Browse Publications Technical Papers 2004-22-0020

A Theoretical Math Model for Projecting Ais3+ Thoracic Injury for Belted Occupants in Frontal Impacts 2004-22-0020

A theoretical math model was created to assess the net effect of aging populations versus evolving system designs from the standpoint of thoracic injury potential. The model was used to project the next twenty-five years of thoracic injuries in Canada. The choice of Canada was topical because rulemaking for CMVSS 208 has been proposed recently. The study was limited to properly-belted, front-outboard, adult occupants in 11-1 o'clock frontal crashes. Moreover, only AIS3+thoracic injury potential was considered. The research consisted of four steps. First, sub-models were developed and integrated. The sub-models were made for numerous real-world effects including population growth, crash involvement, fleet penetration of various systems (via system introduction, vehicle production, and vehicle attrition), and attendant injury risk estimation. Second, existing NASS data were used to estimate the number of AIS3+ chest-injured drivers in Canada in 2001. This served as data for model validation. Third, the projection model was correlated favorably with the 2001 field estimate. Finally, for the scenario that 2004-2030 model-year systems would perform like 2000-2003 model-year systems, a projection was made to estimate the long-term effect of eliminating designs that would not comply with the proposed CMVSS 208. The 2006-2030-projection result for this scenario: 764 occupants would benefit from the proposed regulation. This projection was considered to be conservative because future innovation was not considered, and, to date, the fleet's average chest deflections have been decreasing. The model also predicted that, through 2016, the effect of improving system performance would be more influential than the population aging effect; thereafter, the population-aging effect would somewhat counteract the effect of improving system performance. This theoretical math model can provide insights for both designers and rule makers.


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