Electrifying Bike Sharing Systems: Structural Demand Estimation and Large-scale Optimization

Bikeshare systems around the world are increasingly incorporating electric bikes to expand their coverage and increase ridership. This project aims to apply descriptive and prescriptive analytics to support key operational and strategic decisions in bikeshare electrification. First, we will perform empirical analysis to quantify the spatially heterogeneous impact of electric bike availability on bikeshare ridership. Then, we will develop an optimization model that jointly determines charging infrastructure locations and battery swapping policies—two of the most common charging strategies in e-bike sharing systems—to maximize overall ridership. Together, these efforts will offer a comprehensive, data-driven approach to electrifying bikeshare systems and promote the broader adoption of this sustainable mode of transportation.

Faculty Supervisor:

Sheng Liu

Student:

Partner:

Massachusetts Institute of Technology

Discipline:

Engineering

Sector:

Education

University:

University of Toronto

Program: