Quick Response Freight Manual II
U.S. Department of Transportation
Federal Highway Administration
Office of Freight Management and Operations
Phone: 202-366-9210
Fax: 202-366-3302
Web site: http://ops.fhwa.dot.gov/freight
![]()
September 2007
Publication #FHWA-HOP-08-010
EDL #14396
You will need the Adobe Reader to view the PDFs on this page.
PDF Version (2.2 Mb)
Table of Contents
Acknowledgments / Notice / Quality Assurance Statement / Technical Report Documentation Page
Part A
1.0 Introduction
- 1.1 Objectives of the Quick Response Freight Manual
- 1.2 Definition of Freight Transportation
- 1.3 Organization of the Manual
2.0 Freight Demand – Controlling Factors
- 2.1 Economic Structure
- 2.2 Industry Supply Chains and Logistics
- 2.3 Freight Infrastructure/Modes
- 2.4 Freight Traffic Flows
- 2.5 Organization and Public Policy
Part B
3.0 Simple Growth Factor Methods
- 3.1 Introduction
- 3.2 Growth Factors Based on Historical Freight Trends
- 3.3 Growth Factors Based on Direct Economic Projections
4.0 Incorporating Freight into “Four-Step” Travel Forecasting
- 4.1 Introduction
- 4.2 Urban Freight and Commercial Trucks
- 4.3 State Freight Forecasting
- 4.4 Site/Facility Planning
5.0 Commodity Models
- 5.1 Introduction
- 5.2 Acquiring Commodity Tables
- 5.3 Forecasting
- 5.4 Mode Choice
- 5.5 Vehicle Conversion
- 5.6 Assignment
- 5.7 Commodity Flow Survey (CFS)
- 5.8 TRANSEARCH
- 5.9 Freight Analysis Framework (FAF)
6.0 Hybrid Approaches
- 6.1 Introduction
- 6.2 Three-Step Freight Truck Models
- 6.3 Four-Step Commodity Flow Models
- 6.4 Case Studies
- 6.5 Issues with Hybrid Approaches
7.0 Economic Activity Models
- 7.1 Modeling Framework
- 7.2 Data Requirements
- 7.3 Oregon Statewide Passenger and Freight Forecasting Model
- 7.4 Cross-Cascades Model
Part C
8.0 Model Validation
- 8.1 Introduction
- 8.2 Trip Generation Validation
- 8.3 Trip Distribution Validation
- 8.4 Mode Split Validation
- 8.5 Assignment Validation
9.0 Existing Data
- 9.1 Commodity O‑D Tables
- 9.2 Mode-Specific Freight Data
- 9.3 Employment/Industry Data
- 9.4 Performance Data
10.0 Freight Data Collection
11.0 Applications Issues
- 11.1 Introduction
- 11.2 Controlling Factors
- 11.3 Growth Factoring
- 11.4 Network and Zone Structure
- 11.5 Trip Generation
- 11.6 Trip Distribution
- 11.7 Mode Choice
- 11.8 Conversion to Vehicles
- 11.9 Assignment
- 11.10 Integration with Passenger Forecasts
12.0 Case Studies
- 12.1 Los Angeles Freight Forecasting Model
- 12.2 Portland Metro Truck Model
- 12.3 Florida State Freight Model
- 12.4 Texas State Analysis Model (SAM)
13.0 Intermodal Considerations in Freight Modeling and Forecasting
- 13.1 Introduction
- 13.2 Types of Intermodal Freight Transportation
- 13.3 Characteristics of Intermodal Freight Transportation
- 13.4 Intermodal Freight Data Sources
Appendix A. Freight Glossary
Appendix B. Commodity Classifications
- STCC2 and STCC4 Concordance
- SCTG2 to STCC2 Concordance
- SCTG2 to STCC4 Concordance as Used in the Preparation of FAF2
List of Tables
Table 3.1 Linear Growth Regression
Table 3.2 Compound Growth Regression
Table 3.3 Daily Truck-Trip Rates Used in Factoring Truck Trips
Table 3.4 Results of TH 10 Forecast Daily Trucks
Table 4.2 Average Truck Trip Lengths
Table 4.5 Indiana Freight Model Variables Used in Trip Generation
Table 4.6 Indiana Freight Model Production Equations
Table 4.7 Indiana Freight Model Attraction Equations
Table 4.8 Florida Freight Model Commodity Groups
Table 4.9 Florida Freight Model Production Equations
Table 4.10 Attraction Equations
Table 4.11 Wisconsin Freight Model Trip Production and Attraction Regression Models
Table 4.12 Florida Freight Model Productions and Attractions for Ports and Terminals
Table 4.13 Wisconsin Freight Model Freight Outbound Special Generators and Tonnages
Table 4.14 Wisconsin Freight Model Freight Inbound Special Generators and Tonnages
Table 4.15 Indiana Freight Model Trip Distribution Model Coefficients
Table 4.16 Florida Freight Model Trip Distribution Results
Table 4.17 Wisconsin Freight Model Average Trip Lengths by Commodity
Table 4.18 Indiana Freight Model Commodity Density Values for Railcars and Trucks
Table 4.19 Florida Freight Model Tonnage to Truck Conversion Factors
Table 4.20 Wisconsin Freight Model Truck Payload Factors by Commodity and Distance Class
Table 4.21 Florida Freight Model State Line Volume/Count Ratio
Table 4.22 Florida Freight Model Major Statewide Screenline Volume/Count Ratio
Table 4.23 Wisconsin Freight Model HPMS versus Model Truck VMT by Functional Class
Table 4.24 Truck Trip Generation Rates for Air Cargo Operations
Table 5.1 Georgia Freight Model Freight Analysis Framework Annual Percentage Rate of Growth
Table 5.4 Georgia Freight Model TRANSEARCH Tonnage Mode Split
Table 5.5 Tennessee Freight Model Estimated Payload for Commodity Groups
Table 5.6 Virginia Freight Model Truck 1 Load Factors
Table 5.7 Tennessee Freight Model Assignment Validation
Table 7.1 Dynamic Interactions in Integrated Economic Activity Modeling Framework
Table 7.2 Data Inputs for Oregon Statewide Model
Table 8.1 California DMV Vehicle Types by Commercial Vehicle Category
Table 8.2 Business and Personal Services Vehicles in California Cities
Table 8.3 Fleet Sizes across Select Cities in California
Table 8.4 Fleet Sizes across Select Cities in New York State
Table 12.1 SAM Commodity Groups
List of Figures
Figure 4.1 “Four-Step” Process of Freight Forecasting
Figure 4.2 Goods and Modal Characteristics
Figure 5.1 Tennessee Freight Model TRANSEARCH Database Sample Frame
Figure 5.2 Tennessee Freight Model Regions and District Geography
Figure 5.3 Virginia Freight Model Commodity Flow Forecast Methodology
Figure 7.1 Steps Involved in Economic Activity Modeling Framework
Figure 7.2 Modules in the Oregon Statewide Model
Figure 7.3 Dynamic Interactions in an Integrated Land Use-Transportation System
Figure 7.4 The Cross-Cascades Corridor Spatial Input-Output Approach
Figure 7.5 Trip Generation and Distribution in the Cross-Cascade Model
Figure 8.1 Trip Length Frequency Distribution
Figure 8.2 Coincidence Ratio for Trip Distribution
Figure 8.3 Maximum Desirable Deviation in Total Screenline Volumes
Figure 8.4 Assigned versus Observed Average Daily Traffic Volumes
Figure 12.1 LAMTA Model Freight Forecasting Process
Figure 12.2 Highway Network for Florida Intermodal Statewide Highway Freight Model
Next Section