IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v6y2021i2p21-d502353.html
   My bibliography  Save this article

An Open GMNS Dataset of a Dynamic Multi-Modal Transportation Network Model of Melbourne, Australia

Author

Listed:
  • Fatemeh Nourmohammadi

    (Department of Industrial Engineering, Khajeh Nasir University of Technology, Tehran 19991-43344, Iran)

  • Mohammadhadi Mansourianfar

    (Research Center for Integrated Transport Innovation (rCITI), School of Civil and Environmental Engineering, University of New South Wales (UNSW), Sydney, NSW 2052, Australia)

  • Sajjad Shafiei

    (Transport Analytics Group, DATA61, CSIRO, Sydney, NSW 2015, Australia)

  • Ziyuan Gu

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing 210096, China)

  • Meead Saberi

    (Research Center for Integrated Transport Innovation (rCITI), School of Civil and Environmental Engineering, University of New South Wales (UNSW), Sydney, NSW 2052, Australia)

Abstract

Simulation-based dynamic traffic assignment models are increasingly used in urban transportation systems analysis and planning. They replicate traffic dynamics across transportation networks by capturing the complex interactions between travel demand and supply. However, their applications particularly for large-scale networks have been hindered by the challenges associated with the collection, parsing, development, and sharing of data-intensive inputs. In this paper, we develop and share an open dataset for reproduction of a dynamic multi-modal transportation network model of Melbourne, Australia. The dataset is developed consistently with the General Modeling Network Specification (GMNS), enabling software-agnostic human and machine readability. GMNS is a standard readable format for sharing routable transportation network data that is designed to be used in multimodal static and dynamic transportation operations and planning models.

Suggested Citation

  • Fatemeh Nourmohammadi & Mohammadhadi Mansourianfar & Sajjad Shafiei & Ziyuan Gu & Meead Saberi, 2021. "An Open GMNS Dataset of a Dynamic Multi-Modal Transportation Network Model of Melbourne, Australia," Data, MDPI, vol. 6(2), pages 1-9, February.
    • Handle: RePEc:gam:jdataj:v:6:y:2021:i:2:p:21-:d:502353
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/6/2/21/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/6/2/21/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Florian, Michael & Mahut, Michael & Tremblay, Nicolas, 2008. "Application of a simulation-based dynamic traffic assignment model," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1381-1392, September.
    2. Wang, Yi & Szeto, W.Y. & Han, Ke & Friesz, Terry L., 2018. "Dynamic traffic assignment: A review of the methodological advances for environmentally sustainable road transportation applications," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 370-394.
    3. Antonello Ignazio Croce & Giuseppe Musolino & Corrado Rindone & Antonino Vitetta, 2020. "Route and Path Choices of Freight Vehicles: A Case Study with Floating Car Data," Sustainability, MDPI, vol. 12(20), pages 1-15, October.
    4. MERCHANT, Deepak K. & NEMHAUSER, George L., 1978. "A model and an algorithm for the dynamic traffic assignment problems," LIDAM Reprints CORE 346, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Deepak K. Merchant & George L. Nemhauser, 1978. "A Model and an Algorithm for the Dynamic Traffic Assignment Problems," Transportation Science, INFORMS, vol. 12(3), pages 183-199, August.
    Full references (including those not matched with items on IDEAS)

    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. Li, Xue-yan & Li, Xue-mei & Yang, Lingrun & Li, Jing, 2018. "Dynamic route and departure time choice model based on self-adaptive reference point and reinforcement learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 77-92.
    2. Celikoglu, Hilmi Berk, 2013. "Reconstructing freeway travel times with a simplified network flow model alternating the adopted fundamental diagram," European Journal of Operational Research, Elsevier, vol. 228(2), pages 457-466.
    3. Moore, II, James E. & Kim, Geunyoung & Cho, Seongdil & Hu, Hsi-hwa & Xu, Rong, 1997. "Evaluating System ATMIS Technologies Via Rapid Estimation Of Network Flows: Final Report," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt5c70f3d9, Institute of Transportation Studies, UC Berkeley.
    4. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    5. Hemant Gehlot & Arif M. Sadri & Satish V. Ukkusuri, 2019. "Joint modeling of evacuation departure and travel times in hurricanes," Transportation, Springer, vol. 46(6), pages 2419-2440, December.
    6. Zhu, Feng & Ukkusuri, Satish V., 2017. "Efficient and fair system states in dynamic transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 272-289.
    7. Bhoopalam, Anirudh Kishore & Agatz, Niels & Zuidwijk, Rob, 2018. "Planning of truck platoons: A literature review and directions for future research," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 212-228.
    8. Anna Nagurney & Ding Zhang, "undated". "Massively Parallel Computation of Dynamic Traffic Problems Modeled as Projected Dynamical Systems," Computing in Economics and Finance 1996 _039, Society for Computational Economics.
    9. Sheu, Jiuh-Biing, 2006. "A composite traffic flow modeling approach for incident-responsive network traffic assignment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 461-478.
    10. Goliszek Sławomir, 2022. "The potential accessibility to workplaces and working-age population by means of public and private car transport in Szczecin," Miscellanea Geographica. Regional Studies on Development, Sciendo, vol. 26(1), pages 31-41, January.
    11. Lam, William H. K. & Huang, Hai-Jun, 1995. "Dynamic user optimal traffic assignment model for many to one travel demand," Transportation Research Part B: Methodological, Elsevier, vol. 29(4), pages 243-259, August.
    12. Berliant, Marcus, 2017. "Commuting and internet traffic congestion," MPRA Paper 77378, University Library of Munich, Germany.
    13. Jiang, Chenming & Bhat, Chandra R. & Lam, William H.K., 2020. "A bibliometric overview of Transportation Research Part B: Methodological in the past forty years (1979–2019)," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 268-291.
    14. Lam, William H. K. & Yin, Yafeng, 2001. "An activity-based time-dependent traffic assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 35(6), pages 549-574, July.
    15. Aalami, Soheila & Kattan, Lina, 2022. "Proportionally fair flow markets for transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 24-41.
    16. Dell'Orco, Mauro, 2006. "A dynamic network loading model for mesosimulation in transportation systems," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1447-1454, December.
    17. José R. Correa & Andreas S. Schulz & Nicolás E. Stier-Moses, 2004. "Selfish Routing in Capacitated Networks," Mathematics of Operations Research, INFORMS, vol. 29(4), pages 961-976, November.
    18. S. Waller & Athanasios Ziliaskopoulos, 2006. "A Combinatorial user optimal dynamic traffic assignment algorithm," Annals of Operations Research, Springer, vol. 144(1), pages 249-261, April.
    19. Ludovic Leclercq & Mahendra Paipuri, 2019. "Macroscopic Traffic Dynamics Under Fast-Varying Demand," Transportation Science, INFORMS, vol. 53(6), pages 1526-1545, November.
    20. André de Palma & Mogens Fosgerau, 2011. "Dynamic Traffic Modeling," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 9, Edward Elgar Publishing.

    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:jdataj:v:6:y:2021:i:2:p:21-:d:502353. 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.