Combining Operative Train Simulation with Logistics Simulation in SUMO

Geischberger, Jakob; Weik, Norman · 2022 · DOAJ

DOI: 10.52825/scp.v3i.112

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Summary

This paper addresses the disconnect between macroscopic logistics simulations, which analyze the flow of goods in aggregated supply chains, and microscopic railway simulations, which model detailed train operations, signaling, and delay propagation. The authors argue that integrating these perspectives is essential for evaluating how railway-specific operative implications, such as conflicts and delays, affect individual transport units rather than just trains or network areas. The study aims to demonstrate that the open-source microscopic simulation tool SUMO can serve as a unified platform to merge detailed train operations with agent-based logistics simulations, shifting the analytical focus from trains to individual goods. The methodology involves adapting SUMO to fulfill requirements from both disciplines, including the processing of timetables, modeling of signaling and driving dynamics, and the routing of individual goods as agents. The authors utilize integrated clock-face timetables, which coordinate passenger and freight train paths to minimize transfer times, to define "system paths" for freight. Railway infrastructure data is imported from Open Street Map and converted for SUMO, with edge priorities adjusted to ensure realistic routing. Containers are modeled as agents with static tours defined by origin, transshipment stops, and destinations. The simulation captures the interaction between trains and containers, allowing operational disruptions to propagate from the train level to the individual container level. Yard processes are simplified using fixed process times rather than explicit shunting simulations. A proof-of-concept application was conducted on the railway network of northwestern Germany, using data from the planned "Deutschlandtakt" integrated timetable. The study tracked three containers traveling from Kiel to Hamm via the Maschen shunting yard. Results demonstrated that the simulation successfully captured railway-specific operational impacts on individual containers. One container experienced an undisturbed journey, while another encountered delays due to signaling conflicts with a delayed passenger train and congestion near Hamburg, resulting in a later arrival at the yard. A third container’s train was forced to take an alternative route due to disruptions, altering its speed profile and total distance. These trajectories were visualized through speed-over-time plots and time-distance lines, confirming that operational delays and routing deviations are accurately reflected at the container level. The significance of this work lies in its ability to provide a holistic view of rail freight logistics, enabling the analysis of reliability and bottlenecks at the level of individual goods. This approach supports more precise decision-making for supply chain management by quantifying how railway infrastructure and timetable design impact specific transport chains. The authors suggest future research could extend the model to include dynamic intermodal routing, aggregate container chains for system-wide analysis, and integrate harbor and yard capacities to better understand hinterland traffic dependencies.

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• simulator training transfer