Network-wide transfer synchronization strategies in a public bus system with real-time data

Transfer speed and reliability are key factors influencing public transportation use. Fixed schedules often fail under unpredictable traffic, causing missed transfers. To address this challenge, we propose an online stochastic optimization (OSO) framework for the real-time transfer synchronization problem using three control tactics: hold, skip-stop, and speedup. Our approach is based on an offline flow model that minimizes total passenger travel time by solving time-expanded graphs incorporating all possible control tactics. Building on this model, we develop an OSO framework integrating historical and real-time data to generate scenarios on future bus network conditions and make dynamic decisions. These algorithms were implemented in a network-scale simulator of the public transit system of Laval, Canada. The results demonstrate improvements in mean transfer time and in passenger travel times, showcasing the practical potential of using online stochastic optimization for transfer synchronization in multi-line public transit networks.