Name: A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants (Video) | JoVE Journal
Uploaded: 2018-08-26T14:00:00.000+00:00
Duration: 6 min 28 s
Description: Learn a networked desktop virtual reality protocol for decision science and spatial cognition research. This method enables efficient monitoring of multiple participants during wayfinding experiments.

ai_agent_IP

ai_agent

maintenance

instantTrialDurationMinutes

isBiopharma

enableNewMyJoveSectionDesign

educationFeatures

seoMetaApi

ai_copilot_institution_blacklist

ai_chat_institution_blacklist

freeAccessWindow

ssoRoleCapture

scheduledMaintenanceBanner

joveLabsFeatures

disable_autoplay_for_bots

extended_trial_duration

5 minutes

The representative study was funded by the Swiss National Science Foundation as part of the grant &#34;Wayfinding in Social Environments&#34; (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.

All methods described here have been approved by Research Ethics Committee of ETH Z&#252;rich as part of the proposal EK 2015-N-37.
1. Recruit Participants for the Planned Experimental Session.
<ol>
	<li>Sample the participants within particular constraints (e.g., age, gender, educational background) using the participant recruitment system.</li>
	<li>Send invitations by email to the randomly selected participants using the contact information provided by the recruitment system.</li>
	<li>Wait for these participants to register via the online system. Make sure that more participants than required (e.g., 4 overbooked participants for a session that requires 36 people) register. Overbooked participants help ensure that a session is viable in the event of no-shows.</li>
	<li>Ensure that a confirmation email is sent to registered participants automatically.</li>
</ol>
2. Prepare the Experimental Session.
<ol>
	<li>Prepare the laboratory environment.
	<ol>
		<li>Print the participant list from the recruitment system.</li>
		<li>Turn on the server and the lights in the control room of the DeSciL and organize the testing rooms according to the required number of participants.</li>
		<li>Copy the executable experiment program and its corresponding configuration files on the network drive. This executable program deploys a custom-written software framework based on the Unity game engine to support client-server communication among different computers through a local area network. For navigation experiments, the framework provides a bird-eye observer server system for monitoring the client&#8217;s behaviors during the experiment.</li>
		<li>Open PowerShell Integrated Scripting environment on the Windows desktop. In the PowerShell console, specify an array of computer names (e.g., $pool = &#8220;descil-w01&#8221;, &#8220;descil-w02&#8221;&#8230;) to create a client pool object. Next, type Start-Pool $pool to start the client computers and Register-Pool $pool to connect the server to the client computers.</li>
		<li>Prepare the computers on the client side before launching the program. Type Invoke-Pool { Mount-NetworkShare $path} to direct the computers to enter the right folder path.</li>
		<li>Execute the prepared functions on the server (i.e., Start-GameServer) and on the clients (i.e., Invoke-Pool { Start-GameClient }). Specify the IP address of the server as parameter of the function.</li>
		<li>Wait for a message on the server&#8217;s monitor that indicates a successful connection.</li>
		<li>Distribute the consent forms and pens in each cubicle. The consent forms contains the information regarding the study (e.g., the purpose of the study, potential risks and benefits of the experiment), the contact information for the experimenter, and a legal disclaimer.</li>
		<li>Shuffle the deck of seating cards that indicate the seating arrangement of the participants.</li>
	</ol>
	</li>
	<li>Welcome the participants.
	<ol>
		<li>Ask the participants to wait outside of the laboratory. 5 min before the official start time, check the participants&#8217; identity documents to ensure that they match the list of registered participants. At the same time, let the participants pick a card that indicates their seat number. Have the participants walk to the corresponding cubicle and wait for the experiment to begin.</li>
		<li>Wait a few minutes for the participants to read and sign the consent forms. Collect these forms before conducting the experiment.</li>
	</ol>
	</li>
</ol>
3. Conduct the Experiment.
<ol>
	<li>Broadcast the experiment instructions with the microphone to all of the participants. Inform them of the basic rules, including no communication to other participants and no personal electronic devices permitted. Ask the participants to raise their hands if they have any questions regarding the experiment.</li>
	<li>Begin the experiment by presenting the demographic questionnaire (e.g., gender and age) on each client.</li>
	<li>Deploy the training scene to teach the participants how to maneuver through the virtual environment. If the participants have trouble using the control interface (e.g., mouse and keyboard), walk towards their cubicle in order to assist them. Keep monitoring the participants&#8217; progress by requesting screenshots from all of the clients (i.e., type Get-ScreenShots on PowerShell console) until all of the participants have finished the training session.</li>
	<li>After the training session, begin the testing phase of the experiment. Observe the participants&#8217; behaviors from the bird&#8217;s-eye interface on the server computer. Send warning messages to the participants through the program if they are doing something abnormal by clicking on their avatar. Otherwise, try not to interfere with the participants during the experiment.</li>
	<li>Ensure that there is a short waiting period before each trial for loading the next scene and allowing the participants to read the instructions.</li>
</ol>
4. Finalize the Experiment.
<ol>
	<li>Close the server and client program by typing Stop-GameClient and Stop-GameServer in the PowerShell console.</li>
	<li>Ask the participants to remain seated until their number is called over the microphone.</li>
	<li>Extract the participants&#8217; final scores from the file &#8220;Score.txt&#8221; in the project folder on the server computer and convert their scores into a monetary payment.</li>
	<li>Call the cubicle numbers one at a time and meet each participant at the reception desk. Thank the participants and give them the corresponding payment.</li>
	<li>Examine the cubicles and collect any remaining pens or forms.</li>
	<li>Copy and save the experiment data from the server to an external disk for future analysis.</li>
</ol>

