Smart Growth and Urban Goods Movement (2013)

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78 Modeling Tools at PSRC The Puget Sound Regional Council utilizes an integrated modeling system to conduct analy- sis of alternatives in the region (see Figure 11). These tools expand the capabilities to develop and analyze various alternatives, improve accuracy in the forecasts, and provide efficiencies in the analytical process. The capabilities are described for each of the tools that have bearing on the analysis in this report. Regional Economic Model The Puget Sound Economic Forecasting model produces regional and county economies as input to the land-use forecasting model. It consists of two sub-models: one projecting the regional economy and one forecasting the individual county economies. PSRC uses only the regional forecasts as inputs to the land-use forecasting models, given that local land-use trends, patterns, and plans need to be considered in developing a final county-level forecast. Land-Use Model System The new land-use forecasting model, UrbanSim, is a parcel-based, market-driven model.5 In addition to the new capabilities in this model, the model can be applied iteratively for each scenario or alternative to evaluate how the land use is affected by each transportation invest- ment. This is a big shift in the analytical process, in which land use is assumed to be fixed for each forecast year. In addition, these new land-use models are sensitive to land-use and public policies so that the impacts of changes in policy on growth and transportation can be tested. Travel-Demand Model System The regional travel-forecasting model at PSRC has undergone changes to represent activi- ties rather than trips. This is significant because travel decisions are all linked together around activities. For example, if a person goes to work, then stops for gas, food, and to pick up a child on the way home, the choice of mode, destination, timing, and even how many trips to make are all linked to this chain of events. These new models, called activity-based mod- els, track individuals rather than groups of people, which makes them more behaviorally correct than trip-based models. PSRC has incorporated the trip-making component into the A p p e n d i x C 5 For further discussion on UrbanSim, please visit the UrbanSim website at http://www.urbansim.org/Main/WebHome

Modeling Tools at pSRC 79 current regional forecasting process. This allows changes in the number of trips and stops by trip purpose for different transportation alternatives to be determined. PSRC has also implemented some other short-term models, and the complete modeling system is depicted in Figure 12. Improvements include the following: • Pricing/tolling—improved sensitivity in the models to cost • Freight analysis—refined speeds and costs for trucks • Modal-choice analysis—stratified transit modes into local bus, premium bus, light rail, com- muter rail, and ferry • Non-motorized analysis—added pedestrian and bicycle factors • Speed and reliability impacts—added reliability and improved speed validation • Greenhouse-gas emissions—used EPA Moves model to generate emission rates by type for different speed ranges Figure 11. PSRC’s model system. Figure 12. Travel model components. Zonal Data Legend: Input Files Models/Processes Data Output Files Highway Networks Households by Workers, Income, Household Size, and Vehicles Available Activities by Person Type (8) and Purpose (8) Vehicle Availability Model Daily Activity Pattern Model Additional Zonal and Cost Data Transit Networks Trip Distribution Model Mode Choice Model Time of Day Model Trip Tables by 7 Trip Purposes (HBW by 4 income groups) Trip Tables by 5 Trip Purposes and 7 modes Trip Tables for 5 Time Periods and 4 Purposes (HBW by 4 income groups Traffic Analysis Zones Trip Assignment Model Highway and Transit Volumes and Travel Times Truck Model

80 Smart Growth and Urban Goods Movement User Benefit Analysis System PSRC’s Benefit-Cost Analysis (BCA) tool compiles the benefits and costs of transportation measures. The BCA tool reports travel time and reliability benefits and compares these to operat- ing, maintenance, and capital costs to determine the benefit-cost ratio of a program or project. It also reports accident costs and vehicle emissions costs so that these can be directly accounted for in the benefit-cost ratio. In addition, BCA is used to evaluate geographic, socio-demographic, and freight-equity issues by allocating benefits and costs to these market segments. Model Framework There are a series of assumptions in any analytical tool or model that provide a framework for understanding and interpreting the results. Land Use The land-use forecasting model (UrbanSim) produces forecasts of land use and buildings by type. There are 1.18 million parcels in the region, and there are 30 land-use types in six general categories, with each parcel in the Puget Sound region having a unique land-use type. In 2000, there were 23 building types and 1 million buildings in the region. There are a few land-use types that do not have any buildings (these are italicized), and there is one building type (outbuildings) that does not have a corresponding land-use type (see Table 20). Food, Forest, Mining - Agriculture - Fisheries - Forest, harvestable - Forest, protected - Mining Public - Civic and Quasi-Public - Government - Military - Park and Open Space - Recrea
on - School Retail and Service - Commercial Residen al - Group Quarters - Mobile Home Park - Mul
-Family Residen
al - Condo Residen
al - Single-Family Residen
al Industrial - Industrial - Transporta
on, Communica
on, U
li
es - Warehousing - Water - Right of Way - Parking Other - Mixed Use - Office - Hospital, Convalescent Center Note: Land-use types without buildings - No Code - Vacant Developable - Vacant Undevelopable - Other/Outbuilding Table 20. Land-use and building types.

