PROACTIVE AUTOCOMPLETE OF A USER'S IN-VEHICLE OPERATIONS

• US 20160280220A1
• Filed: 03/23/2015
• Published: 09/29/2016
• Est. Priority Date: 03/23/2015
• Status: Active Grant

• Current Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Original Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Inventors: Parundekar, Rahul
• Granted Patent: US 9,688,281 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60Q 1/143 combined with another condition, e.g. using vehicle recognition from camera images or activation of wipers
• CPC Class Codes: B60Q 2300/312 Adverse weather
• CPC Class Codes: B60S 1/0818 including control systems responsive to external conditions, e.g. by detection of moisture, dirt or the like
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 40/08 related to drivers or passengers
• CPC Class Codes: B60W 50/0098 Details of control systems ensuring comfort, safety or stability not otherwise provided for
• CPC Class Codes: B60W 50/10 Interpretation of driver requests or demands

Abstract

The disclosure includes a method for autocompleting an in-vehicle operation that includes monitoring sensors for sensor data. The method includes determining an occurrence of an initial vehicle operation performed by a user based on the sensor data. The method includes determining a vehicle task from a digitally stored dataset based on the initial vehicle operation. The method includes determining a next vehicle operation to autocomplete based on the vehicle task. The method includes autocompleting the next vehicle operation. The method includes determining whether the vehicle task is complete.

Claims

1. A method for autocompleting an in-vehicle operation, the method comprising:

monitoring sensors for sensor data;

determining an occurrence of an initial vehicle operation performed by a user based on the sensor data;

determining a vehicle task from a digitally stored dataset based on the initial vehicle operation;

determining a next vehicle operation to autocomplete based on the vehicle task;

autocompleting the next vehicle operation; and

determining whether the vehicle task is complete.

2. The method of claim 1, further comprising responsive to the vehicle task failing to be complete, determining an additional vehicle operation to autocomplete based on the vehicle task, autocompleting the additional vehicle operation, and repeating until the vehicle task is complete.

3. The method of claim 1, further comprising:

determining a confidence factor that indicates a likelihood that the initial vehicle operation performed by the user was properly determined; and

wherein determining the vehicle task is also based on the confidence factor exceeding a threshold value.

4. The method of claim 1, further comprising:

determining a confidence factor that indicates a likelihood that the vehicle task was properly determined from the digitally stored dataset and the initial vehicle operation; and

wherein determining the next vehicle operation is also based on the confidence factor exceeding a threshold value.

5. The method of claim 1, wherein the sensors include in-vehicle sensors that are used to determine the occurrence of the initial vehicle operation performed by the user.

6. The method of claim 1, further comprising:

receiving weather data or traffic data from a network; and

determining a next vehicle task based on the weather data or the traffic data.

7. The method of claim 1, wherein the sensors detect an environmental condition and the vehicle task is based on the environmental condition.

8. The method of claim 1, further comprising:

determining an occurrence of a subsequent vehicle operation performed by a user in response to autocompleting the vehicle task; and

updating the digitally stored dataset by adding the subsequent vehicle operation to the vehicle task as an additional operation to be autocompleted.

9. The method of claim 1, wherein the digitally stored dataset is a digitally stored table that includes a list of sensors to be monitored for the vehicle task.

10. The method of claim 1, further comprising:

responsive to autocompleting the next vehicle operation, monitoring in-vehicle sensors for sensor data that includes images and sounds of a user; and

generating a familiarity estimate that indicates whether the user is familiar with the next vehicle operation based on the sensor data.

11. The method of claim 10, wherein responsive to the familiarity estimate falling below a threshold value, generating an explanation of the next vehicle operation for the user.

12. The method of claim 1, further comprising:

monitoring a sequence of vehicle operations performed by a user to complete the vehicle task; and

generating the digitally stored dataset by adding the vehicle task with the sequence of vehicle operations performed by the user.

13. The method of claim 1, further comprising:

generating a user interface that includes graphical elements for selecting a level of autocomplete; and

responsive to a user selecting the level of autocomplete, updating the digitally stored dataset to include the level of autocomplete.

14. A non-transitory computer-readable medium having computer instructions stored thereon that are executable by a processing device to perform or control performance of steps comprising:

monitoring sensors for sensor data;

determining an occurrence of an initial vehicle operation performed by a user based on the sensor data;

determining a vehicle task from a digitally stored dataset based on the initial vehicle operation;

determining a next vehicle operation to autocomplete based on the vehicle task;

autocompleting the next vehicle operation; and

determining whether the vehicle task is complete.

15. The non-transitory computer-readable medium of claim 14, the steps further comprising responsive to the vehicle task failing to be complete, determining an additional vehicle operation to autocomplete based on the vehicle task, autocompleting the additional vehicle operation, and repeating until the vehicle task is complete.

16. The non-transitory computer-readable medium of claim 14, the steps further comprising:

determining a confidence factor that indicates a likelihood that the initial vehicle operation performed by the user was properly determined; and

wherein determining the vehicle task is also based on the confidence factor exceeding a threshold value.

17. The non-transitory computer-readable medium of claim 14, wherein the sensors include in-vehicle sensors that are used to determine the occurrence of the initial vehicle operation performed by the user.

18. The non-transitory computer-readable medium of claim 14, the steps further comprising:

receiving weather data or traffic data from a network; and

determining a next vehicle task based on the weather data or the traffic data.

19. The non-transitory computer-readable medium of claim 14, wherein the sensors detect an environmental condition and the vehicle task is based on the environmental condition.

20. The non-transitory computer-readable medium of claim 14, the steps further comprising:

determining an occurrence of a subsequent vehicle operation performed by a user in response to autocompleting the vehicle task; and

updating the digitally stored dataset by adding the subsequent vehicle operation to the vehicle task as an additional operation to be autocompleted

21. A method for autocompleting an in-vehicle operation, the method comprising:

monitoring sensors for sensor data;

determining an occurrence of an initial vehicle operation performed by a user based on the sensor data;

determining a vehicle task from a digitally stored table based on the initial vehicle operation performed by the user;

determining a next vehicle operation to autocomplete based on the vehicle task;

autocompleting, using an onboard computer of a vehicle, the next vehicle operation;

determining whether the vehicle task is complete; and

responsive to the vehicle task failing to be complete, determining an additional vehicle operation to autocomplete based on the vehicle task, autocompleting the additional vehicle operation, and repeating until the vehicle task is complete.