Method and Device for Analyzing Trafficability

• US 20150324649A1
• Filed: 12/06/2013
• Published: 11/12/2015
• Est. Priority Date: 12/11/2012
• Status: Active Grant

• Current Assignee: Conti Temic Microelectronic GmbH (Continental AG)
• Original Assignee: Conti Temic Microelectronic GmbH (Continental AG)
• Inventors: GREWE, Ralph, HEGEMANN, Stefan, ZOBEL, Matthias
• Granted Patent: US 9,690,993 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/40 Analysis of texture depth or shape recovery from texture G06T7/529
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• 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 20/588 Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road

Abstract

The invention relates to a method for analyzing trafficability using a computer, said method comprising the following steps:

• • receiving image data of surroundings (10) in front of a vehicle (S10),
  • analyzing the image data to identify different zones (12, 14, 16, 18, 24) in an image of the surroundings (S12, S14, S16, S18, S20); and
  • analyzing identified different zones (16, 18) in terms of trafficability for the vehicle (S22, S24).

Claims

1. A method for analyzing trafficability using a computer, said method comprising the following steps:

receiving image data of surroundings (10) in front of a vehicle (S10),

analyzing the image data to identify different zones (12, 14, 16, 18, 24) in an image of the surroundings (S12, S14, S16, S18, S20), and

analyzing identified different zones (16, 18) in terms of trafficability for the vehicle (S22, S24).

2. The method according to claim 1, characterized in that the analyzing of the image data to identify different zones comprises the following steps:

calculating of the position of pixels in the space from the image data received from a plurality of images with the aid of a stereovision method (S12),

estimating of a ground plane (12) based on the calculated positions of pixels in the space (S14),

determining of relevant pixels (S16) for a segmenting of the estimated ground plane (12),

carrying out of a segmenting of the estimated ground plane for the relevant pixels (S18), and

outputting of different zones identified by the segmenting (14, 16, 18, 20, 22;

S20).

3. The method according to claim 2, characterized in that a method based on images of surroundings captured with a plurality of camera optics or camera imagers, or a method based on recording with a camera optic at various positions using the vehicle'"'"'s own movement, is used as the stereovision method.

4. The method according to claim 2, characterized in that the segmenting of the estimated ground plane for the relevant pixels is carried out using color, saturation, intensity and/or texture information.

5. The method according to claim 2, characterized in that the segmenting of the estimated ground plane is carried out for the relevant pixels using variance information from the calculated positions of pixels in the space.

6. The method according to claim 1, characterized in that the analyzing of identified different zones in terms of trafficability for the vehicle comprises the identifying of obstacles (20, 22;

30, 32;

S22) comprising raised objects, and/or the identifying of driving activities (28;

S24).

7. The method according to claim 6, characterized in that the identifying of driving activities comprises the receiving and evaluating of data from camera-based, radar-based and/or lidar-based object detection and/or the receiving and evaluating of a list of objects produced with camera-based, radar-based and/or lidar-based object detection.

8. The method according to claim 6, characterized in that the identification of driving activities comprises long-term monitoring of driving activities in order to increase the reliability of detection, the transferring of a trafficability classification to similar image zones and/or a dynamic exclusion of trafficability, in the event of a risk being identified by driving activity monitoring.

9. A device for analyzing trafficability using a computer having

first means (106, 110) for receiving image data of surroundings (10) in front of a vehicle,

second means (108, 110, 112, 114) for analyzing the image data to identify different zones (12, 14, 16, 18, 24) in an image of the surroundings, and

third means (116) for analyzing identified different zones (16, 18) in terms of trafficability for the vehicle.

10. The device according to claim 9, characterized in that

the second means (108, 110, 112, 114) are configured to carry out a method comprising the following steps:

calculating of the position of pixels in the space from the image data received from a plurality of images with the aid of a stereovision method (S12),

estimating of a ground plane (12) based on the calculated positions of pixels in the space (S14),

determining of relevant pixels (S16) for a segmenting of the estimated ground plane (12),

carrying out of a segmenting of the estimated ground plane for the relevant pixels (S18), and

outputting of different zones identified by the segmenting (14, 16, 18, 20, 22;

S20); and

the third means (116) are configured to carry out a method wherein the analyzing of identified different zones in terms of trafficability for the vehicle comprises the identifying of obstacles (20, 22;

30, 32;

S22) comprising raised objects, and/or the identifying of driving activities (28;

S24).