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Fore-sighting autonomous driving - An Ethnographic approach

Thomas Lindgren, Sarah Pink and Vaike Fors

Technological Forecasting and Social Change, 2021, vol. 173, issue C

Abstract: A growing body of Human-Computer-Interaction research and the automotive industry has identified that understanding user needs and creating positive user experience (UX) is crucial in order to successfully introduce Autonomous Driving (AD) vehicles to the market. AD research is commonly undertaken to provide user insights by studying the individual-technology experiences in lab settings or by forecasting attitudes and acceptability through large surveys. However, these approaches base their knowledge on people's past or present expectations and limited real life experiences of AD. To better understand upcoming individual user needs and to enable new innovations beyond acceptability forecasts and UX lab tests, we need to identify new concepts through alternative methodologies that can generate user foresights based on users’ evolving anticipations of AD in their everyday lives. We propose an ethnographic approach with iterative speculative scenarios, which we demonstrate through a study undertaken with participants from five families who were introduced to evolving levels of AD, in real-life situations. To demonstrate the methodology, we draw on empirical findings which reveal anticipatory experiences, which we abstract through the concepts of confidence, hope and being-in-the-moment. We show how these concepts structured our user foresights, and outline the implications of engaging them in innovation processes.

Keywords: User experience; Everyday life; Anticipatory experiences; Autonomous driving; Ethnography; User foresight; Innovation; Speculative scenarios (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:173:y:2021:i:c:s0040162521005382

DOI: 10.1016/j.techfore.2021.121105

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