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Engine control units (ECUs) on heavy trucks have been capable of storing “last stop” or “hard stop” data for some years. These data provide useful information to accident reconstruction personnel. In past studies, these data have been analyzed and compared to higher-resolution on-vehicle data for several heavy trucks and several makes of passenger cars. Previous published studies have been quite helpful in understanding the limitations and/or anomalies associated with these data. This study was designed and executed to add to the technical understanding of heavy truck event data recorders (EDR), specifically data associated with a modern Cummins power plant ECU. Emergency “full-treadle” stops were performed at many combinations of load-speed-surface coefficient conditions. In addition, brake-in-curve tests were performed on wet Jennite for various conditions of disablement of the braking system.

The widespread implementation of air bags has increased the incidence of upper extremity injuries in the automotive crash environment. The first step in reducing these injuries is to determine applicable upper extremity injury criteria. The purpose of this paper is to develop injury risk functions for the fifth percentile female forearm, humerus, wrist, and elbow. Injury tolerance data for each anatomical region were gathered from experiments with controlled impact loading of disarticulated small female cadaver upper extremities. This technique allowed for the applied load to be directly quantified. All data were mass scaled to the fifth percentile female. In order to develop the risk functions, the logit distribution was integrated for the uncensored data, while logistic regression and generalized estimating equations statistical analysis techniques were used for censored data.