IP Library Granted Patent US 12,377,866
Granted Patent B1
US 12,377,866 · App. 18/313,904 · Granted Aug 5, 2025

Processing predicted input data in an autonomous vehicle

Inventors: John Hayes (Mountain View, CA); Volkmar Uhlig (Cupertino, CA); Nima Soltani (Los Gatos, CA)
Assignee: Applied Intuition, Inc.
B60W50/0205B60W60/001G05D1/0088G06F11/0739G06F11/0751G06F11/0793G06N5/04
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Quick Facts
Patent No.
US 12,377,866
App. No.
18/313,904
Granted
Aug 5, 2025
Kind
B1
Abstract

Processing predictive input data in an autonomous vehicle, including: receiving input data for a model; determining whether the input data for the model comprises an indication that the input data was generated based on some amount of predicted data; generating, by the model and based on the input data, output data by modifying, in response to the input data comprising the indication, one or more thresholds or one or more confidence scores of the model used in generating output data; and causing an autonomous vehicle to perform one or more driving decisions based on the output data of the model.

Claims (32)

1. A method comprising:

receiving input data for a model, wherein the model comprises a machine learning model;

determining whether the input data for the model comprises an indication that the input data was generated based on some amount of predicted data;

generating, by the model and based on the input data, output data by modifying, in response to the input data comprising the indication, one or more thresholds or one or more confidence scores of the model used in generating the output data; and

causing an autonomous vehicle to perform one or more driving decisions based on the output data of the model.

2. The method of claim 1 , wherein the model is included in a chain of models for generating the one or more driving decisions.

3. The method of claim 1 , further comprising generating the input data for the model based on predicted input data.

4. The method of claim 3 , wherein generating the input data to the model comprises generating, by another model and based on the predicted input data, the input data.

5. The method of claim 3 , further comprising generating the predicted input data in response to detecting an error in other input data.

6. The method of claim 5 , wherein the other input data comprises sensor data and the predicted input data comprises predicted sensor data.

7. The method of claim 6 , wherein the sensor data comprises video data and the predicted sensor data comprises predicted video data.

8. An apparatus configured to perform steps comprising:

receiving input data for a model, wherein the model comprises a machine learning model;

determining whether the input data for the model comprises an indication that the input data was generated based on some amount of predicted data;

generating, by the model and based on the input data, output data by modifying, in response to the input data comprising the indication, one or more thresholds or one or more confidence scores of the model used in generating the output data; and

causing an autonomous vehicle to perform one or more driving decisions based on the output data of the model.

9. The apparatus of claim 8 , wherein the model is included in a chain of models for generating the one or more driving decisions.

10. The apparatus of claim 8 , further comprising generating the input data for the model based on predicted input data.

11. The apparatus of claim 10 , wherein generating the input data to the model comprises generating, by another model and based on the predicted input data, the input data.

12. The apparatus of claim 10 , wherein the steps further comprise generating the predicted input data in response to detecting an error in other input data.

13. The apparatus of claim 12 , wherein the other input data comprises sensor data and the predicted input data comprises predicted sensor data.

14. The apparatus of claim 13 , wherein the sensor data comprises video data and the predicted sensor data comprises predicted video data.

15. A computer program product disposed upon a non-transitory computer readable medium, the computer program product comprising computer program instructions that, when executed, cause a computer system of the autonomous vehicle to carry out the steps of:

receiving input data for a model, wherein the model comprises a machine learning model;

determining whether the input data for the model comprises an indication that the input data was generated based on some amount of predicted data;

generating, by the model and based on the input data, output data by modifying, in response to the input data comprising the indication, one or more thresholds or one or more confidence scores of the model used in generating the output data; and

causing an autonomous vehicle to perform one or more driving decisions based on the output data of the model.

16. The computer program product of claim 15 , wherein the model is included in a chain of models for generating the one or more driving decisions.

17. The computer program product of claim 16 , further comprising generating the input data for the model based on predicted input data.

18. The computer program product of claim 17 , wherein generating the input data to the model comprises generating, by another model and based on the predicted input data, the input data.

19. The computer program product of claim 17 , wherein the steps further comprise generating the predicted input data in response to detecting an error in other input data.

20. The computer program product of claim 19 , wherein the other input data comprises sensor data and the predicted input data comprises predicted sensor data.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 18, 2024
From: GHOST AUTONOMY, INC.
To: APPLIED INTUITION, INC.
Reel/Frame 068982/0647 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 8, 2023
From: HAYES, JOHN; UHLIG, VOLKMAR; SOLTANI, NIMA
To: GHOST AUTONOMY INC.
Reel/Frame 063569/0340 →
Continuity (1)
Continuation 16906752 · Jun 19, 2020
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Cited By (1)
US 12,711,730