Innovations in Freight Demand Modeling and Data Improvement (2014)

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Rail Freight Commodity Models: A First Generation Effort in Iowa Phillip Mescher Iowa Department of Transportation Ronald Eash and Mary Lupa Parsons Brinkerhoff Presentation Notes: Presentation by Phillip Mescher, Iowa Department of Transportation (DOT). Iowa’s first generation traffic model was developed in 2007 as a passenger car and truck model. This model is used by MPOs and regional planning affiliations (RPAs) for planning, engineering, and safety studies. The second-generation model, in progress, updates the base year of analysis to 2010 and represents a beginning of emphasis on freight and commodity movements. This model is being used to develop metrics, such as Iowa corn ton-miles by rail. The data sets being utilized are FAF3 data, disaggregated to county-level data and Federal Railroad Administration’s (FRA) confidential rail waybill data. Major tasks remaining include developing mode choice, finalizing commodity tables, and identify emerging new markets. This model will assist in creating new metrics, developing scenarios for analysis, and tracking rail ownership changes. Abstract Public sector planners, at the rural RPA, MPO, and state levels have long had an interest in building and applying truck models. These truck models typically use zonal level employment data by category and integrate truck “special generators” that represent very large manufacturing, warehousing and intermodal facilities. Gravity models are used in most cases with two or three truck sizes and weights modeled. Truck commodity models have evolved greatly in recent decades, as planners and decision makers began to understand clearly the amount of highway capacity used by commercial vehicles as well as the disproportionate wear and tear on pavements when they carry trucks as opposed to cars. A small number of these truck models address the fact that the U.S. rail network delivers commodities to points, typically rail-truck transfer sites, where they may enter the truck “universe” and be added to the final truck trip tables in the travel model. What has generally been set aside in this effort is the development of a true rail freight commodity model. In 2012, the Iowa DOT launched a statewide model update which includes the development of a first generation rail freight commodity module, scheduled for delivery in January 2014. This ambitious project fits three criteria noted under the topic “Modeling and Logistics Data Integration” in the “Call for Papers: Innovations in Freight Modeling & Data”: 23

Modeling and Logistics Data Integration • Integrating public and private data sources—new sources of data that can be merged to create improved opportunities for modeling. • Freight demand modeling recommendations—new modeling technologies. • Using private-sector data for public-sector models—types of data that can be integrated and used in the public sector. The chief criterion for including the Iowa DOT rail freight commodity effort in the upcoming SHRP 2 freight symposium, however, is that it opens new ground in the arena of statewide planning and modeling. While rough and in progress, the Iowa DOT effort can provide to peers and interested parties: • Model architecture, describing the statewide framework in which the rail models operate. • Overview of the ongoing rail freight commodity model supply components o Assignable rail network (national), o Assignable rail network (Iowa), o Centroid or loading point strategy, and o Rail ownership link segment handling. • Overview of the ongoing rail freight commodity model demand components o First step FAF-to-county disaggregation by freight mode by goods (FAF-to-county), o Discussion of disaggregation at a sub-county traffic analysis zone scale, o Truck-rail interface, and o Domestic and international commodity movements handling. • Comprehensive public and private rail data review. This presentation addresses three key topics related to the Iowa DOT rail freight commodity models: (1) model architecture, (2) rail freight model structures, and (3) applicability to states, MPOs, and decision makers in the planning and modeling community. This abstract will endeavor to communicate the importance of this emerging modeling tool. Iowa DOT Model (iTRAM) Architecture The Iowa DOT rail effort is in progress and is best explained in the context of the statewide travel demand model, known as the iTRAM, Iowa Traffic Analysis Model. This model, first launched in 2005, features state and national passenger car and truck models. References to both passenger rail and freight commodity rail have not been a priority until this most recent (2012) model enhancement phase. Commodity Flow Processing U.S. commodities are processed in a stand-alone model. The process follows these steps: 24

