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  Measuring, modelling and minimizing perceived motion incongruence for vehicle motion simulation

Cleij, D. (2020). Measuring, modelling and minimizing perceived motion incongruence for vehicle motion simulation. Berlin, Germany: Logos Verlag.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0006-A927-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0006-A928-F
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 Creators:
Cleij, D1, 2, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Humans always wanted to go faster and higher than their own legs could carry them. This led them to invent numerous types of vehicles to move fast over land, water and air. As training how to handle such vehicles and testing new developments can be dangerous and costly, vehicle motion simulators were invented. Motion-based simulators in particular, combine visual and physical motion cues to provide occupants with a feeling of being in the real vehicle. While visual cues are generally not limited in amplitude, physical cues certainly are, due to the limited simulator motion space. A motion cueing algorithm (MCA) is used to map the vehicle motions onto the simulator motion space. This mapping inherently creates mismatches between the visual and physical motion cues. Due to imperfections in the human perceptual system, not all visual/physical cueing mismatches are perceived. However, if a mismatch is perceived, it can impair the simulation realism and even cause simulator sickness. For MCA design, a good understanding of when mismatches are perceived, and ways to prevent these from occurring, are therefore essential. In this thesis a data-driven approach, using continuous subjective measures of the time-varying Perceived Motion Incongruence (PMI), is adopted. PMI in this case refers to the effect that perceived mismatches between visual and physical motion cues have on the resulting simulator realism. The main goal of this thesis was to develop an MCA-independent off-line prediction method for time-varying PMI during vehicle motion simulation, with the aim of improving motion cueing quality. To this end, a complete roadmap, describing how to measure and model PMI and how to apply such models to predict and minimize PMI in motion simulations is presented. Results from several human-in-the-loop experiments are used to demonstrate the potential of this novel approach.

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 Dates: 2020
 Publication Status: Published in print
 Pages: 294
 Publishing info: Berlin, Germany : Logos Verlag
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 Rev. Type: -
 Identifiers: ISBN: 978-3-8325-5044-8
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Title: MPI Series in Biological Cybernetics
Source Genre: Series
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Pages: - Volume / Issue: 57 Sequence Number: - Start / End Page: - Identifier: -