Figure 7

A schematic explanation of the core mechanism of the Delay Propagation Model. In this picture, a train i departs from the station A and acquires a departure delay from a distribution depending on the out-degree of A in the railway network. When the train i passes through station B, its delay \(\delta t_{i}\) gets two contributes: (i) a stochastic exogenous delay \(\delta t_{\mathrm{exo}}\) depending on the length of the link d the train i is going to travel; (ii) a propagated delay \(\delta t_{j}\) depending on the presence of a delayed train j travelling on a nearby link. If there is such a train j with a positive delay \(\delta t_{j} > 0\), this delay is propagated to train i with probability β, which is the only free parameter of the model