Operations management
Giving timetables T
Lift, Italy, is pioneering a new approach to timetable planning which is reducing the impact of delays on operations, as Marco Chiandoni explains.
RIESTE has a long railway tradition. The former port of the Austrian Empire is the terminus of the iconic Semmering railway, which connects the city with Vienna and was the first railway to be selected as a Unesco world heritage site. The city is also home to Trieste University which is continuing this railway legacy as the modern-day home of one of Italian State Railways’ three former engineering schools which was established in the region when it became part of Italy at the end of World War I. Research at the institution in recent years has focused on railway operations, and has resulted in the establishment of a spin-off company, the Railway and Traffic Laboratory (Lift). Founded by Professor Giovanni Longo, the company is applying the results of this research initially in multiple case studies and now increasingly in software tools that are being adopted by various operations planners all over the world. In 2011 the research group received
the Young Researcher Award from the International Association of Railway Operations Research (Iaror) for presenting an innovative method that incorporates variables such as driving
Lift’s timetable method Dis
styles and stop times into timetable planning. The algorithm, which is simple and applicable even on a large scale, estimates the probability of traffic conflicts, and as a result delays within a few seconds during the timetable planning process, providing planners with an estimation of the robustness of a particular timetable.
Lift has also developed an approach based mainly on real traffic analyses and micro-simulation which considers the trade-off between the number of operated services and corresponding service reliability. This system estimates the impact on system performance and compares the reliability of different timetable alternatives. Micro-simulation is a widely-used method to support railway planning. At Lift, thanks to the data management tool Treno, which integrates analyses of real operational data and automates several manual steps, the time required to perform a study shrinks, while the level of detail improves. The approach has already been used to understand the impact of proposed infrastructure improvements or the layout of new lines on timetable planning.
The goal of all infrastructure managers and railways when planning
infrastructure projects is to maximise the benefits of investments by selecting a flexible layout. As a result new lines and stations are often very compatible with different operational concepts. However, Swiss Federal Railways (SBB) has often planned new lines specifically for a given timetable, which is a radically different approach. Longo says to account for these varying philosophies, Lift’s idea is to integrate the simulation results of different scenarios such as timetable and infrastructure with multi-criteria approaches that identify the optimal solution.
“If the railway requires a high-speed line, we start by asking the desired running time and the number of services and then develop several scenarios,” he says.
This method was used to define an
incremental improvement plan for Algerian Railways’ core network. Starting from the anticipated demand and the expected long-term volume of services, the system developed and tested a network configuration to identify the best fit to meet these requirements at minimal cost and under different timetable options in order to assess its flexibility. The interventions were then divided into a number of
Distance stance
D a ecnist
Distance
Time T Tiime Time Time Ti
Even correctly-planned timetables (left) might lead to unstable operations. The methods developed by Lift consider the real behaviour of trains when planning a timetable. The probability of conflicts (right) is shown on timetable graphs as overlapping occupation areas.
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