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Visual Analytic of Traffic Simulation Data: A Review

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Smart Cities (ICSC-Cities 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1938))

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Abstract

In the contemporary world, transportation is one of the foremost necessities for modern society, particularly within urban locales. Effective traffic management and planning represent indispensable tasks to maintain a seamless traffic flow and reduce congestion. To achieve this objective, traffic simulation data plays a pivotal role by furnishing intricate insights into traffic patterns, vehicle positions, events, and other pertinent aspects of a specific area. The visualization of traffic simulation data assumes paramount importance, serving as a vital tool for comprehending this information and making informed decisions. This paper provides a comprehensive review of the state of the art regarding web-based visualization techniques focused on traffic data provided by simulators, especially Multi-Agent Transport Simulation (MATSim). In addition, it will shed light on the most commonly employed features designed to facilitate the temporal analysis of traffic data, encompassing movement and congestion patterns. These resources hold significant potential for transport planners and traffic management professionals in creating web-based visualizations.

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Notes

  1. 1.

    https://www.matsim.org/.

  2. 2.

    https://www.ptvgroup.com/en/products/ptv-vissim.

  3. 3.

    https://eclipse.dev/sumo/.

References

  1. Andrienko, G., Andrienko, N., Bak, P., Keim, D., Wrobel, S.: Visual Analytics of Movement. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-37583-5

    Book  Google Scholar 

  2. Andrienko, N., Andrienko, G., Gatalsky, P.: Exploratory spatio-temporal visualization: an analytical review. J. Vis. Lang. Comput. 14(6), 503–541 (2003)

    Article  Google Scholar 

  3. Bachechi, C., Po, L., Rollo, F.: Big Data analytics and visualization in traffic monitoring. Big Data Res. 27, 100292 (2022)

    Article  Google Scholar 

  4. Carter, N., et al.: Developing mobility and traffic visualization applications for connected vehicles. arXiv preprint arXiv:1811.11012 (2018)

  5. Charlton, B., Laudan, J.: Web-based data visualization platform for MATSim. Transp. Res. Rec. 2674(10), 124–133 (2020)

    Article  Google Scholar 

  6. Charlton, W., Leich, G., Kaddoura, I.: Open-source web-based visualizer for dynamic-response shared taxi simulations. Procedia Comput. Sci. 184, 728–733 (2021)

    Article  Google Scholar 

  7. Charlton, W., Sana, B.: SimWrapper, an open source web-based platform for interactive visualization of microsimulation outputs and transport data. Procedia Comput. Sci. 220, 724–729 (2023)

    Article  Google Scholar 

  8. Chen, W., Guo, F., Wang, F.Y.: A survey of traffic data visualization. IEEE Trans. Intell. Transp. Syst. 16(6), 2970–2984 (2015)

    Article  Google Scholar 

  9. Erath, A., Fourie, P.J.: Interactive analysis and decision support with MATSim. In: The Multi-agent Transport Simulation MATSim, pp. 253–258. Ubiquity Press (2016)

    Google Scholar 

  10. Hammer, P.L., Rudeanu, S.: Boolean Methods in Operations Research and Related Areas. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-85823-9

    Book  Google Scholar 

  11. Islam, M., Jin, S.: An overview of data visualization. In: 2019 International Conference on Information Science and Communications Technologies (ICISCT), pp. 1–7. IEEE (2019)

    Google Scholar 

  12. Jung, J., Oh, T., Kim, I., Park, S.: Open-sourced real-time visualization platform for traffic simulation. Procedia Comput. Sci. 220, 243–250 (2023)

    Article  Google Scholar 

  13. Kohlhammer, J., Keim, D., Pohl, M., Santucci, G., Andrienko, G.: Solving problems with visual analytics. Procedia Comput. Sci. 7, 117–120 (2011)

    Article  Google Scholar 

  14. Lee, C., et al.: A visual analytics system for exploring, monitoring, and forecasting road traffic congestion. IEEE Trans. Vis. Comput. Graph. 26(11), 3133–3146 (2019)

    Article  Google Scholar 

  15. Miranda, D., Arruda, F.: Method for simulating a MATSim multi-agent activity-based transport model in developing countries, July 2019

    Google Scholar 

  16. Petrovska, N., Stevanovic, A.: Traffic congestion analysis visualisation tool. In: 2015 IEEE 18th International Conference on Intelligent Transportation Systems, pp. 1489–1494. IEEE (2015)

