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Zeit:  Freitag, 21. Oktober 2022, 14:30 Uhr
Ort:   Raum 9U10 (2359|0.10), E3, Informatikzentrum, Ahornstr. 55

Referent: Rebecca Haehn M.Sc. (Theory of Hybrid Systems)

Thema: Optimisation and Analysis of Railway Timetables
under Consideration of Uncertainties

Abstract:

Railway systems are complex systems that are strongly affected by
uncertainties like weather, technical problems, or demand. Despite
these uncertainties, railway systems need to function efficiently. In
general this thesis aims to advance the consideration of uncertainty in
the railway planning process to optimally utilise the existing railway
network capacity. The focus in this thesis is on the delays that result
from the uncertain environmental conditions. To consider these in the
railway planning process, a symbolic simulation algorithm is proposed
to examine the delay propagation in a railway network for a given
timetable. This allows to estimate the timetable robustness and the
network capacity. Several performance indicators for railway timetables
that can be evaluated using the symbolic simulation are discussed. To
optimally utilise the network capacity also an algorithm to schedule
additional freight trains is presented.

The main contributions of this thesis are the following:
- An algorithm to schedule additional freight trains is presented,
to utilise the remaining network capacity without disturbing an
existing timetable.
- A novel symbolic simulation algorithm for railway timetables is
proposed. The algorithm receives as input a railway infrastructure
model, a corresponding timetable, and discrete primary delay dis-
tributions. It computes iteratively over time the delay propagation
in the given railway system. Symbolic expressions are used to
represent multiple possible values for the primary delays. This
enables to simulate all discrete primary delay combinations at once.
- An implementation of these algorithms is provided in C++ and
evaluated on some real-world railway infrastructure networks and
timetables based on the German railway system. The applicability
and functionality of the algorithms is demonstrated.

The proposed symbolic simulation algorithm is aimed to be a helpful
addition to existing railway timetable simulations, which are mostly
based on Monte Carlo simulation. In contrast to those, the symbolic
approach stores the history of specific train states, which can be used to
explain the occurring delays. In addition, the results of the symbolic
simulation are exact with respect to the input model and the discrete
primary delay distributions.


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