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Estimation of Pedestrian Flows in Urban Context: A Comparison Between the Pre and Post Pandemic Period

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Computational Science and Its Applications – ICCSA 2022 Workshops (ICCSA 2022)

Abstract

The Covid-19 pandemic, within a few months, radically changed the organization of daily life on a global scale; this has affected all aspects related to everyday life such as home-to-work or not home-to the work trips, accessibility of destination, recreational activities and so on.

The need to reduce coronavirus transmission, especially indoors, has imposed the “social or physical distancing” that has required administrations to reorganize roads and sidewalks for public use both to tackle this crisis and to prepare for the future pandemic challenges. Following a previous extensive study devoted to the analysis and prediction of pedestrian flows in urban area in the city of Cassino, a new experimental campaign has been recently designed and carried out in order to validate the previous methodology and/or to highlight new trends in urban pedestrian activities.

Comparison between pre-pandemic and post-pandemic data and calibrated models provided an interesting insight on the pedestrian behavioral impacts of emergency measures undertaken during pandemic. It is believed that obtained results may provide a useful knowledge for urban planners and designers to retrofit urban spaces taking into account the new pedestrian attitudes to mobility induced by the pandemic.

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References

  1. UNICEF: Generation COVID: Respond. Recover. Reimagine (2019). https://unicef.decimalstudios.com/stories/italy. Accessed Dec 2021

  2. Borkowski, P., Jażdżewska-Gutta, M., Szmelter-Jarosz, A.: Lockdowned: everyday mobility changes in response to COVID-19. J. Transp. Geogr. 90, 102906 (2021)

    Article  Google Scholar 

  3. Campisi, T., Basbas, S., Tanbay, N.A., Georgiadis, G.: Some considerations on the key factors determining the reduction of public transport demand in Sicily during COVID-19 pandemic. Int. J. Transp. Dev. Integr. 6(1), 81–94 (2022)

    Article  Google Scholar 

  4. D’Apuzzo, M., Santilli, D., Evangelisti, A., Nicolosi, V.: Some remarks on soft mobility: a new engineered approach to the cycling infrastructure design. In: Gervasi, O., et al. (eds.) ICCSA 2021, Part X. LNCS, vol. 12958, pp. 441–456. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-87016-4_33. ISBN 978-3-030-87015-7

    Chapter  Google Scholar 

  5. WHO: Moving around during the COVID-19 outbreak (2019). https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/publications-and-technical-guidance/environment-and-food-safety. Accessed Mar 2022

  6. United Nations: The 17 Goals (2015). https://sdgs.un.org/goals. Accessed Mar 2022

  7. Alleanza Italiana per lo Sviluppo Sostenibile (ASviS): L’Agenda 2030 dell’Onu per lo sviluppo sostenibile (2015). https://asvis.it/l-agenda-2030-dell-onu-per-lo-sviluppo-sostenibile/. Accessed Mar 2022

  8. Ewing, R., Cervero, R.: Travel and the built environment. J. Am. Plan. Assoc. 76, 265–294 (2010)

    Article  Google Scholar 

  9. Lee, C., Moudon, A.V.: The 3Ds + R: quantifying land use and urban form correlates of walking. Transp. Res. Part D Transp. Environ. 11, 204–215 (2006)

    Article  Google Scholar 

  10. Song, Y., Knaap, G.J.: Measuring urban form: is Portland winning the war on sprawl? J. Am. Plan. Assoc. 70, 210–225 (2004)

    Article  Google Scholar 

  11. Cervero, R., Radisch, C.: Travel choices in pedestrian versus automobile oriented neighborhoods. Working Paper 644, University of California at Berkeley, Berkeley, CA (1995)

    Google Scholar 

  12. Landis, B., Ottenberg, R., Vattikuti, V.: The roadside pedestrian environment: toward a comprehensive level of service. Paper 990570, TRB, National Research Council, Washington, D.C. (1999)

    Google Scholar 

  13. Kitamura, R., Mokhtarian, P.A., Laidet, L.: A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area. Transportation 24, 125–158 (1997)

    Article  Google Scholar 

  14. D’Apuzzo, M., Santilli, D., Evangelisti, A., Pelagalli, V., Montanaro, O., Nicolosi, V.: An exploratory step to evaluate the pedestrian flow in urban environment. In: Gervasi, O., et al. (eds.) ICCSA 2020, Part VII. LNCS, vol. 12255, pp. 645–657. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-58820-5_47. ISBN 978-3-030-58819-9. https://link.springer.com/chap-ter/10.1007/978-3-030-58820-5_47

