A proof of concept model to calculate white and grey matter AIS injuries in pedestrian collisions.

In the real world, the severity of traumatic injuries is measured using the Abbreviated Injury Scale (AIS) and is often estimated, in finite element human computer models, with the maximum principal strains (MPS) tensor. MPS can predict when a serious injury is reached, but cannot provide any AIS measures lower and higher from this. To overcome these limitations, a new organ trauma model (OTM2), capable of calculating the threat to life of any organ injured, is proposed. The OTM2 model uses a power method, namely peak virtual power, and defines brain white and grey matters trauma responses. It includes human age effect (volume and stiffness), localised impact contact stiffness and provides injury severity adjustments for haemorrhaging. The focus, in this case, is on real-world pedestrian brain injuries. OTM2 model was tested against three real-life pedestrian accidents and has proven to reasonably predict the post mortem (PM) outcome. Its AIS predictions are closer to the real-world injury severity than the standard maximum principal strain (MPS) methods currently used. This proof of concept suggests that OTM2 has the potential to improve forensic predictions as well as contribute to the improvement in vehicle safety design through the ability to measure injury severity. This study concludes that future advances in trauma computing would require the development of a brain model that could predict haemorrhaging.

Centre of gravity of motor vehicles.

In vehicular accident reconstruction, a number of parameters need to be estimated, as commonly no specific measurement data or convenient measurement methods are available. One of these parameters is the position of a car's centre of gravity. Depending on the impact configuration, the centre of gravity may have a significant influence on the reconstruction result. A number of regression models and rules of thumb have already been developed in the past to calculate the position of the centre of gravity. The further automotive vehicle development in recent years has led to different vehicle architectures with larger masses. This study therefore deals with developing and testing a new regression model for vehicles, distinguishing between conventional and electric drives. That is based on the analysis of 147 rollover stability measurements of road vehicles from the years 2016-2022. The model developed from these tests for the centre of gravity height shows a good fit with the measurement data and only requires knowledge of the roof height.

Influence of Blind Spot Assistance Systems in Heavy Commercial Vehicles on Accident Reconstruction.

Accidents between right-turning commercial vehicles and crossing vulnerable road users (VRUs) in urban environments often lead to serious or fatal injuries and therefore play a significant role in forensic accident analysis. To reduce the risk of accidents, blind spot assistance systems have been installed in commercial vehicles for several years, among other things, to detect VRUs and warn the driver in time. However, since such systems cannot reliably prevent all turning accidents, an investigation by experts must clarify how the accident occurred and to what extent the blind spot assistance system influenced the course of the accident. The occurrence of the acoustic warning message can be defined as an objective reaction prompt for the driver, so that the blind spot assistance system can significantly influence the avoidability assessment. In order to be able to integrate the system into forensic accident analysis, a precise knowledge of how the system works and its limitations is required. For this purpose, tests with different systems and accident constellations were conducted and evaluated. It was found that the type of sensor used for the assistance systems has a great influence on the system's performance. The lateral distance between the right side of the commercial vehicle and the VRU, as well as obstacles between them, along with the speed difference can have great influence on the reliability of the assistance system. Depending on the concrete time of the system's warning signal, the accident can be avoided or not by the driver when reacting to this signal.

Prediction of skull fractures in blunt force head traumas using finite element head models.

Traumatic head injuries remain a leading cause of death and disability worldwide. Although skull fractures are one of the most common head injuries, the fundamental mechanics of cranial bone and its impact tolerance are still uncertain. In the present study, a strain-rate-dependent material model for cranial bone has been proposed and implemented in subject-specific Finite Element (FE) head models in order to predict skull fractures in five real-world fall accidents. The subject-specific head models were developed following an established image-registration-based personalization pipeline. Head impact boundary conditions were derived from accident reconstructions using personalized human body models. The simulated fracture lines were compared to those visible in post-mortem CT scans of each subject. In result, the FE models did predict the actual occurrence and extent of skull fractures in all cases. In at least four out of five cases, predicted fracture patterns were comparable to ones from CT scans and autopsy reports. The tensile material model, which was tuned to represent rate-dependent tensile data of cortical skull bone from literature, was able to capture observed linear fractures in blunt indentation loading of a skullcap specimen. The FE model showed to be sensitive to modeling parameters, in particular to the constitutive parameters of the cortical tables. Nevertheless, this study provides a currently lacking strain-rate dependent material model of cranial bone that has the capacity to accurately predict linear fracture patterns. For the first time, a procedure to reconstruct occurrences of skull fractures using computational engineering techniques, capturing the all-in-all fracture initiation, propagation and final pattern, is presented.

Reconstruction of a Car-Running Pedestrian Accident Based on a Humanoid Robot Method.

Due to the characteristics of multibody (MB) and finite element (FE) digital human body models (HBMs), the reconstruction of running pedestrians (RPs) remains a major challenge in traffic accidents (TAs) and new innovative methods are needed. This study presents a novel approach for reconstructing moving pedestrian TAs based on a humanoid robot method to improve the accuracy of analyzing dynamic vehicle-pedestrian collision accidents. Firstly, we applied the theory of humanoid robots to the corresponding joints and centroids of the TNO HBM and implemented the pedestrian running process. Secondly, we used rigid-flexible coupling HBMs to build pedestrians, which can not only simulate running but also analyze human injuries. Then, we validated the feasibility of the RP reconstruction method by comparing the simulated dynamics with the pedestrian in the accident. Next, we extracted the velocity and posture of the pedestrian at the moment of collision and further validated the modeling method through a comparison of human injuries and forensic autopsy results. Finally, by comparing two other cases, we can conclude that there are relative errors in both the pedestrian injury results and the rest position. This comparative analysis is helpful for understanding the differences in injury characteristics between the running pedestrian and the other two cases in TAs.

Psychological Autopsy in Small Penis Syndrome: Determining the Manner and Circumstance of Death Following a Vehicular Accident.

Road traffic accidents and related deaths are on the rise, especially in developing countries. Even though uncommon and probably under-recognized, predisposing psychiatric states may be contributory, posing the question of whether these could be avoided. Psychological autopsy, despite not being performed routinely, might play a pivotal role in such instances, in reconstructing events leading to the catastrophe and determining the role played by the parties involved. The legal implications, such as the exoneration of the wrongly accused, might be substantial. This case report presents a death of a middle-aged South Asian male with strong history and evidence of small penis anxiety following a direct collision in a road traffic accident. It highlights the careful evaluation of the clinical history of the deceased by a psychological autopsy and reiterates the importance of the former in suspected cases.

Assessment of child safety on bicycles in baby carriers - The importance of evaluating both head and neck injuries.

INTRODUCTION: The paper addresses an important accident type that involves children in bicycle seats - the bicycle fall over. It is a significant and common accident type and many parents have been reported to experience this type of "close call." The fall over occurs at low velocities and even while a bicycle is standing still, and may result from a split-second lack of attention on behalf of the accompanying adult (e.g. while loading groceries, i.e. while not being exposed to traffic per se). Moreover, irrespective of the low velocities involved, the trauma that may result to the head of the child is considerable and may be life-threatening, as shown in the study. METHOD: The paper presents two methods to address this accident scenario in a quantitative way: in-situ accelerometer-based measurement and numerical modeling approaches. It is shown that the methods produce consistent results under the prerequisites of the study. They are therefore promising methods to be used in the study of this type of accident. RESULTS: The importanance of the protective role of a child helmet is without discussion in everyday traffic.However, this study draws attention to one particular effect observed in this accident type: that the geometry of the helmet may at times expose the child's head to considerably larger forces, by having contact with the ground. The study also highlights the importance of neck bending injuries during bicycle fall over, which are often neglected in the safety assessment - not only for children in bicycle seats. The study concludes that considering only head acceleration may lead to biased conclusions about using helmets as protective devices.

Understanding the new trends in pedestrian injury distribution and mechanism through data linkage and modeling.

The objectives of this study were to 1) collect and analyze recent pedestrian crash cases for better understanding of the pedestrian injury distribution and mechanism, 2) use computational simulations to reconstruct pedestrian cases and estimate potential benefit of pedestrian automatic emergency braking (PedAEB) in reducing pedestrian injury risks, and 3) estimate how future pedestrian crash distribution might influence priorities for pedestrian protection. Analyses of national crash-injury dataset showed that the overall number of pedestrians in crashes as well as the serious and fatal pedestrian injuries in the U.S. have been increasing in recent years. Striking vehicle type has changed (i.e., decreased proportion of passenger cars and increase of SUVs and pickup trucks) from 20 years ago mirroring changes in the fleet distribution of vehicle sales. A total of 432 pedestrian injury cases were generated by linking the Michigan trauma data and police-reported crash data from 2013 to 2018. Among the linked cases, pickup trucks and SUVs were involved in crashes with more injuries across body regions. Notably, AIS 3+ chest injuries occur at almost the same rate as lower extremity injuries. A method, combining MADYMO simulations (n = 3,500), response surface model, and data mining, was developed to reconstruct 25 linked pedestrian crash cases to estimate the effectiveness of PedAEB. Based on national field data and MADYMO simulations, PedAEB was estimated to be effective in reducing the risk of head and lower extremity injuries but is relatively less effective in reducing the risk of chest injuries. The increased proportions of SUVs and pickup trucks in the vehicle fleet and the higher penetration of PedAEB may highlight the importance of future research into chest injury risk for pedestrian protection.

