VI-MotionCueing enables to accurately reproduce the driver’s feelings, which is an essential aspect to fully perceive the dynamics of each vehicle model and its variants on a dynamic driving simulator.
VI-MotionCueing, developed in collaboration with the University of Padova (Italy), is based on an innovative algorithm which, given vehicle translational accelerations and rotational velocities, converts them into admissible movements of the driver’s seat, for any motion platform architecture.
VI-MotionCueing is based on Model Predictive Control (MPC), a methodology that allows implementing a mathematical model of the vestibular motion perception and of the platform structure.
Tuning of VI-MotionCueing can be performed by modifying a set of parameters to achieve a satisfactory trade-off between best perception and the respect of the working area. Among them, it is possible to separately tune each direction of motion, the length of prediction horizon, the range of dynamics within which the algorithm operates.
Compared to the so-called “classical” approach, the usage of MPC allows to limit the platform motion without affecting the driver perception. Moreover the typical shortcomings of the “classical approach”, among which the generation of opposite sign acceleration (motion inversion) and the necessity of empirical tuning, are overcome.
Further advantages are:
Improved consistency between real vehicle dynamics and platform movements;
Possibility to take into account the hard constraints of the platform (displacements, velocities, acceleration);
Possibility to perform efficient prepositioning
Realistic motion platform movements (on all types of motion platforms)
Algorithm based on model predictive control that minimizes motion sickness
Better driver experience
Effectively handles limits of the working space
Possibility of anticipating platform positioning based on vehicle dynamics prediction
Overcomes the problem of motion inversion
Respects the physics of the vehicle chassis motion without introducing empirical filters