Where shall we sync? Clustering passenger flows to identify urban public transport hubs and their key synchronization priorities

Minimizing passenger transfer times through public transport (PT) transfer synchronization is important during tactical planning and real-time control. However, there are computational challenges for solving this Timetable Synchronization Problem (TSP) for large, real-world urban PT networks. Hence, in this study we propose a data-driven,...

Supervised learning: Predicting passenger load in public transport

In this extended abstract, we show the supervised learning approach to<br/>predicting passenger load of trams, based on historical passenger load patterns. We look at two different cases: predicting long-term passenger load of any given day and time, and predicting short-term passenger load at a particular public transport vehicle.