Incomplete decapitation with exenteration of the brain in a motorcyclist run over by a semitrailer.

Although decapitation is a well-known traumatic mechanism in road traffic deaths, incomplete decapitation of a motorcyclist with exenteration of the brain has not yet been reported in the forensic literature in a victim run over by a vehicle. This paper deals with an autopsy case of a 69-year-old motorcyclist, who had been run over by a semitrailer, as a result of which flattening of the head with extrusion of the brain and incomplete decapitation occurred at the level of the fourth cervical vertebra. This constellation allows to define a special mechanism of accident-related decapitation. Moreover, the case underlines the importance of a multidisciplinary approach for the reconstruction of the accident as well as for the assessment of its judicial consequences. On the suspicion of a hit-and-run accident, simulation tests were performed by technical experts. These tests revealed that the motorcycle may not have been conspicuous for the truck driver prior to and during the accident. Consequently, the charge of manslaughter and failure to render assistance against the truck driver was dropped.

In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation.

Traumatic brain injury (TBI) is a prevalent injury among cyclists experiencing head collisions. In legal cases, reliable brain injury evaluation can be difficult and controversial as mild injuries cannot be diagnosed with conventional brain imaging methods. In such cases, accident reconstruction may be used to predict the risk of TBI. However, lack of collision details can render accident reconstruction nearly impossible. Here, we introduce a reconstruction method to evaluate the brain injury in a bicycle-vehicle collision using the crash helmet alone. Following a thorough inspection of the cyclist's helmet, we identified a severe impact, a moderate impact and several scrapes, which helped us to determine the impact conditions. We used our helmet test rig and intact helmets identical to the cyclist's helmet to replicate the damage seen on the cyclist's helmet involved in the real-world collision. We performed both linear and oblique impacts, measured the translational and rotational kinematics of the head and predicted the strain and the strain rate across the brain using a computational head model. Our results proved the hypothesis that the cyclist sustained a severe impact followed by a moderate impact on the road surface. The estimated head accelerations and velocity (167 g, 40.7 rad/s and 13.2 krad/s2) and the brain strain and strain rate (0.541 and 415/s) confirmed that the severe impact was large enough to produce mild to moderate TBI. The method introduced in this study can guide future accident reconstructions, allowing for the evaluation of TBI using the crash helmet only.

Effect of different helmets against ground impact based on the in-depth reconstruction of electric two-wheeler accidents.

Skull fracture and brain injury are frequent head injuries in electric two-wheeler (ETW) accidents, and the type of helmet and impact conditions affect the effectiveness of the helmet in protecting the rider's head. The purpose of this study was to conduct in-depth reconstructions of rider's head-to-ground impacts in ten ETW accidents by using a multi-body system combined with a finite element approach and to evaluate the effect of two typical full-face helmets (FFH) and one half-coverage helmet (HCH) through head accelerations and intracranial biomechanics injury metrics in ground impacts. The results showed that all three helmets reduced the risk of skull fracture in most cases, however, FFH performed better due to its wider protection area. In addition, three helmets showed varying degrees of overall reduction in measuring all indicators of brain injury. Although the effectiveness of the helmets on angular acceleration was largely influenced by the angle and location of impact, it was certain that wearing an FFH was more likely to reduce rotational head movements than an HCH, and that the FFH also offered the better advantage in reducing diffuse axonal injury (DAI) risk due to its better resistance to ejection in a crash.

Uncertainty analysis of vehicle-pedestrian accident reconstruction based on unscented transformation.

