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

A method for generating case-specific vehicle models from a single-view vehicle image for accurate pedestrian injury reconstructions

Developing vehicle finite element (FE) models that match real accident-involved vehicles is challenging. This is related to the intricate variety of geometric features and components. The current study proposes a novel method to efficiently and accurately generate case-specific buck models for car-to-pedestrian simulations. To achieve this, we implemented the vehicle side-view images to detect the horizontal position and roundness of two wheels to rectify distortions and deviations and then extracted the mid-section profiles for comparative calculations against baseline vehicle models to obtain the transformation matrices. Based on the generic buck model which consists of six key components and corresponding matrices, the case-specific buck model was generated semi-automatically based on the transformation metrics. Utilizing this image-based method, a total of 12 vehicle models representing four vehicle categories including family car (FCR), Roadster (RDS), small Sport Utility Vehicle (SUV), and large SUV were generated for car-to-pedestrian collision FE simulations in this study. The pedestrian head trajectories, total contact forces, head injury criterion (HIC), and brain injury criterion (BrIC) were analyzed comparatively. We found that, even within the same vehicle category and initial conditions, the variation in wrap around distance (WAD) spans 84-165 mm, in HIC ranges from 98 to 336, and in BrIC fluctuates between 1.25 and 1.46. These findings highlight the significant influence of vehicle frontal shape and underscore the necessity of using case-specific vehicle models in crash simulations. The proposed method provides a new approach for further vehicle structure optimization aiming at reducing pedestrian head injury and increasing traffic safety.

A data-mining study on the prediction of head injury in traffic accidents among vulnerable road users with varying body sizes and head anatomical characteristics

Body sizes and head anatomical characteristics play the major role in the head injuries sustained by vulnerable road users (VRU) in traffic accidents. In this study, in order to study the influence mechanism of body sizes and head anatomical characteristics on head injury, we used age, gender, height, and Body Mass Index (BMI) as characteristic parameters to develop the personalized human body multi-rigid body (MB) models and head finite element (FE) models. Next, using simulation calculations, we developed the VRU head injury dataset based on the personalized models. In the dataset, the dependent variables were the degree of head injury and the brain tissue von Mises value, while the independent variables were height, BMI, age, gender, traffic participation status, and vehicle speed. The statistical results of the dataset show that the von Mises value of VRU brain tissue during collision ranges from 4.4 kPa to 46.9 kPa at speeds between 20 and 60 km/h. The effects of anatomical characteristics on head injury include: the risk of a more serious head injury of VRU rises with age; VRU with higher BMIs has less head injury in collision accidents; height has very erratic and nonlinear impacts on the von Mises values of the VRU's brain tissue; and the severity of head injury is not significantly influenced by VRU's gender. Furthermore, we developed the classification prediction models of head injury degree and the regression prediction models of head injury response parameter by applying eight different data mining algorithms to this dataset. The classification prediction models have the best accuracy of 0.89 and the best R2 value of 0.85 for the regression prediction models.

Development of personalizable female and male pedestrian SAFER human body models

OBJECTIVES

Vulnerable road users are globally overrepresented as victims of road traffic injuries. Developing biofidelic male and female pedestrian human body models (HBMs) that represent diverse anthropometries is essential to enhance road safety and propose intervention strategies.

METHODS

In this study, 50th percentile male and female pedestrians of the SAFER HBM were developed via a newly developed image registration-based mesh morphing framework. The performance of the HBMs was evaluated by means of a set of cadaver experiments, involving subjects struck laterally by a generic sedan buck.

RESULTS

In simulated whole-body pedestrian collisions, the personalized HBMs effectively replicate trajectories of the head and lower body regions, as well as head kinematics, in lateral impacts. The results also demonstrate the personalization framework's capacity to generate personalized HBMs with reliable mesh quality, ensuring robust simulations.

CONCLUSIONS

The presented pedestrian HBMs and personalization framework provide robust means to reconstruct and evaluate head impacts in pedestrian-to-vehicle collisions thoroughly and accurately.

