The Federal Highway Administration (FHWA) estimates domestic freight volumes to grow by more than 65 percent, increasing from 13.5 billion tons in 1998 to 22.5 billion tons in 2020. According to the U.S. Government Accountability Office, the volumes of goods shipped by trucks and railroads are projected to increase by 98 percent and 88 percent, respectively, by 2035. Since the Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) required states and metropolitan planning organizations (MPO’s) to consider urban freight in their long range plans, a number of states have adopted statewide freight forecasting models.

The State of California is the leading freight destination by value in the United States. It is a major multimodal gateway and hub for international trade, and is home to significant international freight gateways for freight transportation by water, air and truck, and has a significant freight rail network. Three of the five busiest ports in the United States are located in California, with the San Pedro Bay Ports (SPBP) complex (comprising the Port of Long Beach and Los Angeles) leading the nation, together forming the fifth busiest port complex in the world, and a very important contributor to both California’s and the nation’s economies. In 2010, about 38 percent of all container traffic at water ports in the United States was handled by the SPBP complex. In addition, over 886,000 jobs are supported by international trade activities indirectly and directly related to the SPBP complex, which generate more than $6.7 billion in state and local tax revenues. Even with the recent economic downturn, container traffic at the SPBP complex still increased more than 50 percent between 2000 and 2008 from 9.5 million twenty-foot equivalent units (TEUs) to 14.3 million TEUs. Notwithstanding, Los Angeles International Airport is the fifth busiest airport in the Unites States by total cargo throughput, and the Otay Mesa Land Port Of Entry (LPOE) is the fourth busiest land port in the United States. California is also home to Southern California Association of Governments (SCAG), the nation's largest metropolitan planning organization, representing six counties, 191 cities and more than 18 million residents.

California is the world’s 12th largest source of carbon dioxide emissions, and recently took the lead by adopting the AB 32: Global Warming Solutions Act. AB 32 requires the state’s global warming emissions to be reduced to 1990 levels by 2020 in an “environmentally just” manner. While existing policies such as California’s emissions standards for vehicles and renewable energy requirements are expected to meet the 2020 goal halfway, additional policies will be needed to fully comply with the Act. Senate Bill 375 is the country’s first law to control greenhouse gas emissions using land use strategies. The amended Senate Bill 391 requires that the California Transportation Plan be updated by December 31, 2015 with a plan that identifies integrated multimodal transportation system options to address how emissions reductions would be achieved. These regulations and policies make it crucial for the state to have the necessary tools at its disposal in the next decade to analyze different economic, social, and environmental policies associated with goods movement. One of the key strategic responses by the California Department of Transportation (Caltrans) to this issue is the development of the California Statewide Freight Forecasting Model (CSFFM).

In addition to Caltrans, a number of local and state agencies have a stake in the creation of a statewide freight model. Stakeholders include the California Air Resources Board (CARB), the California Energy Commission, the California metropolitan planning organizations (MPO’s) including SACOG, SCAG, MTC, and SANDAG, and all the ports and freight facility operators. Some of these agencies have created their own local freight models, such as the Heavy Duty Truck Model at SCAG, while others use models that can benefit from integration with a statewide freight model, such as the California Statewide Travel Demand Model (CSTDM).

CSFFM is a policy-sensitive tool that is designed using the Citilabs CUBE software platform to forecast multi-modal vehicle and commodity flows within California. The model will address socioeconomic conditions, freight-related land use policies, environmental policies and multimodal infrastructure investments. The model comprises five core modules: The Commodity Module, Mode-Split Module, Transshipment Module, Seasonality and Payload Factor Module, and Network Module.

The Commodity Module consists of the total generation, domestic flow distribution, and import/export gateway distribution steps. From these three steps, the module produces production and attraction and distribution of commodities by tonnage based on demographic and economic data as well as impedance information (i.e., travel time and cost). The Mode-Split Module determines the mode-share for each mode corresponding to each origin-destination pair. Incremental logit models are used in this module to evaluate the impact of changes in mode attributes. The Transshipment Module breaks intermodal trips into their component segments by mode and assigns commodity flows at the transport logistics nodes (TLNs). The Seasonality and Payload Factor Module uses truck tonnage, multimodal information, and trucks from transshipment to produce seasonal and annual flows by truck class and commodity group. Lastly, the Network Module consists of route choice and traffic assignment. This module uses multi-class assignment to assign trucks to the network and all-or-nothing for the rail assignment. The outputs are truck flows in four truck categories at the network level, rail tonnage flows at the network level, and air, water and pipeline tonnage flows at the Origin-Destination (OD) matrix level.

The analysis zone scheme comprises 97 Freight Analysis Zones (FAZs) within California that are defined at the county and sub-county level, and conform to MPO and air basin boundaries. There are 38 import/export gateways (19 land ports, 8 airports, and 11 seaports), and 31 TLNs (13 airports and 18 rail terminals including five virtual rail terminals) inside of California. Outside of California, the scheme includes 118 domestic regions and 8 international regions that conform to the Freight Analysis Framework (FAF) zones.

The model includes fifteen commodity groups (CGs) based on the aggregation of the two-digit Standard Classification of Transported Goods (SCTG) commodity classes used by FAF.

Several key features of the CSFFM facilitate compatibility with other regional and statewide models in California. The FAZs are defined at the county and sub-county level. In addition, all FAZs conform to existing MPO and CARB air basin boundaries, and are composed of CSTDM TAZ aggregations.

Due to the aggregation level of the FAZs, the CSFFM is not suited for sub-regional analyses. For such purposes, analysts are directed to regional-level models available at various regions or metropolitan areas. The CSFFM’s primary purpose is to provide analysis of inter-regional freight movements at the statewide level. Because the CSFFM is designed to partner with the CSTDM, it shares the same underlying master California highway network as the CSTDM to ensure compatibility and consistency.

The model is designed to be used by state agencies such as Caltrans, the California Air Resources Board, the California Energy Commission, and regional agencies such as Metropolitan Planning Organizations and Regional Transportation Planning Agencies. It is designed to be used as a policy-sensitive model for forecasting commodity flows and commercial vehicle flows within California to address issues such as socioeconomic conditions, land use policies related to freight, environmental policies, and multimodal infrastructure investments.

The CSFFM was calibrated and validated using available truck count data at Weigh-In-Motion sites in California for the years 2007 and 2010, respectively. This report also provides presents forecast results for the year 2020 and 2040, based on estimated input data corresponding to these forecast years.