Starting a project “Impact Of Ride-Sharing In New York City”

This new collaborative project with NYU C2SMART Center just received support from US Department of Transportation and Arcadis!

The project will develop a citywide data-driven transportation simulation modeling framework for probabilistic assessment of the associated mode-shift and resulting environmental, social and economic impacts of ride-sharing solutions (e.g. UberPOOL, Lyft shared etc) on urban transportation system in New York City efficiently leveraging available partial transportation data. The impacts in question include: travel time cut for passengers, reduction of traffic, gas consumption/ emissions by type (CO, NOx, PM2.5), travel time/cost savings for passengers, increased earnings for Lyft and Uber drivers, jobs for for-hire-vehicle drivers. Once developed, the new framework is readily applicable to the predictive assessment of the impacts of many other transportation pricing and policy decisions.

Starting the project METS-R: Multi-modal Energy-optimal Trip Scheduling in Real-time for Transportation Hubs

This ongoing collaborative project focuses on development and evaluation of the real-time energy-efficient autonomous vehicle solutions to serve major transportation hubs of NYC (such as JFK, LaGuardia, Penn station). Our lab’s role includes anomaly detection in transportation demand data as well as implementing dynamic ride-sharing and routing solutions for shared autonomous mobility.

The project is conducted in collaboration with Purdue university under support of US Department Of Energy.