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Auflistung nach Autor:in "Mathis, Lesley-Ann"

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  • Workshopbeitrag
    A Platform for Rapid Prototyping and Evaluation of Concepts for Interactive In-Vehicle Displays for Automated Vehicles
    (Mensch und Computer 2021 - Workshopband, 2021) Dandekar, Aditya; Mathis, Lesley-Ann; Pfleging, Bastian
    Nowadays, automotive user interface research strives towards investigating automated vehicles. To test user concepts, especially pertaining to fully automated vehicles, several methods are evolving, such as Virtual Reality studies, simulator studies, or Wizard-of- Oz experiments. In all of these methods, researchers need to find an appropriate driving environment which is often created through a driving simulator or a real-life driving video. There is a lack of tools which give researchers the opportunity to rapidly create prototypes for their evaluation. To solve this issue for the case of investigating interactions with windshield displays and dashboards, we design a tool that can be used to support these studies and interfaces in various context. The experimenter can develop a virtual user interface through our platform. The interface can be deployed either in a lab setting where the driving context is provided through simulation or recorded driving videos, or it can be easily deployed in a Wizardof- Oz car. In this position paper, we present the framework of the tool and foster the discussion for such an idea and its use cases.
  • Konferenzbeitrag
    When to Approach the User: Investigating Suitable Context Factors for Proactive Voice Assistance in Automated Cars
    (Proceedings of Mensch und Computer 2024, 2024) Mathis, Lesley-Ann; Bubeck, Carla Bernadette; Peissner, Matthias
    Future voice assistants in automated cars are expected to provide a more interactive user experience by making proactive suggestions. For the design of proactive behavior, the right timing of the interaction is key to ensure user acceptance. Context situations during an automated ride are influenced by different factors, which need to be considered to initiate a proactive interaction. The goal of this study is to investigate how different context factors influence the suitability of proactive suggestions and relate to the suggested content. A conjoint analysis was designed to measure users’ preferences for different situations. Results indicate that selected context factors are considered suitable or unsuitable for a proactive approach, independent of the suggested content. The content's relevancy contributes to the general acceptance, with more relevant suggestions considered suitable in more context situations. The presented results will inform the modelling approach of a voice assistant prototype for future studies.