Systems and methods for determining the status and details of a traffic light

• US 10,012,997 B2
• Filed: 06/29/2016
• Issued: 07/03/2018
• Est. Priority Date: 01/30/2014
• Status: Active Grant

• Current Assignee: MobilEye Vision Technologies Ltd. (Intel Corporation)
• Original Assignee: MobilEye Vision Technologies Ltd. (Intel Corporation)
• Inventors: Ben Shalom, Itai, Shalev-Shwartz, Shai, Bagon, Eyal, Taieb, Yoav, Shashua, Amnon, Huberman, David
• Primary Examiner(s): Gilliard, Delomia L
• Application Number:
  US15/197,112
• Publication Number:
  US 20160306361A1
• Time in Patent Office: 734 Days
• Field of Search: None
• CPC Class Codes: B60K 31/00 Vehicle fittings, acting on a single sub-unit only, for automatically controlling vehicle speed, i.e. preventing speed from exceeding an arbitrarily established velocity or maintaining speed at a particular velocity, as selected by the vehicle operator fittings acting on two or more sub-units B60W30/14; speedometers G01P; systems or devices for controlling speed in general G05D13/00 ; in traffic anti-collision system for road vehicles G08G1/16
• CPC Class Codes: B60T 7/12 for automatic initiation; for initiation not subject to will of driver or passenger limiting speed of vehicles other than rail vehicles B60K31/00
• CPC Class Codes: B60W 10/20 including control of steering systems
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2552/15 Road slope, i.e. the inclination of a road segment in the longitudinal direction
• CPC Class Codes: B60W 2552/30 Road curve radius
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/20 Static objects
• CPC Class Codes: B60W 2554/4029 Pedestrians
• CPC Class Codes: B60W 2554/4041 Position
• CPC Class Codes: B60W 2554/4042 Longitudinal speed
• CPC Class Codes: B60W 2554/80 Spatial relation or speed relative to objects
• CPC Class Codes: B60W 2554/806 Relative heading
• CPC Class Codes: B60W 2555/60 Traffic rules, e.g. speed limits or right of way
• CPC Class Codes: B60W 2710/207 Steering angle of wheels
• CPC Class Codes: B60W 30/00 Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
• CPC Class Codes: B60W 30/09 Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B60W 30/12 Lane keeping
• CPC Class Codes: B60W 30/14 Adaptive cruise control
• CPC Class Codes: B60W 30/18163 Lane change; Overtaking manoeuvres
• CPC Class Codes: B60W 60/00276 : for two or more other traffic participants
• CPC Class Codes: B62D 6/00 : Arrangements for automatically controlling steering depending on driving conditions sensed and responded to, e.g. control circuits means for initiating a change in direction B62D1/00; steering valves B62D5/06; combined with means for inclining the vehicle body or wheels on bends B62D9/00
• CPC Class Codes: G01S 19/42 : Determining position
• CPC Class Codes: G05D 1/0246 : using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0276 : using signals provided by a source external to the vehicle involving a plurality of vehicles G05D1/0287; automatically controlling vehicle speed responsive to externally generated signals B60K31/0058
• CPC Class Codes: G06T 2207/30256 : Lane; Road marking
• CPC Class Codes: G06T 2207/30261 : Obstacle
• CPC Class Codes: G06T 7/62 : of area, perimeter, diameter or volume
• CPC Class Codes: G06V 20/58 : Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• CPC Class Codes: G06V 20/584 : of vehicle lights or traffic lights
• CPC Class Codes: G06V 20/588 : Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
• CPC Class Codes: G08G 1/095 : Traffic lights
• CPC Class Codes: G08G 1/165 : for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/167 : Driving aids for lane monitoring, lane changing, e.g. blind spot detection
• CPC Class Codes: H04N 7/181 : for receiving images from a plurality of remote sources
• CPC Class Codes: H04N 7/183 : for receiving images from a single remote source

Abstract

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a traffic light detection system is provided for a vehicle. One or more processing devices associated with the system receive at least one image of an area forward of the vehicle via a data interface, with the area including at least one traffic lamp fixture having at least one traffic light. The processing device(s) determine, based on at least one indicator of vehicle position, whether the vehicle is in a turn lane. Also, the processing device(s) process the received image(s) to determine the status of the traffic light, including whether the traffic light includes an arrow. Further, the system may cause a system response based on the determination of the status of the traffic light, whether the traffic light includes an arrow, and whether the vehicle is in a turn lane.

