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An eight-group taxonomy was created to classify real-world frontal crashes from the Crashworthiness Data System (CDS) component of the National Automotive Sampling System (NASS). Three steps were taken to develop the taxonomy: (1) frontal-impact towaway crashes were identified by examining 1985-2005 model year light passenger vehicles with Collision Deformation Classification (CDC) data from the 1995-2005 calendar years of NASS; (2) case reviews, engineering judgments, and categorization assessments were conducted on these data to produce the eight-group taxonomy; and (3) two subsets of the NASS dataset were analyzed to assess the consistency of the resulting taxonomic-group frequencies. “Full-engagement” and “Offset” crashes were the most frequent crash types, each contributing approximately 33% to the total. The group identified as “D, Y, Z No-Rail” was the most over-represented crash type for vehicles with at least one seriously-injured occupant.

A theoretical, mathematical, risk assessment procedure was developed to estimate the fraction of drivers that incurred head and thoracic AIS3+ injuries in full-engagement frontal crashes. The estimates were based on numerical simulations of various real-world events, including variations of crash severity, crash speed, level of restraint, and occupant size. The procedure consisted of four steps: (1) conduct the simulations of the numerous events, (2) use biomechanical equations to transform the occupant responses into AIS3+ risks for each event, (3) weight the maximum risk for each event by its real-world event frequency, and (4) sum the weighted risks. To validate the risk assessment procedure, numerous steps were taken. First, a passenger car was identified to represent average field performance.

A new, AIS3+ 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 AIS3+ 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.

Do older light trucks, often with second (and subsequent) owners, present a higher risk to either their own occupants or to other road users? And is the safety record for newer trucks better or worse than the record for their older counterparts? To answer these questions, fatalities in crashes involving at least one light truck were examined using the Fatal Analysis Reporting System (FARS). Fatality rates for both occupants of the light truck and for other road users (occupants of other motor vehicles, pedestrians, etc.) in these crashes were computed, based both on the number of registered vehicles and on the vehicle miles of travel. Two trends in these fatality rates are observed. First, as light trucks age, a consistent decline is found in risk both to their own occupants and to other road users. Second, a distinct decrease is found in road user risk for newer light trucks compared to older light trucks when they were new, both for their own occupants and for other road users.