Kaye Sullivan

Where Are All the Children Seated and When Are They Restrained

The restraint usage and seating location of children in crash-involved passenger cars were estimated using National Accident Sampling System (NASS) data. Whether drivers of cars were restrained or not appears to play a dominant role in whether child passengers were likewise restrained or not. Most infant passengers were restrained irrespective of driver restraint usage. In contrast, the restraint usage of older children was dramatically influenced by the drivers restraint usage. if the driver was restrained, restraint usage by children dropped only slightly. If, however, the driver was unrestrained, restraint usage by children dropped by an order of magnitude. This precipitous drop in restraint usage appears to have occurred by the age of five or six. Thereafter, the restraint usage of children riding with unrestrained drivers remained low and relatively constant. Unrestrained drivers, who had a considerably greater fraction of unrestrained child passengers, were likely to compound an already unsafe situation by placing their unrestrained child passengers in the front seat more frequently.(A) For the covering abstract of the conference see IRRD 899572.

Predictions of AIS3+ Thoracic Risks for Belted Occupants in Full-Engagement, Real-World Frontal Impacts: Sensitivity to Various Theoretical Risk Curves

A new, AlS3+ thoracic risk equation based on chest deflection was derived and assessed for drivers subjected to concentrated (belt-like) loading. The new risk equation was derived from analysis of an existing database of post mortem human subjects in controlled, laboratory sled tests. Binary logistic regression analysis was performed on a subset of the data, namely, 25th-75th percentile men (by weight) from 36-65 years old whose thoracic deformation patterns were due to concentrated (belt-like) loading. Other subsets of data had insufficient size to conduct the analysis. The resulting thoracic risk equation was adjusted to predict the AlS3+ thoracic risks for average-aged occupants in frontal crashes (i.e., 30 years old). Biomechanical scaling was used to derive the corresponding relationships for the small female and large male dummies. The new thoracic risk equations and three other sets of existing equations were evaluated as predictors of real-world crash outcomes. Specifically, thoracic risks associated with belt-only drivers in 1985-1997 model year passenger cars were derived via the four different sets of equations. Comparisons were made from two standpoints: (1) point estimates for 48 km/h potentially barrier-like frontal crashes and (2) aggregate risk estimates derived from simulations of full-engagement, non-rollover, tow-away frontal crashes through 56 km/h. In both cases, the new risk equation agreed with field results. Moreover, an existing thoracic risk equation with a commonly held assumption was shown to significantly overstate observed thoracic field risks.

Considerations of "Combined Probability of Injury" in the next-generation USA frontal NCAP.

Objective: The numerical basis for assigning star ratings in the next-generation USA New Car Assessment Program (NCAP) for frontal impacts was assessed. That basis, the Combined Probability of Injury, or CPI, is the probability of an occupant sustaining an injury to any of the specified body regions. For an NCAP test, a CPI value is computed by (a) using risk curves to convert body-region responses from a test dummy into body-region risks and (b) using a theoretical, overarching CPI equation to convert those separate body-region risks into a single CPI value. Though the general concept of applying a CPI equation to assign star ratings has existed since 1994, there will be numerous changes to the 2011 frontal NCAP: there will be two additional body regions (n = 4 vs. 2), the injury probabilities will be evaluated for lower-severity (more likely) injury levels, and some of the occupant responses will change. These changes could yield more disperse CPIs that could yield more disperse ratings. However, the reasons for this increased dispersion should be consistent with real-world findings. Related assessments were the topic of this two-part study, focused on drivers. Methods: In Part 1, the CPI equation was assessed without applying risk curves. Specifically, field injury probabilities for the four body regions were used as inputs to the CPI equation, and the resulting equation-produced CPIs were compared with the field CPIs. In Part 2, subject to analyses of test dummy responses from recent NCAP tests, the effect of risk curve choice on CPIs was assessed. Specifically, dispersion statistics were compared for CPIs based on various underlying risk curves applied to data from 2001–2005 model year vehicles (n = 183). Results and Conclusions: From Part 1, the theoretical CPI equation for four body regions demonstrated acceptable fidelity when provided field injury rates (R2= 0.92), with the equation-based CPIs being approximately 12 percent lower than those of ideal correlation. From Part 2, the 2011 NCAP protocol (i.e., application of a four-body-region CPI equation whose inputs were from risk curves) generally increased both the CPIs and their dispersion relative to the current NCAP protocol. However, the CPIs generally increased due to an emphasis on neck injury—an emphasis not observed in real-world crashes. Subject to alternative risk curves for the neck and chest, again there was increased dispersion of the CPIs, but the unrealistic emphasis on the neck was eliminated. However, risk estimates for the knee/thigh/hip (KTH) for NCAP-type events remained understated and did not fall within the confidence bands of the field data. Accordingly, KTH risk estimation is an area for future research.