A transportation system that uses waves of data to balance the flow of traffic

Duration: 8 weeks

Partners: Ruby He & Gerald Warhaftig

My Role: UX Research, UX Design, 3D CAD



As cities and roads become more crowded, the existing public transportation system will no longer be efficient enough to meet the increased demand. How can we use technology to alleviate traffic on the road and create a more sustainable way for everyone to get around in the future?

Research & Problem Scoping

Our prompt for this project was simply "telematics in transportation". To begin to define our scope, we read articles on the different transportation systems currently in smart cities, the science behind traffic, the social and economic influences in transportation, and the existing problems with modern day transport. We found that while the U.S has %5 of the world population, it has over 20% of the world’s automobiles. About 28% of America's total energy is used on transporting people and goods, which is a huge environmental cost that we should aim to reduce. After our secondary research, we created a concept map and stakeholder map together to think through the different aspects of our space, as well as all the influencers and recipients of transport.


We then started to gather insights and find trends by interviewing people on their good and bad experiences in daily travel, incentives, and behaviors. From 12 interviews and 46 survey responses, some key findings were that people:


I take the bus and I don't know other [not the usual] routes well enough to know what stops to get off at.

Sometimes I want to go the fast way and sometimes I want to go the scenic route, it depends.

I bus, so there aren't many choices to get to my common destinations.


Our research led us to the frustration specifically around busing, but since we did our research in Pittsburgh, we must acknowledge that

  1. Pittsburgh is a very bus-able city
  2. more than half of our interviewees were students who had free bus passes
  3. the steel city's historically blue collar demographic attributes to less car ownership
  4. we had exposure to Uber's self driving cars which reinforced the likelihood of an autonomous future


Riders need a more empowering busing experience so that they can travel freely without worrying about reliability, efficiency, or cost.

Co-designing the Future

To improve the busing experience, we wanted to dig deeper to understand the space where there's currently a lot of waiting and lack of reliability: the bus stop itself. We put up interactive posters around the city (outside the college bubble) and asked riders to draw their ideal bus stop.

From the posters and drawings, we gathered that people wanted to be more comfortable, productive, and entertained. We also looked back at our stakeholder map and concept map to make sure we were considering the problem as part of the larger ecosystem. We realized that while there’s a huge opportunity to improve the experience for people while they wait for the bus, that unpredictible wait itself is affected by constant change on the road. The traffic on the road affects and is caused by everyone, regardless of their mode of transportation. In order to make the bus rider's experience more predictable, we have to manage the entire flow of traffic. For example, even if a rider gets to the bus stop just as the bus pulls up, they might feel relieved they'll get to their destination on time, but still get stuck in traffic later during their travel. We can use data to predict who will be on the road, so a more seamless riding experience starts before the bus stop itself.

Solution Brainstorming
With our accumulated research, we knew that we had to design a solution with 3 goals in mind:
  1. Transportation in the future must allow people to feel productive, giving them control over how they get from A to B.
  2. With the increase in population and transportation demand, we must use data to alleviate traffic so that people can spend more time doing meaningful activities and building relationships in their lives.
  3. The design must be inclusive of all people on the road, taking into account what each type of rider values during daily travel.
We talked about how currently, people first pick a mode of transportation, and then plan around it. Transportation is vehicle-centric, not people-centric. A person who is busing first decides that a bus is the fastest/most comfortable way to get to their destination, then plans for how early they should get to the bus stop to wait for the bus, and then deals with the unpredictability of the travel time on the bus. We wanted to challenge this model of transportation.
Before traveling, people can just go to a "mobility" station, where all modes of transportation are accessible. Why choose the mode of transportation first? Why choose just one mode of transportation at all?
We asked users to tell us what info they need and considerations that come with each mode of transportation.
By comparing the pros and cons of each transportation mode, we began to think of ways to address the weaknesses of each. By offering the option to combine various forms of transportation in one journey, we can utilize the strengths of what each mode provides. To solidify this idea, we sorted the types of info that would be needed per ride method.
Proposed Solution


Ripple is a transportation system that uses data to optimize efficiency, cost, and reliability while giving riders control over the goal of each trip. It consists of multi-modal mobility stops called Ripple Points, a network of sensors called Ripple Waves, and a mobile touchpoint called Ripple Drop. Together, they allow riders to consciously use transportation as a means to be more physically active, get to their location faster, travel with others, or reduce their carbon footprint.

Ripple Experience Map
Ripple Use Cases


Ripple is

productive: Riders can choose how to travel, and spend travel time as a means of doing something productive, whether it be staying on the move, meeting people, or actively going green.

reliable: Ripple Waves uses data about city events, personal schedules, and vehicle ETAs to always provide users with the fastest options. By offering all modes of transportation at Points, people don't have to wait any more than they want to.

efficient: It uses data seamlessly by analyzing current and future road conditions to suggest the best way for riders to get to their destination.

cost-optimized: Ripple allows for switching between ride methods in each trip, balancing the cost between modes.

inclusive and empowering: By directing people on routes they don’t usually go on, we enable them to confidently travel and experience new spots along the way, get to know people in their community, and also arrive faster via less crowded streets.

Ripple Final Deliverable