Freight and Land Use Travel Demand Evaluation: Final Report

Appendix C: Freight/Land Use Travel Demand Evaluation Literature Review
Section 3: Literature Scan

The literature scan researched foundational resources and supplementary material to assess the state of practice in research and development/applications for freight demand evaluation using information produced since the QRFM was published. The literature scan will guide the development of detailed discussions with key stakeholders and aid in identifying user needs.

Much information exists on current gaps; however, not much is available in terms of how to close those gaps. Additionally, in an environment where new techniques are ever-evolving, the question becomes, "What is the best way to document the state of the practice?"

There is a continuing cycle of research and synthesis (see Table 1), which is described in more detail below. The QRFM was produced in 2007 as the results of prior research were incorporated into similar synthesis documents. Additionally, NCHRP and second Strategic Highway Research Program (SHRP2) Capacity 20 (C20) program efforts have aimed to develop the next generation of research needs. Both SHRP2 initiatives and FTG analyses (summarized in NCFRP Report 37) reflect key advances in the freight planning process.

Table 1: Research Cycle and Foundational Resources

The Research/Synthesis Cycle
QRFM published as landmark document (2007)
Syntheses of information identified current status/need (2008-2010)
SHRP2 C20 organized next wave of research (2012-2016)
SHRP2 studies are now being completed (2016-2017) and will be ready for "synthesis" in products like QRFM update
Foundational Resources
ITE Trip Generation Handbook, 3rd Edition
NCFRP Report 24: Smart Growth and Urban Goods Movement
NCFRP Report 25: Freight Data Sharing Guidebook
NCFRP Report 26: Subnational Commodity Flow Data
NCFRP Report 37: Using Commodity Flow Survey Microdata and Other Establishment Data to Estimate the Generation of Freight, Freight Trips, and Service Trips: Guidebook
NCHRP Report 739: Freight Trip Generation and Land Use
NCHRP Report 750: Strategic Issues Facing Transportation, Volume 1: Scenario Planning for Freight Transportation Infrastructure Investment
NCHRP Project 08-96: Integration of Freight Considerations into Smart Growth Design

QRFM (2007)

Model Types

The QRFM describes several types of models:

• Four-Step Travel Forecasting: Addresses how the traditional "four-step" transportation forecasting process (trip generation, trip distribution, mode split, and network assignment) is used to forecast goods movement in traditional urban transportation planning models, in State transportation planning models, and in site planning.
• Commodity Modeling: Discusses how commodity flow surveys can be used in freight forecasting in place of traditional trip tables.
• Economic Activity Modeling: Discusses how freight forecasting can be included within more comprehensive economic/land use/ecological models.
• Hybrid Modeling: Discusses how different freight models can be combined with multimodal commodity methods to better understand goods movement flows.

Model Application

QRFM Chapters 8-11 focus on application-ready updates from recent research reports including:

• Model validation: Considers how to calibrate freight models and forecasts, and how to validate models.
• Existing data sources: Discusses the availability of data, the content of that data, and the advantages and disadvantages of using existing freight data.
• Data collection methods: Discusses why existing data may be insufficient and why new data sources may be required to support freight modeling.
• Application issues: Discusses why freight forecasts are needed, their attributes, and how forecasts are used in the transportation planning process.

Case Studies

This section of the QRFM covers how methodological and data issues were addressed at various government levels and in different regions, including by States and multistate partnerships, large and small urban areas, and individual sites such as ports, airports, industrial parks, and intermodal railroad terminals. Models discussed include:

• Southern California Association of Governments heavy-duty truck model (Los Angeles, California)
• Freight Action Strategy truck forecasting model (Seattle, Washington)
• San Joaquin Valley truck model (Central California)

NCHRP Syntheses

TRB released a series of relevant summary documents after publication of the QRFM. These documents generally supported both the current state of the practice as reflected in QRFM and helped define a framework for the subsequent wave of travel demand-related research advanced by SHRP2. Relevant summary NCHRP documents include the following:

• NCHRP Synthesis 384 (2008), Forecasting Metropolitan and Commercial Freight Travel
• NCHRP Synthesis 406 (2010), Advance Practices in Travel Forecasting
• NCHRP Synthesis 410 (2010), Freight Transportation Surveys

These reports contributed to the base of freight travel demand literature, but have not been explicitly included in this literature review as their contents are reflected and updated in subsequent NCHRP and NCFRP reports developed after 2010.

