Pedestrian head translation, rotation and impact velocity: the influence of vehicle speed, pedestrian speed and pedestrian gait

Subject-specific finite element head models for skull fracture evaluation-a new tool in forensic pathology

Post-mortem computed tomography (PMCT) enables the creation of subject-specific 3D head models suitable for quantitative analysis such as finite element analysis (FEA). FEA of proposed traumatic events is an objective and repeatable numerical method for assessing whether an event could cause a skull fracture such as seen at autopsy. FEA of blunt force skull fracture in adults with subject-specific 3D models in forensic pathology remains uninvestigated. This study aimed to assess the feasibility of FEA for skull fracture analysis in routine forensic pathology. Five cases with blunt force skull fracture and sufficient information on the kinematics of the traumatic event to enable numerical reconstruction were chosen. Subject-specific finite element (FE) head models were constructed by mesh morphing based on PMCT 3D models and A Detailed and Personalizable Head Model with Axons for Injury Prediction (ADAPT) FE model. Morphing was successful in maintaining subject-specific 3D geometry and quality of the FE mesh in all cases. In three cases, the simulated fracture patterns were comparable in location and pattern to the fractures seen at autopsy/PMCT. In one case, the simulated fracture was in the parietal bone whereas the fracture seen at autopsy/PMCT was in the occipital bone. In another case, the simulated fracture was a spider-web fracture in the frontal bone, whereas a much smaller fracture was seen at autopsy/PMCT; however, the fracture in the early time steps of the simulation was comparable to autopsy/PMCT. FEA might be feasible in forensic pathology in cases with a single blunt force impact and well-described event circumstances.

Pedestrian injuries in the United States: Shifting injury patterns with the introduction of pedestrian protection into the passenger vehicle fleet

OBJECTIVE

Between 2010 and 2020, an annual average of more than 70,000 pedestrians were injured in U.S. motor vehicle crashes. Pedestrian fatalities increased steadily over that period, outpacing increases in vehicle occupant fatalities. Strategies for reducing pedestrian injuries include pedestrian crash prevention and improved vehicle design for protection of pedestrians in the crashes that cannot be prevented. This study focuses on understanding trends in injuries sustained in U.S. pedestrian crashes to inform continuing efforts to improve pedestrian crash protection in passenger vehicles.

METHODS

More than 160,000 adult pedestrians injured in motor vehicle crashes who were admitted to U.S. trauma centers between 2007 and 2016 were drawn from the National Trauma Data Bank (NTDB) Research Data Sets. The injuries in those cases were used to explore the shifting patterns of pedestrian injuries.

RESULTS

The proportion of pedestrians with thorax injuries increased 3.0 percentage points to 30.7% of trauma center-admitted NTDB pedestrian cases over the 10 years studied, and the proportion with pelvis/hip injuries increased to 21.2%. The proportion of cases with head injuries fell to 48.6%, and the percentage of pedestrians with lower extremity injury (44%) did not change significantly over the 10 year period. Assessment of possible reasons for the shifts suggested that increasing numbers of sport utility vehicles, population increases among the oldest age groups, and improvements in pedestrian protection in U.S. passenger vehicles likely contributed to, but did not completely account for, the relative changes in injury frequency in each body region.

CONCLUSIONS

More important than the reasons for the shifts in the relative frequency of injury to each body region are the conclusions that can be drawn regarding priorities for pedestrian protection research. Though head/face and lower extremity injuries remained the most frequently injured body regions in adult pedestrians admitted to NTDB trauma centers, the relative frequency of thorax and pelvis/hip injuries increased steadily, underlining the increasing importance of pedestrian protection research on these body regions.

Holistic pedestrian safety assessment for average males and females

Objective

An integrated assessment framework that enables holistic safety evaluations addressing vulnerable road users (VRU) is introduced and applied in the current study. The developed method enables consideration of both active and passive safety measures and distributions of real-world crash scenario parameters.

Methods

The likelihood of a specific virtual testing scenario occurring in real life has been derived from accident databases scaled to European level. Based on pre-crash simulations, it is determined how likely it is that scenarios could be avoided by a specific Autonomous Emergency Braking (AEB) system. For the unavoidable cases, probabilities for specific collision scenarios are determined, and the injury risk for these is determined, subsequently, from in-crash simulations with the VIVA+ Human Body Models combined with the created metamodel for an average male and female model. The integrated assessment framework was applied for the holistic assessment of car-related pedestrian protection using a generic car model to assess the safety benefits of a generic AEB system combined with current passive safety structures.

Results

In total, 61,914 virtual testing scenarios have been derived from the different car-pedestrian cases based on real-world crash scenario parameters. Considering the occurrence probability of the virtual testing scenarios, by implementing an AEB, a total crash risk reduction of 81.70% was achieved based on pre-crash simulations. It was shown that 50 in-crash simulations per load case are sufficient to create a metamodel for injury prediction. For the in-crash simulations with the generic vehicle, it was also shown that the injury risk can be reduced by implementing an AEB, as compared to the baseline scenarios. Moreover, as seen in the unavoidable cases, the injury risk for the average male and female is the same for brain injuries and femoral shaft fractures. The average male has a higher risk of skull fractures and fractures of more than three ribs compared to the average female. The average female has a higher risk of proximal femoral fractures than the average male.

Conclusions

A novel methodology was developed which allows for movement away from the exclusive use of standard-load case assessments, thus helping to bridge the gap between active and passive safety evaluations.

A Method for Evaluating Brain Deformation Under Sagittal Blunt Impacts Using a Half-Skull Human-Scale Surrogate

Trauma to the brain is a biomechanical problem where the initiating event is a dynamic loading (blunt, inertial, blast) to the head. To understand the relationship between the mechanical parameters of the injury and the spatial and temporal deformation patterns in the brain, there is a need to develop a reusable and adaptable experimental traumatic brain injury (TBI) model that can measure brain motion under varying parameters. In this effort, we aim to directly measure brain deformation (strain and strain rates) in different brain regions in a human head model using a drop tower.

METHODS

Physical head models consisting of a half, sagittal plane skull, brain, and neck were constructed and subjected to crown and frontal impacts at two impact speeds. All tests were recorded with a high-speed camera at 1000 frames per second. Motion of visual markers within brain surrogates were used to track deformations and calculate spatial strain histories in 6 brain regions of interest. Principal strains, strain rates and strain impulses were calculated and reported.

RESULTS

Higher impact velocities corresponded to higher strain values across all impact scenarios. Crown impacts were characterized by high, long duration strains distributed across the parietal, frontal and hippocampal regions whereas frontal impacts were characterized by sharply rising and falling strains primarily found in the parietal, frontal, hippocampal and occipital regions. High strain rates were associated with short durations and impulses indicating fast but short-lived strains. 2.23 m/s (5 mph) crown impacts resulted in 53% of the brain with shear strains higher than 0.15 verses 32% for frontal impacts.

CONCLUSIONS

The results reveal large differences in the spatial and temporal strain responses between crown and forehead impacts. Overall, the results suggest that for the same speed, crown impact leads to higher magnitude strain patterns than a frontal impact. The data provided by this model provides unique insight into the spatial and temporal deformation patterns that have not been provided by alternate surrogate models. The model can be used to investigate how anatomical, material and loading features and parameters can affect deformation patterns in specific regions of interest in the brain.

