CASPEr: an Approach to Characterize the Performance of Onboard Airplane Energy State and Automation Mode Prediction Functions

The Commercial Aviation Safety Team (CAST) has identified a set of safety enhancements to mitigate the risks of loss of control in-flight (LOCI) accidents and incidents involving commercial transport airplanes. In support of this, NASA has been developing technologies intended to enhance flight crew awareness of airplane systems, attitude, and energy state. This report describes preliminary ideas for a methodology to assess the goodness of onboard airplane energy state and automation mode prediction functions. The methodology is intended to contribute to the goal of moving these prediction technologies to the readiness level required for transition to industry and reduce the technology certification risks. In addition, this report describes a simulation-based approach named CASPEr (Characterization of Airplane State Prediction Error) to characterize the performance of these predictive functions over a wide range of operational conditions. The first exploratory version of this approach is described. The bulk of the report documents the initial results of tests to characterize the performance of an airplane trajectory prediction function. Future reports will give additional performance characterization results for this function and a complete description of the proposed methodology to assess such functions.