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Why Do I Have to Take Over Control? Evaluating Safe Handovers with Advance Notice and Explanations in HAD

Frederik Wiehr; Anke Hirsch; Lukas Schmitz; Nina Knieriemen; Antonio Krüger; Alisa Kovtunova; Stefan Borgwardt; Ernie Chang; Vera Demberg; Marcel Steinmetz; Jörg Hoffmann
In: Proceedings of the 2021 International Conference on Multimodal Interaction. ACM International Conference on Multimodal Interaction (ICMI-2021), New York, NY, USA, ICMI '21, ISBN 9781450384810, Association for Computing Machinery, 2021.


In highly automated driving (HAD), it is still an open question how machines can safely hand over control to humans, and if an advance notice with additional explanations can be beneficial in critical situations. Conceptually, use of formal methods from AI – description logic (DL) and automated planning – in order to more reliably predict when a handover is necessary, and to increase the advance notice for handovers by planning ahead at runtime, can provide a technological support for explanations using natural language generation. However, in this work we address only the user’s perspective with two contributions: First, we evaluate our concept in a driving simulator study (N=23) and find that an advance notice and spoken explanations were preferred over classical handover methods. Second, we propose a framework and an example test scenario specific to handovers that is based on the results of our study.

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