Method for detecting a traffic lane by means of a camera

• US 9,257,045 B2
• Filed: 07/06/2012
• Issued: 02/09/2016
• Est. Priority Date: 08/05/2011
• Status: Active Grant

• Current Assignee: Conti Temic Microelectronic GmbH (Continental AG)
• Original Assignee: Conti Temic Microelectronic GmbH (Continental AG)
• Inventors: Zobel, Matthias, Heinrich, Stefan, Klein, Wladimir
• Primary Examiner(s): PHAM, TOAN NGOC
• Application Number:
  US14/234,485
• Publication Number:
  US 20140152432A1
• Time in Patent Office: 1,313 Days
• Field of Search: 340/435, 340/436, 340/425.5, 340/933, 340/937
• US Class Current: 1/1
• 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 1/167 Driving aids for lane monitoring, lane changing, e.g. blind spot detection

Abstract

A method of detecting a roadway edge and/or a traffic lane on a roadway includes:

• • acquiring at least one image of surroundings of a vehicle with a camera;
  • detecting a driving corridor from the at least one image; and
  • performing a structure detection on the at least one image while taking the determined driving corridor into consideration in order to determine a course of a roadway edge from the at least one image.

Claims

1. A method for traffic lane detection in a driver assistance system of a vehicle, comprising the following steps performed in the driver assistance system:

with a camera, acquiring at least one image of surroundings of the vehicle;

detecting a driving corridor from the at least one image;

performing structure detection in the at least one image while taking the detected driving corridor into consideration to detect a roadway edge and to determine a course of the roadway edge from the at least one image; and

based on the determined course of the roadway edge, estimating a position of a traffic lane to perform the traffic lane detection.

2. The method according to claim 1, wherein the camera is a stereo camera and information about a height of an area in front of the vehicle in the image is analyzed for detecting the driving corridor.

3. The method according to claim 1, wherein the camera is a mono camera, by which a sequence of successive images of the surroundings of the vehicle is acquired, wherein a spatial structure of at least motionless aspects of the surroundings of the vehicle is inferred from changes in the successive images and information about a height of the spatial structure of the motionless aspects of the surroundings of the vehicle in front of the vehicle is analyzed for detecting the driving corridor.

4. The method according to claim 1, wherein results of previous detections are stored and are used as a basis for a comparison for performing the detecting of the driving corridor.

5. The method according to claim 1, wherein data of at least one vehicle dynamics sensor are additionally taken into consideration when detecting the driving corridor.

6. The method according to claim 1, wherein data of at least one radar sensor and/or lidar sensor are additionally taken into consideration when detecting the driving corridor.

7. The method according to claim 1, wherein the structure detection is only performed in an area of the at least one image in which the detected driving corridor is situated.

8. The method according to claim 1, wherein the structure detection is based on region segmentation of the at least one image.

9. The method according to claim 1, wherein the structure detection is based on a correlation analysis, in which the at least one image or an image detail thereof is compared with stored patterns of typical roadway edges.

10. The method according to claim 1, further comprising a step of outputting to a driver of the vehicle, an information about the determined course of the roadway edge.

11. The method according to claim 1, further comprising taking information about lane markings from a lane marking detection into consideration for the traffic lane detection.

12. The method according to claim 1, further comprising, in the driver assistance system, performing an automatic driver assistance function in response to and dependent on the determined course of the roadway edge.

13. The method according to claim 1, wherein results of previous detections are stored and are used as a basis for a comparison for performing the structure detection to detect the roadway edge.

14. A method of operating a driver assistance system of a vehicle to determine a traffic lane on a roadway on which the vehicle is driving, comprising steps:

a) with a camera, producing image data of surroundings of the vehicle including a driving surface of the roadway and an adjacent area that is adjacent to the driving surface and off of the roadway;

b) in the driver assistance system, performing a structure detection on the image data regarding the driving surface of the roadway and the adjacent area, and from the structure detection detecting a physical roadway edge of the driving surface of the roadway as a border between the driving surface and the adjacent area;

c) in the driver assistance system, performing a lane determination comprising estimating a position of the traffic lane on the roadway relative to the physical roadway edge; and

d) outputting from the driver assistance system to a driver of the vehicle an information regarding the position of the traffic lane or the physical roadway edge, or performing with the driver assistance system an automatic driver assistance function responsive to and dependent on the position of the traffic lane or the physical roadway edge.

15. The method according to claim 14, wherein the lane determination is performed without consideration of lane lines or other roadway markings on the roadway, and whether or not there are lane lines or other roadway markings present on the roadway.

16. The method according to claim 14, further comprising detecting, in the image data, lane lines or other roadway markings on the roadway, and wherein the lane determination further comprises determining the position of the traffic lane from the detected lane lines or other roadway markings merged or plausibilized with the position estimated relative to the physical roadway edge.

17. The method according to claim 14, further comprising:

detecting, in the image data, lane lines or other roadway markings, and

based on a position of the detected lane lines or other roadway markings selecting a portion of the image data to be evaluated in the structure detection to detect the physical roadway edge, or based on a position of the detected physical roadway edge selecting a portion of the image data to be evaluated for the detecting of the lane lines or other roadway markings.

18. The method according to claim 14, wherein the structure detection comprises pattern recognition by comparing an actual pattern of the image data regarding the driving surface of the roadway and the adjacent area, with stored patterns of typical roadway edges.

19. The method according to claim 14, wherein the structure detection comprises performing region segmentation on the image data to segment the image data into distinct regions including a first region containing the driving surface and a second region containing the adjacent area.

20. The method according to claim 14, wherein the step d) comprises the performing of the automatic driver assistance function responsive to and dependent on the position of the traffic lane or the physical roadway edge.