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This paper describes the development of the fixed seat eyellipse in the October 2008 revision of SAE Recommended Practice J941. The eye locations of 23 men and women with a wide range of stature were recorded as they sat in each of three second-row bench seats in a laboratory mockup. Testing was conducted at 19-, 23-, and 27-degree seat back angles. Regression analysis demonstrated that passenger eye location was significantly affected by stature and by seat back angle. The regression results were used to develop an elliptical approximation of the distribution of adult passenger eye locations, applying a methodology previously used to develop the driver eyellipse in SAE J941-2002.

Seat comfort is driven in part by the fit between the sitter and seat. Traditional anthropometric data provide little information about the size and shape of the torso that can be used for backrest design. This study introduces a methodology for using three-dimensional computer models of the human torso based on a statistical analysis of body shapes for conducting automated fit assessments. Surface scan data from 296 men and 417 women in a seated posture were analyzed to create a body shape model that can be adjusted to a range of statures, body shape, and postures spanning those typical of vehicle occupants. Finite-element models of two auto seat surface were created, along with custom software that generates body models and postures them in the seat. A simple simulation technique was developed to rapidly assess the fit of the torso relative to the seat back.

A study of automotive seating comfort and related design factors was conducted, utilizing subjective techniques of seat comfort assessment and objective measures of the seat/subject interaction. Eight male subjects evaluated four different test seats during a short-term seating session and throughout a three-hour driving simulation. For the latter, subjects operated a static laboratory driving simulator, performing body-area discomfort evaluations at thirty-minute intervals. Cross-modality matching (CMM), a subjective assessment technique in which a stimulus is rated by matching to the level of another stimulus, was used during the long-term driving simulation to evaluate discomfort. Subject posture, muscle activity in the lower back and abdomen, and pressure levels at key support locations on the seat were monitored. In addition, a sonic digitizing system was used to record seat indentation contours and to characterize the subjects' spinal contours.

SAE Recommended Practice J941 describes the eyellipse, a statistical representation of driver eye locations, that is used to facilitate design decisions regarding vehicle interiors, including the display locations, mirror placement, and headspace requirements. Eye-position data collected recently at University of Michigan Transportation Research Institute (UMTRI) suggest that the SAE J941 practice could be improved. SAE J941 currently uses the SgRP location, seat-track travel (L23), and design seatback angle (L40) as inputs to the eyellipse model. However, UMTRI data show that the characteristics of empirical eyellipses can be predicted more accurately using seat height, steering-wheel position, and seat-track rise. A series of UMTRI studies collected eye-location data from groups of 50 to 120 drivers with statures spanning over 97 percent of the U.S. population. Data were collected in thirty-three vehicles that represent a wide range of vehicle geometry.

Standing reach envelopes are important tools for the design of industrial and vehicle environments. Previous work in this area has focussed on manikin-based (where a few manikins are used to simulate individuals reaching within the region of interest) and population-based (where data are gathered on many individuals reaching in a constrained environment) approaches. Each of these methods has merits and shortfalls. The current work bridges the manikin- and population-based approaches to assessing reach by creating population models using kinematic simulation techniques driven by anthropometric data. The approach takes into account body dimensions, balance, and postural cost to create continuous models that can be used to assess designs with respect to both maximal and submaximal reaches. Cost is quantified as the degree to which the torso is involved in the reach, since the inclination of the torso is a good measure of lower-back load and may be related to subjective reach difficulty.

Accurate representation of working postures is critical for ergonomic assessments with digital human models because posture has a dominant effect on analysis outcomes. Most current digital human modeling tools require manual manipulation of the digital human to simulate force-exertion postures or rely on optimization procedures that have not been validated. Automated posture prediction based on human data would improve the accuracy and repeatability of analyses. The effects of hand force location, magnitude, and direction on whole-body posture for standing tasks were quantified in a motion-capture study of 20 men and women with widely varying body size. A statistical analysis demonstrated that postural variables critical for the assessment of body loads can be predicted from the characteristics of the worker and task.

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.

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.

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.

Seat fit is characterized by the spatial relationship between the seat and the vehicle occupant’s body. Seat surface pressure distribution is one of the best available quantitative measures of this relationship. However, the relationships between sitter attributes, pressure, and seat fit have not been well established. The objective of this study is to model seat pressure distribution as a function of the dimensions of the seat and the occupant’s body. A laboratory study was conducted using 12 production driver seats from passenger vehicles and light trucks. Thirty-eight men and women sat in each seat in a driving mockup. Seat surface pressure distribution was measured on the seatback and cushion. Relevant anthropometric dimensions were recorded for each participant and standardized dimensions based on SAE J2732 (2008) were acquired for each test seat.

