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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.

Five different nonplanar mirrors were evaluated as driver-side rearview mirrors in a field test using Ford employees. Two were spherical convex (differing in radius of curvature), and three were aspheric (differing primarily in the proportion of their surfaces over which radius of curvature was variable). Each participant drove for four weeks with one of the nonplanar mirrors. At three times during the test the participants filled out questionnaires concerning their experience with the mirrors. Driver preferences for the experimental mirrors increased moderately between surveys at one week and at four weeks. At four weeks, all five nonplanar mirrors were preferred to the standard flat mirror by at least a small amount. For each of the five mirror designs there was a large range of opinion. Most notably, a small number of people strongly disliked the aspheric design that involved the largest variable-radius area.

Current anthropomorphic test device (ATD) positioning procedures for drivers and front-seat passengers place the crash dummy within the vehicle by reference to the seat track. Midsize-male ATDs are placed at the center of the fore-aft seat track adjustment range, while small-female and large-male ATDs are placed at the front and rear of the seat track, respectively. Research on occupant positioning at UMTRI led to the development of a new ATD positioning procedure that places the ATDs at positions more representative of the driving positions of people who match the ATD's body dimensions. This paper presents a revised version of the UMTRI ATD positioning procedure. The changes to the procedure improve the ease and repeatability of ATD positioning while preserving the accuracy of the resulting ATD positions with respect to the driving positions of people matching the ATD anthropometry.

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.

Dynamic seat-position testing conducted recently at UMTRI on several different vehicles indicates that, in many cases, the current seating accommodation model represented in SAE J1517 does not accurately predict the distribution of driver seat positions. In general, J1517 tends to predict population percentile seat positions that are forward of observed percentile seat positions, and differences can be as much as 60 mm. It was hypothesized that vehicle factors other than seat height can have substantial and independent effects on driver seat position. The effects of steering-wheel position, seat height, seat-cushion angle, and transmission type on driver fore/aft seat position are being investigated, and results are being used to develop a new driver seating accommodation model called SAM.

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.

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.

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.

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.

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.

Current ATD positioning practices depend on seat track position, seat track travel range, and design seatback angle to determine appropriate occupant position and orientation for impact testing. In a series of studies conducted at the University of Michigan Transportation Research Institute, driver posture and position data were collected in forty-four vehicles. The seat track reference points currently used to position ATDs (front, center, and rear of the track) were found to be poor predictors of the average seat positions selected by small female, midsize male, and large male drivers. Driver-selected seatback angle was not closely related to design seatback angle, the measure currently used to orient the ATD torso. A new ATD Positioning Model was developed that more accurately represents the seated posture and position of drivers who match the ATD statures.

The NASS-CDS (1998-2008) and CIREN datasets were analyzed to identify factors contributing to abdominal injury in crash environments where belt use and airbag deployment are common. In frontal impacts, the percentage of occupants sustaining abdominal injury is three times higher for unbelted compared to belted front-row adult occupants (p≺0.0001) at both AIS2+ and AIS3+ injury levels. Airbag deployment does not substantially affect the percentage of occupants who sustain abdominal injuries in frontal impacts (p=0.6171), while belt use reduces the percentage of occupants sustaining abdominal injury in both nearside and farside crashes (p≺0.0001). Right-front passengers in right-side impacts have the highest risk (1.91%) of AIS 3+ abdominal injury (p=0.03). The percentage of occupants with AIS 3+ abdominal injuries does not vary with age for frontal, nearside, or farside impacts.

In the mid 1970s, UMTRI investigated the biomechanical properties of the head and neck using 180 “normal” adult subjects selected to fill eighteen subject groups based on age (young, mid-aged, older), gender, and stature (short, medium, and tall by gender). Lateral-view radiographs of the subjects’ cervical spines and heads were taken with the subjects seated in a simulated automotive neutral posture, as well as with their necks in full-voluntary flexion and full-voluntary extension. Although the cervical spine and lower head geometry were previously measured manually and documented, new technologies have enabled computer digitization of the scanned x-ray images and a more comprehensive and detailed analysis of the variation in cervical spine and lower head geometry with subject age, stature, and gender. After scanning the radiographic images, 108 skeletal landmarks on the cervical vertebrae and 10 head landmarks were digitized.