Image based occupant classification systems for determining occupant classification and seat belt status and vehicles having same

• US 8,036,795 B2
• Filed: 10/08/2008
• Issued: 10/11/2011
• Est. Priority Date: 10/08/2008
• Status: Expired due to Fees

• Current Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Original Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Inventors: Allen, Brian T.
• Primary Examiner(s): Ilan; Ruth
• Application Number:
  US12/247,376
• Publication Number:
  US 20100087990A1
• Time in Patent Office: 1,098 Days
• Field of Search: 382/103, 382/104, 340/457.1, 701/45, 280/735, 180/268
• US Class Current: 701/45
• CPC Class Codes: B60R 11/04 Mounting of cameras operative during drive; Arrangement of controls thereof relative to the vehicle
• CPC Class Codes: B60R 21/01538 for image processing, e.g. cameras or sensor arrays

Abstract

An image based occupant classification system includes an image sensor and an image processor. The image sensor is configured to capture vehicular occupant information. The image processor is in communication with the image sensor. The image processor is configured to perform first sampling operations upon the vehicular occupant information to determine occupant classification. The image processor is further configured to perform second sampling operations upon the vehicular occupant information to determine a seat belt status. Each of the first sampling operations is conducted at a separate time from each of the second sampling operations. Vehicles are also provided.

Claims

1. An image based occupant classification system comprising:

an image sensor configured to capture vehicular occupant information; and

an image processor in communication with the image sensor, the image processor being configured to employ an occupant classification algorithm to facilitate performance of first sampling operations to determine occupant classification and being further configured to employ a seat belt detection algorithm to facilitate performance of second sampling operations to determine a seat belt status, the image processor being further configured to place a first hold on the occupant classification algorithm when employing the seat belt detection algorithm and place a second hold on the seat belt detection algorithm when employing the occupant classification algorithm;

wherein;

each of the first sampling operations facilitates one of actuation of the image sensor to capture vehicular occupant information and analysis of the vehicular occupant information already captured by the image sensor during a preceding first sampling operation;

each of the second sampling operations facilitates one of actuation of the image sensor to capture vehicular occupant information and analysis of the vehicular occupant information already captured by the image sensor during a preceding second sampling operation; and

each of the first sampling operations is conducted at a separate time from each of the second sampling operations.

2. The image based occupant classification system of claim 1 wherein each of the first sampling operations and each of the second sampling operations are performed successively by the image processor.

3. The image based occupant classification system of claim 1 wherein the vehicular occupant information includes near-infrared images.

4. The image based occupant classification system of claim 1 wherein the image processor is further configured to determine, from the second sampling operations, whether an occupant is secured by a seat belt.

5. The image based occupant classification system of claim 4 further comprising a seat belt reminder indicia, wherein the image processor is further configured to actuate the seat belt reminder indicia in response to the seat belt status.

6. The image based occupant classification system of claim 1 further comprising:

a supplemental restraint system processor in communication with the image processor, the supplemental restraint system processor being configured to monitor collision conditions; and

an airbag controller in communication with the supplemental restraint system processor, the airbag controller being configured to selectively deploy an airbag in response to the collision conditions;

wherein the supplemental restraint system processor is further configured to selectively inhibit the airbag controller according to the scat belt status.

7. A vehicle comprising:

a passenger compartment;

a seat belt configured to selectively secure a seated occupant within the passenger compartment;

an image sensor configured to capture vehicular occupant information; and

an image processor in communication with the image sensor and configured to employ an occupant classification algorithm to facilitate performance of first sampling operations to determine occupant classification and being further configured to employ a seat belt detection algorithm to facilitate performance of second sampling operations to determine a seat belt status, the image processor being further configured to place a first hold on the occupant classification algorithm when employing the seat belt detection algorithm and place a second hold on the seat belt detection algorithm when employing the occupant classification algorithm;

wherein;

each of the first sampling operations facilitates one of actuation of the image sensor to capture vehicular occupant information and analysis of vehicular occupant information already captured by the image sensor during a preceding first sampling operation;

each of the second sampling operations facilitates one of actuation of the image sensor to capture vehicular occupant information and analysis of vehicular occupant information already captured by the image sensor during a preceding second sampling operation; and

each of the first sampling operations is conducted by the image processor at a separate time from each of the second sampling operations.