In order to investigate the sensitivity of parameters and analyze the uncertainty of reconstructed results in traffic accident, the impact of correlations between parameters on accident reconstruction results was taken into account using uncertainty analysis. Based on unscented transformation (UT), a parameter sensitivity analysis method and an efficient uncertainty analysis method in accident reconstruction were proposed. Sensitivity analysis was performed through the sigma point sets generated by the UT method. A first-order response surface model was constructed to analyze the sensitivity of accident reconstruction parameters combined with regression analysis, which is more flexible and controllable than the general experimental design. For the uncertainty analysis of the reconstructed results, the other methods have been used to demonstrate the validity of the proposed method, including the first second-order method of moments (FOSM), the uncertainty theory, and the Monte Carlo (MC) methods, through analyzing the numerical and real-world cases. The results show that the presented method has high accuracy, significantly reduces the computational burden, and does not depend on the distribution type of variables. When considering the effect of the correlation between parameters of the vehicle-pedestrian crash on accident reconstruction results, the results show that the correlation coefficient between random variables had a much more significant impact on the standard deviation of vehicle speed than on the mean value of vehicle speed. Regardless of negative or positive correlations, the relative error of standard deviation of vehicle speed increased continuously as the correlation increased, reaching 52%. The proposed method is effective and reliable for vehicle collision accident reconstruction under uncertainty and correlation, which can provide more comprehensive information in accident reconstruction.

Stabbed by motorcycle? Reconstruction of an unusual traffic accident.

The reconstruction of traffic accidents involving powered two-wheelers (PTWs) frequently proves to be a challenging task. A case in which a fatal head-on crash of a PTW with a small truck where only minor vehicles damage was observed but resulted in isolated fatal chest trauma is discussed here. External examination of the corpse revealed two lacerations on the back, at the first glance implying sharp trauma. Based on the accident traces, the technical expert assumed an emergency break of the PTW rider resulting in a rotation of the PTW in terms of a wheelie on the front wheel. The first contact between the PTW rider and the tail end of the small truck probably occurred with the upper side of the helmet, and then, the back handle of the PTW caused the stab-like injuries followed by compression of the rider between the small truck or asphalt and the PTW. Based on the few accident traces available, neither a reconstruction of the pre-impact velocity nor a detailed reconstruction of the PTW rider kinematics was possible. However, using an interdisciplinary approach, the principal collision position as well as the injury mechanisms could be reconstructed.

Determination of vehicle speed from recorded video using the open-source software Kinovea.

Video devices of different kind often record traffic accidents, including vehicle-pedestrian collisions and hit-and-run accidents. In these cases, the vehicle speed is valuable information because it can assist the investigators in an accident reconstruction. This paper examines the use of Kinovea, an open-source video annotation tool designed for sport analysis, to estimate vehicle speed in forensic videos. Kinovea does not require a complex methodology, and it can be used to make the calculation easily. A series of vehicle driving experiments using an appropriately calibrated speed radar system (so called Scout Speed) were carried out, and measurements were compared with the estimated speed. In controlled conditions, the comparison of Scout reference speed and calculated average vehicle speed by means of Kinovea found an average difference of 0.43 km/h, with a margin of error of ±0.64 km/h. In addition, further preliminary tests were carried out to check the reliability of the measurements under lower resolution conditions. Also, in these cases the calculations were in line with the ground truth. Therefore, in the tested conditions, Kinovea demonstrated to be an easy and reliable tool available for forensic video examiners. Further tests need to be conducted in order to address the applicability of the measurement technique with true CCTV/surveillance video recordings.

Accurate Reconstruction of Traffic Accident Based on Multiple Optimization Algorithms and Evaluation of Craniocerebral Injury Risk / 医用生物力学

Objective To investigate the effect of different optimization algorithms on accurate reconstruction of traffic accidents. Methods Non-dominated sorting genetic algorithm-II ( NSGA-II), neighborhood cultivation genetic algorithm (NCGA) and multi-objective particle swarm optimization (MOPSO) were used to optimize the multi-rigid body dynamic reconstruction of a real case. The effects of different optimization algorithms on convergence speed and optimal approximate solution were studied. The optimal initial impact parameters were simulated as boundary conditions of finite element method, and the simulated results were compared with the actual injuries. Results NCGA had a faster convergence speed and a better result in optimization process. The kinematic response of pedestrian vehicle collision reconstructed by the optimal approximate solution was consistent with the surveillance video. The prediction of craniocerebral injury was basically consistent with the cadaver examination. Conclusions The combination of optimization algorithm, rigid multibody and finite element method can complete the accurate reconstruction of traffic accidents and reduce the influence of human factors.

