Sumonity: Bridging SUMO and Unity for Enhanced Traffic Simulation Experiences
DOI:
https://doi.org/10.52825/scp.v5i.1115Keywords:
Co-Simulation, Unity, Vehicle Control, Traffic SimulationAbstract
This paper presents "Sumonity," an interface that bridges SUMO (Simulation of Urban MObility) and Unity, combining SUMO's robust traffic modeling capabilities with Unity's advanced graphical and physical engine, enhancing realism in traffic simulations. The study explores Sumonity's development and implementation, showcasing its capabilities. The interface offers a significant improvement in simulation fidelity by adopting a pure pursuit control approach within Unity for simulating each traffic agent. This methodological shift allows for more granular control over individual vehicle behaviors, aligning with autonomous and common vehicle dynamics. The paper also discusses the broader implications of Sumonity for future research in this field.
Downloads
References
A. Hayat, Z. Iftikhar, M. Khan, A. Mehbodniya, J. Webber, and S. Hanif, “A novel pseudonym changing scheme for location privacy preservation in sparse traffic areas,” IEEE Access, vol. PP, pp. 1–1, Jan. 2023. DOI: https://doi.org/10.1109/ACCESS.2023.3303846.
M. Qurashi, H. Jiang, and C. Antoniou, “Modeling autonomous dynamic vanpooling services in sumo by integrating a dynamic routing scheduler,” 2020. [Online]. Available: https://api.semanticscholar.org/CorpusID:251387188.
P. Fernandes and U. Nunes, “Platooning of autonomous vehicles with intervehicle communications in sumo traffic simulator,” in 13th International IEEE Conference on Intelligent Transportation Systems, 2010, pp. 1313–1318. DOI: https://doi.org/10.1109/ITSC.2010.5625277.
A. Keler, A. Kunz, S. Amini, and K. Bogenberger, “Calibration of a microscopic traffic simulation in an urban scenario using loop detector data: A case study within the digital twin munich,” SUMO Conference Proceedings, vol. 4, p. 153, Jun. 2023. DOI: https://doi.org/10.52825/scp.v4i.223. [Online]. Available: https://www.tib-op.org/ojs/index.php/scp/article/view/153-163.
J. J. Gonzalez-Delicado, J. Gozalvez, J. Mena-Oreja, M. Sepulcre, and B. Coll-Perales, “Alicante-murcia freeway scenario: A high-accuracy and large-scale traffic simulation scenario generated using a novel traffic demand calibration method in sumo,” IEEE Access, vol. 9, pp. 154 423–154 434, 2021. DOI: https://doi.org/10.1109/ACCESS.2021.3126269.
M. Harth, M. Langer, and K. Bogenberger, “Automated calibration of traffic demand and traffic lights in sumo using real-world observations,” SUMO Conference Proceedings, vol. 2, pp. 133–148, Jun. 2022. DOI: https://doi.org/10.52825/scp.v2i.120. [Online]. Available: https://www.tib-op.org/ojs/index.php/scp/article/view/120.
Y. Sashank, N. A. Navali, A. Bhanuprakash, B. A. Kumar, and L. Vanajakshi, “Calibration of sumo for indian heterogeneous traffic conditions,” in Recent Advances in Traffic Engineering, S. S. Arkatkar, S. Velmurugan, and A. Verma, Eds., Singapore: Springer Singapore, 2020, pp. 199–214, ISBN: 978-981-15-3742-4.
P. Gipps, “A behavioural car-following model for computer simulation,” Transportation Research Part B: Methodological, vol. 15, no. 2, pp. 105–111, 1981, ISSN: 0191-2615. DOI: https://doi.org/10.1016/0191 - 2615(81 ) 90037 - 0. [Online]. Available: https://www.sciencedirect.com/science/article/pii/0191261581900370.
G. Newell, “A simplified car-following theory: A lower order model,” Transportation Research Part B: Methodological, vol. 36, no. 3, pp. 195–205, 2002, ISSN: 0191-2615. DOI: https://doi.org/10.1016/S0191 - 2615(00 ) 00044 - 8. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0191261500000448.
M. Treiber, A. Hennecke, and D. Helbing, “Congested traffic states in empirical observations and microscopic simulations,” Physical Review E, vol. 62, pp. 1805–1824, Feb. 2000. DOI: https://doi.org/10.1103/PhysRevE.62.1805.
V. Punzo and F. Simonelli, “Analysis and comparison of microscopic traffic flow models with real traffic microscopic data,” Transportation Research Record, vol. 1934, no. 1, pp. 53–63, 2005. DOI: 10.1177/0361198105193400106. eprint: https://doi.org/10.1177/0361198105193400106. [Online]. Available: https://doi.org/10.1177/0361198105193400106.
E. Brockfeld and P. Wagner, “Calibration and validation of microscopic traffic flow models,” in Traffic and Granular Flow ’03, S. P. Hoogendoorn, S. Luding, P. H. L. Bovy, M. Schreckenberg, and D. E. Wolf, Eds., Berlin, Heidelberg: Springer Berlin Heidelberg, 2005, pp. 67–72, ISBN: 978-3-540-28091-0.
