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14 Truck Data1 provides data on freight and nonfreight truck address this issue, both as short-term incremental improve- volumes. The assignment of disaggregation of the FAF2 ments and long-term improvements. origin-destination (OD) database to the network can provide estimates of truck volumes by Standard Classification of Better Methods to Consider Transportation Goods two-digit (SCTG2) commodity. By Nonfreight Trucks identifying the link flows at the locations with seasonal truck percentages as freight, nonfreight, and/or by SCTG2 com- Expanding on a paradigm developed by Hunt and Stefan,2 modity, it may be possible to identify the appropriate sea- trucking activity in a model area can be considered to have the sonal factors that should be used for these commodities. following four components: 1. Interregional freight, typically trips with at least one trip Modal Diversion Consistent with end external to the region that is being modeled. Exam- the Geographies of Public Agencies ples include long-haul truckload, less than truckload, and Modal diversion requires data outside of the area covered private trucks. by most DOT and MPO models supporting public decisions. 2. Intraregional freight truck tours, those trucks that move The development of national multimodal databases of flows, individual shipments of goods locally within a model region. behavioral characteristics, and networks may be needed to Examples include parcel pickups and delivery trucks dis- address this issue. Research needs to be undertaken into the tributing goods to retail, office, and commercial establish- variables that are considered in the mode choice of freight ments, as well as homes. 3. Intraregional service truck tours, those trucks that move decisionmakers. Behavioral characteristics typically are deter- in individual movements to offer services locally within a mined though a preference survey. There are national freight model region, to support construction, service, utility, and flow databases that could be adapted as revealed-preference other service operations. Examples include trucks oper- databases. Other national databases exist that could provide ated by telephone and cable companies, contractors, and values for some of the decision variables that might be part repair and service companies. of the modal decision. An analysis of the modal choices, as 4. Fleet allocations and patrols, those trucks that are assigned revealed in existing freight databases together with available to patrol or operate on fixed routes within a specific geo- information on explanatory variables using standard mode- graphic area or road links within the model region, rather choice regression software, may provide useful insights into than to move individual shipments of goods or services. which variables are important in modal-choice decisions for Examples include garbage trucks, newspaper or mail deliv- freight, as well as the degree to which these explanatory vari- ery, as well as roads and parks maintenance. ables are considered. Methods exist to address all of these components singly or 3.2 Topics Not Selected for in combination. For example, the FHWA's Accounting for Further Research Commercial Vehicles in Urban Transportation Models already outlines procedures to better account for commercial truck The topics presented in Section 3.1 were the focus of addi- activity, exclusive of intercity trucking, particularly Compo- tional research as documented in the remainder of this sec- nents 3 and 4 above. (It should be noted that Accounting for tion. Topics that were not selected for additional research, Commercial Vehicles identified many other commercial vehi- but were identified as addressing critical gaps, are described cle trips for business services--e.g., realtors, salesmen--that in this section. involve automobiles. Although this travel is a substantial por- tion of total commercial vehicle travel, it does not overlap Freight Data to Support Model with freight truck trips and these automobile commercial Specification, Calibration, and Validation trips are not included in this proposed topic.) NCHRP 606 addresses methods to account for Component 1. The Quick The focus of NCFRP Project 6 was intended to exclude Response Freight Manuals (1996 and 2007 editions)34 address data needs. Although the quality and availability of data was a principal issue raised by the interview respondents, there are 2 Hunt, J. D., and K. J. Stefan, "Tour-Based Microsimulation of Urban Commercial other ongoing TRB and U.S.DOT projects and programs to Movements," Transportation Research Part B 41, (2007): 9811,013. 3 Cambridge Systematics, Inc., Comsis Corporation, and University of Wisconsin Milwaukee, Quick Response Freight Manual; Federal Highway Administration, 1FAF2 Highway Link and Truck Data and Documentation: 2002 and 2035, Federal Office of Planning and Environment, September 1996. Highway Administration, Office of Freight Management and Operations, 4 Cambridge Systematics, Inc., Quick Response Freight Manual II; Federal High- way Administration, November 2007.

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15 methods to account for Components 2 and 3. What is not Classification System [NAICS] versus Standard Industrial available is some indication of the expected size of these truck Classifications [SICs] industries). Local commodity, employ- components in model regions. ment databases, and surveys fare no better. It is possible to determine the base-year existing truck activity within a region from FHWA's Highway Perfor- Improved Methods for Nonhighway mance Monitoring System (HPMS). HPMS provides statis- Freight Assignment tically based estimates of truck activity for the states and urban areas typically covered by models. The FAF network In addition to truck freight activity on highways, domestic flow datasets, or improvements to those datasets, can be freight is carried by rail, barge, and other domestic water ves- used to provide estimates of Component 1, and that portion sels, air, pipeline, and combinations of these same modes to of Component 2 covered by the FAF. FHWA's Accounting travel between an origin and a destination. Air travel is not for Commercial Vehicles in Urban Transportation Models5 constrained to specific network links. Although water is con- outlines methods where vehicle registration data and/or air strained to specific systems of public waterways, the options quality mobile source inventory data can be used to provide to divert from these waterways are limited and assignment by individual estimates for Component 4, and Components 2 water is a trivial problem. Rail travel operates almost exclu- and 3, respectively. sively on privately owned tracks where the assignment serves For at least some urban areas, it may be possible to use all the business needs of the railroad trains, not the freight being of these methods and data simultaneously to arrive at esti- carried. Although improved rail routing methods would seem mates of the total HPMS reported truck VMT in each region, desirable, this topic is being pursued by other research, includ- ing research by the railroads. Additionally, rail assignments which should be coming from the sum of the trucking com- serve the multistate business interests of the railroads and ponents identified. This information on the allocation of freight those interests are not easily confined to the areas served by a and nonfreight truck VMT in the areas served by models state or MPO model. should be of value in the calibration and validation of the truck components of those models. Simplified Methods for Considering the Economic Impact of Freight Improvements Better Incorporation of Labor and Equipment Productivity in Freight Models Although transportation projects advanced as freight projects may have significant impact on the economy, those The economic activities that produce or consume freight projects also have benefits to passenger and other travel. can be expected to become more productive, such that the rela- Additionally, transportation projects intended to benefit gen- tionship between economic activity and the freight required to eral travel may have significant impacts on the transport of support this activity may not match the relationships incorpo- freight; those benefits to the transport of freight may have sig- rated into existing models. Similarly, the carriers who transport nificant impacts on freight-dependent industries as well as freight also continue to increase productivity such that the rela- other sectors of the economy. Given that the scope of this tionships between the volume of freight and the number of topic transcends freight, the subject may be pursued more vehicles required to move the freight, as included in existing appropriately in conjunction with more comprehensive meth- models, would no longer be applicable. ods to better account for the economic impacts of transporta- Although it might be possible to develop this information tion projects and to properly attribute those benefits to all using time series of equipment and/or labor availability sectors of travel demand, including freight. together with time series data of commodity flow, such datasets are not readily available. Where times series of com- Better Consideration and Forecasting modity flow databases do exist (e.g., Commodity Flow Sur- of Trip by Empty and Repositioning vey [CFS], FAF, TRANSEARCH), either there have been Freight Vehicles significant changes in the methods used to collect the data, or the commodity classification scheme has changed (e.g., Stan- Although understanding the movement of empty and repo- dard Transportation Commodity Code [STCC] to SCTG). sitioning freight trucks is important, it is a subtopic to devel- That same issue exists for the potential regression datasets oping a better understanding of the chaining of freight (e.g., employment classified by the North American Industry activities discussed previously. Thus, additional research on this topic should be deferred, unless subsequent research on truck chaining does not adequately advance the understand- 5Cambridge Systematics, Inc., Accounting for Commercial Vehicles in Urban Trans- ing of the movement of empty vehicles, including the reposi- portation Models, Federal Highway Administration, 2004. tioning of trucks for the next trip.