<ol><li>Waller, D., Nadel, L. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aWaller%2C+D+%22Handbook+of+Spatial+Cognition%22">Handbook of Spatial Cognition</a>. , American Psychological Association. Washington D.C. (2013).</li>
<li>Denis, M. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aDenis%2C+M+%22Space+and+Spatial+Cognition%3A+A+Multidisciplinary+Perspective%22">Space and Spatial Cognition: A Multidisciplinary Perspective</a>. , Routledge. Abingdon, Oxon. (2017).</li>
<li>Moussaïd, M., Kapadia, M., Thrash, T., Sumner, R. W., Gross, M., Helbing, D., Hölscher, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Crowd+behaviour+during+high-stress+evacuations+in+an+immersive+virtual+environment%5BTitle%5D)+AND+%22Journal+of+the+Royal+Society+Interface%22%5BJournal%5D)">Crowd behaviour during high-stress evacuations in an immersive virtual environment.</a> Journal of the Royal Society Interface. 13 (122), 20160414(2016).</li>
<li>Grübel, J., Weibel, R., Jiang, M. H., Hölscher, C., Hackman, D. A., Schinazi, V. R. <a target="_blank" href="https://link.springer.com/chapter/10.1007/978-3-319-68189-4_10">EVE: A Framework for Experiments in Virtual Environments.</a> Spatial Cognition X: Lecture Notes in Artificial Intelligence. , 159-176 (2017).</li>
<li>Loomis, J. M., Blascovich, J. J., Beall, A. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Immersive+virtual+environment+technology+as+a+basic+research+tool+in+psychology%5BTitle%5D)+AND+%22Behavior+Research+Methods%2C+Instruments%2C+%26+Computers%22%5BJournal%5D)">Immersive virtual environment technology as a basic research tool in psychology.</a> Behavior Research Methods, Instruments, & Computers. 31 (4), 557-564 (1999).</li>
<li>Brooks, F. P. <a target="_blank" href="https://dl.acm.org/citation.cfm?id=618660">What's Real About Virtual Reality?</a> Proceedings IEEE Virtual Reality. , Cat. No. 99CB36316 (1999).</li>
<li>Moorthy, K., Munz, Y., Jiwanji, M., Bann, S., Chang, A., Darzi, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Validity+and+reliability+of+a+virtual+reality+upper+gastrointestinal+simulator+and+cross+validation+using+structured+assessment+of+individual+performance+with+video+playback%5BTitle%5D)+AND+%22Surgical+Endoscopy+and+Other+Interventional+Techniques%22%5BJournal%5D)">Validity and reliability of a virtual reality upper gastrointestinal simulator and cross validation using structured assessment of individual performance with video playback.</a> Surgical Endoscopy and Other Interventional Techniques. 18 (2), 328-333 (2004).</li>
<li>Weisberg, S. M., Schinazi, V. R., Newcombe, N. S., Shipley, T. F., Epstein, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Variations+in+cognitive+maps%3A+Understanding+individual+differences+in+navigation%5BTitle%5D)+AND+%22Journal+of+Experimental+Psychology%3A+Learning+Memory+and+Cognition%22%5BJournal%5D)">Variations in cognitive maps: Understanding individual differences in navigation.</a> Journal of Experimental Psychology: Learning Memory and Cognition. 40 (3), 669-682 (2014).</li>
<li>Schinazi, V. R., Nardi, D., Newcombe, N. S., Shipley, T. F., Epstein, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Hippocampal+size+predicts+rapid+learning+of+a+cognitive+map+in+humans%5BTitle%5D)+AND+%22Hippocampus%22%5BJournal%5D)">Hippocampal size predicts rapid learning of a cognitive map in humans.</a> Hippocampus. 23 (6), 515-528 (2013).</li>
<li>Ruddle, R. A., Payne, S. J., Jones, D. M. <a target="_blank" href="http://orca.cf.ac.uk/35419/1/Ruddle%201998.pdf">Navigating Large-Scale &#34;Desk- Top&#34; Virtual Buildings: Effects of orientation aids and familiarity.</a> Presence. 7 (2), 179-192 (1998).</li>
