Analysis and Prediction of Disruptions in Metro Networks

Public transport disruptions can result in major impacts for passengers and operator. Our study objective is to predict disruption exposure at different stations, incorporating their location-specific characteristics. Based on a 13-month incident database for the Washington metro network, we successfully develop a supervised learning model to...

Rolling horizon predictions of bus trajectories

Bus travel times are subject to inherent and recurrent uncertainties. A real-time prediction scheme regarding how the transit system evolves will potentially facilitate more adaptive operations as well as more adaptive passengers’ decisions. This scheme should be tractable, sufficiently fast and reliable to be used in real time applications. For...