Evaluation of a new body-sideslip-based driving simulator motion cueing algorithm

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-sideslip-based 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.