Head Impact Location, Speed and Angle from Falls and Trips in the Workplace

Traumatic brain injury (TBI) is a common injury in the workplace. Trips and falls are the leading causes of TBI in the workplace. However, industrial safety helmets are not designed for protecting the head under these impact conditions. Instead, they are designed to pass the regulatory standards which test head protection against falling heavy and sharp objects. This is likely to be due to the limited understanding of head impact conditions from trips and falls in workplace. In this study, we used validated human multi-body models to predict the head impact location, speed and angle (measured from the ground) during trips, forward falls and backward falls. We studied the effects of worker size, initial posture, walking speed, width and height of the tripping barrier, bracing and falling height on the head impact conditions. Overall, we performed 1692 simulations. The head impact speed was over two folds larger in falls than trips, with backward falls producing highest impact speeds. However, the trips produced impacts with smaller impact angles to the ground. Increasing the walking speed increased the head impact speed but bracing reduced it. We found that 41% of backward falls and 19% of trips/forward falls produced head impacts located outside the region of helmet coverage. Next, we grouped all the data into three sub-groups based on the head impact angle: [0°, 30°], (30°, 60°] and (60°, 90°] and excluded groups with small number of cases. We found that most trips and forward falls lead to impact angles within the (30°, 60°] and (60°, 90°] groups while all backward falls produced impact angles within (60°, 90°] group. We therefore determined five representative head impact conditions from these groups by selecting the 75th percentile speed, mean value of angle intervals and median impact location (determined by elevation and azimuth angles) of each group. This led to two representative head impact conditions for trips: 2.7 m/s at 45° and 3.9 m/s at 75°, two for forward falls: 3.8 m/s at 45° and 5.5 m/s at 75° and one for backward falls: 9.4 m/s at 75°. These impact conditions can be used to improve industrial helmet standards.

Multiobjective optimization algorithm for accurate MADYMO reconstruction of vehicle-pedestrian accidents

In vehicle-pedestrian accidents, the preimpact conditions of pedestrians and vehicles are frequently uncertain. The incident data for a crash, such as vehicle deformation, injury of the victim, distance of initial position and rest position of accident participants, are useful for verification in MAthematical DYnamic MOdels (MADYMO) simulations. The purpose of this study is to explore the use of an improved optimization algorithm combined with MADYMO multibody simulations and crash data to conduct accurate reconstructions of vehicle-pedestrian accidents. The objective function of the optimization problem was defined as the Euclidean distance between the known vehicle, human and ground contact points, and multiobjective optimization algorithms were employed to obtain the local minima of the objective function. Three common multiobjective optimization algorithms-nondominated sorting genetic algorithm-II (NSGA-II), neighbourhood cultivation genetic algorithm (NCGA), and multiobjective particle swarm optimization (MOPSO)-were compared. The effect of the number of objective functions, the choice of different objective functions and the optimal number of iterations were also considered. The final reconstructed results were compared with the process of a real accident. Based on the results of the reconstruction of a real-world accident, the present study indicated that NSGA-II had better convergence and generated more noninferior solutions and better final solutions than NCGA and MOPSO. In addition, when all vehicle-pedestrian-ground contacts were considered, the results showed a better match in terms of kinematic response. NSGA-II converged within 100 generations. This study indicated that multibody simulations coupled with optimization algorithms can be used to accurately reconstruct vehicle-pedestrian collisions.

Reconstruction of a real-world car-to-pedestrian collision using geomatics techniques and numerical simulations

The aim of this study is to provide an improved method for traffic accident reconstruction based on geomatics techniques and numerical simulations. A combination of various techniques was used. First, an unmanned aerial vehicle (UAV), laser scanner and structured-light scanner were used to obtain information on the accident scene, vehicle and victim. The collected traces provided detailed initial impact conditions for subsequent numerical simulations. Then, multi-body system (MBS) simulations were conducted to reconstruct the kinematics of the car-to-pedestrian collision. Finally, a finite element (FE) simulation using the THUMS model was performed to predict injuries. A real-life vehicle-pedestrian collision was used to verify the feasibility and effectiveness of this method. The reconstruction result revealed that the kinematic and injury predictions of the numerical simulations effectively conformed to the surveillance video and investigation of the actual accident. UAV photogrammetry was demonstrated to be more efficient in accident data collection than hand sketch and measurement, and 3D laser scanning enabled an easier and more accurate modeling process of vehicle. The present study shows the feasibility of this method for use in traffic accident reconstruction.

Numerical investigation of the rider's head injury in typical single-electric self-balancing scooter accident scenarios

As the use of electric self-balancing scooters (ESSs) increases, so does the number of related traffic accidents. Because of the special control method, mechanical structure and driving posture, ESSs are prone to various single-vehicle accidents, such as collisions with fixed obstacles and falls due to mechanical failures. In various ESS accident scenarios, the rider's head injury is the most frequent injury type. In this study, several typical single-ESS accident scenarios are reconstructed via computational methods, and the risk of riders' head/brain injury is assessed in depth using various injury criteria. Results showed that two types of ESSs (solo- and two-wheeler) do not have clear differences in head kinematics and head injury risks; the head kinematics (or falling posture) and ESS accident scenario exhibit a distinct effect on the head injury responses; half of the analysed ESS riders have a 50% probability of skull fracture, a few riders have a 50% risk of abbreviated injury scale (AIS) 4+ brain injury, and none has a diffuse axonal injury; the ESS speed plays an important role in producing the head/brain injury in ESS riders, and generally, higher ESS speed generates higher level of predicted head injury parameters. These findings will provide theoretical support for preventing head injury among ESS riders and data support for developing and legislating ESSs.

Computational prediction of head-ground impact kinematics in e-scooter falls

E-scooters are the fastest growing mode of micro-mobility with important environmental benefits. However, there are serious concerns about injuries caused by e-scooter accidents. Falls due to poor road surface conditions are a common cause of injury in e-scooter riders, and head injuries are one of the most common and concerning injuries in e-scooter falls. However, the head-ground impact biomechanics in e-scooter falls and its relationship with e-scooter speed and design, road surface conditions and wearing helmets remain poorly understood. To address some of these key questions, we predicted the head-ground impact force and velocity of e-scooter riders in different falls caused by potholes. We used multi-body dynamics approach to model a commercially available e-scooter and simulate 180 falls using human body models. We modelled different pothole sizes to test whether the pothole width and depth influences the onset of falls and head-ground impact velocity and force. We also tested whether the e-scooter travelling speed has an influence on the head-ground impact velocity and force. The simulations were carried out with three human body models to ensure that the results of the study are inclusive of a wide range of rider sizes. For our 10 in. diameter e-scooter wheels, we found a sudden increase in the occurrence of falls when the pothole depth was increased from 3 cm (no falls) to 6 cm (41 falls out of 60 cases). When the falls occurred, we found a head-ground impact force of 13.2 ± 3.4kN, which is larger than skull fracture thresholds. The head-ground impact speed was 6.3 ± 1.4 m/s, which is the same as the impact speed prescribed in bicycle helmet standards. All e-scooter falls resulted in oblique head impacts, with an impact angle of 65 ± 10° (measured from the ground). Decreasing the e-scooter speed reduced the head impact speed. For instance, reducing the e-scooter speed from 30 km/h to 20 km/h led to a 14% reduction in the mean impact speed and 12% reduction in the mean impact force, as predicted by the models. The models also showed that the median male riders were sustaining higher head-ground impact force and speed compared with the small female and large male riders. The findings of this study can assist authorities and e-scooter hiring companies to take more informed actions about road surface conditions and speed limits. These results can also help define representative impact test conditions for assessing the performance of helmets used by e-scooter riders in order to reduce head and brain injuries in e-scooter falls.

