Name: using a virtual reality walking simulator to investigate pedestrian behavior
Uploaded: 2020-06-09T12:30:00
Description: Watch this Scientific Journal Video about Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior at JoVE.com

The Korea Institute funded this work for Advancement of Technology and Ministry of Trade, Industry, and Energy (grant number 10044775).

This experimental protocol involves human subjects. The procedure was approved by the Kunsan National University Research Board.
1. Preparation of equipment
NOTE: The equipment includes the following: a personal computer (PC, 3.3 GHz with 8 GM) with a mouse, keyboard, and monitor; Walking Simulator software installed on the desktop PC; a customized treadmill (width: 0.67 m, length: 1.26 m, height: 1.10 m) equipped with handrails, a belt, and a magnetic encoder with a ...

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Previous studies have used simulators with projected screens16,17, but this protocol improves ecological validity via a fully immersive virtual view (i.e., 360 degrees). In addition, requiring participants to walk on a treadmill enables the examination of how children and young adults calibrate their actions to a changing environment. This experimental design&#8217;s virtual scene changes simultaneously with participant motions, and the vehicles arrive at the ped...

An erratum was issued for:&#160;<a href="https://www.jove.com/t/61116/using-virtual-reality-walking-simulator-to-investigate-pedestrian">Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior</a>. An&#160;affiliation was updated.
The first affiliation was updated from:
Department of Sports Science, Kunsan National University
to:
Department of Sport and Exercise&#160;Sciences, Kunsan National University

An erratum was issued for:&#160;<a href="https://www.jove.com/t/61116/using-virtual-reality-walking-simulator-to-investigate-pedestrian">Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior</a>. Author and affiliation information&#160;were&#160;updated.

Erratum: Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

Gap crossing, an interceptive behavior, requires moving oneself in relation to a gap between two moving vehicles1,2,3,4. Gap crossing involves perceiving oncoming vehicles and controlling movement in relation to moving traffic. This requires actions to be precisely coupled with perceived information. Many previous studies have examined perceptual judgment and gap-crossing behavior using artificial roads, roadside simulators, and screen projection virtual environments5,6. However, previous road-crossing literature has an incomplete understanding of this behavior, and the ecological validity of these studies has been questioned7,8,9.
This protocol presents a research paradigm for studying gap crossing behavior in virtual reality, thus maximizing ecological validity. A walking simulator is used to examine the perception and actions of gap crossing behavior. The simulator provides a safe walking environment for participants, and the actual walking in the simulated environment allows researchers to fully capture the reciprocal relationship between perception and action. Individuals who actually cross a road are known to judge the time gap more accurately than those who only verbally decide to cross10. The virtual environment is ecologically valid and allows researchers to easily change task-related variables by altering the program&#8217;s parameters.
In this study, a participant&#8217;s initial starting location is manipulated to assess the velocity control while approaching the gap. This protocol allows the investigation of pedestrian locomotion control while intercepting a gap. Analyzing a participant&#8217;s velocity changing over time allows a functional interpretation of velocity adjustments while he or she approaches a gap.
In addition, the spatial and temporal characteristics of intercepted objects specify how a person can move. In a gap crossing environment, changing of the gap size (inter-vehicle distances) and vehicle size should affect how a pedestrian&#8217;s locomotion also changes. Accordingly, manipulating the gap characteristics will likely cause velocity adjustments in the participant&#8217;s approaching behavior. Thus, manipulating gap characteristics (i.e., gap size and vehicle size) provides valuable information for understanding crossing behavior changes according to various gap characteristics. This study examines how children and young adults regulate their velocity when crossing gaps in various crossing environments. The speed regulation profile can be assessed for various gap crossing environments with different starting locations, inter-vehicle distances, and vehicle sizes.

<table>
	<tbody>
		<tr>
			<td>Customized treadmill</td>
			<td>Kunsan National University</td>
			<td></td>
			<td>Treadmill built for this study</td>
		</tr>
		<tr>
			<td>Desktop PC</td>
			<td>Multiple companies</td>
			<td></td>
			<td>Standard Desktop PC</td>
		</tr>
		<tr>
			<td>Oculus Rift Development Kit</td>
			<td>Oculus VR, LLC</td>
			<td>DK1</td>
			<td>Virtual reality headset</td>
		</tr>
		<tr>
			<td>Walking Simulator Software</td>
			<td>Kunsan National University</td>
			<td></td>
			<td>Software deloped for this experiment</td>
		</tr>
	</tbody>
</table>

using a virtual reality walking simulator to investigate pedestrian behavior

To cross a road successfully, individuals must coordinate their movements with moving vehicles. This paper describes use of a walking simulator in which people walk on a treadmill to intercept gaps between two moving vehicles in an immersive virtual environment. Virtual reality allows for a safe and ecologically varied investigation of gap crossing behavior. Manipulating the initial starting distance can further the understanding of a participant&#8217;s speed regulation while approaching a gap. The speed profile may be assessed for various gap crossing variables, such as initial distance, vehicle size, and gap size. Each walking simulation results in a position/time series that can inform how velocity is adjusted differently depending on the gap characteristics. This methodology can be used by researchers investigating pedestrian behavior and behavioral dynamics while employing human participants in a safe and realistic setting.

