Roadside assistance system

• US 10,553,119 B1
• Filed: 10/04/2018
• Issued: 02/04/2020
• Est. Priority Date: 10/04/2018
• Status: Active Grant

• Current Assignee: Allstate Insurance Company (Allstate Corporation)
• Original Assignee: Allstate Insurance Company (Allstate Corporation)
• Inventors: Shah, Hiral T., Singh, Chetan Prakash, Sankara Narayanan, Subbu Arunachalam, Turnbull, Paul R., Williams, Byron J., Janvier, Nedier
• Primary Examiner(s): Vu, Quoc Thai N
• Application Number:
  US16/151,929
• Time in Patent Office: 488 Days
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G08G 1/205 Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 2015/223 Execution procedure of a spoken command
• CPC Class Codes: G10L 25/30 using neural networks
• CPC Class Codes: H04W 4/40 for vehicles, e.g. vehicle-to-pedestrians [V2P]

Abstract

According to some aspects of this disclosure a roadside assistance application programming interface (API) may allow any type of application, internet of things device, voice recognition device, and others to provide roadside assistance functionality. According to some aspects of this disclosure a device may communicate with sensors or an on-board diagnostics system of a vehicle and retrieve vehicle data. The device may recommend a service based on the vehicle data. The device may send a request for roadside assistance. The device may be used to enroll a user as a member of a roadside assistance benefits program. The above mentioned steps may all be performed via a single application running on the device. According to some aspects of this disclosure a device may process a roadside assistance request and determine a roadside assistance service provider to send to a user that requested roadside assistance.

Claims

1. A method comprising:

receiving, by a mobile device and from an on-board diagnostic system of a vehicle, vehicle information indicating a service is needed for the vehicle, wherein the mobile device is executing an application implementing a roadside assistance application programming interface (API);

displaying, on a display of the mobile device via the application, information related to the service;

receiving, by the mobile device, voice input from a user corresponding to the information;

determining, by parsing the voice input with a neural network, an intent of the voice input, wherein the intent of the voice input indicates a roadside assistance request;

sending, from the mobile device and to a roadside assistance server, the roadside assistance request, wherein the roadside assistance request comprises a type of service to be performed on the vehicle and a location of the vehicle;

receiving, from the roadside assistance server, a benefits enrollment prediction, wherein the benefits enrollment prediction is generated using machine learning;

sending, based on the benefits enrollment prediction, enrollment information to the roadside assistance server; and

receiving service information via the application, wherein the service information comprises a location of a service provider vehicle that is scheduled to respond to the roadside assistance request.

2. The method of claim 1, further comprising:

generating a feature vector based on the vehicle information;

outputting the feature vector to a recommender system; and

generating, by the recommender system, a recommended type of roadside service for the vehicle, wherein the type of service is the recommended type of roadside service.

3. The method of claim 2, wherein the vehicle information comprises tire pressure information obtained from a tire pressure sensor of the vehicle and engine speed information obtained from an engine speed sensor of the vehicle.

4. The method of claim 1, wherein the roadside assistance request further comprises a benefits enrollment request and further comprising:

receiving, by the mobile device and via the application executing on the mobile device, a notification indicating that the user has been enrolled in a benefits program and indicating a type of benefits plan in which the user is enrolled.

5. The method of claim 1, wherein the location of the vehicle is obtained from a global positioning system (GPS) of the vehicle.

6. The method of claim 1, wherein the application comprises a social media application.

7. The method of claim 1, wherein the service information further comprises an estimated time of arrival, a make, a model, and a license plate number of the service provider vehicle.

8. The method of claim 1, further comprising:

engaging in a conversation with the user via a natural language processing engine of the application, wherein the roadside assistance request is generated based on the conversation.

