IP Library Granted Patent US 11,567,211
Granted Patent B2
US 11,567,211 · App. 16/983,599 · Granted Jan 31, 2023

Systems and methods for estimating vehicle speed based on radar

Inventor: Farzad Cyrus Foroughi Abari (San Bruno, CA)
Assignee: WOVEN PLANET NORTH AMERICA, INC.
G01S17/931B60W30/146G01S13/865G06V20/58G08G1/166B60W2554/00G01S2013/932
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Quick Facts
Patent No.
US 11,567,211
App. No.
16/983,599
Granted
Jan 31, 2023
Kind
B2
Abstract

Systems, methods, and other embodiments relate to determining the speed of a vehicle. In one embodiment, a method includes receiving a first frame of data generated by a first sensor of a vehicle, the first frame of data including a first set of angular positions associated with a first set of objects in the environment. The method includes receiving a second frame of data generated by a second sensor of the vehicle, the second frame of data including a second set of angular positions associated with a second set of objects in the environment. The method includes generating a speed estimate for the vehicle in relation to the first set of objects and the second set of objects based at least in part on the first set of angular positions of the first frame of data and the second set of angular positions of the second frame of data.

Claims (56)

1. A computer-implemented method comprising:

receiving, by a computing system of a vehicle, a first frame of data generated by a first sensor of the vehicle, the first frame of data including a first set of angular positions associated with a first set of objects in an environment of the vehicle;

receiving, by the computing system, a second frame of data generated by a second sensor of the vehicle, the second frame of data including a second set of angular positions associated with a second set of objects in the environment;

generating, by the computing system, a speed estimate for the vehicle in relation to the first set of objects and the second set of objects based at least in part on the first set of angular positions of the first frame of data and the second set of angular positions of the second frame of data; and

controlling the vehicle according to the speed estimate.

2. The computer-implemented method of claim 1 , further comprising:

determining whether one or more angular positions of at least one of the first set of angular positions or the second set of angular positions are associated with a moving object; and

subsequent to determining that the one or more of the angular positions are associated with the moving object, filtering out the one or more angular positions from at least one of the first frame of data or the second frame of data.

3. The computer-implemented method of claim 2 , wherein the first frame of data is associated with a first field-of-view and the second frame of data is associated with a second field-of-view different than the first field-of-view.

4. The computer-implemented method of claim 1 , wherein a speed of the vehicle and speeds of objects of the first set of objects and the second set of objects are associated with a scenario occurring in the environment of the vehicle.

5. The computer-implemented method of claim 1 , wherein the generating the speed estimate comprises:

generating a first speed estimate based on the first set of angular positions of the first frame of data;

generating a second speed estimate based on the second set of angular positions of the second frame of data; and

combining the first speed estimate and the second speed estimate.

6. The computer-implemented method of claim 5 , wherein:

the first sensor is a first radar system,

the second sensor is a second radar system, and

the first frame of data and the second frame of data are captured at the same time.

7. The computer-implemented method of claim 5 , further comprising:

weighting at least one of the first speed estimate or the second speed estimate before the combining of the first speed estimate and the second speed estimate.

8. The computer-implemented method of claim 1 , wherein generating the speed estimate for the vehicle comprises:

fitting a curve to the first set of angular positions included in the first frame of data and the second set of angular positions included in the second frame of data.

9. The computer-implemented method of claim 8 , further comprising:

determining a fit quality metric for the curve; and

determining a weight based on the fit quality metric.

10. The computer-implemented method of claim 9 , wherein the fit quality metric is at least one of a sum of squares due to error (SSE), an R-square, an adjusted R-square, or a root mean squared error (RMSE).

11. A system comprising;

at least one processor; and

a memory storing instructions that, when executed by the at least one processor, cause the system to perform steps comprising:

receiving a first frame of data generated by a first sensor of a vehicle, the first frame of data including a first set of angular positions associated with a first set of objects in an environment of the vehicle;

receiving a second frame of data generated by a second sensor of the vehicle, the second frame of data including a second set of angular positions associated with a second set of objects in the environment;

generating a speed estimate for the vehicle in relation to the first set of objects and the second set of objects based at least in part on the first set of angular positions of the first frame of data and the second set of angular positions of the second frame of data; and

controlling the vehicle according to the speed estimate.

12. The system of claim 11 , wherein the instructions cause the system to perform the steps further comprising:

determining whether one or more angular positions of at least one of the first set of angular positions or the second set of angular positions are associated with a moving object; and

subsequent to determining that the one or more of the angular positions are associated with the moving object, filtering out the one or more angular positions from at least one of the first frame of data or the second frame of data.

13. The system of claim 12 , wherein the first frame of data is associated with a first field-of-view and the second frame of data is associated with a second field-of-view different than the first field-of-view.

14. The system of claim 11 , wherein a speed of the vehicle and speeds of objects of the first set of objects and the second set of objects are associated with a scenario occurring in the environment of the vehicle.

15. The system of claim 11 , wherein the generating the speed estimate comprises:

generating a first speed estimate based on the first set of angular positions of the first frame of data;

generating a second speed estimate based on the second set of angular positions of the second frame of data; and

combining the first speed estimate and the second speed estimate.

16. A non-transitory computer-readable medium comprising computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to perform steps comprising:

receiving a first frame of data generated by a first sensor of a vehicle, the first frame of data including a first set of angular positions associated with a first set of objects in an environment of the vehicle;

receiving a second frame of data generated by a second sensor of the vehicle, the second frame of data including a second set of angular positions associated with a second set of objects in the environment; and

generating a speed estimate for the vehicle in relation to the first set of objects and the second set of objects based at least in part on the first set of angular positions of the first frame of data and the second set of angular positions of the second frame of data; and

controlling the vehicle according to the speed estimate.

17. The non-transitory computer-readable medium of claim 16 , wherein the instructions cause the computing device to perform the steps further comprising:

determining whether one or more angular positions of at least one of the first set of angular positions or the second set of angular positions are associated with a moving object; and

subsequent to determining that the one or more of the angular positions are associated with the moving object, filtering out the one or more angular positions from at least one of the first frame of data or the second frame of data.

18. The non-transitory computer-readable medium of claim 17 , first frame of data is associated with a first field-of-view and the second frame of data is associated with a second field-of-view different than the first field-of-view.

19. The non-transitory computer-readable medium of claim 16 , wherein a speed of the vehicle and speeds of objects of the first set of objects and the second set of objects are associated with a scenario occurring in the environment of the vehicle.

20. The non-transitory computer-readable medium of claim 16 , wherein the generating the speed estimate comprises:

generating a first speed estimate based on the first set of angular positions of the first frame of data;

generating a second speed estimate based on the second set of angular positions of the second frame of data; and

combining the first speed estimate and the second speed estimate.

Assignments (3)
CHANGE OF NAME Recorded Jun 22, 2023
From: WOVEN PLANET NORTH AMERICA, INC.
To: WOVEN BY TOYOTA, U.S., INC.
Reel/Frame 064065/0601 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 20, 2021
From: LYFT, INC.; BLUE VISION LABS UK LIMITED
To: WOVEN PLANET NORTH AMERICA, INC.
Reel/Frame 056927/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 12, 2021
From: LYFT, INC.; MAGNA AUTONOMOUS SYSTEMS, LLC
To: LYFT, INC.; MAGNA AUTONOMOUS SYSTEMS, LLC
Reel/Frame 057434/0623 →
Continuity (2)
Continuation 16237153 · Dec 31, 2018
Related Publication 20210041569A1 · Feb 11, 2021