How will individuals travel post-COVID? A statistical framework to identify the determinants of different travel behaviors

The outbreak of the pandemic in 2020 has caused an unforeseen situation that significantly changed individuals’ travel patterns around the globe. The transmission prevention measures that were put in place have had both short- and long-term effects on people's activity systems and their daily travel patterns. In order to investigate the pandemic's effects on travel patterns and activity systems, a web-based questionnaire was developed and distributed in Montreal, Canada, in April and May of 2020. In addition to questions about activities before and during COVID-19, a section on how people anticipated travelling in the post-pandemic era was also included in the questionnaire. This research presents insights into how people are planning to travel in the post-COVID period utilizing K-means clustering and Multinomial Logit (MNL) models. the data gathered from the survey resulted into 1620 completed questionnaires, out of which 1597 were valid. This investigation offers crucial insights on anticipated changes in travel frequency, use of public transportation, and use of bicycles throughout the post-pandemic era. The findings of this study will help planners and policymakers create plans that will better prepare the cities for the post-pandemic era by taking into account the projected changes in people's travel patterns.

Mots clés

• COVID-19
• anticipated travel behavior
• trip frequency
• K-means clustering
• MNL model