Research Project - VR Environments

Task 8 Train Station

In this task, users need to listen to the human character in front of them who at some point will give information about the train and number that the user needs to catch (train with number 19-Gloucester Road). Users than can walk and go inside of the trains. If the train where the user goes inside is 19-Gloucester Road, then the task is completed. If not, users need to go outside and find the right train. Nearby will be a ticket machine where they can go, press a button to listen again the train number and destination.

To understand users ability to focus on a switched attention and measured auditory and visual memory and response strategy.

Groups of participants:
-People with ADHD/ADHD traits

Task Details:
The task will include train station ambience sound, train sounds such as arriving, opening doors, leaving. The trains will arrive randomly with their number and destination.

Trains destinations:

train destinations = {

      "5 Oxford Circus",
      "7 Great Portland Street",
      "11 Baker Street",
      "19 Gloucester Road",
      "29 Tottenham Court Road",
      "45 Bond Street",
      "58 Marble Arch",
      "73 Edgware Road",
      "95 Piccadilly Circus"


Trains will wait for 10 seconds before leaving. The delay between each train (after the train has left) will be 2 seconds. The task can take approximately 5 minutes, but this depends on the person and when the right train arrives. There is a time limit of 10 minutes that task will end after this time even if user hasn’t cached the right train. In this case, we would still collect data from the task, but the reaction time will be 10 minutes.

Q1: Where were you supposed to go but you couldn’t make it? (Right answer event)
Q2: Where was the human avatar going? (Right answer Work)
Q3: I felt present and involved in VR.
Q4: The task was interesting and was similar to a scenario that can happen in our day-to-day life.
Q5: I think I didn’t do very well in completing this task.
Q6: I think I did very well in completing this task.

Data Collected:
-From the task (we save username, ticket machine pressed (how many times they pressed the ticket machine), accuracy (low, medium, or high depending on the time catching the right train and ticket machine pressed), reaction time (from after the human character stops speaking), timestamp)
-Eye tracker VR Add on (Pupil Labs)
-EEG VR Add on (Looxid Link)
-From the questionnaire

-Alienware m15 Gaming Laptop
-HTC Vive Pro
-Fovitec 2x 7'6" Light Stand VR Compatible Kit
-Pupil Labs
-Looxid Link

-Unity Asset Store

Programming Languages used:
-Python using Spyder in Anaconda
-Jupyter Notebook