Collision and injury mitigation system using fuzzy cluster tracking

• US 6,898,528 B2
• Filed: 07/23/2002
• Issued: 05/24/2005
• Est. Priority Date: 07/23/2002
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Cheok, Ka C., Smid, Edzko, Rao, Manoharprasad K., Zorka, Nicholas
• Primary Examiner(s): Black, Thomas G.
• Assistant Examiner(s): To, Tuan C
• Application Number:
  US10/201,676
• Publication Number:
  US 20040019425A1
• Time in Patent Office: 1,036 Days
• Field of Search: 180/730.2, 180/268, 180/283, 180/271, 180/273, 180/274, 180/282, 180/167, 180/169, 340/903, 382/111, 382/156, 342/52, 342/53, 342/54, 342/72, 342/60, 342/70, 342/71, 342/195, 701/301, 701/45, 706/57, 706/2, 706/46, 706/900, 706/905, 706/8, 280/735, 280/734, 280/728.1
• US Class Current: 701/301
• CPC Class Codes: G08G 1/163 involving continuous checking

Abstract

A collision and injury mitigation system (10) for an automotive vehicle (12) is provided. The system (10) includes two or more object detection sensors (15) that detect an object and generate one or more object detection signals. A controller (16) is electrically coupled to the two or more object detection sensors and performs a fuzzy logic technique to classify the object as a real object or a false object in response to the one or more object detection signals. A method for performing the same is also provided.

Claims

1. A collision and injury mitigation system for an automotive vehicle comprising:

two or more object detection sensors detecting an object and generating one or more object detection signals; and

a controller electrically coupled to said two or more object detection sensors performing a fuzzy logic technique to classify said object as a real object or a false object in response to said one or more object detection signals.

2. A system as in claim 1 wherein performing a fuzzy logic to classify said object comprises performing a clustering method.

3. A system as in claim 1 further comprises said controller using triangulation in combination with said fuzzy logic to classify said object.

4. A system as in claim 1 further comprising a filter to track said object relative to the vehicle or an object other than the vehicle.

5. A system as in claim 4 wherein said filter is a Kalman filter.

6. A system as in claim 1 wherein said controller in classifying said object determines velocity of said object relative to the vehicle or an object other than the vehicle.

7. A system as in claim 1 wherein said controller in classifying said object determines direction of travel of said object relative to the vehicle or an object other than the vehicle.

8. A system as in claim 1 wherein said controller in classifying said object predicts velocity of said object relative to the vehicle or an object other than the vehicle.

9. A system as in claim 1 wherein said controller in classifying said object predicts direction of travel of said object relative to the vehicle or an object other than the vehicle.

10. A system as in claim 1 wherein said controller in classifying said object utilizes magnitude of said one or more object detection signals.

11. A system as in claim 1 further comprising:

a countermeasure electrically coupled to said controller;

said controller activating said countermeasure in response to said object classification.

12. A system as in claim 1 wherein said controller assesses the threat of said object in response to said object classification.

13. A method of classifying an object by a collision and injury mitigation system for an automotive vehicle comprising:

detecting an object and generating one or more object detection signals; and

performing a fuzzy logic technique to classify said detected object as a real object or a false object in response to said one or more object detection signals.

14. A method as in claim 13 further comprising assessing the threat of said one or more objects in response to said object classification.

15. A method as in claim 13 further comprising filtering said one or more object detection signals to track said object.

16. A method as in claim 13 further comprises filtering said one or more object detection signals to predict the future path of said object.

17. A method as in claim 13 wherein said clustering method comprises using at least one of the following:

amplitude information, range rate information, or range information.

18. A method of classifying an object by a collision and injury mitigation system for an automotive vehicle comprising:

detecting one or more objects and generating one or more object detection signals;

performing a triangulation technique on said object detection signals and generating an object detection database;

performing a fuzzy logic clustering technique on said object detection database and generating clusters;

filtering said clusters to remove false objects from said object detection database and generating an real object list; and

classifying objects in said real object list.

19. A method as in claim 18 further comprising determining admissibility of said object detection signals.

20. A method as in claim 18 further comprising assessing the threat of an object in said real object list.

21. A collision and injury mitigation system for an automotive vehicle comprising:

two or more object detection sensors detecting an object and generating one or more object detection signals;

a countermeasure; and

a controller electrically coupled to said two or more object detection sensors performing a triangulation technique and a fuzzy logic technique to generate clusters and filtering said clusters to classify said object as a real object or a false object in response to said one or more object detection signals, said controller activating said countermeasure in response to said object classification.