A high-fidelity biomechanical modeling framework for injury prediction during frontal car crash

Injuries arising from car crashes are ubiquitous across the globe and account for over 1.3 million fatalities annually. 93% of mortalities are observed in middle- and low-income countries owing to the lack of infrastructure in the safety assessment of car designs. It is therefore imperative to predict the extent of injuries to the occupants during car crashes, which would lead to safer vehicle design. To date, conventional computational testing methods use Hybrid III dummies, which fail to reproduce fracture and tear injuries. In this work, a full-frontal collision of a vehicle against a rigid wall with a highly biofidelic human body model of an occupant was simulated for the first time to investigate fractures and tears using a novel fracture modeling technique. Fractures were observed in ribs (5-7), which occurred at stresses of 120 MPa at the left lateral vertebrosternal region. In the lower extremity, tears in the ligaments at 70.80 MPa, and fractures in the tibia and femur at 236 MPa were quantified. Stresses in the skull were limited to 11 MPa, indicating a possibility of concussion rather than fractures. The developed computational model would be indispensable for car manufacturers to test the crash impact on the human body at all possible accident scenarios accurately, which will help design better solutions for automotive injury mitigation.

Numerical Reconstruction of Cyclist Impact Accidents: Can Helmets Protect the Head-Neck of Cyclists?

Cyclists are vulnerable road users and often suffer head-neck injuries in car-cyclist accidents. Wearing a helmet is currently the most prevalent protection method against such injuries. Today, there is an ongoing debate about the ability of helmets to protect the cyclists' head-neck from injury. In the current study, we numerically reconstructed five real-world car-cyclist impact accidents, incorporating previously developed finite element models of four cyclist helmets to evaluate their protective performances. We made comparative head-neck injury predictions for unhelmeted and helmeted cyclists. The results show that helmets could clearly lower the risk of severe (AIS 4+) brain injury and skull fracture, as assessed by the predicted head injury criterion (HIC), while a relatively limited decrease in AIS 4+ brain injury risk can be achieved in terms of the analysis of CSDM0.25. Assessment using the maximum principal strain (MPS0.98) and head impact power (HIP) criteria suggests that helmets could lower the risk of diffuse axonal injury and subdural hematoma of the cyclist. The helmet efficacy in neck protection depends on the impact scenario. Therefore, wearing a helmet does not seem to cause a significant neck injury risk level increase to the cyclist. Our work presents important insights into the helmet's efficacy in protecting the head-neck of cyclists and motivates further optimization of protective equipment.

Investigation of traffic accidents involving seated pedestrians using a finite element simulation-based approach

Pedestrians who use wheelchairs (seated pedestrians) report 36% - 75% higher mortality rates than standing pedestrians in car-to-pedestrian collisions but the cause of this mortality is unknown. This is the first study to investigate the cause of seated pedestrian mortality in vehicle impacts using finite element simulations. In this study a manual wheelchair model was developed using geometry taken from publicly available CAD data, and was tested to meet ISO standards. The GHBMC 50^th percentile male simplified occupant model was used as the seated pedestrian and the EuroNCAP family car and sports utility vehicle models were used as the impacting vehicles. The seated pedestrian was impacted by the two vehicles at three different locations on the vehicle and at 30 and 40 km/h. In 75% of the impacts the pedestrian was ejected from the wheelchair. In the rest of the impacts, the pedestrian and wheelchair were pinned to the vehicle and the pedestrian was not ejected. The underlying causes of seated pedestrian mortality in these impacts were head and brain injury. Life-threatening head injury risks (0.0% - 100%) were caused by the ground-pedestrian contact, and life-threatening brain injury risks (0.0 - 97.9%) were caused by the initial vehicle-wheelchair contact and ground-pedestrian contact. Thoracic and abdominal compression reported no risks of life-threatening injuries, but may do so in faster impacts or with different wheelchair designs. Protective equipment such as the wheelchair seatbelt or personal airbag may be useful in reducing injury risks but future research is required to investigate their efficacy.

