Motion scaling for high-performance driving simulators

Alain Berthoz, Willem Bles, H. H. Bülthoff, B. J.Correia Grácio, Philippus Feenstra, Nicolas Filliard, R. Hühne, Andras Kemeny, M. Mayrhofer, M. Mulder, H. G. Nusseck, P. Pretto, Gilles Reymond, R. Schlüsselberger, J. Schwandtner, H. Teufel, Benjamin Vailleau, M. M.René Van Paassen, Manuel Vidal, Mark Wentink

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)

Abstract

Advanced driving simulators aim at rendering the motion of a vehicle with maximum fidelity, which requires increased mechanical travel, size, and cost of the system. Motion cueing algorithms reduce the motion envelope by taking advantage of limitations in human motion perception, and the most commonly employed method is just to scale down the physical motion. However, little is known on the effects of motion scaling on motion perception and on actual driving performance. This paper presents the results of a European collaborative project, which explored different motion scale factors in a slalom driving task. Three state-of-the-art simulator systems were used, which were capable of generating displacements of several meters. The results of four comparable driving experiments, which were obtained with a total of 65 participants, indicate a preference for motion scale factors below 1, within a wide range of acceptable values (0.4-0.75). Very reduced or absent motion cues significantly degrade driving performance. Applications of this research are discussed for the design of motion systems and cueing algorithms for driving simulation.

Original languageEnglish
Article numberA1
Pages (from-to)265-276
Number of pages12
JournalIEEE Transactions on Human-Machine Systems
Volume43
Issue number3
DOIs
Publication statusPublished - 2013 May

Keywords

  • Human factors
  • Road vehicles
  • Virtual reality

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Control and Systems Engineering
  • Signal Processing
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

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