English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Buffer times are essential for preventing delay propagation and ensuring robustness in railway timetabling. While robustness analysis deals with ensuring the effectiveness of allocated buffer times in schedules, the number of trains is generally assumed to be fixed. The feasibility of the train operation concept needs to be checked by strategic long-term capacity planning beforehand. Capacity analysis methods depend on buffer times and involve some sort of delay prognosis. The goal of the present paper is to analyse the effects of buffer time distributions on nominal capacity obtained with stochastic (analytic) capacity analysis approaches. Complementing previous work where Monte-Carlo simulation had been applied, it is shown how convolution integrals arising in analytic delay propagation models can be explicitly calculated using moment generating functions. Based on this approach, a generalisation of the STRELE framework, which is the standard methodology of German infrastructure manager DB Netz AG for capacity analysis of railway lines, is derived and the effects of different buffer time distributions on nominal capacity are studied.

THE IMPACT OF BUFFER TIME DISTRIBUTIONS ON THE NOMINAL CAPACITY OF RAILWAY LINES