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The impact of explainability & mental modeling on human flawed thinking in automated driving

  • If we, as user experience designers, want to create truly user-centered experiences, we need to understand not only what people want, but what they need and how they behave. Human behavior, however, also results from the choices people make every day. The same applies to the development and design of automated transportation. To achieve and maintain these goals, we need to accept that human decisions are not only made on a rational level, but rather on the basis of mental shortcuts, which may be efficient, but can also lead to cognitive biases and thus to sub-optimal results. This master’s thesis specifically sheds light on four cognitive biases - truthiness, illusion of control, action bias and automation bias -, their existence in automated driving, as well as their relationship to each other and possible influencing factors. As part of a preliminary study (n=117), which was implemented as an online questionnaire, the existence of the cognitive biases in focus of this work is examined in more detail and initial findings ofIf we, as user experience designers, want to create truly user-centered experiences, we need to understand not only what people want, but what they need and how they behave. Human behavior, however, also results from the choices people make every day. The same applies to the development and design of automated transportation. To achieve and maintain these goals, we need to accept that human decisions are not only made on a rational level, but rather on the basis of mental shortcuts, which may be efficient, but can also lead to cognitive biases and thus to sub-optimal results. This master’s thesis specifically sheds light on four cognitive biases - truthiness, illusion of control, action bias and automation bias -, their existence in automated driving, as well as their relationship to each other and possible influencing factors. As part of a preliminary study (n=117), which was implemented as an online questionnaire, the existence of the cognitive biases in focus of this work is examined in more detail and initial findings of visualizations and explanations as an influencing factor are collected. In the further course, a user study (n=34) was completed to build on the knowledge gained and examine the accuracy of the mental model of the occupants of an automated ride and their individual personality traits as further influential parameters. This work should serve as a cornerstone to include cognitive biases and their influencing forces in the development of automated vehicles in the future and to use the knowledge gathered to integrate psychological aspects that affect every human being into user-centered humanmachine interactions.show moreshow less

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Metadaten
Author:Annalena Maria Vogl
Language:English
Document Type:Master's Thesis
Reviewer(s) at THI:Andreas Riener, Carina Manger
Publishing Institution:Technische Hochschule Ingolstadt
Date of first Publication:2024/02/01
Year of first Publication:2024
Place of publication:Ingolstadt
Pages:82, LVII
URN:urn:nbn:de:bvb:573-46308
Faculties / Institutes / Organizations:Fakultät Informatik
Degree Programmes:User Experience Design (M. Sc.)
Licence (German):License Logo Urheberrechtsschutz
Release Date:2024/03/21