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Ankle injuries continue to occur in motor vehicle collisions, particularly in female occupants. The causes of these injuries are sometimes unclear. Further understanding of ankle fracture tolerance and refinement of ankle injury prediction tools would help future injury prediction efforts. The goal of this study was to identify ankle injury types of interest and develop a test methodology to induce these injuries. Cases were examined from NHTSA’s Crash Injury Research Engineering Network (CIREN) database. 68 cases with distal tibia fracture were identified from CIREN years 2017+ (vehicle models years 2010+). The most common fractures were pilon fractures and malleolar fractures. Based on these results, a test methodology was developed to induce pilon and medial malleolar fractures in isolated cadaveric tibiae to quantify local fracture tolerance. Nineteen post-mortem human subject (PMHS) specimens (9 male and 10 female across a wide anthropometric range) were tested.

The purpose of this study was to characterize front stiffness response of contemporary sport utility vehicles (SUVs) and trucks. Vehicle front impact test data were obtained from data published by the National Highway Traffic Safety Administration [NHTSA]. For all tests, force data were obtained from barrier load cells and stroke data were derived from accelerometers. Data from 53 truck and SUV tests were aggregated by vehicle product segment according to body style to obtain mean ± standard deviation (SD) stiffness corridors: (1) compact unibody SUV/crossover, (2) small unibody SUV/crossover, (3) mid-size unibody SUV/crossover, (4) frame SUV, and (5) frame truck. To compare between vehicle product segments, this study also considered the average stiffness (slope) within the stroke region required to achieve 300 kN total barrier force. Across unibody SUV segments, average stiffness varied from 1.4–1.8 kN/mm.

Analyzing dynamic postures of vehicle occupants in various situations is valuable for improving occupant accommodation and safety. Accurate tracking of an occupant’s head is of particular importance because the head has a large range of motion, controls gaze, and may require special protection in dynamic events including crashes. Previous vehicle occupant posture studies have primarily used marker-based optical motion capture systems or multiple video cameras for tracking facial features or markers on the head. However, the former approach has limitations for collecting on-road data, and the latter is limited by requiring intensive manual postprocessing to obtain suitable accuracy. This paper presents an automated on-road head tracking method using a single Microsoft Kinect V2 sensor, which uses a time-of-flight measurement principle to obtain a 3D point cloud representing objects in the scene at approximately 30 Hz.

Current finite element (FE) human body models (HBMs) generally only represent young and mid-size male occupants and do not account for body shape and composition variations among the population. Because it generally takes several years to build a whole-body HBM, a method to rapidly develop HBMs with a wide range of human attributes (size, age, obesity level, etc.) is critically needed. Therefore, the objective of this study was to evaluate the feasibility of using a mesh morphing method to rapidly generate skeleton and whole-body HBMs based on statistical geometry targets developed previously. THUMS V4.01 mid-size male model jointly developed by Toyota Motor Corporation and Toyota Central R&D Labs was used in this study as the baseline HBM to be morphed. Radial basis function (RBF) was used to morph the baseline model into the target geometries.