On the fragility of a train timetable

In dense railway traffic, even the small delay of a single train may propagate through the network, causing a sequence of knock-on delays and significant deviations from the timetable. To mitigate the propagation of delays, railway infrastructure managers can generally employ two strategies: (i) in real time, train dispatchers can limit delay propagation by rescheduling trains, i.e., by adjusting the timetable in response to disturbances; (ii) in the timetable design phase, train planners can try to build delay-resilient timetables, which requires a complicated and lengthy iterative process. The ability of a timetable to “absorb” delays whenever they occur is known as robustness. While there is no unanimous consensus on a measure to quantify such robustness, it is normally a global measure, and therefore it is unable to highlight whether specific train paths or regions of the railway network are less robust than others. Moreover, only a few academic works incorporate the possibility of mitigating delays in real time through dispatching when evaluating robustness measures. These shortcomings motivate the present work. In this paper, we introduce the concept of fragility as a new practical tool to analyze a given timetable in order to identify the specific sections where a primary delay is most likely to generate knock-on delays, factoring in optimal future dispatching decisions. We also discuss the relationship between the fragility concept and the so-called recovery cost. We present computational results on real-life scenarios from a busy railway line in Norway and discuss several potential uses of fragility to improve decisions at different levels of the railway planning process, including dispatching, timetable design, and network design.

Authors

Publication Details

Journal
Omega
Published
2025-04-29
DOI
https://doi.org/10.1016/j.omega.2025.103341
Citations
6
Primary Topic
Railway Systems and Energy Efficiency
Type
article
Field-Weighted Citation Impact
7.45
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On the fragility of a train timetable

Dario Pacciarelli, Giorgio Sartor, Carlo Mannino, Marta Leonina Tessitore et al.
6 citations
Omega
Railway Systems and Energy Efficiency
7.45
article

On the fragility of a train timetable

Dario Pacciarelli, Giorgio Sartor, Carlo Mannino, Marta Leonina Tessitore, Marcella Samà
article en
6 citations

Abstract

In dense railway traffic, even the small delay of a single train may propagate through the network, causing a sequence of knock-on delays and significant deviations from the timetable. To mitigate the propagation of delays, railway infrastructure managers can generally employ two strategies: (i) in real time, train dispatchers can limit delay propagation by rescheduling trains, i.e., by adjusting the timetable in response to disturbances; (ii) in the timetable design phase, train planners can try to build delay-resilient timetables, which requires a complicated and lengthy iterative process. The ability of a timetable to “absorb” delays whenever they occur is known as robustness. While there is no unanimous consensus on a measure to quantify such robustness, it is normally a global measure, and therefore it is unable to highlight whether specific train paths or regions of the railway network are less robust than others. Moreover, only a few academic works incorporate the possibility of mitigating delays in real time through dispatching when evaluating robustness measures. These shortcomings motivate the present work. In this paper, we introduce the concept of fragility as a new practical tool to analyze a given timetable in order to identify the specific sections where a primary delay is most likely to generate knock-on delays, factoring in optimal future dispatching decisions. We also discuss the relationship between the fragility concept and the so-called recovery cost. We present computational results on real-life scenarios from a busy railway line in Norway and discuss several potential uses of fragility to improve decisions at different levels of the railway planning process, including dispatching, timetable design, and network design.

OmegaVol. 137
Openalex Percentile: Top 3%
Railway Systems and Energy Efficiency
7.45
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.