Enhancing Timetable Planning With Stochastic
Dwell Time Modelling
Author(s)
G. Longo & G. Medeossi
Abstract
Estimating stop time is a critical task for timetable planning, especially since
actual dwell time shows a significant variability that could hinder service
reliability. Therefore its importance has increased as railways seek to maximize
infrastructure utilization while improving the quality standards, including
reliability.
A significant amount of scientific work focussing on the estimation of dwell
time within different transit systems can be found in literature. However, it is
mostly focused on aspects such as, for example, the time required for each
passenger to board depending on the number of steps, while in very few reports
the applicability of the models and their practical relevance are described.
This study presents an approach for estimating the stop time distribution of
train services and using them in simulation or timetable planning tools. Based on
conventional parameters on the one hand and on track occupancy data collected
by train describers on the other, the models include an algorithm to derive the
stop time from the track occupancy data and a multi-parametric dwell time
estimation.
When past track occupancy data is available, the parameters are estimated:
the calibrated model can be used as input to plan or simulate future scenarios
considering, for example, new rolling stock or different service patterns.
The results of model calibration and its use in a test network around Venice
are described in the last part of the paper.
Keywords: stochastic simulation, railway planning, dwell time, train
performance.
Keywords
stochastic simulation, railway planning, dwell time, train
performance
Related Book
Other papers in this volume
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