Human Autonomy Teaming needs clear patterns that can be understood by all human and machine team members in order to become really cooperative. The proposed contribution addresses this challenge by linking the paradigm of cooperative automation with interaction patterns and image schemes. Image schemes derived in psychology and describe the fundamental linking principles of human (embodied) cognition and the world. As an example, cooperative automation, interaction pattern and image schemes are applied to heavy military ground vehicles. Military vehicles like heavy trucks, tanks or excavators face the challenge of being sufficiently guarded against enemy fire and being safely manoeuvrable. The latter includes driving capability but also vision in order to see where the vehicle is driving. Current military vehicles therefore face a trade-off between optimal vision and optimal armour resulting in more obstruction of the driver’s sight and the necessity of an assisting or automating co-driver when using a heavily armoured truck, tank or excavator. In order to overcome such limitations the human co-driver can be replaced by a cooperative automation that supports the driver in the driving tasks as an autonomous but cooperative team member in a cooperatively guided vehicle. To efficiently communicate information between co-automation and the crew, interaction patterns and AR was applied.
Human Autonomy Teaming using Cooperative Automation, Interaction Patterns and Image Schemes
2019
2019
Aufsatz (Konferenz)
Elektronische Ressource
Unbekannt
NTRS
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