A public transit app providing location-based guidance and help to the autistic community.

A collaborative graduate course project. Define and respond to a design challenge on the topic of mental health informed by qualitative research.

I led the qualitative research, interaction design and motion design.

Target Audience

There are 3.5 million Americans suffering from Autism Spectrum Disorder. They are all impaired by heightened social anxieties at different levels.

Why public transit?

Autistic people have the same travel demands, but they have limited transportation resources. The only available options for them are paratransit, transportation training and relatives driving.

We used different research methods to answer 3 guiding research questions, and generated 3 key insights.

research question 01

What are the pain points when riding public transit?

research question 02

How do autistic community cope with public transit?

research question 03

What transit tools do autistic riders prefer?

Based on research insights, we ideated 90 ideas to converge into 3 design directions.

01 Define Success

Desired Outcome

We wanted user to achieve growth and independence over time using the support of the transit service.

02 Narrowing the Scope

Idea Down Selection

We synthesized 3 design principles. Using the method of Barometer voting and 6 thinking hat, we narrowed down to 3 design directions.



design principle, the board, barometer voting, and 6 thinking hat

location-based notification

The artifact will automatically remember the daily routes of users. When users are at home getting ready for transportation, they will receive a notification about the traffic estimate including punctuality and the crowdedness of the transportation.

Split-Screen App

The artifact will allow users to interact with 2 applications at once by providing a split-screen function in the app. Users will be able to track their routes while also occupying themselves with music, video, sketching, etc.

Custosmizable Communication Page

With users’ comfort and discretion, the platform allows them to create a personalized message to display to other actors when users have a request or need they must express.

The Pivot

We took three mockup concepts and conducted user testing. The purpose of prototyping is to understand what feature is the most helpful for autistic users, how explicit is the information.



To our surprise, participants expressed that they would not use the communication feature. Presenting a phone to strangers to show text to them is a red flag and would lead to immediate rejection. They also expressed that exposing their conditions in public would make them feel uncomfortable.

Through user testing, we learned a critical pain point on the transit journey for autistic riders: communication in emergencies.

We mapped different stakeholders invovled to define the community that can help autistic riders, as well as user flows to envision the user journey.

Stakeholder Map

Storyboard


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Userflow and Screenflow


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By providing location-based and contextual guidance throughout the transit journey, our goal was to successfully guide autistic adults that are inexperienced riders from their location to their desired destination.

Learn what to expect on public transit beforehand

Get real-time transit guidance on the journey

Call for in-person help in emergency situations

Design System

*view full design spec doc here

Reflections

Customize UI

In the final presentation, we showcased Infinite Transit to Dr. Natasha. Besides approval of the overall experience, she pointed out that it would be great to allow users to have an onboarding experience where they can customize the layout, color, text and map according to their preference, since different autistic riders would have different sensitivity to color and information density.

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Understand allyship further

The experience of Infinite Transit would not be able to provide great support without a strong early traction of users engaging in the community. The viability of the service needs to be further validated with user interviews with allyship.

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Inclusivity needs smart technology

When we conducted our user research, we noticed that Google Maps has been a comforting transit app for a lot of autistic users, for it is not only giving a wide range of information before users go on a trip, but also its machine learning algorithm helps to accurately predict the transit arrival time and crowdedness through location-tracking. This is an example of how technologies that are invisible to a service can greatly improve the experience of a service, and further benefit marginalized communities such as autistic riders.