Decision Algorithm for Smart Airbag Deployment Safety Issues
Airbag deployment has been known to be responsible
for huge death, incidental injuries and broken bones due to low crash
severity and wrong deployment decisions. Therefore, the authorities
and industries have been looking for more innovative and intelligent
products to be realized for future enhancements in the vehicle safety
systems (VSSs). Although the VSSs technologies have advanced
considerably, they still face challenges such as how to avoid
unnecessary and untimely airbag deployments that can be hazardous
and fatal. Currently, most of the existing airbag systems deploy
without regard to occupant size and position. As such, this paper will
focus on the occupant and crash sensing performances due to frontal
collisions for the new breed of so called smart airbag systems. It
intends to provide a thorough discussion relating to the occupancy
detection, occupant size classification, occupant off-position
detection to determine safe distance zone for airbag deployment,
crash-severity analysis and airbag decision algorithms via a computer
modeling. The proposed system model consists of three main
modules namely, occupant sensing, crash severity analysis and
decision fusion. The occupant sensing system module utilizes the
weight sensor to determine occupancy, classify the occupant size,
and determine occupant off-position condition to compute safe
distance for airbag deployment. The crash severity analysis module is
used to generate relevant information pertinent to airbag deployment
decision. Outputs from these two modules are fused to the decision
module for correct and efficient airbag deployment action. Computer
modeling work is carried out using Simulink, Stateflow,
SimMechanics and Virtual Reality toolboxes.
[1] M. Devy, A. Giralt, and A. Marin-Hernandez, "Detection and
Classification of Passenger Seat Occupancy using Stereovision", Proc.
of the IEEE Intelligent Vehicle Symposium, Dearborn (MI), USA, Oct.
3-5, 2000, pp. 714-719.
[2] H. Kong, Q. Sun, ,W. Bauson, S. Kiselewich, P. Ainslie, and R.
Hammoud, "Disparity Based Image Segmentation for Occupant
Classification", Proc. of the IEEE Computer Society Conf. on
Computer Vision and Pattern Recognition Workshops (CVPRW04),
2004, pp.126-133
[3] J. Krumm, and G. Kirk, "Video Occupant Detection for airbag
Deployment", Proc. of the Fourth IEEE Workshop on Applications of
Computer Vision (WACV '98), 19-21 Oct. 1998, pp. 30 - 35.
[4] S. Enouen, D. A. Guenther, & T. F. MacLaughlin, "Comparison of
Models Simulating Occupant Response with Airbags", SAE Trans.
Section 3, 840451, pp. 343-358, 1984.
[5] R. Brantman, and D. Breed, "Use of the Computer Simulation in
Evaluating Airbag System Performance", SAE Trans. Section 4,
851188, pp. 1072-1081, 1985.
[6] K. Watanabe, and Y. Umezawa, "Optimal Triggering of an Airbag"
Proc. of the IEEE Intelligent Vehicles '93 Symposium, 14-16 July,
1993, pp. 78-83.
[7] S. Gautama, S. Lacorix, and, M. Devy , "Evaluation of Stereo Matching
Algorithms for Occupant Detection", Proc. of the International
Workshop on Recognition, Analysis, and Tracking of Faces and
Gestures in Real-Time Systems, 26-27 Sept. 1999, pp. 177-184.
[8] M. E. Farmer, and A.K. Jain, "Integrated Segmentation and
Classification for Automotive Airbag Suppression". Proc. of the IEEE
Int. Conf. on Image Processing, 14-17 Sept. 2003, 3, pp. 1053-1056.
[9] D. Chaikin, "Airbags" Popular Mechanics", pp. 81, 1991.
[10] S. B. David, S. Lori, J. Carlson, and M. Koyzreff, "Development of an
Occupant Position Sensor System to Improve Frontal Crash
Protection", Proc. of the 18 th International Technical Conf. on the
Enhanced Safety of Vehicles (ESV), Paper No. 325, Paris, 2001.
[11] C-Y. Chan, "On the Detection of Vehicular CrashesÔÇöSystem
Characteristics and Architecture", IEEE Transaction on Vehicular
Technology, Vol. 51, No. 1, pp. 80-193, 2002,
[12] C-Y. Chan, "A Treatise on Crash Sensing for Automotive Air Bag
Systems", IEEE/ASME Transaction on Mechatronics, Vol. 7, No. 5,
pp. 220-234, 2002.
[13] G. W. McIver, "Method and apparatus for sensing a vehicle crash
condition using velocity enhanced acceleration crash metrics," U.S.
Patent 5 587 906 (1996).
[14] R. Shaw, and J. Onder, "Emergency Rescue Guidelines for Air Bag
Equipped Vehicles", National Highway Traffic Safety Administration
(NHTSA),http://www.emergencygrapevine.com/vl0102/ergair.htm,
(2002).
[1] M. Devy, A. Giralt, and A. Marin-Hernandez, "Detection and
Classification of Passenger Seat Occupancy using Stereovision", Proc.
of the IEEE Intelligent Vehicle Symposium, Dearborn (MI), USA, Oct.
