ABSTRACT
The COVID-19 pandemic had a significant impact on travel mode choices in cities across the world. Driven by perceptions of risk and the fear of infection, the pandemic resulted in an increased preference for private vehicles and active modes and a reduced preference for public transit and ride-sourcing. As travel behavior and modal preferences evolve, a key question is whether the pandemic will result in long-term changes to travel mode choices. This study uses data from a web-based survey to examine the factors influencing mode choices for non-commuting trips in the post-pandemic era. Specifically, it uses stated preference data to develop a random parameter mixed logit model, which is used to compare the elasticity of key variables across different income and age groups. The results of the study highlight the influence of sociodemographic attributes and pre-pandemic travel habits on anticipated post-pandemic mode choices. Additionally, the results suggest that frequent users of private vehicles, public transit, and active modes are likely to continue to use these modes post-pandemic. Furthermore, the results highlight the potential for the perception of shared modes to influence post-pandemic mode choice decisions. The results of the study offer insights into policy measures that could be applied to address the increased use of private vehicles and reduced use of transit during the pandemic, while also emphasizing the need to ensure that certain segments of the population can maintain a sufficient level of mobility and access to transport.
ABSTRACT
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.
ABSTRACT
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.
ABSTRACT
The COVID-19 virus has unimaginably disrupted the transit system and its overall functions. Users' vigilant safety concerns posed by the pandemic and the consequent transit avoidance behaviour for a prolonged period could have lasting impacts on their transit preferences, leaving transit agencies to search for effective post-pandemic transit resilience policies. This study examines potential post-pandemic interventions and pandemic-induced psychological attributes impacting the future transit choice behaviour of non-transit users of the pandemic. It utilised data from a transit demand and choice adaptation survey in the Greater Toronto Area, Canada. A two-stage model was formulated to jointly capture the pre-pandemic transit usage choices of those who did not make transit trips during the pandemic and the respective post-pandemic transit choices for these user groups. The models depicted that the post-pandemic transit choices were inversely affected by one's pandemic concerns. In contrast, the choices were positively influenced by respondents' views on post-pandemic transit usage and keeping the adopted safety policies in place. Regarding the conventional level of service attributes, paid park and ride facilities enhanced the probability of post-pandemic transit choice almost by 15% for occasional users. In comparison, the changes due to reliable service ranged from 10 to 11% for pre-pandemic users. Analogous propensity was seen for fare schemes offering free transfers between cross borders and 25% or more off-peak discounts on base fares. Moreover, more direct transit routes and increased parking costs by vehicular modes post the pandemic encourage travellers to retake transit.
ABSTRACT
COVID-19 had an unprecedented impact on transit demand and usage. Stiff and vigilant hygiene safety requirements changed travellers' mode choice preferences during the COVID-19 pandemic. Specifically, transit modal share is radically impacted. Therefore, quantitative measurements on transit demand impact are urgently needed to facilitate evidence-based policy responses to COVID-19. Thus, we collected 1000 random samples through a web-based survey in the Greater Toronto Area (GTA), Canada, on traveler's modal choices behavior during the COIVD-19 pandemic. The paper presents an analysis with this firsthand dataset to understand transit users' behavioral adaptation resulting from the spreading of COVID-19 in 2020. We found that the transit frequency dropped by 21% to 71% for various socioeconomic groups in the GTA during the pandemic. The transit modal share dipped for all trip purposes. For private vehicle owners, around 70% of transit users switched to their private vehicles. More than 60% of those without cars switched to active transport for all travel purposes. Also, ride-hailing services are the second most popular substitution of transit for them. More than 80% of the respondents agreed with all transit safety policies, such as mandatory face-covering listed in the survey. Moreover, a similar proportion of the respondents agreed to return to public transit in the future. Multinomial, nested, and mixed logit models are estimated to capture relationships between modal choices and various factors. We found that the daily number of new COVID-19 cases impacts the choice of transit negatively. However, vaccine availability and mandatory face-covering onboard positively affect travellers' choices of riding transit during the pandemic.
