Systems and methods for detecting traffic lights

• US 9,272,709 B2
• Filed: 01/30/2015
• Issued: 03/01/2016
• 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
• Primary Examiner(s): Koziol, Stephen R
• Assistant Examiner(s): Gilliard, Delomia L
• Application Number:
  US14/610,495
• Publication Number:
  US 20150210277A1
• Time in Patent Office: 396 Days
• Field of Search: 382/104
• US Class Current: 1/1
• 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 system includes at least one image capture device configured to acquire a plurality of images of a traffic light located in a region above the vehicle, outside of a sightline of a typical driver location in the vehicle. The system further includes a data interface, and at least one processing device. The at least one processing device may be configured to receive the plurality of images via the data interface, determine a status of the traffic light based on analysis of at least a first image from among the plurality of images, determine a change in status of the traffic light based on at least a second image from among the plurality of images, and cause a system response based on the determination of the change in status.

Claims

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

at least one image capture device configured to acquire a plurality of images of a traffic light, wherein the traffic light is located in a region above the vehicle and outside of a sightline of a typical driver location in the vehicle;

a data interface; and

at least one processing device configured to;

receive the plurality of images via the data interface;

determine a status of the traffic light based on analysis of at least a first image from among the plurality of images;

determine a change in status of the traffic light based on at least a second image from among the plurality of images; and

cause a system response based on the determination of the change in status.

2. The traffic light detection system of claim 1, wherein the at least one image capture device includes a sensor and a lens whose focal length is shorter than a short side of the sensor.

3. The traffic light detection system of claim 1, wherein the at least one processing device is further configured to correct optical distortion in the at least a first image.

4. The traffic light detection system of claim 1, wherein a vertical field-of-view from the typical driver location in the vehicle is about 65 degrees and a vertical field-of-view of the at least one image capture device is more than 65 degrees.

5. The traffic light detection system of claim 1, wherein the at least one image capture device is configured for location within the vehicle.

6. The traffic light detection system of claim 1, wherein the at least one processing device is further configured to determine a status of the traffic light when the at least one image capture device acquires the plurality of images through a windshield of the vehicle.

7. The traffic light detection system of claim 1, wherein the at least one image capture device is configured to capture images of traffic lights located in a conic section zone of between 150 to 180 degrees relative to a location of the at least one image capture device.

8. The traffic light detection system of claim 1, wherein the at least one image capture device is configured to capture images of traffic lights located in a conic section zone of between 170 to 180 degrees relative to a location of the at least one image capture device.

9. The traffic light detection system of claim 1, wherein the system response includes reporting the change in status to the driver of the vehicle.

10. The traffic light detection system of claim 1, wherein the system response includes accelerating to a driver-specified cruise speed.

11. The traffic light detection system of claim 1, wherein the at least one processing device is further configured to determine a relevance of the traffic light captured in the plurality of images based on at least one indicator of vehicle position.

12. The traffic light detection system of claim 11, wherein the at least one indicator of vehicle position includes a lane marker recognized based on analysis of the plurality of images.

13. The traffic light detection system of claim 11, wherein the at least one indicator of vehicle position includes a vehicle location acquired by GPS.

14. The traffic light detection system of claim 13, wherein the at least one processing device is configured to compare the GPS acquired vehicle location to map data to determine the relevance of the traffic light.

21. The traffic light detection system of claim 1, wherein the at least one image capture device includes an ultra-wide lens associated with a vertical direction.

15. A vehicle, comprising:

a body;

at least one image capture device configured to acquire a plurality of images of a traffic light, wherein the traffic light is located in a region above the vehicle and outside of a sightline of a typical driver location in the vehicle;

a data interface; and

at least one processing device configured to;

receive the plurality of images via the data interface;

determine a status of the traffic light based on analysis of at least a first image from among the plurality of images;

determine a change in status of the traffic light based on at least a second image from among the plurality of images; and

cause a system response based on the determination of the change in status.

16. The vehicle of claim 15, wherein the at least one image capture device is configured for location within the vehicle.

17. The vehicle of claim 15, wherein the at least one processing device is further configured to determine a status of the traffic light when the at least one image capture device acquires the plurality of images through a windshield of the vehicle.

18. The vehicle of claim 15, wherein the system response includes reporting the change in status to the driver of the vehicle.

19. The vehicle of claim 15, wherein the system response includes accelerating to a driver specified cruise speed.

20. A method for navigating a vehicle, the method comprising:

acquiring, via at least one image capture device, a plurality of images of a traffic light, wherein the traffic light is located in a region above the vehicle and outside of a sightline of a typical driver location in vehicle;

determining a status of the traffic light based on analysis of at least a first image from among the plurality of images;

determining a change in status of the traffic light based on at least a second image from among the plurality of images; and

causing a system response based on the determination of the change in status.