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Computer modelling, virtual prototyping and simulation is widely used in the automotive industry to optimize the development process. While the use of CAE is widespread, on its own it lacks the ability to provide observable acoustics or tactile vibrations for decision makers to assess, and hence optimize the customer experience. Subjective assessment using Driver-in-Loop simulators to experience data has been shown to improve the quality of vehicles and reduce development time and uncertainty. Efficient development processes require a seamless interface from detailed CAE simulation to subjective evaluations suitable for high level decision makers. In the context of perceived vehicle vibration, the need for a bridge between complex CAE data and realistic subjective evaluation of tactile response is most compelling. A suite of VI-grade noise and vibration simulators have been developed to meet this challenge.

Due to the high center of gravity of medium-duty vehicles, rollover accidents can easily occur during high-speed cornering and lane changes. In order to prevent the deformation of the body structure, which would restrict the survival space and cause compression injuries to occupants, it is necessary to investigate methods for mitigating these incidents. This paper establishes a numerical model of right-side rollover for a commercial medium-duty vehicle in accordance with ECE R66 regulations, and the accuracy of the model is verified by experiment. According to the results, the material and size parameters of the key components of the right side pillar are selected as design variables. The response result matrix was constructed using the orthogonal design method for total mass, energy absorption, maximum collision acceleration, and minimum distance from the survival space.

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.

Ergonomics plays an important role in automobile design to achieve optimal compatibility between occupants and vehicle components. The overall goal is to ensure that the vehicle design accommodates the target customer group, who come in varied sizes, preferences and tastes. Headroom is one such metric that not only influences accommodation rate but also conveys a visual perception on how spacious the vehicle is. An adequate headroom is necessary for a good seating comfort and a relaxed driving experience. Headroom is intensely discussed in magazine tests and one of the key deciding factors in purchasing a car. SAE J1100 defines a set of measurements and standard procedures for motor vehicle dimensions. H61, W27, W35, H35 and W38 are some of the standard dimensions that relate to headroom and head clearances.

Designing an automotive seat, it is required to perform a detailed study of anthropometry, which deals with measurement of human individuals and understanding human physical variations. It also requires application-based movement study of driver’s hands, feet’s & overall body movement. It is very difficult to design seat curvatures based on any static manikin-based software. We at VECV, have developed a new concept using mixed reality VR technology to capture all body movements for designing best in class seat curvature to accommodate variety of drivers with different body types. We have designed a specialized static bunk, which has a wide range of seat, steering and ABC paddle adjustments, which are integrated with virtual data. We use to study and capture the data of driving position and other ergonomic postures of wide range of people with different body types on this static bunk according to their comfortable driving posture.

Recently, several datasets have become available for occupant monitoring algorithm development, including real and synthetic datasets. However, real data acquisition is expensive and labeling is complex, while virtual data may not accurately reflect actual human physiology. To address these issues and obtain high-fidelity data for training intelligent driving monitoring systems, we have constructed a hybrid dataset that combines real driving image data with corresponding virtual data generated from 3D driving scenarios. We have also taken into account individual anthropometric measures and driving postures. Our approach not only greatly enriches the dataset by using virtual data to augment the sample size, but it also saves the need for extensive annotation efforts. Besides, we can enhance the authenticity of the virtual data by applying ergonomics techniques based on RAMSIS, which is crucial in dataset construction.

There are established federal requirements and industry standards for frontal crash testing of motor vehicles. Consistently applied methods support reliability, repeatability, and comparability of performance metrics between tests and platforms. However, real world collisions are rarely identical to standard test protocols. This study examined the effects of occupant anthropometry and passive restraint deployment timing on occupant kinematics and biomechanical loading in a moderate-severity (approximately 30 kph delta-V) offset frontal crash scenario. An offset, front-to-rear vehicle-to-vehicle crash test was performed, and the dynamics of the vehicle experiencing the frontal collision were replicated in a series of three sled tests. Crash test and sled test vehicle kinematics were comparable. A standard or reduced-weight 50th percentile male Hybrid III ATD (H3-50M) or a standard 5th percentile female Hybrid III ATD (H3-5F) was belted in the driver’s seating position.

A total of 93 tests were conducted in daytime conditions to evaluate the effect on the Time to Collision (TTC), emergency braking, and avoidance rates of the Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) provided by a 2022 Tesla Model 3 against a 4ActivePA adult static pedestrian target. Variables that were evaluated included the vehicle speed on approach, pedestrian offsets, pedestrian clothing, and user-selected FCW settings. As a part of the Tesla’s Collision Avoidance AssistTM, these user-selected FCW settings change the timing of the issuance of the visual and/or audible warning provided. This testing evaluated the Tesla at speeds of 25 and 35 miles per hour (mph) versus a stationary pedestrian target in early, medium, and late FCW settings. Testing was also conducted with a 50% pedestrian offset and 75% offset conditions relative to the right side of the Tesla.

Abstract Compared to other age groups, older adults are at more significant risk of hip fracture when they fall. In addition to the higher risk of falls for the elderly, fear of falls can reduce this population’s outdoor activity. Various preventive solutions have been proposed to reduce the risk of hip fractures ranging from wearable hip protectors to indoor flooring systems. A previously developed rubberized asphalt mixture demonstrated the potential to reduce the risk of head injury. In the current study, the capability of the rubberized asphalt sample was evaluated for the risk of hip fracture for an average elderly male and an average elderly female. A previously developed human body model was positioned in a fall configuration that would give the highest impact forces toward regular asphalt.

To harmonize and define terminology associated with occupant protection for children for vehicle manufacturers and child restraint manufacturers in the United States and Canada.