SHRP and SHRP2 Initiatives

In the 1987 highway bill, U.S. Congress authorized the original SHRP as a five-year, $150-million research program. At that time, the U.S. transportation and public works system was in the public spotlight due to its state of deterioration. SHRP was proposed as a highway research program that would concentrate efforts on a short list of high-value activities. These fell under four major technical research areas, including:

• Improved performance of asphalt materials
• Improved concrete and the protection of reinforced concrete structures
• Efficient methods of highway maintenance, including control of snow and ice
• Long-term durability of pavements

SHRP2 was authorized in 2005. Its focus was to find strategic solutions to three national transportation challenges:

• Improving highway safety.
• Reducing congestion
• Improving methods for renewing roads and bridges

There has been a recommendation for a future SHRP comprised of several primary research program areas:

• Accelerating the renewal of America’s highways
• Making significant improvement in highway safety
• Providing a highway system with reliable travel times

SHRP2 C20 - Freight Demand Modeling and Data Improvement (2013)

The SHRP2 C20 initiative assesses the state of the practice of freight demand modeling and freight data as related to highway capacity planning and programming. While passenger travel modeling is moving toward more activity-based modeling techniques, freight demand models have remained relatively unchanged. However, new information technology advances have greatly improved how transportation planners access freight data.

Land Use and Demographic Considerations with QRFM Elements

Table 2 below identifies land use and demographic considerations with QRFM elements.

Element B: Establish techniques and standard practices to review and evaluate freight forecasts. This element directly addresses the objective of improving and expanding upon the current state of the practice.

Elements D, E, H, I, and J address topics beyond the QRFM:

• Element D: Develop methods that predict mode shift and highway capacity implications of various what-if scenarios (scenario planning).
• Element E: Develop a range of freight forecasting methods and tools that address decisionmaking needs that can be applied at all levels (national, regional, State, metropolitan planning organization (MPO), municipal (geographic scales).
• Element H: Determine how economic, demographic, and other factors and conditions drive freight patterns and characteristics. Document economic and demographic changes related to freight choices (economic/demographic trends).
• Element I: Develop freight data sources for application at subregional levels (geographic scales).
• Element J: Develop and standardize a portfolio of core freight data sources and data sets that supports planning, programming, and project prioritization (data sources).

Table 2: Sample Research Initiatives from SHRP2
Source: SHRP2

Freight Decisionmaking Needs and Gaps

SHRP2 has also advanced research on behavior/agent-based supply chain modeling that will allow State DOTs and MPOs to better understand freight travel behavior as it relates to industry decisionmaking processes used for logistics and freight movement.

Table 3 highlights freight decisionmaking needs, gaps between those needs and the current modeling and data practices, and data and modeling requirements to meet those needs. Essentially, it is a comprehensive list of knowledge gaps.

