A closed form railway line delay propagation model. (May 2019)

• Record Type: Journal Article
• Authors: Harrod, Steven; Cerreto, Fabrizio; Nielsen, Otto Anker
• Is Part Of: Transportation research. Volume 102(2019)
• Page Start: 189
• Page End: 209
• Publication Date: 2019-05
• Subjects: Rail transportation -- Train delays -- Timetable robustness -- Timetable design -- Delay propagation; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2019.02.022
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: This paper formulates an analytical estimate of aggregate railway delay. Analysis of the function demonstrates that timetable supplement and buffer are most effective within certain ratios. Numerical analysis shows that the model provides insight even when the theoretical assumptions are violated. This model can be adapted to heterogeneous traffic patterns and network boundaries. The model may be scaled and calibrated to match simulation model output. Abstract: Railway service quality can be measured by the aggregate delay over a time horizon due to an event that delays a given train. Timetables for railway services may dampen delay propagations to subsequent trains by adding either supplement time or buffer time to the timetable. The evaluation of these variables is often performed by time consuming analysis with simulation software, or other complex, time-consuming calculations. This paper proposes instead an analytical closed form formulation of aggregate delay, which offers theoretical insights into railway delays and managerial insight into the properties of timetables at an aggregate level, and which may function as a fast sub-algorithm for timetable evaluations in larger optimization and transport models. Analysis of the function recommends a restraint in the utilization of timetable supplement and buffer, as their delay-damping effect decreases with their magnitude. Further, the effect of different threshold values in delay measurement is demonstrated, giving information valuable to the design of service contracts. Numerical analysis of a common suburban railway line shows that the polynomial function provides guidance and insight even when theoretical assumptions are violated.