<li>Riva, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Virtual+Reality+in+Psychotherapy%3A+Review%5BTitle%5D)+AND+%22CyberPsychology+%26+Behavior%22%5BJournal%5D)">Virtual Reality in Psychotherapy: Review.</a> CyberPsychology & Behavior. 8 (3), 220-230 (2005).</li>
<li>Ruse, S. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Development+of+a+Virtual+Reality+Assessment+of+Everyday+Living+Skills%5BTitle%5D)+AND+%22Journal+of+Visualized+Experiments%22%5BJournal%5D)">Development of a Virtual Reality Assessment of Everyday Living Skills.</a> Journal of Visualized Experiments. (86), 1-8 (2014).</li>
<li>Ploydanai, K., van den Puttelaar, J., van Herpen, E., van Trijp, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Using+a+Virtual+Store+As+a+Research+Tool+to+Investigate+Consumer+In-store+Behavior%5BTitle%5D)+AND+%22Journal+of+Visualized+Experiments%22%5BJournal%5D)">Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior.</a> Journal of Visualized Experiments. (125), 1-15 (2017).</li>
<li>Satava, R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Virtual+reality+surgical+simulator+-+The+first+steps%5BTitle%5D)+AND+%22Surgical+Endoscopy%22%5BJournal%5D)">Virtual reality surgical simulator - The first steps.</a> Surgical Endoscopy. 7 (3), 203-205 (1993).</li>
<li>Stanney, K. M., Hale, K. S. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aStanney%2C+KM+%22Handbook+of+virtual+environments%3A+Design%2C+implementation%2C+and+applications%22">Handbook of virtual environments: Design, implementation, and applications</a>. , CRC Press. 811-834 (2014).</li>
<li>Ryu, J., Kim, G. J. <a target="_blank" href="https://dl.acm.org/citation.cfm?id=1077551">Using a vibro-tactile display for enhanced collision perception and presence.</a> Proceedings of the ACM symposium on Virtual reality software and technology VRST 04. , 89(2004).</li>
<li>Louison, C., Ferlay, F., Mestre, D. R. <a target="_blank" href="https://ieeexplore.ieee.org/document/7893324/">Spatialized vibrotactile feedback contributes to goal-directed movements in cluttered virtual environments.</a> 2017 IEEE Symposium on 3D User Interfaces (3DUI). , 99-102 (2017).</li>
<li>Knierim, P., et al. <a target="_blank" href="https://dl.acm.org/citation.cfm?id=3050426">Tactile Drones - Providing Immersive Tactile Feedback in Virtual Reality through Quadcopters.</a> Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems - CHI EA '17. , 433-436 (2017).</li>
<li>Serafin, S., Nordahl, R., De Götzen, A., Erkut, C., Geronazzo, M., Avanzini, F. <a target="_blank" href="https://ieeexplore.ieee.org/document/7361283/">Sonic interaction in virtual environments.</a> 2015 IEEE 2nd VR Workshop on Sonic Interactions for Virtual Environments (SIVE). , 1-2 (2015).</li>
<li>Grübel, J., Thrash, T., Hölscher, C., Schinazi, V. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Evaluation+of+a+conceptual+framework+for+predicting+navigation+performance+in+virtual+reality%5BTitle%5D)+AND+%22PLoS+One%22%5BJournal%5D)">Evaluation of a conceptual framework for predicting navigation performance in virtual reality.</a> PLoS One. 12 (9), (2017).</li>
<li>Thrash, T., Kapadia, M., Moussaid, M., Wilhelm, C., Helbing, D., Sumner, R. W., Hölscher, C. <a target="_blank" href="https://www.mitpressjournals.org/doi/pdf/10.1162/PRES_a_00237">Evaluation of control interfaces for desktop virtual environments.</a> Presence. 24 (4), (2015).</li>
