Optimizing an Optimization-Based MCA using Perceived Motion Incongruence Models

D. Cleij, D.M. Pool, Max Mulder, Heinrich H. Bülthoff

Research output: Contribution to conferencePaperpeer-review

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Abstract

In this paper the potential of Motion Incongruence Rating (MIR) models for the optimization of Motion Cueing Algorithms (MCAs) is investigated. In a human-in-the-loop simulator experiment, two optimization-based MCAs are compared for a roundabout scenario simulated on a medium-stroke hexapod simulator. The first MCA uses standard cueing error weights from reference literature in its cost function, while for the second case these weights were based on a MIR model fitted to previous experiment data. Results show that such models provide a promising cueing error weight estimation method for optimization-based MCAs, but also highlight the limitations of these models due to, for example, their dependency on the richness of the datasets to which they are fitted.
Original languageEnglish
Number of pages8
Publication statusPublished - 2020
EventDriving Simulation Conference Europe 2020 VR - Antibes, France
Duration: 9 Sep 202011 Sep 2020
Conference number: 19
https://dsc2020.org/

Conference

ConferenceDriving Simulation Conference Europe 2020 VR
Abbreviated titleDSC 2020 Europe
CountryFrance
CityAntibes
Period9/09/2011/09/20
Internet address

Keywords

  • Motion cueing algorithms
  • motion incongruence models
  • model predictive control
  • continuous ratings

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