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.

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.

An appropriately contoured lumbar support is widely regarded as an essential component of a comfortable auto seat. A frequently stated objective for a lumbar support is to maintain the sitter's lumbar spine in a slightly extended, or lordotic, posture. Although sitters have been observed to sit with substantial lordosis in some short-duration testing, long-term postural interaction with a lumbar support has not been documented quantitatively in the automotive environment. A laboratory study was conducted to investigate driver posture with three seatback contours. Subjects† from four anthropometric groups operated an interactive laboratory driving simulator for one-hour trials. Posture data were collected by means of a sonic digitizing system. The data identify driver-selected postures over time for three lumbar support contours. An increase of 25 mm in the lumbar support prominence from a flat contour did not substantially change lumbar spine posture.

Prominent, longitudinally convex lumbar supports are frequently recommended for auto seats based on the assumption that such supports will induce sitters to choose postures with substantial lumbar lordosis. Lumbar lordosis has been associated with reduced spine loading as measured by pressure in the intervertebral disks. Data from a laboratory study of the influence of lumbar support on driving posture demonstrate that, on average, lumbar lordosis is not strongly affected by large increases in lumbar support prominence. These findings, and their implications for seat design, are reviewed.

Data from the 1990 U.S. Nationwide Personal Transportation Survey were analyzed to determine the distribution of trip durations and sitting times for use in the design of automobile seat comfort studies. Two measures relating to the incidence and prevalence of long-term sitting were calculated and presented for the U.S. population and various subgroups. The information can be used to select an appropriate test duration for comfort studies. The subgroup data allow the test duration to be tailored for specific market segments.

For many industrial tasks (push, pull, lift, carry, etc.), restrictions on grip locations and visibility constrain the hand and head positions and help to define feasible postures. In contrast, foot locations are often minimally constrained and an ergonomics analyst can choose several different stances in selecting a posture to analyze. Also, because stance can be a critical determinant of a biomechanical assessment of the work posture, the lack of a valid method for placing the feet of a manikin with respect to the task compromises the accuracy of the analysis. To address this issue, foot locations and orientations were captured in a laboratory study of sagittal plane and asymmetric manual load transfers. A pilot study with four volunteers of varying anthropometry approached a load located on one of three shelves and transferred the load to one of six shelves.

Simulations of humans performing seated reaches require accurate descriptions of the movements of the body segments that make up the torso. Data to generate such simulations were obtained in a laboratory study using industrial, auto, and truck seats. Twelve men and women reached to push-button targets located throughout their right-hand reach envelopes as their movements were recorded using an electromagnetic tracking system. The data illustrate complex patterns of motion that depend on target location and shoulder range of motion. Pelvis motion contributes substantially to seated reach capability. On padded seats, the effective center of rotation of the pelvis is often within the seat cushion below the pelvis rather than at the hips. Lumbar spine motions differ markedly depending on the location of the target. A categorization of reach targets into four zones differentiated by torso kinematics is proposed.

Human figure models are commonly used to facilitate ergonomic assessments of vehicle driver stations and other workplaces. One routine method of workstation assessment is to conduct a suite of ergonomic analyses using a family of boundary manikins, chosen to represent a range of anthropometric extremes on several dimensions. The suitability of the resulting analysis depends both on the methods by which the boundary manikins are selected and on the methods used to posture the manikins. The automobile driver station design problem is used to examine the relative importance of anthropometric and postural variability in ergonomic assessments. Postural variability is demonstrated to be nearly as important as anthropometric variability when the operator is allowed a substantial range of component adjustment. The consequences for boundary manikin procedures are discussed, as well as methods for conducting accurate and complete assessments using the available tools.

The WorldSID project is a global effort to design a new generation side impact crash test dummy under the direction of the International Organization for Standardization (ISO). The first WorldSID crash dummy will represent a world-harmonized mid-size adult male. This paper discusses the research and rationale undertaken to define the anthropometry of a world standard midsize male in the typical automotive seated posture. Various anthropometry databases are compared region by region and in terms of the key dimensions needed for crash dummy design. The Anthropometry for Motor Vehicle Occupants (AMVO) dataset, as established by the University of Michigan Transportation Research Institute (UMTRI), is selected as the basis for the WorldSID mid-size male, updated to include revisions to the pelvis bone location. The proposed mass of the dummy is 77.3kg with full arms. The rationale for the selected mass is discussed. The joint location and surface landmark database is appended to this paper.

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.