Citizen Perception of Future Street Scenarios

Last registered on September 08, 2022


Trial Information

General Information

Citizen Perception of Future Street Scenarios
Initial registration date
August 31, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
September 08, 2022, 11:43 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.



Primary Investigator

ETH Zurich

Other Primary Investigator(s)

PI Affiliation
ETH Zurich
PI Affiliation
ETH Zurich

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Road infrastructures have limited capacity and need to be used more sustainably in the future, satisfying diverse and variable demands. We, therefore, explore the concept of adaptive infrastructures and flexible usage patterns of roads. For this purpose, we have created various scenarios in computer simulations, which have then been explored by experimental subjects in a three-dimensional virtual reality setting using VR glasses. Based on their feedback, we assess what scenarios are more or less promising for the future organisation of urban mobility.
External Link(s)

Registration Citation

Argota Sanchez-Vaquerizo, Javier , Carina I. Hausladen and Carina Ines Hausladen. 2022. "Citizen Perception of Future Street Scenarios." AEA RCT Registry. September 08.
Sponsors & Partners


Experimental Details


Our independent variable is an information treatment: Group *information* will watch videos from a birdseye perspective for every scenario (basic/flexible/laneless). Subsequently, the participant has to cross the street. Group *efficacy* first watches the videos in the same order as group information. Additionally, they will watch the same videos on a split-screen to compare the differences (in efficacy) across scenarios and situations. Hence, they additionally get qualitative information about the efficacy of a traffic scenario.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
The experiment tests whether the user’s information about the scenario influences stress, perceived safety, willingness to cross and share the street, and physiological parameters.
Primary Outcomes (explanation)
Stress, perceived safety, and willingness to cross and share the street are self-reported. Stress is measured via the Short Stress State Questionnaire. Physiological parameters are measured via the Garmin HRM-Pro breast strap, and the Empatica embrace two wristband:
1. Heart rate sensor: To measure the heart rate and the heart rate variation (HRV). HRV characteristics describe stress, ease, engagement, and any imbalance within the autonomous nervous system.
2. Electrodermal activity (EDA) sensor: To understand the changes in skin electrical conductance in response to sweat secretion. It has been found that EDA has a strong association with emotional arousal
3. Inertial sensors: Combination of sensors like accelerometer, gyroscope, and magnetometer to identify the body position, acceleration, and orientation. The data could provide valuable insights into different stimuli that affect body movements.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
After entering the lab, participants take a seat at a computer. The session has five steps:
1. Before each experimental session, participants will be given an information sheet and asked to complete an informed
consent form.
2. Next, participants complete the pre-test questions from the SSSQ.
3. Participants watch videos (22”) through VR glasses, depending on their treatment group.
4. Next, participants stand up and get verbal instructions on how to
wear the VR glasses (see appendix). Then they try the
functionality of the headset and the controllers in an abstract VR environment. Steps 4 and 5 are supervised 1:1 by the experimenter.
5. Then they repeat the following steps three times in three different traffic sessions:
a. First, they watch (through an oculus quest 2) a traffic scenario in which they are asked to cross the street. Participants will have small breaks between replays.
b. They return to the computer and answer the post-test questions from SSSQ, perceived level of safety, willingness to cross and the walkable street survey.
6. Finally, participants complete socio-demographic and open-ended questions. Participants will read a debriefing on the exact data that has been collected. More precisely, they will be informed that we evaluate heart rate variability, skin conductance, stride length, walking cadence, vertical ratio, ground contact time, and respiration rate to quantify the difference in reaction to the different scenarios.
Experimental Design Details
Randomization Method
Participants are handled 1:1; therefore, treatment condition alternate, e.g. the first participant is in treatment *information*, the second in *efficacy*, and the third in *information*.
Randomization Unit
Randomization takes part on the participant level.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Twenty participants in each treatment group.
Sample size: planned number of observations
40 participants.
Sample size (or number of clusters) by treatment arms
40 participants.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Ethics Commission of ETH Zurich
IRB Approval Date
IRB Approval Number
EK 2020-N-183


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials