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A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published: August 26th, 2018



1Chair of Cognitive Science, ETH Zürich, 2Digital Society Initiative, University of Zürich, 3Department of Geography, University of Zürich, 4Decision Science Laboratory, ETH Zürich, 5Computer Science Department, Rutgers University

This paper describes a method for conducting multi-user experiments on decision-making and navigation using a networked computer laboratory.

Investigating the interactions among multiple participants is a challenge for researchers from various disciplines, including the decision sciences and spatial cognition. With a local area network and dedicated software platform, experimenters can efficiently monitor the behavior of the participants that are simultaneously immersed in a desktop virtual environment and digitalize the collected data. These capabilities allow for experimental designs in spatial cognition and navigation research that would be difficult (if not impossible) to conduct in the real world. Possible experimental variations include stress during an evacuation, cooperative and competitive search tasks, and other contextual factors that may influence emergent crowd behavior. However, such a laboratory requires maintenance and strict protocols for data collection in a controlled setting. While the external validity of laboratory studies with human participants is sometimes questioned, a number of recent papers suggest that the correspondence between real and virtual environments may be sufficient for studying social behavior in terms of trajectories, hesitations, and spatial decisions. In this article, we describe a method for conducting experiments on decision-making and navigation with up to 36 participants in a networked desktop virtual reality setup (i.e., the Decision Science Laboratory or DeSciL). This experiment protocol can be adapted and applied by other researchers in order to set up a networked desktop virtual reality laboratory.

Research on spatial cognition and navigation typically studies the spatial decision-making (e.g., turning left or right at an intersection) and mental representation of individuals in real and virtual environments1,2. The advantages of virtual reality (VR) include the prevention of ethical and safety issues (e.g., during a dangerous evacuation3), the automatic measurement and analysis of spatial data4, and a balanced combination of internal and external validity5,6,

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All methods described here have been approved by Research Ethics Committee of ETH Zürich as part of the proposal EK 2015-N-37.

1. Recruit Participants for the Planned Experimental Session.

  1. Sample the participants within particular constraints (e.g., age, gender, educational background) using the participant recruitment system.
  2. Send invitations by email to the randomly selected participants using the contact information provided by the recruitment system.

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For each client on each trial, the experiment data from the DeSciL typically include trajectories, time stamps, and measures of performance (e.g., whether the participant turned in the "correct" direction at a particular intersection). A representative study investigated the effects of signage complexity on the route choice for a crowd of human participants (with virtual avatars) in a simple Y-shaped virtual environment. In this experiment, 28 participants (12 women and 1.......

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In this article, we described a multi-user desktop virtual reality laboratory in which up to 36 participants can interact and simultaneously navigate through various virtual environments. The experimental protocol details the steps necessary for this type of research and unique to multi-user scenarios. Considerations specific to these scenarios include the number of participants in attendance, the cost of seemingly small experimenter errors, rendering and networking capacities (both server- and client-side), training wit.......

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The representative study was funded by the Swiss National Science Foundation as part of the grant "Wayfinding in Social Environments" (No. 100014_162428). We want to thank M. Moussaid for insightful discussions. We also want to thank C. Wilhelm, F. Thaler, H. Abdelrahman, S. Madjiheurem, A. Ingold, and A. Grossrieder for their work during the software development.


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Name Company Catalog Number Comments
PC Lenovo IdeaCentre AIO 700 24’’ screen, 16 GB RAM, and SSDs. CPU: Intel core i7. GPU:NVidia GeForce GTX 950A
Keyboard Lenovo LXH-EKB-10YA
Mouse Lenovo SM-8825
Eye tracker Tobii Technology Tobii EyeX Data rate: 60 Hz. Tracking screen size: Up to 27″
Communication audio system Biamp Systems Networked paging station - 1 Ethernet:100BaseTX

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