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Analysis of pedestrian-to-vehicle collisions can be complex due to the nature of the interaction and the physics involved. The scarcity of evidence like video evidence (from CCTV or dashcams), data from the vehicle's ECU, witness accounts, and physical evidence such as tyre marks, complicates the analysis of these incidents. In cases with limited evidence, current forensic methods often rely on prolonged inquiry processes or computationally intensive simulations. Without adequate data, accurately estimating pedestrian kinematics and addressing hit-and-run scenarios becomes challenging. This research provides an alternative approach to enhancing pedestrian forensic analysis based on machine learning (ML) algorithms trained on over 3000 multi-body computer simulations with a diverse set of vehicle profiles and pedestrian anthropometries.

Current recommendations for restraining child occupants are based on biomechanical testing and data from national and international field studies primarily conducted prior to 2011. We hypothesized that analysis to identify factors associated with pediatric injury in motor-vehicle crashes using a national database of more recent police-reported crashes in the United States involving children under age 13 where type of child restraint system (CRS) is recorded would support previous recommendations. Weighted data were extracted from the National Automotive Sampling System General Estimates System (NASS-GES) for crash years 2010 to 2015. Injury outcomes were grouped as CO (possible and no injury) or KAB (killed, incapacitating injury, non-incapacitating injury). Restraint was characterized as optimal, suboptimal, or unrestrained based on current best practice recommendations. Analysis used survey methods to identify factors associated with injury.

Recent field data have shown that the occupant protection in vehicle rear seats failed to keep pace with advances in the front seats likely due to the lack of advanced safety technologies. The objective of this study was to optimize advanced restraint systems for protecting rear seat occupants with a range of body sizes under different frontal crash pulses. Three series of sled tests (baseline tests, advanced restraint trial tests, and final tests), MADYMO model validations against a subset of the sled tests, and design optimizations using the validated models were conducted to investigate rear seat occupant protection with 4 Anthropomorphic Test Devices (ATDs) and 2 crash pulses.

Recent field data have shown that the occupant protection in vehicle rear seats failed to keep pace with advances in the front seats likely due to the lack of advanced safety technologies. The objective of this study was to optimize advanced restraint systems for protecting rear seat occupants with a range of body sizes under different frontal crash pulses. Three series of sled tests (baseline tests, advanced restraint trial tests, and final tests), MADYMO model validations against a subset of the sled tests, and design optimizations using the validated models were conducted to investigate rear seat occupant protection with 4 Anthropomorphic Test Devices (ATDs) and 2 crash pulses.

Occupant stature and body shape may have significant effects on injury risks in motor vehicle crashes, but the current finite element (FE) human body models (HBMs) only represent occupants with a few sizes and shapes. Our recent studies have demonstrated that, by using a mesh morphing method, parametric FE HBMs can be rapidly developed for representing a diverse population. However, the biofidelity of those models across a wide range of human attributes has not been established. Therefore, the objectives of this study are 1) to evaluate the accuracy of HBMs considering subject-specific geometry information, and 2) to apply the parametric HBMs in a sensitivity analysis for identifying the specific parameters affecting body responses in side impact conditions. Four side-impact tests with two male post-mortem human subjects (PMHSs) were selected to evaluate the accuracy of the geometry and impact responses of the morphed HBMs.

Law enforcement officers (LEO) make extensive use of vehicles to perform their jobs, often spending large portions of a shift behind the wheel. Few LEO vehicles are purpose-built; the vast majority are modified civilian vehicles. Data from the field indicate that LEO suffer from relatively high levels musculoskeletal injury that may be due in part to poor accommodation provided by their vehicles. LEO are also exposed to elevated crash injury risk, which may be exacerbated by a compromise in the performance of the occupant restraint systems due to body-borne equipment. A pilot study was conducted to demonstrate the application of three-dimensional anthropometric scanning and measurement technology to address critical concerns related to vehicle design. Detailed posture and belt fit data were gathered from five law enforcement officers as they sat in the patrol vehicles that they regularly used and in a mockup of a mid-sized vehicle.

The objective of this study is to develop a method that uses a combination of field data analysis, naturalistic driving data analysis, and computational simulations to explore the potential injury reduction capabilities of integrating passive and active safety systems in frontal impact conditions. For the purposes of this study, the active safety system is actually a driver assist (DA) feature that has the potential to reduce delta-V prior to a crash, in frontal or other crash scenarios. A field data analysis was first conducted to estimate the delta-V distribution change based on an assumption of 20% crash avoidance resulting from a pre-crash braking DA feature. Analysis of changes in driver head location during 470 hard braking events in a naturalistic driving study found that drivers’ head positions were mostly in the center position before the braking onset, while the percentage of time drivers leaning forward or backward increased significantly after the braking onset.

The aging population is a growing concern as the increased fragility and frailty of the elderly results in an elevated incidence of injury as well as an increased risk of mortality and morbidity. To assess elderly injury risk, age-specific computational models can be developed to directly calculate biomechanical metrics for injury. The first objective was to develop an older occupant Global Human Body Models Consortium (GHBMC) average male model (M50) representative of a 65 year old (YO) and to perform regional validation tests to investigate predicted fractures and injury severity with age. Development of the GHBMC M50 65 YO model involved implementing geometric, cortical thickness, and material property changes with age. Regional validation tests included a chest impact, a lateral impact, a shoulder impact, a thoracoabdominal impact, an abdominal bar impact, a pelvic impact, and a lateral sled test.

This research proposes the use of Artificial Neural Networks (ANN) to predict the road input for road load data generation for variants of a vehicle as vehicle parameters are modified. This is important to the design engineers while the vehicle variant is still in the initial stages of development, hence no prototypes are available and accurate proving ground data acquisition is not possible. ANNs are, with adequate training, capable of representing the complex relationships between inputs and outputs. This research explores the implementation of the ANN to predict road input for vehicle variants using a quarter vehicle test rig. The training and testing data for this research are collected from a validated quarter vehicle model.

Eight whole fresh-frozen cadavers (6 female, 2 male) that were elderly and/or female were laterally impacted using UMTRI's dual-sled side-impact test facility. Cadavers were not excluded on the basis of old age or bone diseases that affect tolerance. A thinly padded, multi-segment impactor was used that independently measured force histories applied to the shoulder, thorax, abdomen, greater trochanter, iliac wing, and femur of each PMHS. Impactor plates were adjusted vertically and laterally toward the subject so that contact with body regions occurred simultaneously and so that each segment contacted the same region on every subject. This configuration minimized the effects of body shape on load sharing between regions. Prior to all tests, cadavers were CT scanned to check for pre-existing skeletal injuries. Cadavers were excluded if they had pre-existing rib fractures or had undergone CPR.

Sloped medians provide a run-off area for errant vehicles so that they can be safely stopped off-road with or without barriers placed in the sloped median. However, in order to optimize the design of sloped medians and the containment barriers, it is essential to accurately model the behavior of vehicles on such sloped terrain surfaces. In this study, models of a vehicle fleet comprising a small sedan and a pickup truck and sloped terrain surface are developed in CarSim™ to simulate errant vehicle behavior on sloped median. Full-scale crash tests were conducted using the vehicle fleet driven across a 9.754 meters wide median with a 6:1 slope at speeds ranging from 30 to 70 km/h. Measured data such as the lateral accelerations of the vehicle as well as chassis rotations (roll and pitch) were synchronized with the vehicle motion obtained from the video data.

A laboratory study of posture and belt fit was conducted with 46 men and 51 women, 61% of whom were age 60 years or older and 32% age 70 years or older. In addition, 28% of the 97 participants were obese, defined as body mass index ≥ 30 kg/m2. A mockup of a passenger vehicle driver's station was created and five belt anchorage configurations were produced by moving the buckle, outboard-upper (D-ring), and outboard-lower anchorages. An investigator recorded the three-dimensional locations of landmarks on the belt and the participant's body using a coordinate measurement machine. The location of the belt with respect to the underlying skeletal structures was analyzed, along with the length of belt webbing. Using linear regression models, an increase in age from 20 to 80 years resulted in the lap belt positioned 18 mm further forward relative to the pelvis, 26 mm greater lap belt webbing length, and 19 mm greater shoulder belt length.

NHTSA estimates that more than half of the lives saved (168,524) in car crashes between 1960 and 2002 were due to the use of seat belts. Nevertheless, while seat belts are vital to occupant crash protection, safety researchers continue efforts to further enhance the capability of seat belts in reducing injury and fatality risk in automotive crashes. Examples of seat belt design concepts that have been investigated by researchers include inflatable, 4-point, and reverse geometry seat belts. In 2011, Ford Motor Company introduced the first rear seat inflatable seat belts into production vehicles. A series of tests with child and small female-sized Anthropomorphic Test Devices (ATD) and small, elderly female Post Mortem Human Subjects (PMHS) was performed to evaluate interactions of prototype inflatable seat belts with the chest, upper torso, head and neck of children and small occupants, from infants to young adolescents.

Lateral impact tests were performed using seven male post-mortem human subjects (PMHS) to characterize the force-deflection response of contacted body regions, including the lower abdomen. All tests were performed using a dual-sled, side-impact test facility. A segmented impactor was mounted on a sled that was pneumatically accelerated into a second, initially stationary sled on which a subject was seated facing perpendicular to the direction of impact. Positions of impactor segments were adjusted for each subject so that forces applied to different anatomic regions, including thorax, abdomen, greater trochanter, iliac wing, and thigh, could be independently measured on each PMHS. The impactor contact surfaces were located in the same vertical plane, except that the abdomen plate was offset 5.1 cm towards the subject.

