HUMAN PERCEPTION MODEL FOR SPEED CONTROL PERFORMANCE

• US 20080195569A1
• Filed: 02/12/2007
• Published: 08/14/2008
• Est. Priority Date: 02/12/2007
• Status: Active Grant

• Current Assignee: Deere & Company
• Original Assignee: Deere & Company
• Inventors: Norris, William Robert, Reid, John Franklin, Gilmore, Brian Joseph, Rornig, Bernard Edwin
• Granted Patent: US 7,895,135 B2
• Time in Patent Office: Days
• US Class Current: 706/52
• CPC Class Codes: F02D 2200/501 Vehicle speed
• CPC Class Codes: F02D 2200/606 Driving style, e.g. sporty or economic driving
• CPC Class Codes: F02D 2200/702 Road conditions
• CPC Class Codes: F02D 41/1404 Fuzzy logic control

Abstract

A human perception model for a speed control method including the steps of obtaining a steering angle, a velocity error and a distance error. The method further includes the steps of applying the steering angle, inputting a measure of operator aggressiveness and defuzzifying an output. The applying step includes applying the steering angle, the velocity error and the distance error to fuzzy logic membership functions to produce an output that is applied to a velocity rule base. The inputting step inputs a measure of operator aggressiveness to the velocity rule base. The defuzzifying step defuzzifies an output from the velocity rule base to produce a speed signal.

Claims

1. A human perception model for a speed control method, comprising the steps of:

obtaining a steering angle;

obtaining a velocity error;

obtaining a distance error;

applying said steering angle, said velocity error and said distance error to fuzzy logic membership functions to produce an output that is applied to a velocity rule base;

inputting a measure of operator aggressiveness to said velocity rule base; and

defuzzifying an output from said velocity rule base to produce a speed signal.

2. The method of claim 1, further comprising the step of receiving said speed signal by a vehicle control unit.

3. The method of claim 2, further comprising the step of inputting an operator reaction time to said vehicle control unit.

4. The method of claim 1, further comprising the step of changing set points dependent on said distance error.

5. The method of claim 4, further comprising the step of using operator experience/perception information by said fuzzy logic membership functions.

6. The method of claim 1, further comprising the step of establishing a required path which serves as an input to said obtaining a distance error step.

7. The method of claim 6, wherein said establishing a required path step also serves as an input to said obtaining a velocity error step.

8. The method of claim 6, further comprising the step of establishing required vehicle speed set points as an input to said obtaining a distance error step.

9. The method of claim 8, wherein said establishing required vehicle speed set points step also serves as an input to said obtaining a velocity error step.

10. The method of claim 9, further comprising the step of obtaining at least one of an orientation, a location and a velocity to input to at least one of said obtaining a velocity error step and said obtaining a distance error step.

11. A human perception model for a speed control method, comprising the steps of:

applying a steering angle, a velocity error and a distance error to fuzzy logic membership functions to produce an output that is applied to a velocity rule base;

inputting a measure of operator aggressiveness to said velocity rule base; and

defuzzifying an output from said velocity rule base to produce a speed signal.

12. The method of claim 11, further comprising the step of receiving said speed signal by a vehicle control unit.

13. The method of claim 12, further comprising the step of inputting an operator reaction time to said vehicle control unit.

14. The method of claim 11, further comprising the step of changing set points dependent on said distance error.

15. The method of claim 14, further comprising the step of using operator experience/perception information by said fuzzy logic membership functions.

16. The method of claim 11, further comprising the step of establishing a required path which serves as an input to obtain said distance error.

17. The method of claim 16, wherein said establishing a required path step also serves as an input to obtain said velocity error.

18. The method of claim 16, further comprising the step of establishing required vehicle speed set points as an input to obtain said distance error.

19. The method of claim 18, wherein said establishing required vehicle speed set points step also serves as an input to obtain said velocity error.

20. The method of claim 19, further comprising the step of obtaining at least one of an orientation, a location and a velocity to input obtain said velocity error and said distance error.