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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.

Seat belt anchorage locations have a strong effect on occupant protection. Federal Motor Vehicle Safety Standard (FMVSS) 210 specifies requirements for the layout of the anchorages relative to the seating reference point and seat back angle established by the SAE J826 H-point manikin. Sled testing and computational simulation has established that belt anchorage locations have a strong effect on occupant kinematics, particularly for child occupants using the belt as their primary restraint. As part of a larger study of vehicle geometry, the locations of the anchorage points in the second-row, outboard seating positions of 83 passenger cars and light trucks with a median model year of 2005 were measured. The lower anchorage locations spanned the entire range of lap belt angles permissible under FMVSS 210 and the upper anchorages (D-ring locations) were distributed widely as well.

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.

Four unembalmed human cadavers were used in eight direct-forearm-airbag-interaction static deployments to assess the relative aggressivity of two different airbag modules. Instrumentation of the forearm bones included triaxial accelerometry, crack detection gages, and film targets. The forearm-fracture predictors, peak and average distal forearm speed (PDFS and ADFS), were evaluated and compared to the incidence of transverse, oblique, and wedge fractures of the radius and ulna. Internal-airbag pressure and axial column loads were also measured. The results of this study support the use of PDFS or ADFS for the prediction of airbag-induced upper-extremity fractures. The results also suggest that there is no direct relationship between internal-airbag pressure and forearm fracture. The less-aggressive system (LAS) examined in this study produced half the number of forearm fracture as the more-aggressive system (MAS), yet exhibited a more aggressive internal-pressure performance.

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.

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.

Contact between the knees and knee bolster commonly occurs in frontal collisions. The contact region on the bolster and the knee anatomy involved are related to the pre-crash positioning of the knees. The location of the distal (or infra-) patella was recorded on volunteers of widely varying stature after they had selected a comfortable driving position in mockups of three vehicles representing a large variation in size and shape: sedan, crossover SUV, and full-size pickup. On average, the right knees were grouped more tightly and were located more forward and lower than the left knees. On average, the knees were positioned 200 mm from the knee bolster for all subjects. The range of distance separating the distal patellae (within subject knee-to-knee distance) varied from 184–559 mm for all subjects for the three vehicles.

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.

Assessments of reach capability using human figure models are commonly performed by exercising each joint of a kinematic chain, terminating in the hand, through the associated ranges of motion. The result is a reach envelope determined entirely by the segment lengths, joint degrees of freedom, and joint ranges of motion. In this paper, the validity of this approach is assessed by comparing the reach envelopes obtained by this method to those obtained in a laboratory study of men and women. Figures were created in the Jack human modeling software to represent the kinematic linkages of participants in the laboratory study. Maximum reach was predicted using the software's kinematic reach-envelope generation methods and by interactive manipulation. Predictions were compared to maximum reach envelopes obtained experimentally. The findings indicate that several changes to the normal procedures for obtaining maximum reach envelopes for seated tasks are needed.

Effective application of human figure models to truck interior design requires accurate data on the postures and positions of truck drivers. Errors in positioning of figure models propagate to errors in reach, visibility, and other analyses. This paper describes methods used in a recent study to measure in-vehicle driving postures in Class 6, 7, and 8 trucks. A three-dimensional coordinate measurement machine was used to measure body landmark locations after a driver completed a short road course. The data were used to validate posture-prediction models developed in a previous laboratory study. Vehicle calibration, driver selection, and testing methods are reviewed.

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.

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.

A person's ability to perform a task is often limited by their ability to maintain balance. This is particularly true in lateral work performed in seated environments. For a truck driver operating the shift lever of a manual transmission, excessive shift forces can necessitate pulling on the steering wheel with the other hand to maintain balance, creating a potentially unsafe condition. An analysis of posture and balance in truck shifter operation was conducted using balance limits to define the acceptable range of shifter locations. The results are dependent on initial driver position, reach postures, and shoulder strength. The effects of shifter force direction and magnitude were explored to demonstrate the application of the analysis method. This methodology can readily be applied to other problems involving hand-force exertions in seated environments.

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.

Vehicle motions can adversely affect the ability of a driver or occupant to quickly and accurately push control buttons located in many advanced vehicle control, navigation and communications systems. A pilot study was conducted using the U.S. Army Tank Automotive and Armaments Command (TACOM) Ride Motion Simulator (RMS) to assess the effects of vertical ride motion on the kinematics of reaching. The RMS was programmed to produce 0.5 g and 0.8 g peak-to-peak sinusoidal inputs at the seat-sitter interface over a range of frequencies. Two participants performed seated reaching tasks to locations typical of in-vehicle controls under static conditions and with single-frequency inputs between 0 and 10 Hz. The participants also held terminal reach postures during 0.5 to 32 Hz sine sweeps. Reach kinematics were recorded using a 10-camera VICON motion capture system. The effects of vertical ride motion on movement time, accuracy, and subjective responses were assessed.

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.