Improving mode awareness of the VNAV function with a Multiple Hypothesis Prediction method

Abstract

This paper describes a Multiple Hypothesis Prediction (MHP) method that is used to improve aircraft state (energy and attitude) and automation mode awareness. The paper specifically focuses on its application for mode awareness during the use of the Vertical Navigation (VNAV) function. VNAV is used during the majority of the flight phases to govern vertical motion of aircraft and it is essential for flight constraint compliance and flight performance optimization. The existence of the VNAV sub-modes (i.e., VNAV SPD, VNAV PTH, and VNAV ALT), however, has often been confusing to the flight crew and the mode transition logic between these sub-modes is very complex. A previous survey has shown that VNAV is considered to be “the most disliked feature of automated cockpit systems” by many pilots. The MHP method presented in this paper reduces the occurrence of VNAV mode confusion by predicting aircraft trajectory and mode transitions with multiple hypotheses and alerting the flight crew of the hazardous situations when necessary. Violation of a waypoint altitude restriction is used as the example to evaluate the effectiveness of the MHP method, and both simulation and Human-In-The-Loop (HITL) study results show that this method increases the mode awareness of VNAV considerably and reduces the possibility of a potential waypoint altitude violation.