8. The vehicle of claim 7 wherein each of the first sampling operations and each of the second sampling operations are performed successively by the image processor.

9. The vehicle of claim 7 wherein at least about ten of the first sampling operations are performed for each of the second sampling operations that is performed by the image processor.

10. The vehicle of claim 7 wherein the vehicular occupant information includes near-infrared images.

11. The vehicle of claim 7 wherein the image processor is further configured to determine, front the second sampling operations, whether an occupant is secured by the seat belt.

12. The vehicle of claim 11 further comprising a seat belt reminder indicia, wherein the image processor is further configured to actuate the seat belt reminder indicia in response to the seat belt status.

13. The vehicle of claim 7 wherein the vehicle comprises a pillar and a ceiling, the passenger compartment is at least partially defined by the pillar and the ceiling, and the image sensor is attached to at least one of the pillar and the ceiling.

14. The vehicle of claim 7 further comprising:

an airbag;

a supplemental restraint system processor in communication with the image processor, the supplemental restraint system processor being configured to monitor collision conditions; and

an airbag controller in communication with the supplemental restraint system processor, the airbag controller being configured to selectively deploy the airbag in response to collision conditions;

wherein the supplemental restraint system processor is further configured to selectively inhibit the airbag controller according to the seat belt status.

15. The vehicle of claim 14 wherein the supplemental restraint system further comprises an accelerometer.

16. An image based occupant classification system comprising:

an image sensor configured to capture vehicular occupant information; and

an image processor in communication with the image sensor, the image processor being configured to employ an occupant classification algorithm to facilitate performance of first sampling operations to determine occupant classification and being further configured to employ a seat belt detection algorithm to facilitate performance of second sampling operations to determine a seat belt status;

wherein;

each of the first sampling operations facilitates one of actuation of the image sensor to capture vehicular occupant information and analysis of vehicular occupant information already captured by the image sensor during a preceding first sampling operation;

each of the second sampling operations facilitates one of actuation of the image sensor to capture vehicular occupant information and analysis of vehicular occupant information already captured by the image sensor during a preceding second sampling operation;

each of the first sampling operations is conducted at a separate time from each of the second sampling operations; and

at least about ten of the first sampling operations are performed for each of the second sampling operations that is performed by the image processor.

17. A method comprising:

capturing vehicular occupant information;

employing an occupant classification algorithm;

performing first sampling operations with the occupant classification algorithm, each of the first sampling operations facilitating one of actuating of the image sensor to capture vehicular occupant information and analyzing vehicular occupant information already captured by the image sensor during a preceding first sampling operation;

determining occupant classification from the first sampling operations;

employing a seat belt detection algorithm;

performing second sampling operations with the seat belt detection algorithm at separate times than the first sampling operations, each of the second sampling operations facilitating one of actuating the image sensor to capture vehicular occupant information and analyzing vehicular occupant information already captured by the image sensor during a preceding second sampling operation;

determining seat belt status from the second sampling operations; and

employing the occupant classification algorithm at least about ten times for each time that the seat belt detection algorithm is employed.

18. A method comprising:

capturing vehicular occupant information;

employing an occupant classification algorithm;

performing first sampling operations with the occupant classification algorithm, each of the first sampling operations facilitating one of actuating of the image sensor to capture vehicular occupant information and analyzing vehicular occupant information already captured by the image sensor during a preceding first sampling operation;

determining occupant classification from the first sampling operations;

employing a seat belt detection algorithm;

performing second sampling operations with the seat belt detection algorithm at separate times than the first sampling operations, each of the second sampling operations facilitating one of actuating the image sensor to capture vehicular occupant information and analyzing vehicular occupant information already captured by the image sensor during a preceding second sampling operation;

determining seat belt status from the second sampling operations; and

placing a first hold on the occupant classification algorithm during employment of the seat belt detection algorithm; and

placing a second hold on the seat belt detection algorithm during employment of the occupant classification algorithm.

19. The method of claim 18 further comprising employing the occupant classification algorithm and the seat belt detection algorithm successively.

20. The method of claim 18 further comprising repeating the occupant classification algorithm at least twice when the second hold is placed on the seat belt detection algorithm.

21. The method of claim 18 further comprising repeating the seat belt detection algorithm at least twice when the first hold is placed on the occupant classification algorithm.