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Repurposing Open Traffic Data for Estimating the Mobility Performance

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Smart Energy for Smart Transport (CSUM 2022)

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Abstract

Traffic monitoring and advanced urban analytics play an important role in city planning and in attaining sustainable mobility through data-driven decision-making. With the advent of open-sourced data initiatives, new data-sharing technologies and software, also analytical methods, and data integration techniques are forced to subsequent levels. In this paper, we present two pilot studies of a recently conducted national project, joining vehicle counts and the travel times to present roadway traffic flows. We introduce a targeted selection of indicators and demonstrate the applicability of travel time metrics and the vehicle count measures, by combining different open datasets and transferable analyses to advance the interpretation strength of the data. Concretely, we apply regression methods based on the cosinor model, which allows us to analyze the rhythmic behavior of travel time and congestion trends. Furthermore, following the principles of data integration and data reusability we examine, using regression modeling and cross-validation, the possibilities to interchangeably use the governmental roadway counting database, vehicle counting by WeCount Ljubljana Telraam database, and the travel times records sourced by Google Direction API. The data analyzed indicate the possible interchangeability in selected scenarios and confirm the prospective to be used as complementary systems in the city monitoring and for urban sustainability assessment.

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Notes

  1. 1.

    Directive (EU) 2019/1024 of the European Parliament and of the Council on open data and the re-use of public sector information: https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:32019L1024.

  2. 2.

    Detection and analysis of rhythmic patterns were initially introduced and developed, especially in the field of biology and medicine [9].

  3. 3.

    Slovenian Research Agency [J5-1798, 2019–2022].

  4. 4.

    https://we-count.net/networks/ljubljana.

  5. 5.

    Data ownership: All intellectual property rights in the traffic statistics collected by Telraam and the data.

    bases it contains belong to the Telraam Alliance, in this case to the WeCount Ljubljana team from University.

    of Ljubljana Faculty of Architecture.

    The WeCount Ljubljana Telraam sensors data are openly available under the CC-BY-NC license (https://creativecommons.org/licenses/by-nc/4.0/legalcode; https://telraam.zendesk.com/hc/en-us/articles/360056754532-Telraam-Data-License). The creator(s) of the Licensed Material is: WeCount Ljubljana Telraam. A copyright notice is: ©WeCount Ljubljana Telraam. A notice that refers to this Public License is: All intellectual property rights from the WeCount Ljubljana Telraam belong to the University of Ljubljana Faculty of Architecture, WeCount Ljubljana team. Funding: This work was part of the WeCount: Citizens Observing UrbaN Transport project. The project received financial support from the EU Research and Innovation Framework Programme Horizon 2020 under Agreement number 87274.

  6. 6.

    The free-flow travel time rate in our case was defined, as suggested by [34], by the 85th -percentile travel time during overnight hours (10 p.m. to 5 a.m.).

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Acknowledgments

We would like to thank the Slovenian Ministry of Infrastructure, and the Municipality of Ljubljana for granting access to the inductive loop counters data. We would also like to acknowledge the WeCount Ljubljana Telraam project team (https://www.we-count.net, specifically Tomaž Berčič) for enabling Open Access to the collected data. This work was supported by the Slovenian Research Agency [J5-1798, 2019–2022; P5-0068, 2017–2023; P2-0359, 2013–2023] and H2020 WeCount-project, under grant agreement No. 872743. The funding body had no role in the design of the study and collection, analysis, and interpretation of data nor in writing the manuscript.

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Authors and Affiliations

  1. Faculty of Architecture, University of Ljubljana, Ljubljana, Slovenia

    Špela Verovsek, Tadeja Zupančič, Matevž Juvančič & Lucija Ažman Momirski

  2. Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia

    Miha Janež & Miha Moškon

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  1. Špela Verovsek
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  2. Tadeja Zupančič
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  3. Matevž Juvančič
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  4. Lucija Ažman Momirski
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Correspondence to Špela Verovsek .

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Editors and Affiliations

  1. Department of Civil Engineering, University of Thessaly, Volos, Greece

    Eftihia G. Nathanail

  2. Department of Planning and Regional Development, University of Thessaly, Volos, Greece

    Nikolaos Gavanas

  3. Department of Civil Engineering, University of Thessaly, Volos, Greece

    Giannis Adamos

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Verovsek, Š., Zupančič, T., Juvančič, M., Momirski, L.A., Janež, M., Moškon, M. (2023). Repurposing Open Traffic Data for Estimating the Mobility Performance. In: Nathanail, E.G., Gavanas, N., Adamos, G. (eds) Smart Energy for Smart Transport. CSUM 2022. Lecture Notes in Intelligent Transportation and Infrastructure. Springer, Cham. https://doi.org/10.1007/978-3-031-23721-8_45

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  • DOI: https://doi.org/10.1007/978-3-031-23721-8_45

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