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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.

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.

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.

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.

Posture and external loads such as hand forces have a dominant effect on ergonomic analysis outcomes. Yet, current digital human modeling tools used for proactive ergonomics analysis lack validated models for predicting postures for standing hand-force exertions. To address this need, the effects of hand magnitude and direction on whole-body posture for standing static hand-force exertion tasks were quantified in a motion-capture study of 19 men and women with widely varying body size. The objective of this work was to identify postural behaviors that might be incorporated into a posture-prediction algorithm for standing hand-force tasks. Analysis of one-handed exertions indicates that, when possible, people tend to align their bodies with the direction of force application, converting potential cross-body exertions into sagittal plane exertions. With respect to the hand-force plane, pelvis position is consistent with a postural objective of reducing rotational trunk torques.

Industrial tasks performed by standing workers are among those most commonly simulated using digital human models. Workers often walk, turn, and take acyclic steps as they perform these tasks. Current h uman modeling tools lack the capability to simulate these whole body motions accurately. Most models simulate walking by replaying joint angle trajectories corresponding to a general gait pattern. Turning is simulated poorly if at all, and violations of kinematic constraints between the feet and ground are common. Moreover, current models do not accurately predict foot placement with respect to loads and other hand targets, diminishing the utility of the associated ergonomic analyses. A new approach to simulating stepping and walking in task-oriented activities is proposed. Foot placements and motions are predicted from operator and task characteristics using empirical models derived from laboratory data and validated using field data from an auto assembly plant.

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.

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.

The development of a new carrier route vehicle for the U.S. Postal Service began with the design of the vehicle interior from an operator-centered perspective. A task analysis of the postal worker while driving and while performing mail-handling operations guided the layout of the vehicle interior. The Jack™ human modeling software was used, along with SAE Recommended Practices and other tools, to create a vehicle environment that will accommodate a large percentage of the operator population. The challenges of designing for this unique work environment provided a good opportunity to evaluate the relative strengths and weaknesses of the available human factors tools, including the Jack™ digital human figure model. This paper describes the development of the vehicle interior, discusses some lessons learned, and concludes with recommendations for increased functionality and improved integration of vehicle interior design tools.

Workstation design is one of the most essential components of proactive ergonomics, and digital human models have gained increasing popularity in the analysis and design of current and future workstations (Chaffin 2001). Using digital human technology, it is possible to simulate interactions between humans and current or planned workstations, and conduct quantitative ergonomic analyses based on realistic human postures and motions. Motion capture has served as the primary means by which to acquire and visualize human motions in a digital environment. However, motion capture only provides motions for a specific person performing specific tasks. Albeit useful, at best this allows for the analysis of current or mocked-up workstations only. The ability to subsequently modify these motions is required to efficiently evaluate alternative design possibilities and thus improve design layouts.

As part of the Automotive Seat and Package Evaluation and Comparison Tools (ASPECT) program, UMTRI researchers developed a new H-point manikin that is intended to replace the current SAE J826 manikin. The original manikin is used in many automotive applications, including as a platform for a belt-fit test device (BTD). In the current project, components and procedures were developed to measure belt fit using the ASPECT manikin. Contoured lap and torso forms were constructed using anthropometric data from an earlier UMTRI study. Prototype forms were mounted on the ASPECT manikin for testing in a laboratory fixture and in vehicles. The testing demonstrated that the ASPECT-BTD produces consistent measures of belt fit that vary in expected ways with belt geometry.

Few studies have systematically examined the effects of truck and bus workstation geometry on driver posture and position. This paper presents methods for determining drivers' postural responses and preferred component locations using a reconfigurable vehicle mockup. Body landmark locations recorded using a three-dimensional digitizer are used to compute a skeletal-linkage representation of the drivers' posture. A sequential adjustment procedure is used to determine the preferred positions and orientations of key components, including the seat, steering wheel, and pedals. Data gathered using these methods will be used to create new design tools for trucks and buses, including models of driver-selected seat position, eye location, and needed component adjustment ranges. The results will also be used to create accurate posture-prediction models for use with human modeling software.

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.

The ASPECT (Automotive Seat and Package Evaluation and Comparison Tools) manikin provides new capabilities for vehicle and seat measurement while maintaining continuity with previous practices. This paper describes how the manikin is used in the development of new designs, the audit verification of build, and in benchmarking competitive vehicles and seats. The measurement procedures are discussed in detail, along with the seat and package dimensions that are associated with the new tool.

The primary objective of the ASPECT (Automotive Seat and Package Evaluation and Comparison Tools) program was to develop a new generation of the SAE J826 H-point manikin. The new ASPECT manikin builds on the long-term success of the H-point manikin while adding new measurement capability and improved ease of use. The ASPECT manikin features an articulated torso linkage to measure lumbar support prominence; new contours based on human subject data; a new weighting scheme; lightweight, supplemental thigh, leg, and shoe segments; and a simpler, user-friendly installation procedure. This paper describes the new manikin in detail, including the rationale and motivation for the design features. The ASPECT manikin maintains continuity with the current SAE J826 H-point manikin in important areas while providing substantial new measurement capability.

The ASPECT program, conducted to develop new Automotive Seat and Package Evaluation and Comparison Tools, used posture and position data from hundreds of vehicle occupants to develop a new physical manikin and related tools. Analysis of the relationships between anthropometric measures established the criteria for subject selection. The study goals and the characteristics of the data collected determined the sampling approach and number of subjects tested in each study. Testing was conducted in both vehicle and laboratory vehicle mockups. This paper describes the subject sampling strategies, anthropometric issues, and general data collection methods used for the program's eight posture studies.

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.

The factors that influence airbag-induced upper-extremity injuries sustained by drivers were investigated in this study. Seven unembalmed human cadavers were used in nineteen direct-forearm-interaction static deployments. A single horizontal-tear-seam airbag module and two different inflators were used. Spacing between the instrumented forearm and the airbag module was varied from 10 cm to direct contact in some tests. Forearm-bone instrumentation included triaxial accelerometry, crack detection gages, and film targets. Internal airbag pressure was also measured. The observed injuries were largely transverse, oblique, and wedge fractures of the ulna or radius, or both, similar to those reported in field investigations. Tears of the elbow joint capsule were also found, both with and without fracture of the forearm.

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.