Hardware independent mapping of multiple sensor configurations for classification of persons

• US 6,876,912 B2
• Filed: 10/07/2003
• Issued: 04/05/2005
• Est. Priority Date: 07/12/2000
• Status: Expired due to Fees

• Current Assignee: Continental Automotive GmbH (Continental AG)
• Original Assignee: Siemens AG
• Inventors: Winkler, Gerd
• Primary Examiner(s): Cuchlinski, Jr., William A.
• Assistant Examiner(s): Hernandez, Olga
• Application Number:
  US10/680,749
• Publication Number:
  US 20040073347A1
• Time in Patent Office: 546 Days
• Field of Search: 701/45, 701/36, 280/734, 280/735
• US Class Current: 701/45
• CPC Class Codes: B60R 21/01516 using force or pressure sensing means
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands

Abstract

Sensors are mounted within a seat structure for measuring seat occupant weight. The sensors can be mounted in any one of various sensor configurations. So that common hardware can be used for each different sensor configuration, a virtual matrix is created and output from the sensors is mapped into the virtual matrix. The virtual matrix includes virtual cell locations that do not have a corresponding sensor output; i.e., there are fewer physical cells (sensors) than virtual cell locations in the virtual matrix. A weight output signal from each sensor is mapped into the corresponding position in the virtual matrix and the remaining virtual cell locations have values assigned to them based on data supplied by the surrounding physical cells. Seat occupant weight is determined based on output from the virtual matrix and the occupant is placed into one of the various occupant classifications. Deployment force of a restraint system is controlled based on the classification of the seat occupant.

Claims

1. A system for determining seat occupant weight comprising:

a plurality of sensors mounted within a seat structure for generating a plurality of occupant weight signals in response to a weight force applied to said seat structure, said sensors being mounted in a predetermined sensor configuration comprising a plurality of discrete sensor locations, and wherein each discrete sensor location generates one or said plurality of occupant weight signals; and

a control unit electrically connected to said sensors for receiving said occupant weight signal, mapping said occupant weight signals from said sensors into a virtual matrix defining a theoretical sensor configuration that comprises a plurality of virtual sensor positions,and generating an output signal representing seat occupant weight based on output from the virtual matrix.

2. The system according to claim 1 wherein said sensors are mounted within said seat structure in one of a plurality of predetermined seat sensor configurations and wherein said control unit includes hardware that is common to each of said predetermined seat sensor configurations.

3. The system according to claim 1 wherein said control unit includes electrically erasable programmable read only memory.

4. The system according to claim 1 wherein said control unit includes a printed circuit board having a plurality of connectors for attachment to said sensors and a central processing unit for generating said virtual matrix and mapping said occupant weight signals from said sensors into said virtual matrix.

5. The system according to claim 1 including a restraint control wherein said output signal is classified into one of a plurality of predetermined occupant weight classes and transmitted to said restraint control.

6. A method for classifying vehicle occupants by measuring seat occupant weight comprising the steps of:

(a) supporting a plurality of sensors with a seat structure and mounting the sensors in a predetermined sensor configuration wherein the predetermined sensor configuration comprises a plurality of discrete sensor locations;

(b) generating a weight signal from each discrete sensor location in response to a weight force applied to the seat structure;

(c) mapping the weight signals from the sensors into a virtual matrix defining a theoretical sensor configuration wherein the theoretical sensor configuration comprise a plurality of virtual sensor positions; and

(d) determining weight on the sea structure based on output from the virtual matrix.

7. The method according to claim 6 wherein the predetermined sensor configuration is identical to the theoretical sensor configuration.

8. The method according to claim 6 wherein the predetermined sensor configuration is different than the theoretical sensor configuration.

9. The method according to claim 6 wherein step (c) includes mapping each one of the weight signals into one of the virtual sensor positions.

10. The method according to claim 9 wherein step (c) includes mapping each one of the weight signals into a virtual sensor position that corresponds generally to a location of the discrete sensor location from which the weight signal is generated.

11. The method according to claim 10 wherein the virtual matrix includes a greater number of virtual sensor positions than discrete sensor locations and step (c) includes determining which virtual sensor positions do not have corresponding mapped weight signals and assigning a value for each of the remaining virtual sensor positions based on weight signal data from discrete sensor locations surrounding each of the remaining virtual sensor positions.

12. The method according to claim 6 including (e) classifying each seat occupant into one of a plurality of predetermined occupant weight classes based on at least the output from the virtual matrix.

13. The method according to claim 12 including (f) providing seat occupant weight classification to a restraint control.

14. The method according to claim 6 wherein step (a) further includes mounting the sensors in a non-symmetrical pattern.

15. The method according to claim 6 wherein step (a) further includes mounting the sensors in a symmetrical pattern.

16. The method according to claim 6 including providing hardware for receiving the weight signals, storing the virtual matrix, and mapping the weight signals into the virtual matrix.

17. The method according to claim 16 wherein step (a) includes mounting the sensors into one of a plurally of predetermined sensor configurations and further including using common hardware for all predetermined sensor configurations.