Urban Mobility AI Workshop

Workshop Abstract

The challenges urban mobility management faces include the increasing amount of data, the complexity of the problem, and the involvement of many stakeholders. How to utilize the data and artificial intelligence (AI) tools for effective and safe management of urban mobility remains an open challenge. The goal of this workshop is to promote mutual conversations among people from academia, industry, and agencies, and identify a pathway for collaborative efforts to cope with such challenges. It will be a 1-day event with speakers and audience who will sit together to discuss the potential cross-disciplinary collaboration leveraging data, optimization, and machine learning, as well as an initiative to establish an academia-industry-agency partnership.

In the morning session, we aim to explore the impact that combining Machine Learning (ML) and Mathematical Optimization (MO) can have when it comes in making good (hopefully optimal) decisions in a variety of real-world problems, such as those arising in transportation, including electrification of transportation systems, ridesharing, and congestion pricing. In particular, we are interested in methods that guarantee scalability, interpretability, explainability, and fairness.In the afternoon panel session, representatives from industry and agencies will present their perspectives in urban mobility management, challenges and opportunities. An interactive discussion will follow to identify a roadmap for a potential academia-industry-agency partnership.