Table 3: Freight Decision-Making Needs and Gaps from SHRP2
Source: SHRP2

Table ES-2. Freight Decision-Making Needs and Gaps

Decision-Making Needs	Gaps Between Needs and Current Practices	Data or Modeling Requirements to Close Gaps
Standardized data sources with common definitions	Various data sources collected through different programs result in extensive inconsistencies.	Homogeneous data for ease of incorporation into freight models and for consistency of freight models in different regions. Reduction in data manipulation to improve accuracy.
Statistical sampling of truck shipments	Detailed knowledge of truck movements in local areas. Understanding of current truck activity by different industry segments (long-haul, local, drayage).	An ongoing standard data-collection program to gather local truck movements. Compilation of truck data to a level comparable to rail industry data (i.e., Carload Waybill Sample).
Standardized analytic tools and applications	Range of various tools that require unique data sets.	Consistency in modeling approaches and data needs for similar geographic scales.
Inclusion of behavior-based elements in freight models	Current practices use truck movements and commodity flows, but should be based on the behaviors, economic principles, and business practices that dictate the movement of freight. Current modeling tools do not accurately reflect real-world supply chains and logistics practices.	Determination of the influencing behavioral factors that affect freight movement and ongoing data collection to inform models. Behavior-based freight modeling tools to take advantage of newly collected data sets for various geographic analyses. Incorporation of intermodal transfers, consolidation and distribution practices and other shipper and carrier practices in modeling tools.
Data development to understand the nature, volume, and trends of intermodal transfers	Public sector access to intermodal transfer data of containers, bulk material, and roll-on-roll-off cargo is lacking for most transfer facilities other than those of large ports and rail yards.	Data sets developed through collaboration with the private sector to inform the planning practice knowledge base and models on intermodal transfers. Protocols to collect data on a regular basis.
Industry-level freight data development at a subregional level and within urban areas	Freight data are generally not industry-specific, which translates into forecasts that are not sensitive to the unique industry trends that are critical to regions that rely heavily on specific industries.	Industry-level forecasts that are sensitive to the unique factors of different industries. Tools and data at a disaggregated level (local) that can be aggregated for larger geographic analyses. Tools and models to take advantage of the new data sets.
Incorporation of local land use policies and controls for better local forecasting accuracy	Current freight data and models lack local detail related to the generation of freight activity, which hampers local efforts to effectively plan for the last mile.	Enhanced understanding of land use decisions and their implications on freight activity. Resources for local organizations to incorporate land use considerations into freight planning data and models.
Development of a correlation between freight activity and various economic influences and macroeconomic trends	Freight models are typically based on population-, employment-, and industry-level productivity forecasts, with no consideration for the impacts of other economic factors.	Enhanced models that incorporate a wide array of economic factors in forecasting freight demand.
Better accuracy of freight forecasts	Freight models rarely (if ever) are reviewed to check the accuracy of their forecasts, calling into question their reliability and accuracy.	A systemic approach for freight model and data owners to review and evaluate forecasts (every 3 to 5 years) and adjust models and data methods accordingly.
Development of a process to routinely generate new data sources and problem-solving methods	The improvement of freight planning nationally depends on continuing innovation and steady progress in the development of models, analytic tools, and knowledge acquisition.	A value-adding and sustainable process to generate new and innovative ideas. Acknowledgment of failed practices that can contribute to the knowledge base of practitioners.
Use of ITS resources to generate data for freight modeling	Technologies that can be used to collect freight data have not been used to their potential. Data can provide a wealth of information related to current conditions and diversions as a result of traffic incidents.	An understanding of the information needed by the modeling community and the standard to which it can be used. An accessible data bank for freight modeling developed with the cooperation of GPS device providers, ITS infrastructure owners, and other data providers.
Development of a universal, multimodal, network-based model for various geographic scales	The fragmentation of modeling techniques and data means that practitioners typically must develop or improvise data and models for their own applications. Agencies with fewer resources are not able to adequately analyze freight movements. Some freight transfer modes are analyzed more than others because they have more data available for analysis.	An open-source data bank and universal freight monitoring tool is the ultimate goal. A level field among different modes of freight transportation in terms of quantity and accuracy of data and complexity of modeling tools.
Development of benefit-cost analysis tools that go beyond traditional financial measures	Analysis of the benefits of project-based scenarios lacks the precision required for those decisions, including direct and indirect impacts, costs, and benefits.	Tools that incorporate a comprehensive analysis of the factors associated with infrastructure development, expansion, and enhancement specifically related to freight.
Development of funding assessments resulting from freight forecasts	Transportation funding scenarios and what-if analyses are limited in their ability to forecast revenues associated with freight movement.	Estimated costs and potential funding sources that can be justified based on credible freight forecasts.
Creation of tools to support the infrastructure design process	Infrastructure design, unless specific to freight, rarely focuses efforts on how best to accommodate freight movements.	Incorporation of freight forecasts into infrastructure design related to vehicle size and weight and future freight activity (i.e., tonnage) by mode.
Development of knowledge and skills among the freight planning community as a foundation for improved analysis	The freight planning community is relatively small and knowledge transfer is challenging. Talented innovators who can lead new approaches to freight transportation planning are pursuing careers in other industries.	A comprehensive knowledge base for planning professionals that includes the wide range of subject areas related to freight transportation. Greater recognition or formal standing of freight planning as a profession with an associated body of knowledge.