9. A system comprising:

a computing device associated with a vehicle and an apparatus,

wherein the computing device comprises one or more processors, and memory storing machine readable instructions that, when executed by the one or more processors of the computing device cause the computing device to;

receive, by a mobile device and from an on-board diagnostic system of a vehicle, vehicle information indicating a service is needed for the vehicle, wherein the mobile device is executing an application implementing a roadside assistance application programming interface (API);

display, on a display of the mobile device via the application, information related to the service

receive by the mobile device, voice input from a user corresponding to the information;

determine, by parsing the voice input with a neural network, an intent of the voice input, wherein the intent of the voice input indicates a roadside assistance request;

send, from the mobile device and to a roadside assistance server, the roadside assistance request, wherein the roadside assistance request comprises a type of service to be performed on the vehicle and a location of the vehicle;

receive, from the roadside assistance server, a benefits enrollment prediction, wherein the benefits enrollment prediction is generated using machine learning;

send, based on the benefits enrollment prediction, enrollment information to the roadside assistance server; and

receive service information via the application, wherein the service information comprises a location of a service provider vehicle that is scheduled to respond to the roadside assistance request; and

wherein the apparatus comprises one or more processors, and memory storing machine readable instructions that, when executed by the one or more processors, cause the apparatus to;

receive the roadside assistance request from the computing device.

10. The system of claim 9, wherein the machine readable instructions that, when executed by the one or more processors of the computing device further cause the computing device to:

generate a feature vector based on the vehicle information;

output the feature vector to a recommender system; and

generate by the recommender system, a recommended type of roadside service for the vehicle, wherein the type of service is the recommended type of roadside service.

11. The system of claim 10, wherein the vehicle information comprises tire pressure information obtained from a tire pressure sensor of the vehicle and engine speed information obtained from an engine speed sensor of the vehicle.

12. The system of claim 9, wherein the roadside assistance request further comprises a benefits enrollment request and wherein the machine readable instructions that, when executed by the one or more processors of the computing device further cause the computing device to:

receive, by the mobile device and via the application executing on the mobile device, a notification indicating that the user has been enrolled in a benefits program and indicating a type of benefits plan in which the user is enrolled.

13. The system of claim 9, wherein the location of the vehicle is received from a global positioning system (GPS) of the vehicle.

14. The system of claim 9, wherein the application comprises a social media application.

15. The system of claim 9, further comprising:

engaging in a conversation with the user via a natural language processing engine of the application, wherein the roadside assistance request is generated based on the conversation.

16. An apparatus comprising:

one or more processors; and

memory storing machine readable instructions that, when executed by the one or more processors cause the apparatus to;

receive, by a mobile device and from an on-board diagnostic system of a vehicle, vehicle information indicating a service is needed for the vehicle, wherein the mobile device is executing an application implementing a roadside assistance application programming interface (API);

display, on a display of the mobile device via the application, information related to the service;

receive, by the mobile device, voice input from a user corresponding to the information;

determine, by parsing the voice input with a neural network, an intent of the voice input, wherein the intent of the voice input indicates a roadside assistance request;

send, from the mobile device and to a roadside assistance server, the roadside assistance request, wherein the roadside assistance request comprises a type of service to be performed on the vehicle and a location of the vehicle;

receive, from the roadside assistance server, a benefits enrollment prediction, wherein the benefits enrollment prediction is generated using machine learning;

send, based on the benefits enrollment prediction, enrollment information to the roadside assistance server; and

receive service information via the application, wherein the service information comprises a location of a service provider vehicle that is scheduled to respond to the roadside assistance request.

17. The apparatus of claim 16, wherein the machine readable instructions that, when executed by the one or more processors cause the apparatus to:

generate a feature vector based on the vehicle information;

output the feature vector to a recommender system; and

generate, by the recommender system, a recommended type of roadside service for the vehicle, wherein the type of service is the recommended type of roadside service.

18. The apparatus of claim 16, wherein the vehicle information comprises tire pressure information obtained from a tire pressure sensor of the vehicle and engine speed information obtained from an engine speed sensor of the vehicle.

19. The apparatus of claim 16, wherein the location of the vehicle is obtained by the application from a global positioning system (GPS) of the vehicle.

20. The apparatus of claim 16, wherein the service information further comprises an estimated time of arrival, a make, a model, and a license plate number of the service provider vehicle.