System and method for actuating vehicle safety device using damped measures

• US 5,337,238 A
• Filed: 10/08/1991
• Issued: 08/09/1994
• Est. Priority Date: 10/08/1991
• Status: Expired due to Term

• Current Assignee: Automotive Systems Laboratory, Incorporated (Ningbo Junsheng Investment Group Co., Ltd.)
• Original Assignee: Automotive Systems Laboratory, Incorporated (Ningbo Junsheng Investment Group Co., Ltd.)
• Inventors: Gioutsos, Tony, Piskie, Michael A.
• Primary Examiner(s): Black, Thomas G.
• Assistant Examiner(s): PARK, COLLIN
• Application Number:
  US07/773,676
• Time in Patent Office: 1,036 Days
• Field of Search: 364/424.01, 364/424.05, 307/10.1, 180/268, 180/271, 180/282, 280/728, 280/734, 280/735, 340/436, 340/669
• US Class Current: 701/47
• CPC Class Codes: B60R 2021/01322 comprising variable thresholds, e.g. depending from other collision parameters
• CPC Class Codes: B60R 21/0132 responsive to vehicle motion parameters , e.g. to vehicle longitudinal or transversal deceleration or speed value
• CPC Class Codes: B60R 21/01332 by frequency or waveform analysis
• CPC Class Codes: B60R 21/01336 using filtering

Abstract

A system and method for triggering deployment of a vehicle air bag in response to a crash or sudden vehicle deceleration responsive to values for modified velocity, predicted acceleration, high-frequency velocity, and high-variance velocity. The air bag is triggered when at least two of the values for modified velocity, predicted acceleration, high-frequency velocity, and high-variance velocity exceed their respective thresholds.

Claims

1. A system for actuating a vehicle safety device in the event of a vehicle crash or sudden vehicle deceleration comprises:

means for generating sampled data representative of the instantaneous acceleration of said vehicle;

a RAM for storing consecutive values of said acceleration data;

means for calculating a low-variance jerk value from said stored data set;

means for calculating a high-variance jerk value from said stored data set;

means for calculating at least one modified velocity value from said stored data set;

means for calculating a predicted acceleration value using said low-variance jerk value;

means for calculating a high-frequency velocity value using said low-variance jerk value;

means for calculating a high-variance velocity value using said high-variance jerk value; and

means responsive to said values for modified velocity, predicted acceleration, high-frequency velocity, and high-variance velocity for actuating said vehicle safety device when at least two of said values exceed threshold values therefor.

2. A method for actuating a vehicle safety device in the event of a vehicle crash or sudden vehicle deceleration comprising the steps of:

receiving information representative of instantaneous vehicle acceleration;

storing said received acceleration information in a RAM;

generating a low-variance jerk value from said stored acceleration information;

generating a high-variance jerk value from said stored acceleration information;

generating a first velocity value and a second velocity value using said stored acceleration information;

generating a predicted acceleration value using said low-variance jerk value;

generating a high-frequency past history value using said low-variance jerk value;

generating a high-variance past history value using said high-variance jerk value; and

actuating said vehicle safety device if, while said first velocity value exceeds a first threshold value, said predicted acceleration value has exceeded a second threshold value and said high-variance velocity value has exceeded a second threshold value; and

while said second velocity value exceeds a fourth threshold value, said predicted acceleration value has exceeded a fifth threshold value and said high-frequency past history measure has exceeded a sixth threshold value.

3. The method of claim 2, wherein said step of generating said low-variance jerk value from said stored acceleration information includes the steps of:

separating said stored acceleration information into a first data set and a second data set, said first data set containing older received acceleration information than said second data set;

rank-order filtering said stored acceleration information in said first data set and said second data set, respectively;

inverting a value of said stored acceleration information having a given rank in said first data set; and

combining a value of said stored acceleration information having a rank in said second data set equal to said given rank with said inverted value of said acceleration information having said given rank in said first data set.

4. The method of claim 2, wherein said step of generating a high-variance jerk value from said stored acceleration information includes the steps of:

rank-order filtering said stored acceleration information;

inverting a low-rank value of said stored acceleration information; and

combining a high-rank value of said stored acceleration information with said inverted low-rank value of said stored acceleration information.

5. The method of claim 2, wherein said step of generating said first and second velocity measures using said received acceleration information includes the steps of:

rank-order filtering said stored acceleration information; and

integrating a low-rank value of said stored acceleration information to obtain said first velocity measure; and

integrating stored acceleration information having a high rank and stored acceleration having a high rank.

6. The method of claim 5, including the step of modifying said rank-order filtered acceleration information prior to said integrating step.

7. The method of claim 6, wherein said step of modifying said rank-order filtered acceleration information includes the steps of:

generating a modification factor using at least one of the group consisting of a predetermined constant, said received acceleration information, said first velocity value, said second velocity value, said low-variance jerk value and said high-variance jerk value; and

subtracting said modification factor from said rank-order filtered acceleration information.

8. The method of claim 2, wherein said step of generating said predicted acceleration value using said low-variance jerk value includes the steps of:

accumulating said low-variance jerk value over time to obtain a first accumulated value for low-variance jerk; and

periodically subtracting a damp factor from said first accumulated value for low-variance jerk to obtain said predicted acceleration value.

9. The method of claim 8, wherein said low-variance jerk value is added to said first accumulated value for low-variance jerk only when the absolute value of said low-variance jerk value exceeds a seventh threshold value.

10. The method of claim 8, including the step of weighting said low-variance jerk value using a relatively high-rank value of said stored acceleration information.