<li>Ruddle, R. A., Volkova, E., Bülthoff, H. H. <a target="_blank" href="https://dl.acm.org/citation.cfm?id=2465785">Learning to walk in virtual reality.</a> ACM Transactions on Applied Perception. 10 (2), 1-17 (2013).</li>
<li>Moussaïd, M., Perozo, N., Garnier, S., Helbing, D., Theraulaz, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+walking+behaviour+of+pedestrian+social+groups+and+its+Impact+on+crowd+dynamics%5BTitle%5D)+AND+%22PLoS+One%22%5BJournal%5D)">The walking behaviour of pedestrian social groups and its Impact on crowd dynamics.</a> PLoS One. 5 (4), e10047(2010).</li>
<li>Bode, N. W. F., Franks, D. W., Wood, A. J., Piercy, J. J. B., Croft, D. P., Codling, E. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Distinguishing+Social+from+Nonsocial+Navigation+in+Moving+Animal+Groups%5BTitle%5D)+AND+%22The+American+Naturalist%22%5BJournal%5D)">Distinguishing Social from Nonsocial Navigation in Moving Animal Groups.</a> The American Naturalist. 179 (5), 621-632 (2012).</li>
<li>Kinateder, M., et al. <a target="_blank" href="https://www.sciencedirect.com/science/article/abs/pii/S1369847814000771">Social influence on route choice in a virtual reality tunnel fire.</a> Transportation Research Part F: Traffic Psychology and Behaviour. 26, 116-125 (2014).</li>
<li>Drury, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Cooperation+versus+competition+in+a+mass+emergency+evacuation%3A+A+new+laboratory+simulation+and+a+new+theoretical+model%5BTitle%5D)+AND+%22Behavior+Research+Methods%22%5BJournal%5D)">Cooperation versus competition in a mass emergency evacuation: A new laboratory simulation and a new theoretical model.</a> Behavior Research Methods. 41 (3), 957-970 (2009).</li>
<li>Helbing, D., Buzna, L., Johansson, A., Werner, T. <a target="_blank" href="https://pubsonline.informs.org/doi/abs/10.1287/trsc.1040.0108">Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions.</a> Transportation Science. 39 (1), 1-24 (2005).</li>
<li>Moussaïd, M., Helbing, D., Theraulaz, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((How+simple+rules+determine+pedestrian+behavior+and+crowd+disasters%5BTitle%5D)+AND+%22Proceedings+of+the+National+Academy+of+Sciences+of+the+United+States+of+America%22%5BJournal%5D)">How simple rules determine pedestrian behavior and crowd disasters.</a> Proceedings of the National Academy of Sciences of the United States of America. 108 (17), 6884-6888 (2011).</li>
<li>Singh, S., Kapadia, M., Faloutsos, P., Reinman, G. An open framework for developing, evaluating, and sharing steering algorithms. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aSingh%2C+S+%22International+Workshop+on+Motion+in+Games%22">International Workshop on Motion in Games</a>. , Springer. Berlin, Heidelberg. 158-169 (2009).</li>
<li>Singh, S., Kapadia, M., Hewlett, B., Reinman, G., Faloutsos, P. A modular framework for adaptive agent-based steering. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aSingh%2C+S+%22Symposium+on+Interactive+3D+Graphics+and+Games%22">Symposium on Interactive 3D Graphics and Games</a>. , ACM. (2011).</li>
<li>Bode, N., Codling, E. <a target="_blank" href="https://www.sciencedirect.com/science/article/pii/S0003347213002443">Human exit route choice in virtual crowd evacuations.</a> Animal Behaviour. 86, 347-358 (2013).</li>
<li>Bode, N. W. F., Kemloh Wagoum, A. U., Codling, E. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Human+responses+to+multiple+sources+of+directional+information+in+virtual+crowd+evacuations%5BTitle%5D)+AND+%22Journal+of+the+Royal+Society+Interface%22%5BJournal%5D)">Human responses to multiple sources of directional information in virtual crowd evacuations.</a> Journal of the Royal Society Interface. 11 (91), 20130904(2014).</li>
