Adaptive Manual Control: a Predictive Coding Approach

Improved understanding of human adaptation can be used to design better (semi-)automated systems that can support the human controller when task characteristics suddenly change. This paper evaluates the effectiveness of a model-based adaptive control technique, Model Reference Adaptive Control (MRAC), for describing the adaptive control policy...

Between-simulator comparison of motion-filter order and break frequency effects on manual control

This paper investigates the interaction effects of motion filter order and break frequency on pilots’ manual control behavior and control performance using two simulators. Eighteen pilots performed the experiment in the Vertical Motion Simulator (VMS) at NASA Ames Research Center and 20 pilots in the SIMONA Research Simulator at Delft University...

Linear Mixed-Effects Models for Human-in-the-Loop Tracking Experiment Data

Linear mixed-effects models provide several benefits over more traditional statistical inference tests and are particularly useful for most human-in-the-loop tracking experiment data. However, surprisingly, mixed models are virtually not used for the analysis of tracking experiment data. This paper uses linear mixed-effects models to analyze...

A Simulator Comparison Study into the Effects of Motion Filter Order on Pilot Control Behavior

This paper describes an experiment investigating the effects of motion filter order on human manual control tracking behavior and performance. The experiment was performed on two simulators: the Vertical Motion Simulator at NASA Ames Research Center and the SIMONA Research Simulator at Delft University of Technology. Eighteen pilots in the...

Manual control cybernetics: State-of-the-art and current trends

Manual control cybernetics aims to understand and describe how humans control vehicles and devices using mathematical models of human control dynamics. This “cybernetic approach” enables objective and quantitative comparisons of human behavior, and allows a systematic optimization of human control interfaces and training...

Relating Eye Activity Measures to Human Controller Remnant Characteristics

This study attempts to partially explain the characteristics of the human perceptual remnant, following Levison’s representation of the remnant as an equivalent observation noise. Eye activity parameters are recorded using an eye tracker in two compensatory tracking tasks in which the visual information is presented using either a first or...

Modeling Human Multimodal Perception and Control Using Genetic Maximum Likelihood Estimation

This paper presents a new method for estimating the parameters of multi-channel pilot models that is based on maximum likelihood estimation. To cope with the inherent nonlinearity of this optimization problem, the gradient-based Gauss-Newton algorithm commonly used to optimize the likelihood function in terms of output error is complemented with...