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A Set of Design Principles for Personalized Information in Automated Driving User Interfaces Based on Theory and Empirical Evidence

Tim Driesen-Micklitz , Michael Fellmann and Carsten Röcker,
Jun 2023

In automated driving (AD), high technology and individual users connect. They do so via user interfaces (UI). Since every human differs significantly in preferences and requirements towards UIs and the information shown, we now face the challenge to meet these individual requirements to enhance the customer experience in AD. We showed in two driving simulator studies that differences in information preferences for the UI are connected to differences in user characteristics. Based on this, we now create a set of design principles (DP) including its mathematical modeling that helps to translate user characteristics into personalized interface configurations. As user characteristics, we incorporate experience with AD, driving frequency, sight impairs, and attitude towards technology. For information, we chose surrounding traffic, surrounding infrastructure, and potential limits of the AD system. We hope that the DPs contribute to theoretical knowledge and future vehicle development processes fostering users’ feelings of safety, comfort, and satisfaction.

Literature procurement: IEEE
@article{2666,
author= {Driesen-Micklitz, Tim and Fellmann, Michael and Röcker, Carsten},
title= {A Set of Design Principles for Personalized Information in Automated Driving User Interfaces Based on Theory and Empirical Evidence},
journal= {2023 IEEE Intelligent Vehicles Symposium (IV)},
year= {2023},
volume= {},
number= {},
pages= {0},
month= {Jun},
note= {},
}