<li>Pandzic, I. S., Capin, T., Lee, E., Thalmann, N. M., Thalmann, D. A flexible architecture for virtual humans in networked collaborative virtual environments. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aPandzic%2C+IS+%22Computer+Graphics+Forum%22">Computer Graphics Forum</a>. 16, Blackwell Publishers Ltd. (1997).</li>
<li>Joslin, C., Pandzic, I. S., Thalmann, N. M. <a target="_blank" href="http://www.miralab.ch/bibliography/69.pdf">Trends in networked collaborative virtual environments.</a> Computer Communications. 26 (5), 430-437 (2003).</li>
<li>Molka-Danielsen, J., Chabada, M. Application of the 3D multi user virtual environment of Second Life to emergency evacuation simulation. <a target="_blank" href="https://ieeexplore.ieee.org/abstract/document/5428708/">System Sciences (HICSS), 2010 43rd Hawaii International Conference</a>. , IEEE. 1-9 (2010).</li>
<li>Normoyle, A., Drake, J., Safonova, A. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aNormoyle%2C+A+%22Egress+online%3A+Towards+leveraging+massively%2C+multiplayer+environments+for+evacuation+studies%22">Egress online: Towards leveraging massively, multiplayer environments for evacuation studies</a>. , Tech Reports No MS-CIS-12-15 (2012).</li>
<li>Bock, O., Baetge, I., Nicklisch, A. <a target="_blank" href="https://www.sciencedirect.com/science/article/pii/S0014292114001159">hroot: Hamburg registration and organization online tool.</a> European Economic Review. 71, 117-120 (2014).</li>
<li>Tanvir Ahmed, D., Shirmohammadi, S., Oliveira, J., Bonney, J. <a target="_blank" href="https://ieeexplore.ieee.org/document/4373946/">Supporting large-scale networked virtual environments.</a> Virtual Environments, Human-Computer Interfaces and Measurement Systems, 2007. IEEE Symposium. , 150-154 (2007).</li>
<li>Cipresso, P., Bessi, A., Colombo, D., Pedroli, E., Riva, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Computational+psychometrics+for+modeling+system+dynamics+during+stressful+disasters%5BTitle%5D)+AND+%22Frontiers+in+Psychology%22%5BJournal%5D)">Computational psychometrics for modeling system dynamics during stressful disasters.</a> Frontiers in Psychology. 8, 1-6 (2017).</li>
<li>Bernold, E., Gsottbauer, E., Ackermann, K., Murphy, R. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aBernold%2C+E+%22Social+framing+and+cooperation%3A+The+roles+and+interaction+of+preferences+and+beliefs%22">Social framing and cooperation: The roles and interaction of preferences and beliefs</a>. , 1-26 (2015).</li>
<li>Balietti, S., Goldstone, R. L., Helbing, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Peer+review+and+competition+in+the+Art+Exhibition+Game%5BTitle%5D)+AND+%22Proceedings+of+the+National+Academy+of+Sciences+of+the+United+States+of+America%22%5BJournal%5D)">Peer review and competition in the Art Exhibition Game.</a> Proceedings of the National Academy of Sciences of the United States of America. 113 (30), 8414-8419 (2016).</li>
<li>Gomez-Marin, A., Paton, J. J., Kampff, A. R., Costa, R. M., Mainen, Z. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Big+behavioral+data%3A+Psychology%2C+ethology+and+the+foundations+of+neuroscience%5BTitle%5D)+AND+%22Nature+Neuroscience%22%5BJournal%5D)">Big behavioral data: Psychology, ethology and the foundations of neuroscience.</a> Nature Neuroscience. 17 (11), 1455-1462 (2014).</li>
</ol>

