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The intent of this study was to compare the neck responses measured from the Hybrid III 3 and 6-year-old ATDs in laboratory testing to injuries sustained by three children in a field crash and investigate the appropriateness of recommended in-position neck injury assessment reference values (IARVs), and the regulated out-of-position (OOP) IARVs specified in FMVSS 208 for the Hybrid III 3 and 6-year-old ATDs. This paper principally reports on apparent artifacts associated with the Hybrid III 3 and 6-year-old ATDs, which complicated investigating the appropriateness of the in-position and out-of-position neck IARVs. In tests using 3-point belt restraints, these apparent artifacts included: 1) High neck extension moments, which produced the peak Nij values, without significant observed relative head-to-neck motion, 2) Neck tension forces well in excess of the IARVs that occurred when the ATD's chin contacted the chest.

Injuries to the knee-thigh-hip (KTH) complex in frontal motor vehicle crashes are of substantial concern because of their frequency and potential to result in long-term disability. Current frontal impact Anthropometric Test Dummies (ATDs) have been shown to respond differently than human cadavers under frontal knee impact loading and consequently current ATDs (and FE models thereof) may lack the biofidelity needed to predict the incidence of knee, thigh, and hip injuries in frontal crashes. These concerns demand an efficient and biofidelic tool to evaluate the occurrence of injuries as a result of KTH loading in frontal crashes. The MADYMO human finite element (FE) model was therefore adapted to simulate bone deformation, articulating joints and soft tissue behavior in the KTH complex.

Interaction of the human arm and deploying airbag has been studied in the laboratory using post mortem human subjects (PMHS). These studies have shown how arm position on the steering wheel and proximity to the airbag prior to deployment can influence the risk of forearm bone fractures. Most of these studies used older driver airbag modules that have been supplanted by advanced airbag technology. In addition, new numerical human body models have been developed to complement, and possibly replace, the human testing needed to evaluate new airbag technology. The objective of this study is to use a finite element-based numerical (MADYMO) model, representing the human arm, to evaluate the effects of advanced driver airbag parameters on the injury potential to the bones of the forearm. The paper shows how the model is correlated to Average Distal Forearm Speed (ADFS) and arm kinematics from two PMHS tests.

Injuries of the Occipitoatlantoaxial (Occ-C2) region (also known as atlanto-occipital injuries) are the most common form of cervical injury in children aged ten years and younger. The crash studied in this paper is unique in that there were three children ages 3, 6 and 7 involved in a frontal crash with a delta V of 28mph with each child receiving a nonfatal Occ-C2 injury of varying degrees. The 3 and 6 year-old children were remarkably similar in height and weight to the 3 and 6 year-old Hybrid III ATD's. Also, unique to this case is the fact that the right rear 6 year-old occupant likely sustained an Occ-C2 injury prior to impact with the frame of the front passenger seat. This crash environment was recreated utilizing MADYMO occupant simulation software. The models for the Hybrid III 3 and 6 year-old ATDs were used to represent the occupants in this crash.

The crash modes that occur each day on streets and highways have not changed dramatically over the past 50 years. The need to better understand those crash modes and their relation to rapidly emerging, tailorable restraint systems has intensified recently. The algorithms necessary for predicting a deployment event are based on an approach of coupling the occupant kinematics in a crash to the sensing technology that will activate the restraint system. This paper describes methods of computer modeling, occupant sensing and vehicle crash dynamics to define a crash sensing system that reacts to a complex set of input conditions to invoke an effective restraint response.