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Technical Paper

Development of Brain Injury Criteria (BrIC)

Rotational motion of the head as a mechanism for brain injury was proposed back in the 1940s. Since then a multitude of research studies by various institutions were conducted to confirm/reject this hypothesis. Most of the studies were conducted on animals and concluded that rotational kinematics experienced by the animal's head may cause axonal deformations large enough to induce their functional deficit. Other studies utilized physical and mathematical models of human and animal heads to derive brain injury criteria based on deformation/pressure histories computed from their models.
Technical Paper

On the Development of the SIMon Finite Element Head Model

The SIMon (Simulated Injury Monitor) software package is being developed to advance the interpretation of injury mechanisms based on kinematic and kinetic data measured in the advanced anthropomorphic test dummy (AATD) and applying the measured dummy response to the human mathematical models imbedded in SIMon. The human finite element head model (FEHM) within the SIMon environment is presented in this paper. Three-dimensional head kinematic data in the form of either a nine accelerometer array or three linear CG head accelerations combined with three angular velocities serves as an input to the model. Three injury metrics are calculated: Cumulative strain damage measure (CSDM) – a correlate for diffuse axonal injury (DAI); Dilatational damage measure (DDM) – to estimate the potential for contusions; and Relative motion damage measure (RMDM) – a correlate for acute subdural hematoma (ASDH).
Technical Paper

Strategies for Passenger Car Designs to Improve Occupant Protection in Real World Side Crashes

The National Highway Traffic Safety Administration (NHTSA) upgraded the side impact protection requirement in Federal Motor Vehicle Safety Standard (FMVSS) No. 214 and added dynamic requirements to reduce the likelihood of thoracic injuries in side crashes. As part of the agency's research in developing the requirements of the standard, NHTSA developed a mathematical model for simulation of side impacts. This paper investigates the overall safety performance, based on Thoracic Trauma Index (TTI) as the criteria for passenger cars in real world side crashes, with the aid of the simulation model. A Thoracic Trauma Index Factor (TTIF) is utilized to compare relative safety performance of passenger cars under various conditions of impact. The concept of relating energy dissipation in various side structure and padding countermeasures is used to develop a family of curves that are representative of a design platform.
Technical Paper

Variability of Hybrid III Clearance Dimensions within the FMVSS 208 and NCAP Vehicle Test Fleets and the Effects of Clearance Dimensions on Dummy Impact Responses

Locations of key body segments of Hybrid III dummies used in FMVSS 208 compliance tests and NCAP tests were measured and subjected to statistical analysis. Mean clearance dimensions and their standard deviations for selected body segments of driver and passenger occupants with respect to selected vehicle surfaces were determined for several classes of vehicles. These occupant locations were then investigated for correlation with impact responses measured in crash tests and by using a three dimensional human-dummy mathematical model in comparable settings. Based on these data, the importance of some of the clearance dimensions between the dummy and the vehicle surfaces was determined. The study also compares observed Hybrid III dummy positions within selected vehicles with real world occupant positions reported in published literature.
Journal Article

Analysis and Mathematical Modeling of Car-Following Behavior of Automated Vehicles for Safety Evaluation

With the emergence of Driving Automation Systems (SAE levels 1-5), the necessity arises for methods of evaluating these systems. However, these systems are much more challenging to evaluate than traditional safety features (SAE level 0). This is because an understanding of the Driving Automation system’s response in all possible scenarios is desired, but prohibitive to comprehensively test. Hence, this paper attempts to evaluate one such system, by modeling its behavior. The model generated parameters not only allow for objective comparison between vehicles, but also provide a more complete understanding of the system. The model can also be used to extrapolate results by simulating other scenarios without the need for conducting more tests. In this paper, low speed automated driving (also known as Traffic Jam Assist (TJA)) is studied. This study focused on the longitudinal behavior of automated vehicles while following a lead vehicle (LV) in traffic jam scenarios.