The authors have nothing to disclose.

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...

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 validity5,6,7. For example, Weisberg and colleagues extended previous research on individual differences in spatial knowledge acquisition by demonstrating that spatial tasks in VR can provide an objective behavioral measure of spatial ability8. This study also suggested that the navigation behavior in VR approximates real-world navigation because the virtual environment was modeled after the university campus used by Schinazi and colleagues9 (see also the study of Ruddle and colleagues10). VR has also been applied to psychotherapy11, clinical assessment12, consumer behavior13, and surgery14,15. However, most VR systems lack proprioceptive and audio feedback that may improve presence and immersion16,17,18,19, require training with the control interface20,21,22, and lack social cues. Indeed, people in the real world often move in groups23, avoid or follow other people3,24, and make decisions based on social context25,26.
At the same time, research on crowd behavior often focuses on emergent characteristics of crowds (e.g., lane formation, congestion at bottlenecks) that are simulated on a computer or observed in the real world. For example, Helbing and colleagues used a combination of real-world observations and computer simulations in order to suggest improvements to traffic flow in an intersection by separating inflow and outflow with physical barriers and placing an obstacle in the center27. Moussa&#239;d and colleagues used a heuristics-based model to study high-density situations during a crowd disaster28. This approach suggested improvements to an environmental setting for mass events in order to avoid crowd disasters. With the aid of an existing open source framework, the implementation of such simulations could be relatively easy. SteerSuite is an open source framework that allows users to simulate steering algorithms and crowd behavior easily by providing tools for facilitating, benchmarking, and testing29. This framework can provide the core of an agent&#39;s navigation rationale, which is critical for successful crowd simulation. In addition, Singh and colleagues demonstrated a single platform that combines a variety of steering techniques30. While researchers can propose design interventions using such simulations, they are rarely validated with human participants in a controlled setting. Controlled experiments are rare in crowd research because they can be difficult to organize and dangerous to the participants.
VR has been employed to investigate social behavior using simple and complex virtual environments with one or more computer-simulated agents. In the study of Bode and colleagues31,32, the participants were asked to evacuate a simple virtual environment from a top-down perspective among several agents and found that exit choice was affected by static signage and motivation. Presenting participants with a more complex environment from a first-person perspective, Kinateder and colleagues found that the participants were more likely to follow a single computer-simulated agent during the escape from a virtual tunnel fire25. In a complex virtual environment with multiple agents, Drury and colleagues found that the participants tended to assist a fallen agent during an evacuation when they identified with the crowd26. Collectively, these findings suggest that VR can be an effective way of eliciting social behaviors, even with computer-simulated agents. However, some crowd behaviors may only be observed when there is a realistic social signal (i.e., when the participants are aware that the other avatars are controlled by people3). In order to address this shortcoming, the present protocol describes a method for conducting controlled experiments with multiple users in a networked VR setup. This approach has been employed in a recent study by Moussaid and colleagues in order to investigate the evacuation behavior of 36 networked participants3.
