Stapp car crash journal最新文献

This study aimed to clarify the relationship between truck-cyclist collision impact velocity and the serious-injury and fatality risks to cyclists, and to investigate the effects of road type and driving scenario on the frequency of cyclist fatalities due to collisions with vehicles. We used micro and macro truck-cyclist collision data from the Japanese Institute for Traffic Accident Research and Data Analysis (ITARDA) database. We classified vehicle type into five categories: heavy-duty trucks (gross vehicle weight [GVW] ≥11 × 10³ kg [11 tons (t)], medium-duty trucks (5 × 10³ kg [5 t] ≤ GVW < 11 × 10³ kg [11 t]), light-duty trucks (GVW <5 × 10³ kg [5 t]), box vans, and sedans. The fatality risk was ≤5% for light-duty trucks, box vans, and sedans at impact velocities ≤40 km/h and for medium-duty trucks at impact velocities ≤30 km/h. The fatality risk was 6% for heavy-duty trucks at impact velocities ≤10 km/h. Thus, the fatality risk appears strongly associated with vehicle class and impact velocity. The results revealed that a 10 km/h reduction in impact velocities could mitigate the severity of cyclist injuries at impact velocities ≥30 km/h for all five vehicle types. The frequency of cyclist fatalities at intersections with traffic signals involving heavy-duty trucks was significantly higher during daytime than that at nighttime. Fatalities involving vehicles making a left turn generally increased with vehicle weight. The frequency of cyclist fatalities involving vehicles making a left turn was the largest for heavy-duty trucks both during daytime (67.6%) and at nighttime (52.3%).

Tank Automotive Research, Development and Engineering Center (TARDEC) conducted a comprehensive analysis of data collected during the evaluation of head and neck impact during injurious and non-injurious loading. This evaluation included impact velocity, helmet to roof clearance, and neck angle using a fully instrumented Hybrid III head and neck assembly. The results of this effort were compared against post mortem human subject (PMHS) data from similar testing conducted in conjunction with the Warrior Injury Assessment Manikin (WIAMan) program. The results identified the most severe helmet to roof clearance and neck angles. TARDEC used this knowledge as the foundation for continued research into head and neck impact injury mitigation through the use of passive technology and interior vehicle design.

Improving injury prediction accuracy and fidelity for mounted Warfighters has become an area of focus for the U.S. military in response to improvised explosive device (IED) use in both Iraq and Afghanistan. Although the Hybrid III anthropomorphic test device (ATD) has historically been used for crew injury analysis, it is only capable of predicting a few select skeletal injuries. The Computational Anthropomorphic Virtual Experiment Man (CAVEMAN) human body model is being developed to expand the injury analysis capability to both skeletal and soft tissues. The CAVEMAN model is built upon the Zygote 50^th percentile male human CAD model and uses a finite element modeling approach developed for high performance computing (HPC). The lower extremity subset of the CAVEMAN human body model presented herein includes: 28 bones, 26 muscles, 40 ligaments, fascia, cartilage and skin. Sensitivity studies have been conducted with the CAVEMAN lower extremity model to determine the structures critical for load transmission through the leg in the underbody blast (UBB) environment. An evaluation of the CAVEMAN lower extremity biofidelity was also carried out using 14 unique data sets derived by the Warrior Injury Assessment Manikin (WIAMan) program cadaveric lower leg testing. Extension of the CAVEMAN lower extremity model into anatomical tissue failure will provide additional injury prediction capabilities, beyond what is currently achievable using ATDs, to improve occupant survivability analyses within military vehicles.

The objective of this study is to present a quantitative comparison of the biofidelity of the THOR and Hybrid III 50^th percentile male ATDs. Quantitative biofidelity was assessed using NHTSA's Biofidelity Ranking System in a total of 21 test conditions, including impacts to the head, face, neck, upper thorax, lower oblique thorax, upper abdomen, lower abdomen, femur, knee, lower leg, and whole-body sled tests to evaluate upper body kinematics and thoracic response under frontal and frontal oblique restraint loading. Biofidelity Ranking System scores for THOR were better (lower) than Hybrid III in 5 of 7 body regions for internal biofidelity and 6 of 7 body regions for external biofidelity. Nomenclature is presented to categorize the quantitative results, which show overall good internal and external biofidelity of the THOR compared to the good (internal) and marginal (external) biofidelity of the Hybrid III. The results highlight the excellent internal and external biofidelity of the THOR thorax.

