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Technical Paper

Laboratory Investigations and Mathematical Modeling of Airbag-Induced Skin Burns

Although driver-side airbag systems provide protection against serious head and chest injuries in frontal impacts, injuries produced by the airbag itself have also been reported. Most of these injuries are relatively minor, and consist primarily of skin abrasions and burns. Previous investigations have addressed the mechanisms of airbag-induced skin abrasion. In the current research, laboratory studies related to the potential for thermal burns due to high-temperature airbag exhaust gas were conducted. A laboratory apparatus was constructed to produce a 10-mm-diameter jet of hot air that was directed onto the leg skin of human volunteers in time-controlled pulses. Skin burns were produced in 70 of 183 exposures conducted using air temperatures ranging from 350 to 550°C, air velocities from 50 to 90 m/s, and exposure durations from 50 to 300 ms.
Technical Paper

An Improved Seating Accommodation Model with Application to Different User Populations

A new approach to driver seat-position modeling is presented. The equations of the Seating Accommodation Model (SAM) separately predict parameters of the distributions of male and female fore/aft seat position in a given vehicle. These distributions are used together to predict specific percentiles of the combined male-and-female seat-position distribution. The effects of vehicle parameters-seat height, steering-wheel-to-accelerator pedal distance, seat-cushion angle, and transmission type-are reflected in the prediction of mean seat position. The mean and standard deviation of driver population stature are included in the prediction for the mean and standard deviation of the seat-position distribution, respectively. SAM represents a new, more flexible approach to predicting fore/aft seat-position distributions for any driver population in passenger vehicles. Model performance is good, even at percentiles in the tails of the distribution.
Technical Paper

Predicting the Effects of Muscle Activation on Knee, Thigh, and Hip Injuries in Frontal Crashes Using a Finite-Element Model with Muscle Forces from Subject Testing and Musculoskeletal Modeling

In a previous study, the authors reported on the development of a finite-element model of the midsize male pelvis and lower extremities with lower-extremity musculature that was validated using PMHS knee-impact response data. Knee-impact simulations with this model were performed using forces from four muscles in the lower extremities associated with two-foot bracing reported in the literature to provide preliminary estimates of the effects of lower-extremity muscle activation on knee-thigh-hip injury potential in frontal impacts. The current study addresses a major limitation of these preliminary simulations by using the AnyBody three-dimensional musculoskeletal model to estimate muscle forces produced in 35 muscles in each lower extremity during emergency one-foot braking.
Technical Paper

Validation of the Human Motion Simulation Framework: Posture Prediction for Standing Object Transfer Tasks

The Human Motion Simulation Framework is a hierarchical set of algorithms for physical task simulation and analysis. The Framework is capable of simulating a wide range of tasks, including standing and seated reaches, walking and carrying objects, and vehicle ingress and egress. In this paper, model predictions for the terminal postures of standing object transfer tasks are compared to data from 20 subjects with a wide range of body dimensions. Whole body postures were recorded using optical motion capture for one-handed and two-handed object transfers to target destinations at three angles from straight ahead and three heights. The hand and foot locations from the data were input to the HUMOSIM Framework Reference Implementation (HFRI) in the Jack human modeling software. The whole-body postures predicted by the HFRI were compared to the measured postures using a set of measures selected for their importance to ergonomic analysis.
Technical Paper

Modeling Ascending and Descending Stairs Using the Human Motion Simulation Framework

The Human Motion Simulation Framework (Framework) is a hierarchical set of algorithms for predicting and analyzing task-oriented human motion. The Framework was developed to improve the performance of commercial human modeling software by increasing the accuracy of predicted motions and the speed of generating simulations. This paper presents the addition of stair ascending and descending to the Transition Stepping and Timing (Transit) model, a component of the Framework that predicts gait and acyclic stepping.
Technical Paper

Simulating Complex Automotive Assembly Tasks using the HUMOSIM Framework

Efficient methods for simulating operators performing part handling tasks in manufacturing plants are needed. The simulation of part handling motions is an important step towards the implementation of virtual manufacturing for the purpose of improving worker productivity and reducing injuries in the workplace. However, industrial assembly tasks are often complex and involve multiple interactions between workers and their environment. The purpose of this paper is to present a series of industrial simulations using the Human Motion Simulation Framework developed at the University of Michigan. Three automotive assembly operations spanning scenarios, such as small and large parts, tool use, walking, re-grasping, reaching inside a vehicle, etc. were selected.
Technical Paper