Research on networked VR has focused on topics unrelated to navigation strategies33,34 and/or relied on existing online gaming platforms such as Second Life. For example, Molka-Danielsen and Chabada investigated evacuation behavior in terms of exit choice and spatial knowledge of the building using participants recruited among existing users of Second Life35. While the authors provide some descriptive results (e.g., visualizations of trajectories), this study had difficulties with participant recruitment, experimental control, and generalization beyond this specific case. More recently, Normoyle and colleagues found that existing users of Second Life and participants in a laboratory were comparable in terms of evacuation performance and exit choice and different in terms of self-reported presence and frustration with the control interface36. The findings from these two studies highlight some of the challenges and opportunities afforded by online and laboratory experiments. Online studies are capable of drawing from a much larger and motivated population of potential participants. However, laboratory studies allow for more experimental control of the physical environment and potential distractions. In addition, online studies may pose some ethical concerns regarding data anonymity and confidentiality.
As a networked desktop VR laboratory, the Decision Science Laboratory (DeSciL) at ETH Z&#252;rich is primarily used to study economic decision-making and strategic interactions in a controlled environment. The technical infrastructure at the DeSciL consists of hardware, software for laboratory automation, and software that supports the multi-user desktop VR setup. The hardware includes high-performance desktop computers with Microsoft Windows 10 Enterprise operating system, control interfaces (e.g., mouse and keyboard, joysticks), headphones, and eye trackers (Table of Materials). All client computers are connected with Ethernet of one gigabit per second to the university network and the same network file share. There is no visible delay or lag when there are 36 clients connected. The number of frames per second is consistently above 100. The experiments are also managed and controlled with laboratory automation software based on Microsoft PowerShell (i.e., PowerShell Desired State Configuration and PowerShell Remoting). All relevant steps of the protocol are preprogrammed with PowerShell scripts called Cmdlets (e.g., Start-Computer, Stop-Computer). During the experiment, these scripts can be executed simultaneously and remotely on all client computers. This type of laboratory automation ensures an identical state of the client computers, reduces potential errors and complexity during scientific testing, and prevents researchers from having to perform repetitive manual tasks. For the navigation experiments, we use the Unity game engine (&#60;https://unity3d.com/&#62;) in order to support the development of 2D and 3D environments for multi-user, interactive desktop VR. The 36 client computers are connected to a server via an authoritative server architecture. At the start of every experiment, each client sends an instantiation request to the server, and the server responds by instantiating an avatar for that user on all of the connected machines. Each user&#39;s avatar has a camera with a 50 degrees field of view. Throughout the experiment, the clients send user&#39; input to the server, and the server updates the movement of all of the clients.
In the physical laboratory, each computer is contained in a separate cubicle within three semi-independent rooms (Figure 1). The overall size of the laboratory is 170 m2 (150 m2 for experiment room and 20 m2 for control room). Each of these rooms is equipped with audio and video recording devices. Experiments are controlled from a separate adjacent room (i.e., by providing instructions and initiating the experimental program). From this control room, the experimenters can also observe the participants in both physical and virtual environments. Together with the Department of Economics at the University of Z&#252;rich, the DeSciL also maintains the University Registration Center for Study Participants, which was implemented based on h-root37.
Although similar systems have been described in the literature38, the DeSciL is the first functional laboratory that is suitable for multi-user desktop VR experiments on navigation and crowd behavior to our knowledge. Here, we describe the protocol for conducting an experiment in the DeSciL, present representative results from one study on social navigation behavior and discuss the potential and limitations of this system.