Realistic Reference for Evaluation of Vehicle Safety Focusing on Pedestrian Head Protection Observed From Kinematic Reconstruction of Real-World Collisions

Head-to-vehicle contact boundary condition and criteria and corresponding thresholds of head injuries are crucial in evaluation of vehicle safety performance for pedestrian protection, which need a constantly updated understanding of pedestrian head kinematic response and injury risk in real-world collisions. Thus, the purpose of the current study is to investigate the characteristics of pedestrian head-to-vehicle contact boundary condition and pedestrian AIS3+ (Abbreviated Injury Scale) head injury risk as functions of kinematic-based criteria, including HIC (Head Injury Criterion), HIP (Head Impact Power), GAMBIT (Generalized Acceleration Model for Brain Injury Threshold), RIC (Rotational Injury Criterion), and BrIC (Brain Injury Criteria), in real-world collisions. To achieve this, 57 vehicle-to-pedestrian collision cases were employed, and a multi-body modeling approach was applied to reconstruct pedestrian kinematics in these real-world collisions. The results show that head-to-windscreen contacts are dominant in pedestrian collisions of the analysis sample and that head WAD (Wrap Around Distance) floats from 1.5 to 2.3 m, with a mean value of 1.84 m; 80% of cases have a head linear contact velocity below 45 km/h or an angular contact velocity less than 40 rad/s; pedestrian head linear contact velocity is on average 83 ± 23% of the vehicle impact velocity, while the head angular contact velocity (in rad/s) is on average 75 ± 25% of the vehicle impact velocity in km/h; 77% of cases have a head contact time in the range 50–140 ms, and negative and positive linear correlations are observed for the relationships between pedestrian head contact time and WAD/height ratio and vehicle impact velocity, respectively; 70% of cases have a head contact angle floating from 40° to 70°, with an average value of 53°; the pedestrian head contact angles on windscreens (average = 48°) are significantly lower than those on bonnets (average = 60°); the predicted thresholds of HIC, HIP, GAMBIT, RIC, BrIC2011, and BrIC2013 for a 50% probability of AIS3+ head injury risk are 1,300, 60 kW, 0.74, 1,470 × 10⁴, 0.56, and 0.57, respectively. The findings of the current work could provide realistic reference for evaluation of vehicle safety performance focusing on pedestrian protection.

Kinetic and Kinematic Features of Pedestrian Avoidance Behavior in Motor Vehicle Conflicts

The active behaviors of pedestrians, such as avoidance motions, affect the resultant injury risk in vehicle–pedestrian collisions. However, the biomechanical features of these behaviors remain unquantified, leading to a gap in the development of biofidelic research tools and tailored protection for pedestrians in real-world traffic scenarios. In this study, we prompted subjects (“pedestrians”) to exhibit natural avoidance behaviors in well-controlled near-real traffic conflict scenarios using a previously developed virtual reality (VR)-based experimental platform. We quantified the pedestrian–vehicle interaction processes in the pre-crash phase and extracted the pedestrian postures immediately before collision with the vehicle; these were termed the “pre-crash postures.” We recorded the kinetic and kinematic features of the pedestrian avoidance responses—including the relative locations of the vehicle and pedestrian, pedestrian movement velocity and acceleration, pedestrian posture parameters (joint positions and angles), and pedestrian muscle activation levels—using a motion capture system and physiological signal system. The velocities in the avoidance behaviors were significantly different from those in a normal gait (p < 0.01). Based on the extracted natural reaction features of the pedestrians, this study provides data to support the analysis of pedestrian injury risk, development of biofidelic human body models (HBM), and design of advanced on-vehicle active safety systems.

Evaluating the effectiveness of crosswalk tactile paving on street-crossing behavior: A field trial study for people with visual impairment

People with visual impairment cannot easily obtain external information through vision and thus they face more challenges when traveling than sighted people. The travel environment for people with visual impairment includes pedestrian safety concerns, especially when crossing roads at intersections. Tactile paving can be used as a guidance cue for street-crossing purposes but its use is not yet widespread globally (except at some test sites in Japan). This study investigated the effectiveness of tactile paving on crosswalks based on a field trial conducted in China. A drone and three-axis accelerometer were used to collect participants' behavioral data. Several quantitative indices for street-crossing behavior, including trajectory, maximum distance of the directional deviation, crossing speed, crossing time, and gait regularity and symmetry, were investigated to measure the participants' street-crossing performance. Before-after comparative analysis of the quantitative index results was conducted to compare the participants' use of crosswalks with and without tactile paving. The results reveal that tactile paving helps people with visual impairment to maintain a straight crossing path, avoid directional deviation, reduce their crossing time, and improve their gait regularity and symmetry. Study participants reported positive impressions of the effectiveness of crosswalk tactile paving based on one-to-one interviews conducted after the crosswalk tests. The results also indicate that crosswalk tactile paving is more effective for people with blindness than for those with low vision. This study's findings could serve as a theoretical basis for the deployment of various barrier-free traffic facilities (especially street-crossing facilities) for people with visual impairment.

The Influence of Gait Stance and Vehicle Type on Pedestrian Kinematics and Injury Risk

Pedestrians are one of the most vulnerable road users. In 2019, the USA reported the highest number of pedestrian fatalities number in nearly three decades. To better protect pedestrians in car-to-pedestrian collisions (CPC), pedestrian biomechanics must be better investigated. The pre-impact conditions of CPCs vary significantly in terms of the characteristics of vehicles (e.g., front-end geometry, stiffness, etc.) and pedestrians (e.g., anthropometry, posture, etc.). The influence of pedestrian gait posture has not been well analyzed. The purpose of this study was to numerically investigate the changes in pedestrian kinematics and injuries across various gait postures in two different vehicle impacts. Five finite element (FE) human body models, that represent the 50th percentile male in gait cycle, were developed and used to perform CPC simulations with two generic vehicle FE models representing a low-profile vehicle and a high-profile vehicle. In the impacts with the high-profile vehicle, a sport utility vehicle, the pedestrian models usually slide above the bonnet leading edge and report shorter wrap around distances than in the impacts with a low-profile vehicle, a family car/sedan (FCR). The pedestrian postures influenced the postimpact rotation of the pedestrian and consequently, the impacted head region. Pedestrian posture also influenced the risk of injuries in the lower and upper extremities. Higher bone bending moments were observed in the stance phase posture compared to the swing phase. The findings of this study should be taken into consideration when examining pedestrian protection protocols. In addition, the results of this study can be used to improve the design of active safety systems used to protect pedestrians in collisions.

Current state and progress of research on forensic biomechanics in China

Forensic biomechanics gradually has become a significant component of forensic science. Forensic biomechanics is evidence-based science that applies biomechanical principles and methods to forensic practice, which has constituted one of the most potential research areas. In this review, we introduce how finite element techniques can be used to simulate forensic cases, how injury criteria and injury scales can be used to describe injury severity, and how tests of postmortem human subjects and dummy can be used to provide essential validation data. This review also describes research progress and new applications of forensic biomechanics in China.Key pointsThe review shows the main research progress and new applications of forensic biomechanics in China.The review introduces eight cases about the application of forensic biomechanics, including the multiple rigid body reconstruction, the finite element applications, study of mechanical properties, traffic crash reconstruction based on multiple techniques and analysis of morphomechanical mechanism about blood dispersal.Though forensic biomechanics has a great advantage for the evaluation of injury mechanisms, it still has some uncertainties owing to the uniqueness of the human anatomy, the complexity of biological materials, and the uncertainty of injury-causing circumstances.

