Accurate train arrival delay prediction is critical for real-time train dispatching and for the
improvement of the transportation service. This study proposes a data-driven method that …

Railway capacity is seemingly easy but truly complex concept due to its interaction with all
the pillars of railways such as infrastructure, rolling stock, signaling and operation planning …

We propose machine learning models that capture the relation between passenger train
arrival delays and various characteristics of a railway system. Such models can be used at …

This paper proposes a novel approach for energy-efficient timetabling by adjusting the
running time allocation of given timetables using train trajectory optimization. The approach …

This paper presents a carefully designed train delay prediction model, called FCLL-Net,
which combines a fully-connected neural network (FCNN) and two long short-term memory …

The train trajectory optimization problem aims at finding the optimal speed profiles and
control regimes for a safe, punctual, comfortable, and energy-efficient train operation. This …

Train drivers in Sweden had the opportunity to test the new European Rail Transport
Management System (ERTMS) during the early implementation of this signaling system in …

This paper reschedules train services on a double-track high speed railway in a disrupted
situation, where one track of a segment is temporarily unavailable. We have to decide the …

The performance of railway operations depends highly on the quality of the railway
timetable. In particular for dense railway networks it can be challenging to obtain a stable …

Chinese high-speed railways faced a fast development in recent years. Their performances
are still confronted with disruptions unavoidably, which impact on the reliability of the traffic …