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Eight whole fresh-frozen cadavers (6 female, 2 male) that were elderly and/or female were laterally impacted using UMTRI's dual-sled side-impact test facility. Cadavers were not excluded on the basis of old age or bone diseases that affect tolerance. A thinly padded, multi-segment impactor was used that independently measured force histories applied to the shoulder, thorax, abdomen, greater trochanter, iliac wing, and femur of each PMHS. Impactor plates were adjusted vertically and laterally toward the subject so that contact with body regions occurred simultaneously and so that each segment contacted the same region on every subject. This configuration minimized the effects of body shape on load sharing between regions. Prior to all tests, cadavers were CT scanned to check for pre-existing skeletal injuries. Cadavers were excluded if they had pre-existing rib fractures or had undergone CPR.

Lateral impact tests were performed using seven male post-mortem human subjects (PMHS) to characterize the force-deflection response of contacted body regions, including the lower abdomen. All tests were performed using a dual-sled, side-impact test facility. A segmented impactor was mounted on a sled that was pneumatically accelerated into a second, initially stationary sled on which a subject was seated facing perpendicular to the direction of impact. Positions of impactor segments were adjusted for each subject so that forces applied to different anatomic regions, including thorax, abdomen, greater trochanter, iliac wing, and thigh, could be independently measured on each PMHS. The impactor contact surfaces were located in the same vertical plane, except that the abdomen plate was offset 5.1 cm towards the subject.

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.

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.

Turn signals mounted on exterior rearview mirrors are increasingly being used as original equipment on passenger cars and light trucks. The potential for mirror-mounted turn signals (MMTS) to improve the geometric visibility of turn signals is examined in this paper. A survey of U.S. and UN-ECE regulations showed that the turn signals of a vehicle that is minimally compliant with U.S. regulations are not visible to a driver of a nearby vehicle in an adjacent lane. Measurements of mirror location and window geometry were made on 74 passenger cars and light trucks, including 38 vehicles with fender-mounted turn signals (FMTS). These data were combined with data on driver eye locations from two previous studies to assess the relative visibility of MMTS and conventional signals. Simulations were conducted to examine the potential for signals to be obstructed when a driver looks laterally through the passenger-side window.

Late model passenger cars and light trucks incorporate occupant protection systems with airbags and knee restraints. Knee restraints have been designed principally to meet the unbelted portions of FMVSS 208 that require femur load limits of 10-kN to be met in barrier crashes up to 30 mph, +/- 30 degrees utilizing the 50% male Anthropomorphic Test Device (ATD). In addition, knee restraints provide additional lower-torso restraint for belt-restrained occupants in higher-severity crashes. An analysis of frontal crashes in the University of Michigan Crash Injury Research and Engineering Network (UM CIREN) database was performed to determine the influence of vehicle, crash and occupant parameters on knee, thigh, and hip injuries. The data sample consists of drivers and right front passengers involved in frontal crashes who sustained significant injuries (Abbreviated Injury Scale [AIS] ≥ 3 or two or more AIS ≥ 2) to any body region.

A new method is presented for physically measuring drivers' field of view in rearview mirrors. A portable coordinate measurement apparatus (FARO Arm) is used to measure the mirror locations, contours, and curvature. Measurements of the driver's head and eye locations while looking into each mirror are also made. Raytracing is used to map the two- or three-dimensional field of view in each mirror. The method differentiates between monocular, binocular, and ambinocular fields of view, and can account for head movements. This method has been applied to passenger cars, light trucks, and heavy trucks to document how drivers aim their mirrors during normal use.

The National Highway Traffic Safety Administration and the University of Michigan Transportation Institute are investigating truck design countermeasures to provide safety benefits during collisions with light vehicles. The goal is to identify approaches that would best balance costs and benefits. This paper outlines the first phase of this study, an analysis of two-vehicle, truck/light vehicle crashes from 1996 through 1998 using several crash data bases to obtain a current description and determine the scope of the aggressivity problem. Truck fronts account for 60% of light vehicle fatalities in collisions with trucks. Collision with the front of a truck carries the highest probability of fatal (K) or incapacitating (A) injury. Truck sides account for about the same number of K and A-injuries combined as truck fronts, though injury probability is substantially lower than in crashes involving the front of a truck.

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.

Most human figure models used in ergonomic analyses present postural comfort ratings based on joint angles, and present a single comfort score for the whole body or on a joint-by-joint basis. The source data for these ratings is generally derived from laboratory studies that link posture to ratings. Lacking in many of these models is a thorough treatment of the distribution of ratings for the population of users. Information about ratings distributions is necessary to make cost-effective tradeoffs when design changes affect subjective responses. This paper presents experimental and analytic methods used to develop distribution models for incorporating subjective rating data in ergonomic assessments.

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.

For the 1997 data year, UMTRI's Center for National Truck Statistics collected data on rear underride as part of its Trucks Involved in Fatal Accidents (TIFA) survey. Data collected included whether the truck had a rear underride guard, whether the striking vehicle underrode the truck, and how much underride occurred. A primary goal was to evaluate rear underride of straight trucks. Overall, 453 medium and heavy trucks were struck in the rear by a nontruck vehicle in a fatal crash in 1997. Some underride occurred in at least 272 (60.0%) of the rear-end crashes. For straight trucks, there was some underride in 77 (52.0%) of the crashes, no underride occurred in 43 (29.1%) of the fatal rear-end crashes, and underride could not be determined in the remaining 28 (18.9%) straight truck rear-end crashes. Despite the fact that three-fourths of tractor combinations had an underride guard on the trailer, underride was more common for tractor combinations.

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.

An easy-to-use computer program for ride analysis was recently developed. The result of this effort-RideSim- predicts time history responses, power spectral density (PSD) functions, and a driver oriented measure of ride comfort. RideSim employs a graphical user interface (called SGUI, for simulation graphical user interface) to control data preparation, simulation execution, animation, and data analysis. The SGUI allows the user to operate the program by pointing and clicking with a mouse, rather than by using cumbersome text commands. It also manages the vehicle dynamics parameters, the resulting simulation output, and results of post-processing analyses (i.e., PSD analysis). The vehicle dynamics model was generated with the AUTOSIM multibody dynamics program. This program uses Kane’s Method and computer algebra to create a parametric dynamics simulation that can be easily linked to the SGUI.

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 (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.

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.

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.

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.