Mobile UX, Service Design

The future of autonomous commuting


CONCEPT: Avivi is an autonomous shuttle service that offers commuters a fixed route in the morning and a flexible on-demand service after work. Avivi is designed to bring autonomous vehicles to the public in a way that is sustainable, affordable, and dependable.

CHALLENGE: Design an ecosystem that spans across multiple channels; 7 weeks

TEAM: Carlie Guilfoile, Ulu Mills

TOOLS: Adobe AfterEffects, InDesign, Illustrator, Fusion 360, Pen + Paper



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A multimodal service that utilizes AV technology to connect commuters to public transit in a way that fits their schedule.

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How might we leverage autonomous vehicle technology to bridge the transportation gap sustainably, affordably, and dependably?


There are many possible futures.

By 2030, 20M+ AVs are expected to be in operation. While this is reality, there are many possible futures that dictate how these vehicles will shape our cities, towns, and roadways.

We can leverage new tech to put city resources to better use.

Public transportation and city budgets have a limited reach. The last mile problem hinders people from taking buses, trains, and subways.

Most Americans are driving to work.

90% of U.S. commuters use personal vehicles as their primary mode of transportation – causing major road congestion during commute times.




Ulu and I partnered with a mutual interest in creating something for social good. During our early meetings, we discussed what current disruptive technologies have potential to have the most positive effects on communities. I shared my personal interest in transportation and energy and proposed that we think about how autonomous vehicles might shape our communities and roadways for the better.



Defining Stakeholders

We developed an Autonomous Vehicle territory map to discover shared concerns among stakeholders in the commuting space. After our first few iterations, we realized that visualizing these shared concerns was difficult because there was a lot of overlap between different assemblages of stakeholders.

Our final territory map reflected the fact that these lines of concern were blurred, by showing a group of users in the center, surrounded by their granular concerns, with overarching themes in the last layer.

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Research Methods



To understand commuter’s perceptions of autonomous vehicles and motivations for their way of commute.


To learn about the industry trends, the latest technologies and challenges.


The transportation industry is evolving quickly, so we looked at the usability of services and business structures transportation companies are using.


We dug into news articles, research journals, and business publications that provide insight on the social, environmental, and economic effects of AVs.

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Surveys on Daily Commuting

We followed up with two surveys, asking commuters about their various attitudes and experiences with commuting and AVs. With 70+ respondents, we learned that:

  1. Many people like public transit because it's a time of solitude where they can enjoy a book or podcast uninterrupted by the stresses of driving.

  2. They dislike it because of its unpredictability, vulnerability to delays, and pains of connecting from one's home.

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“I’m happiest when I don’t have to think about my commute and it just goes well.” –Respondent


Expert Interviews

We conducted 4 interviews with professionals at the forefront of autonomous vehicle research. While many couldn’t discuss their research explicitly, they helped us to begin asking the questions that are driving much of the AV research happening today.

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Competitive Analysis & Secondary Research


We researched 5 ride sharing & transit services to determine our service model. We also did research on pilot AV services, like the Mcity Driverless Shuttle and May Mobility AV Shuttles in Detroit.

We focused on identifying: Service value; Sign-up process; Payment models; Service structure 

Much like Chariot, we wanted to have different types of payment options (All Access vs Credits) to make our service flexible, yet efficient. We also found interest in how Via licenses their technology to local transportation authorities. In combination with our scenarios and exploratory research, competitive analysis helped us lay a foundation for how we wanted to serve our user.

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Design Imperatives

This wealth of information from stakeholders and experts, along with secondary research, helped us to formulate the design imperatives that guided us through the development of our service.

Our service must prioritize safety.

Our service should consider reliability and comfort.

Our service could address the bigger picture.

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We developed four unique personas and scenarios that helped us think about what an autonomous ride-sharing service might look like for people of different income levels, different living situations and commuting needs. Another thing we were able to do here was begin to experiment with voice, visual and tactile features – and how they would fit into a system that spanned home, vehicle and work. Going into testing, we decided to try a branching storyboard model to gut check different components.

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Speed Dating


We tested with prospective users: commuters who own a car, but do not use it to commute to work. This helped us to discover which touchpoints would be most useful to our target audience. We learned that is that users wanted to be able to go on autopilot (a best case scenario when riding public transit currently) and be able to enjoy solitude (the greatest affordance of commuting by car), and just about everything else was superfluous. Anything we created would have to facilitate those things in order to resonate with our target users. Relating back to our imperatives, this translated to a slight reprioritization:

  1. Comfort: On short commutes, people value “me time” over added features. 

  2. Reliability: To users, reliability means being able to get to work everyday at a certain time, but having flexibility on the way home.

  3. Safety: In the context of a service, people are less concerned about safety than they are about ease.

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Next we developed wireframes for the key user touch points, including sign up, saved routes, and shuttle routes. The wireframes served as a tool to help us organize content, consider hierarchy, and begin testing the presentation of dense content about shuttle routes and the unique service value (AM vs PM rides).

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Avivi Service Flow

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Avivi Touchpoint Design


All Access Pass

The primary point of communication with the service is the app. Here, users can select their plans, plan and track routes, and receive notifications for most convenient connections. When a commuter signs up with Avivi, they will pick a payment option, which allows them either a guaranteed seat everyday of their commute, or credits to catch a ride when it’s convenient for them.


Set A Morning Route

All Access users have the ability to set up a fixed routes in the morning that will connect them with public transit. Users put in their home and work address, the days of their commute, and the time they want to arrive at work. The Avivi app intelligently recommends routes that will work for them.

Smart Fob

To allow for personalization, safety, and seamless transfers, the Avivi key acts as a check-in device on the shuttle and partnering public transit connections. Once the individual has boarded the shuttle, they can tap the Avivi fob on the seat to personalize seat settings, such as vibrating when it’s time to get off .

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Avivi Mobile Application

Avivi Mobile Application

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Avivi Connected Fob





This is a vast research landscape at the moment, and it was a lot to take on for a six-week project. We were lucky to conduct it at Carnegie Mellon and in Pittsburgh, because it afforded access to conversations with people who could help frame the potential of AVs in a way that sifting through research papers alone could not. Our solution at its core is quite simple, but it only works with autonomous technology, and their insight was essential for framing it properly.


Based on research and testing, we believe that the service model, with a core customer base using the service in a scheduled manner supplemented by users who fill empty seats at the last minute, is a very economically sound use of AVs and can be of help to a wide range of users. This essentially is the model that many existing train services use, with both reserved and unreserved seats, and we see the potential for applying a similar model to help sustain a commuting transit service that gets regular scheduled usage.


We would have further developed our service-scape in three key areas. First, we would have developed an in-car screen component to communicate safety measures to the riders. We didn’t develop this piece for the presentation because we received mixed feedback around this component during user testing. We also felt like there was more research to be done around when to provide visual feedback to the riders. Second, given more time, we would have done more testing and prototyping on the SOS feature of the Avivi key. We explored this feature as a tool for interpersonal safety but ultimately didn’t feel like it was an essential element of our user’s system.  Third, we would like to test more users in order to consider features and comfort levels for different lengths of commute.