Subjective Evaluation of Motion Cueing Algorithms: A Comparative Study on Real-World Expectations in a Robot-Based Driving Simulator

@inproceedings{Nicolai2025,
title = {Subjective Evaluation of Motion Cueing Algorithms: A Comparative Study on Real-World Expectations in a Robot-Based Driving Simulator},
author = {Tim Nicolai and Sebastian Emmerich and René Reinhard and Jonathan Schneider and Michael Burger
},
editor = {Andras Kemeny and Jean-Rémy Chardonnet and Florent Colombet and Stéphane Espié},
doi = {https://doi.org/10.82157/dsa/2025/15},
isbn = {978-2-9573777-7-0},
year  = {2025},
date = {2025-09-24},
booktitle = {Proceedings of the Driving Simulation Conference 2025 Europe XR},
pages = {125-130},
address = {Stuttgart, Germany},
organization = {Driving Simulation Association},
abstract = {The growing prevalence of interactive driving simulators as effective instruments in various fields, including driver training, vehicle dynamics design, and advanced driving assistance system testing, highlights the
significance of precise vehicle motion replication and driver immersion. Motion cueing algorithms (MCAs) play a
pivotal role in generating realistic motion feedback based on driver interactions within simulated environments.
These algorithms are designed to regulate motion platforms, thereby emulating accelerations and angular velocities, and thus replicating a vehicle’s physical dynamics. A taxonomy of MCA methodologies is available, primarily
categorized into filter-based and optimization-based approaches. However, a consensus on the relative effectiveness of these methodologies remains elusive. Recent efforts have centered on the development of both subjective
and objective evaluation criteria to facilitate the comparison of diverse MCAs. While earlier studies have primarily
focused on hexapod-based driving simulators, which are the most common, the unique design and functionality of
robot-based motion platforms suggest potential differences in driving experience and simulation capabilities. The
present study aims to investigate whether the evaluation of MCAs in robot-based driving simulators differs from that
in hexapod-based systems, thereby contributing to a more profound understanding of motion cueing effectiveness
across disparate simulation platforms. Contrary to other studies, participants evaluate an interactive ride against
their real-world expectations.},
keywords = {},
}

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TY  - CONF
TI  - Subjective Evaluation of Motion Cueing Algorithms: A Comparative Study on Real-World Expectations in a Robot-Based Driving Simulator
AU  - Nicolai, Tim
AU  - Emmerich, Sebastian
AU  - Reinhard, René
AU  - Schneider, Jonathan
AU  - Burger, Michael
C1  - Stuttgart, Germany
C3  - Proceedings of the Driving Simulation Conference 2025 Europe XR
DA  - 2025/09/24
PY  - 2025
SP  - 125
EP  - 130
LA  - en-US
PB  - Driving Simulation Association
SN  - 978-2-9573777-7-0
L2  - https://proceedings.driving-simulation.org/proceeding/dsc-2025/subjective-evaluation-of-motion-cueing-algorithms-a-comparative-study-on-real-world-expectations-in-a-robot-based-driving-simulator
ER  - 

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