@article{ref1,
title="Statistical models for predicting automobile driving postures for men and women including effects of age",
journal="Human factors",
year="2015",
author="Park, Jangwoon and Ebert, Sheila M. and Reed, Matthew P. and Hallman, Jason J.",
volume="58",
number="2",
pages="261-278",
abstract="BACKGROUND: Previously published statistical models of driving posture have been effective for vehicle design but have not taken into account the effects of age. <br><br>OBJECTIVE: The present study developed new statistical models for predicting driving posture. <br><br>METHODS: Driving postures of 90 U.S. drivers with a wide range of age and body size were measured in laboratory mockup in nine package conditions. Posture-prediction models for female and male drivers were separately developed by employing a stepwise regression technique using age, body dimensions, vehicle package conditions, and two-way interactions, among other variables. <br><br>RESULTS: Driving posture was significantly associated with age, and the effects of other variables depended on age. A set of posture-prediction models is presented for women and men. The results are compared with a previously developed model. <br><br>CONCLUSION: The present study is the first study of driver posture to include a large cohort of older drivers and the first to report a significant effect of age. APPLICATION: The posture-prediction models can be used to position computational human models or crash-test dummies for vehicle design and assessment.<p /> <p>Language: en</p>",
language="en",
issn="0018-7208",
doi="10.1177/0018720815610249",
url="http://dx.doi.org/10.1177/0018720815610249"
}