IP Library Granted Patent US 10,181,084
Granted Patent B2
US 10,181,084 · App. 15/498,911 · Granted Jan 15, 2019

Combining multiple estimates of an environment into a consolidated estimate for an autonomous vehicle

Inventors: David Ian Franklin Ferguson (San Francisco, CA); David Harrison Silver (Santa Clara, CA)
Assignee: Waymo LLC
G06K9/00798G05D1/0088G05D1/0246G06K9/6202G06T7/74G06T2207/30256
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Quick Facts
Patent No.
US 10,181,084
App. No.
15/498,911
Granted
Jan 15, 2019
Kind
B2
Abstract

A vehicle is provided that may combine multiple estimates of an environment into a consolidated estimate. The vehicle may receive first data indicative of the region of interest in an environment from a sensor of the vehicle. The first data may include a first accuracy value and a first estimate of the region of interest. The vehicle may also receive second data indicative of the region of interest in the environment, and the second data may include a second accuracy value and a second estimate of the region of interest. Based on the first data and the second data, the vehicle may combine the first estimate of the region of interest and the second estimate of the region of interest.

Claims (70)

1. A method performed by a computing device comprising one or more processors, the method comprising:

obtaining first data including a first estimate of a location of a region of interest of a road, the first data having been acquired at a first time, wherein the first data comprises a predetermined map of the road, and wherein an autonomous vehicle is operating on the road;

based on the first data, determining a first variance in the first estimate of the location;

receiving, via at least one sensor coupled to the autonomous vehicle, second data including a second estimate of the location, the second data having been acquired at a second time different from the first time;

based on the second data, determining a second variance in the second estimate of the location; and

based on the first estimate, the first variance, the second estimate, and the second variance, determining third data including a combined estimate of the location and further including a combined variance in the combined estimate.

2. The method of claim 1 , further comprising:

based on the third data, providing instructions to control the autonomous vehicle on the road.

3. The method of claim 1 , wherein the first estimate comprises a first plurality of coordinate points corresponding to the location, and

wherein the second estimate comprises a second plurality of coordinate points corresponding to the location.

4. The method of claim 3 , wherein the second variance is determined further based on one or more of (i) an operational state of the at least one sensor, (ii) a distance between the second plurality of coordinate points and the at least one sensor, and (iii) sensor data indicative of environmental conditions present at the second time.

5. The method of claim 1 , wherein the first estimate comprises a first image portion, and

wherein the second estimate comprises a second image portion.

6. The method of claim 1 , wherein the first estimate comprises a first plurality of coordinate points corresponding to the location,

wherein the second estimate comprises a second plurality of coordinate points corresponding to the location,

wherein the combined estimate comprises a third plurality of coordinate points corresponding to the location,

wherein the first variance comprises, for each coordinate point of the first plurality of coordinate points, an associated respective variance value that indicates how accurately the coordinate point corresponds to the location,

wherein the second variance comprises, for each coordinate point of the second plurality of coordinate points, an associated respective variance value that indicates how accurately the coordinate point corresponds to the location, and

wherein the combined variance comprises, for each coordinate point of the third plurality of coordinate points, an associated respective variance value that indicates how accurately the coordinate point corresponds to the location.

7. The method of claim 6 , wherein one or more of the first, second, and third pluralities of coordinate points is a plurality of two-dimensional (2D) coordinate points.

8. An autonomous vehicle comprising:

at least one sensor configured to sense a road on which the autonomous vehicle is operating;

at least one processor; and

data storage comprising instructions executable by the at least one processor to cause a computing system to perform operations comprising:

obtaining first data including a first estimate of a location of a region of interest of the road, the first data having been acquired at a first time, wherein the first data comprises a predetermined map of the road;

based on the first data, determining a first variance in the first estimate of the location;

receiving, via the at least one sensor, second data including a second estimate of the location, the second data having been acquired at a second time different from the first time;

based on the second data, determining a second variance in the second estimate of the location; and

based on the first estimate, the first variance, the second estimate, and the second variance, determining third data including a combined estimate of the location and further including a combined variance in the combined estimate.

9. The vehicle of claim 8 , wherein the operations further comprise:

based on the third data, providing instructions to control the autonomous vehicle on the road.

10. The vehicle of claim 8 , wherein the first estimate comprises a first plurality of coordinate points corresponding to the location,

wherein the second estimate comprises a second plurality of coordinate points corresponding to the location, and

wherein the second variance is determined further based on one or more of (i) an operational state of the at least one sensor, (ii) a distance between the second plurality of coordinate points and the at least one sensor, and (iii) sensor data indicative of environmental conditions present at the second time.

11. The vehicle of claim 8 , wherein the first time is before the second time.

12. The vehicle of claim 8 ,

wherein the first estimate comprises a first plurality of coordinate points corresponding to the location,

wherein the second estimate comprises a second plurality of coordinate points corresponding to the location,

wherein the combined estimate comprises a third plurality of coordinate points corresponding to the location,

wherein the first variance comprises, for each coordinate point of the first plurality of coordinate points, an associated respective variance value that indicates how accurately the coordinate point corresponds to the location,

wherein the second variance comprises, for each coordinate point of the second plurality of coordinate points, an associated respective variance value that indicates how accurately the coordinate point corresponds to the location, and

wherein the combined variance comprises, for each coordinate point of the third plurality of coordinate points, an associated respective variance value that indicates how accurately the coordinate point corresponds to the location.