SHRP2 C20 Subsequent Studies

The SHRP2 Implementation Assistance Program has funded pilot projects in 11 States to develop state-of-the-art tools for freight modeling and data analysis. This includes development of behavior/agent-based supply chain models, methods for understanding freight delivery patterns in urban areas, testing emerging technologies to collect data on freight traffic, interactive mapping and visualization of freight data, platforms for sharing data on a regional level, and tools for greater insight into the linkage between industry and infrastructure needs.

Four pilot projects focus on modeling and seven focus on data. Several of these studies are expected to be directly applicable to QRFM. Other studies show some potential for new techniques, or may just provide good sources for up-to-date case study information; the ones at the bottom of the list tend to focus less on travel demand practices but may also have potential as case studies. Table 4 provides additional information about the 11 pilot projects.

Table 4: SHRP2 C20 Pilot Projects

Recipient	Project Type	Project Status	QRFM Applicability	Notes
FL Department of Transportation	Data	Complete	Yes	Successful methodology for estimating fuel consumption based on local factors (i.e., land use, socio-economic, roadway, traffic inputs)
Capital District Transportation Committee (NY)	Data	Complete	Yes	Land use data model components
SD Department of Transportation	Data	Complete	Yes	Agricultural and land use data used as part of methodology to develop improved traffic counts
Maricopa Association of Governments (AZ)	Modeling	Substantially Complete	Yes	Land use data model components
Maryland State Highway Administration	Modeling	Substantially Complete	Yes	Land use data model components
City of Winston-Salem (NC)	Data	Complete	Yes	Development of freight facility database for use in informing land use planning, economic development or transportation improvement priorities
Metro (Portland) Metropolitan Planning Organization (OR)	Modeling	In Progress	Yes	Land use data model components
WA Department of Transportation (WA)	Data	Complete	Yes	Used interviews and questionnaires to collect business characteristics like route and mode choice and supported truck trip modeling by collecting truck count data at food distribution facilities under a variety of land use scenarios
Mid-America Regional Council (MO)	Data	Complete	Case Study Potential	Low applicability potential
Delaware Valley Regional Planning Commission (PA)	Data	Complete	Case Study Potential	Freight data clearinghouse enhancement and plotted major freight facilities in the region, but land use data was not a major project input or output
WI Department of Transportation	Modeling	Complete	Case Study Potential	Low applicability potential

NCFRP Report 24: Smart Growth and Urban Goods Movement (2013)

NCFRP Report 24 summarizes contemporary literature on the impacts of smart growth on goods movement and identifies areas for further research. The effort included outreach to a variety of goods movement practitioners and urban planners. The Puget Sound region was used as a testbed for incorporating several emerging practices for goods movement and smart growth scenario planning.

NCFRP Report 25: Freight Data Sharing Guidebook (2013)

NCFRP Report 25 provides a series of guidelines for sharing freight data, primarily between public and private freight stakeholders. The report recognizes the difficulties of obtaining data from private entities as well as the significant costs associated with data collection. The report provides examples of how to overcome these barriers. Additionally, it highlights 18 different public and commercial data sources that practitioners can access without restrictions.

