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“Can you rely on me?” Evaluating a Confidence HMI for Cooperative, Automated Driving

  • Jakob Benedikt Peintner
  • , Carina Manger
  • , Andreas Riener

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

First concepts for cooperative driving already illustrate the potential of the cooperation between human drivers and automated vehicles. However, the main influencing factors that determine an efficient and effective cooperation still need to be investigated. We therefore examined the effects of displaying the vehicle’s intended decision in a critical situation in combination with a confidence value. In a driving simulator study (N=49), the automated vehicle communicated uncertainty in predicting the behavior of a pedestrian and the participants could support the automation by entering their own decision to stop or drive through. The results show that the time until entering the own decision (system override) was longer when a pending system decision was indicated with a confidence value in the HMI. A low confidence value resulted in the longest interaction times. In addition, trust in automation and usability were lower compared to the baseline cooperative HMI without a confidence value.
Original languageEnglish
Title of host publicationAutomotiveUI '22: Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
Pages340-348
Number of pages9
ISBN (Electronic)9781450394154
DOIs
Publication statusPublished - 17 Sept 2022

Publication series

NameMain Proceedings - 14th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2022

Fields of science

  • 202017 Embedded systems
  • 102 Computer Sciences
  • 102009 Computer simulation
  • 102013 Human-computer interaction
  • 102019 Machine learning
  • 102020 Medical informatics
  • 102021 Pervasive computing
  • 102022 Software development
  • 102025 Distributed systems
  • 211902 Assistive technologies
  • 211912 Product design

JKU Focus areas

  • Digital Transformation

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