Understanding Work Task Assessment Sensitivity to the Prediction of Standing Location

Digital human models (DHM) are now widely used to assess worker tasks as part of manufacturing simulation. With current DHM software, the simulation engineer or ergonomist usually makes a manual estimate of the likely worker standing location with respect to the work task. In a small number of cases, the worker standing location is determined through physical testing with one or a few workers. Motion capture technology is sometimes used to aid in quantitative analysis of the resulting posture. Previous research has demonstrated the sensitivity of work task assessment using DHM to the accuracy of the posture prediction. This paper expands on that work by demonstrating the need for a method and model to accurately predict worker standing location. The effect of standing location on work task posture and the resulting assessment is documented through three case studies using the Siemens Jack DHM software.
Technical Paper

Characterization of Knee-Thigh-Hip Response in Frontal Impacts Using Biomechanical Testing and Computational Simulations

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.
Technical Paper

Modeling Vehicle Ingress and Egress Using the Human Motion Simulation Framework

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.
Technical Paper

Development, Evaluation, and Sensitivity Analysis of Parametric Finite Element Whole-Body Human Models in Side Impacts

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.
Technical Paper

Characterizing Vehicle Occupant Body Dimensions and Postures Using a Statistical Body Shape Model

Reliable, accurate data on vehicle occupant characteristics could be used to personalize the occupant experience, potentially improving both satisfaction and safety. Recent improvements in 3D camera technology and increased use of cameras in vehicles offer the capability to effectively capture data on vehicle occupant characteristics, including size, shape, posture, and position. In previous work, the body dimensions of standing individuals were reliably estimated by fitting a statistical body shape model (SBSM) to data from a consumer-grade depth camera (Microsoft Kinect). In the current study, the methodology was extended to consider seated vehicle occupants. The SBSM used in this work was developed using laser scan data gathered from 147 children with stature ranging from 100 to 160 cm and BMI from 12 to 27 kg/m2 in various sitting postures.
Technical Paper

A Task-Based Stepping Behavior Model for Digital Human Models

Cyclical stepping (gait) has been studied extensively. Some of these results are reflected in the straight and curved path step-following algorithms in commercial digital human modeling (DHM) implementations. With the aid of these algorithms, DHM users define start, intermediate, and end path points and the software generates a walking-like motion along the path. Most of these algorithms have substantial limitations, among them that the figures exhibit “foot skate,” meaning that the kinematic constraint of foot contact with the ground is not respected. Turning is accomplished by pivoting the entire figure, rather than through realistic lower-extremity motions. The simulation of the non-cyclical stepping motions accompanying manual material handling pickup and delivery tasks requires manual manikin manipulation. This paper proposes a paradigm for the simulation of stepping behavior in digital human models based on a model of foot placements and motions.
Technical Paper

The HUMOSIM Ergonomics Framework: A New Approach to Digital Human Simulation for Ergonomic Analysis

The potential of digital human modeling to improve the design of products and workspaces has been limited by the time-consuming manual manipulation of figures that is required to perform simulations. Moreover, the inaccuracies in posture and motion that result from manual procedures compromise the fidelity of the resulting analyses. This paper presents a new approach to the control of human figure models and the analysis of simulated tasks. The new methods are embodied in an algorithmic framework developed in the Human Motion Simulation (HUMOSIM) laboratory at the University of Michigan. The framework consists of an interconnected, hierarchical set of posture and motion modules that control aspects of human behavior, such as gaze or upper-extremity motion. Analysis modules, addressing issues such as shoulder stress and balance, are integrated into the framework.
Technical Paper

ASPECT: The Next-Generation H-Point Machine and Related Vehicle and Seat Design and Measurement Tools

The ASPECT program was conducted to develop new Automotive Seat and Package Evaluation and Comparison Tools. This paper presents a summary of the objectives, methods, and results of the program. The primary goal of ASPECT was to create a new generation of the SAE J826 H-point machine. The new ASPECT manikin has an articulated torso linkage, revised seat contact contours, a new weighting scheme, and a simpler, more user-friendly installation procedure. The ASPECT manikin simultaneously measures the H-point location, seat cushion angle, seatback angle, and lumbar support prominence of a seat, and can be used to make measures of seat stiffness. In addition to the physical manikin, the ASPECT program developed new tools for computer-aided design (CAD) of vehicle interiors. The postures and positions of hundreds of vehicle occupants with a wide range of body size were measured in many different vehicle conditions.
Technical Paper