    Chapter  Google Scholar 

  15. Santilli, D., D’Apuzzo, M., Evangelisti, A., Nicolosi, V.: Towards sustainability: new tools for planning urban pedestrian mobility. Sustainability 13, 9371 (2021). https://doi.org/10.3390/su13169371

    Article  Google Scholar 

  16. Raford, N., Ragland, D.: Pedestrian volume modeling for traffic safety and exposure analysis. University of California Traffic Safety Center White Paper, Berkeley, CA, USA (2005)

    Google Scholar 

  17. Desyllas, J., Duxbury, E., Ward, J., Smith, A.: Pedestrian demand modeling of large cities: an applied example from London. The Center for Advanced Spatial Analysis, Sendai, Japan (2003)

    Google Scholar 

  18. Federal Highway Administration: Guidebook on methods to estimate non-motorized travel: overview of methods. Publication No. FHWA-RD-98-165, United States Department of Transportation: McLean, VI, USA (1999)

    Google Scholar 

  19. McNally, M.: The four-step model. In: Hensher, D.A., Button, K.J. (eds.) Handbook of Transport Modeling. Pergamon, New York (2000)

    Google Scholar 

  20. Olson, J., Spring, D.: Sketch-plan method for estimating pedestrian traffic for central business districts and suburban growth corridors. Transp. Res. Rec. 1578, 38–47 (1997)

    Article  Google Scholar 

  21. Hillier, B., Penn, A., Hanson, J., Grajewski, T., Xu, J.: Natural movement: or, configuration and attraction in urban pedestrian movement. Environ. Plan. B Plan. Des. 20(1), 29–66 (1993)

    Article  Google Scholar 

  22. Dai, X., Yu, W.: Configurational exploration of pedestrian and cyclist movements: a case study of Hangzhou, China. ITU A|Z, pp. 119–129 (2014)

    Google Scholar 

  23. Jiang, B., Claramunt, C.: Integration of space syntax into GIS: new perspectives for urban morphology. Trans. GIS 6(3), 295–309 (2002)

    Article  Google Scholar 

  24. Ostwald Michael, J.: The mathematics of spatial configuration: revisiting, revising and critiquing justified plan graph theory. Nexus Netw. J. 13(2), 445–470 (2011)

    Article  Google Scholar 

  25. Xu, Y., Rollo, J., Jones, D.S., Esteban, Y., Tong, H., Mu, Q.: Towards sustainable heritage tourism: a space syntax-based analysis method to improve tourists’ spatial cognition in chinese historic districts. Buildings 10(2), 29 (2020)

    Article  Google Scholar 

  26. Volchenkov, D., Blanchard, P.: Scaling and universality in city space syntax: between Zipf and Matthew. Phys. A Stat. Mech. Appl. 387(10), 2353–2364 (2008)

    Article  Google Scholar 

  27. Al_Sayed, K.: Space syntax methodology. Bartlett School of Architecture, UCL, London, UK (2018). Proceedings of the Ninth International Space Syntax Symposium, Seoul, Korea, 31 October–3 November 2013

    Google Scholar 

  28. ISTAT: Territorial Bases and Census Variables. https://www.istat.it/it/archivio/104317. Accessed Mar 2022

  29. Kuzmyak, J.R., Walters, J., Bradley, M., Kockelman, K.M.: Estimating bicycling and walking for planning and project development: a guidebook (No. Project 08-78) (2014)

    Google Scholar 

  30. QGIS.org: QGIS Geographic Information System. QGIS Association (2022). http://www.qgis.org

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Acknowledgments

The help of Eng. Biagio Mancino in collecting pedestrian data within the post-pandemic period is gratefully acknowledged.

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Correspondence to Mauro D’Apuzzo .

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D’Apuzzo, M., Santilli, D., Evangelisti, A., Nicolosi, V., Cappelli, G. (2022). Estimation of Pedestrian Flows in Urban Context: A Comparison Between the Pre and Post Pandemic Period. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds) Computational Science and Its Applications – ICCSA 2022 Workshops. ICCSA 2022. Lecture Notes in Computer Science, vol 13380. Springer, Cham. https://doi.org/10.1007/978-3-031-10542-5_33

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  • DOI: https://doi.org/10.1007/978-3-031-10542-5_33

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