A model predictive control approach for discrete-time rescheduling in complex central railway station areas

Railway networks are operated more and more at capacity margins, schedules are becoming more susceptible to disturbances, and delays propagate and hamper the service level experienced by the customers. As a consequence railway traffic management is becoming increasingly challenging, thus motivating the development of computer-aided systems. This paper proposes a dispatching assistant in the form of a model predictive control framework for a complex central railway station area. The closed-loop discrete-time system suggests rescheduling trains according to solutions of a binary linear optimization model. The model assigns precomputed blocking-stairways to trains while respecting resource-based clique constraints, connection constraints, platform related constraints and consistency constraints with the objective of maximizing customer satisfaction. In collaboration with the Swiss Federal Railways (SBB), the approach was successfully applied for an operational day at the central railway station area Berne, Switzerland. The model is capable of considering many alternative routing possibilities and departure timings, a potential of our approach, which can also be deduced from computational results.