Repository logo
Research Outputs
Projects
People
Statistics
  1. Home
  2. HSG CRIS
  3. HSG Publications
  4. Comparing Pedestrian Navigation Methods in Virtual Reality and Real Life
Details

Comparing Pedestrian Navigation Methods in Virtual Reality and Real Life

Type
conference paper
Date Issued
2019
Author(s)
Savino, Gian-Luca  
;
Emanuel, Niklas
;
Kowalzik, Steven
;
Kroll, Felix
;
Lange, Marvin
;
Laudan, Matthis
;
Leder, Rieke
;
Liang, Zhanhua
;
Markhabayeva, Dayana
;
Schmeißer, Martin
;
Schütz, Nicolai
;
Stellmacher, Carolin
;
Xu, Zihe
;
Bub, Kerstin
;
Kluss, Thorsten
;
Maldonado, Jaime
;
Kruijff, Ernst
;
Schöning, Johannes  
Abstract
Mobile navigation apps are among the most used mobile applications and are often used as a baseline to evaluate new mobile navigation technologies in field studies. As field studies often introduce external factors that are hard to control for, we investigate how pedestrian navigation methods can be evaluated in virtual reality (VR). We present a study comparing navigation methods in real life (RL) and VR to evaluate if VR environments are a viable alternative to RL environments when it comes to testing these. In a series of studies, participants navigated a real and a virtual environment using a paper map and a navigation app on a smartphone. We measured the differences in navigation performance, task load and spatial knowledge acquisition between RL and VR.
Keywords
Virtual Reality
Navigation
Multi-Modal Interaction
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/124722
File(s)
Thumbnail Image
Name

Comparing_Pedestrian_Navigation_Methods_in_Virtual_Reality_and_Real_Life_ICMI19.pdf

Size

1.7 MB

Format

Adobe PDF

Checksum (MD5)

71c8f919d266962325d9679aa03917bc

Support
HSG researchers can find instructions here for adding or importing publications (DOI, ORCID). Please send questions to alexandria@unisg.ch

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Accessibility settings
  • Privacy policy
  • End User Agreement
  • Send Feedback
Repository logo COAR Notify