Cooperation between people and automation has been part of our everyday lives in many areas for decades. In safety-critical applications, such as aviation, it is particularly important that this cooperation not only runs efficiently but also reliably. Thomas B. Sheridan (MIT) has described the classic work share between humans and automation with his principles of "Human Supervisory Control". According to these principles, people transfer certain subtasks to automation, which then implements them using machines. Today, however, we have the situation that automation is increasingly able to take on higher-value cognitive tasks (see research focus: Cognitive Achitectures). In addition, there are possibilities to change the allocation of tasks between humans and automation from rigid to liquid (see research focus: Adaptive Automation/Autonomy). 

Our goal is to find new paradigms of cooperation between humans and (increasingly intelligent) automation and to describe them in terms of "design patterns". The goals of using such design patterns are summarized under the keyword "Human-Autonomy Teaming (HAT)".


Taking into account the expected future cognitive abilities of automation, work processes of man-machine systems must be described in a strict "top-down" approach, as is usual in "Systems Engineering (SE)". In addition to the classical SE, the role of the human being in the work process must be consistently included in the design process from the very beginning. Only then is it possible to include not only hierarchical but also heterarchical models of cooperation between man and automation, i.e. models in which humans and machines co-operatively distribute cognitive tasks among themselves, in the system design. In this way it is possible to define requirements for cognitive agents and their interaction with humans without getting lost in vague terms such as "intelligence" and "autonomy" in connection with technical systems.


The Chair of Aircraft Dynamics and Flight Guidance is consistently developing a theory to describe highly automated human-machine systems. Here the Work Process and the Work System, as well as the role of the human ("worker") and the technology ("tool") are central concepts. Cognitive agents can adopt both roles. We refer to this idea as "Dual Mode Cognitive Design" and it was described comprehensively for the first time in a Monograph in 2010. Furthermore, possible relations, hierarchical and heterarchical, between humans, agents and conventional automation are described in terms of design patterns.

At the institute we mainly examine the following design patterns:

  • Delegation of high-value tasks to manned and unmanned aircraft (see research fields: Mission Management, UAV Automation). In this context, the paradigm of task-based UAV management should be mentioned above all, which was investigated in detail in the following dissertations:
    • Johann Uhrmann: "Task-based Multi UAV Guidance from the Helicopter Cockpit using Cognitive Automation"
    • Sebastian Clauß: "Agent Supervisory Control as an Approach to Task-based Delegation of a Cognitive Agent aboard a UAV"
  • Pilot assistance systems that function as digital copilots (see research field: Assistance Systems). This is one of the most intensively researched design patterns of the institute to date. The following dissertations should be mentioned in this context:
    • Felix Maiwald: "Automatic Workload Prediction for a Resource-adaptive Pilot Associate System"
    • Andreas Rauschert: "Cognitive Assistant System for UAV Guidance in Manned-Unmanned Teaming Flight Missions"
    • Nikolaus Theißing: "Intervention Strategy for Assistant Systems for Correction of Operator Errors"
  • Team-based management of UAV. This means that orders are no longer placed with individual UAVs, but with a small group of UAVs. In addition to the teams, we also investigate swarms, which in turn represent different requirements for the interaction between man and machine. In connection with UAV teams, the following dissertations should be mentioned in addition to current work:
    • Claudia Meitinger: "Cognitive Automation for Cooperative UAG Guidance"
    • Stefan Gangl: "Cooperative Multi UAV Guidance from a Single-Seat Fighter Aircraft"
  • Mixed-Initiative Mission Planning. With this approach, mission plans are created by pilots and machine planning functions in teamwork. This means that the initiative to further develop, optimise or correct a mission plan, for example for Manned-unmanned Teaming (MUM-T) missions, can come from the pilot or from a planning agent. Dissertations on this topic are currently in preparation.
  • Adaptive Automation (see research field: Adaptive Automation). Here, interventions of the automation, e.g. of an assistance system, are to be adapted to the mental state of the human user. This closes a "control loop" which should lead to the mental workload ("MWL") of the user being kept in a tolerable range. A number of dissertations are currently being prepared on this design pattern. The following doctoral theses have already been completed:
    • Diana Donath: "Behavioral Analysis of Operator Workload in Multi UAV Guidance"
    • Felix Maiwald: "Automatic Workload Prediction for a Resource-adaptive Pilot Associate System"