Investigation on the Modeling and Reconstruction of Head Injury Accident Using ABAQUS/Explicit.

A process of modeling and reconstructing human head injuries involved in traffic crashes based on ABAQUS/Explicit is presented in this paper. A high-fidelity finite element (FE) model previously developed by the authors is employed to simulate a real accident case that led to head injury. The most probable head impact position informed by CT images is used for the FE modeling and simulation since the head impact position is critical for accident reconstruction and future analysis of accidents that involve human head injuries. Critical von Mises stress on the skull surface of the head model is chosen as the evaluation criterion for the head injury and FE simulations on 60 cases with various human head-concrete ground impact conditions (impact speeds and angles) were run to obtain those stress values. The FE simulation results are compared with the CT images to determine the minimum speed that will cause skull fracture and the corresponding contact angle at that speed. Our study shows that the minimum speed that would cause skull fracture is 3.5 m/s when the contact angle between the occipital position of the injured head and the ground is about 30°. Effects of the impact speed and the contact angle on the maximum von Mises stress of the head model are revealed from the simulations. The method presented in this paper will help forensic pathologists to examine the head impact injuries and find out the real reasons that lead to those injuries.

Does Vehicle-2-X Radio Transmission Technology Need to Be Considered within Accident Analysis in the Future?

In this analysis, Cooperative Intelligent Transportation System relevant scenarios are created to investigate the need to differentiate Vehicle-to-X transmission technologies on behalf of accident analysis. For each scenario, the distances between the vehicles are calculated 5 s before the crash. Studies on the difference between Dedicated Short-Range Communication (IEEE 802.11p) and Cellular Vehicle-to-X communication (LTE-V2C PC5 Mode 4) are then used to assess whether both technologies have a reliable connection over the relevant distance. If this is the case, the transmission technology is of secondary importance for future investigations on Vehicle-to-X communication in combination with accident analysis. The results show that studies on freeways and rural roads can be carried out independently of the transmission technology and other boundary conditions (speed, traffic density, non-line of sight/line of sight). The situation is different for studies in urban areas, where both technologies may not have a sufficiently reliable connection range depending on the traffic density.

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.

Optimization of the driver's seat belt and injury biomechanical analysis in real-world minivan small offset impact accident scenarios.

To minimize injuries and protect the safety of the driver in minivan small offset collisions, an optimized pre-tensioned force-limiting seat belt was proposed herein. An accident with detailed information, such as medical reports, vehicle inspection reports, and accident scene photographs, was reconstructed using HyperMesh software. The effectiveness of both the accident model and the pre-tensioned force-limiting seat belt was evaluated. To obtain the optimal seat belt parameters for driver protection, first, force-limiting A, pre-tensioned force B, and pre-tensioned time C factors were selected in designing an orthogonal test with different factor levels. The influence laws of each factor on the injury biomechanical characteristics of the driver were analyzed via the direct analysis method. Moreover, each kind of critical injury value of the human body was synthesized, and the radial basis function surrogate model was constructed. The three seat belt parameters were optimized using the NSGA-II multi-objective genetic algorithm. The results showed that the optimal balance variable parameter of the seat belt was 4751.618 N-2451.839 N-17.554 ms (A-B-C). Finally, the optimal scheme was verified in a system simulating a minivan small offset collision. The results showed that after optimization, the skull von Mises stress was reduced by 36.9%, and the stress of the cervical vertebra cortical bone and cancellous bone decreased by 29.1% and 30.8%, respectively. In addition, the strains of the ribs and lungs decreased by 31.2% and 30.7%, respectively.

Methods for fusing uncertain results obtained from different models in accident reconstruction.

Considering that almost all existing solutions of fusing different reconstructed results require experts' opinions and the issue of how to fuse probabilistic results and mixed results has not been discussed. Two solutions are proposed. The first is based on the Monte Carlo Method (FMCM), while the second is based on the Sub-Interval Technique (FSIT). The method based on FMCM generates sample points according to the distribution of each uncertain result firstly, and then gives out the cumulative distribution function of the final fused result by statistical analysis. The method based on FSIT gets the result fusion interval set according to lower and upper bounds of all interval results and a given length d of each sub-interval firstly, and then calculate the weighted matrix of the result fusion interval. As a result, the cumulative distribution function of the final fused result can also be given out by statistical analysis. Finally, three real accidents are given to demonstrate the methods of FMCM and FSIT, the results of which show that both work well in practice.