Topology-Preserving Simplification of OpenStreetMap Network Data for Large-scale Simulation in SUMO




SUMO, Traffic Simulation, Road network conversion, OpenStreetMap


Converting OpenStreetMap (OSM) data to a road network suitable for microscopic traffic simulation keeps being a challenging task: both missing information and excessive details, as well as wrong typologies present in the dataset frequently confuses automatic converters. In this paper, we present a method along with a reference implementation, Traffic Simulation Map Maker (TSMM), which aims at substantially increasing the automation level of road network prototyping by simplifying the OSM data while preserving important topology information. The main objective of this work is to enable the study of traffic simulation dynamics at scale using real-world road networks, while minimizing the need for solving the long tail of problems related to the road network generation. Our proposed approach yields what we believe is a good trade-off between precision and automation, making bold yet acceptable decisions that solve most of the errors at the source, i.e., the map. While there is definitely a loss in fidelity with respect to the real world, many properties of the road network are preserved. We argue that TSMM greatly improves the availability of arbitrarily large and usable road networks on top of available OSM maps by reducing the complexity for conversion tools and traffic simulation researchers alike. A proof-of-concept study using OSM data from Binjiang, China, demonstrates that TSMM is able to generate a road network with well-preserved topological information which avoids the many errors and deadlocks that occur when building the network using the original input sources.


Download data is not yet available.


M. Fellendorf and P. Vortisch, “Microscopic traffic flow simulator VISSIM,” in Fundamentals of traffic simulation. Springer New York, 2010, pp. 63–93. doi:

D. Zehe, S. Nair, A. Knoll, and D. Eckhoff, “Towards CityMoS: A Coupled City-Scale Mobility Simulation Framework,” in 5th GI/ITG KuVS Fachgespräch Inter-Vehicle Communication (FG-IVC 2017), Erlangen, Germany: FAU Erlangen-Nuremberg, 2017.

P. A. Lopez et al., “Microscopic Traffic Simulation using SUMO,” in 2018 21st International Conference on Intelligent Transportation Systems (ITSC), IEEE, Nov. 2018. doi:

J. Bennett, OpenStreetMap. Packt Publishing Ltd, 2010.

D. Krajzewicz, G. Hertkorn, C. Rössel, and P. Wagner, “SUMO (Simulation of Urban MObility)-an opensource traffic simulation,” in Proceedings of the 4th middle East Symposium on Simulation and Modelling (MESM20002), 2002, pp. 183–187.

F. Tabet et al., “OSMRunner: A System for Exploring and Fixing OSM Connectivity,” in 22nd IEEE International Conference on Mobile Data Management (MDM 2021), IEEE, 2021, pp. 193–200. doi: MDM52706.2021.00039.

C. Bewermeyer, R. Berndt, S. Schellenberg, R. German, and D. Eckhoff, “Poster: cOSMetic – towards reliable OSM to sumo network conversion,” in 2015 IEEE Vehicular Networking Conference (VNC), IEEE, 2015, pp. 151–152. doi:

M. Haklay and P. Weber, “OpenStreetMap: User-Generated Street Maps,” IEEE Pervasive Computing, vol. 7, no. 4, pp. 12–18, Oct. 2008. doi:

L. Codecá, R. Frank, S. Faye, and T. Engel, “Luxembourg SUMO Traffic (LuST) Scenario: Traffic Demand Evaluation,” IEEE Intelligent Transportation Systems Magazine, vol. 9, no. 2, pp. 52–63, 2017. doi:

M. Rapelli, C. Casetti, and G. Gagliardi, “TuST: from Raw Data to Vehicular Traffic Simulation in Turin,” in 2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT), IEEE, Oct. 2019. doi:

H. Wang, J. Wang, P. Yu, X. Chen, and Z. Wang, “Extraction and construction algorithm of traffic road network model based on OSM file,” in 2021 4th International Conference on Advanced Algorithms and Control Engineering (ICAACE 2021), vol. 1848, Sanya, China: IOP, Jan. 2021, p. 012 084. doi:

T. Ziemke and S. Braun, “Automated generation of traffic signals and lanes for MATSim based on Open-StreetMap,” Elsevier Procedia Computer Science, vol. 184, pp. 745–752, 2021. doi:

Y. Xu, Z. Xie, L. Wu, and Z. Chen, “Multilane roads extracted from the OpenStreetMap urban road network using random forests,” Wiley Transactions in GIS, vol. 23, no. 2, pp. 224–240, Dec. 2019. doi:

Q. Li, H. Fan, X. Luan, B. Yang, and L. Liu, “Polygon-based approach for extracting multilane roads from OpenStreetMap urban road networks,” Taylor & Francis International Journal of Geographical Information Science, vol. 28, no. 11, pp. 2200–2219, May 2014. doi:




How to Cite

Meng, Z., Du, X., Sottovia, P., Foroni, D., Axenie, C., Wieder, A., … Sommer, C. (2022). Topology-Preserving Simplification of OpenStreetMap Network Data for Large-scale Simulation in SUMO. SUMO Conference Proceedings, 3, 181–197.

Conference Proceedings Volume


Conference papers