Method and apparatus for rear cross traffic collision avoidance

• US 20080306666A1
• Filed: 06/05/2007
• Published: 12/11/2008
• Est. Priority Date: 06/05/2007
• Status: Abandoned Application

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations Incorporated (Motors Liquidation Co. GUC Trust)
• Inventors: Zeng, Shuqing, Ganesan, Prasanna Vignesh V., Salinger, Jeremy A.
• Application Number:
  US11/758,187
• Publication Number:
  US 20080306666A1
• Time in Patent Office: Days
• US Class Current: 701/70
• CPC Class Codes: B60Q 9/006 using a distance sensor
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/168 Driving aids for parking, e.g. acoustic or visual feedback on parking space

Abstract

A rear cross-traffic collision avoidance system that provides a certain action, such as a driver alert or automatic braking, in the event of a collision threat from cross-traffic. The system includes object detection sensors for detecting objects in the cross-traffic and vehicle sensors for detecting the vehicle turning. A controller uses the signals from the object detection sensors and the vehicle sensors to determine and identify object tracks that may interfere with the subject vehicle based on the vehicle turning.

Claims

1. A system for providing rear cross-traffic collision avoidance for a subject vehicle, said system comprising:

object detection sensors for detecting objects and providing object sensor signals;

vehicle sensors for sensing vehicle turning and providing vehicle sensor signals;

an object tracking and classification processor responsive to the object sensor signals, said tracking and classification processor identifying and tracking objects that potentially may interfere with the subject vehicle and providing target identification and tracking signals;

a host vehicle path prediction processor responsive to the vehicle sensor signals, said host vehicle path prediction processor providing path curvature signals indicating the curvature of a path of the subject vehicle;

a target selection processor responsive to the target identification and tracking signals and the path curvature signals, said target selection processor identifying potential objects in the tracking and classification signals that may be in a collision path with the subject vehicle, and providing potential objects signals; and

a threat assessment processor responsive to the potential objects signal and determining whether action should be taken to avoid a collision with an object.

2. The system according to claim 1 wherein the threat assessment processor determines whether a potential collision with an object is a minor potential collision or an imminent collision.

3. The system according to claim 2 wherein the threat assessment processor provides a visual, auditory and/or sensory warning to the subject vehicle driver if the threat assessment processor determines that the potential collision is a minor potential collision.

4. The system according to claim 3 wherein the threat assessment processor provides the warning if the object would have to execute a maneuver that would require the object to apply braking above a predetermined threshold or swerve with a lateral acceleration above a predetermined threshold.

5. The system according to claim 2 wherein the threat assessment processor causes the vehicle brakes to be applied if the threat assessment processor determines that the potential collision is an imminent collision.

6. The system according to claim 5 wherein the threat assessment processor causes the vehicle brakes to be applied if the object would have to brake above a predetermined threshold or swerve with a lateral acceleration above a predetermined threshold to avoid a collision with the subject vehicle.

7. The system according to claim 1 wherein the object detection sensors are selected from the group consisting of radar sensors and cameras.

8. The system according to claim 1 wherein the vehicle sensors are selected from the group consisting of steering wheel angle sensors and yaw rate sensors.

9. The system according to claim 1 wherein the host vehicle path prediction processor uses a bicycle model to determine the curvature of the path of the subject vehicle.

10. The system according to claim 1 wherein the object tracking classification processor uses a Kalman filter tracker to fuse object tracks.

11. The system according to claim 1 wherein the object detection sensors are positioned at a rear of the subject vehicle and the system is a cross-traffic collision avoidance system so as to prevent the subject vehicle from colliding with another vehicle when the subject vehicle backs into cross-traffic.

12. A system for providing rear cross-traffic collision avoidance between a subject vehicle backing into cross-traffic and target vehicles traveling in the cross-traffic, said system comprising:

object detection sensors for detecting the target vehicles in the cross-traffic as the subject vehicle backs up;

vehicle sensors for detecting turning of the subject vehicle; and

a controller for determining a path curvature of the subject vehicle and identifying and tracking target vehicles that potentially may interfere with the subject vehicle, said controller causing certain actions to be taken if a potential collision with one of the target vehicles is determined.

13. The system according to claim 12 wherein the controller determines whether the potential collision with one of the target vehicles is a minor potential collision or an imminent collision.

14. The system according to claim 13 wherein the controller causes a warning to the subject vehicle driver if the potential collision is a mild potential collision and provides automatic braking if the potential collision is an imminent collision.

15. The system according to claim 12 wherein the object detection sensors are selected from the group consisting of radar sensors and cameras.

16. The system according to claim 12 wherein the vehicle sensors are selected from the group consisting of steering wheel angle sensors and yaw rate sensors.

17. The system according to claim 12 wherein the controller uses a bicycle model to determine the curvature of the path of the subject vehicle.

18. The system according to claim 12 wherein the controller uses a Kalman filter tracker to fuse object tracks.

19. A method for providing rear cross-traffic collision avoidance between a subject vehicle backing into cross-traffic and target vehicles traveling in the cross-traffic, said method comprising:

detecting the target vehicles in the cross-traffic;

detecting turning of the subject vehicle as the subject vehicle backs into the cross-traffic;

identifying and tracking the target vehicles in the cross-traffic that may potentially interfere with the subject vehicle;

determining a path curvature of the subject vehicle; and

causing certain actions to be taken if a potential collision with one of the target vehicles is determined.

20. The method according to claim 19 wherein causing certain actions to be taken includes providing a vehicle warning if the potential collision is considered minor and providing vehicle braking if the potential collision is determined to be imminent.