New Motion Cueing Algorithm for Improved Evaluation of Vehicle Dynamics on a Driving Simulator

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Event
WCX™ 17: SAE World Congress Experience
Authors Abstract
Content
In recent years, driving simulators have become a valuable tool in the automotive design and testing process. Yet, in the field of vehicle dynamics, most decisions are still based on test drives in real cars. One reason for this situation can be found in the fact that many driving simulators do not allow the driver to evaluate the handling qualities of a simulated vehicle. In a driving simulator, the motion cueing algorithm tries to represent the vehicle motion within the constrained motion envelope of the motion platform. By nature, this process leads to so called false cues where the motion of the platform is not in phase or moving in a different direction with respect to the vehicle motion. In a driving simulator with classical filter-based motion cueing, false cues make it considerably more difficult for the driver to rate vehicle dynamics. A team with members from the University of Stuttgart, Cruden B.V., and AUDI AG developed a new motion cueing methodology for the use in a driving simulator dedicated to vehicle dynamics. The new algorithm is a track based approach that makes use of the vehicle’s position on the track and does not use high-pass filters. It therefore allows minimization of false cues, thereby giving the driver the best possible information on the handling qualities of the car. In this paper, the basic principles of the algorithm are described, as well as the implementation in a driving simulator. Comparison with data from a handling track shows the advantages of the new methodology over the classical motion cueing approach.
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DOI
https://doi.org/10.4271/2017-01-1566
Pages
10
Citation
Brems, W., Kruithof, N., Uhlmann, R., Wagner, A. et al., "New Motion Cueing Algorithm for Improved Evaluation of Vehicle Dynamics on a Driving Simulator," SAE Int. J. Veh. Dyn., Stab., and NVH 1(2):253-262, 2017, https://doi.org/10.4271/2017-01-1566.
Additional Details
Publisher
Published
Mar 28, 2017
Product Code
2017-01-1566
Content Type
Journal Article
Language
English