A parametric model obtained by fitting a set of data to a function generally uses a procedure such as maximum likelihood or least squares. In general this will generate the best estimate for the distribution of the data overall but will not necessarily generate a reasonable estimation for the tail of the distribution unless the function fitted resembles the underlying distribution function. A distribution function can represent an estimate that is significantly different from the actual tail data, while the bulk of the data is reasonably represented by the central part of the fitted distribution. Extreme value theory can be used to improve the predictive capabilities of the fitted function in the tail region. In this study the peak-over-threshold approach from the extreme value theory was utilized to show that it is possible to obtain a better fit of the tail of a distribution than the procedures that use the entire distribution only. Additional constraints, on the current use of the extreme value approach with respect to the selection of the threshold (an estimate of the beginning of the tail region) that minimize the sensitivity to individual data samples associated with the tail section as well as contamination from the central distribution are used. Once the threshold is determined, the maximum likelihood method was used to fit the exceedances with the Generalized Pareto Distribution to obtain the tail distribution. The approach was then used in the analysis of airbag inflator pressure data from tank tests, crash velocity distribution and mass distribution from the field crash data (NASS). From the examples, the extreme (tail) distributions were better estimated with the Generalized Pareto Distribution, than a single overall distribution, along with the probability of the occurrence for a given extreme value, or a rare observation such as a high speed crash. It was concluded that the peak-over-threshold approach from extreme value theory can be a useful tool in the vehicle crash, biomechanics and injury tolerance data analysis and in estimation of the occurrence probability of an extreme phenomenon given a set of accurate observations.

Under body blast (UBB) loading to military transport vehicles is known to cause foot-ankle fractures to occupants due to energy transfer from the vehicle floor to the feet of the soldier. The soldier posture, the proximity of the event with respect to the soldier, the personal protective equipment (PPE) and age/sex of the soldier are some variables that can influence injury severity and injury patterns. Recently conducted experiments to simulate the loading environment to the human foot/ankle in UBB events (~5ms rise time) with variables such as posture, age and PPE were used for the current study. The objective of this study was to determine statistically if these variables affected the primary injury predictors, and develop injury risk curves. Fifty belowknee post mortem human surrogate (PMHS) legs were used for statistical analysis. Injuries to specimens involved isolated and multiple fractures of varying severity. The Sanders classification was used to grade calcaneus severity and the AO/OTA classification for distal tibia fracture. Injury risk curves were developed using survival regression analysis and covariates were included whenever statistically significant (p<0.05). With peak force as the injury predictor and age and boot as covariates, the model was statistically significant. However, boot use changed the pattern of injury from predominately calcaneus to predominantly tibia. Also, a severity based risk curve showed tolerance differences between calcaneus (minor/major) and tibia (severity-I/ severity- II) injuries. The tibia demonstrated higher tolerance as compared to either minor or major calcaneus injury. These findings can play a vital role in development of safety systems to mitigate injuries to the occupant.

This study addresses the virtual optimization of the technical specifications for a recently developed Advanced Pedestrian Legform Impactor (aPLI). The aPLI incorporates a number of enhancements for improved lower limb injury predictability with respect to its predecessor, the FlexPLI. It also incorporates an attached Simplified Upper Body Part (SUBP) that enables the impactor's applicability to evaluate pedestrian's lower limb injury risk also with high-bumper cars. The response surface methodology was applied to optimize both the aPLI's lower limb and SUBP specifications, while imposing a total mass upper limit of 25 kg that complies with international standards for maximum weight lifting allowed for a single operator in the laboratory setting. All parameters were virtually optimized considering variable interaction, which proved critical to avoid misleading specifications. The results from this study can be used to construct physical aPLIs that are expected to be used in future car-to-pedestrian crash safety testing programs worldwide.

This two-part study analyzed occupant kinematics in simulated collisions of future automated driving vehicles in terms of seating configuration. In part one, a frontal collision was simulated with four occupants with the front seats reversed. The left front seat occupant was unbelted while the others were belted. In part two of the study, occupant restraint was examined in various seating configurations using a single seat model with a three-point seatbelt. The seat direction with respect to impact was considered as forward, rearward, and lateral facing in 45 degree increments. The effect of seat recline was also studied in the forward-facing and rear-facing cases by assuming three positions: driving position, resting position and relaxed position. Occupants were represented by human body finite element models. The results of part one showed that the front seat (rear-facing) occupants were restrained by the seatback, resulting in T1 forward displacement less than 100 mm; the rear seat occupants were restrained by the seatbelt resulting larger T1 forward displacement more than 500 mm. The results of the part two showed the directional dependence of occupant restraint. Greater T1 displacements were observed when the occupant faced lateral or front oblique. However, the seatbelt provided some restraint in all directions considered. The seatback generated contact force to the occupant when it was in the impact direction, including the lateral directions. The relaxed position allowed increased excursion compared to the driving position when the occupant faced rearward, but the magnitude of this increase was lower with lower impact speed.