Investigating Driver Headroom Perception: Methods and Models

Recent changes in impact protection requirements have led to increased padding on vehicle interior surfaces. In the areas near the driver's head, thicker padding can reduce the available headspace and may degrade the driver's perception of headroom. A laboratory study of driver headroom perception was conducted to investigate the effects of physical headroom on the subjective evaluation of headroom. Ninety-nine men and women rated a range of headroom conditions in a reconfigurable vehicle mockup. Unexpectedly, driver stature was not closely related to the perception of headroom. Short-statured drivers were as likely as tall drivers to rate a low roof condition as unacceptable. Statistical models were developed from the data to predict the effects of changes in headroom on the percentage of drivers rating the head-room at a specified criterion level.
Technical Paper

Automobile Occupant Posture Prediction for Use with Human Models

A new method of predicting automobile occupant posture is presented. The Cascade Prediction Model approach combines multiple independent predictions of key postural degrees of freedom with inverse kinematics guided by data-based heuristics. The new model, based on posture data collected in laboratory mockups and validated using data from actual vehicles, produces accurate posture predictions for a wide range of passenger car interior geometries. Inputs to the model include vehicle package dimensions, seat characteristics, and occupant anthropometry. The Cascade Prediction Model was developed to provide accurate posture prediction for use with any human CAD model, and is applicable to many vehicle design and safety assessment applications.
Technical Paper

New Concepts in Vehicle Interior Design Using ASPECT

The ASPECT (Automotive Seat and Package Evaluation and Comparison Tools) program developed a new physical manikin for seat measurement and new techniques for integrating the seat measurements into the vehicle design process. This paper presents an overview of new concepts in vehicle interior design that have resulted from the ASPECT program and other studies of vehicle occupant posture and position conducted at UMTRI. The new methods result from an integration of revised versions of the SAE seat position and eyellipse models with the new tools developed in ASPECT. Measures of seat and vehicle interior geometry are input to statistical posture and position prediction tools that can be applied to any specified user population or individual occupant anthropometry.
Technical Paper

Comparison of Methods for Predicting Automobile Driver Posture

Recent research in the ASPECT (Automotive Seat and Package Evaluation and Comparison Tools) program has led to the development of a new method for automobile driver posture prediction, known as the Cascade Model. The Cascade Model uses a sequential series of regression functions and inverse kinematics to predict automobile occupant posture. This paper presents an alternative method for driver posture prediction using data-guided kinematic optimization. The within-subject conditional distributions of joint angles are used to infer the internal cost functions that guide tradeoffs between joints in adapting to different vehicle configurations. The predictions from the two models are compared to in-vehicle driving postures.
Technical Paper

The Virtual Driver: Integrating Task Planning and Cognitive Simulation with Human Movement Models

Digital human modeling has traditionally focused on the physical aspects of humans and the environments in which they operate. As the field moves towards modeling dynamic and more complex tasks, cognitive and perceptual aspects of the human's performance need to be considered. Cognitive modeling of complex tasks such as driving has commonly avoided the complexity of physical simulation of the human, distilling motor performance to motion execution times. To create a more powerful and flexible approach to the modeling of human/machine interaction, we have integrated a physical architecture of human motion (the Human Motion Simulation Ergonomics Framework—HUMOSIM) with a computational cognitive architecture (the Queueing network model human processor—QN–MHP). The new system combines the features of the two separate architectures and provides new capabilities that emerge from their integration.
Technical Paper

Optimizing Vehicle Occupant Packaging

Occupant packaging practice relies on statistical models codified in SAE practices, such as the SAE J941 eyellipse, and virtual human figure models representing individual occupants. The current packaging approach provides good solutions when the problem is relatively unconstrained, but achieving good results when many constraints are active, such as restricted headroom and sightlines, requires a more rigorous approach. Modeling driver needs using continuous models that retain the residual variance associated with performance and preference allows use of optimization methodologies developed for robust design. Together, these models and methods facilitate the consideration of multiple factors simultaneously and tradeoff studies can be performed. A case study involving the layout of the interior of a passenger car is presented, focusing on simultaneous placement of the seat and steering wheel adjustment ranges.