Queues, and Spaces framed by Time

Study of how people move through spaces along a linear timeline, a perceived one, along with the psychology and design behind it.

I approach this with first a broad overview of the many different types of lines and spaces and business models that reflect this diversity.

Time and it’s designed manifestations

After analyzing a lot of different spaces and types of queues, I narrowed down on Oishi, because they have an interesting physical-digital queue system that allows them to go through nearly half a thousand customers a day within a small restaurant space and little to no physical line pile up.

Some basic layout and physical feature analysis below:

The highlighted are significant features within the space that catch your attention and are important in how they move you through both the physical space and the perceived timeline.

Carpet and Menu:

Food Case:

Chairs around the perimeter of the room:

Complimentary tea:

ok yeah yeah yeah, so all these things either direct the person around a space, notify, or occupy their attention. Sure, fine, that’s great….but can their purposes be done in more interesting ways?

Problems I have with the current system:

• the physical line to order isn’t long, but the wait for food is.
• the digital queue is a step in the right direction because now you can relax where you want and be notified when your food is ready, but AAAAAGH — I can’t stand the ALARMING ding dong! that comes with the sign announcing every order number. Can it be done in a way that doesn’t interrupt everyone in the vicinity or alarm the customer?
• Because there isn’t any visible/clear logic to when an order is done, (as in #308 can come way before #300 depending on cooktime) there’s always some anxiety I feel when I see the board announcing a number after me; I ask, did I miss mine already?

From there, things I want to explore:

• Can I see the food making process? I don’t want to wait in line for it the way you do at inoodle, chipotle or piada, but it’d be nice to have some transparency.
• Can we make something that augments the experience of the digital queue within a physical space? No more alarming vibrators or ding dong door bell receipt number displays.

Possible implementations of analysis:

• Mock restaurant: food vending popup: Buy food, set up a room and invite testers inside and see how my system handles their wait times
• If digital, small working demo projected?
• Small scale, working model and concept video? Interactive wall?

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4 hours on Saturday, record when people enter, where they wait, what they do while they wait, and then ask them in person how long the wait for their order felt like. Compare their feeling with records of how long they actually took.

Took lots of timelapses, but encountered difficulty with owner of the restaurant. I stayed in a corner and tried to be discrete with a iphone filming a timelapse.

My classmate Soonho filmed the upstairs dining/waiting room.

From studying the spaces and people’s activities I wanted to see whether their was a reflection of how people occupied and moved through space in how they experienced or moved through time.

A flexible, modular structure program that could take real data and compare the different ‘paths’ and its repercussions to perceived time relationship to actual time would help synthesize observations and aid in drawing correlations with less personal bias and preconceptions.

That being said, the modular program would be more of a research aid, and for presentation purposes will need to be put into context and built up to. The end result of making the program is an interactive separate visualization to play with after watching the video that builds up the conceptual framework .

Video presentation of research:

• timelapse of people moving phsycially through space
• Quick conceptual framework aided by the echo effect in After effects that emphasizes points of ‘occupation’ and makes the movements transitioning between crucis points faded away.
• Slight abstraction of the timelapse — lines through picture space of the different possible paths
• slightly more abstract graph of people’s movement and how they occupy their waiting time and those factor’s relation to how far off their percieved time is from the actual time passed.

Project assets:

https://www.youtube.com/watch?v=8_QFzXDK588 video tutorial on animated ‘tron’ styled lines inspired our capture of line paths

The paths were common routes and combinations people took:

1. came in, ordered, waited downstairs, picked up order, left
2. came in, ordered, waited downstairs, picked up order, stayed to eat
3. came in, ordered, waited upstairs, picked up order, left
4. came in, ordered, waited upstairs, picked up order, stayed to eat

Of those 4 options, there were variations in whether the person came in solo, or in a group and what they did to occupy their waiting time.

These come from data collected from live observation and encoded into numbers. Each row of {#,#,#,#,#,#,#,#} is the data from an individual. Each number within indivudal {}’s answers a question according to the commented out text at the top of the program.

ex: {0,#,#,#,#,#,#,#} = the first number in this array denotes the answer to the first question of whether this person came in to Oishi by themselves or in a group. The fact that this number is a 0 as opposed to a 1 means they came by themselves (solo).

While I was there, I wondered about possible confounding variables:

I wanted to see the people who did something other than look at their phone and talk so I clicked on the ‘other’ node in the “WHAT THEY DO WHILE WAITING” column. Note that he came in a little after 2pm, waited downstairs, wasn’t occupied with his phone or talking, and left immediately after picking up his order. Ok, so that’s what he did literally….how did he experience this time perceptually?

Turning the axis reveals how this person’s perceived time compared to everyone else.

This is the raw screen recording of the java program running, but will actually be used as a background asset to the video presentation.

ok, so having the time (12pm — 4pm) on the side is incredibly confusing for people if it’s the first thing they see. They then have trouble understanding the nodes as locations and activities and are confused about the ‘time hops’

I’ve removed the time, because what this visualization seeks to explore is how people occupy themselves, the space (upstairs or downstairs) and whether they stay to eat or not, and how all of those might have a general trend or effect on people’s perception of time in relation to actual time.

Along the xy plane, the infographic is useful for determining trends of occupation;

the node ‘talking to others’ is clicked on, and only the people who occupied themselves while waiting for their food by talking to others are highlighted. From here, we can see that talking to others is common both upstairs and downstairs and has little to do with location

This is great for trying to find trends and general overarching correlations

Only the people who occupied their wait time by talking to other people are highlighted above. As they turn from xy axis to view the xz axis, we see that most people who talked are under the redline. The redline denotes if perceived time felt the same as actual time and thus, the experience with time is rather neutral or straightforward. Anything above the red line is for people who reported feeling more time pass than actually did, and the lines below or those that reported less time than actually passed. A trend could be said that people who talk to each other feel lile time is a quick experience because they reported feeling as if less than actual time passed.