Estimated and underreported parameters in report based vehicle-bicycle accident reconstructions have a significant influence

This study aimed to reconstruct four real life vehicle-bicycle collisions and evaluates the reconstruction parameters that affect the outcome of head injuries in report based accident reconstructions. A computational model of a car was developed in the multibody software MADYMO (MAthematical DYnamic MOdeling) and was used together with a validated bicycle model and the MADYMO 50 percentile pedestrian model. The accidents were reconstructed through an optimal fit method, based on kinematic and medical information. After the reconstruction, a parametric study on cyclists' movement and accident conditions was performed on the different cases. The velocity of the car and the angle of impact were found to significantly affect the accident outcome. This was demonstrated in terms of head injury criteria such as the Head Injury Criterion (HIC), the peak linear and peak angular velocity and acceleration. It was shown that the severity of the injury increases exponentially with increasing collision velocities. Additionally, the bicycle's parameters; crank rotation, handlebar angle and seat position revealed a large heterogeneity in the results. The maximum alteration between the lowest and highest HIC-value found for a complete crank rotation was a 416 % difference. For a handlebar rotation up to 100° or seat height alteration of maximum 34 cm, this value was respectively 169 % and 294 %. These high percentages of change indicate the need for cycling phase information for case-specific vehicle-bicycle accident reconstructions.

The predictive capacity of the MADYMO ellipsoid pedestrian model for pedestrian ground contact kinematics and injury evaluation

Pedestrian injuries occur in both the primary vehicle contact and the subsequent ground contact. Currently, no ground contact countermeasures have been implemented and no pedestrian model has been validated for ground contact, though this is needed for developing future ground contact injury countermeasures. In this paper, we assess the predictive capacity of the MADYMO ellipsoid pedestrian model in reconstructing six recent pedestrian cadaver ground contact experiments. Whole-body kinematics as well as vehicle and ground contact related aHIC (approximate HIC) and BrIC scores were evaluated. Reasonable results were generally achieved for the timings of the principal collision events, and for the overall ground contact mechanisms. However, the resulting head injury predictions based on the ground contact HIC and BrIC scores showed limited capacity of the model to replicate individual experiments. Sensitivity studies showed substantial influences of the vehicle-pedestrian contact characteristic and certain initial pedestrian joint angles on the subsequent ground contact kinematics and injury predictions. Further work is needed to improve the predictive capacity of the MADYMO pedestrian model for ground contact injury predictions.

Analysis of craniocerebral injury in facial collision accidents

Considering that the Pc-Crash multibody dynamics software can reproduce the accident process accurately and obtain the collision parameters of pedestrian heads at the moment of head landing, the finite element analysis method can accurately analyze the injury of the pedestrian head when the boundary conditions are known. This paper combines the accident reconstruction method with the finite element analysis method to study the injury mechanism of pedestrian head impact on the ground in vehicle pedestrian collision accidents to provide a theoretical basis for pedestrian protection and the improvement of vehicle shapes. First, a real-life vehicle pedestrian collision is reproduced by Pc-Crash. The simulation results show that the rigid multibody model can accurately simulate the scene of the accident, then the speed and angle of the pedestrian head landing moment can be obtained at the same time. Second, the finite element model of human heads with a detailed facial structure is established and verified. Finally, the collision parameters obtained from the accident reconstruction are used as the boundary conditions to analyze the collision between the pedestrian head and the ground, and the biomechanical parameters, such as intracranial pressure, von Mises stress, shear stress and strain, can be determined. The results show that the stress wave will propagate inside and outside the skull and cause stress concentration in the skull and the brain tissue to varying degrees after the pedestrian head strikes the ground. When the stress exceeds a certain limit, it will cause different degrees of brain tissue injury.

Neck injury mechanisms in train collisions: Dynamic analysis and data mining of the driver impact injury

Human necks are vulnerable in train collision accidents. To design a safer cab workspace, the driver neck injury mechanism should be investigated first. In this study, this issue is addressed by investigating how neck injuries are influenced by the cab workspace dimensions. The driver-console-seat dynamic models are developed to quantify the neck injuries. The three-pivot head-neck-upper torso model is used to evaluate the relative rotation angle between head and upper torso (β+γ). The injury mechanism with the larger (β+γ) value results in more severe neck injuries. The decision tree model is established to explore the most important cab workspace dimensional parameter. The driver submarining posture (the driver exhibits the tendency of sliding down from the seat after contacting the console) generates more (β+γ) value than the flipping over behavior (the driver contacts the console and the upper body continues to move over the top of the console). Four neck injury mechanisms are classified, in which the chest-first impact mechanisms are more dangerous than the knee-first impact mechanisms. The distance between the console edge and knee bolster has the greatest effect on the neck injury. This parameter determines the injury mechanism type as it influences the first contact region of the driver. The distance between the console and seat and the pedal height are the secondary dominant attributes. These three parameters should be considered preferentially for establishing driver protection measures.

Are riders of electric two-wheelers safer than bicyclists in collisions with motor vehicles?

Electric two-wheelers (E2Ws) have become newly popular transportation tools with the associated growing traffic safety concerns. E2W riders and bicyclists behave similarly as vulnerable road users (VRUs), while exhibited dissimilarities in riding postures and interactions with the two-wheelers. Existing epidemiology reveals prominent differences in injury risks between E2W riders and other vulnerable road users in collisions with motor vehicles. The objective of this study is to investigate the factors influencing kinematics and head injury risks of two-wheeler rides in two-wheeler-vehicle collisions and compare between E2W-vehicle and bicycle-vehicle collisions. Via multi-body modeling of two two-wheeler types, two vehicle types, and three rider statures in MADYMO, twelve collision scenarios were developed. A simulation matrix considering a range of impact velocities and relative positions was performed for each scenario. A subsequent parametric analysis was conducted with focus on the kinematics and head injury risks of two-wheeler riders. Results show that the head injury risk increased with vehicle moving velocity, while the two-wheeler velocity and relative location between rider and vehicle prior to the collision exhibited highly non-linear influence on the kinematical response. The rider with larger stature had higher possibilities to miss head impact on the vehicle. In collisions with the sedan, E2W riders would sustain lower head injury risks with lower contacting velocity on the windshield than bicyclists. While in collisions with the SUV, E2W riders would sustain increasing head injury risks due to the higher structural stiffness at contact, and the risk level was about the same as bicyclists. The findings revealed the loading mechanisms behind the different head injury risks between E2W riders and bicyclists.

Parameter sensitivity analysis of pedestrian head dynamic response and injuries based on coupling simulations

There are a very limited number of reports studying on the dynamic response and injuries of pedestrian head in the scenarios with head hitting windshield. This study aims to investigate the significant factors that affect the dynamic response and injuries of pedestrian head through finite element-multi-body coupling simulations. Two finite element vehicle models and two multi-body pedestrian human models were used to build the coupling simulations. Orthogonal experimental design and analysis of variance were used for parameter combination and data analysis. This study demonstrated that the dynamic response of pedestrian head and HIC15 were strongly associated with collision speed and pedestrian orientation. Vehicle type had a significant influence on the dynamic response of pedestrian head and HIC15, while there was no significant relationship between the dynamic response of pedestrian head and HIC15 and the size of pedestrian human models. Collision speed, pedestrian orientation, and vehicle type should be prioritized over the other collision parameters in the study of head injury mechanism and reconstruction of vehicle-pedestrian collisions in the scenarios with head hitting windshield.

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.

Prediction of injury risks and features among scooter riders through MADYMO reconstruction of a scooter-microvan accident: Identifying the driver and passengers

In dealing with a scooter-related traffic accident with rider death, it is necessary to identify the driver responsible for the accident. This study aimed to reconstruct the kinematics of a scooter-microvan accident involving three riders and explored the differences in injury risks and characteristics of the scooter driver and passengers. We reconstructed a real accident by using MADYMO multi-body simulation software. Moreover, we designed two-variable simulation experiments to analyze how the velocity and impact angle of the microvan are related to the injuries of the three riders. When the microvan speed is set at 18 km/h and that of the scooter is set at 28.8 km/h, the simulated kinematics correlates well with real accident data, and the impact positions and injury parameters correlate well with the actual injuries. When the impact angle is smaller than 30° and the microvan impact velocity is lower than 40 km/h, the head injury of the driver is more life-threatening than the corresponding injuries of the rear passengers. When the impact angle is 15° and the microvan impact velocity is in the range of 0-20 km/h, the femur fracture risk is higher for the driver than for passengers. As the impact angle increases to 45°, passengers have a higher risk of femur fracture than the driver in the velocity range of 0-10 km/h. This impact velocity range becomes 0-30 km/h at an impact angle of 60° and then 40-70 km/h at an impact angle of 90°. Our study shows that the multibody method can reconstruct accidents and predict the different injury features and risks between the driver and passengers, which is useful in identifying the driver.

Have pedestrian subsystem tests improved passenger car front shape?

Subsystem impactor tests are the main approaches for evaluation of safety performance of vehicle front design for pedestrian protection in legislative regulations. However, the main aspects of vehicle safety for pedestrians are shape and stiffness, and though it is clear that subsystem impact tests encourage lower vehicle front stiffness, it is unclear whether they promote improved vehicle front shapes for pedestrian protection. The purpose of this paper is therefore to investigate the effects of European pedestrian safety regulations on passenger car front shape and pedestrian injury risk using recent German In-Depth Accident Study (GIDAS) pedestrian collision data and numerical simulations. Firstly, a sample of 579 pedestrian collision cases involving 190 different car models between 2000-2015 extracted from the GIDAS was used to compare front-end shapes of passenger cars manufactured before and after the legislative pedestrian safety regulations were introduced in Europe. The focus was on changes in passenger car front shape and differences in pedestrian AIS2+ (Abbreviated Injury Scale at least level 2) leg, pelvis/femur and head injury risk observed in collisions. Multi-body simulations were also used to assess changes in vehicle aggressivity due to the observed changes in vehicle shape. The results show that newer passenger cars tend to have a flatter and wider bumper, higher bonnet leading edge, shorter and steeper bonnet and a shallower windscreen. Both the collision data and the numerical simulations indicate that newer passenger car front bumper designs are significantly safer for pedestrians' legs. However, the results also show that the higher bonnet leading edge in newer passenger cars is poor for pedestrian pelvis/femur protection, even though newer cars show an obviously lower AIS2+ injury risk to younger pedestrians in collisions. Newer cars have a lower AIS2+ head injury risk for pedestrians in collisions, but the numerical analysis indicate that this is not likely due to shape changes in passenger car fronts. Overall, the introduction of pedestrian safety regulations has resulted in reductions in pedestrian injury risk, but further benefits would accrue from tests which promote a lower bonnet leading edge. The influence of vehicle shape on pedestrian head injury risk remains unclear.

Identification of pre-impact conditions of a cyclist involved in a vehicle-bicycle accident using an optimized MADYMO reconstruction combined with motion capture

The aim of the present study was to develop an improved method, using MADYMO multi-body simulation software combined with an optimization method and three-dimensional (3D) motion capture, for identifying the pre-impact conditions of a cyclist (walking or cycling) involved in a vehicle-bicycle accident. First, a 3D motion capture system was used to analyze coupled motions of a volunteer while walking and cycling. The motion capture results were used to define the posture of the human model during walking and cycling simulations. Then, cyclist, bicycle and vehicle models were developed. Pre-impact parameters of the models were treated as unknown design variables. Finally, a multi-objective genetic algorithm, the nondominated sorting genetic algorithm II, was used to find optimal solutions. The objective functions of the walk parameter were significantly lower than cycle parameter; thus, the cyclist was more likely to have been walking with the bicycle than riding the bicycle. In the most closely matched result found, all observed contact points matched and the injury parameters correlated well with the real injuries sustained by the cyclist. Based on the real accident reconstruction, the present study indicates that MADYMO multi-body simulation software, combined with an optimization method and 3D motion capture, can be used to identify the pre-impact conditions of a cyclist involved in a vehicle-bicycle accident.

Numerical Investigation on Head and Brain Injuries Caused by Windshield Impact on Riders Using Electric Self-Balancing Scooters

To investigate head-brain injuries caused by windshield impact on riders using electric self-balancing scooters (ESS). Numerical vehicle ESS crash scenarios are constructed by combining the finite element (FE) vehicle model and multibody scooter/rider models. Impact kinematic postures of the head-windshield contact under various impact conditions are captured. Then, the processes during head-windshield contact are reconstructed using validated FE head/laminated windshield models to assess the severity of brain injury caused by the head-windshield contact. Governing factors, such as vehicle speed, ESS speed, and the initial orientation of ESS rider, have nontrivial influences over the severity of a rider's brain injuries. Results also show positive correlations between vehicle speed and head-windshield impact speeds (linear and angular). Meanwhile, the time of head-windshield contact happens earlier when the vehicle speed is faster. According to the intensive study, windshield-head contact speed (linear and angular), impact location on the windshield, and head collision area are found to be direct factors on ESS riders' brain injuries during an impact. The von Mises stress and shear stress rise when relative contact speed of head-windshield increases. Brain injury indices vary widely when the head impacting the windshield from center to the edge or impacting with different areas.

Comparative analyses of bicyclists and motorcyclists in vehicle collisions focusing on head impact responses

To investigate the differences of the head impact responses between bicyclists and motorcyclists in vehicle collisions. A series of vehicle–bicycle and vehicle–motorcycle lateral impact simulations on four vehicle types at seven vehicle speeds (30, 35, 40, 45, 50, 55 and 60 km/h) and three two-wheeler moving speeds (5, 7.5 and 10 km/h for bicycle, 10, 12.5 and 15 km/h for motorcycle) were established based on PC-Crash software. To further comprehensively explore the differences, additional impact scenes with other initial conditions, such as impact angle (0, π/3, 2π/3 and π) and impact position (left, middle and right part of vehicle front-end), also were supplemented. And then, extensive comparisons were accomplished with regard to average head peak linear acceleration, average head impact speed, average head peak angular acceleration, average head peak angular speed and head injury severity. The results showed there were prominent differences of kinematics and body postures for bicyclists and motorcyclists even under same impact conditions. The variations of bicyclist head impact responses with the changing of impact conditions were a far cry from that of motorcyclists. The average head peak linear acceleration, average head impact speed and average head peak angular acceleration values were higher for motorcyclists than for bicyclists in most cases, while the bicyclists received greater average head peak angular speed values. And the head injuries of motorcyclists worsened faster with increased vehicle speed. The results may provide even deeper understanding of two-wheeler safety and contribute to improve the public health affected by road traffic accidents.

Exploring the mechanisms of vehicle front-end shape on pedestrian head injuries caused by ground impact

In pedestrian-vehicle accidents, pedestrians typically suffer from secondary impact with the ground after the primary contact with vehicles. However, information about the fundamental mechanism of pedestrian head injury from ground impact remains minimal, thereby hindering further improvement in pedestrian safety. This study addresses this issue by using multi-body modeling and computation to investigate the influence of vehicle front-end shape on pedestrian safety. Accordingly, a simulation matrix is constructed to vary bonnet leading-edge height, bonnet length, bonnet angle, and windshield angle. Subsequently, a set of 315 pedestrian-vehicle crash simulations are conducted using the multi-body simulation software MADYMO. Three vehicle velocities, i.e., 20, 30, and 40km/h, are set as the scenarios. Results show that the top governing factor is bonnet leading-edge height. The posture and head injury at the instant of head ground impact vary dramatically with increasing height because of the significant rise of the body bending point and the movement of the collision point. The bonnet angle is the second dominant factor that affects head-ground injury, followed by bonnet length and windshield angle. The results may elucidate one of the critical barriers to understanding head injury caused by ground impact and provide a solid theoretical guideline for considering pedestrian safety in vehicle design.

The influence of passenger car front shape on pedestrian injury risk observed from German in-depth accident data

Quantified relationships between passenger car front shape and pedestrian injury risk derived from accident data are sparse, especially considering the significant recent changes in car front design. The purpose of this paper is therefore to investigate the detailed effects of passenger car front shape on injury risk to a pedestrian's head, thorax, pelvis and leg in the event of a vehicle pedestrian impact. Firstly, an accident sample of 594 pedestrian cases captured during 2000-2015 from the German In-Depth Accident Study (GIDAS) database was employed. Multicollinearity diagnostic statistics were then used to detect multicollinearity between the predictors. Following this, logistic regression was applied to quantify the effects of passenger car front shape on injury risks while controlling for impact speed and pedestrian age. Results indicate that the bumper lower depth (BLD), bumper lower height (BLH), bumper upper height (BUH) and normalised bumper lower/upper height (NBLH/NBUH) are statistically significant for AIS2+ leg injury risk. The normalised bonnet leading edge height (NBLEH) has a statistically significant influence on AIS2+ femur/pelvis injury occurrence. The passenger car front shape did not show statistical significance for AIS3+ thorax and head injuries. The impact speed and pedestrian age are generally significant factors influencing AIS2+ leg and pelvis injuries, and AIS3+ thorax and head injuries. However, when head impacts are fixed on the central windscreen region both pedestrian age and impact speed are not statistically significant for AIS3+ head injury. For quantified effects, when controlling for speed, age and BUH, an average 7% and 6% increase in AIS2+ leg injury odds was observed for every 1cm increase in BLD and BLH respectively; 1cm increase in BUH results in a 7% decrease in AIS2+ leg injury odds when the BLD or BLH are fixed respectively (again controlling for impact speed and pedestrian age); the average AIS2+ femur/pelvis injury odds increase by 74% for a 10% increase in NBLEH. These findings suggest that passenger car bumpers should support the lower leg with a low and flat lower bumper and even contact up to the femur area with a high upper bumper which extends above the knee to protect the pedestrian's leg. A low passenger car bonnet leading edge helps to reduce femur/pelvis injury risk. The passenger car front shape parameters are less influential than impact speed and pedestrian age for pedestrian injury risk.

Safer passenger car front shapes for pedestrians: A computational approach to reduce overall pedestrian injury risk in realistic impact scenarios

Vehicle front shape has a significant influence on pedestrian injuries and the optimal design for overall pedestrian protection remains an elusive goal, especially considering the variability of vehicle-to-pedestrian accident scenarios. Therefore this study aims to develop and evaluate an efficient framework for vehicle front shape optimization for pedestrian protection accounting for the broad range of real world impact scenarios and their distributions in recent accident data. Firstly, a framework for vehicle front shape optimization for pedestrian protection was developed based on coupling of multi-body simulations and a genetic algorithm. This framework was then applied for optimizing passenger car front shape for pedestrian protection, and its predictions were evaluated using accident data and kinematic analyses. The results indicate that the optimization shows a good convergence and predictions of the optimization framework are corroborated when compared to the available accident data, and the optimization framework can distinguish 'good' and 'poor' vehicle front shapes for pedestrian safety. Thus, it is feasible and reliable to use the optimization framework for vehicle front shape optimization for reducing overall pedestrian injury risk. The results also show the importance of considering the broad range of impact scenarios in vehicle front shape optimization. A safe passenger car for overall pedestrian protection should have a wide and flat bumper (covering pedestrians' legs from the lower leg up to the shaft of the upper leg with generally even contacts), a bonnet leading edge height around 750mm, a short bonnet (<800mm) with a shallow or steep angle (either >17° or <12°) and a shallow windscreen (≤30°). Sensitivity studies based on simulations at the population level indicate that the demands for a safe passenger car front shape for head and leg protection are generally consistent, but partially conflict with pelvis protection. In particular, both head and leg injury risk increase with increasing bumper lower height and depth, and decrease with increasing bonnet leading edge height, while pelvis injury risk increases with increasing bonnet leading edge height. However, the effects of bonnet leading edge height and windscreen design on head injury risk are complex and require further analysis.

Exploration of Pedestrian Head Injuries-Collision Parameter Relationships through a Combination of Retrospective Analysis and Finite Element Method

There are a very limited number of reports concerning the relationship between pedestrian head injuries and collision parameters through a combination of statistical analysis methods and finite element method (FEM). This study aims to explore the characteristics of pedestrian head injuries in car–pedestrian collisions at different parameters by using the two means above. A retrospective analysis of pedestrian head injuries was performed based on detailed investigation data of 61 car–pedestrian collision cases. The head damage assessment parameters (head injury criterion (HIC), peak stress on the skull, maximal principal strain for the brain) in car–pedestrian simulation experiments with four contact angles and three impact velocities were obtained by FEM. The characteristics of the pedestrian head injuries were discussed by comparing and analyzing the statistical analysis results and finite element analysis results. The statistical analysis results demonstrated a significant difference in skull fractures, contusion and laceration of brain and head injuries on the abbreviated injury scale (AIS)3+ was found at different velocities (p < 0.05) and angles (p < 0.05). The simulation results showed that, in pedestrian head-to-hood impacts, the values of head damage assessment parameters increased with impact velocities. At the same velocity, these values from the impact on the pedestrian’s back were successively greater than on the front or the side. Furthermore, head injury reconstruction and prediction results of two selected cases were consistent with the real injuries. Overall, it was further spelled out that, for shorter stature pedestrians, increased head impact velocity results in greater head injury severity in car–pedestrian collision, especially in pedestrian head-to-hood impacts. Under a back impact, the head has also been found to be at greater damage risk for shorter stature pedestrians, which may have implications on automotive design and pedestrian protection research if prevention and treatment of these injuries is to be prioritized over head injuries under a front or side impact.

