Statewide Mobility Services Program Strategic Procurement Planning

The current Statewide Active Transportation Demand Management (ATDM) program is nearing the end of its contract period. This assignment will assist NYSDOT in setting a strategic direction and executing a procurement strategy for a new Statewide Mobility Services Program, building on the strengths of the evolving ATDM Program while leveraging the opportunities now available in the private marketplace.

Utilizing Social Media Data for Estimating Transit Performance Metrics in a Pre- and Post-COVID-19 World

This perception of transit can be captured through the sentiment of posts made by users on social media. Performance metrics based on user perception can provide the service provider a customer-facing view of their service and help enhance their service and address the user concerns, especially from a public health standpoint in a post-COVID lockdown world, appropriately.

A Trusted Data Platform for Transportation Data Sharing

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.

Automated Truck Lanes in Urban Area for Through and Cross Border Traffic

This research project will investigate the design and operations of dedicated lanes for fully automated trucks, the suitability of existing infrastructure to accommodate these novel technologies, and the potential economic ramifications on the surrounding region. The project will use the I-10 Freeway in El Paso, Texas, from the New Mexico border in the west to milepost 55 in the east, as the testbed.

Integrative Vehicle-Traffic Control in Connected/Automated Cities

In this project, the research team built on work done in a Year 1 C2SMART project, in which a decomposition method was developed to address traffic signal optimization. This project aims to develop methods to deal with mixed traffic flow and develop CAV-based signal coordination methods with multiple signalized intersections

Design of Resilient Smart Highway Systems with Data-Driven Monitoring from Networked Cameras

This project aims to develop a systematic way to design smart highway systems with networked video monitoring and control resiliency against environment disruptions and sensor failures. The research team will investigate deep learning methods for extracting fine-grained local categorical traffic information from surveillance videos and novel graph neural network methods to correlate and propagate the local information through the highway network for global states estimation, such as vehicle tracking and reidentification or traffic prediction in an unobserved area.