ABSTRACT
Social distancing strategies and strict hygiene adherence during the pandemic have added an extra dimension to the safety requirements of transit usage. Thus, travelers? altered safety perceptions, which can affect transit usage, need to be assessed for effective policy decisions for the post-pandemic period. This study examined the interaction between in-vehicle safety perception and transit usage using an integrated approach by jointly modeling them, considering the fear of virus infection. A multivariate ordered probit model was developed for the investigation using a dataset collected through a web-based travel survey conducted in the Greater Toronto Area, Canada. The results reveal that, along with socioeconomic attributes, many pandemic-related variables and latent attitudinal factors affect the propensity to use transit. It is observed that those having a better safety perception of the bus are more inclined to use transit more frequently than others. Apart from safety perception, those who were more cautious, over the age of 34, and shifted to working from home during the pandemic had an adverse propensity to use transit. However, a higher propensity toward transit usage was observed for pre-pandemic transit users and for those who had a higher level of satisfaction with transit attributes during the pandemic. A similar tendency was also observed for fully vaccinated residents.
ABSTRACT
The COVID-19 lockdown provided many individuals an opportunity to explore changes in their daily routines, particularly when considered in combination with an ever-changing Information and Communication Technology (ICT) landscape. These new routines and alternative activities have the potential to be continued in the post-COVID era. Transportation planners must understand how routines vary to effectively estimate activity-travel scheduling. The purpose of this study is to determine the influence of the COVID-19 pandemic lockdown on activity-travel behavior and the adoption of ICT-based alternative options. A special emphasis is placed on predicting the long-term effects of this disturbance on activity-travel scheduling. This study examines the changes in the frequency and mode of completing five of the most repetitious tasks in the daily schedule (working, grocery and non-grocery shopping, preparing/eating meals, and visiting family/friends) during the lockdown and immediately after reopening. We find an increased preference for home meal preparation over online ordering and a reluctance to engage in in-person shopping until a substantial proportion of the population has acquired a vaccination against the virus. Respondents prefer to work from home if they have adequate access to home office materials (e.g., desk, chair, computer monitor). Individuals with children must also consider suitable childcare before considering a return to work.
ABSTRACT
The spread of the novel coronavirus disease-2019 (COVID-19) since early in 2020 has affected every aspect of daily life, including urban passenger travel patterns. Lockdowns to control the spread of COVID-19 created unprecedented travel demand contexts that have never been seen in modern history. So, it is essential to benchmark trends of travel behaviour, especially people's daily travel patterns that are necessary to develop a comprehensive understanding of the impacts of COVID-19. A multi-cycle benchmarking household travel study: the COVid-19 influenced Households' Interrupted Travel Schedules (COVHITS) Survey was implemented in the Greater Toronto Area with a random sample of over 4000 households. The results indicated a stark alteration in people's daily activity-travel patterns due to COVID-19. The pandemic caused a substantial decline in mobility in the study area. The average weekday household trip rate dropped from 5.2 to 2.0 trips. Transit modal shares suffered severely during the paramedic, while private car dependency was enhanced. Overall, transit modal share dropped from 17.3% to 8.1% in the study area, while the modal share of private cars increased from 70.8% to 74.1%. Factors such as having to work from home, ownership of private cars, and household incomes influenced mobility levels of the people in the study area during the pandemic. While overlooked, travel demand analysis can reveal effective strategies to curb the spread of such contagious diseases. An econometric model and analysis of sample data reveal several potential strategies. These include: (1) working/learning from home should be implemented until the end of the pandemic; (2) transit agencies should provide as much transit frequency as possible (particularly for bus routes) during peak hours to avoid crowding inside transit vehicles and project a positive image of public transit; and (3) strict restrictions should be implemented in regions with lower confirmed COVID-19 cases, as they became attractive destinations during the pandemic.
ABSTRACT
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.