Driving simulators play an important role in the development of new vehicles and advanced driver assistance devices. In fact, on the one hand, having a human driver on a driving simulator allows automotive OEMs to bridge the gap between virtual prototyping and on-road testing during the vehicle development phase. On the other hand, novel driver assistance systems (such as advanced accident avoidance systems) can be safely tested by having the driver operating the vehicle in a virtual, highly realistic environment, while being exposed to hazardous situations. In both applications, it is crucial to faithfully reproduce in the simulator the drivers perception of forces acting on the vehicle and its acceleration. The strategy used to operate the simulator platform within its limited working space to provide the driver with the most realistic perception goes under the name of motion cueing. In this paper we describe a novel approach to motion cueing design that is based on Model Predictive Control techniques. Two features characterize the algorithm, namely, the use of a detailed model of the human vestibular system and a predictive strategy based on the availability of a virtual driver. Differently from classical schemes based on washout filters, such features allows a better implementation of tilt coordination and to handle more efficiently the platform limits.


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    Title :

    An MPC approach to the design of motion cueing algorithms for driving simulators


    Contributors:
    Baseggio, M. (author) / Beghi, A. (author) / Bruschetta, M. (author) / Maran, F. (author) / Minen, D. (author)


    Publication date :

    2011-10-01


    Size :

    1691360 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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