In the last decades, supervisory control has become an important concept of human-machine interaction in context of safety-critical systems, as they can be found in transportation, industrial, and medical. The reason is the ever increasing level of automation. Within this concept building and maintaining situation awareness is very important. However, human factors research revealed that insufficient situation awareness is the main cause of human error in context of supervisory control domains. The key enabler of good situation awareness is adequate monitoring behavior. Therefore, it is a safety-critical requirement that displays are designed in a way that supports human operators to selectively perceive the information they need. However, human factors research again showed that monitoring behavior is very often inadequate, e.g., because of incorrect or incomplete mental models, distraction due to misplaced salience, perservation or fatigue. In this work, we present an assistant system to improve the monitoring behavior of a human operator in charge of supervisory control of multiple highly-automated unmanned aerial vehicles. The underlying concept is based on the real-time assessment and augmentation of monitoring performance. The real-time assessment of monitoring performance is based on an eye tracking-based tool that allows to assess the demand for attention of information conveyed by a user interface for supervisory control of multiple highly-automated unmanned aerial vehicles. The real-time augmentation of monitoring performance is based on two strategies to adapt the characteristics of the user interface used by a human operator to supervise many highly-automated unmanned aerial vehicles. The first strategy invokes visual cues on a situation awareness display to support visual search for information demanding attention. The second strategy invokes visual cues on a peripheral display to support the human operator's awareness for monitoring behavior adequacy.
5 / 2016
D3CoS Designing Dynamic Distributed Cooperative Systems