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. 2022 Aug 4;22(15):5837.
doi: 10.3390/s22155837.

A Case Study on Vestibular Sensations in Driving Simulators

Jose V Riera  1   2 , Sergio Casas  1   2 , Francisco Alonso  3   4 , Marcos Fernández  1   2
Affiliations

A Case Study on Vestibular Sensations in Driving Simulators

Jose V Riera et al. Sensors (Basel). .

Abstract

Motion platforms have been used in simulators of all types for several decades. Since it is impossible to reproduce the accelerations of a vehicle without limitations through a physically limited system (platform), it is common to use washout filters and motion cueing algorithms (MCA) to select which accelerations are reproduced and which are not. Despite the time that has passed since their development, most of these algorithms still use the classical washout algorithm. In the use of these MCAs, there is always information that is lost and, if that information is important for the purpose of the simulator (the training simulators), the result obtained by the users of that simulator will not be satisfactory. This paper shows a case study where a BMW 325Xi AUT fitted with a sensor, recorded the accelerations produced in all degrees of freedom (DOF) during several runs, and data have been introduced in mathematical simulation software (washout + kinematics + actuator simulation) of a 6DOF motion platform. The input to the system has been qualitatively compared with the output, observing that most of the simulation adequately reflects the input to the system. Still, there are three events where the accelerations are lost. These events are considered by experts to be of vital importance for the outcome of a learning process in the simulator to be adequate.

Keywords: car characterization; driving simulator; motion cueing algorithm; motion platform; vestibular perception; washout filter.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Stewart 6DOF motion platform.
Figure 2
Figure 2
Outline of the tests to be performed.
Figure 3
Figure 3
Sensor, camera and laptop installation for real-time sample collection.
Figure 4
Figure 4
Data collected by the sensor.
Figure 5
Figure 5
Schematic diagram of a classical washout operation.
Figure 6
Figure 6
Response of the platform simulation software to well-known inputs.
Figure 7
Figure 7
Timeline of the most important events that occurred on a data collection trip.
Figure 8
Figure 8
Input/Output results in the different DOFs.
Figure 9
Figure 9
Event 1 details.
Figure 10
Figure 10
Event 2 details.
Figure 11
Figure 11
Event 3 details.
See this image and copyright information in PMC

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