The transportation sector is entering an era of increasingly both “big” and “proprietary” data. New technological trends are emerging that shift the most critical sources of transportation system data from roadside infrastructure to personal and vehicle-based communications. This trend has been moving data and knowledge from the public realm to the private, inhibiting public debate and decision-making. However, novel urban analytics techniques can extract information from public and semi-public data sources, providing important insights into the impacts of emerging mobility services.
The objectives of the proposed research are to generate multi-modal integrated datasets of novel urban mobility services (carshare, bikeshare, ride-hailing), to use the datasets to investigate and model the interacting demand for these services (as substitutes and complements), and to engage with local governments to share insights about the impacts of new mobility services.
Hassanpour, A., A. Bigazzi, and D. MacKenzie, “Equity of access to Uber’s wheelchair accessible service.” Computers, Environment and Urban Systems, Vol. 89, 2021.
Hassanpour, A., A. Bigazzi, and D. MacKenzie, “What can publicly-available API data tell us about supply and demand for new mobility services?” Transportation Research Record, Vol. 2674, No. 1, pp. 178-187, 2020.
Hassanpour, A., A. Bigazzi and D. MacKenzie, “Uber Accessibility Services in Portland, Oregon: Variability in Access and Relationships to Socio-Demographics.” American Collegiate Schools of Planning 60th Annual Conference, Online due to COVID-19, November 4-8, 2020.
Hassanpour, A., A. Bigazzi and D. MacKenzie, “Can web data be harvested to help cities understand the impacts of private bikeshare systems?”, Velo-City 2019 Conference, Dublin, Ireland, June 25-28, 2019.
Hassanpour, A. and A. Bigazzi, “Mining web data to help cities understand the impacts of Transportation Network Companies.” Canadian Transportation Research Forum, Vancouver, May 26-29, 2019.