Comparison of Quality Metrics between Motion Cueing Algorithms in a Virtual Test Environment

@inproceedings{Kolff2020,
title = {Comparison of Quality Metrics between Motion Cueing Algorithms in a Virtual Test Environment},
author = {Maurice Kolff and Joost Venrooij and Daan M. Pool and Max Mulder},
editor = {Andras Kemeny and Jean-Rémy Chardonnet and Florent Colombet},
year  = {2020},
date = {2020-09-09},
booktitle = {Proceedings of the Driving Simulation Conference 2020 Europe VR},
pages = {93-99},
address = {Antibes, France},
organization = {Driving Simulation Association},
abstract = {Motion cueing algorithm design often involves a trade-off between priorities due to the limited workspace of the simulator. Such a trade-off requires a detailed understanding of human perception, which we do not yet have. For that reason, objective motion cueing quality metrics, based on the difference between vehicle and simulator signals, offer a fast and simple alternative. Next to motion cueing quality, we argue that the total motion cueing algorithm (MCA) quality is about more than only the quality of the motion, and can also entail implementation and operational aspects of an MCA for a specific use-case and simulator combination, i.e., it is a task-dependent issue. In this paper this idea is discussed by comparing three objective motion cueing quality metrics (absolute difference, delay and cross-correlation) from literature and two metrics regarding simulator operations (workspace management and energy consumption). Comparing such metrics is difficult, but is nevertheless useful to improve the process of simulator operations if various MCAs and/or simulators are available, to aid their selection process. As a first step towards such a method, a Virtual Test Environment (VTE) was developed as a versatile software environment to compare these metrics, as well as to visualize simulator motion and its characteristics in a 3D-animation. This aims at helping MCA designers in making choices between different MCA types, their configurations, simulators and use-cases, guiding them to select the best-suited motion cueing solution.},
keywords = {motion cueing, objective criteria, quality comparison, test environment},
}

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TY  - CONF
TI  - Comparison of Quality Metrics between Motion Cueing Algorithms in a Virtual Test Environment
AU  - Kolff, Maurice
AU  - Venrooij, Joost
AU  - Pool, Daan M. 
AU  - Mulder, Max
C1  - Antibes, France
C3  - Proceedings of the Driving Simulation Conference 2020 Europe VR
DA  - 2020/09/09
PY  - 2020
SP  - 93
EP  - 99
LA  - en-US
PB  - Driving Simulation Association
L2  - https://proceedings.driving-simulation.org/proceeding/dsc-2020/comparison-of-quality-metrics-between-motion-cueing-algorithms-in-a-virtual-test-environment
ER  - 

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