Featured Projects

Our research focuses on network optimization and demand modeling for shared mobility systems (e.g., carsharing, parking-sharing and ridesharing) and multimodal mobility service (e.g., Mobility-as-a-Service). We also investigated the impact of risk perception and risk attitude in travel behavior using experimental economics approaches and the application of machine learning methods in transport modeling.

Our techniques combine ideas from various research areas, including linear programming, nonlinear optimization, bi-level optimization, game theory, mechanism design, statistics, discrete choice modeling, experimental economics, machine learning and reinforcement learning.

Investigating vehicle utilization patterns of carsharing users

Facing the growing demand for carsharing services, it is critical for operators to accurately predict users’ preferences on different vehicle types and their vehicle usage. This vehicle choice behavior involves choosing multiple vehicle types simultaneously and allocating continuous amounts of budget…

Keep reading

%d bloggers like this: