Vello: Same System, Less CongestionDesign Strategy, Product Design, UX/UI Design
Vello is a transit mobile app plugin for Toronto, Canada that reduces congestion on local transit, by leveraging existing infrastructure. Vello shows which system, lines, cars are least packed, so you don’t have to miss your train.
*** UPDATE IN PROGRESS***
To hear more about this project check out my Behance project page
Rides are more comfortable and you get up-to-the-second news on the transit system by other Vello users.
We conducted 20 interviews to try to truly understand the problem, empathize with the transit users and gain insight into the situation. One user commented, “The TTC [Toronto Transit Commission] could be more proactive. We are your customers at the end of the day. The TTC is supposed to be providing a service for us.”
The lack of transparency provided through existing transit applications leads to concerns with personal comfort and safety.
WHAT IS WRONG WITH THE TORONTO TRANSIT SYSTEM?
Toronto public transit is well over capacity. This is a long-standing and long-accepted fact among Torontonians. Transportation has become such a key issue in the city that it is a driving force in city of Toronto municipal elections (CBC). Transit was tied for the top issue for citizens in 2014, according to The Globe and Mail.
– High levels of congestion
– Slow speed to resolve delays
– A lack of transparency
– No opportunity for user feedback in the current public transportation system
=> Daily commuters are finding it nearly impossible to get from point A to point B on time.
Conducted interviews with 20 users – age range 20-35 to try to understand the problems, empathize with our users and gain insights.
To reduce congestion, a private relief line that users could pay a small fee for would be something that citizens would want and would be a service that would help solve the problem of congestion in transit.
People understood and were sympathetic to the fact that the City of Toronto doesn’t have the money to create full new relief lines. Users actually did not desire a solution to this problem – they just wanted more transparency and information from their transit system. Transparency was desired if transit congestion was going to make a user late, and more knowledge and information about why there were major delays throughout the city. This was repeated over and over again by users of different ages, backgrounds and occupations. Another issue that kept coming up was that of increasing safety on public transit.
We also realized the shortcomings within existing transit apps – they do not serve all types of users. For example, the type of user most teammates interviewed was “the frequent transit user”. This users does not rely on search and explore functionality and is currently under-served. They do not use an app, as they know what each leg of their journey ought to be already. As such, they miss notices and notifications that come up on a phone if one was using Google Maps to navigate. This user would benefit from core features that make their journey more efficient, reliable and comfortable.
Based on the user interviews conducted by our team we narrowed-in our project scope. We also created 2 personas based on common repeating themes and lifestyle similarities from the people who were interviewed. These were later used and referred back to throughout the wireframe iteration process. They influenced UI decisions and allowed us to keep focus on what audience we were designing into.