Emerging technologies such as automated vehicles, advanced data analytics and machine learning, and on-demand ride services will not only fundamentally alter the transportation landscape but will provide new data that can be used for transportation planning and analysis. This project is examining the properties of these new data and identifying potential applications. Phase I developed a preliminary framework for integrating emerging and conventional data from diverse sources. Using the Seattle SR 99 Tunnel Tolling Project as a case study, Phase II began to demonstrate the value of emerging big data (more specifically, app-based data) and their fusion with data from other, conventional sources in evaluating a project’s impact on transportation system performance and in answering critical and time-sensitive planning and policy-related questions. This continuation of Phase II will focus on investigating other potential future data sources, such as transportation network companies, insurance providers, and automakers, and on sharing methodologies created for data processing, origin/destination estimation, and validation. The researchers will make all work open source in order to help state, regional, and local agencies better coordinate among agencies and with data providers.
Principal Investigators:
Jeff Ban, Civil and Environmental Engineering, UW
Cynthia Chen, Civil and Environmental Engineering, UW
Sponsor: WSDOT
WSDOT Technical Monitor: Natarajan Janarthanan
WSDOT Project Manager: Doug Brodin
Scheduled completion: December 2023