Enhanced Truck Data Collection and Analysis for Emissions Modeling

Goods movement is a vital part of the national economy, with freight movement growing faster than passenger travel. The growth in freight traffic is contributing to urban congestion, resulting in hours of delay, increased shipping costs, wasted fuel, and greater emissions of greenhouse gases and criteria pollutants. The limited national data on urban goods movement are insufficient for a thorough understanding of the characteristics of the trucks operating in metropolitan areas and the complex logistical chains they serve. For instance, there are at least three distinct segments of urban freight - long haul, drayage, and pickup and delivery. It is believed that truck fleet characteristics differ between the segments, but only local registration data exist at a level of detail needed to support regional transportation plans, transportation improvement plans, and state implementation plans. The lack of data to drive model estimation results in inaccurate base year emissions inventories and limits the ability to design and implement effective policies to reduce freight-related emissions. It is critical that research consider all types of commercial vehicles, not just heavy trucks, since small vehicles and vans are estimated to account for 40% of urban truck traffic. While the majority of urban freight travel demand models apply methods similar to passenger forecasting, some agencies are using advanced methods to estimate freight activity. For example, the Chicago Metropolitan Agency for Planning has developed a meso-scale freight model and the Southern California Association of Governments has implemented a multimodal modeling framework to support freight transportation decision making. In Canada, TransLink, in partnership with Transport Canada and the British Columbia Ministry of Transport, has developed freight planning data and tools through the Applied Freight Research Initiative (AFRI) for the Metro Vancouver region. Research is needed to build on the existing state-of-the art freight estimation methods in order to improve air quality modeling and transportation planning. The objective of this research is to develop a guide for transportation practitioners on methods, procedures, and data sets needed to capture commercial vehicle activity, vehicle characteristics, and operations to assist in estimating and forecasting criteria pollutants, air toxics, and greenhouse gas emissions from goods and services movement. The guide should address a broad range of issues and needs associated with estimating and forecasting commercial vehicle activity for emission modeling which may include but not be limited to the following: (1) Recent freight and emissions modeling research that complements the current research; (2) Methods to classify various trucking segments for emissions analyses; (3) Methods to collect and evaluate truck activity data by different truck segments; (4) Methods to collect truck vehicle characteristics and truck inventory data; (5) Methods to collect and evaluate truck operational data; (6) Methods to address the data interface and any potential gaps between freight forecasting and emissions modeling.


  • English


  • Status: Proposed
  • Contract Numbers:

    Project 08-101

  • Sponsor Organizations:

    Federal Highway Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590

    American Association of State Highway & Transportation Officials

    444 North Capitol Street, NW, Suite 225
    Washington, DC  United States  20001

    National Cooperative Highway Research Program

    Transportation Research Board
    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Project Managers:

    Rogers, William

  • Start Date: 20150402
  • Expected Completion Date: 0
  • Actual Completion Date: 0
  • Source Data: RiP Project 37558

Subject/Index Terms

Filing Info

  • Accession Number: 01543421
  • Record Type: Research project
  • Source Agency: Transportation Research Board
  • Contract Numbers: Project 08-101
  • Files: TRB, RiP
  • Created Date: Nov 14 2014 1:01AM