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Towards a meta-scientific systems thinking approach to Human-Robot and Automated Vehicle - Other Road User Interactions

Daniel Eisele

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In this position paper, I discuss how researchers in the fields of Human-Robot interaction and Automated Vehicles-Other Road User Interaction can benefit from systems thinking.

I presented the paper at a workshop on Transferability between Human-Robot Interaction (HRI) and Autonomous Vehicle Interaction Research at the AutomotiveUI 2024 conference.



Abstract #

Substantial resources are being invested in integrating social robots and automated vehicles (AVs) into everyday life. I argue that both social robots and AVs with artificial intelligence (AI) can be considered social actors within the broader category of “intelligent machines”. If they are indeed integrated into society on a large scale, the fields of Human-Robot Interaction (HRI) and Automated Vehicles-Other Road User Interaction (AV-ORU) face the challenge of studying their behavior and impact within an emerging hybrid human-machine society. However, both disciplines are in their early stages regarding the exploration of interdependencies between their entities of interest and the complex adaptive systems in which they (will) operate. I propose that meta-scientific insights from systems science provide valuable perspectives to guide the formulation of research questions and the design of future studies across both disciplines.


Recommended Citation:

Eisele, D. (2024). Towards a Meta-Scientific Systems Thinking Approach to Human-Robot and Automated Vehicle-Other Road User Interactions. In Symbiotic: A Workshop on Transferability between Human-Robot Interaction (HRI) and Autonomous Vehicle Interaction Research. Part of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI ’24), Stanford, USA. https://doi.org/10.1145/3640792.3675723