Influence of walking on knee ligament response in car-to-pedestrian collisions

Pedestrians are likely to experience walking before accidents. The walking process imposes cyclic loading on knee ligaments and increases knee joint temperature. Both cyclic loading and temperature affect the material properties of ligaments, which further influence the risk of ligament injury. However, the effect of such walking-induced material property changes on pedestrian ligament response has not been considered. Therefore, in this study, we investigated the influence of walking on ligament response in car-to-pedestrian collisions. Using Total Human Model for Safety (THUMS) model, knee ligament responses (i.e., cross-sectional force and local strain) were evaluated under several crash scenarios (i.e., two impact speeds, two knee contact heights, and three pedestrian postures). In worst case scenarios, walking-induced changes in ligament material properties led to a 10% difference in maximum local strain and a 6% difference in maximum cross-sectional force. Further considering the material uncertainty caused by experimental dispersion, the ligament material property changes due to walking resulted in a 28% difference in maximum local strain and a 26% difference in maximum cross-sectional force. This study demonstrates the importance of accounting for walking-induced material property changes for the reliability of safety assessments and injury analysis.

Effects of different preservation on the mechanical properties of cortical bone under quasi-static and dynamic compression

Introduction: Mechanical properties of biological tissue are important for numerical simulations. Preservative treatments are necessary for disinfection and long-term storage when conducting biomechanical experimentation on materials. However, few studies have been focused on the effect of preservation on the mechanical properties of bone in a wide strain rate. The purpose of this study was to evaluate the influence of formalin and dehydration on the intrinsic mechanical properties of cortical bone from quasi-static to dynamic compression. Methods: Cube specimens were prepared from pig femur and divided into three groups (fresh, formalin, and dehydration). All samples underwent static and dynamic compression at a strain rate from 10^-3 s^-1 to 10³ s^-1. The ultimate stress, ultimate strain, elastic modulus, and strain-rate sensitivity exponent were calculated. A one-way ANOVA test was performed to determine if the preservation method showed significant differences in mechanical properties under at different strain rates. The morphology of the macroscopic and microscopic structure of bones was observed. Results: The results show that ultimate stress and ultimate strain increased as the strain rate increased, while the elastic modulus decreased. Formalin fixation and dehydration did not affect elastic modulus significantly whereas significantly increased the ultimate strain and ultimate stress. The strain-rate sensitivity exponent was the highest in the fresh group, followed by the formalin group and dehydration group. Different fracture mechanisms were observed on the fractured surface, with fresh and preserved bone tending to fracture along the oblique direction, and dried bone tending to fracture along the axial direction. Discussion: In conclusion, preservation with both formalin and dehydration showed an influence on mechanical properties. The influence of the preservation method on material properties should be fully considered in developing a numerical simulation model, especially for high strain rate simulation.

Hello, world! VIVA+: A human body model lineup to evaluate sex-differences in crash protection

Finite element Human Body Models are increasingly becoming vital tools for injury assessment and are expected to play an important role in virtual vehicle safety testing. With the aim of realizing models to study sex-differences seen in the injury- and fatality-risks from epidemiology, we developed models that represent an average female and an average male. The models were developed with an objective to allow tissue-based skeletal injury assessment, and thus non-skeletal organs and joints were defined with simplified characterizations to enhance computational efficiency and robustness. The model lineup comprises female and male representations of (seated) vehicle occupants and (standing) vulnerable road users, enabling the safety assessment of broader segments of the road user population. In addition, a new workflow utilized in the model development is presented. In this workflow, one model (the seated female) served as the base model while all the other models were generated as closely-linked derivative models, differing only in terms of node coordinates and mass distribution. This approach opens new possibilities to develop and maintain further models as part of the model lineup, representing different types of road users to reflect the ongoing transitions in mobility patterns (like bicyclists and e-scooter users). In this paper, we evaluate the kinetic and kinematic responses of the occupant and standing models to blunt impacts, mainly on the torso, in different directions (front, lateral, and back). The front and lateral impacts to the thorax showed responses comparable to the experiments, while the back impact varied with the location of impact (T1 and T8). Abdomen bar impact showed a stiffer load-deflection response at higher intrusions beyond 40 mm, because of simplified representation of internal organs. The lateral shoulder impact responses were also slightly stiffer, presumably from the simplified shoulder joint definition. This paper is the first in a series describing the development and validation of the new Human Body Model lineup, VIVA+. With the inclusion of an average-sized female model as a standard model in the lineup, we seek to foster an equitable injury evaluation in future virtual safety assessments.

