English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Offline motion simulation framework: Optimizing motion simulator trajectories and parameters

MPS-Authors
/persons/resource/persons192766

Katliar,  M
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons192609

Olivari,  M
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84423

Drop,  FM
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84957

Nooij,  SAE
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons83839

Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Katliar, M., Olivari, M., Drop, F., Nooij, S., Diehl, M., & Bülthoff, H. (2019). Offline motion simulation framework: Optimizing motion simulator trajectories and parameters. Transportation Research Part F: Traffic Psychology and Behaviour, 66, 29-46. doi:10.1016/j.trf.2019.07.019.


Cite as: https://hdl.handle.net/21.11116/0000-0007-7FBF-5
Abstract
This paper presents a method to simultaneously compute optimal simulator motions and simulator parameters for a predefined set of vehicle motions. The optimization can be performed with a model of human motion perception or sensory dynamics taken into account. The simulator dynamics, sensory dynamics, and optimality criterion are provided by the user. The dynamical models are defined by implicit index-1 differential-algebraic equations (DAE). The direct collocation method is used to find the numerical solution of the optimization problem. The possible applications of the method include calculating optimal simulator motion for scenarios when the future motion is perfectly known (e.g., comfort studies with autonomous vehicles), optimizing simulator design, and evaluating the maximum possible cueing fidelity for a given simulator. To demonstrate the method, we calculated optimal trajectories for a set of typical car maneuvers for the CyberMotion Simulator at the Max-Planck Institute for Biological Cybernetics. We also optimize the configurable cabin position of the simulator and assess the corresponding motion fidelity improvement. The software implementation of the method is publicly available.