Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

Summary

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.

Abstract

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’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.

Introduction

Gap crossing, an interceptive behavior, requires moving oneself in relation to a gap between two moving vehicles^1,2,3,4. 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 environments^5,6. However, previous road-crossing literature has an incomplete understanding of this behavior, and the ecological validity of these studies has been questioned^7,8,9.

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’s parameters.

In this study, a participant’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’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’s locomotion also changes. Accordingly, manipulating the gap characteristics will likely cause velocity adjustments in the participant’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.

Protocol

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 USB cable; and an Oculus Rift virtual reality device (DK1, U.S., 1280 x 800 pixels). The equipment also includes a customized manual treadmill. The treadmill turns via the walking motions of the participants and does not use an internal motor.

1. Prepare sufficient space for the treadmill and a nearby desk for the PC. A photograph of the experimental setup is shown in Figure 1A.
2. Connect the equipment as shown in Figure 2.
   1. Connect treadmill’s magnetic encoder to the PC via a USB port.
   2. Connect the treadmill to a power source.
   3. Connect the headset to the PC via DVI/HDMI and USB ports.

2. Preparation of walking simulator configurations

1. Access the walking simulator directory on the PC and open the “Config” directory.
   NOTE: Each configuration is saved as a text file in the “Config” directory with file names of “config001”, “config002”, etc. Here, 001, 002, etc. are the configuration numbers. Steps 2.2–2.8 describe how to create the configuration files so that they are readable by the simulator software. A schematic of a two-vehicle crossing situation showing customizable initial distances is shown in Figure 3. An example configuration file with proper formatting is shown in Figure 4. Section headings of the configuration file use square brackets (e.g., “[WALKER]”).
2. Complete the section [WALKER] containing the parameter regarding the starting point of the participants.
   1. Set the parameter “Distance”, which indicates the starting distance of the participant from the starting point in meters (m).
3. Complete the section [CAR] containing parameters regarding the first vehicle.
   1. Set the parameter “Type” (which indicates the type of vehicle) to “1” for sedan, “2” for bus, or “0” to remove the vehicle.
   2. Set the parameter “Speed” (which indicates the vehicle speed) to the desired value in km/h.
   3. Set the parameter “Distance” (which indicates initial distance of the vehicle from the crossing point) to the desired value in meters.
4. Complete the section [SECONDCAR] containing the parameters related to the second vehicle. Parameters are identical to those of [CAR].
   NOTE: In two-vehicle studies, the gap is defined as the empty space between the two vehicles. The gap size, defined as the length of time during which the gap is along the participant’s walking path, is a function of the “Distance”, “Speed”, and “Type” parameters of [CAR] and [SECONDCAR].
5. Complete the section [NEXTCAR] containing parameters related to additional vehicles. The parameters are identical to those of [CAR].
   NOTE: This option can be used to investigate pedestrian behavior within continuous traffic flow. This option is not discussed in the representative results section.
6. Complete the section [ROAD], containing the parameter for lane selection. Set the parameter “lane” to “1” to use the lane closer to pedestrian’s starting position, or “2” for the lane further away. [OBSTACLE] indicates the parameters that configure a vehicle traveling in the second lane at the same speed as the first vehicle.
   NOTE: When using the closer lane as the primary lane, this option can be used to place additional vehicles on the farther lane going in the same direction. Hence, it can be used to study the impedance of the view of a vehicle by a parallel vehicle. This section has parameters “Type” and “Distance” with the same definitions described above. This option is not discussed in the representative results section. All results shown involve two vehicles driving in the lane closer to the pedestrian.
7. Complete the section [SAVE], which contains the parameter related to sampling frequency. Set the parameter “numberpersecond” to the desired value in Hz.
8. Save the configuration file and exit.
9. Repeat sections 2.2–2.8 for all desired configurations and prepare data sheets with the list of configurations (in a randomized order) to be used in the experiment.
10. Prepare three configuration files to be used in the practice trials.
    NOTE: The first practice configuration should have no vehicles (i.e., all “Type” parameters set to “0”). The second and third practice configuration files should have vehicles. The third configuration should have lenient crossing conditions. The same configuration may be used for the second and third practice trials, depending on the experimental design.

