Maneuver Prediction and Prepositioning for Lateral and Yaw Motion Cueing

This study investigates the effectiveness of vehicle dynamics and road environment data for predicting lateral accelerations and yaw rates. This prediction is used to preposition a simulator in anticipation of this motion. A prediction model was created using the road curvature at a specific look-ahead<br/>time and the current vehicle velocity....

Probabilistic Maneuver Prediction for Motion Cueing in Driving Simulation

Potential usage of the workspace of driving simulators is restricted by a lack of knowledge on oncoming maneuvers, due to the unpredictable nature of human drivers. This research aims to explore the possibility of using information from driver inputs, dynamic vehicle states, and features of the road environment to improve motion cueing through...

Simulator motion cueing error detection using a wavelet-based algorithm

Understanding the process of human motion perception is essential for optimizing the motion cueing algorithms (MCAs) used by motion simulators. Previous research has shown that different motion cueing error types can be distinguished, at least some of which are rated differently by humans for equal error magnitude. Optimizing a motion simulation...