3-5, 2000, pp. 714-719.
[2] H. Kong, Q. Sun, ,W. Bauson, S. Kiselewich, P. Ainslie, and R.
Hammoud, "Disparity Based Image Segmentation for Occupant
Classification", Proc. of the IEEE Computer Society Conf. on
Computer Vision and Pattern Recognition Workshops (CVPRW04),
2004, pp.126-133
[3] J. Krumm, and G. Kirk, "Video Occupant Detection for airbag
Deployment", Proc. of the Fourth IEEE Workshop on Applications of
Computer Vision (WACV '98), 19-21 Oct. 1998, pp. 30 - 35.
[4] S. Enouen, D. A. Guenther, & T. F. MacLaughlin, "Comparison of
Models Simulating Occupant Response with Airbags", SAE Trans.
Section 3, 840451, pp. 343-358, 1984.
[5] R. Brantman, and D. Breed, "Use of the Computer Simulation in
Evaluating Airbag System Performance", SAE Trans. Section 4,
851188, pp. 1072-1081, 1985.
[6] K. Watanabe, and Y. Umezawa, "Optimal Triggering of an Airbag"
Proc. of the IEEE Intelligent Vehicles '93 Symposium, 14-16 July,
1993, pp. 78-83.
[7] S. Gautama, S. Lacorix, and, M. Devy , "Evaluation of Stereo Matching
Algorithms for Occupant Detection", Proc. of the International
Workshop on Recognition, Analysis, and Tracking of Faces and
Gestures in Real-Time Systems, 26-27 Sept. 1999, pp. 177-184.
[8] M. E. Farmer, and A.K. Jain, "Integrated Segmentation and
Classification for Automotive Airbag Suppression". Proc. of the IEEE
Int. Conf. on Image Processing, 14-17 Sept. 2003, 3, pp. 1053-1056.
[9] D. Chaikin, "Airbags" Popular Mechanics", pp. 81, 1991.
[10] S. B. David, S. Lori, J. Carlson, and M. Koyzreff, "Development of an
Occupant Position Sensor System to Improve Frontal Crash
Protection", Proc. of the 18 th International Technical Conf. on the
Enhanced Safety of Vehicles (ESV), Paper No. 325, Paris, 2001.
[11] C-Y. Chan, "On the Detection of Vehicular CrashesÔÇöSystem
Characteristics and Architecture", IEEE Transaction on Vehicular
Technology, Vol. 51, No. 1, pp. 80-193, 2002,
[12] C-Y. Chan, "A Treatise on Crash Sensing for Automotive Air Bag
Systems", IEEE/ASME Transaction on Mechatronics, Vol. 7, No. 5,
pp. 220-234, 2002.
[13] G. W. McIver, "Method and apparatus for sensing a vehicle crash
condition using velocity enhanced acceleration crash metrics," U.S.
Patent 5 587 906 (1996).
[14] R. Shaw, and J. Onder, "Emergency Rescue Guidelines for Air Bag
Equipped Vehicles", National Highway Traffic Safety Administration
(NHTSA),http://www.emergencygrapevine.com/vl0102/ergair.htm,
(2002).
@article{"International Journal of Information, Control and Computer Sciences:61769", author = "Aini Hussain and M A Hannan and Azah Mohamed and Hilmi Sanusi and Burhanuddin Yeop Majlis", title = "Decision Algorithm for Smart Airbag Deployment Safety Issues", abstract = "Airbag deployment has been known to be responsible
for huge death, incidental injuries and broken bones due to low crash
severity and wrong deployment decisions. Therefore, the authorities
and industries have been looking for more innovative and intelligent
products to be realized for future enhancements in the vehicle safety
systems (VSSs). Although the VSSs technologies have advanced
considerably, they still face challenges such as how to avoid
unnecessary and untimely airbag deployments that can be hazardous
and fatal. Currently, most of the existing airbag systems deploy
without regard to occupant size and position. As such, this paper will
focus on the occupant and crash sensing performances due to frontal
collisions for the new breed of so called smart airbag systems. It
intends to provide a thorough discussion relating to the occupancy
detection, occupant size classification, occupant off-position
detection to determine safe distance zone for airbag deployment,
crash-severity analysis and airbag decision algorithms via a computer
modeling. The proposed system model consists of three main
modules namely, occupant sensing, crash severity analysis and
decision fusion. The occupant sensing system module utilizes the
weight sensor to determine occupancy, classify the occupant size,
and determine occupant off-position condition to compute safe
distance for airbag deployment. The crash severity analysis module is
used to generate relevant information pertinent to airbag deployment
decision. Outputs from these two modules are fused to the decision
module for correct and efficient airbag deployment action. Computer
modeling work is carried out using Simulink, Stateflow,
SimMechanics and Virtual Reality toolboxes.", keywords = "Crash severity analysis, occupant size classification,
smart airbag, vehicle safety system.", volume = "2", number = "3", pages = "897-7", }