Shared Control Between Pilots and Autopilots: Illustration of a Cyber-Physical Human System

TL;DR

This paper explores shared control schemes between pilots and autopilots based on the Capacity for Maneuver (CfM) concept, demonstrating improved safety and control effectiveness in simulated severe anomaly scenarios.

Contribution

It introduces CfM-based shared control architectures for pilot-autopilot interaction, offering promising alternatives to traditional disengagement methods in aircraft automation.

Findings

CfM-based control schemes reduce tracking errors

They increase overall actuator capacity (CfM)

Human-in-the-loop simulations validate effectiveness

Abstract

Although increased automation has made it easier to control aircraft, ensuring a safe interaction between the pilots and the autopilots is still a challenging problem, especially in the presence of severe anomalies. Current approach consists of autopilot solutions that disengage themselves when they become ineffective. This may cause reengagement of the pilot at the worst possible time, which can result in undesired consequences. In this paper, a series of research studies that propose pilot-autopilot interaction schemes based on the Capacity for Maneuver (CfM) concept, are covered. CfM refers to the remaining capacity of the actuators that can be used for bringing the aircraft to safety. It is demonstrated that CfM-based pilot-autopilot interaction schemes, or Shared Control Architectures (SCA), can be promising alternatives to the existing schemes. Two SCAs are tested in the experiments. In SCA1, the pilot takes over the control from the autopilot using the monitored CfM information. In SCA2, the pilot takes on the role of a supervisor helping the autopilot whenever a need arises, based on the CfM information. Whenever the aircraft experiences a severe anomaly, the pilot assesses the situation based on his/her CfM monitoring and intervenes by providing two control system parameter estimates to the autopilot. This increases the effectiveness of the autopilot. Using human-in-the-loop simulations, it is shown that CfM based interactions provides smaller tracking errors and larger overall CfM. The subjects including a commercial airline pilot and several university students are trained using a systematic procedure. Creation of new cyber physical & human systems is inevitable along with deeper engagement with the social science community so as to get better insight into human decision making. The results reported here should be viewed as a first of several steps in this research direction.