Ergonomics plays an important role in safety, comfort, and convenience of occupants in passenger cars. Customers come in different sizes; have different preferences and exhibit different seating behaviors while driving a car. With sophisticated interior styling themes aimed at satisfying the increasing customer demands, dashboard packaging and its integration in the vehicle has become a challenging task. This has a deteriorating effect on the driver knee clearance since dashboard has penetrated more into cockpit area to house the complex integration. With drivers having significant workload, their postures are within a presumable range of prediction. However, there still exists ‘out-of-customary’ behaviors while driving a vehicle. Drivers tend to sit in a slouched posture, and this leads to an involuntary knee engagement resulting in activation of critical controls like EPB (Electronic Parking Brake). EPB is an Active Safety feature and on activating it, the vehicle stops immediately.

The purpose of this study is to conduct dynamic seat pressure mapping on vehicle seats during its operation on different test tracks under ambient environmental conditions for a defined speed. The test track comprises of pave roads, high frequency track, low frequency track and twist track. The variations in pressure distribution on seat during diverse road load inputs help to understand the seat cushion and back comfort for unique percentiles of human subjects ranging from 50th to 95th percentile population. For conducting the study, a sport utility vehicle (SUV) loaded with leatherette seats has chosen. Totally six participants (human subjects), five male and one female selected for the study based on their BMI (Body mass index) and body morphology. Pressure mats suitable for taking dynamic load inputs and able to log the data at a defined sampling rate mounted on seats and secured properly. The pressure mats should cover the seat cushion, bolster areas and back seat completely.

The car door handle is an essential component of any vehicle, as it plays a crucial role in providing access to the cabin and ensuring safety of the passenger. The primary function of the car door handle is to allow entry and exit from the vehicle while preventing unauthorized access. In addition to this, car door handles also play a critical role in ensuring passenger safety by keeping the door closed during accidents or when there is a significant amount of G-force acting on the vehicle. A typical car door handle comprises several components including the structure, cover, bowden lever, bracket, pins and other child parts. The structure provides the ergonomics and rigidity for grabbing the handle, while the cover gives the handle an aesthetic appearance. The Bowden lever facilitates the unlatching of the door and the intermediate parts ensure that the handle operates smoothly.

Effective smart cockpit interaction design can address the specific needs of children, offering ample entertainment and educational resources to enhance their on-board experience. Currently, substantial attention is focused on smart cockpit design to enrich the overall travel engagement for children. Recognizing the contrasts between children and adults in areas such as physical health, cognitive development, and emotional psychology, it becomes imperative to meticulously customize the design and optimization processes to cater explicitly to their individual requirements. However, a noticeable gap persists in both research methodologies and product offerings within this domain.

Abstract Rib fractures are associated with high rates of morbidity and mortality. Improved methods to assess rib bone quality are needed to identify at-risk populations. Quantitative computed tomography (QCT) can be used to calculate volumetric bone mineral density (vBMD) and bone mineral content (BMC), which may be related to rib fracture risk. The objective of this study was to determine if vBMD and BMC from QCT predict human rib structural properties. 127 mid-level (5th–7th) ribs were obtained from adult female (n = 67) and male (n = 60) postmortem human subjects (PMHS). Isolated rib QCT scans were performed to calculate vBMD and BMC.

Abstract Objective: This study aimed to optimize restraint systems and improve safety equity by using parametric human body models (HBMs) and vehicle models accounting for variations in occupant size and shape as well as vehicle type. Methodology: A diverse set of finite element (FE) HBMs were developed by morphing the GHBMC midsize male simplified model into statistically predicted skeleton and body shape geometries with varied age, stature, and body mass index (BMI). A parametric vehicle model was equipped with driver, front passenger, knee, and curtain airbags along with seat belts with pretensioner(s) and load limiter and has been validated against US-NCAP results from four vehicles (Corolla, Accord, RAV4, F150). Ten student groups were formed for this study, and each group picked a vehicle model, occupant side (driver vs. passenger), and an occupant model among the 60 HBMs.

Abstract Letter from the Special Issue Editors

Abstract In this study, a parametric thoracic spine (T-spine) model was developed to account for morphological variations among the adult population. A total of 84 CT scans were collected, and the subjects were evenly distributed among age groups and both sexes. CT segmentation, landmarking, and mesh morphing were performed to map a template mesh onto the T-spine vertebrae for each sampled subject. Generalized procrustes analysis (GPA), principal component analysis (PCA), and linear regression analysis were then performed to investigate the morphological variations and develop prediction models. A total of 13 statistical models, including 12 T-spine vertebrae and a spinal curvature model, were combined to predict a full T-spine 3D geometry with any combination of age, sex, stature, and body mass index (BMI). A leave-one-out root mean square error (RMSE) analysis was conducted for each node of the mesh predicted by the statistical model for every T-spine vertebra.

Abstract Introduction: The use of less lethal impact munitions (LLIMs) by law enforcement has increased in frequency, especially following nationwide protests regarding police brutality and racial injustice in the summer of 2020. There are several reports of the projectiles causing severe injuries when they penetrate the skin including pulmonary contusions, bone fractures, liver lacerations, and, in some cases, death. The penetration threshold of skin in different body regions is due to differences in the underlying structure (varying degree of muscle, adipose tissue, and presence or absence of bone). Objective: The objective of this study was to further investigate what factors affected the likelihood of skin penetration in various body regions and to develop corresponding penetration risk curves.

Abstract Analysis of Kinetic Metrics in Submarining vs Non-Submarining Conditions for a 6YO Pediatric Human Body Model in Frontal Impacts