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Travel Demand Prediction during COVID-19 Pandemic: Educational and Working Trips at the University of Padova

Author

Listed:
  • Riccardo Ceccato

    (Department of Civil, Architectural and Environmental Engineering, University of Padova, Via Marzolo, 9, 35131 Padova, Italy)

  • Riccardo Rossi

    (Department of Civil, Architectural and Environmental Engineering, University of Padova, Via Marzolo, 9, 35131 Padova, Italy)

  • Massimiliano Gastaldi

    (Department of Civil, Architectural and Environmental Engineering, University of Padova, Via Marzolo, 9, 35131 Padova, Italy
    Department of General Psychology, University of Padova, Via Venezia, 8, 35131 Padova, Italy)

Abstract

The diffusion of the COVID-19 pandemic has induced fundamental changes in travel habits. Although many previous authors have analysed factors affecting observed variations in travel demand, only a few works have focused on predictions of future new normal conditions when people will be allowed to decide whether to travel or not, although risk mitigation measures will still be enforced on vehicles, and innovative mobility services will be implemented. In addition, few authors have considered future mandatory trips of students that constitute a great part of everyday travels and are fundamental for the development of society. In this paper, logistic regression models were calibrated by using data from a revealed and stated-preferences mobility survey administered to students and employees at the University of Padova (Italy), to predict variables impacting on their decisions to perform educational and working trips in the new normal phase. Results highlighted that these factors are different between students and employees; furthermore, available travel alternatives and specific risk mitigation measures on vehicles were found to be significant. Moreover, the promotion of the use of bikes, as well as bike sharing, car pooling and micro mobility among students can effectively foster sustainable mobility habits. On the other hand, countermeasures on studying/working places resulted in a slight effect on travel decisions.

Suggested Citation

  • Riccardo Ceccato & Riccardo Rossi & Massimiliano Gastaldi, 2021. "Travel Demand Prediction during COVID-19 Pandemic: Educational and Working Trips at the University of Padova," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6596-:d:572002
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    References listed on IDEAS

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    7. Song, Jie & Zhang, Liye & Qin, Zheng & Ramli, Muhamad Azfar, 2022. "Spatiotemporal evolving patterns of bike-share mobility networks and their associations with land-use conditions before and after the COVID-19 outbreak," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
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