System and Method for Controlling Vehicle Headlights

• US 20080294315A1
• Filed: 04/07/2008
• Published: 11/27/2008
• Est. Priority Date: 06/07/1995
• Status: Active Grant

• Current Assignee: American Vehicular Sciences LLC (Acacia Research Corporation)
• Original Assignee: Intelligent Technologies International, Inc.
• Inventors: Breed, David S.
• Granted Patent: US 8,538,636 B2
• Time in Patent Office: Days
• US Class Current: 701/49
• CPC Class Codes: B60N 2/002 Seats provided with an occupancy detection means mounted therein or thereon detection means responsive to presence or absence of children B60N2/266
• CPC Class Codes: B60N 2/0268 using sensors or detectors for adapting the seat or seat part, e.g. to the position of an occupant
• CPC Class Codes: B60N 2/0272 using sensors or detectors for detecting the position of seat parts
• CPC Class Codes: B60Q 1/143 combined with another condition, e.g. using vehicle recognition from camera images or activation of wipers
• CPC Class Codes: B60Q 2300/41 preceding vehicle
• CPC Class Codes: B60Q 2300/42 oncoming vehicle
• CPC Class Codes: B60R 16/037 for occupant comfort , e.g. for automatic adjustment of appliances according to personal settings, e.g. seats, mirrors, steering wheel
• CPC Class Codes: B60R 2001/1223 with sensors or transducers
• CPC Class Codes: B60R 2001/1253 with cameras, video cameras or video screens
• CPC Class Codes: B60R 2021/0027 Post collision measures, e.g. notifying emergency services
• CPC Class Codes: B60R 2021/01315 monitoring occupant displacement
• CPC Class Codes: B60R 21/0134 responsive to imminent contact with an obstacle , e.g. using radar systems
• CPC Class Codes: B60R 21/01516 using force or pressure sensing means
• CPC Class Codes: B60R 21/0153 using field detection presence sensors
• CPC Class Codes: B60R 21/01534 using electromagneticwaves, e.g. infrared
• CPC Class Codes: B60R 21/01536 using ultrasonic waves
• CPC Class Codes: B60R 21/01538 for image processing, e.g. cameras or sensor arrays
• CPC Class Codes: B60R 21/01542 detecting passenger motion
• CPC Class Codes: B60R 21/01544 detecting seat belt parameters, e.g. length, tension or height-adjustment
• CPC Class Codes: B60R 21/01548 sensing the amount of belt winded on retractor
• CPC Class Codes: B60R 21/01552 : detecting position of specific human body parts, e.g. face, eyes or hands
• CPC Class Codes: B60R 21/01554 : Seat position sensors
• CPC Class Codes: B60R 21/203 : in steering wheels or steering columns
• CPC Class Codes: B60R 25/25 : using biometry
• CPC Class Codes: B60R 25/255 : Eye recognition
• CPC Class Codes: B60R 25/257 : Voice recognition
• CPC Class Codes: E05F 15/43 : responsive to disruption of energy beams, e.g. light or sound
• CPC Class Codes: E05F 15/431 : specially adapted for vehicle windows or roofs
• CPC Class Codes: E05F 2015/433 : using reflection from the obstruction
• CPC Class Codes: E05Y 2900/55 : Windows
• CPC Class Codes: G01S 13/04 : Systems determining presence of a target based on relative movement of target G01S13/56
• CPC Class Codes: G01S 15/04 : Systems determining presence of a target
• CPC Class Codes: G01S 15/06 : Systems determining the position data of a target
• CPC Class Codes: G01S 15/87 : Combinations of sonar systems
• CPC Class Codes: G01S 15/88 : Sonar systems specially adapted for specific applications seismic or acoustic prospecting or detecting G01V1/00
• CPC Class Codes: G01S 17/88 : Lidar systems specially adapted for specific applications
• CPC Class Codes: G01S 17/89 : for mapping or imaging
• CPC Class Codes: G01S 7/417 : involving the use of neural networks
• CPC Class Codes: G01S 7/4802 : using analysis of echo signal for target characterisation; Target signature; Target cross-section
• CPC Class Codes: G01S 7/539 : using analysis of echo signal for target characterisation; Target signature; Target cross-section
• CPC Class Codes: G06V 10/82 : using neural networks
• CPC Class Codes: G06V 20/584 : of vehicle lights or traffic lights
• CPC Class Codes: G06V 20/59 : inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
• CPC Class Codes: G06V 40/10 : Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G10K 2210/1282 : Automobiles
• CPC Class Codes: G10K 2210/3219 : Geometry of the configuration