J. van Lint and S. Calvert, “A generic multi-level framework for microscopic traffic simulation—theory and an example case in modelling driver distraction,” Transportation Research Part B: Methodological, vol. 117, pp. 63–86, 2018, ISSN: 0191-2615. DOI: https://doi.org/10.1016/j.trb.2018.08.009. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0191261518302704.
J. Barcelo, “Models, traffic models, simulation, and traffic simulation,” in Jan. 2011, pp. 1–62, ISBN: 978-1-4419-6141-9. DOI: https://doi.org/10.1007/978-1-4419-6142-6_1.
M. Pechinger, G. Schr¨oer, K. Bogenberger, and C. Markgraf, “Roadside infrastructure support for urban automated driving,” IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 10, pp. 10 643–10 652, 2023. DOI: https://doi.org/10.1109/TITS.2023.3277138.
M. Szalai, B. Varga, T. Tettamanti, and V. Tihanyi, “Mixed reality test environment for autonomous cars using unity 3d and sumo,” in 2020 IEEE 18th World Symposium on Applied Machine Intelligence and Informatics (SAMI), 2020, pp. 73–78. DOI: https://doi.org/10.1109/SAMI48414.2020.9108745.
X. Liao, X. Zhao, Z. Wang, et al., “Game theory-based ramp merging for mixed traffic with unity-sumo co-simulation,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 52, no. 9, pp. 5746–5757, 2022. DOI: https://doi.org/10.1109/TSMC.2021.3131431.
J. Lindner, G. Grigoropoulos, A. Keler, et al., “A mobile application for resolving bicyclist and automated vehicle interactions at intersections,” in 2022 IEEE Intelligent Vehicles Symposium (IV), 2022, pp. 785–791. DOI: https://doi.org/10.1109/IV51971.2022.9827439.
J. Lindner, A. Keler, G. Grigoropoulos, et al., “A coupled driving simulator to investigate the interaction between bicycles and automated vehicles,” in 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 2022, pp. 1335–1341. DOI: https://doi.org/10.1109/ITSC55140.2022.9922400.
F. Denk, C. Himmels, V. Andreev, et al., “Studying interactions of motorists and vulnerable road users: Empirical comparison of test track and simulator experiments,” in 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023, pp. 992–999. DOI: https://doi.org/10.1109/ITSC57777.2023.10421865.
M. Sekeran, A. A. Syed, J. Lindner, M. Margreiter, and K. Bogenberger, Investigating lane-free traffic with a dynamic driving simulator, 2023. arXiv: 2311.16142 [cs.RO].
X. Liao, X. Zhao, Z. Wang, et al., “Game theory-based ramp merging for mixed traffic with unity-sumo co-simulation,” 2022. DOI: https://doi.org/10.1109/tsmc.2021.3131431.
C. Olaverri-Monreal, J. Errea-Moreno, A. Díaz-Álvarez, C. Biurrun-Quel, L. Serrano-Arriezu, and M. Kuba, “Connection of the sumo microscopic traffic simulator and the unity 3d game engine to evaluate v2x communication-based systems,” 2018. DOI: https://doi.org/10.3390/S18124399.
M. Klischat, O. Dragoi, M. Eissa, and M. Althoff, “Coupling sumo with a motion planning framework for automated vehicles,” 2019. DOI: https://doi.org/10.29007/1P2D.
M. Althoff, M. Koschi, and S. Manzinger, “Commonroad: Composable benchmarks for motion planning on roads,” in Proc. of the IEEE Intelligent Vehicles Symposium, 2017, ISBN: 9781509048045. DOI: https://doi.org/10.1109/ivs.2017.7995802.
L. Artal-Villa, A. Hussein, and C. Olaverri-Monreal, “Extension of the 3dcoautosim to simulate vehicle and pedestrian interaction based on sumo and unity 3d,” 2019.
C. Biurrun-Quel, L. Serrano-Arriezu, and C. Olaverri-Monreal, “Microscopic driver-centric simulator: Linking unity3d and sumo,” in 2017. DOI: https://doi.org/10.1007/978-3-319-56535-4_83.
M. Pechinger, G. Schr¨oer, K. Bogenberger, and C. Markgraf, “Cyclist safety in urban automated driving - sub-microscopic hil simulation,” in 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, pp. 615–620. DOI: https://doi.org/10.1109/ITSC48978.2021.9565108.
A. Dosovitskiy, G. Ros, F. Codevilla, A. M. López, and V. Koltun, “Carla: An open urban driving simulator.,” in CoRL, ser. Proceedings of Machine Learning Research, vol. 78, PMLR, 2017, pp. 1–16. [Online]. Available: http://dblp.uni-trier.de/db/conf/corl/corl2017.html#DosovitskiyRCLK17.
R. C. Coulter, “Implementation of the pure pursuit path tracking algorithm,” Carnegie Mellon University, Pittsburgh, PA, Tech. Rep. CMU-RI-TR-92-01, Jan. 1992.
Downloads
Published
How to Cite
Conference Proceedings Volume
Section
License
Copyright (c) 2024 Mathias Pechinger, Johannes Lindner
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
Accepted 2024-04-03
Published 2024-07-17
Funding data
-
Bundesministerium für Wirtschaft und Klimaschutz
Grant numbers FKZ 19A22006T -
Bundesministerium für Bildung und Forschung