Web data extraction and mining to help cities understand the impacts of new mobility services

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.