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Citizen Science for Traffic Monitoring: Investigating the Potentials for Complementing Traffic Counters with Crowdsourced Data

Author

Listed:
  • Miha Janež

    (Faculty of Computer and Information Science, University of Ljubljana, 1000 Ljubljana, Slovenia)

  • Špela Verovšek

    (Faculty of Architecture, University of Ljubljana, 1000 Ljubljana, Slovenia)

  • Tadeja Zupančič

    (Faculty of Architecture, University of Ljubljana, 1000 Ljubljana, Slovenia)

  • Miha Moškon

    (Faculty of Computer and Information Science, University of Ljubljana, 1000 Ljubljana, Slovenia)

Abstract

Traffic counts are among the most frequently employed data to assess the traffic patterns and key performance indicators of next generation sustainable cities. Automatised counting is often based on conventional traffic monitoring systems such as inductive loop counters (ILCs). These are costly to install, maintain, and support. In this paper, we investigate the possibilities to complement and potentially replace the existing traffic monitoring infrastructure with crowdsourcing solutions. More precisely, we investigate the capabilities to predict the ILC-obtained data using Telraam counters, low-cost camera counters voluntarily employed by citizens and freely accessible by the general public. In this context, we apply different exploratory data analysis approaches and demonstrate a regression procedure with a selected set of regression models. The presented analysis is demonstrated on different urban and highway road segments in Slovenia. Our results show that the data obtained from low-cost and easily accessible counters can be used to replace the existing traffic monitoring infrastructure in different scenarios. These results confirm the prospective to directly apply the citizen engagement in the process of planning and maintaining sustainable future cities.

Suggested Citation

  • Miha Janež & Špela Verovšek & Tadeja Zupančič & Miha Moškon, 2022. "Citizen Science for Traffic Monitoring: Investigating the Potentials for Complementing Traffic Counters with Crowdsourced Data," Sustainability, MDPI, vol. 14(2), pages 1-18, January.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:2:p:622-:d:719069
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    Citations

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    Cited by:

    1. Miha Moškon & Tadeja Režen & Matevž Juvančič & Špela Verovšek, 2022. "Integrative Analysis of Rhythmicity: From Biology to Urban Environments and Sustainability," IJERPH, MDPI, vol. 20(1), pages 1-13, December.

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