A virtual test system representing the distribution of pedestrian impact configurations for future vehicle front-end optimization

OBJECTIVES

The purpose of this study is to define a computationally efficient virtual test system (VTS) to assess the aggressivity of vehicle front-end designs to pedestrians considering the distribution of pedestrian impact configurations for future vehicle front-end optimization. The VTS should represent real-world impact configurations in terms of the distribution of vehicle impact speeds, pedestrian walking speeds, pedestrian gait, and pedestrian height. The distribution of injuries as a function of body region, vehicle impact speed, and pedestrian size produced using this VTS should match the distribution of injuries observed in the accident data. The VTS should have the predictive ability to distinguish the aggressivity of different vehicle front-end designs to pedestrians.

METHODS

The proposed VTS includes 2 parts: a simulation test sample (STS) and an injury weighting system (IWS). The STS was defined based on MADYMO multibody vehicle to pedestrian impact simulations accounting for the range of vehicle impact speeds, pedestrian heights, pedestrian gait, and walking speed to represent real world impact configurations using the Pedestrian Crash Data Study (PCDS) and anthropometric data. In total 1,300 impact configurations were accounted for in the STS. Three vehicle shapes were then tested using the STS. The IWS was developed to weight the predicted injuries in the STS using the estimated proportion of each impact configuration in the PCDS accident data. A weighted injury number (WIN) was defined as the resulting output of the VTS. The WIN is the weighted number of average Abbreviated Injury Scale (AIS) 2+ injuries recorded per impact simulation in the STS. Then the predictive capability of the VTS was evaluated by comparing the distributions of AIS 2+ injuries to different pedestrian body regions and heights, as well as vehicle types and impact speeds, with that from the PCDS database. Further, a parametric analysis was performed with the VTS to assess the sensitivity of the injury predictions to changes in vehicle shape (type) and stiffness to establish the potential for using the VTS for future vehicle front-end optimization.

RESULTS

An STS of 1,300 multibody simulations and an IWS based on the distribution of impact speed, pedestrian height, gait stance, and walking speed is broadly capable of predicting the distribution of pedestrian injuries observed in the PCDS database when the same vehicle type distribution as the accident data is employed. The sensitivity study shows significant variations in the WIN when either vehicle type or stiffness is altered.

CONCLUSIONS

Injury predictions derived from the VTS give a good representation of the distribution of injuries observed in the PCDS and distinguishing ability on the aggressivity of vehicle front-end designs to pedestrians. The VTS can be considered as an effective approach for assessing pedestrian safety performance of vehicle front-end designs at the generalized level. However, the absolute injury number is substantially underpredicted by the VTS, and this needs further development.

Simulative investigation on head injuries of electric self-balancing scooter riders subject to ground impact

The safety performance of an electric self-balancing scooter (ESS) has recently become a main concern in preventing its further wide application as a major candidate for green transportation. Scooter riders may suffer severe brain injuries in possible vehicle crash accidents not only from contact with a windshield or bonnet but also from secondary contact with the ground. In this paper, virtual vehicle-ESS crash scenarios combined with finite element (FE) car models and multi-body scooter/human models are set up. Post-impact kinematic gestures of scooter riders under various contact conditions, such as different vehicle impact speeds, ESS moving speeds, impact angles or positions, and different human sizes, are classified and analyzed. Furthermore, head-ground impact processes are reconstructed using validated FE head models, and important parameters of contusion and laceration (e.g., coup or contrecoup pressures and Von Mises stress and the maximum shear stress) are extracted and analyzed to assess the severity of regional contusion from head-ground contact. Results show that the brain injury risk increases with vehicle speeds and ESS moving speeds and may provide fundamental knowledge to popularize the use of a helmet and the vehicle-fitted safety systems, and lay a strong foundation for the reconstruction of ESS-involved accidents. There is scope to improve safety for the use of ESS in public roads according to the analysis and conclusions.

Are electric self-balancing scooters safe in vehicle crash accidents?

With the pressing demand of environmentally friendly personal transportation vehicles, mobility scooters become more and more popular for the short-distance transportation. Similar to pedestrians and bicyclists, scooter riders are vulnerable road users and are expected to receive severe injuries during traffic accidents. In this research, a MADYMO model of vehicle-scooter crash scenarios is numerically set up. The model of the vehicle with the scenario is validated in pedestrian-vehicle accident investigation with previous literatures in terms of throwing distance and HIC15 value. HIC15 values gained at systematic parametric studies. Injury information from various vehicle crashing speeds (i.e. from 10m/s to 24m/s), angles (i.e. from 0 to 360°), scooter's speeds (i.e. from 0m/s to 4m/s), contact positions (i.e. left, middle and right bumper positions) are extracted, analyzed and then compared with those from widely studied pedestrian-vehicle and bicycle-vehicle accidents. Results show that the ESS provides better impact protection for the riders. Riding ESS would not increase the risk higher than walking at the same impact conditions in terms of head injury. The responsible reasons should be the smaller friction coefficient between the wheel-road than the heel-road interactions, different body gestures leading to different contact positions, forces and timing. Results may shed lights upon the future research of mobility scooter safety analysis and also the safety design guidance for the scooters.

The influence of gait stance on pedestrian lower limb injury risk

The effect of pedestrian gait on lower limb kinematics and injuries has not been analyzed. The purpose of this paper was therefore to investigate the effect of pedestrian gait on kinematics and injury risk to the lower limbs using the Total Human Model for Safety adult male pedestrian model together with FE models of vehicle front structures. The modeling results indicate that the tibia and femur cortical bone von-Mises stress and the lateral knee bending angle of an adult pedestrian are strongly dependent on the gait stance when struck by both a sedan car and an SUV at 40km/h. The gait analysis shows that generally the leg of an adult pedestrian has lower injury risk when the knee is flexed and linear regressions show high negative correlation between knee flexion angle during impact and knee lateral bending angle and also high negative correlation between lower leg axial rotation during impact and knee lateral bending angle. Furthermore, in some gait stances a self-contact between the legs occurs, and the peak bones stresses and knee shearing displacement in the leg are then increased. Assessment of pedestrian lower limb injury should take account of these gait stance effects.

The influence of vehicle front-end design on pedestrian ground impact

Accident data have shown that in pedestrian accidents with high-fronted vehicles (SUVs and vans) the risk of pedestrian head injuries from the contact with the ground is higher than with low-fronted vehicles (passenger cars). However, the reasons for this remain poorly understood. This paper addresses this question using multibody modelling to investigate the influence of vehicle front height and shape in pedestrian accidents on the mechanism of impact with the ground and on head ground impact speed. To this end, a set of 648 pedestrian/vehicle crash simulations was carried out using the MADYMO multibody simulation software. Impacts were simulated with six vehicle types at three impact speeds (20, 30, 40km/h) and three pedestrian types (50th % male, 5th % female, and 6-year-old child) at six different initial stance configurations, stationary and walking at 1.4m/s. Six different ground impact mechanisms, distinguished from each other by the manner in which the pedestrian impacted the ground, were identified. These configurations have statistically distinct and considerably different distributions of head-ground impact speeds. Pedestrian initial stance configuration (gait and walking speed) introduced a high variability to the head-ground impact speed. Nonetheless, the head-ground impact speed varied significantly between the different ground impact mechanisms identified and the distribution of impact mechanisms was strongly associated with vehicle type. In general, impact mechanisms for adults resulting in a head-first contact with the ground were more severe with high fronted vehicles compared to low fronted vehicles, though there is a speed dependency to these findings. With high fronted vehicles (SUVs and vans) the pedestrian was mainly pushed forward and for children this resulted in high head ground contact speeds.

