IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i13p7162-d582379.html
   My bibliography  Save this article

Data-Driven Methodology for Sustainable Urban Mobility Assessment and Improvement

Author

Listed:
  • Marko Šoštarić

    (Faculty of Transport and Traffic Sciences, University of Zagreb, Vukelićeva 4, 10000 Zagreb, Croatia)

  • Krešimir Vidović

    (Ericsson Nikola Tesla, Krapinska 45, 10000 Zagreb, Croatia)

  • Marijan Jakovljević

    (Faculty of Transport and Traffic Sciences, University of Zagreb, Vukelićeva 4, 10000 Zagreb, Croatia)

  • Orsat Lale

    (Faculty of Transport and Traffic Sciences, University of Zagreb, Vukelićeva 4, 10000 Zagreb, Croatia)

Abstract

The transport system is sensitive to external influences generated by various economic, social and environmental changes. The society and the environment are changing extremely fast, resulting in the need for rapid adjustment of the transport system. Traffic system management, especially in urban areas, is a dynamic process, which is why transport planners are in need of a proven and validated methodology for fast and efficient transport data collection, fusion and analytics that will be used in sustainable urban mobility policy creation. The paper presents a development of a methodology in data rich reality that combines traditional and novel data science approach for transport system analysis and planning. The result is overall process consisting of 150 steps from first desktop research to final solution development. It enables urban mobility stakeholders to identify transport problems, analyze the urban mobility situation and to propose dedicated measures for sustainable urban mobility strengthening. The methodology is based on a big data research and analysis on anonymized big data sets originating from mobile telecommunication network, where the extraction of mobility data from the big dataset is the most innovative part of the proposed process. The extracted mobility data were validated through a “conventional” field research. The methodology was, for additional testing, applied in a pilot study, performed in the City of Rijeka in Croatia. It resulted in a set of alternative measures for modal shift from passenger cars to sustainable mobility modes, that were validated by the local public and urban mobility stakeholders.

