Mapping and Analysis of Human Guidance Performance From Trajectory Ensembles

This paper describes a mapping method for the analysis of guidance performance. Spatial state and time-to-go maps, along with their statistics, are computed from an ensemble of trajectories. The mapping technique is motivated by the concept of spatial value function associated with an optimal guidance model. For illustration, the method is applied to trajectories collected from a human-operated miniature helicopter in a precision interception task. The closed-loop dynamics of the helicopter under human control was modeled as a mass-point system. The closed-loop model provides a formal interpretation for the extracted maps and is also used to compute optimal trajectories that serve as absolute baseline for the guidance performance. The maps extracted from the experimental trajectories show that human guidance performance is sufficiently stationary and spatially coherent to be meaningfully embedded in a spatial map. The comparison with the optimal baseline makes it possible to identify the subject's specific performance gaps. Performance metrics that are defined and computed on hand of the maps enable more detailed assessment of the operator's performance. The general results demonstrate that the guidance performance of a trained subject can be meaningfully modeled as a guidance policy based on a simple closed-loop mass-point model.