IP Library Granted Patent US 10,830,669
Granted Patent B2
US 10,830,669 · App. 16/660,244 · Granted Nov 10, 2020

Perception simulation for improved autonomous vehicle control

Inventors: Xing Sun (San Diego, CA); Wutu Lin (San Diego, CA); Yufei Zhao (San Diego, CA); Liu Liu (San Diego, CA)
Assignee: TUSIMPLE, INC.
G01M17/00B60W30/00
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 10,830,669
App. No.
16/660,244
Granted
Nov 10, 2020
Kind
B2
Abstract

A system and method for real world autonomous vehicle perception simulation are disclosed. A particular embodiment includes: receiving perception data from a plurality of sensors of an autonomous vehicle; configuring the perception simulation operation based on a comparison of the perception data against ground truth data; generating simulated perception data by simulating errors related to the physical constraints of one or more of the plurality of sensors, and by simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors; and providing the simulated perception data to a motion planning system for the autonomous vehicle.

Claims (34)

1. A system comprising:

a data processor; and

a perception simulation module, executable by the data processor, the perception simulation module being configured to perform a perception simulation operation for autonomous vehicles, the perception simulation operation being configured to:

receive perception data from a plurality of sensors of an autonomous vehicle;

configure the perception simulation operation based on a comparison of the perception data against ground truth data;

generate simulated perception data by simulating errors related to the physical constraints of one or more of the plurality of sensors, and by simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors, wherein simulating errors related to the physical constraints of one or more of the plurality of sensors includes applying a maximum range beyond which the one or more of the plurality of sensors cannot detect objects; and

provide the simulated perception data to a motion planning system for the autonomous vehicle.

2. The system of claim 1 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating a false positive or false negative object detection.

3. The system of claim 1 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating noise in vehicle localization.

4. The system of claim 1 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating noise in lane detection.

5. The system of claim 1 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating errors in object type classification.

6. The system of claim 1 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating errors in object location.

7. The system of claim 1 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating errors in data produced by an image processing module.

8. A method comprising:

receiving perception data from a plurality of sensors of an autonomous vehicle;

configuring the perception simulation operation based on a comparison of the perception data against ground truth data;

generating simulated perception data by simulating errors related to the physical constraints of one or more of the plurality of sensors, and by simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors, wherein simulating errors related to the physical constraints of one or more of the plurality of sensors includes applying a maximum range beyond which the one or more of the plurality of sensors cannot detect objects; and

providing the simulated perception data to a motion planning system for the autonomous vehicle.

9. The method of claim 8 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating a false positive or false negative object detection.

10. The method of claim 8 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating noise in vehicle localization.

11. The method of claim 8 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating noise in lane detection.

12. The method of claim 8 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating errors in object type classification.

13. The method of claim 8 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating errors in object location.

14. The method of claim 8 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating errors in data produced by an image processing module.

15. A non-transitory machine-useable storage medium embodying instructions which, when executed by a machine, cause the machine to:

receive perception data from a plurality of sensors of an autonomous vehicle;

configure the perception simulation operation based on a comparison of the perception data against ground truth data;

generate simulated perception data by simulating errors related to the physical constraints of one or more of the plurality of sensors, and by simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors, wherein simulating errors related to the physical constraints of one or more of the plurality of sensors includes applying a maximum range beyond which the one or more of the plurality of sensors cannot detect objects; and

provide the simulated perception data to a motion planning system for the autonomous vehicle.

16. The non-transitory machine-useable storage medium of claim 15 wherein the ground truth data is produced by a ground truth data simulation system.

17. The non-transitory machine-useable storage medium of claim 15 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating a false positive or false negative object detection.

18. The non-transitory machine-useable storage medium of claim 15 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating noise in vehicle localization.

19. The non-transitory machine-useable storage medium of claim 15 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating noise in lane detection.

20. The non-transitory machine-useable storage medium of claim 15 wherein simulating noise in data provided by a sensor processing module corresponding to one or more of the plurality of sensors includes simulating errors in object type classification.

Assignments (3)
CHANGE OF NAME Recorded Dec 3, 2025
From: TUSIMPLE, INC.
To: CREATEAI, INC.
Reel/Frame 073832/0553 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 6, 2020
From: SUN, XING; LIN, WUTU; LIU, LIU; ZHAO, YUFEI
To: TUSIMPLE
Reel/Frame 053122/0586 →
CHANGE OF NAME Recorded Jan 30, 2020
From: TUSIMPLE
To: TUSIMPLE, INC.
Reel/Frame 051757/0470 →
Continuity (2)
Division 15598693 · May 18, 2017
Related Publication 20200049592A1 · Feb 13, 2020
Cited By (1)
US 12,242,274