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The New York City (NYC) metropolitan region is home to close to 20 million residents, more than 600,000 business establishments, more than 1.3 million registered trucks, and more than 8.8 million employees. Every year, more than 80 million trucks cross the toll facilities administered by the various transportation agencies (New York Metropolitan Transportation Council, 2004). This traffic translates into a total amount of cargo of about 200 million tons. The bulk of these goods accounts for 79% of the region’s goods while the national average is 44%. As freight transportation is becoming more critical to the region, NYMTC has recognized the need to take proactive steps to enhance the overall efficiency of the freight transportation system, as a way to enhance the region and the Nation’s competitiveness.

To consider freight issues systematically and quantitatively, effective and efficient freight data collection plays a crucial role, especially for (a) improvement strategies evaluation for freight mobility, (b) system performance forecasting, (c) mitigating the impacts of truck traffic, (d) determining the impacts on air quality, and (e) improving the safety and security performance of the road network. This project proposes to establish an efficient and cost-effective freight data collection framework for NYMTC to address data needs in freight modeling. The framework is part of a comprehensive process that is comprised of a number of major components:

  • Freight data needs and data sources. This task is based on the project team’s extensive research experience on data collection on freight transportation and traffic/transportation systems. The team shall review relevant publications from NYMTC and shall update the freight modeling report authored by the PI to reflect the most recent development in freight data collection and modeling.
  • Estimation of total deliveries by ZIP code. The project team has trip generation data and several other datasets that will benefit this project. The team would meet with NYMTC staff to discuss how to take advantage of the data. The team shall conduct a quantitative estimation of deliveries by ZIP code in the NYMTC area.
  • Definition of data collection framework. The team shall conduct an extensive review of the state-of-the-art freight data collection methods, and their pros and cons. Based on the review, the team shall propose the most cost-effective ways to combine various methods that can ensure NYMTC’s stated objectives for the regional freight model development.
  • Investigation of freight system characteristics of the NYMTC region. This shall be built upon the project team’s extensive knowledge about the characteristics of the region’s freight transportation system. The team shall identify major freight flows in the area, re-estimate trip generation models, analyze ZIP code employment data and estimate total deliveries of ZIP code, and geocode large freight traffic generators.
  • Estimation of data collection cost. Based on the identified data needs and data sources, the regional freight traffic characteristics, and review of current data collection methods, the team shall provide estimates of data collection costs for specific approaches, and shall propose a comprehensive data collection framework. The main objective here is to recommend the most cost-effective data collection procedure to NYMTC.

The proposed study shall be built upon the project team’s extensive research activities on freight modeling, hand-on experiences on freight data collection and analysis, and knowledge of the characteristics of the region’s freight transportation systems. This project will directly benefit from the considerable expertise of Professor Holguín-Veras, who has been in charge of: five major freight origin-destination studies in different countries, and dozens of special purpose freight data collection efforts. His expertise on this important subject has led to his involvement as an advisor in freight data collection and freight modeling to the Bureau of Transportation Statistics and the U.S. Census Bureau, Transport Canada, the Ministry of Transportation in Colombia, the Ministry of Transportation and Land Use in France, among others. This vast experience provides him with a unique perspective on freight data collection that is bound to benefit the project and NYMTC. The project shall produce an actionable set of recommendations regarding the most efficient and cost-effective freight data collection framework to support NYMTC’s modeling objectives.