Optimization-based Motion Cueing Algorithm for Worst Case Maneuvers in Driving Simulation

@inproceedings{Jacumet2025,
title = {Optimization-based Motion Cueing Algorithm for Worst Case Maneuvers in Driving Simulation},
author = {Robert Jacumet and Janik Wetzel and Sebastian Wagner and Markus Schwienbacher and Dirk Wollherr and Marion Leibold
},
editor = {Andras Kemeny and Jean-Rémy Chardonnet and Florent Colombet and Stéphane Espié},
doi = {https://doi.org/10.82157/dsa/2025/20},
isbn = {978-2-9573777-7-0},
year  = {2025},
date = {2025-09-24},
booktitle = {Proceedings of the Driving Simulation Conference 2025 Europe XR},
pages = {163-168},
address = {Stuttgart, Germany},
organization = {Driving Simulation Association},
abstract = {Driving simulator motion systems are controlled by Motion Cueing Algorithms (MCAs), which aim to create a realistic motion experience. Optimization-based MCAs, being the most promising in terms of motion cueing quality, aim to minimize the cueing error between the vehicle motion and the simulator motion at each timestep. Motivated by recent findings that suggest the worst motion recreation during simulated driving dominates the overall perception of realism, we propose a methodology for optimizing motion cueing quality during these worst case moments. In the proposed three step open-loop framework, first, a baseline motion is computed and the worst case moments are found. Subsequently, the optimization is performed twice more, focusing on motions that cause ratings above the mean rating and windows of expected worst ratings, respectively. This methodology can be appended to general open-loop optimization-based MCAs. While the developed MCA framework manages to reduce motion mismatches and expected ratings in the targeted worst case maneuvers, a participant study on a driving simulator does not show improved worst participant ratings or significant overall rating improvements.
},
keywords = {},
}

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TY  - CONF
TI  - Optimization-based Motion Cueing Algorithm for Worst Case Maneuvers in Driving Simulation
AU  - Jacumet, Robert
AU  - Wetzel, Janik
AU  - Wagner, Sebastian
AU  - Schwienbacher, Markus
AU  - Wollherr, Dirk
AU  - Leibold, Marion
C1  - Stuttgart, Germany
C3  - Proceedings of the Driving Simulation Conference 2025 Europe XR
DA  - 2025/09/24
PY  - 2025
SP  - 163
EP  - 168
LA  - en-US
PB  - Driving Simulation Association
SN  - 978-2-9573777-7-0
L2  - https://proceedings.driving-simulation.org/proceeding/dsc-2025/optimization-based-motion-cueing-algorithm-for-worst-case-maneuvers-in-driving-simulation
ER  - 

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