kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
E-ScootAR: Exploring Unimodal Warnings for E-Scooter Riders in Augmented Reality
Technical University of Darmstadt, Germany.ORCID iD: 0000-0002-6571-0623
LMU Munich, Germany.
Technical University of Darmstadt, Germany.
Technical University of Darmstadt, Germany.
Show others and affiliations
2022 (English)In: CHI 2022 - Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery (ACM) , 2022, article id 406Conference paper, Published paper (Refereed)
Abstract [en]

Micro-mobility is becoming a more popular means of transportation. However, this increased popularity brings its challenges. In particular, the accident rates for E-Scooter riders increase, which endangers the riders and other road users. In this paper, we explore the idea of augmenting E-Scooters with unimodal warnings to prevent collisions with other road users, which include Augmented Reality (AR) notifications, vibrotactile feedback on the handlebar, and auditory signals in the AR glasses. We conducted an outdoor experiment (N = 13) using an Augmented Reality simulation and compared these types of warnings in terms of reaction time, accident rate, and feeling of safety. Our results indicate that AR and auditory warnings lead to shorter reaction times, have a better perception, and create a better feeling of safety than vibrotactile warnings. Moreover, auditory signals have a higher acceptance by the riders compared to the other two types of warnings.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2022. article id 406
Keywords [en]
augmented reality, E-Scooter, micro-mobility, traffic safety
National Category
Vehicle and Aerospace Engineering Infrastructure Engineering
Identifiers
URN: urn:nbn:se:kth:diva-335640DOI: 10.1145/3491101.3519831Scopus ID: 2-s2.0-85129720480OAI: oai:DiVA.org:kth-335640DiVA, id: diva2:1795018
Conference
2022 CHI Conference on Human Factors in Computing Systems, CHI EA 2022, Virtual, Online, United States of America, Apr 30 2022 - May 5 2022
Note

Part of ISBN 9781450391566

QC 20230907

Available from: 2023-09-07 Created: 2023-09-07 Last updated: 2025-02-14Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Matviienko, Andrii

Search in DiVA

By author/editor
Matviienko, Andrii
Vehicle and Aerospace EngineeringInfrastructure Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 24 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf