We’ve hit a breaking point with congestion and our infrastructure. Data suggests that boomers and millennials alike are gravitating toward cities at an unprecedented rate. At present, 55% of the world’s population lives in urban areas. By 2050, two-thirds of us will (Siemens, 2018). With all these people coming and staying in NYC, how can we keep our transit systems up to par, support the growing needs of this growing population, and ensure businesses can still prosper so those benefits of being at the epicenter of culture and access are not diminished?
New transportation products, services, and research have been plentiful over the last few years. We have easy access to Citi Bikes and started leveraging our waterfront with new ferries. We can pick up important packages in our Amazon lockers versus waiting for home delivery. We have wifi on our subways (finally, kind of). We have numerous ride-sharing apps. Waze was designed to help us navigation out of grid-lock two exits before. And Google Maps can predict the exact minute your L train will arrive and even give you directions in Augmented Reality. We are even anticipating driverless cars and smart cities in the near future as well. It’s an exciting time, but it would be naive of us to think that there won’t be some shaking moments in this transportation evolution.
Havas has partnered with 5 teams of talented faculty members and graduate students from NYC Media Lab’s consortium of universities to harness the power of technology, emerging media, and data. The effort will inform future NYC transportation needs for commuters, business, or city transit companies.
Teams underwent an iterative prototyping process alongside executive mentors at Havas, and built solutions within the context of several guiding questions: How will technologies like artificial intelligence, machine learning and computer vision shape the future of transportation in cities? How will data and technology transform how we experience, access and move within cities?
SVA, Interaction Design (IxD)
Team Members: Jennifer Wei; Ke Hu; Margarita Yong; and Jason Branch
The proposal is an on-demand city bus service that connects disparate neighborhoods and businesses. We aim to provide commuters with the convenience of ride-share but the affordability of public transit using real-time data.
Team Members: Mohab El-Hakim; Ahmed Hussein; Matthew Volovski; Issa Dahdal; and Leanna Bonanno
The project objective is to develop a working prototype to stream the passenger density in NYC subway cars through live data displayed on a website, phone application or on the subway platform. Travelers will be able to quickly find the least crowded subway car on the platform or use an alternative subway line with lower density. The prototype includes setup and programming of a security camera using AI to detect the presence of passengers through image processing.
The New School, Design & Technology
Team Member: Jacqueline Wu
Sub-Signals reimagines the form and function of New York’s subway globes as visual navigational tools at street level entry. The proposal embeds transit data into the urban environment to improve commuters’ wayfinding experience and reconsiders how cities might leverage existing public infrastructure for new use.