1. For 2007 and 2040, FAF3 data for four freight modes in Iowa are processed. The result is a master set of commodities for truck, rail, water, and intermodal modes for the base and future. 2. Disaggregation of the commodity flows will then be conducted. Three large sets of commodity flow tables are initially produced for domestic county-to-county, country-to- county import, and county-to-country export flows. Each of these three data sets contains a table for every mode-commodity combination in the FAF. The county flow tables are further disaggregated into project zones within the Iowa study area and combined into larger districts outside the study area. The disaggregation employment data sources vary from census and federal departmental offerings to private county level data and Iowa DOT public and private data holdings. 3. Intermodal commodity flows will be reallocated to the truck, rail, or water flows, using a freight mode choice approach. 4. The resulting commodity flow movements will be processed as follows: a. Truck movements will be routed to the main iTRAM model. b. Rail movements will be assigned to the rail network and the truck trips that serve these trips will be routed to the main iTRAM model. c. Truck trips that serve water freight movements will be routed to the main iTRAM model. Rail Freight Model Structures It is the rail freight commodity area that is the focus of this proposed presentation. A small number of rail freight commodity model efforts have been conducted as of the writing of this abstract. Even a cursory review will illuminate the challenges with respect to supply and demand data and approaches for rail commodity models. It is the intent of this abstract to present these challenges in an outline form. SUPPLY SIDE–RAIL FREIGHT COMMODITY MODELS • Networks: Iowa DOT staff members have taken a fundamental step with respect to rail models by developing the Iowa rail network. Class II railroads such as the Iowa Northern, the Appanoose County Community Railroad, and others will also be included in the rail freight model. Select Class I and II railroads outside of Iowa—particularly parallel to the rivers—will be reviewed for inclusion in the detailed Iowa rail network as well. 25

The Iowa rail network noted above is the first building block of the rail freight model. Once the network was built and reviewed, however, it became apparent that rail networks and freight rail models are very different from the corresponding highway-based network and models. Over the history of travel demand analysis, rail networks have received very little study compared to highway networks. The key rail network model components requiring study and integration are noted in the following. • Zones: The traffic analysis zone (TAZ) structure established for the iTRAM will be active in the freight rail model as well. It will not, however, be the core zonal structure for rail freight. The rail zones will be a disaggregation of the FAF3 districts into counties and finally into points consistent with the observed data in Iowa. The points can be mapped to TAZs once the locations are established. • Rail Segment Capacity: There must be a means of measuring rail capacity so that rail capacity deficiencies can be quantified. According to a rail study that has built assignable rail networks, the capacity of rail corridors is determined by a large number of factors, including the number of tracks, the frequency and length of sidings, the capacity of the yards and terminals along a corridor to receive the traffic, the type of control systems, the terrain, the mix of train types, the power of the locomotives, track speed, and individual railroad operating practices. Complete, consistent, and current information on all these factors is not always available so the capacity of the primary corridors can be estimated using only three dominant factors: number of tracks, type of signal system, and mix of train types. It is anticipated that rail segments in Iowa will start with these calculations and then evolve to use a customized combination of the available Iowa rail attributes to measure capacity. Train length will also figure into the capacity calculation. • Rail Segment Modes: Just as highway segments can have modes such as “truck only” or “trucks prohibited,” the rail network will be designed so that only certain commodities and/or industries will be permitted to use any particular rail line segment, often keyed to the rail ownership. This customization will be Iowa-centered, will use the U.S. Surface Transportation Board’s rail waybill data and will be responsive to the origins and destinations of the freight commodity being transferred. • Centroids: Rail freight originates in very different locations from persons traveling from households or from work. The iTRAM rail model has been conceptualized from the beginning to use the rail waybill data as the source of origin, destination, and commodity type; number of rail cars, tons, and revenue; length of haul; participating railroads; interchange locations; and Uniform Rail Costing System (URCS) shipment variable cost estimates. • Centroid Connectors: Household-based travel models allow trips to enter the highway network from each zone evenly to any of the reasonable (and connected) road segments in the network. In the case of a rail centroid connector, commodities do not use the shortest rail path to exit the zone. Instead, the goods will seek the closest rail segment that 26