3. Participation screening and preparation

1. Recruit participants with normal or corrected-to-normal vision.
   NOTE: All participants should be free of any conditions that prevent normal walking. They should be free of any dizziness while walking, and they should not have any history of serious traffic accidents.
2. Ask the participant to sign a written, informed consent form before each experiment.
3. Prepare an audio recording with verbal instructions of the task and play the recording to the participant.
   NOTE: The verbal instructions should narrate the basic procedure described below and give any specific prompts required by the experimental design.
4. Encourage the participant to ask any questions about the experiment.
5. Lead the participant to stand on the treadmill when ready.
6. Harness the stabilizing belt to the participant’s waist. Instruct the participant to hold the handrails at all times during the experiment.

4. Running the practice trials

1. Instruct the participant to practice walking on the treadmill, with the belt on, while holding the handrails.
2. Begin the walking simulator program by double-clicking the executable simulator program once the participant is able to walk on the treadmill comfortably.
   NOTE: The black and white cartoon crosswalk shown in Figure 1B is displayed between crossing trials. At this point, it should be shown on the PC screen.
3. Instruct the participant to wear the headset. Give assistance as needed. Check for both comfort and stability with respect to head turns.
4. Calibrate the headset so that the black and white cartoon crosswalk is properly aligned with participant’s view.
   NOTE: Sections 4.5–4.7 describe three practice trials, which are designed to gradually allow the participant to become accustomed to the simulator environment. If the participant fails any trial due to misunderstanding of the instructions, up to two more extra trials should be performed until the participant understands the instructions. Extra trials are not performed in cases of failure to cross for reasons other than misunderstanding the rules (e.g., if a collision occurs).
5. Begin the first practice trial.
   NOTE: The first practice trial should be without any vehicles for the participant to become accustomed to walking in the virtual reality setting.
   1. Inform the participant that the first practice trial will occur without any vehicles.
   2. Instruct the participant to look straight ahead.
   3. Enter the first practice trial’s configuration number in the text box on the bottom of the screen.
   4. Click the “Start” button at the bottom of the screen.
      NOTE: The program should display the realistic setting depicted in Figure 1C on the screen.
   5. Inform the participant to get ready when hearing “Ready” and to begin walking when hearing “Go”. Give the verbal cues “Ready” and “Go”.
6. Second practice trial
   NOTE: The second practice trial should introduce the vehicles without walking. The direction of the virtual reality view shifts as the participant’s head is turned.
   1. Instruct the participant in this trial, at the verbal cue “Go”, to look to the left and simultaneously take a small step forward, but not to walk forward any further. The participant should instead watch the vehicles pass by.
   2. Type the second trial’s configuration number into the text box and click “Start” by providing the verbal cues.
      NOTE: The vehicles begin moving as the participant begins moving.
7. Third practice trial
   NOTE: The third practice trial should be similar to the experimental configurations, but with lenient crossing conditions.
   1. Inform the participant that 1) the third practice trial will involve two vehicles coming from the left side, and 2) he/she should attempt to cross the road between the two vehicles.
   2. Enter the third practice trial number in the text box by providing the verbal cue.
   3. Click the “Start” button and begin the trial by providing the verbal cues.

5. Virtual walking experiment

1. Confirm that the participant understands the experimental task and is able to perform it.
2. When the participant is ready, type in the first configuration number from the data sheet on the text box and click “Start”.
3. Perform the simulation as done in the final practice trial.
   NOTE: At the end of each crossing trial, the program displays “S”, “F”, or “C”, depending on whether the result is a successful crossing (i.e., the participant crosses to the other side of the street with no collisions), no crossing (participant does not cross to the other side), or a collision (participant has contact with a vehicle), respectively.
4. Record the result next to the configuration number on the data sheet.
5. Repeat for all configurations on the data sheet and complete the experiment.

6. Data export and analysis

1. Retrieve the data files for analysis. The walking simulator software saves each run as a spreadsheet file in the “Data” folder.
2. Analyze data with the preferred tools. The output data records the positions and velocities of the walker and the vehicles as a time series. Use this data to analyze participant movements and the dependence on traffic conditions.

Results

The walking simulator can be used to examine a pedestrian’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’s and young adults’ road-crossing behaviors.

A quantified velocity profile and crossing position within the gap used...

Discussion

Previous studies have used simulators with projected screens^16,17, 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’s virtual scene changes simultaneously with participant motions, and the vehicles arrive at the ped...

Materials

Name	Company	Catalog Number	Comments
Customized treadmill	Kunsan National University		Treadmill built for this study
Desktop PC	Multiple companies		Standard Desktop PC
Oculus Rift Development Kit	Oculus VR, LLC	DK1	Virtual reality headset
Walking Simulator Software	Kunsan National University		Software deloped for this experiment