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The causes of injuries suffered by drivers in “small-overlap frontal crashes” (SOFC) were examined. These crashes were defined as ones in which vehicles are loaded outside their longitudinal side members. SOFC accident data sets stored in the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) database were investigated. Percentages of cases sustaining injury to each body region of drivers were calculated, and the differences between the percentages of injury by body region were examined. To investigate the injury mechanisms, SOFC tests with two types of rigid barrier were then conducted. Injury values in each body region were analyzed to validate the reproducibility of SOFC test as a relevant test.

The goal of this study was to develop injury probability functions for the leg bending moment and MCL (Medial Collateral Ligament) elongation of the Flexible Pedestrian Legform Impactor (Flex-PLI) based on human response data available from the literature. Data for the leg bending moment at fracture in dynamic 3-point bending were geometrically scaled to an average male using the standard lengths obtained from the anthropometric study, based on which the dimensions of the Flex-PLI were determined. Both male and female data were included since there was no statistically significant difference in bone material property. Since the data included both right censored and uncensored data, the Weibull Survival Model was used to develop a human leg fracture probability function.

The pole side impact test has been mandatory in Euro NCAP since 2009 and it includes, in addition to the head, assessments on other critical body regions that might be affected such as the chest, abdomen and pelvis. This paper describes a new test method for predicting Anthropomorphic Test Device responses to calculate injury index in side impact tests of a rigid pole under Euro NCAP conditions. Simplified sled tests are very effective in reducing the cost and time of development of more advanced side impact safety devices. To accomplish sled tests successfully, it is necessary to reconstruct accurately the combined dynamic deformation behavior of door and seat in pole impact. That behavior varies among different dummy response regions. Conventional sled test methods, published in previous literature, can reconstruct the deformation of the entire door using a single actuator at constant intrusion velocity but actual door velocity isn't constant in full scale vehicle crash tests.

An analysis of drivers' facial expressions and subsidiary behavior events (e.g., yawning, self-touching hand motions, etc.) revealed a significant correlation between the struggle against sleepiness and the frequency of occurrence of such events. We counted drivers' subsidiary behavior events by video analysis and defined nine categories of events related to the mouth, hands, head, shoulders, body and eyes. Mouth-related events were further categorized as yawning, stifling a yawn, exhaling and deep breathing. Yawning and self-touching hand motions in particular were observed in relatively large numbers among subsidiary behavior events. Based on this observation, we created an algorithm for detecting yawning and self-touching hand motions using a monocular camera and calculated the frequency of these subsidiary behavior events. In experiments, we compared the frequency of the subsidiary behavior events at the outset of driving and after the passage of time.

Evaluation of pedestrian leg protection performance using the Flex-PLI-GTR (Flexible Pedestrian Legform Impactor Global Technical Regulation) impactor is initiated in JNCAP in 2011. Therefore, a finite element (FE) model of Flex-PLI-GTR is needed for use in digital car development in order to satisfy pedestrian leg protection performance requirements. This paper describes the FE model of Flex-PLI-GTR that has been developed to meet this need. There are three important features of this FE model for obtaining sufficient simulation accuracy. First, the shapes of all Flex-PLI-GTR structures were modeled in detail. Shape information of the inner structures was obtained by computerized tomography scanning and shape information of the inner structures of the outer skin was obtained by laser measurement. Furthermore, the shape of the wrapped skin was incorporated into the FE model based on a wrapping simulation.