11. The method of claim 2, wherein said step of generating said high-frequency past history value using said low-variance jerk value includes the steps of:

accumulating said low-variance jerk value over time to obtain a second accumulated value for low-variance jerk; and

periodically subtracting a damp factor from said second accumulated value for low-variance jerk to obtain said high-frequency past history value.

12. The method of claim 11, wherein said low-variance jerk value is added to said second accumulated value for low-variance jerk only when the absolute value of said low-variance jerk value exceeds a eighth threshold value.

13. The method of claim 11, including the step of weighting said low-variance jerk value using a relatively low-rank value of said stored acceleration information.

14. The method of claim 2, wherein said step of generating said high-variance past history value using said high-variance jerk value includes the steps of:

accumulating said high-variance jerk value over time to obtain an accumulated value for said high-variance jerk; and

periodically subtracting a damp factor from said accumulated value for said high-variance jerk to obtain said high-frequency past history value.

15. The method of claim 14, wherein said high-variance jerk value is added to said accumulated value for said high-variance jerk only when the absolute value of said high-variance jerk value exceeds a ninth threshold value.

16. The method of claim 2, further including the step of actuating said vehicle safety device if, while said first velocity value exceeds a tenth threshold value and said second velocity value exceeds an eleventh threshold value, said predicted acceleration value exceeds a twelfth threshold value.

17. A system for controlling actuation of a vehicle safety device in an event of a vehicle crash or sudden vehicle deceleration comprising:

means for receiving information representative of instantaneous vehicle acceleration;

means for storing said received acceleration information;

means for generating a low-variance jerk value from said stored acceleration information;

means for generating a high-variance jerk value from said stored acceleration information;

means for generating a first velocity value and a second velocity value using said stored acceleration information;

means for generating a predicted acceleration value using said low-variance jerk value;

means for generating a high-frequency past history value using said low-variance jerk value;

means for generating a high-variance past history value using said high-variance jerk value; and

means for actuating said vehicle safety device if, while said first velocity value exceeds a first threshold value, said predicted acceleration value has exceeded a second threshold value and said high-variance velocity value has exceeded a second threshold value; and

, while said second velocity value exceeds a fourth threshold value, said predicted acceleration value has exceeded a fifth threshold value and said high-frequency past history measure has exceeded a sixth threshold value.

18. The system of claim 17, wherein said means for generating said low-variance jerk value from said stored acceleration information includes:

means for separating said stored acceleration information into a first data set and a second data set, said first data set containing older received acceleration information than said second data set;

means for rank-order filtering said stored acceleration information in said first data set and said second data set, respectively;

means for inverting a value of said stored acceleration information having a given rank in said first data set; and

means for combining a value of said stored acceleration information having a rank in said second data set equal to said given rank with said inverted value of said acceleration information having said given rank in said first data set.

19. The system of claim 17, wherein said means for generating a high-variance jerk value from said stored acceleration information includes:

means for rank-order filtering said stored acceleration information;

means for inverting a low-rank value of said stored acceleration information; and

means for combining a high-rank value of said stored acceleration information with said inverted low-rank value of said stored acceleration information.

20. The system of claim 17, wherein said means for generating said first and second velocity measures using said received acceleration information includes:

means for rank-order filtering said stored acceleration information; and

means for integrating a low-rank value of said stored acceleration information to obtain said first velocity measure; and

means for integrating stored acceleration information having a high rank and stored acceleration having a high rank.

21. The system of claim 20, including means for modifying said rank-order filtered acceleration information prior to integrating in said integrating means.

22. The system of claim 21, wherein said means for modifying said rank-order filtered acceleration information includes:

means for generating a modification factor using at least one of the group consisting of a predetermined constant, said received acceleration information, said first velocity value, said second velocity value, said low-variance jerk value and said high-variance jerk value; and

means for subtracting said modification factor from said rank-order filtered acceleration information.

23. The system of claim 17, wherein said means for generating said predicted acceleration value using said low-variance jerk value includes the steps of:

means for accumulating said low-variance jerk value over time to obtain a first accumulated value for low-variance jerk; and

means for periodically subtracting a damp factor from said first accumulated value for low-variance jerk to obtain said predicted acceleration value.

24. The system of claim 23, wherein said low-variance jerk value is added to said first accumulated value for low-variance jerk only when the absolute value of said low-variance jerk value exceeds a seventh threshold value.

25. The system of claim 23, including means for weighting said low-variance jerk value using a relatively high-rank value of said stored acceleration information.

26. The system of claim 17, wherein said means for generating said high-frequency past history value using said low-variance jerk value includes:

means for accumulating said low-variance jerk value over time to obtain a second accumulated value for low-variance jerk; and

means for periodically subtracting a damp factor from said second accumulated value for low-variance jerk to obtain said high-frequency past history value.

27. The system of claim 26, wherein said low-variance jerk value is added to said second accumulated value for low-variance jerk only when the absolute value of said low-variance jerk value exceeds a eighth threshold value.

28. The system of claim 26, including means for weighting said low-variance jerk value using a relatively low-rank value of said stored acceleration information.

29. The system of claim 17, wherein said means for generating said high-variance past history value using said high-variance jerk value includes:

means for accumulating said high-variance jerk value over time to obtain an accumulated value for said high-variance jerk; and

means for periodically subtracting a damp factor from said accumulated value for said high-variance jerk to obtain said high-frequency past history value.

30. The system of claim 29, wherein said high-variance jerk value is added to said accumulated value for said high-variance jerk only when the absolute value of said high-variance jerk value exceeds a ninth threshold value.

31. The system of claim 17, further including means for actuating said vehicle safety device if, while said first velocity value exceeds a tenth threshold value and said second velocity value exceeds an eleventh threshold value, said predicted acceleration value exceeds a twelfth threshold value.