One idea we had was to use augmented reality to help a user better understand the use of a new car at a dealership. The idea of having my stuff in a car makes it so much more personal, and for some, seeing the new car in the context of everyday travel for them could be a way to understand how it would fit in their life.
We used ethnographic interviews, shared travel experiences, and open-source data to think about the different data points that come together in the choice to select different modes of travel. Are you traveling with a partner or with kids, are you on your way to give a presentation, are you coming from a hotel in a new city? How do these contexts drive decision-making, and which attribute the most weight to the choice?
Super Ford is a game that gives reputation to shared resources and vehicles in a city. Our team began to wonder how you could give a sense of ownership or responsibility to those who lack it. In this case, when you don’t own your car, every car, bike, train, or bus is treated as a service you have no say in. This “fake” ownership can come in the form of interesting digital/physical interactions in which physical artifacts have a life on the web.
There are many decisions that go into choosing our transportation. Money, time, number of seats, privacy, space, and scenery are all some we have all felt the pain of sacrificing on. We wondered if we could prompt travelers for these interesting desires to choose a method of transport more tied to their values. What are the knobs or metrics of transportation that each user would have weights on in a machine learning model?
We tapped into unique Ford employee perspectives to determine which of our initial questions were most fruitful to tackle. We used clay as a medium to understand nostalgia for old cars, to visualize past road trips, and to re-discover play in the workplace.
We asked questions like "Think of a journey that you recently took that makes you smile."" and asked participants to make the answers out of clay. No stakes, no judgment, no instructions. They told stories about their abstract creations to clue us in to the inspirations behind the art.
How can we use the history of someone's movement (tracked by the iphone app 'Moves', and exported to Google Maps) to encourage people to explore their surroundings and break the barriers of their usual routines? This prototype uses personal, artful data visualization to inform consumers of unnoticed habits. It explores the idea of movement data as art (with the choice of line thickness, color, composition, etc. as critically important components to eventual behavior modification regarding transportation).
What is a simple way to see the emotional state or priorities of a traveler before they choose a standard mode of transport that they do not actually enjoy? This interface is the human facing side of the pseudocode to the left and would slowly disappear in the app as it got to know the user better.
Cliff Nass said that if you want to prove that a technology is smart, you must also show that it is kind. We took this to heart when we set out to build a prototype around increasing passengers’ trust in autonomous vehicles. For this prototype, an in-car display shows your vehicle and communicates what actions it is taking and why. Are you concerned about the cyclist you see up ahead? Your car sees it too, and acknowledges it by displaying their location on the screen.
Calendars and to-do lists on our phones help us keep track of the time-based components of our schedules, but we often overlook the spatial component. By integrating calendar events with your vehicle’s vitals, this prototype helps you take the journey into account as you go about your day to mitigate unwelcome surprises. Do you have a doctor’s appointment right after work tomorrow? And you won’t have enough gas to get home afterwards? Your vehicle will ask whether you want to fill up now in preparation.