Hardware independent mapping of multiple sensor configurations for classification of persons

• US 20050090959A1
• Filed: 11/12/2004
• Published: 04/28/2005
• Est. Priority Date: 07/12/2000
• Status: Active Grant

• Current Assignee: Continental Automotive Systems US Incorporated (Continental AG)
• Original Assignee: Continental Automotive GmbH (Continental AG)
• Inventors: Winkler, Gard
• Granted Patent: US 7,460,938 B2
• Time in Patent Office: Days
• 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

1-24. -24. (canceled)

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

(a) mounting a plurality of sensors within a seat structure;

(b) generating a plurality of occupant weight signals from the sensors in response to a weight force applied to the seat structure;

(c) mapping the occupant weight signals from the sensors into a virtual matrix; and

(d) determining seat occupant weight based on output from the virtual matrix.

26. The method according to claim 25 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.

27. The method according to claim 26 including (f) providing seat occupant weight classification to a restraint control.

28. The method according to claim 25 wherein step (a) further includes mounting the sensors in a non-symmetrical pattern.

29. The method according to claim 25 wherein step (a) further includes mounting the sensors in a symmetrical pattern.

30. The method according to claim 25 wherein step (c) further includes generating the virtual matrix to define a theoretical optimal pattern having a theoretical optimal number of seat sensor positions.

31. The method according to claim 30 including providing hardware for receiving the occupant weight signals, storing the virtual matrix, and mapping the occupant weight signals into the virtual matrix.

32. The method according to claim 31 wherein step (a) includes mounting the sensors into one of multiple different seat sensor configurations and further including using common hardware for each different seat sensor configuration.

33. The method according to claim 31 wherein step (a) includes mounting the sensors into one of multiple different seat sensor configurations and further including using identical hardware for each different seat sensor configuration.

34. The method according to claim 25 wherein said virtual matrix comprises a theoretical sensor configuration stored within a control unit.

35. The method according to claim 25 wherein said virtual matrix comprises a theoretical sensor configuration having a plurality of virtual sensor positions and wherein step (c) includes mapping the weight signals into the virtual sensor positions.

36. The method according to claim 35 wherein step (a) includes mounting the sensors in a predetermined sensor configuration having a plurality of discrete sensor locations and wherein step (b) includes generating a weight signal from each discrete sensor location.

37. The method according to claim 36 wherein step (c) includes mapping each weight signal into one of the virtual sensor positions.

38. The method according to claim 37 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.

39. 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; and

a control unit electrically connected to said sensors for receiving said occupant weight signals and mapping said occupant weight signals from said sensors into a virtual matrix to generate an output signal representing seat occupant weight.

40. The system according to claim 39 wherein said sensors are mounted within said seat structure in one of a plurality of seat sensor configurations and wherein said control unit includes hardware that is common to each of said seat sensor configurations.

41. The system according to claim 39 wherein said control unit includes electrically erasable programmable read only memory.

42. The system according to claim 39 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.

43. The system according to claim 39 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.

44. The system according to claim 39 wherein said virtual matrix comprises a theoretical sensor configuration stored within said control unit and includes an optimal number of theoretical sensor positions.

45. The system according to claim 39 wherein said virtual matrix comprises a theoretical sensor configuration having a plurality of virtual sensor positions, and wherein said control unit maps the weight signals into the virtual sensor positions.

46. The system according to claim 45 wherein said sensors are mounted in a predetermined sensor configuration having a plurality of discrete sensor locations with each discrete sensor location generating a corresponding weight signal and wherein said control unit maps each weight signal into one of said virtual sensor positions.

47. The system according to claim 46 wherein said virtual matrix includes a greater number of virtual sensor positions than discrete sensor locations and wherein said control unit identifies which virtual sensor positions do not have corresponding mapped weight signals and assigns a value for each remaining virtual sensor position based on weight signal data from discrete sensor locations surrounding each of the remaining virtual sensor positions.

48. 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;

(b) generating a weight signal from each sensor 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; and

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

49. The method according to claim 48 wherein step (a) includes mounting the sensors in a predetermined sensor configuration.

50. The method according to claim 49 wherein the predetermined sensor configuration is identical to the theoretical sensor configuration.

51. The method according to claim 49 wherein the predetermined sensor configuration is different than the theoretical sensor configuration.

52. The method according to claim 49 wherein the predetermined sensor configuration comprises a plurality of discrete sensor locations and step (b) includes generating a weight signal from each discrete sensor location.

53. The method according to claim 48 wherein said virtual matrix is remote from said sensors.