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New York MTA Releases Granular Congestion Relief Zone Data

The dataset allows users to view the numbers of vehicles entering into the Manhattan Central Business District by date, time, and location in 10-minute increments. The dataset can further be tabulated by vehicles class.

January 31, 2025
New York MTA Releases Granular Congestion Relief Zone Data

The MTA Open Data program is managed by the Data & Analytics team, the MTA's center of excellence in the management, usage, and sharing of data. 

Photo: Marc A. Hermann

2 min to read


The New York Metropolitan Transportation Authority (MTA) released data on the volume of vehicles entering into Manhattan’s Congestion Relief Zone (CRZ), by location, time, and type of vehicle. 

The dataset, MTA Congestion Relief Zone Vehicle Entries, is available to view on the MTA’s data transparency website. 

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MTA’s Dataset

The dataset allows users to view the numbers of vehicles entering into the Manhattan Central Business District by date, time, and location in 10-minute increments. The dataset can further be tabulated by vehicles class. 

Among some top-line findings, the data offers details on how some drivers have been entering the zone before 5 a.m., to avoid the peak period toll, helping to reduce congestion through tunnels into Manhattan. The data also reveals that about 11% or 12% of vehicles stay on the excluded roadways. 

“The MTA has made public a highly detailed dataset on a complex and historic program in record time,” said MTA Deputy Chief, Policy and External Relations, Juliette Michaelson. “This dataset is the first of a series related to the congestion relief zone tolling program. We look forward to seeing what other stakeholders can do with the data, as we do with all of the nearly 150 datasets the MTA publishes.” 

MTA Open Data

The MTA Open Data program is managed by the Data & Analytics team, the MTA's center of excellence in the management, usage, and sharing of data. 

Its three main functions are to aggregate and harmonize the MTA’s many diverse data sources, to devise and automate creative analyses that uncover valuable insights in that data, and to publicly share the resulting products. 

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