New York City Department of Transportation (NYCDOT) over the past few years has been upgrading its Intelligent Transportation Systems (ITS) infrastructure. Specifically NYCDOT has been installing Advanced Solid State Traffic Controllers (ASTC), a city wide wireless network (NYCWiN), and a sophisticated Traffic Control System (TCS) in the Traffic Management Center (TMC). Capitalizing on the deployment of these advanced technologies, NYCDOT Instituted the "Midtown in Motion" (MIM) project to enhance multimodal mobility in the Midtown Core of Manhattan, a 110 square block area or "box" from 2nd to 6th Avenues, 42nd to 57th Streets. MIM was announced by Mayor Michael R. Bloomberg on July 18, 2011.

The MIM Project utilizes "active traffic management (ATM)" and the full capabilities of the NYCDOT Intelligent Transportation System (ITS) infrastructure. The signal-timing measures applied by MIM complement other efforts by the City to improve traffic operations. As part of this project E-ZPass tag readers were installed to provide travel time data, and microwave sensors were deployed to provide flow/occupancy, both in real time. The ATM is based on a two level control strategy to improve mobility using both travel time and flow/occupancy data. The real time data is being archived by NYCDOT and serves as a large and rich data warehouse.

This supplements other efforts by NYCDOT of building a data warehouse of routine traffic data (counts, volumes, speeds, etc) collected as part of DOT and other agency projects. Also, NYCDOT Division of Planning and Sustainability (P&S) has developed a large scale model of Manhattan as a macro/meso/micro level called the "Manhattan Traffic Model" (MTM). In addition the P&S division has an agreement with the Taxi and Limousine Commission (TLC) to have access to GPS trip information (start/end) of all yellow medallion taxi trips (metered trips) in New York City.

The availability of the MIM, MTM, and the taxi GPS data base provide an excellent opportunity to perform data mining/analysis for investigating trends and constructing metrics. NYCDOT has a cooperative agreement with NYU-Poly to provide the data. Professor Emeritus McShane will be involved in working with NYCDOT on the adaptive control/learning (MIM) and directing efforts that make extensive use of the database. Professor Falcocchio will direct an effort at NYU-Poly to investigate how to develop metrics and performance measures from the available database. Several PhD students at NYU-Poly are already involved in the beginnings of this initiative. Also, NYCDOT will provide reviews and serve in a guidance role as part on its ongoing services.