SUMO Simulation of DLR's Research Intersection

Authors

DOI:

https://doi.org/10.52825/scp.v6i.2633

Keywords:

Trajectory Data, Calibration and Validation, SUMO

Abstract

Trajectory data are great data to work with, since they are the most natural data for traffic. However, they provide considerable challenges when tried to put into a micro-simulation framework such as SUMO. This work here gives an example what had to be done to arrive at a simulation that is driven by these data. Succeeding in this, microscopic tools can be much better tested against real data.

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References

J. Treiterer, and J. Myers, "The hysteresis phenomenon in traffic flow", Transportation and traffic theory, vol. 6, pp. 13–38, 1974.

B. Coifman, L. Li, and W. Xiao, "Resurrecting the Lost Vehicle Trajectories of Treiterer and Myers with New Insights into a Controversial Hysteresis", Transportation Research Record, vol. 2672, no. 20, pp. 25-38, 2018. DOI: 10.1177/0361198118786473.

V. Alexiadis, J. Colyar, J. Halkias, R. Hranac, and G. McHale, "The Next Generation Simulation Program", ITE Journal, vol. 74, no. 8, pp. 22 - 26, 2004.

E. Barmpounakis, and N. Geroliminis, "On the new era of urban traffic monitoring with massive drone data: The pNEUMA large-scale field experiment", Transportation Research Part C: Emerging Technologies, vol. 111, pp. 50-71, 2020. DOI: 10.1016/j.trc.2019.11.023.

D. Gloudemans, Y. Wang, J. Ji et al., "I-24 MOTION: An instrument for freeway traffic science", Transportation Research Part C: Emerging Technologies, vol. 155, p. 104311, 2023. DOI: 10.1016/j.trc.2023.104311.

A. Kutsch, M. Margreiter, and K. Bogenberger, "TUMDOT-MUC: Data Collection and Processing of Multimodal Trajectories Collected by Aerial Drones", Data Science for Transportation, vol. 6, no. 2, p. 15, 2024. DOI: 10.1007/s42421-024-00101-5.

M. Berghaus, S. Lamberty, J. Ehlers, E. Kalló, and M. Oeser, "Vehicle trajectory dataset from drone videos including off-ramp and congested traffic – Analysis of data quality, traffic flow, and accident risk", Communications in Transportation Research, vol. 4, p. 100133, 2024. DOI: 10.1016/j.commtr.2024.100133.

C. Schicktanz, L. Klitzke, K. Gimm et al., "DLR Urban Traffic dataset (DLR UT)", version 1.2.0, Zenodo, 2025. DOI: 10.5281/zenodo.14773161.

P. Alvarez Lopez, O. A. Banse Bueno, M. P. S. Barthauer et al., "Simulation of Urban Mobility (SUMO) (Version 1.22.0)", Feb. 2025. [Online]. Available: https://elib.dlr.de/212503/.

P. A. Lopez, M. Behrisch, L. Bieker-Walz et al., "Microscopic Traffic Simulation using SUMO", in The 21st IEEE International Conference on Intelligent Transportation Systems, IEEE, 2018. [Online]. Available: https://elib.dlr.de/124092/.

Institute of Transportation Systems of DLR, "‘Research Intersection’ – a hub for data collection in the field", 2025. Accessed: Apr. 1, 2025. [Online]. Available: https://www.dlr.de/en/ts/research-transfer/research-infrastructure/test-areas/acquisition-technology/research-intersection.

VVM, "VVM - Verification Validation Methods", 2023. Accessed: Mar. 7, 2025. [Online]. Available: https://www.vvm-projekt.de/en/project.

KoFeMo, "Kombinierte Untersuchung von Feinstaub und Mobilität – KoFeMo", 2024. Accessed: Mar. 7, 2025. [Online]. Available: https://bmdv.bund.de/SharedDocs/DE/Artikel/DG/mfund-projekte/kofemo.html.

Published

2025-07-15

How to Cite

Flötteröd, Y.-P., & Wagner, P. (2025). SUMO Simulation of DLR’s Research Intersection. SUMO Conference Proceedings, 6, 25–32. https://doi.org/10.52825/scp.v6i.2633

Conference Proceedings Volume

Section

Conference papers
Received 2025-03-08
Accepted 2025-04-25
Published 2025-07-15