fulfills other criteria, such as a selected track owner, shipping cost, origin-destination efficiency, or other. The centroid connector approach will be similar to a transit park-and- ride model in which drivers find and use the most efficient station based on criteria other than distance. • Daily/Annual Frame: Household-based travel demand models such as the iTRAM forecast an average weekday of travel during a representative year. Because freight flows are forecast through the FAF3, the starting point for the demand is a set of annual commodity flows. Rail freight capacity is likely to be calculated in units of trains per day. Hence the year-to-day assumptions become highly important. • Rail Interface with Truck and Intermodal: Interviews with stakeholders in Iowa as well as a wide variety of data sources have demonstrated a strong connection in Iowa between trucks and rail. These important transfer points will be investigated via the numerous public and private point data sources. While the rail network within Iowa is the main focus of the freight rail model, the model requires a national rail component in order to accurately capture Iowa rail flows. Outside the state, the Oak Ridge National Laboratory (ORNL) GIS and network products were downloaded and adapted for use as the national rail network. The total national network will be assembled from Iowa active rail and ORNL rail network components. DEMAND SIDE—RAIL FREIGHT COMMODITY MODELS The key to understanding the allocation of commodity flows to the rail network is the confidential Carload Waybill Sample collected and provided by the U.S. Surface Transportation Board (STB). The STB has statutory authority over the Carload Waybill Sample (49 CFR 1244). Railroads terminating over 4,500 cars per year are required to file a sample of waybills with the STB. The primary purpose of the Carload Waybill Sample (CWS) is regulatory oversight. The Iowa DOT has obtained this database for both 2009 and 2010. Rail movements are generally aggregated to the Bureau of Economic Analysis (BEA) region to BEA region level at the five- digit Standard Transportation Commodity Code level, and thus the BEA geography will provide a means for an intermediate disaggregation of rail flows. Within Iowa, there are other potential sources of rail demand data in addition to the waybill. Because one primary goal of the update is to capture freight faithfully in Iowa, a library of freight special generator points for rail is under development. These points are derived from industry and DOT databases and include the following: 1. Raillinc: A comprehensive list of rail geography, including rail station name, location in latitude-longitude, standard point location code (SPLC), and track and junction information. 27

2. Iowa DOT Point Files: The Iowa DOT has researched and mapped a set of important point location maps relevant to freight, including a. Biodiesel and ethanol processing plants b. Grain facilities transfer points c. Wind turbine production sites d. Others, as identified 3. Caliper Corporation U.S. Point Files: the software vendor provides a starting point file for intermodals. 4. Other: As model development proceeds, data collection will proceed to deliver the most detailed state information to the rail model. WHERE SUPPLY AND DEMAND MEET The freight rail assignment is expected to consist of a simple all-or-nothing assignment with impedance equal to weighted travel time and interline transfer penalties. The steps are as follows: • Allocate commodities to trains. • Commodity to car type/capacity factors developed from the Carload Waybill Sample (CWS). • Generalize train lengths based on observation. • Adjust directional volumes by freight car type to account for backhauls. • Factor to average weekday trains, understanding that discussions with the Iowa DOT will ascertain the most useful assumption to identify rail capacity needs in the state. • Assign to the final Iowa and national rail network. There are a great number of issues related to freight rail assignment. Specific business functions of rail freight, such as competition and cooperation between railroads, as well as the future rail regulatory environment, will be interpreted in a sketch fashion, integrating the basics, where possible. It is the goal of the rail freight assignment to take the first steps in rail freight modeling: getting the right goods in the right rail cars, modeling rail freight transfers accurately, and discovering relationships between make/use commodity relationships nationwide to construct a reasonable model. The rail model will be calibrated by adjusting the interline penalties to match Class I rail movements. Applicability to States, MPOs, and Decision Makers in the Planning and Modeling Community The Iowa DOT has gone out on a limb to add a first generation rail freight model to its suite of statewide modeling tools. It is well understood by state planners that private business owners, 28

both on the truck and rail sides, do not share data freely and openly with the public or with public agencies. Hence, the ability to calibrate and validate rail freight models is very much limited and is a huge challenge. The first generation rail freight model is expected to answer DOT rail planning questions at the conceptual level including • Summary statistics: Rail ton-miles by commodity within Iowa, base and future; • What-if analysis: o Test placement of a new truck-rail intermodal or mega-warehouse or distribution center, and o Test the viability of a new short line railroad; and • Rail ownership changes. The specific capabilities envisioned for the iTRAM may not be readily transferable to smaller scale geographies, such as MPOs or corridors. The reason for this limit is the scale at which a tool such as rail freight can maintain accuracy, and the confidence we have in the disaggregation process when it must be conducted at a sub-county level. However, for state or regional studies, the iTRAM rail freight commodity model is expected to be transferable in its concept, given that local knowledge is used in the adapting process. While very much a work in progress, the iTRAM rail freight model is expected to advance the practice of freight modeling nationwide. 29