Aside the capital investment and without the ability to otherwise simulate, motion capture is the preferred method by which to model human movements in a digital environment. However, these capture sessions are almost universally conducted in stationary environments. While this may be adequate for modeling many industrial applications of digital modeling, many other jobs require operators to perform tasks while being exposed to a moving environment (e.g. postal drivers, flight attendants, and numerous military and transportation operations). The Ride Motion Simulator (RMS) at the US Army-Tank Automotive and armaments Command (TACOM) simulated single-axis sinusoids and 6DOF ride motion, in which twelve participants were asked to perform extended reaches to eight push-button targets. In order to better ascertain the effects of dynamic ride motion on in-vehicle reaching tasks, we used a twelve-camera VICON optical motion capture system to record and UGS PLM Solutions' JACK to analyze the associated kinematic and kinetic motions. Recent studies have presented methodologies and results from motion capture studies of human reach performance under ride motion perturbation (Rider et al. 2003a, 2003b). Additional studies are underway to augment the development of regression models predicting movement time and the required target size based on task and ride conditions. Results of the reach data reveal the critical nature of the design and layout of controls, with respect to torso-included motions, ellipsoid-shaped buttons, and an increase in movement time required to successfully complete an in-vehicle task under ride motion.