Casper-1, Part 6: Uncertainty Quantification, Factor Effects, and Outlier Analysis for an On-Board Airplane Trajectory Prediction Function

Abstract

This report presents data analysis results for a simulation-based approach named CASPEr (Characterization of Airplane State Prediction Error) to characterize the performance of onboard energy state and automation mode prediction functions for terminal area arrival and approach phases of flight over a wide range of conditions. In particular, the results include quantification of energy state (i.e., altitude and airspeed) prediction performance, models for prediction performance as a function of initial energy state (i.e., initial altitude, airspeed, and weight) and weather factors, and analysis of outlier prediction performance. Wind speed, wind direction, and wind gradient were found to be major factors in energy state prediction performance. Initial energy and gust intensity were also significant factors in airspeed prediction performance. Furthermore, the results suggest that errors in automation mode prediction may be a major contributor to outlier prediction performance