Feasibility Study for Freight Data Collection

Welcome to the website of the Feasibility Study for Freight Data Collection project funded by the New York Metropolitan Transportation Council.

Executive Summary

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 proposed 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 will review relevant publications from NYMTC and will 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. Once an agreement is reached the team will conduct a quantitative estimation of deliveries by ZIP code in the NYMTC area.

·    Definition of data collection framework. The team will 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 will 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 will be built upon the project team’s extensive knowledge about the characteristics of the region’s freight transportation system. The team will 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 will provide estimates of data collection costs for specific approaches, and will propose a comprehensive data collection framework. The main objective here is to recommend the most cost-effective data collection procedure to NYMTC.

This research project is being conducted by a team from the Rensselaer Polytechnic Institute. The Principal Investigator is Professor José Holguín-Veras and the Co-Principal Investigators is Professors Jeff Ban (Rensselaer).  Research assistants are Miguel Jaller and Lisa Destro.


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