My research interest includes developing appropriate planning methodology and policy analysis tools (mathematical models) that can give realistic predictions of travel demands in the context of an emerging mobility landscape. I believe that the most essential pre-requisite for such advanced transport modelling is detailed and accurate input data. If we mis contextualize the data, then the model outputs will be wrong and the resulting policy decisions will be faulty or sub-optimal at best. As such, in my PhD thesis, I have focused on developing fusion methods to meaningfully combine travel data from multiple sources, because the traditional data sources alone cannot provide the detailed input required for accurate behaviour modelling and demand analysis in the rapidly evolving mobility context.
What has motivated your interests and journey? How do you hope to make a difference?
The mobility landscape is currently experiencing unprecedented changes. New technologies (e.g., connected and autonomous vehicles, shared mobility services), renewed focus of equity and sustainability for urban transport, and major disruptions like the ongoing global pandemic are affecting the fundamental way we work, move, and think. Traditional data and demand models are unable to accommodate the resulting changes and increased complexities of our activity-travel behaviour. This has motivated me to develop next-generation models that can realistically predict our activity-travel decisions in a wide range of future scenarios. I hope that my research outputs will assist in the evidence-based planning of emerging cities, thereby contributing to the economic development, public safety, and social equity within the urban areas.
What’s the latest project you have been working on that you would like to share with the SofC audiences?
My latest project investigates how the COVID-19 pandemic is affecting bicycle sharing demand in Toronto. Compared to riding transit and carpooling, bicycle sharing is a more efficient and safer shared travel option to maintain social distancing. In the project, I am using historical ridership data of Bike Share Toronto to analyze (1) how the spatial and temporal patterns of bikeshare trips compare before and during the pandemic, and (2) what are the key socio-demographic, land use and built environment, and weather factors associated with changed bike share ridership during the pandemic. The findings of the project will be useful for making informed policy recommendations about the locations of new stations and the expansion of the cycling network to ensure transport equity across the city.
As a student, researcher and or activist, what have you learned from the COVID-19 pandemic and its global impact? How do you envision post-pandemic recovery? What do you hope for?
The COVID-19 pandemic has changed well-established mobility patterns and travel demand. On one hand, people are moving less due to policies like work-from-home, online learning, and e-shopping. On the other hand, the need for social distancing has increased the use of private modes and drastically decreased transit ridership. In the post-pandemic era, we will continue to see this complex effect unfold further. The increased dependence on the automobile, the reduced demand for transit, and the increased number of delivery trips to our homes might increase the overall carbon footprint of the transportation system. I hope proper policy decisions are implemented to tackle this negative effect while promoting the growth of sustainable alternatives of personal automobiles in the form of efficient and competitive transit services, walkable streets, and well-connected cycling networks.
Please share with us your experiences at the SofC. How do you think being a member of the SofC Urban Leadership Fellowship and Academy Program has contributed to your scholarship and added to your experience as a student?
My experience as a SofC Fellow has been overwhelmingly positive, engaging, and impactful. The program gave me a unique opportunity to connect with students, mentors, and professionals from diverse backgrounds. Through my interaction with them, I have learned more about smart and sustainable cities and how to achieve the vision of urban sustainability through active community engagement. The suggestions of my peer mentor have allowed me to articulate my research findings better. Moreover, I had the opportunity to present my project at an interdisciplinary academic platform which has been a unique learning experience for me.
Any final words or message?
I want to thank Professor Marieme Lo for her excellent leadership and mentorship throughout the program. She gave us full creative licenses to formulate our individual projects while giving us constructive feedback and suggestion to keep our deliverables impactful and time bound. I am truly grateful to her and the entire team for providing extensive support, right connections, and meaningful interactions even in the virtual environment during the pandemic. Such exceptional support and motivation have empowered me to envision an impactful project and successfully complete it within the short time frame.
Sanjana Hossain is a Ph.D. candidate in Civil & Mineral Engineering at the University of Toronto. Her research interests include the development of data fusion methods for travel demand modelling, travel survey methods, and travel behaviour analysis. She is also an expert in econometric modelling and transportation policy analysis.