IP Library Granted Patent US 10,696,300
Granted Patent B2
US 10,696,300 · App. 16/459,575 · Granted Jun 30, 2020

Vehicle tracking

Inventors: Peter Ondruska (London, GB); Lukas Platinsky (London, GB); Suraj Mannakunnel Surendran (London, GB)
Assignee: BLUE VISION LABS UK LIMITED
B60W30/0956G01C21/3635G01C21/3647G05D1/0212G06F17/18G06K9/00671G06K9/00791G06T7/20B60W2520/06B60W2520/10G05D1/027G05D1/0214G05D1/0231G05D2201/0213
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Quick Facts
Patent No.
US 10,696,300
App. No.
16/459,575
Granted
Jun 30, 2020
Kind
B2
Abstract

The present invention relates to a method and system for accurately predicting future trajectories of observed objects in dense and ever-changing city environments. More particularly, the present invention relates to the use of prior trajectories extracted from mapping data to estimate the future movement of an observed object. As an example, an observed object may be a moving vehicle. Aspects and/or embodiments seek to provide a method and system for predicting future movements of a newly observed object, such as a vehicle, using motion prior data extracted from map data.

Claims (37)

1. A method for estimating movements of an object, the method comprising;

determining, by a system, initial state data of the object at a first time;

determining, by the system, sequential trajectory data for one or more prior moving objects that intersected vicinity of the position of the object;

estimating, by the system, future positions of the object, at a second time, based on the sequential trajectory data for the one or more prior moving objects; and

constraining, by the system, the future positions of the object based on a comparison between the object and the one or more prior moving objects for which the sequential trajectory data intersects the vicinity of the position of the object, wherein the constrained future positions of the object are indicative of the estimated movement of the object at the second time.

2. The method of claim 1 wherein the initial state data of the object comprises a position, rotation and velocity in a 3D space.

3. The method of claim 1 wherein the sequential trajectory data is extracted from data used to construct 3D maps of an environment.

4. The method of claim 1 wherein determining the sequential trajectory data comprises using at least one visual data sensor in the one or more prior moving objects.

5. The method of claim 4 wherein said at least one visual data sensor comprises any or a combination of: an image camera; a video camera; a monocular camera; a depth camera; a stereo image camera; a high dynamic range camera, a light detection and ranging sensor; a radio detection and ranging sensor; an inertial measurement unit.

6. The method of claim 1 wherein determining the sequential trajectory data comprises performing structure from motion.

7. The method of claim 1 wherein estimating future positions of the object further comprises hypothesising that the object is following a trajectory path of each of the one or more prior moving objects in the same location as the object.

8. The method of claim 1 wherein estimating future positions of the object further comprises using location data from the one or more prior moving objects.

9. The method of claim 1 wherein estimating future positions of the object further comprises estimating a future pose of the object.

10. The method of claim 9 wherein the future pose estimate comprises a random noise model inclusion so as to account for deviations in the trajectory.

11. The method of claim 9 wherein the future pose estimate is the observed pose of a prior moving object, having previously intersected the vicinity of the position of the object, after a time interval.

12. The method of claim 1 wherein constraining the future positions of the object further comprises determining state comparisons between the one or more prior moving objects and the object.

13. The method of claim 12 , wherein the differences comprises any one of, or any combination of:

a difference in a Euclidean distance in the 3D space;

relative difference of heading angle; and

difference in linear speed.

14. The method of claim 12 wherein constraining the future positions of the object are weighted in order to output either a wider or narrower set of samples.

15. A system for estimating movements of an object, the 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:

determining initial state data of the object at a first time;

determining sequential trajectory data for one or more prior moving objects that intersected vicinity of the position of the object;

estimating future positions of the object, at a second time, based on the sequential trajectory data for the one or more prior moving objects; and

constraining the future positions of the object based on a comparison between the object and the one or more prior moving objects for which the sequential trajectory data intersects the vicinity of the position of the object, wherein the constrained future positions of the object are indicative of the estimated movement of the object at the second time.

16. A computer program product comprising instructions which, when executed by a computer, cause the computer to perform a method comprising:

determining initial state data of an object at a first time;

determining sequential trajectory data for one or more prior moving objects that intersected vicinity of the position of the object;

estimating future positions of the object, at a second time, based on the sequential trajectory data for the one or more prior moving objects; and

constraining the future positions of the object based on a comparison between the object and the one or more prior moving objects for which the sequential trajectory data intersects the vicinity of the position of the object, wherein the constrained future positions of the object are indicative of the estimated movement of the object at the second time.

17. The system of claim 15 wherein estimating future positions of the object further comprises hypothesising that the object is following a trajectory path of each of the one or more prior moving objects in the same location as the object.

18. The system of claim 15 wherein constraining the future positions of the object further comprises determining state comparisons between the one or more prior moving objects and the object.

19. The computer program product of claim 16 wherein estimating future positions of the object further comprises hypothesising that the object is following a trajectory path of each of the one or more prior moving objects in the same location as the object.

20. The computer program product of claim 16 wherein constraining the future positions of the object further comprises determining state comparisons between the one or more prior moving objects and the object.

Assignments (5)
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 Jan 22, 2020
From: SURENDRAN, SURAJ MANNAKUNNEL
To: BLUE VISION LABS UK LIMITED
Reel/Frame 051583/0936 →
CORRECTIVE ASSIGNMENT TO CORRECT THE RECEIVING PARTY NAME PREVIOUSLY RECORDED AT REEL: 50705 FRAME: 568. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Dec 4, 2019
From: ONDRUSKA, PETER; PLATINSKY, LUKAS
To: BLUE VISION LABS UK LIMITED
Reel/Frame 051188/0157 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 14, 2019
From: ONDRUSKA, PETER; PLATINSKY, LUKAS
To: LYFT, INC.
Reel/Frame 050705/0568 →