Citation

Wang K, Hossain S, Nurul Habib K. Transp. Res. A Policy Pract. 2022; 166: 62-85.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.tra.2022.10.004

PMID

unavailable

Abstract

The outbreak of coronavirus disease 2019 (COVID-19) spreads globally, disrupting every aspect of everyday activities. Countermeasures during the pandemic, such as remote working and learning, proliferated tele-activities worldwide during the COVID −19 pandemic. The prevalence of telecommuting could lead to new activity-travel patterns. It is in the interest of transport demand modellers to capture this developing trend of telecommuting using state-of-art travel demand forecasting techniques. This study develops a modelling framework using activity-based and agent-based microsimulation to forecast activity-travel demand considering telecommuting and the pandemic. For empirical application, the modelling framework investigates changes in travel behaviours in post-secondary students when all major post-secondary institutions in the Greater Toronto Area (GTA), Canada, decided to go virtual during the pandemic. The empirical investigation reveals that enforced telecommuting and the pandemic caused significant mobility drops and shifts in students' trip starting time patterns. While only considering the influence of telecommuting, the empirical exercise reveals noteworthy dynamics between telecommuting and the overall travel demand. Telecommuting could simultaneously reduce the need to commute but also induce discretionary travel. When telecommuting is enforced, students' overall trip rates drop by 14.2%, despite increasing trip rates for all discretionary activities except shopping/market. Moreover, the study demonstrates that it is beneficial to model at-home productive and maintenance episodes when telecommuting is prominent.

Language: en

Keywords

Activity-based models; Activity-travel pattern; Agent-based microsimulation; COVID-19; Post-secondary students; Telecommuting