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Licensed Unlicensed Requires Authentication Published by De Gruyter Oldenbourg January 16, 2021

Evaluating feedback requirements for trust calibration in automated vehicles

Philipp Wintersberger ORCID logo, Frederica Janotta, Jakob Peintner, Andreas Löcken and Andreas Riener

Abstract

The inappropriate use of automation as a result of trust issues is a major barrier for a broad market penetration of automated vehicles. Studies so far have shown that providing information about the vehicle’s actions and intentions can be used to calibrate trust and promote user acceptance. However, how such feedback could be designed optimally is still an open question. This article presents the results of two user studies. In the first study, we investigated subjective trust and user experience of (N=21) participants driving in a fully automated vehicle, which interacts with other traffic participants in virtual reality. The analysis of questionnaires and semi-structured interviews shows that participants request feedback about the vehicle’s status and intentions and prefer visual feedback over other modalities. Consequently, we conducted a second study to derive concrete requirements for future feedback systems. We showed (N=56) participants various videos of an automated vehicle from the ego perspective and asked them to select elements in the environment they want feedback about so that they would feel safe, trust the vehicle, and understand its actions. The results confirm a correlation between subjective user trust and feedback needs and highlight essential requirements for automatic feedback generation. The results of both experiments provide a scientific basis for designing more adaptive and personalized in-vehicle interfaces for automated driving.

ACM CCS:

Funding source: Bundesministerium für Verkehr und Digitale Infrastruktur

Award Identifier / Grant number: 16AVF2145E

Award Identifier / Grant number: 16AVF2145F

Funding source: Bundesministerium für Bildung und Forschung

Award Identifier / Grant number: 13FH7I01IA

Funding statement: F. Janotta, A. Löcken and A. Riener are supported by the German Federal Ministry of Transport and Digital Infrastructure (BMVI) through the Automated and Connected Driving funding program under Grant Nos. 16AVF2145E and 16AVF2145F (SAVe). P. Wintersberger and J. Peintner are supported under the FH-Impuls program of the German Federal Ministry of Education and Research (BMBF) under Grant Number 13FH7I01IA (SAFIR). Further, we want to thank Hannah Nicklas and Spiegel Institut Germany for their support.

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Received: 2020-07-10
Revised: 2020-10-11
Accepted: 2020-11-05
Published Online: 2021-01-16
Published in Print: 2021-06-25

© 2021 Walter de Gruyter GmbH, Berlin/Boston