Suggested Citation

  • Marko Šoštarić & Krešimir Vidović & Marijan Jakovljević & Orsat Lale, 2021. "Data-Driven Methodology for Sustainable Urban Mobility Assessment and Improvement," Sustainability, MDPI, vol. 13(13), pages 1-22, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:13:p:7162-:d:582379
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/13/7162/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/13/7162/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Patrick Bonnel & Etienne Hombourger & Ana-Maria Olteanu-Raimond & Zbigniew Smoreda, 2015. "Passive Mobile Phone Dataset to Construct Origin-destination Matrix: Potentials and Limitations," Post-Print halshs-01664219, HAL.
    2. Krešimir Vidović & Marko Šoštarić & Sadko Mandžuka & Goran Kos, 2020. "Model for Estimating Urban Mobility Based on the Records of User Activities in Public Mobile Networks," Sustainability, MDPI, vol. 12(3), pages 1-27, January.
    3. Ivana Semanjski & Rik Bellens & Sidharta Gautama & Frank Witlox, 2016. "Integrating Big Data into a Sustainable Mobility Policy 2.0 Planning Support System," Sustainability, MDPI, vol. 8(11), pages 1-19, November.
    4. Filippo Simini & Marta C. González & Amos Maritan & Albert-László Barabási, 2012. "A universal model for mobility and migration patterns," Nature, Nature, vol. 484(7392), pages 96-100, April.
    5. Milne, Dave & Watling, David, 2019. "Big data and understanding change in the context of planning transport systems," Journal of Transport Geography, Elsevier, vol. 76(C), pages 235-244.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xi Lu & Jiaqing Lu & Xinzheng Yang & Xumei Chen, 2022. "Assessment of Urban Mobility via a Pressure-State-Response (PSR) Model with the IVIF-AHP and FCE Methods: A Case Study of Beijing, China," Sustainability, MDPI, vol. 14(5), pages 1-23, March.
    2. Min Wu & Bingxin Yan & Ying Huang & Md Nazirul Islam Sarker, 2022. "Big Data-Driven Urban Management: Potential for Urban Sustainability," Land, MDPI, vol. 11(5), pages 1-16, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rawad Choubassi & Lamia Abdelfattah, 2020. "How Big Data is Transforming the Way We Plan Our Cities," Briefs, Fondazione Eni Enrico Mattei, December.
    2. Chen, Yanguang, 2023. "Demonstration of duality of fractal gravity models by scaling symmetry," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    3. Kevin Credit & Zander Arnao, 2023. "A method to derive small area estimates of linked commuting trips by mode from open source LODES and ACS data," Environment and Planning B, , vol. 50(3), pages 709-722, March.
    4. Tranos, Emmanouil & Incera, Andre Carrascal & Willis, George, 2022. "Using the web to predict regional trade flows: data extraction, modelling, and validation," OSF Preprints 9bu5z, Center for Open Science.
    5. Laila Oubahman & Szabolcs Duleba, 2022. "A Comparative Analysis of Homogenous Groups’ Preferences by Using AIP and AIJ Group AHP-PROMETHEE Model," Sustainability, MDPI, vol. 14(10), pages 1-18, May.
    6. Huang, Feihu & Qiao, Shaojie & Peng, Jian & Guo, Bing & Xiong, Xi & Han, Nan, 2019. "A movement model for air passengers based on trip purpose," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 798-808.
    7. Varga, Levente & Tóth, Géza & Néda, Zoltán, 2017. "An improved radiation model and its applicability for understanding commuting patterns in Hungary," MPRA Paper 76806, University Library of Munich, Germany.
    8. Sgrignoli, Paolo & Metulini, Rodolfo & Schiavo, Stefano & Riccaboni, Massimo, 2015. "The relation between global migration and trade networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 245-260.
    9. James Truscott & Neil M Ferguson, 2012. "Evaluating the Adequacy of Gravity Models as a Description of Human Mobility for Epidemic Modelling," PLOS Computational Biology, Public Library of Science, vol. 8(10), pages 1-12, October.
    10. Alattar, Mohammad Anwar & Cottrill, Caitlin & Beecroft, Mark, 2021. "Public participation geographic information system (PPGIS) as a method for active travel data acquisition," Journal of Transport Geography, Elsevier, vol. 96(C).
    11. Chen, Yong & Geng, Maosi & Zeng, Jiaqi & Yang, Di & Zhang, Lei & Chen, Xiqun (Michael), 2023. "A novel ensemble model with conditional intervening opportunities for ride-hailing travel mobility estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    12. Md Altab Hossin & Jie Du & Lei Mu & Isaac Owusu Asante, 2023. "Big Data-Driven Public Policy Decisions: Transformation Toward Smart Governance," SAGE Open, , vol. 13(4), pages 21582440231, December.
    13. Chaogui Kang & Yu Liu & Diansheng Guo & Kun Qin, 2015. "A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-11, November.
    14. Luo, Xiaohu & Caron, Justin & Karplus, Valerie J. & Zhang, Da & Zhang, Xiliang, 2016. "Interprovincial migration and the stringency of energy policy in China," Energy Economics, Elsevier, vol. 58(C), pages 164-173.
    15. Mark Thissen & Olga Ivanova & Giovanni Mandras & Trond Husby, 2019. "European NUTS 2 regions: construction of interregional trade-linked Supply and Use tables with consistent transport flows," JRC Working Papers on Territorial Modelling and Analysis 2019-01, Joint Research Centre.
    16. Thompson, C.A. & Saxberg, K. & Lega, J. & Tong, D. & Brown, H.E., 2019. "A cumulative gravity model for inter-urban spatial interaction at different scales," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    17. Gonzalo Suarez & Rachata Muneepeerakul, 2022. "Modeling human migration driven by changing mindset, agglomeration, social ties, and the environment," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-11, February.
    18. Rosita De Vincentis & Federico Karagulian & Carlo Liberto & Marialisa Nigro & Vincenza Rosati & Gaetano Valenti, 2022. "A Data-Driven Approach to Analyze Mobility Patterns and the Built Environment: Evidence from Brescia, Catania, and Salerno (Italy)," Sustainability, MDPI, vol. 14(21), pages 1-14, November.
    19. Vinyas Harish & Felipe J. Colón-González & Filipe R. R. Moreira & Rory Gibb & Moritz U. G. Kraemer & Megan Davis & Robert C. Reiner & David M. Pigott & T. Alex Perkins & Daniel J. Weiss & Isaac I. Bog, 2024. "Human movement and environmental barriers shape the emergence of dengue," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    20. Paul Baustert & Tomás Navarrete Gutiérrez & Thomas Gibon & Laurent Chion & Tai-Yu Ma & Gabriel Leite Mariante & Sylvain Klein & Philippe Gerber & Enrico Benetto, 2019. "Coupling Activity-Based Modeling and Life Cycle Assessment—A Proof-of-Concept Study on Cross-Border Commuting in Luxembourg," Sustainability, MDPI, vol. 11(15), pages 1-24, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:13:p:7162-:d:582379. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.