Cube Dynasim Case Study: Italian Railways

Company: RFI (National infrastructure manager, Ferrovie dello Stato Italiane Group)
Location: Rome, Italy

Challenge: To improve the quality of their services along single-track rail lines, RFI needed a methodology for identifying the best scenario for doubling specific sections of the route, accounting for stress on the rail system infrastructure, customer experience and bottom-line project cost.

Solution: With Citilabs’ Cube Dynasim, RFI created and ran a series of micro-simulations to test different route and schedule adjustments and identified changes that would provide optimal infrastructure upgrades.



RFI administers most of Italy’s railway network. As one of the leading infrastructure managers in Europe, RFI is constantly looking for ways to improve the country’s rail services.

In order to identify optimal scenarios for potential infrastructure upgrades, RFI developed a methodology to analyze and compare multiple route and schedule adjustments. To test this new methodology, RFI selected the Roma Ciampino — Velletri rail line as a case study, to explore possible improvements to frequency of service and help accommodate more commuters.


To get the most from their investments, RFI sought to understand which of several proposed route and schedule changes would (1) alleviate the most stress on the rail system infrastructure, (2) guarantee a significant increase in customer service levels, and (3) avoid the time and expense required to completely duplicate the single-track rail line.

“RFI’s most important goal was to quickly assess the impact of different infrastructural and operational alternatives on the case study,” said Giulia Costagli, director of the research department at RFI (CeSPI). “The current infrastructure won’t allow a consistent increase in trains, hence limiting both transport capacity development and the quality, in terms of punctuality, offered to the clients.”



RFI needed a way to explore the impact of multiple scenarios and quickly compare possible directions for the project, all of which were significantly different in terms of cost. Based on a positive experience from former projects, RFI reached out to Citilabs to help create and run the assessment using the Cube Dynasim Railways.

“For RFI it was fundamental to have an idea, before deeper analysis, about the ‘optimal’ solution, limiting the costs for new/improved infrastructures and guaranteeing a significant increase in terms of level of service,” Costagli explained.

“Before starting the modelling exercise, the project was in a phase of general evaluation of the different scenarios. Although it was quite clear that some of the planned alternatives were not optimal, or were over-engineered compared to the needs, it was extremely difficult to give firm answers and justify them. Using Cube helped us understand specific differences among the scenarios and fine tune our project.”

To help RFI determine the best course of action, Cube Dynasim ran a series of simulations and extracted data for every scenario, including:

  • Departure delays due to red signals or train priority
  • Number of stops
  • Total time spent at red signals

The information gleaned from the exercise let RFI analyze the effect of each potential change, such as train frequency, infrastructure adjustments and route delays due to conflicting trains.

Regarding each service, additional information is saved regarding the speed, the acceleration and the position of the train. This information can be plotted in a chart to better understand the conflicts and the delays between services.


“The simulation provided several useful insights thanks to the provided metrics, such as maximum, average and minimum delays on the different scenarios, or the time lost at the stations,” reported Costagli.

In many cases, project assessments like these were made based solely on experience and the use of Excel spreadsheets and databases. Cube Dynasim gave RFI the ability to compare and contrast multiple scenarios using 2D and 3D visualizations, an intuitive graphical interface and hard data.

RFI was able to identify minimum, maximum and average delays for all trains in the simulated period for each scenario, tested for both 15- and 20-minute departure intervals. Test results revealed line duplication along two specific parts of the route would provide results comparable with more extensive projects but at a much lower cost.

In Their Words

“Citilabs experts demonstrated to be a very efficient team, responding to the needs with no delay. It’s noticeable to mention that to complete some tasks of the project, the software itself needed to be modified to include some specific functionalities to better analyze the line. Citilabs responded extremely quickly and the software was modified to fully respond to our needs.”

     - Giulia Costagli, director of the research department at Italian Railways RFI (CeSPI)


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