This study evaluated the biomechanical performance of a rear-seat inflatable seatbelt system and compared it to that of a 3-point seatbelt system, which has a long history of good real-world performance. Frontal-impact sled tests were conducted with Hybrid III anthropomorphic test devices (ATDs) and with post mortem human subjects (PMHS) using both restraint systems and a generic rear-seat configuration. Results from these tests demonstrated: a) reduction in forward head excursion with the inflatable seatbelt system when compared to that of a 3-point seatbelt and; b) a reduction in ATD and PMHS peak chest deflections and the number of PMHS rib fractures with the inflatable seatbelt system and c) a reduction in PMHS cervical-spine injuries, due to the interaction of the chin with the inflated shoulder belt. These results suggest that an inflatable seatbelt system will offer additional benefits to some occupants in the rear seats.

The NASS-CDS (1998-2008) and CIREN datasets were analyzed to identify factors contributing to abdominal injury in crash environments where belt use and airbag deployment are common. In frontal impacts, the percentage of occupants sustaining abdominal injury is three times higher for unbelted compared to belted front-row adult occupants (p≺0.0001) at both AIS2+ and AIS3+ injury levels. Airbag deployment does not substantially affect the percentage of occupants who sustain abdominal injuries in frontal impacts (p=0.6171), while belt use reduces the percentage of occupants sustaining abdominal injury in both nearside and farside crashes (p≺0.0001). Right-front passengers in right-side impacts have the highest risk (1.91%) of AIS 3+ abdominal injury (p=0.03). The percentage of occupants with AIS 3+ abdominal injuries does not vary with age for frontal, nearside, or farside impacts.

The objectives of this study were to examine the response, repeatability, and injury predictive ability of the Hybrid III small-female dummy to static out-of-position (OOP) deployments using a depowered driver-side airbag. Five dummy tests were conducted in two OOP configurations by two different laboratories. The OOP configurations were nose-on-rim (NOR) and chest-on-bag (COB). Four cadaver tests were conducted using unembalmed small-female cadavers and the same airbags used in the dummy tests under similar OOP conditions. One cadaver test was designed to increase airbag loading of the face and neck (a forehead-on-rim, or FOR test). Comparison between the dummy tests of Lab 1 and of Lab 2 indicated the test conditions and results were repeatable. In the cadaver tests no skull fractures or neck injuries occurred. However, all four cadavers had multiple rib fractures.

A finite element (FE) model with knee-thigh-hip (KTH) and lower-extremity muscles has been developed to study the potential effects of muscle tension on KTH injuries due to knee bolster loadings in frontal crashes. This model was created by remeshing the MADYMO human lower-extremity FE model to account for regional differences in cortical bone thickness, trabecular bone, cortical bone with directionally dependent mechanical properties and Tsai-Wu failure criteria, and articular cartilage. The model includes 35 Hill-type muscles in each lower extremity with masses based on muscle volume. The skeletal response of the model was validated by simulating biomechanical tests without muscle tension, including cadaver skeletal segment impact tests documented in the literature as well as recent tests of seated whole cadavers that were impacted using knee-loading conditions similar to those produced in FMVSS 208 testing.

Development and validation of crash test dummies and computational models that are capable of predicting the risk of injury to all parts of the knee-thigh-hip (KTH) complex in frontal impact requires knowledge of the force transmitted from the knee to the hip under knee impact loading. To provide this information, the knee impact responses of whole and segmented cadavers were measured over a wide range of knee loading conditions. These data were used to develop and help validate a computational model, which was used to estimate force transmitted to the cadaver hip. Approximately 250 tests were conducted using five unembalmed midsize male cadavers. In these tests, the knees were symmetrically impacted with a 255-kg padded impactor using three combinations of knee-impactor padding and velocity that spanned the range of knee loading conditions produced in FMVSS 208 and NCAP tests. Each subject was tested in four conditions.

The ease of getting into and out of passenger cars and light trucks is a critical component of customer acceptance and product differentiation. In commercial vehicles, the health and safety of drivers is affected by the design of the steps and handholds they use to get into and out of the cab. Ingress/egress assessment appears to represent a substantial application opportunity for digital human models. The complexity of the design space and the range of possible biomechanical and subjective measures of interest mean that developing useful empirical models is difficult, requiring large-scale subject testing with physical mockups. Yet, ingress and egress motions are complex and strongly affected by the geometric constraints and driver attributes, posing substantial challenges in creating meaningful simulations using figure models.