Driving Simulator Experiment Stakeholder Perspectives on Motion Cueing Algorithm Quality

Abstract

In driving simulation, the choice of a simulator, motion cueing algorithm, and associated set of tuning parameters for an experiment is typically made with an exclusive focus on the quality of the motion. In practice, many other metrics could affect this choice as well, such as tuning complexity, algorithm stability, or the financial costs of the simulation. Arguably, the complete motion cueing algorithm quality is thus more than the quality of the motion alone. This paper presents results of a survey which attempted to identify the most important metrics from the perspective of the main experiment stakeholders. Four stakeholder groups in typical driving simulator experi- ments are defined: The experimenters, motion cueing engineers, operators, and participants. All groups received the same survey, asking them to indicate how important various metrics are for them. Results show that, next to the quality of the motion, experimenters and participants are generally interested in reducing simulator sickness. The motion cueing engineers rank tuning effort and tuning complexity as most important metrics. Operators prefer an easy to use and overall stable motion cueing. A typical BMW experiment is discussed as example, which shows that the choice for a simulator and motion cueing algorithm can indeed differ when including these metrics in a trade-off, compared to when only motion quality is considered. The presented methods allow for a better, multi- faceted selection of the simulator, motion cueing algorithm, and associated tuning parameters, improving future driving simulation experiments.