Selection and comparison of human-factors related measures for evaluations of in-vehicle
devices involves weighting of multiple criteria. It may result in a complex decision-making process for the
practitioner, specifically in a time pressured industrial context. Visual information seeking has
successfully been applied to reduce the complexity of datasets in healthcare and other fields. Information
is presented visually and divided in ‘Overview’, representing the data by its characteristic criteria, and
‘Details’, which are presented on demand. This division reduces information load for the user and eases
comparison based on characteristics. This project, first, aims to understand what criteria practitioners use
to decide about the suitability of a measure for an in-vehicle evaluation. Secondly, criteria practitioners use
to select measures are implemented in a new interface approach based on methods of visual information
seeking to support users in the selection and comparison of human-factors related measures for in-vehicle
evaluations. Overall, the interface exposes practitioners to new measures, enables them to rapidly compare
measures, and obtain information to practically apply the
