Abstract
DOI: 10.2514/1.C000204 Human pilot control during the landing approach is modeled using a stochastic switched model, which is a combination of the conventional linear regression model and a hidden Markov model. Using this model, the time histories of pilot control can be categorized in several states, such as pitch stabilizing mode. First, the selection of modelinputsisdiscussed.Basedondataobtainedin flightsimulatorexperiments,thepilotapproachcontrolmodelis constructed for several cases, with different wind conditions applying an expectation-maximization algorithm. The obtained models are analyzed with respect to the timing of state transitions and the stochastic-switched-model gain parameters. The current findings suggest that the proposed analysis method has a great potential to reveal a pilot’s decision-making process.
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