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  Offline motion simulation framework: Optimizing motion simulator trajectories and parameters

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.

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Genre: Journal Article

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 Creators:
Katliar, M1, 2, Author              
Olivari, M1, 2, Author              
Drop, FM1, 2, Author              
Nooij, SAE1, 2, Author              
Diehl, M, Author
Bülthoff, HH1, 2, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 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.

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 Dates: 2019-10
 Publication Status: Published in print
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 Rev. Type: -
 Identifiers: DOI: 10.1016/j.trf.2019.07.019
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Title: Transportation Research Part F: Traffic Psychology and Behaviour
Source Genre: Journal
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Publ. Info: Oxford, UK : Pergamon, Elsevier Science
Pages: - Volume / Issue: 66 Sequence Number: - Start / End Page: 29 - 46 Identifier: ISSN: 1369-8478