This study aimed to develop a demand model for an eFFCS service in the City of Seattle, which can increase the feasibility of eFFCS by reducing the cost of relocation by optimally locating the charging stations near the areas of heavy usage and real-time control to minimize manual relocation.
Led by INTERCEP founding director Bill Raisch, this project aims to adapt an information sharing and situational awareness technology platform currently used by INTERCEP’s Metropolitan Resilience Network to support transportation data sharing and stakeholder engagement in New York City and each of the C2SMART consortium member cities. This platform is designed to help users understand their larger operating environment, identify risks in that environment, and make informed decisions during disruptions using the assembled data.
This project aims to develop new models of pedestrian mobility using WiFi probe data as a novel data source. The models will be designed to scale to any region with a similar WiFi network infrastructure. Deliverables will also include a research paper submitted to a peer-reviewed journal and a final report.
Cities like NYC and Seattle need to deal with significant growth of urban deliveries as a result of increasing e-commerce compounded by increased stay-at-home behavior due to COVID-19. We propose to develop a citywide model of truck network flows, one that relates changes to truck routes to changes in truck tours or to time-of-day congestion pricing policies.