A data-driven approach for quantifying the resilience of railway networks

Disruptions occur frequently in railway networks, requiring timetable adjustments, while causing serious delays and cancellations. However, little is known about the performance dynamics during disruptions nor the extent to which the resilience curve applies in practice. This paper presents a data-driven quantification approach for an ex-post...

Dynamic railway timetable rescheduling for multiple connected disruptions

Unexpected disruptions occur in the railways on a daily basis, which are typically handled manually by experienced traffic controllers with the support of predefined contingency plans. When several disruptions occur simultaneously, it is rather hard for traffic controllers to make rescheduling decisions, because (1) the predefined contingency...

Integrated timetable rescheduling and passenger reassignment during railway disruptions

During railway disruptions, most passengers may not be able to find preferred alternative train services due to the current way of handling disruptions that does not take passenger responses into account. To offer better alternatives to passengers, this paper proposes a novel passenger-oriented timetable rescheduling model, which integrates...