Maximum likelihood estimation of multi-modal pilot control behavior in a target-following task

Modeling multi-modal perception and control of pilots can be an important tool when designing new manual control systems or assessing simulator fidelity. This paper introduces a new pilot model parameter estimation technique based on maximum likelihood estimation. The method provides new possibilities for analyzing multi-modal control behavior in a target-following task. The new method is applied to data from an experiment comparing pilot control behavior in real flight and in a flight simulator. Previously, the data from this experiment could only be used to estimate a lumped, single modality, pilot model. The results from the maximum likelihood estimation technique indeed give new insights into the pilots use of different modalities in the aircraft and in the simulator.