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.

KINEMATICS AND INJURY MECHANISM OF CYCLIST LOWER LIMB IN VEHICLE-TO-BICYCLE COLLISIONS

Accident data show that lower limb is one of the most frequently injured body parts for cyclists in vehicle collisions. However, studies of cyclist lower limb injuries and protection are still sparse. Therefore, the purpose of this study is to investigate the kinematics and injury mechanism of cyclist lower limb in vehicle-to-bicycle collisions considering different impact boundary conditions. To achieve this, the finite element (FE) modeling approach and an FE human body lower limb model with detailed muscles were employed, and impact boundary conditions with different vehicle front-end shapes and cycling postures were considered. Predictions of lower limb kinematics, knee ligament elongation and bending moment of upper and lower leg were used for analysis. The simulation results show that cycling posture has a significant influence on cyclist lower limb kinematics and injury risk, lateral bending toward the direction of vehicle or vehicle moving combining with lateral shearing is the main mechanism for cyclist knee ligament injuries, and injuries to long bones of cyclist leg in vehicle impacts could form lateral bending at both directions. The findings suggest that the influence of cycling posture and distinct difference in injury mechanism between cyclist and pedestrian should be considered in the assessment of vehicle safety design for cyclist lower limb protection.

The effect of posterior tethers on the biomechanics of proximal junctional kyphosis: The whole human finite element model analysis

Little is known about the effects of posterior tethers on the development of proximal junctional kyphosis (PJK). We evaluated the ability of posterior tethers to the proximal motion segment stiffness in long instrumented spinal instrumentation and fusion using a whole body human FE model. A series of finite element (FE) analysis of long segmental spinal fusion (SF) from the upper thoracic vertebra (T1) or lower thoracic vertebra (T9) to the sacrum with pedicle screws and rods were performed using an entire human body FE model (includes 234,910 elements), and compressive stresses (CS) on the anterior column, and tensile stresses (TS) on the posterior ligamentous complex (PLC) in the upper-instrumented vertebra (UIV) and the vertebra adjacent to the UIV (UIV + 1) were evaluated with posterior tethers or without posterior tethers. The models were tested at three T1 tilts (0, 20, 40 deg.), with 20% muscle contraction. Deformable material models were assigned to all body parts. Muscle-tendon complexes were modeled by truss elements with a Hill-type muscle material model. The CS of anterior column decreased with increasing T1 slope with tethers in both models, while the CS remained relatively large in T9 model compared with T1 model (T1 UIV; 0.96 to 1.56 MPa, T9 UIV; 4.79 to 5.61 MPa). The TS of the supraspinous ligament was markedly reduced in both T1 and T9 models with posterior tethers (11-35%). High vertebral CS on UIV and UIV + 1 were seen in the T9 UIV model, and the TS on the PLC were increased in both UIV models. Posterior tethers may decrease PJK development after SF with a proximal thoracic UIV, while both posterior tethers and vertebral augmentation may be necessary to reduce PJK development with a lower thoracic UIV.

A Computational Biomechanics Human Body Model Coupling Finite Element and Multibody Segments for Assessment of Head/Brain Injuries in Car-To-Pedestrian Collisions

