Exploring the spatiotemporal factors affecting bicycle-sharing demand during the COVID-19 pandemic.

This study investigates the roles of the socio-economic, land use, built environment, and weather factors in shaping up the demand for bicycle-sharing trips during the COVID-19 pandemic in Toronto. It uses "Bike Share Toronto" ridership data of 2019 and 2020 and a two-stage methodology. First, multilevel modelling is used to analyze how the factors affect monthly station-level trip generation during the pandemic compared to pre-pandemic period. Then, a geographically weighted regression analysis is performed to better understand how the relationships vary by communities and regions. The study results indicate that the demand of the service for commuting decreased, and the demand for recreational and maintenance trips increased significantly during the pandemic. In addition, higher-income neighborhoods are found to generate fewer weekday trips, whereas neighbourhoods with more immigrants experienced an increase in bike-share ridership during the pandemic. Moreover, the pandemic trip generation rates are more sensitive to the availability of bicycle facilities within station buffers than pre-pandemic rates. The results also suggest significant spatial heterogeneity in terms of the level of influence of the explanatory factors on the demand for bicycle-sharing during the pandemic. Based on the findings, some neighbourhood-specific policy recommendations are made, which inform decisions regarding the locations and capacity of new stations and the management of existing stations so that equity concerns about the usage of the system are adequately accounted for.

Exploring the impacts of the COVID-19 pandemic on modality profiles for non-mandatory trips in the Greater Toronto Area.

The ongoing COVID-19 pandemic has drastically altered daily life in cities across the world. To slow the spread of COVID-19, many countries have introduced mobility restrictions, ordered the temporary closure of businesses, and encouraged social distancing. These policies have directly and indirectly influenced travel behaviour, particularly modal preferences. The purpose of this paper to explore modality profiles for non-mandatory trips and analyze how they have changed in response to the pandemic and pandemic-related public health policies. The data used for this study were collected from web-based surveys conducted in the Greater Toronto Area. Modality profiles were identified through the application of latent class cluster analysis, with six modality profiles being identified for both the pre-pandemic and pandemic periods. The results indicate that the importance of public transit has declined during the pandemic, while the roles of private vehicles and active modes have become more prominent. However, individuals' changes in modal preferences vary based on their pre-pandemic modality profile. In particular, it appears that pre-pandemic transit users with access to a private vehicle have substituted public transit for travel by private vehicle, while those without private vehicle access are continuing to use public transit for non-mandatory trips. Consequently, pandemic-related transportation policies should consider those who do not have access to a private vehicle and aim to help those making non-mandatory trips using transit or active modes comply with local public health guidelines while travelling. The results highlight how the changes in modal preferences that occurred due to the pandemic differ among different segments of the population.