<table><tbody><tr><td>PC</td><td>Lenovo</td><td>IdeaCentre AIO 700</td><td>24&amp;rsquo;&amp;rsquo; screen, 16 GB RAM, and SSDs. CPU: Intel core i7. GPU:NVidia GeForce GTX 950A</td></tr><tr><td>Keyboard</td><td>Lenovo</td><td>LXH-EKB-10YA</td><td></td></tr><tr><td>Mouse</td><td>Lenovo</td><td>SM-8825</td><td></td></tr><tr><td>Eye tracker</td><td>Tobii Technology</td><td>Tobii EyeX</td><td>Data rate: 60 Hz. Tracking screen size: Up to 27&amp;Prime;</td></tr><tr><td>Communication audio system</td><td>Biamp Systems</td><td>Networked paging station - 1</td><td>Ethernet:100BaseTX</td></tr></tbody></table>

a networked desktop virtual reality setup for decision science and navigation experiments with multiple participants

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

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.

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 16 men; m...

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 ...

a-networked-desktop-virtual-reality-setup-for-decision-science

Research

JoVE Journal

Behavior

Classical fear conditioning paradigm was adapted for human participants in a fully immersive virtual reality setting. Using a discrimination paradigm, conditioned fear, cue and context memory retention, and extinction was measured with skin conductance response to dynamic virtual snakes and spiders (the conditioned stimuli) in two distinct virtual contexts.

Human Fear Conditioning Conducted in Full Immersion 3-Dimensional Virtual Reality 

An efficient way to gain insight into how humans navigate themselves in three dimensions is described. The method takes advantage of a motion simulator capable of moving observers in ways unattainable by traditional simulators. Results confirm that movement in the horizontal plane is underestimated, while vertical movement is overestimated.

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

A new computational system featuring GPU-accelerated molecular dynamics simulation and 3D/VR visualization, analysis and manipulation of nanostructures has been implemented, representing a novel approach to advance materials research and promote innovative investigation and alternative methods to learn about material structures with dimensions invisible to the human eye.

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Virtual reality (VR) experiments can be difficult to implement and require meticulous planning. This protocol describes a method for the design and implementation of VR experiments that collect physiological data from human participants. The Experiments in Virtual Environments (EVE) framework is employed to accelerate this process.

Virtual Reality Experiments with Physiological Measures

Here, we present a simplified open-source hardware and software setup for investigating mouse spatial learning using virtual reality (VR). This system displays a virtual linear track to a head-restrained mouse running on a wheel by utilizing a network of microcontrollers and a single-board computer running an easy-to-use Python graphical software package.

An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice

A new virtual reality flight simulator was built, which enables efficient and low-cost evaluation of flight performance and eye movement patterns. It also provides a high-potential research tool for ergonomics and other research.

Evaluating Flight Performance and Eye Movement Patterns Using Virtual Reality Flight Simulator

Here, we present a novel, brief, and active spatial navigation task that assesses both spatial navigation and episodic memory ability. Importantly, spatial navigation and episodic memory were associated with one another, and this task demonstrated sensitivity to exercise.

Assessing Human Spatial Navigation in a Virtual Space and its Sensitivity to Exercise

This study describes a WebVR-based online virtual reality (VR) laboratory system that provides users with immersive and interactive experimentation capabilities supported by VR devices. The proposed system not only helps to enhance the realism of user participation in online experiments but is also applicable to a wide range of online laboratory frameworks.

Online Virtual Reality Networked Control Laboratory Applied in Control Engineering Education

The article describes the experimental procedures for the commonly used linear track virtual reality (VR) paradigm in mice as well as determining the feasibility of running complex VR tasks by testing a Y-shaped signal discrimination task.

Behavioral Training Procedures for Head-fixed Virtual Reality in Mice

Here we describe the experimental procedures involved in two-photon imaging of mouse cortex during behavior in a virtual reality environment.

Two-photon Calcium Imaging in Mice Navigating a Virtual Reality Environment

Learn a networked desktop virtual reality protocol for decision science and spatial cognition research. This method enables efficient monitoring of multiple participants during wayfinding experiments.

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

Explore More Videos