Controlling host vehicle based on detected movement of a target vehicle

• US 10,127,465 B2
• Filed: 06/27/2017
• Issued: 11/13/2018
• Est. Priority Date: 06/27/2016
• Status: Active Grant

• Current Assignee: MobilEye Vision Technologies Ltd. (Intel Corporation)
• Original Assignee: MobilEye Vision Technologies Ltd. (Intel Corporation)
• Inventors: Cohen, Barak, Stein, Gideon
• Primary Examiner(s): Coleman, Stephen
• Application Number:
  US15/634,450
• Publication Number:
  US 20170371344A1
• Time in Patent Office: 504 Days
• Field of Search: None
• CPC Class Codes: B60W 30/08 Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
• CPC Class Codes: G01C 21/34 Route searching; Route guidance
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/0246 using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/228 Command input arrangements located on-board unmanned vehicles
• CPC Class Codes: G05D 1/249 from positioning sensors located off-board the vehicle, e.g. from cameras
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10021 Stereoscopic video; Stereoscopic image sequence
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/10048 Infrared image
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 2207/20084 Artificial neural networks [ANN]
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 2207/30256 Lane; Road marking
• CPC Class Codes: G06T 2207/30261 Obstacle
• CPC Class Codes: G06T 2207/30264 Parking
• CPC Class Codes: G06T 7/269 using gradient-based methods
• CPC Class Codes: G06T 7/277 involving stochastic approaches, e.g. using Kalman filters
• CPC Class Codes: G06T 7/521 from laser ranging, e.g. using interferometry; from the projection of structured light
• CPC Class Codes: G06T 7/579 from motion
• CPC Class Codes: G06T 7/593 : from stereo images
• CPC Class Codes: G06T 7/73 : using feature-based methods
• CPC Class Codes: G06V 20/584 : of vehicle lights or traffic lights

Abstract

Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system for navigating a host vehicle based on movement of a target vehicle toward a lane being traveled by the host vehicle may include at least one processing device. The processing device may be programmed to receive a plurality of images associated with an environment of the host vehicle, analyze at least one of the plurality of images to identify the target vehicle and at least one wheel component on a side of the target vehicle, analyze a region including the at least one wheel component of the target vehicle to identify motion associated with the at least one wheel component of the target vehicle, and cause at least one navigational change of the host vehicle based on the identified motion associated with the at least one wheel component.

Claims

1. A system for navigating a host vehicle based on movement of a target vehicle toward a lane being traveled by the host vehicle, the system comprising:

at least one processing device programmed to;

receive, from an image capture device, a plurality of images associated with an environment of the host vehicle;

analyze at least one of the plurality of images to identify the target vehicle and at least one wheel component on a side of the target vehicle;

analyze, in at least two of the plurality of images, a region including the at least one wheel component of the target vehicle to identify motion associated with the at least one wheel component of the target vehicle; and

cause at least one navigational change of the host vehicle based on the identified motion associated with the at least one wheel component of the target vehicle.

2. The system of claim 1, wherein the at least one navigational change includes a change in a heading direction of the host vehicle.

3. The system of claim 1, wherein the at least one navigational change includes applying brakes of the host vehicle.

4. The system of claim 1, wherein identifying the target vehicle includes associating at least one bounding box with a shape of the target vehicle.

5. The system of claim 1, wherein the region including the at least one wheel component of the target vehicle includes a region adjacent to a road surface.

6. The system of claim 1, wherein identifying motion associated with the at least one wheel component includes monitoring at least two of the plurality of images for an indication of rotation of the at least one wheel component.

7. The system of claim 1, wherein the at least one wheel component includes at least one of a tire, a hubcap, or a wheel structure.

8. The system of claim 1, wherein identifying motion associated with the at least one tire wheel component includes identifying at least one feature associated with the at least one wheel component and identifying an indicator of a positional change of the at least one feature.

9. The system of claim 8, wherein the at least one processing device is further configured to determine a speed at which the target vehicle is moving based on the positional change of the at least one feature associated with the at least one wheel component.

10. The system of claim 9, wherein the at least one processing device is further configured to determine a lateral safety distance for the vehicle based on the speed of the target vehicle.

11. The system of claim 10, wherein the at least one navigational change of the target vehicle is based on the determined lateral safety distance.

12. A method for navigating a host vehicle based on movement of a target vehicle toward a lane being traveled by the host vehicle, the method comprising:

receiving, from an image capture device, a plurality of images associated with an environment of the host vehicle;

analyzing at least one of the plurality of images to identify the target vehicle and at least one wheel component on a side of the target vehicle;

analyzing, in at least two of the plurality of images, a region including the at least one wheel component of the target vehicle to identify motion associated with the at least one wheel component of the target vehicle; and

causing at least one navigational change of the host vehicle based on the identified motion associated with the at least one wheel component of the target vehicle.

13. The method of claim 12, wherein identifying the target vehicle includes associating at least one bounding box with a shape of the target vehicle.

14. The method of claim 12, wherein identifying motion associated with the at least one wheel component includes monitoring at least two of the plurality of images for an indication of rotation of the at least one wheel component.

15. The method of claim 12, wherein identifying motion associated with the at least one tire wheel component includes identifying at least one feature associated with the at least one wheel component and identifying an indicator of a positional change of the at least one feature.

16. The method of claim 15, further comprising:

determining a speed at which the target vehicle is moving based on the positional change of the at least one feature associated with the at least one wheel component; and

determining a lateral safety distance for the vehicle based on the speed of the target vehicle.

17. A non-transitory computer-readable medium storing instructions, which, when executed by at least one processing device, perform a method comprising:

receiving, from an image capture device, a plurality of images associated with an environment of a host vehicle;

analyzing at least one of the plurality of images to identify a target vehicle and at least one wheel component on a side of the target vehicle;

analyzing, in at least two of the plurality of images, a region including the at least one wheel component of the target vehicle to identify motion associated with the at least one wheel component of the target vehicle; and

causing at least one navigational change of the host vehicle based on the identified motion associated with the at least one wheel component of the target vehicle.

18. The non-transitory computer-readable medium of claim 17, wherein identifying motion associated with the at least one tire wheel component includes identifying at least one feature associated with the at least one wheel component and identifying an indicator of a positional change of the at least one feature.

19. The non-transitory computer-readable medium of claim 17, wherein identifying the target vehicle includes associating at least one bounding box with a shape of the target vehicle.

20. The non-transitory computer-readable medium of claim 19, further storing instructions to:

determine a speed at which the target vehicle is moving based on the positional change of the at least one feature associated with the at least one wheel component; and

determine a lateral safety distance for the vehicle based on the speed of the target vehicle.