NCFRP Report 739: Freight Trip Generation and Land Use (2013)

NCHRP Report 739 identified the need to make an important distinction between FG, FTG, and STG. FG is an expression of economic activity performed at a business establishment. Input materials are processed and transformed generating an output that, in most cases, is transported elsewhere for further processing, storage, distribution, or consumption. In contrast, FTG is the result of the logistic decisions concerning how best to transport the FG in terms of shipment size, frequency of deliveries, and the vehicle/mode used. STG is the travel made by local service industry personnel, such as craftsman and technicians who deliver, install, and maintain goods or services at their final destinations. The separation of FTG and STG by industry is important for understanding and predicting total freight travel demand. For instance, a fabricating plant that makes bathroom fixtures has a high ratio of FTG to STG, whereas a local plumber has a high ratio of STG to FTG.

NCFRP Report 37: Using Commodity Flow Survey Microdata and Other Establishment Data to Estimate the Generation of Freight, Freight Trips, and Service Trips: Guidebook (2017)

NCFRP Report 37 describes how industry-specific land classification systems such as the Standard Industrial Codes (SIC) or North American Industry Classification System (NAICS) provide a much better framework for forecasting freight generation (total flow of goods) than do more generalized codes, for example those defined by ITE for total vehicle trip generation or use in MPO forecasts (i.e., office, commercial, industrial jobs).

NCFRP Report 37 describes how industry-specific codes better link FTG (the flow of goods expressed in terms of vehicle trips) and service trip generation (truck trips generated primarily to provide services rather than delivering goods). New models to reflect these approaches have been developed through studies sponsored by TRB, with a focus on the New York City and Albany regions. The comparison of different types of freight demand models in a database (as described by NCHRP Report 739) is now being replaced by a single FTG software tool. This tool is in development and can be accessed here: https://coe-sufs.org/wordpress/ncfrp33/appendix/ftg/.

Developed by the Rensselaer Polytechnic Institute, the software applies FTG models at the ZIP code and two-digit NAICS code levels and made available during 2017.

ITE Trip Generation Handbook (2014)

The ITE Trip Generation Handbook provides guidance for site-specific trip generation with a special focus on person and vehicle trips by land use code. The handbook provides guidance on NCRFP Report 26 and NCHRP Report 739/NCFRP Report 19.

Additional Resources for "Thinking Beyond QRFM"

The foundational documents described in this report form the primary basis for considering updates to the QRFM. The following additional areas of interest reflect subjects that were not addressed in the QRFM, but are of increasing interest to the transportation industry. The initial exploration of these topics in the literature review includes best practices from other agencies, references to the QRFM in peer-reviewed literature beyond the foundational resources, and current agency and institutional consideration of the broader topics described as "thinking beyond QRFM." The initial findings below were expanded on during the peer exchanges.

Automated and Connected Vehicles (AV/CV)

The topic of automated vehicles for goods movement has generated significant research on a wide range of topics including highway safety, institutional and legal policies, just-in-time deliveries, and regulations enforcement. The initial review of the foundational literature indicates that industry consensus has not yet resulted in practical guidance for the application of AV/CV technologies into goods movement forecasting or transportation planning practices. The peer exchange events included this as an area of focus; there is a need to confirm the hypothesis that the specific role (or absence thereof) of the truck driver is not yet valued as a discriminator in freight travel demand analysis. Such analysis would be needed for more effective jurisdictional programmatic or facility planning. To evaluate this hypothesis, the definition of "automated" vehicle can be extended to concepts like last-mile deliveries by drones and robots.

Congestion Pricing

The QRFM recognized that users may need to realize tolls could create a dampening effect on demand. However it did not provide guidance on this issue beyond the use of time and cost impedance variables common to statewide or metropolitan travel demand models. Congestion pricing for facilities (such as with managed lanes) is an area of increased importance for truck trip assignment, considering the increased use of tolling for revenue generation and travel demand management both by location and time of day. This is an area where both attitudinal research and operational research has been robust, but the initial literature scan did not find compelling consensus on emerging or best practices specific to the freight industry.

