Meinhardt, Luca-Maxim;
Colley, Mark;
Tahmid, Marjana;
Rädler, Max;
Rukzio, Enrico;
(2024)
Wind of Change: Investigating Information Visualizations for Passengers and Residents' Perception of Automated Urban Air Mobility.
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
, 8
(4)
, Article 171. 10.1145/3699753.
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Abstract
Automated Urban Air Mobility (UAM) is expected to improve passenger transportation but raises concerns about passenger trust and its impact on residents. We address these issues through three online studies using 360-degree videos. The study on adverse lighting and weather conditions (N=31) shows that bounding box visualizations of other air taxis positively impact passengers' perceived safety. Especially during fog, passengers' perceived safety is reduced when no additional information besides the path is shown. The second study (N=29) extends these findings to emergency scenarios (wind gusts, bird flocks, and rotor breakdown) and shows that visualizations of the alternate path increase perceived safety and trust. Finally, studying the impact of UAM on residents (N=29), we found significant concerns about visual pollution and privacy, especially in the suburbs but also in offices. Our findings provide actionable insights into UAM perception and societal acceptability for future aerial transportation design and infrastructure.
Type: | Article |
---|---|
Title: | Wind of Change: Investigating Information Visualizations for Passengers and Residents' Perception of Automated Urban Air Mobility |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1145/3699753 |
Publisher version: | http://dx.doi.org/10.1145/3699753 |
Language: | English |
Additional information: | This work is licensed under a Creative Commons Attribution International 4.0 License. © 2024 Copyright held by the owner/author(s). |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10200775 |
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