Topology-Preserving Simplification of OpenStreetMap Network Data for Large-scale Simulation in SUMO
Keywords: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.
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Copyright (c) 2022 Zhuoxiao Meng, Xiaorui Du, Paolo Sottovia, Daniele Foroni, Cristian Axenie, Alexander Wieder, David Eckhoff, Stefano Bortoli, Alios Knoll, Christoph Sommer
This work is licensed under a Creative Commons Attribution 3.0 Unported License.