Abstract

Control system and method for automatically controlling headlights of a vehicle includes an optical system for imaging external sources of light within a predetermined field of view and an image processing system for processing images from the optical system and providing a control signal for controlling the headlights as a function of the processed images. Processing the images may entail identifying a source of radiation in the images, the control signal being provided to dim the headlights when a source of radiation in the images is identified as a headlight or taillight of another vehicle. To this end, the image processing system may include a trained pattern recognition system for processing the images to identify the source of radiation, e.g., a pattern recognition algorithm generated from data of possible sources of radiation including headlights and taillights of vehicles and patterns of received radiation from the possible sources.

Claims

1. A control system for automatically controlling headlights of a vehicle, comprising:

an optical system for imaging external sources of light within a predetermined field of view; and

an image processing system for processing images from said optical system and providing a control signal for controlling the headlights as a function of the processed images.

2. The control system of claim 1, wherein the processing of the images by said image processing system includes identifying a source of radiation in the images, the control signal being provided to dim the headlights when a source of radiation in the images is identified as headlight or taillight of another vehicle.

3. The control system of claim 1, wherein said image processing system comprises trained pattern recognition means for processing the images to identify the source of radiation.

4. The control system of claim 3, wherein said pattern recognition means are structured and arranged to apply a pattern recognition algorithm generated from data of possible sources of radiation including headlights of vehicles and patterns of received radiation from the possible sources.

5. The control system of claim 4, wherein the possible sources of radiation further includes taillights of vehicles.

6. The control system of claim 3, wherein said trained pattern recognition means comprise a neural network.

7. The control system of claim 1, wherein said optical system comprises a CCD array.

8. The control system of claim 1, wherein said optical system is arranged on a rear view mirror in an interior of the vehicle.

9. The control system of claim 1, wherein said optical system is arranged on a part of the vehicle that is not movable relative to a frame of the vehicle.

10. The control system of claim 1, wherein said optical system includes an image array sensor containing a plurality of pixels.

11. The control system of claim 1, wherein said optical system includes a plurality of image array sensors.

12. A method for automatically controlling headlights of a vehicle, comprising:

imaging external sources of light within a predetermined field of view to obtain images of an environment outside of the vehicle;

processing the obtained images from the optical system; and

providing a control signal for controlling the headlights as a function of the processed images.

13. The method of claim 12, wherein the step of processing the obtained images comprises identifying a source of radiation in the images, and the step of providing the control signal comprises providing a control signal to dim the headlights when a source of radiation in the images is identified as headlight or taillight of another vehicle.

14. The method of claim 12, wherein the step of processing the images comprises training a pattern recognition algorithm to identify the source of radiation in a training stage in which known sources of radiation are provided, images including these known sources are obtained and the pattern recognition is formed based on the association of the known sources with the obtained images.

15. The method of claim 14, wherein the pattern recognition algorithm is a neural network.

16. The method of claim 12, further comprising arranging an optical system on a rear view mirror in an interior of the vehicle to image the external sources of light.

17. The method of claim 12, further comprising arranging an optical system on a part of the vehicle that is not movable relative to a frame of the vehicle to image the external sources of light.

18. The method of claim 12, wherein the step of imaging the external sources of light comprises arranging an image array sensor containing a plurality of pixels on the vehicle.

19. The method of claim 12, wherein the step of imaging the external sources of light comprises arranging a plurality of image array sensors on the vehicle.

20. In a vehicle including headlights and a rear view mirror situated inside a passenger compartment of the vehicle, a control system for automatically controlling the headlights of a vehicle, comprising:

an optical system for imaging external sources of light, said optical system being arranged on said rear view mirror;

an image processing system for receiving images from said optical system and identifying whether sources of light in the images originate from headlights or taillights of other vehicles,

said image processing system being arranged to dim the headlights when it identifies that a source of light in an image originates from the headlights or taillights of another vehicle.