D8.2 Developed methods and models for evaluating feedback loops between planning and operations

The present document constitutes the Deliverable D8.2 “Developed methods and models for evaluating feedback loops between planning and operations” in the framework of the Flagship Project FP1-MOTIONAL as described in the EU-RAIL MAWP. The overall objective of this task is to develop and improve railway traffic simulation methods and models to improve feedback loops between planning and operations. With better modelling of the traffic, we can achieve more reliable and effective evaluation of capacity and punctuality, which can be used to increase the quality of the plan.

In this deliverable, development is presented related to four demonstrations, i.e., demonstrations 9.1–9.4. Also, demonstration 9.8 is presented briefly, even though the main developments there are presented in Deliverable D8.3 (FP1–MOTIONAL,2025). Results of the Deliverable D8.2 are:

• Presentation of PROTON, a simulation tool usable for large networks. PROTON will be demonstrated for a large Swedish case and calibrated and validated with real-world disturbance data.
• Method for calibration and validation of simulation models. These results will be used to calibrate and validate PROTON.
• Improved method for processing historical data to create delay distributions, including small disturbances and calibration of background noise.
• Introduction of a simulation tool for improved feedback between crew plan and operation. With this tool, it is possible to simulate the combination of a timetable, rolling stock and crew to evaluate the robustness of a crew plan.
• A simulation tool that can be used to evaluate different infrastructure layouts and timetables. The goal is to improve a timetable based on feedback loop between C-DAS data and simulation tool/TMS.

Main conclusions are that there is a need for further developments within railway traffic simulation modelling. The more we know about setup of simulations, the faster we can do efficient analyses. With the development presented in this deliverable, we are able to perform better traffic and capacity analyses and give more relevant feedback to planning. Improved input data and stochastic disturbances that are presented in the deliverable will make the results more reliable.