A Novel Human Machine Interface to Support Supervision and Guidance of Multiple Highly Automated Unmanned Aircraft

Abstract

The current paper presents the results of the evaluation of a novel human machine interface for supervision and guidance of multiple highly automated unmanned aircraft. Accidents of unmanned aircraft are often related to deficiencies in the design of the human machine interface. Many of these deficiencies are a consequence of insufficient consideration of human factors engineering principles in the early stages of system development. Therefore, in the design of the current human machine interface, empirically validated human factors methods were applied in order to optimally support a remote pilot in supervising and guiding multiple highly automated unmanned aircraft. An information management concept was developed that allows for an increase in the number of UAS that are being supervised without considerably increasing display complexity. In order to evaluate the human machine interface, two within-subj ect simulation studies were conducted. In both studies, pilots were asked to supervise and guide a varying number of UAS in several experimental scenarios using the new human machine interface. Following the experimental scenarios, a structured interview regarding the design of the human machine interface was conducted. The objective of the first study was to gather initial data on the general usability of the interface. The aim of the second simulation study was to investigate how increasing the number of UAS from one up to five affects the time that a pilot needs to acquire and change specific system parameters of any UAS under supervision. Further, the impact of increasing the number of UAS on pilot workload and situation awareness was assessed. The results of the interviews suggest that the design concept of the human machine interface is feasible and easy to understand. The information management concept was described as reasonable and logical. Important information was accessible quickly and (critical) system states could easily be identified. No significant effects of increasing the number of UASs to be supervised on reaction, workload or situation awareness were observed. The findings suggest that the information management concept is reasonable and usable.