A real time implementation of MPC based motion cueing strategy for driving simulators

Driving simulators are widely used in many different applications, such as driver training, vehicle development, and medical studies. To fully exploit the potential of such devices, it is crucial to develop platform motion control strategies that generate realistic driving feelings. This has to be achieved while keeping the platform within its limited operation space. Such strategies go under the name of motion cueing algorithms. In this paper a particular implementation of a motion cueing algorithm is described, that is based on Model Predictive Control technique. A distinctive feature of such approach is that it exploits a detailed model of the human vestibular system, and consequently differs from standard motion cueing strategies based on washout filters. The algorithm has been evaluated experimentally on a small-size, innovative platform, by performing tests with professional drivers. Results show that the MPC-based motion cueing algorithm allows to effectively handle the platform working area, to limit the presence of those platform movements that are typically associated to driver motion sickness, and to devise simple and intuitive tuning procedures.