Claims

1. A traffic light detection system for a vehicle, the system comprising:

a data interface configured to receive a plurality of images from an image capture device configured to acquire images of an environment forward of the vehicle, the environment including a traffic lamp fixture having at least one traffic light; and

at least one processing device configured to;

receive the plurality of images via the data interface;

align at least two of the plurality of images based on analysis of brightness distribution;

increase a number of pixels associated with a portion of at least one of the aligned images, wherein the portion corresponds to an area of the at least one of the aligned images in which image data corresponding to the traffic light appears;

determine pixel values associated with the increased number of pixels; and

determine, based on the determined pixel values, at least one characteristic of the traffic light.

2. The traffic light detection system of claim 1, wherein the at least one characteristic is at least one of a shape, color, and position.

3. The traffic light detection system of claim 1, wherein increasing the number of pixels associated with the portion of at least one of the aligned images includes dividing at least one pixel associated with the portion into a plurality of pixels.

4. The traffic light detection system of claim 1, wherein aligning the at least two of the plurality of images includes rotating at least one of the at least two of the plurality of images.

5. The traffic light detection system of claim 1, wherein increasing the number of pixels associated with the portion of at least one of the aligned images includes increasing the number of pixels associated with the portion of at least one of the aligned images such that the aligned images are scaled to a predetermined size.

6. The traffic light detection system of claim 5, wherein increasing the number of pixels associated with the portion of at least one of the aligned images includes determining a scaling factor based on a size of an object in the at least one of the aligned images and the predetermined size.

7. The traffic light detection system of claim 1,

wherein the at least one characteristic of the traffic light includes a shape of a visual component of the traffic light, and

wherein the at least one processing device is further configured to determine whether the shape is an arrow.

8. The traffic light detection system of claim 7, wherein the at least one processing device is further configured to determine a status of the traffic light.

9. The traffic light detection system of claim 8, wherein determining a status of the traffic light includes any of determining whether the traffic light is illuminated, determining a position of the traffic light within the traffic lamp fixture, and determining a color associated with the traffic light.

10. The traffic light detection system of claim 8, wherein the at least one processing device is further configured to determine, based on the determination of whether the shape is an arrow and at least one indicator of vehicle position, whether the vehicle is in a turn lane.

11. The traffic light detection system of claim 10, wherein the at least one processing device is further configured to cause a system response based on the determination of the status of the traffic light, the determination of whether the shape is an arrow, and whether the vehicle is in a turn lane.

12. The traffic light detection system of claim 7, wherein the at least one indicator of vehicle position includes a lane marker recognized based on analysis of at least one of the plurality of images.

13. The traffic light detection system of claim 11, wherein the system response includes any of providing a notice to the driver of the vehicle, applying vehicle brakes, discontinuing cruise control, and initiating an automated turning maneuver.

14. The traffic light detection system of claim 10, wherein the at least one indicator of vehicle position includes a distance to an intersection.

15. The traffic light detection system of claim 10, wherein increasing the number of pixels includes expanding the number of pixels by replacing a pixel with a matrix of pixels.

23. The traffic light detection system of claim 1, wherein the at least one characteristic is a visual appearance characteristic.

16. A vehicle, comprising:

a body;

a data interface configured to receive a plurality of images from an image capture device configured to acquire images of an environment forward of the vehicle, the environment including a traffic lamp fixture having at least one traffic light; and

at least one processing device configured to;

receive the plurality of images via the data interface;

align at least two of the plurality of images based on analysis of brightness distribution;

increase a number of pixels associated with a portion of at least one of the aligned images, wherein the portion corresponds to an area of the at least one of the aligned images in which image data corresponding to the traffic light appears;

determine pixel values associated with the increased number of pixels; and

determine, based on the determined pixel values, at least one characteristic of the traffic light.

17. The vehicle of claim 16, wherein the at least one characteristic is at least one of a shape, color, and position.

18. The vehicle of claim 16, wherein increasing the number of pixels associated with the portion of at least one of the aligned images includes dividing at least one pixel associated with the portion into a plurality of pixels.

19. The vehicle of claim 16, wherein aligning the at least two of the plurality of images includes rotating at least one of the at least two of the plurality of images.

20. The vehicle of claim 16,

wherein the at least one characteristic of the traffic light includes a shape of a visual component of the traffic light, and

wherein the at least one processing device is further configured to determine whether the shape is an arrow.

21. The vehicle of claim 16, wherein increasing the number of pixels includes expanding the number of pixels by replacing a pixel with a matrix of pixels.

22. A method for traffic light detection, comprising:

receiving, from an image capture device, a plurality of images;

aligning at least two of the plurality of images based on analysis of brightness distribution;

increasing a number of pixels associated with a portion of at least one of the aligned images, wherein the portion corresponds to an area of the at least one of the aligned images in which image data corresponding to a traffic light appears;

determining pixel values associated with the increased number of pixels; and

determining, based on the determined pixel values, at least one characteristic of the traffic light.