13. The vehicle of claim 8 , wherein determining the third data based on the first estimate, the first variance, the second estimate, and the second variance comprises:

making a comparison between one or both of the first and second variances and a predetermined threshold;

in response to the comparison indicating that one or both of the first and second variances is below the predetermined threshold, (i) causing the at least one sensor to acquire additional data including another estimate of the location and (ii) based on the additional data, determining another variance in the other estimate of the location;

determining that the other variance is above the predetermined threshold; and

in response to determining that the other variance is above the predetermined threshold, determining the third data based at least in part on the other estimate and the other variance.

14. The vehicle of claim 13 , wherein the at least one sensor includes at least one first sensor and further includes at least one second sensor different from the at least one first sensor,

wherein the second data is received via the at least one first sensor, and

wherein causing the at least one sensor to acquire the additional data including the other estimate of the location comprises causing the at least one second sensor to acquire the additional data including the other estimate of the location.

15. A non-transitory computer readable medium having stored therein instructions that when executed by a computing system cause the computing system to perform operations comprising:

obtaining first data including a first estimate of a location of a region of interest of a road, the first data having been acquired at a first time, wherein the first data comprises a predetermined map of the road, and wherein an autonomous vehicle is operating on the road;

based on the first data, determining a first variance in the first estimate of the location;

receiving, via at least one sensor coupled to the autonomous vehicle, second data including a second estimate of the location, the second data having been acquired at a second time different from the first time;

based on the second data, determining a second variance in the second estimate of the location; and

based on the first estimate, the first variance, the second estimate, and the second variance, determining third data including a combined estimate of the location and further including a combined variance in the combined estimate.

16. The non-transitory computer readable medium of claim 15 , wherein the operations further comprise:

based on the third data, providing instructions to control the autonomous vehicle on the road.

17. The non-transitory computer readable medium of claim 15 , wherein determining the third data based on the first estimate, the first variance, the second estimate, and the second variance comprises:

making a comparison between one or both of the first and second variances and a predetermined threshold;

in response to the comparison indicating that one or both of the first and second variances is below the predetermined threshold, (i) causing the at least one sensor to acquire additional data including another estimate of the location and (ii) based on the additional data, determining another variance in the other estimate of the location;

determining that the other variance is above the predetermined threshold; and

in response to determining that the other variance is above the predetermined threshold, determining the third data based at least in part on the other estimate and the other variance.

18. The non-transitory computer readable medium of claim 15 , wherein the first estimate comprises a first plurality of coordinate points, each coordinate point of the first plurality corresponding to a respective lane marker that makes up a distinct portion of the region of interest of the road,

wherein the second estimate comprises a second plurality of coordinate points, each coordinate point of the second plurality corresponding to a respective lane marker that makes up a distinct portion of the region of interest of the road, and

wherein the combined estimate comprises a third plurality of coordinate points, each coordinate point of the third plurality corresponding to a respective lane marker that makes up a distinct portion of the region of interest of the road.

19. The non-transitory computer readable medium of claim 18 , wherein the first variance comprises, for each coordinate point of the first plurality of coordinate points, an associated respective variance value that indicates how accurately the coordinate point corresponds to the respective lane marker,

wherein the second variance comprises, for each coordinate point of the second plurality of coordinate points, an associated respective variance value that indicates how accurately the coordinate point corresponds to the respective lane marker, and

wherein the combined variance comprises, for each coordinate point of the third plurality of coordinate points, an associated respective variance value that indicates how accurately the coordinate point corresponds to the respective lane marker.

20. The non-transitory computer readable medium of claim 18 , wherein one or more of the first, second, and third pluralities of coordinate points is a plurality of three-dimensional (3D) coordinate points.

Assignments (5)
CHANGE OF NAME Recorded Feb 27, 2020
From: GOOGLE INC.
To: GOOGLE LLC
Reel/Frame 052885/0239 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 27, 2020
From: WAYMO HOLDING INC.
To: WAYMO LLC
Reel/Frame 052885/0300 →
CORRECTIVE ASSIGNMENT TO CORRECT THE INCORRECT RECEIVING PARTY DATA PREVIOUSLY RECORDED ON REEL 042193 FRAME 0119. ASSIGNOR(S) HEREBY CONFIRMS THE CORRECT RECEIVING PARTY IS GOOGLE INC.. Recorded Feb 27, 2020
From: FERGUSON, DAVID I; SILVER, DAVID
To: GOOGLE INC.
Reel/Frame 052982/0236 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 27, 2020
From: GOOGLE INC.
To: WAYMO HOLDING INC.
Reel/Frame 052045/0785 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 1, 2017
From: FERGUSON, DAVID I; SILVER, DAVID
To: WAYMO LLC
Reel/Frame 042193/0119 →
Continuity (3)
Continuation 14939232 · Nov 12, 2015
Continuation 13955970 · Jul 31, 2013
Related Publication 20170228604A1 · Aug 10, 2017
Cited By (4)
US 12,339,660 US 12,475,673 US 12,526,547 US 12,571,662