Statistical Models for Predicting Automobile Driving Postures for Men and Women Including Effects of Age.

Abstract

Previously published statistical models of driving posture have been effective for vehicle design but have not taken into account the effects of age. The present study developed new statistical models for predicting driving posture. 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. 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. 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. The posture-prediction models can be used to position computational human models or crash-test dummies for vehicle design and assessment.