Monte carlo method for estimating whole-body injury metrics from pedestrian impact simulation results.

The goal of the current study was to develop a method to estimate whole-body injury metrics (WBIMs), which measure the overall impact of injuries, using stochastic injury prediction results from a computational human surrogate. First, hospitalized pedestrian data was queried to identify injuries sustained by pedestrians and their frequencies. Second, with consideration for an understanding of injury mechanisms and the capability of the computational human surrogate, the whole-body was divided into 17 body regions. Then, an injury pattern database was constructed for each body region for various maximum abbreviated injury scale (MAIS) levels. Third, a two-step Monte Carlo sampling process was employed to generate N virtual pedestrians with an assigned list of injuries in AIS codes. Then, the expected values of WBIMs such as injury severity score (ISS), probability of death, whole-body functional capacity index (WBFCI), and lost years of life (LYL), were estimated. Lastly, the proposed method was verified using injury information from the inpatient pedestrian database. Also, the proposed method was applied to pedestrian impact simulations with various impact speeds to estimate the probability of death with respect to the impact speed. The probability of death from the proposed method was compared with those from epidemiological studies. The proposed method accurately estimated WBIMs such as ISS and WBFCI using either for a given distribution of injury risk or MAIS levels. The predicted probability of death with respect to the impact speed showed a good correlation with those from the epidemiological study. These results imply that if we have a human surrogate that can predict the risk of injury accurately, we can accurately estimate WBIMs using the proposed method. The proposed method can simplify a vehicle design optimization process by transforming the multi-objective optimization problem into the single-objective one. Lastly, the proposed method can be applied to other human surrogates such as occupant models.

Identification of characteristics and frequent scenarios of single-vehicle rollover crashes during pre-ballistic phase; part 1 - A descriptive study.

This study aimed to identify common patterns of pre-ballistic vehicle kinematics and roadway characteristics of real-world rollover crashes. Rollover crashes that were enrolled in the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) between the years 2000 and 2010 were analyzed. A descriptive analysis was performed to understand the characteristics of the pre-ballistic phase. Also, a frequency based pattern analysis was performed using a selection of NASS-CDS variables describing the pre-ballistic vehicle kinematics and roadway characteristics to rank common pathways of rollover crashes. Most case vehicles departed the road due to a loss of control/traction (LOC) (61%). The road departure with LOC was found to be 13.4 times more likely to occur with slippery road conditions compared to dry conditions. The vehicle was typically laterally skidding with yawing prior to a rollover (66%). Most case vehicles tripped over (82%) mostly at roadside/median (69%). The tripping force was applied to the wheels/tires (82%) from the ground (79%). The combination of these six most frequent attributes resulted in the most common scenario, which accounted for 26% of the entire cases. Large proportion of road departure with LOC (61%) implies electronic stability control (ESC) systems being an effective countermeasure for preventing single-vehicle rollover crashes. Furthermore, the correlation between the road departure with LOC and the reduced friction limit suggests the necessity of the performance evaluation of ESC under compromised road surface condition.

Evaluation of biofidelity of THUMS pedestrian model under a whole-body impact conditions with a generic sedan buck.

OBJECTIVE: The goal of this study was to evaluate the biofidelity of the Total Human Model for Safety (THUMS; Ver. 4.01) pedestrian finite element models (PFEM) in a whole-body pedestrian impact condition using a well-characterized generic pedestrian buck model. METHODS: The biofidelity of THUMS PFEM was evaluated with respect to data from 3 full-scale postmortem human subject (PMHS) pedestrian impact tests, in which a pedestrian buck laterally struck the subjects using a pedestrian buck at 40 km/h. The pedestrian model was scaled to match the anthropometry of the target subjects and then positioned to match the pre-impact postures of the target subjects based on the 3-dimensional motion tracking data obtained during the experiments. An objective rating method was employed to quantitatively evaluate the correlation between the responses of the models and the PMHS. Injuries in the models were predicted both probabilistically and deterministically using empirical injury risk functions and strain measures, respectively, and compared with those of the target PMHS. RESULTS: In general, the model exhibited biofidelic kinematic responses (in the Y-Z plane) regarding trajectories (International Organization for Standardization [ISO] ratings: Y = 0.90 ± 0.11, Z = 0.89 ± 0.09), linear resultant velocities (ISO ratings: 0.83 ± 0.07), accelerations (ISO ratings: Y = 0.58 ± 0.11, Z = 0.52 ± 0.12), and angular velocities (ISO ratings: X = 0.48 ± 0.13) but exhibited stiffer leg responses and delayed head responses compared to those of the PMHS. This indicates potential biofidelity issues with the PFEM for regions below the knee and in the neck. The model also demonstrated comparable reaction forces at the buck front-end regions to those from the PMHS tests. The PFEM generally predicted the injuries that the PMHS sustained but overestimated injuries in the ankle and leg regions. CONCLUSIONS: Based on the data considered, the THUMS PFEM was considered to be biofidelic for this pedestrian impact condition and vehicle. Given the capability of the model to reproduce biomechanical responses, it shows potential as a valuable tool for developing novel pedestrian safety systems.

Whole-body Response for Pedestrian Impact with a Generic Sedan Buck.

To serve as tools for assessing injury risk, the biofidelity of whole-body pedestrian impact dummies should be validated against reference data from full-scale pedestrian impact tests. To facilitate such evaluations, a simplified generic vehicle-buck has been recently developed that is designed to have characteristics representative of a generic small sedan. Three 40 km/h pedestrian-impact tests have been performed, wherein Post Mortem Human Surrogates (PMHS) were struck laterally in a mid-gait stance by the buck. Corridors for select trajectory measures derived from these tests have been published previously. The goal of this study is to act as a companion dataset to that study, describing the head velocities, body region accelerations (head, spine, pelvis, lower extremities), angular velocities, and buck interaction forces, and injuries observed during those tests. Scaled, transformed head accelerations exceeded 80 g prior to head contact with the windshield for two of the three tests. Head xaxis angular velocity exceeded 40 rad/s prior to head contact for all three tests. In all cases the peak resultant head velocity relative to the vehicle was greater than the initial impact speed of the vehicle. Corridors of resultant head velocity relative to the vehicle were also developed, bounded by the velocities observed in these tests combined with those predicted to occur if the PMHS necks were perfectly rigid. These results, along with the other kinematic and kinetic data presented, provide a resource for future pedestrian dummy development and evaluation.