Machine learning method and system for executing remote commands to control functions of a vehicle

Patent metadata

Field	Value
Publication number	US-11586159-B2
Application number	US-201916259804-A
Country	US
Kind code	B2
Filing date	Jan 28, 2019
Priority date	Jan 28, 2019
Publication date	Feb 21, 2023
Grant date	Feb 21, 2023

Abstract

In an exemplary embodiment, a vehicle system is provided that includes a sensor, a memory, and a processor. The sensor is configured to at least facilitate obtaining vehicle data pertaining to one or more conditions of the vehicle. The memory is configured to at least facilitate storing historical data pertaining to a user's operation of the vehicle. The processor is coupled to the sensor and the memory, and is configured to at least facilitate: (i) generating one or more predictions of one or more needs for the user, using the vehicle data and the historical data as inputs for a machine learning model; and (ii) providing instructions to implement a vehicle action that accomplishes the one or more needs for the user based on the generated predictions via the machine learning model.

First claim

What is claimed is:

1. A method comprising:
obtaining vehicle data pertaining to one or more conditions of a vehicle;
obtaining historical data pertaining to a user's operation of the vehicle;
generating one or more predictions of one or more needs for the user, via a processor, using the vehicle data and the historical data as inputs for a machine learning model;
providing instructions, via the processor, to implement a vehicle action that accomplishes the one or more needs for the user based on the generated predictions via the machine learning model;
determining a target destination for the vehicle;
determining, using the vehicle data, whether a particular vehicle action is required for the vehicle to reach the target destination; and
providing a notification, to the user, recommending performance of the vehicle action, when it is determined that the particular vehicle action is required for the vehicle to reach the target destination.

2. The method of claim 1 , wherein:
the step of obtaining the historical data comprises obtaining a driving history for the user;
the step of generating one or more predictions comprises predicting when the user will next be using the vehicle, based on the driving history; and
the step of providing the instructions comprises providing the instructions, to implement the vehicle action, about when it is predicted that the user will next be using the vehicle.

3. The method of claim 2 , wherein the step of providing the instructions comprises providing instructions for starting an engine of the vehicle and controlling an environmental control system for the vehicle, about when it is predicted that the user will next be using the vehicle.

4. The method of claim 3 , wherein:
the step of obtaining the vehicle data comprises obtaining an external temperature that is external to the vehicle; and
the step of providing the instructions comprises providing instructions for starting the engine of the vehicle and controlling the environmental control system for the vehicle to attain a desired temperature inside the vehicle based on the external temperature, about when it is predicted that the user will next be using the vehicle.

5. The method of claim 3 , further comprising:
determining whether the vehicle is disposed inside a garage, based on the vehicle data;
wherein the step of providing the instructions comprises providing instructions for starting the engine of the vehicle and controlling the environmental control system for the vehicle, only if the vehicle is not disposed inside the garage.

6. The method of claim 1 , wherein the step of determining the target destination comprises determining the target destination based on the historical data.

7. The method of claim 1 , wherein:
the step of determining whether the vehicle action is required comprises determining whether a fuel refill is required for the vehicle to reach the target destination; and
the step of providing the notification comprises notifying the user that the fuel refill is recommended, when it is determined that the fuel refill is required for the vehicle to reach the target destination.

8. The method of claim 1 , wherein:
the step of determining whether the vehicle action is required comprises determining whether a battery charge is required for the vehicle to reach the target destination; and
the step of providing the notification comprises notifying the user that the battery charge is recommended, when it is determined that the battery charge is required for the vehicle to reach the target destination.

9. A system comprising:
a data module configured to at least facilitate:
obtaining vehicle data pertaining to one or more conditions of a vehicle; and
obtaining historical data pertaining to a user's operation of the vehicle; and

a processing module that is coupled to the data module and configured to at least facilitate, via a processor:
generating one or more predictions of one or more needs for the user, via a processor, using the vehicle data and the historical data as inputs for a machine learning model;
providing instructions, via the processor, to implement a vehicle action that accomplishes the one or more needs for the user based on the generated predictions via the machine learning model;
determining a target destination for the vehicle;
determining, using the vehicle data, whether a particular vehicle action is required for the vehicle to reach the target destination; and
providing a notification, to the user, recommending performance of the vehicle action, when it is determined that the particular vehicle action is required for the vehicle to reach the target destination.

10. The system of claim 9 , wherein:
the data module is configured to at least facilitate obtaining a driving history for the user; and
the processing module is configured to at least facilitate:
predicting when the user will next be using the vehicle, based on the driving history; and
providing the instructions, to implement the vehicle action, about when it is predicted that the user will next be using the vehicle.

11. The system of claim 10 , wherein the processing module is configured to at least facilitate providing instructions for starting an engine of the vehicle and controlling an environmental control system for the vehicle, about when it is predicted that the user will next be using the vehicle.

12. The system of claim 11 , wherein:
the data module is configured to at least facilitate obtaining an external temperature that is external to the vehicle; and
the processing module is configured to at least facilitate providing the instructions for starting the engine of the vehicle and controlling the environmental control system for the vehicle to attain a desired temperature inside the vehicle based on the external temperature, about when it is predicted that the user will next be using the vehicle.

13. The system of claim 11 , wherein the processing module is configured to at least facilitate:
determining whether the vehicle is disposed inside a garage, based on the vehicle data; and
providing the instructions for starting the engine of the vehicle and controlling the environmental control system for the vehicle, only if the vehicle is not disposed inside the garage.

14. The system of claim 9 , wherein the processing module is configured to at least facilitate determining the target destination based on the historical data.

15. The system of claim 9 , wherein the processing module is configured to at least facilitate:
determining whether a fuel refill is required for the vehicle to reach the target destination; and
notifying the user that the fuel refill is recommended, when it is determined that the fuel refill is required for the vehicle to reach the target destination.

16. The system of claim 9 , wherein the processing module is configured to at least facilitate:
determining whether a battery charge is required for the vehicle to reach the target destination; and
notifying the user that the battery charge is recommended, when it is determined that the battery charge is required for the vehicle to reach the target destination.

17. A vehicle system comprising:
a sensor configured to at least facilitate obtaining vehicle data pertaining to one or more conditions of the vehicle;
a memory configured to at least facilitate storing historical data pertaining to a user's operation of the vehicle; and
a processor that is coupled to the sensor and the memory, and that is configured to at least facilitate:
generating one or more predict

Assignees

• Gm Global Tech Operations Llc

Inventors

• Jaggi Kunal
• Goyal Anurag
• Sarma Bhargavi

Classifications

• B60H1/0073

  Control systems or circuits characterised by particular algorithms or computational models, e.g. fuzzy logic or dynamic models · CPC title

• G06N20/00

  Machine learning · CPC title

• G05B13/0265 Primary

  the criterion being a learning criterion · CPC title

• B67D7/08

  Arrangements of devices for controlling, indicating, metering or registering quantity or price of liquid transferred (arrangement of flow- or pressure-control valves B67D7/36; computing, calculating, counting G06; coin-freed apparatus for dispensing fluids G07F13/00; prepayment devices for metering liquids G07F15/00) · CPC title

• B60H1/00657 Primary

  Remote control devices · CPC title