FTG Survey Recommended Practices

The ITE Trip Generation Handbook is one of the foundational resources for this project. As described in the annotated bibliography, the handbook is a best practice that is periodically updated and adopted by ITE through a rigorous peer-review process. The 10th edition of the ITE Trip Generation Handbook was released in 2017. The ITE Trip Generation Handbook covers a wide range of topics beyond goods movement. One of the key freight recommendations is an application for a truck data collection survey, as from Thompson, Yarbrouh, Anderson, Harris, and Harrison in Transportation Research Record Number 2160 (p. 163) published in 2010.

Land Use Context

Two key documents provide useful context for considering the integration of land use context into the freight planning process. NCHRP Project 08-96 summarizes a wide range of strategies for accommodating goods movement demand and operations given the context-sensitivity of particularly freight-sensitive land uses (see Figure 2). It focuses on strategies for areas that are in the process of transitioning from freight-intensive to mixed use.

Related work has been done by Brian Hunter et al. at on identifying freight roadway design considerations (2017 TRB paper 17-01016; this was recognized as a best paper by TRB Committee AT025). This work also builds upon the City of Portland Street Design Guidelines (2008) for Trucks, and elements from Massachusetts DOT on encroachments and Virginia DOT on design vehicle concepts.

Megaregions

The concept of scenario planning for megaregions was examined by Weidner et al. in 2013 TRB paper 13-2236 examining a high energy price scenario for a multistate, multi-MPO region in the mid-Atlantic region. This examination demonstrated the value of scenarios for planning applications below the national commodity flow model. It also showed the ability of megaregion scenarios to link economic, land use, transport, and fiscal models. Overall it showed how decisions made by an MPO within a megaregion can have otherwise unanticipated effects elsewhere in the same megaregion. The applicability of this type of model to the QRFM will depend on the degree to which potential QRFM users gain value in the megaregion scale, which may be of greatest value to coalitions of transportation agencies such as the I-95 Corridor Coalition.

Reliability

Reliability is a topic of growing importance. While data are becoming increasingly more detailed and observed data are more precisely captured, this may still be limited in terms of its value to the freight industry for operations and planning. The QRFM states that reliability has increasingly been viewed as an important element to travelers, but does not provide guidance on how reliability might be incorporated into goods movement planning. Subsequent work by Xia Jin et al. at Florida International University on identifying stated value of reliability (at roughly 50 percent greater than travel time) was recognized as a best paper by TRB Committee AT015 (2017 TRB paper 17-00847). This effort builds upon prior meta-analysis by the same team in 2016 TRB paper 16-2051.

Scenario Planning

Scenario planning is a topic of increasing importance given the recognition that any transportation forecasting process has a range of uncertain, and often uncontrollable input variables and that investment decisions should encompass the widest range of likely futures as reflected in a risk-management approach to forecasting. For this particular topic, one of the foundational documents, NCHRP Report 750 Volume 1, is dedicated to the topic of scenario planning for freight transportation investment. That report is further described in the annotated bibliography.

Other QRFM References and Potential Case Studies

Additional resources were identified through the compendium of TRB annual meeting papers and presentations that cite the QRFM II and may serve as case studies for key topics and/or case studies for use in the next edition of the QRFM. Table 5 describes those additional resources.

Table 5: Additional Resources for QRFM References

Title	Author	TRB Paper Number	Key Topics
Arizona Statewide Travel Markets	Erhardt, Parsons Brinkerhof	TRB: 12-2109	Freight Analysis Framework application, use of 4-step models
Distribution Analysis - Virginia Freight	Duanmu et al., Old Dominion University	TRB: 12-2782	Commodity-based gravity model
Structural commodity generation - California statewide model	Ranaiefar et al., University of California Irvine	TRB: 13-1962	Structural equations model (SEM)
South Carolina Statewide Model Development	Amar et al., CDM Smith	TRB: 16-5539	Integration of MPO models into a statewide model
Spatial Firm Demographic Microsimulator: Development and Validation for Phoenix and Tucson Mega-region, Arizona	Ravulaparthy et al., Maricopa Association of Governments and Cambridge Systematics	TRB: 17-4964	Effect of spatial consideration on freight