Kraft, Edward ; He, Ping ; Rinderknecht, Stephan (2022)
Application of Prepositioning Strategies in a Compensational Motion Cueing Algorithm.
Driving Simulation Conference 2022 Europe VR. Strasbourg (14-16 Sep 2022)
Conference or Workshop Item, Bibliographie
Abstract
Motion cueing algorithms (MCA) are an essential part of the operation of driving simulators. Challenges in choosing and parametrizing these MCA lie in the accuracy and workspace usage efficiency. In addition, false cues have to be minimized to reduce simulator sickness. So-called compensational MCA try to compensate the washout by tilt coordination. To further improve workspace efficiency, prepositioning strategies seek to predict the driver’s behavior and dynamically prepare the simulator for the upcoming movement. In this paper, dynamic prepositioning strategies are applied to a compensational MCA. Their performances are analyzed for two different driving scenarios. The maximum scaling factor was used as an evaluation parameter for the comparison of the investigated prepositioning strategies. The results show that maximum scaling factors can be slightly increased by applying prepositioning strategies. If keeping the scaling factor constant, tilt activity can be reduced which is assumed to be having a positive impact on simulator sickness. The results indicate that prepositioning strategies show the most robust performance for predefined test runs since the driver’s behavior is known in advance. Contrary to expectation, strong washouts in the compensational MCA are not suitable in combination with prepositioning strategies.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2022 |
| Creators: | Kraft, Edward ; He, Ping ; Rinderknecht, Stephan |
| Type of entry: | Bibliographie |
| Title: | Application of Prepositioning Strategies in a Compensational Motion Cueing Algorithm |
| Language: | English |
| Date: | 16 November 2022 |
| Place of Publication: | Strasbourg |
| Publisher: | Driving Simulation Association |
| Book Title: | Proceedings of the Driving Simulation Conference 2022 Europe VR |
| Event Title: | Driving Simulation Conference 2022 Europe VR |
| Event Location: | Strasbourg |
| Event Dates: | 14-16 Sep 2022 |
| URL / URN: | https://proceedings.driving-simulation.org/proceeding/dsc-20... |
| Abstract: | Motion cueing algorithms (MCA) are an essential part of the operation of driving simulators. Challenges in choosing and parametrizing these MCA lie in the accuracy and workspace usage efficiency. In addition, false cues have to be minimized to reduce simulator sickness. So-called compensational MCA try to compensate the washout by tilt coordination. To further improve workspace efficiency, prepositioning strategies seek to predict the driver’s behavior and dynamically prepare the simulator for the upcoming movement. In this paper, dynamic prepositioning strategies are applied to a compensational MCA. Their performances are analyzed for two different driving scenarios. The maximum scaling factor was used as an evaluation parameter for the comparison of the investigated prepositioning strategies. The results show that maximum scaling factors can be slightly increased by applying prepositioning strategies. If keeping the scaling factor constant, tilt activity can be reduced which is assumed to be having a positive impact on simulator sickness. The results indicate that prepositioning strategies show the most robust performance for predefined test runs since the driver’s behavior is known in advance. Contrary to expectation, strong washouts in the compensational MCA are not suitable in combination with prepositioning strategies. |
| Uncontrolled Keywords: | motion cueing, compensational motion cueing algorithm, driver prediction, dynamic prepositioning, workspace usage efficiency |
| Divisions: | 16 Department of Mechanical Engineering 16 Department of Mechanical Engineering > Institute for Mechatronic Systems in Mechanical Engineering (IMS) |
| Date Deposited: | 23 Nov 2022 06:39 |
| Last Modified: | 23 Nov 2022 06:39 |
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