REAR CAMERA LANE DETECTION

• US 20180025234A1
• Filed: 07/20/2016
• Published: 01/25/2018
• Est. Priority Date: 07/20/2016
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Myers, Scott Vincent, Gurghian, Alexandru Mihai, Micks, Ashley Elizabeth, Walsh, Alexandro
• Granted Patent: US 10,762,358 B2
• Time in Patent Office: Days
• CPC Class Codes: B60R 2300/301 combining image information with other obstacle sensor information, e.g. using RADAR/LIDAR/SONAR sensors for estimating risk of collision
• CPC Class Codes: B60R 2300/307 virtually distinguishing relevant parts of a scene from the background of the scene
• CPC Class Codes: B60R 2300/804 for lane monitoring
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 10/82 using neural networks
• 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: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G08G 1/167 Driving aids for lane monitoring, lane changing, e.g. blind spot detection
• CPC Class Codes: H04N 23/90 Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums

Abstract

A method for determining lane information includes receiving perception data from at least two sensors, the at least two sensors including a rear facing camera of a vehicle. The method includes determining, based on the perception data, a number of lanes on a roadway within a field of view captured by the perception data using a neural network. The method includes providing an indication of the number of lanes to an automated driving system or driving assistance system.

Claims

1. A method comprising:

receiving perception data from at least two sensors, the at least two sensors including a rear facing camera of a vehicle;

determining, based on the perception data, a number of lanes on a roadway within a field of view captured by the perception data using a neural network; and

providing an indication of the number of lanes to an automated driving system or driving assistance system.

2. The method of claim 1, the method further comprising determining a current lane in which the vehicle is located using a neural network, wherein the current lane corresponds to a lane position of the vehicle at a time when the perception data was obtained.

3. The method of claim 1, wherein the at least two sensors comprise the rear facing camera and one or more of a light detection and ranging (LIDAR) system, a radar system, an ultrasound sensing system, or an infrared camera system.

4. The method of claim 1, further comprising determining, based on the perception data, road slope in one or more of a vertical direction or a horizontal direction.

5. The method of claim 1, further comprising determining one or more of a driving trajectory or collision avoidance options based on the number of lanes.

6. The method of claim 1, further comprising storing the indication of the number of lanes in a drive history for later access.

7. The method of claim 1, further comprising uploading the indication of the number of lanes to a remote storage location.

8. The method of claim 7, further comprising:

determining a current location of the vehicle;

retrieving drive history data from the remote storage location, wherein the drive history indicates a number of lanes for the current location; and

broadcasting the number of lanes for the current location to one or more vehicle controllers of an automated driving system or driving assistance system.

9. A system comprising:

a perception data component configured to receive perception data from at least two sensors, the at least two sensors including a rear facing camera of a vehicle;

a lane number component configured to determine, using a neural network, a number of lanes on a roadway within a field of view captured by the perception data; and

a report component configured to provide an indication of the number of lanes to an automated driving system or driving assistance system.

10. The system of claim 9, further comprising a current lane component configured to determine a current lane in which the vehicle is located using a neural network, wherein the current lane corresponds to a lane position of the vehicle at a time when the perception data was obtained.

11. The system of claim 9, further comprising a fusion component configured to generate fused sensor data based on the perception data from the at least two sensors, wherein determining the number of lanes comprises determining based on the fused sensor data.

12. The system of claim 9, wherein the at least two sensors comprise the rear facing camera and one or more of a light detection and ranging (LIDAR) system, a radar system, an ultrasound sensing system, or an infrared camera system.

13. The system of claim 9, further comprising a slope component configured to determine, based on the perception data, road slope in one or more of a vertical direction or a horizontal direction.

14. The system of claim 9, further comprising a maneuver component configured to determine one or more of a driving trajectory or collision avoidance options based on the number of lanes.

15. The system of claim 9, wherein the report component is further configured to upload the indication of the number of lanes to a remote storage location.

16. The system of claim 15, further comprising:

a location component configured to determine a current location of the vehicle; and

a drive history component configured to;

retrieve drive history data from the remote storage location, wherein the drive history indicates one or more of a number of lanes or a slope for the current location; and

broadcast the number of lanes or the slope for the current location to one or more vehicle controllers of an automated driving system or driving assistance system.

17. Computer readable storage media storing instructions that, when executed by one or more processors, cause the processors to:

receive perception data from at least two sensors, the at least two sensors including a rear facing camera of a vehicle;

determine, based on the perception data, a number of lanes on a roadway within a field of view of the perception data using a neural network; and

provide an indication of the number of lanes to an automated driving system or driving assistance system.

18. The computer readable storage media of claim 17, further storing instructions that cause the processors to determine a current lane in which the vehicle is located using a neural network, wherein the current lane corresponds to a lane position of the vehicle at a time when the perception data was obtained.

19. The computer readable storage media of claim 17, further storing instructions that cause the processors to determine one or more of a driving trajectory or collision avoidance options based on the number of lanes.

20. The computer readable storage media of claim 17, further storing instructions that cause the processors to:

determine a current location of the vehicle;

retrieve drive history data from the remote storage location, wherein the drive history indicates a number of lanes for the current location; and

broadcast the number of lanes for the current location to one or more vehicle controllers of an automated driving system or driving assistance system.