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Various frontal impact risk curves were assessed for the next-generation USA New Car Assessment Program (NCAP). Specifically, the “NCAP risk curves” — those chosen by the government for the 2011 model year NCAP — as well as other published risk curves were used to estimate theoretically the injury rates of belted drivers in real-world frontal crashes. Two perspectives were considered: (1) a “point” estimate of NCAP-type events from NCAP fleet tests, and (2) an “aggregate” estimate of 0 ≤ ΔV ≤ 56 km/h crashes from a modeled theoretical vehicle whose NCAP performance approximated the average of the studied fleet. Four body regions were considered: head, neck, chest, and knee-thigh-hip complex (KTH). The curve-based injury rates for each body region were compared with those of real-world frontal crashes involving properly-belted adult drivers in airbag-equipped light passenger vehicles. The assessment yielded mixed results.

A set of risk equations was derived to estimate the probability of sustaining a moderate-to-serious injury to the knee-thigh-hip complex (KTH) in a frontal crash. The study consisted of four parts. First, data pertaining to knee-loaded, whole-body, post-mortem human subjects (PMHS) were collected from the literature, and the attendant response data (e.g., axial compressive load applied to the knee) were normalized to those of a mid-sized male. Second, numerous statistical analyses and mathematical constructs were used to derive the set of risk equations for adults of various ages and genders. Third, field data from the National Automotive Sampling System (NASS) were analyzed for subsequent comparison purposes.

Lower-body injury data for adults in real-world frontal impacts in the National Automotive Sampling System (NASS) were collected, analyzed, and modeled via statistical methods. Two levels of lower-body injury were considered: maximum serious-to-fatal (MAIS3+) and moderate-to-fatal (MAIS2+). In the analysis, we observed that a substantial fraction of all lower-body injured occupants had no recorded floor/toe pan intrusion: 47% of all MAIS3+ injured occupants; 69% of all MAIS2+ injured occupants. In the statistical modeling, we developed binary logistic regression models to fit the MAIS3+ and MAIS 2+ injury data. The statistically significant variables (p ≤ 0.05) were the speed change of the crash, postcrash floor/toe pan intrusion, level of restraint, occupant age, and occupant gender.

An age-dependent, serious-to-fatal (AIS3+), thoracic risk curve was derived and evaluated for frontal impacts. The study consisted of four parts. In Part 1, two datasets of post mortem human subjects (PMHS) were generated for statistical and sensitivity analyses. In Part 2, logistic regression analyses were conducted. For each dataset, two statistical methods were applied: (1) a conventional maximum likelihood method, and (2) a modified maximum likelihood method. Therefore, four statistical models were derived — one for each dataset/statistical method combination. For all of the resulting statistical models (risk curves), the linear combination of maximum normalized sternum deflection and age of the PMHS was identified as a feasible predictor of AIS3+ thoracic injury probability. In Part 3, the PMHS-based risk curves were transformed into test-dummy-based risk curves. In Part 4, validation studies were conducted for each risk curve.