Citation: GARRETT, N.J.I. and BEST, M.C., 2013. Model predictive driving simulator motion cueing algorithm with actuator-based constraints. Vehicle System Dynamics, 51 (8) AbstractThe simulator motion cueing problem has been considered extensively in the literature; approaches based on linear filtering and optimal control have been presented and shown to perform reasonably well. More recently, Model Predictive Control (MPC) has been considered as a variant on the optimal control approach; MPC is perhaps an obvious candidate for motion cueing due to its ability to deal with constraints, in this case the platform workspace boundary.This paper presents an MPC-based cueing algorithm that, unlike other algorithms, uses the actuator positions and velocities as the constraints. The result is a cueing algorithm that can make better use of the platform workspace whilst ensuring that its bounds are never exceeded. The algorithm is shown to perform well against the classical cueing algorithm and an algorithm previously proposed by the authors in simulation and in tests with human drivers.

Evaluation of a new body-sideslip-based driving simulator motion cueing algorithm Nikhil JI Garrett and Matthew C Best Abstract This paper describes a new motion cueing algorithm for motion-based driving simulators. The algorithm uses the simulated vehicle's body sideslip angle as the demand for the motion platform's yaw degree of freedom. The current state of the art for motion cueing algorithms involves some form of filter or controller that limits the bandwidth of the vehicle motion before using this as the motion platform demand; the algorithm is tuned such that the platform does not exceed its limits. However, this means that information about the vehicle state that is contained within the motion is removed indiscriminately. Since the body sideslip angle will fit within the platform yaw limit under normal conditions, it does not need to be filtered beforehand, and thus no information must be removed. The implementation of the body-sideslipbased algorithm is described, as is a set of tests using human participants wherein the body sideslip algorithm was compared against the three most popular existing algorithms (namely the classical, adaptive and linear quadratic regulator algorithms) for normal road driving. The results of these tests indicate that the body sideslip algorithm performs as well as, or marginally better than, the other algorithms; future work will test the algorithm under limit handling conditions, to see whether the approach of preserving vehicle state information improves the simulator driver's perception.