Increasing motion fidelity in driving simulators using a fuzzy-based washout filter

The motion cueing algorithm is the procedure used to regenerate vehicle motion cues by transforming translational and rotational motions of a simulated vehicle into the simulator motion such that high fidelity motions can be generated through a washout filter. Classical washout filters are widely being used in different motion simulators because of their low computational load, simplicity, and functionality. However, they have a number of disadvantages that make them unreliable in some cases. One of the main disadvantages is its parameter selecting procedure, which is based on trial-and-error and the worst case driving scenario. In addition, the washout filter parameters are kept constant during different driving scenarios, causing inflexibility of the filter design. This causes conservative platform workspace usage and as a result false motion cues. Furthermore, the mathematical model of human motion sensation plays no role in designing of the classical washout filter. Ignorance of the online information about physical limitations of the platform and the simulator driver motion sensation factors are other main drawbacks of classical washout filters. The aim of this research is to provide a fuzzy logic-based washout filter that considers the motion sensation error between the real vehicle and simulator drivers as well as the distance of the simulator platform from its physical boundaries to correct false motion cues and decrease human sensation errors. The proposed fuzzy-based washout filter also seeks to increase motion fidelity and enable the simulator to use the platform workspace more efficiently. The simulation results show the efficiency of the proposed fuzzy-based washout filter in reducing the human sensation error and enhancing efficiency of the simulator platform workspace usage.