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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.

This study evaluated the response of restrained post-mortem human subjects (PMHS) in 40 km/h frontal sled tests. Eight male PMHS were restrained on a rigid planar seat by a custom 3-point shoulder and lap belt. A video motion tracking system measured three-dimensional trajectories of multiple skeletal sites on the torso allowing quantification of ribcage deformation. Anterior and superior displacement of the lower ribcage may have contributed to sternal fractures occurring early in the event, at displacement levels below those typically considered injurious, suggesting that fracture risk is not fully described by traditional definitions of chest deformation. The methodology presented here produced novel kinematic data that will be useful in developing biofidelic human models.

Pedestrian impact protection has been a growing area of research over the past twenty or more years. The results from many studies have shown the importance of providing protection to vulnerable road users as a means of reducing roadway fatalities. Most of this research has focused on the vehicle fleet as a whole in datasets that are dominated by passenger cars (cars). Historically, the influence of vehicle body type on injury distribution patterns for pedestrians has not been a primary research focus. In this study we used the Pedestrian Crash Data Study (PCDS) database of detailed pedestrian crash investigations to identify how injury patterns differ for pedestrians struck by light trucks, vans, and sport utility vehicles (LTVs) from those struck by cars. AIS 2+ and 3+ injuries for each segment of vehicles were mapped back to both the body region of the pedestrian injured and the vehicle source linked to that injury in the PCDS database.