    Google Scholar 

  17. Pi, M., Yeon, H., Son, H., Jang, Y.: Visual cause analytics for traffic congestion. IEEE Trans. Vis. Comput. Graph. 27(3), 2186–2201 (2019)

    Article  Google Scholar 

  18. Piris, C., et al.: Estudio y desarrollo de una aplicación web para la generación y tratamiento de datos del simulador MATSIm (2013)

    Google Scholar 

  19. Scheepens, R., Hurter, C., Van De Wetering, H., Van Wijk, J.J.: Visualization, selection, and analysis of traffic flows. IEEE Trans. Vis. Comput. Graph. 22(1), 379–388 (2015)

    Article  Google Scholar 

  20. Shakeel, H.M., Iram, S., Al-Aqrabi, H., Alsboui, T., Hill, R.: A comprehensive state-of-the-art survey on data visualization tools: research developments, challenges and future domain specific visualization framework. IEEE Access 10, 96581–96601 (2022)

    Article  Google Scholar 

  21. Strippgen, D.: OTFVis: MATSim’s open-source visualizer. In: The Multi-Agent Transport Simulation MATSim, pp. 225–234 (2016)

    Google Scholar 

  22. Taplin, J.: Simulation models of traffic flow. In: The 34th Annual Conference of the Operational Research Society of New Zealand, New Zealand (1999)

    Google Scholar 

  23. Ullah, M.R., Khattak, K.S., Khan, Z.H., Khan, M.A., Minallah, N., Khan, A.N.: Vehicular traffic simulation software: a systematic comparative analysis. Pakistan J. Eng. Technol. 4(1), 66–78 (2021)

    Google Scholar 

  24. Axhausen, K.W., Horni, A., Nagel, K.: The Multi-Agent Transport Simulation MATSim. Ubiquity Press (2016)

    Google Scholar 

  25. Wang, K., Liang, M., Li, Y., Liu, J., Liu, R.W.: Maritime traffic data visualization: a brief review. In: 2019 IEEE 4th International Conference on Big Data Analytics (ICBDA), pp. 67–72. IEEE (2019)

    Google Scholar 

  26. Waraich, R.A., Charypar, D., Balmer, M., Axhausen, K.W.: Performance improvements for large-scale traffic simulation in MATSim. In: Helbich, M., Jokar Arsanjani, J., Leitner, M. (eds.) Computational Approaches for Urban Environments. GE, vol. 13, pp. 211–233. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-11469-9_9

    Chapter  Google Scholar 

  27. Xu, H., Berres, A., Wang, C.R., LaClair, T.J., Sanyal, J.: Visualizing vehicle acceleration and braking energy at intersections along a major traffic corridor. In: Proceedings of the Twelfth ACM International Conference on Future Energy Systems, pp. 401–405 (2021)

    Google Scholar 

  28. Xu, H., Wang, C., Berres, A., LaClair, T., Sanyal, J.: Interactive web application for traffic simulation data management and visualization. Transp. Res. Rec. 2676(1), 274–292 (2022)

    Article  Google Scholar 

  29. Zhang, H.S., Zhang, Y., Li, Z.H., Hu, D.C.: Spatial-temporal traffic data analysis based on global data management using MAS. IEEE Trans. Intell. Transp. Syst. 5(4), 267–275 (2004)

    Article  Google Scholar 

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Acknowledgment

The authors express their gratitude to the Data Science and Analytics (DataScienceYT) group at Yachay Tech University for their assistance during the development of this work.

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Authors and Affiliations

  1. Yachay Tech University, Urcuquí, 100119, Ecuador

    Christopher Almachi, Rolando Armas & Erick Cuenca

Authors
  1. Christopher Almachi
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  2. Rolando Armas
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  3. Erick Cuenca
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Corresponding author

Correspondence to Christopher Almachi .

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Editors and Affiliations

  1. Universidad de la República, Montevideo, Uruguay

    Sergio Nesmachnow

  2. Universidad de Valladolid, Soria, Soria, Spain

    Luis Hernández Callejo

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Almachi, C., Armas, R., Cuenca, E. (2024). Visual Analytic of Traffic Simulation Data: A Review. In: Nesmachnow, S., Hernández Callejo, L. (eds) Smart Cities. ICSC-Cities 2023. Communications in Computer and Information Science, vol 1938. Springer, Cham. https://doi.org/10.1007/978-3-031-52517-9_4

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  • DOI: https://doi.org/10.1007/978-3-031-52517-9_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-52516-2

  • Online ISBN: 978-3-031-52517-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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