LP (AT&T, Inc.)
• Inventors: Marathe, Nikhil S., Baldwin, Christopher
• Primary Examiner(s): PHAM, TOAN NGOC
• Application Number:
  US15/336,149
• Publication Number:
  US 20170046885A1
• Time in Patent Office: 474 Days
• Field of Search: 340905, 340601, 340438, 340531, 3405391, 340439, 705 1464, 705 1458, 707706, 707802, 707E17108, 701 314, 701 29, 701 33, 701 144
• CPC Class Codes: G07C 5/02 Registering or indicating driving, working, idle, or waiting time only apparatus forming part of taximeters G07B13/00
• CPC Class Codes: G07C 5/08 Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005
• CPC Class Codes: G08G 1/0967 Systems involving transmission of highway information, e.g. weather, speed limits transmission of navigation instructions to the vehicle G08G1/0968
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks

Abstract

Tracking intrinsic and extrinsic vehicle parameters for optimizing vehicle performance is presented herein. A method can include consolidating sets of data associated with a vehicle to generate a model; generating, using the model, recommendation data representing a recommendation associated with an operation of the vehicle; and in response to receiving a request from a device of the vehicle corresponding to the operation of the vehicle, sending, based on the request, a message comprising the recommendation directed to the device of the vehicle. In an example, the method can further include determining, based on crowdsourced data representing the characteristic of the element of the vehicle, whether the characteristic satisfies a defined condition with respect to the operation of the vehicle.

Claims

1. A method, comprising:

in response to evaluating crowdsourced data for a vehicle representative of feedback that has been obtained via network devices, generating, by a system comprising a processor, recommendation data representative of a collaborative recommendation for the vehicle; and

after sending a message comprising the collaborative recommendation directed to a device of the vehicle, determining, by the system, whether the message has been received by the device of the vehicle.

2. The method of claim 1, further comprising:

in response to determining that the message has been received by the device of the vehicle, determining, by the system, whether the collaborative recommendation has been implemented.

3. The method of claim 2, wherein the determining whether the collaborative recommendation has been implemented comprises determining, based on sensor data that has been received from the device, whether the collaborative recommendation has been implemented.

4. The method of claim 2, wherein the determining whether the collaborative recommendation has been implemented comprises determining, based on a confirmation message representative of an input of an occupant of the vehicle, whether the collaborative recommendation has been implemented.

5. The method of claim 2, further comprising:

in response to determining that the collaborative recommendation has not been implemented, modifying, by the system, future recommendations.

6. The method of claim 1, wherein the sending of the message comprises:

predicting, using the crowdsourced data, that the device of the vehicle will send a request corresponding to an operation of the vehicle; and

in response to the predicting, sending the message directed to the device of the vehicle.

7. The method of claim 1, wherein the evaluating the crowdsourced data comprises:

consolidating the crowdsourced data into a data structure representing a model that associates a characteristic of an element of the vehicle with the collaborative recommendation.

8. The method of claim 7, wherein the consolidating comprises:

receiving, from devices of vehicles comprising the vehicle, respective sensor data associated with the characteristic; and

generating the data structure using the respective sensor data.

9. The method of claim 7, wherein the consolidating comprises:

receiving information representing a driving condition with respect to an operation of the vehicle; and

generating the data structure using the information representing the driving condition.

10. The method of claim 1, wherein the evaluating the crowdsourced data comprises:

receiving network based communications representing a characteristic of the vehicle from a group of the network devices via an Internet based interface; and

generating a data structure representing a model that associates the characteristic with the collaborative recommendation.

11. A system, comprising:

a processor, and

a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising;

based on data that has been obtained via network based communications representing a characteristic of a vehicle, generating a collective recommendation for the vehicle; and

in response to sending the collective recommendation directed to a device of the vehicle, determining whether the collective recommendation has been received by the device of the vehicle.

12. The system of claim 11, wherein the operations further comprise:

in response to determining that the collective recommendation has been received by the device of the vehicle, determining whether the collective recommendation has been implemented.

13. The system of claim 11, wherein the generating the collective recommendation comprises:

generating, based on the data, a model associating the characteristic of the vehicle with the collective recommendation.

14. The system of claim 11, wherein the operations further comprise:

receiving the data from respective devices via an interface to a wide area network.

15. The system of claim 11, wherein the generating the collective recommendation comprises:

receiving, from the device of the vehicle, sensor data representing the characteristic; and

determining, based on the sensor data, whether the characteristic satisfies a defined condition with respect to the vehicle.

16. The system of claim 15, wherein the determining whether the characteristic satisfies the defined condition comprises:

in response to determining, based on the sensor data, that the characteristic satisfies the defined condition with respect to the vehicle, performing the generating the collective recommendation.

17. A machine-readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising:

based on data representing a characteristic of a vehicle that has been solicited from contributor devices via an Internet based interface, creating a recommendation with respect to the vehicle; and

in response to sending the recommendation directed to a device of the vehicle, receiving feedback data representing whether the recommendation has been received.

18. The machine-readable storage medium of claim 17, wherein the creating the recommendation comprises:

in response to determining, based on the data, that the characteristic satisfies a defined condition with respect to an operation of the vehicle, performing the creating the recommendation.

19. The machine-readable storage medium of claim 18, wherein the data comprises sensor data, and wherein the creating the recommendation comprises:

receiving, from the device of the vehicle, the sensor data; and

in response to determining, based on the sensor data, that the characteristic satisfies a defined condition with respect to an operation of the vehicle, performing the creating the recommendation.

20. The computer-readable storage device of claim 17, wherein the operations further comprise:

in response to determining that the recommendation has been received, determining whether the recommendation has been implemented.