Stochastic Methods and Hubway

This project investigates data from the Hubway bike-share system deployed throughout greater Boston. Using Hubway's ridership data from the 2012 season, we perform second order analyses to develop intuition about how to augment or improve general understanding of how the system works. Using various stochastic methods, we utilize the volume and temporal distribution of trips from the stations to derive key insights into potential system expansion, ridership forecasting, realignment of corrupted data, and placement of special prototype bicycles.