Refine Your Search

Search Results

Viewing 1 to 9 of 9
Technical Paper

Development of an Improved Driver Eye Position Model

1998-02-23
980012
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.
Technical Paper

Knee, Thigh and Hip Injury Patterns for Drivers and Right Front Passengers in Frontal Impacts

2003-03-03
2003-01-0164
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.
Technical Paper

Comparison of Methods for Predicting Automobile Driver Posture

2000-06-06
2000-01-2180
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.
Technical Paper

Design and Development of the ASPECT Manikin

1999-03-01
1999-01-0963
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.
Technical Paper

ASPECT Manikin Applications and Measurements for Design, Audit, and Benchmarking

1999-03-01
1999-01-0965
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.
Technical Paper

Automobile Occupant Posture Prediction for Use with Human Models

1999-03-01
1999-01-0966
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.
Technical Paper

Investigating Driver Headroom Perception: Methods and Models

1999-03-01
1999-01-0893
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.
Technical Paper

Comparison of Airbag-Aggressivity Predictors in Relation to Forearm Fractures

1998-02-23
980856
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.
Technical Paper

An Improved Seating Accommodation Model with Application to Different User Populations

1998-02-23
980651
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.
X