Rolling in the deep
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RESEARCH ARTICLE
Rolling in the deep User perspectives, expectations, and challenges of data and information distribution in autonomous driving Hannah Biermann1
· Ralf Philipsen1
· Teresa Brell1
· Martina Ziefle1
Received: 9 June 2020 / Accepted: 26 October 2020 © The Author(s) 2020
Abstract Autonomous driving will provide higher traffic safety, meet climate-related issues due to energy-saving mobility, and offer more comfort for drivers. To ensure reliable and safe autonomous traffic, and to provide efficient and time-critical mobility services, data exchange between road users and systems is essential. In public perception, however, sharing data and information may pose a challenge due to perceived privacy restrictions. In this paper, we address user perceptions and their acceptance towards data and information distribution in autonomous driving. In a multi-step empirical procedure, qualitative (focus groups, guided interviews) and quantitative approaches (questionnaire-study) were combined. The findings reveal that autonomous driving is commonly seen as a highly useful and appreciated technology. Though individual risk perceptions and potential drawbacks are manifold, mainly described in terms of data security and privacy-related issues. The findings contribute to research in human-automation interaction, technical development, and public communication strategies. Keywords Autonomous driving · Mobility acceptance · Data security · Privacy · Trust in automation · Mixed methods
1 Introduction Autonomous driving has already been technologically implemented in parts in many countries and will enhance daily mobility in cities in the near future (Grush and Niles 2018). Applications range from commonly used advanced driver assistance systems, such as adaptive cruise control, over prototypes of autonomous buses in public transport, up
Hannah Biermann
[email protected] Ralf Philipsen [email protected] Teresa Brell [email protected] Martina Ziefle [email protected] 1
Human-Computer Interaction Center (HCIC), Chair for Communication Science, RWTH Aachen University, Campus-Boulevard 57, 52074, Aachen, Germany
to tracks on which the possibilities of the innovative technology are tested in real life environments (Haas et al. 2020; Portouli et al. 2017; Reid 2019). The feasibility of such applications includes intelligent transportation systems to coordinate traffic (pedestrians, vehicles, road infrastructure, etc.) (Alam et al. 2016). Based on information and communication technologies, mesh networks provide the opportunity for multiple connected entities to exchange data and interact (Arena and Pau 2019). To classify levels of automation, different systems have been established, such as the standard of the National Highway Transport Safety Administration (NHTSA), the SAE standard, or the standard of the German Federal Highway Research Institute (BASt). Chances for urban mobility are to avoid traffic jams and reduce accidents, thus improving road safety, travel efficiency, a
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