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Parameter Estimation of Multimodal Pilot Models for Manual Target-following Tasks

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84644

Pool,  DM
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Pool, D., Zaal PMT, Mulder M, van Paassen, M., & Mulder, J. (2008). Parameter Estimation of Multimodal Pilot Models for Manual Target-following Tasks. In 27th European Annual Conference on Human Decision-Making and Manual Control (EAM '08) (pp. -).


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-C903-4
Zusammenfassung
Estimation of the parameters of multimodal pilot models can give useful insight in pilots use of visual and simulator motion cues in manual vehicle control tasks. Depending on control task design, current multimodal pilot model identification techniques are in some instances unable to provide reliable parameter estimates. Application of a maximum likelihood estimation algorithm was found to yield good parameter estimates for data from a manual target-following task for which previously used identification techniques fell short, allowing for stronger conclusions on the effect of simulator motion cues on manual control for this task.