The Influence of Neck Muscle Tonus and Posture on Brain Tissue Strain in Pedestrian Head Impacts

Pedestrians are one of the least protected groups in urban traffic and frequently suffer fatal head injuries. An important boundary condition for the head is the cervical spine, and it has previously been demonstrated that neck muscle activation is important for head kinematics during inertial loading. It has also been shown in a recent numerical study that a tensed neck musculature also has some influence on head kinematics during a pedestrian impact situation. The aim of this study was to analyze the influence on head kinematics and injury metrics during the isolated time of head impact by comparing a pedestrian with relaxed neck and a pedestrian with increased tonus. The human body Finite Element model THUMS Version 1.4 was connected to head and neck models developed at KTH and used in pedestrian-to-vehicle impact simulations with a generalized hood, so that the head would impact a surface with an identical impact response in all simulations. In order to isolate the influence of muscle tonus, the model was activated shortly before head impact so the head would have the same initial position prior to impact among different tonus. A symmetric and asymmetric muscle activation scheme that used high level of activation was used in order to create two extremes to investigate. It was found that for the muscle tones used in this study, the influence on the strain in the brain was very minor, in general about 1-14% change. A relatively large increase was observed in a secondary peak in maximum strains in only one of the simulated cases.

A computational simulation study of the influence of helmet wearing on head injury risk in adult cyclists

Evidence for the effectiveness of cycle helmets has relied either on simplified experiments or complex statistical analysis of patient cohorts or populations. This study directly assesses the effectiveness of cycle helmets over a range of accident scenarios, from basic loss of control to vehicle impact, using computational modelling. Simulations were performed using dynamics modelling software (MADYMO) and models of a 50% Hybrid III dummy, a hybrid cross bicycle and a car. Loss of control was simulated by a sudden turn of the handlebars and striking a curb, side and rear-on impacts by a car were also simulated. Simulations were run over a representative range of cycle speeds (2.0-14.0 m s(-1)) and vehicle speeds (4.5-17.9 m s(-1)). Bicycle helmets were found to be effective in reducing the severity of head injuries sustained in common accidents. They reduced the risk of an AIS>3 injury, in cases with head impacts, by an average of 40%. In accidents that would cause up to moderate (AIS=2) injuries to a non-helmeted rider, helmets eliminated the risk of injury. Helmets were also found to be effective in preventing fatal head injuries in some instances. The effectiveness of helmets was demonstrated over the entire range of cycle speeds studied, up to and including 14 m s(-1). There was no evidence that helmet wearing increased the risk of neck injury, indeed helmets were found to be protective of neck injuries in many cases. Similarly, helmets were found to offer an increase in protection even when an increase in cycle speed due to risk compensation was taken into consideration.

MADYMO simulation of children in cycle accidents: a novel approach in risk assessment

Head injuries are a significant cause of death and injury to child cyclists both on and off the road. Current evaluations of the effectiveness of cycle helmets rely on simplified mechanical testing or the analysis of aggregated accident statistics. This paper presents a direct evaluation of helmet efficacy by using computational modelling to simulate a range of realistic accident scenarios, including loss of control, collision with static objects and vehicle impact. A 6-year-old cyclist was modelled (as a Hybrid III 6-year-old dummy), in addition to a typical children's bicycle and a vehicle using the MADYMO dynamics software package. Simulations were performed using ranges of cyclist position, cycle speed and vehicle speed with and without a helmet that meets current standards. Wearing a cycle helmet was found to reduce the probability of head injuries, reducing the average probability of fatality over the scenarios studied from 40% to 0.3%. Similarly, helmet wearing reduced the probability of neck injuries (average probability of fatality reduced from 11% to 1%). There was no evidence that helmet wearing increased the severity of brain or neck injuries caused by rotational accelerations; in fact these were slightly reduced. Similarly, there was no evidence that increased cycling speed, such as might result from helmet related risk compensation, increased the probability of head injury.

An investigation on the head injuries of adult pedestrians by passenger cars in China

OBJECTIVE

To investigate the relative likelihood of pedestrian head injuries based on person, vehicular, and environmental factors in China.

METHODS

A team was established to collect passenger car-pedestrian accident cases occurring between 2006 and 2011 in Beijing, Shanxi Province, and Chongqing, China. Some key variables for person-, vehicle-, and environment-related factors on head injuries were analyzed using multivariate logistic regression analysis to determine relative risk/likelihood. Pedestrians were classified according to injury outcome and age. Pedestrian head injuries were scored using the Abbreviated Injury Scale (AIS).

RESULTS

A total of 285 vehicle-pedestrian crashes were collected and analyzed: 30 in Beijing, 20 in Shanxi Province, and 235 in Chongqing. The distribution in age and road type by study location differed. The injury outcome, head injury severity, and head contact site were different among 4 age groups. The variables including head contact site and impact speed were the common determinants for head injury severity. A higher pedestrian fatality risk was associated with age over 46, impact speeds over 40 km/h, and higher likelihoods of the victim's head striking the windscreen frame/A pillar and of the victim sustaining a head injury. Similarly, a higher risk of head injury was associated with being female, age over 60, impact speeds over 40 km/h, and a likelihood of the victim's head striking the vehicle rather than the ground. Impact speeds of over 40 km/h and head contact site on windscreen frame/A pillar retained a strong association with severe head injury (AIS 5-6) rate.

CONCLUSIONS

Pedestrian age, vehicle impact speed, and head contact site were common pertinent factors for the risk of pedestrian head injury and the risk of death. Further studies would be valuable to fully characterize vehicle-pedestrian crashes in China and to develop targeted injury prevention strategies based on surveillance results.

Repositioning the knee joint in human body FE models using a graphics-based technique

OBJECTIVE

Human body finite element models (FE-HBMs) are available in standard occupant or pedestrian postures. There is a need to have FE-HBMs in the same posture as a crash victim or to be configured in varying postures. Developing FE models for all possible positions is not practically viable. The current work aims at obtaining a posture-specific human lower extremity model by reconfiguring an existing one.

METHODOLOGY

A graphics-based technique was developed to reposition the lower extremity of an FE-HBM by specifying the flexion-extension angle. Elements of the model were segregated into rigid (bones) and deformable components (soft tissues). The bones were rotated about the flexion-extension axis followed by rotation about the longitudinal axis to capture the twisting of the tibia. The desired knee joint movement was thus achieved. Geometric heuristics were then used to reposition the skin. A mapping defined over the space between bones and the skin was used to regenerate the soft tissues. Mesh smoothing was then done to augment mesh quality.

RESULTS

The developed method permits control over the kinematics of the joint and maintains the initial mesh quality of the model. For some critical areas (in the joint vicinity) where element distortion is large, mesh smoothing is done to improve mesh quality.

CONCLUSIONS

A method to reposition the knee joint of a human body FE model was developed. Repositions of a model from 9 degrees of flexion to 90 degrees of flexion in just a few seconds without subjective interventions was demonstrated. Because the mesh quality of the repositioned model was maintained to a predefined level (typically to the level of a well-made model in the initial configuration), the model was suitable for subsequent simulations.