It has been challenging to efficiently and accurately reproduce pedestrian head/brain injury, which is one of the most important causes of pedestrian deaths in road traffic accidents, due to the limitations of existing pedestrian computational models, and the complexity of accidents. In this paper, a new coupled pedestrian computational biomechanics model (CPCBM) for head safety study is established via coupling two existing commercial pedestrian models. The head–neck complex of the CPCBM is from the Total Human Model for Safety (THUMS, Toyota Central R&D Laboratories, Nagakute, Japan) (Version 4.01) finite element model and the rest of the parts of the body are from the Netherlands Organisation for Applied Scientific Research (TNO, The Hague, The Netherlands) (Version 7.5) multibody model. The CPCBM was validated in terms of head kinematics and injury by reproducing three cadaveric tests published in the literature, and a correlation and analysis (CORA) objective rating tool was applied to evaluate the correlation of the related signals between the predictions using the CPCBM and the test results. The results show that the CPCBM head center of gravity (COG) trajectories in the impact direction (YOZ plane) strongly agree with the experimental results (CORA ratings: Y = 0.99 ± 0.01; Z = 0.98 ± 0.01); the head COG velocity with respect to the test vehicle correlates well with the test data (CORA ratings: 0.85 ± 0.05); however, the correlation of the acceleration is less strong (CORA ratings: 0.77 ± 0.06). No significant differences in the behavior in predicting the head kinematics and injuries of the tested subjects were observed between the TNO model and CPCBM. Furthermore, the application of the CPCBM leads to substantial reduction of the computation time cost in reproducing the pedestrian head tissue level injuries, compared to the full-scale finite element model, which suggests that the CPCBM could present an efficient tool for pedestrian brain-injury research.

A Computationally Efficient Finite Element Pedestrian Model for Head Safety: Development and Validation

Head injuries are often fatal or of sufficient severity to pedestrians in vehicle crashes. Finite element (FE) simulation provides an effective approach to understand pedestrian head injury mechanisms in vehicle crashes. However, studies of pedestrian head safety considering full human body response and a broad range of impact scenarios are still scarce due to the long computing time of the current FE human body models in expensive simulations. Therefore, the purpose of this study is to develop and validate a computationally efficient FE pedestrian model for future studies of pedestrian head safety. Firstly, a FE pedestrian model with a relatively small number of elements (432,694 elements) was developed in the current study. This pedestrian model was then validated at both segment and full body levels against cadaver test data. The simulation results suggest that the responses of the knee, pelvis, thorax, and shoulder in the pedestrian model are generally within the boundaries of cadaver test corridors under lateral impact loading. The upper body (head, T1, and T8) trajectories show good agreements with the cadaver data in vehicle-to-pedestrian impact configuration. Overall, the FE pedestrian model developed in the current study could be useful as a valuable tool for a pedestrian head safety study.

A Cortical Thickness Mapping Method for the Coxal Bone Using Morphing

As human body finite element models become more integrated with the design of safety countermeasures and regulations, novel models need to be developed that reflect the variation in the population's anthropometry. However, these new models may be missing information which will need to be translated from existing models. During the development of a 5th percentile female occupant model (F05), cortical thickness information of the coxal bone was unavailable due to resolution limits in the computed tomography (CT) scans. In this study, a method for transferring cortical thickness information from a source to a target model with entirely different geometry and architecture is presented. The source and target models were the Global Human Body Models Consortium (GHBMC) 50th percentile male (M50) and F05 coxal bones, respectively. To project the coxal bone cortical thickness from the M50 to the F05, the M50 model was first morphed using a Kriging method with 132 optimized control points to the F05 anthropometry. This technique was found to be accurate with a mean nodal discrepancy of 1.27 mm between the F05 and morphed M50 (mM50) coxal bones. Cortical thickness at each F05 node was determined by taking the average cortical thickness of every mM50 node, non-linearly weighted by its distance to the F05 nodes. The non-linear weighting coefficient, β, had a large effect on the accuracy and smoothness of the projected cortical bone thickness. The optimal projection had β = 4 and was defined when the tradeoff between projection accuracy and smoothness was equal. Finally, a quasi-static pelvis compression was simulated to examine to effect of β. As β, increased from 0 to 4, the failure force decreased by ~100 N, whereas the failure displacement increased by 0.9 mm. Results from quasi-static compression tests of the F05 pelvis were comparable to experimental results. This method could be applied to other anatomical regions where cortical thickness variation is important, such as the femur and ribs and is not limited to GHBMC-family models. Furthermore, this process will aid the development of subject-specific finite element models where accurate cortical bone thickness measurements cannot be obtained.