The walking simulator can be used to examine a pedestrian&#8217;s crossing behavior while manipulating the initial distance from curb to interception point and the gap characteristics (i.e., gap and vehicle sizes). The virtual environment method allows the manipulation of gap characteristics to understand how dynamically changing crossing environments affect children&#8217;s and young adults&#8217; road-crossing behaviors.
A quantified velocity profile and crossing position within the gap used...

Watch this Scientific Journal Video about Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior at JoVE.com

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

This protocol describes use of a walking simulator that serves as a safe and ecologically valid method to study pedestrian behavior in the presence of moving traffic.

To cross a road successfully, individuals must coordinate their movements with moving vehicles. This paper describes use of a walking simulator in which ...

This highly immersive virtual reality protocol allows us to investigate how people adjust their emotion during crossing. Virtual walking on a treadmill makes it possible to fully captures the reciprocal relationship between perception and action. This message that can provide insight into the field of behavioral ecology as well as allow researchers to explore our passions in pedestrian safety and autonomous vehicle development.It is helpful to use diagrams to visualize the crossing situation so that the researcher may calibrate the parameters correctly to suit the purpose of his or her study. Demonstrating their procedure will be Hui Li, a graduate student from my laboratory. Begin by setting the parameters on the Walking Simulator using the Config Directory.In the car section, set the parameters for the first vehicle. Set type to one for sedan, two for bus or zero for no vehicle. Next, set speed in kilometers per hour and distance to the desired value in meters.Complete the second car section by setting the same parameters. The road section contains parameters for lane selection, set the parameter lane to one to use the lane closer to the pedestrian starting position or two for the lane further away. In the saved section which contains the parameter related to sampling frequency, set the parameter number per second to the desired value in hertz then save the configuration file and exit.Prepare three practice trial configuration files and create a separate sheet with the list of configurations to be used in the experiment in a randomized order. Recruit participants with normal or corrected to normal vision and ask them to sign a written informed consent form before each experiment. Play an audio recording with verbal instructions of the task to the participant.And encourage them to ask questions. When ready lead the participants to the treadmill and harness the stabilizing belt to the participant's waist. Instruct them to hold the hand rails at all times during the experiment.Ask the participants to practice walking on the treadmill with the belt on while holding the hand rails. Once the participant is able to walk on the treadmill comfortably, double-click the Executable Simulator to begin the Walking Simulator Program. Instruct the participant to wear the headset, providing assistance as needed.Check for both comfort and stability with respect to head turns. Calibrate the headset so that the black and white cartoon crosswalk is properly aligned with the participants view. Inform the participant that the first practice trial will occur without any vehicles and begin the trial.Enter the first practice trials configuration number in the text box on the bottom of the screen and click the start button. Instruct the participant to look straight ahead, get ready when they hear ready and begin walking when they hear go, then give the verbal cues ready and go. When finished with the first practice trial perform the second practice trial that introduces vehicles without walking.For the third practice trial, inform the participant that it will involve two vehicles coming from the left side and that he or she should attempt to cross the road between the two vehicles. Enter the third practice trial number in the text box and click the start button. To perform the Virtual Walking Experiment, type in the first configuration number from the data sheet on the text box and click start.Perform the simulation in the same way as the final practice trial and record the results next to the configuration number on the experiment sheet. The Walking Simulator was used to determine if the initial distance from the curve to the intersection point affects the approach velocity of participants. The velocity of young adults increased throughout the approach however, when the initial distance was short, they slowed down at the beginning of the trial and sped up continuously.For children, vehicle size affected the velocity profiles and crossing position induced by the initial distance. Post-walk analysis showed that children sped up throughout the approach however, when they crossed between cars they slowed down at the beginning of the approach for the near initial distance. When children crossed between the buses, their speed neither increased nor decreased at the beginning of the approach for the near initial distance.It was found that children's times of intercept increased significantly as the initial distance increased from near to far however, when crossing between buses, children's times of interception were not significantly different between near and intermediate initial distances. In order for this method to provide accurate information about crossing behavior, the visual field scenes for the virtual reality headset must be properly calibrated. This technique allowed researchers to develop mathematical models of pedestrian behavior which were used to study concepts such as bearing angle and affordance.

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