Traffic congestion is an important aspect of quality of life, mobility and accessibility in urban areas. The economic cost of congestion is in the order of billions of dollars especially for dense urban cities. Besides the congestion which relates to the magnitude of travel time, travel time variability is also studied extensively by researchers as an additional measure for transportation network efficiency. In order to enhance the efficiency of urban traffic flow in New York City (NYC), numerous policies have been discussed, including different transportation pricing schemes. Pricing schemes – particularly variable pricing – should incorporate the severity of congestion and levels of travel time variability at different times of day and areas throughout the City. However, most of the existing discussions are based on number of trips and bridge/tunnel crossings in the City, mainly because the necessary data to calculate travel time related measures have not been extensively available. Meanwhile, wider deployment of new intelligent transportation systems (ITS) tools and the emergence of GPS devices in vehicles have been helping to create comprehensive and reliable data resources to extract the travel time patterns. For instance, NYC Taxi and Limousine Commission (TLC) mandates all registered taxis to install GPS devices and record all trips, including pickup and drop off location as well as travel distance and time information. Using this data, taxis can be utilized as probe vehicles in the network, collecting travel time information in the city 24/7. Until very recently, TLC’s taxi trip dataset were originated by yellow taxis which can legally serve anywhere in the city, but largely serve in Manhattan due to taxi drivers’ higher potential hourly income in relatively more business oriented Manhattan. Consequently, the existing studies could not provide comprehensive spatial travel time patterns for the whole City including Brooklyn, Queens, Bronx and Staten Island. In order to increase the taxi service in the City, TLC introduced boro taxis which are restricted to serve at Brooklyn, Queens (except LGA and JFK airports), Bronx, Staten Island and upper Manhattan (north of north of West 110th street and East 96th street). In this respect, the recently available boro taxi data fill the crucial gap to provide travel time data for unsufficiently covered areas in the City. This proposed study utilizes both yellow and boro taxi datasets to provide the necessary spatio-temporal congestion and travel time variability patterns, in order to aid relevant policy discussions in New York City. Main objectives of the proposed research direction is to identify spatiotemporal congestion and travel time variability, and provide powerful visual maps in order to convey facts to wider audience as well as policy makers. The proposed research direction ultimately pursues to provide classification and clustering models to extract travel time relationships between space and time. These models along with strong descriptive data visualization will help facilitate better understanding of congestion and travel time variability patterns for both public and academic scholars.