Modeling Tools at pSRC 81 Person Type - Full-me worker - Part-me worker - Rered - Non-worker - University student - Student age 16+ - Student age 5–15 - Child under 5 Household Size - One person - Two persons - Three persons - Four or more persons Number of workers - Zero workers - One worker - Two workers - Three or more workers Income Group (2006$) - Under $30,000 - $30,000 to $55,000 - $55,000 to $90,000 - Over $90,000 Note: Household income is assumed to increase with inflaon. Table 21. Household and person characteristics. Demographics and Economics The Puget Sound Economic Forecaster (PSEF) produces forecasts of population by age group (1–4 years, 5–19 years, 20–64 years, and 65 years and older), population by type (household or group quarters), number of households, personal income, and employment by sector. These forecasts are used as regional control totals in the land-use-forecasting process; they do not vary by transportation alternative. The land-use-forecasting model produces a synthetic population database consistent with existing and future regional demographics, with the following characteristics for each house- hold (see Table 21): age of head of household, number of children, number of workers, income, and number of persons. There were 1.28 million households and 3.2 million people in 2000, and there are forecasts of 2.19 million households and 5.0 million people in 2040. There are 19 employment sectors (see Table 22) represented in the economic and land-use forecasting models, 10 employment sectors in the truck forecasting model, and 6 employment sectors in the passenger-travel-demand forecasting model. There were 1.85 million jobs in the Puget Sound region in 2000, and the forecast is for 3.07 million jobs in 2040. The land-use forecasts are sensi- tive to changes in transportation investments and will demonstrate how growth patterns vary by investment package. Travel Characteristics Travel is classified by purpose, mode, and time period in the travel-demand forecasting mod- els. Travel purpose is defined in two ways: first, by identifying the purpose of the primary des- tination of a tour (defined as the series of trips linked together that start and end at home), and second by identifying the individual purpose of a single trip (see Table 23). The daily activity patterns generated for the tour purposes are sensitive to changes in trans- portation investments, toll policies, congestion, and growth patterns. The linking of trips into tours also reflects the fact that travel choices are made based on the whole tour rather than just

82 Smart Growth and Urban Goods Movement Economic and Land-Use Forecasting Truck Model Passenger Model Goods-producing Natural resources and mining Natural Resources Manufacturing Mining Aerospace Manufacturing - Equipment Other durable goods Manufacturing - Products Nondurable goods Construction Construction WTCU Service-producing Wholesale trade Wholesale trade Transportation and warehousing TCU Utilities Telecommunications Other information Retail trade Retail trade Retail trade Financial activities FIRES FIRES Professional and business services Food services and drinking places Educational services Health services Other services Government Government Education/Government Government Education Education Notes FIRES = Finance, Insurance, Real Estate, Services WCTU = Warehouse, Communications, Transportation, Utilities TCU = Transportation, Communications, Utilities Table 22. Employment sectors in economic, land-use, and travel models. Tour Purpose (Desnaon) - Work - School - Escort - Personal Business - Shop - Meal - Social/Recreaonal - Home Trip Purpose (Origin and Desnaon) - Home-based work - Home-based school - Home-based college - Home-based shop - Home-based other - Non-home-based work - Non-home-based other Table 23. Travel purposes.

Modeling Tools at pSRC 83 an individual trip. The current PSRC model represents tours for the trip-generation component of the process but combines this with destination, mode, time of day, and route choice at the individual trip level. These individual trips are not linked together as tours and are therefore less effective in capturing travel decisions that are linked together. PSRC is currently developing the remaining tour models (also called activity-based models) to improve this process. PSRC can report on tours and trips at the household level, but we cannot yet track tours at the destination, mode, time-of-day, or route choice level. Travel Modes Multiple travel modes are represented in the passenger travel-demand forecasting model in three categories: auto, transit, and non-motorized. These are evaluated in a nested logit structure (shown in Figure 13) that groups modes that are more likely to provide trade-offs with one another. Time Periods There are 32 time periods in the detailed time-of-day choice component of the passenger- travel-demand models, and these are aggregated to five time periods for use in other modeling components (see Table 24). The more detailed time periods are used to determine the actual time of an individual trip, and these are aggregated to determine an average travel time, cost, and volume for the aggregated time periods. The more detailed time periods in the time-of-day models can be used in trip assignment, but this is best used for corridor-level analysis and not for regional planning purposes. Travel Costs There are four types of direct costs in the travel-demand forecasting models: auto operating cost, parking costs, tolls, and transit fares. Auto operating costs are applied at 14.4 cents per mile (in 2006 dollars) to all auto modes and to the auto-access-to-transit modes. Daily standard and Figure 13. Travel modes. Auto Transit Walk Bike Walk Access Drive Access Lo ca l B us Pr e m iu m B us Li gh t R ai l Co m m u te r R ai l Fe rry Lo ca l B us Pr e m iu m B us Li gh t R ai l Co m m u te r Ra il Fe rry SOV HOV2 HOV3+ Notes: • Single-Occupant Vehicle (SOV) • High-Occupant Vehicle with 2 people (HOV2) • High-Occupant Vehicle with 3 or more people (HOV3+)

84 Smart Growth and Urban Goods Movement carpool parking costs are used in the work model. Non-work models use hourly parking costs. Ferry fares paid when crossing the Sound with a vehicle are also considered as auto operating costs. In 2006, there was only one toll bridge, the Tacoma Narrows Bridge, which charges $3.00 in one direction. All occupants of shared-ride modes share the auto operating costs and parking costs equally. A zone-to-zone transit-fare matrix representing the fares for each transit mode also is used as input to the model. A bi-directional averaging procedure is used for cost, and all travel costs are assumed to increase with inflation, except parking cost, which assumes a 1.5% increase above inflation based on historical trends. A separate analysis of the impacts of increas- ing gas prices on travel behavior is being conducted to demonstrate the sensitivity of vehicle miles traveled to changes in cost. Special Generators Four types of special generators are added to the trip tables for passenger and truck models: • Sports complex (the SoDo Sports Complex and the Tacoma Dome) • Regional center (the Seattle Center) • Ports (Sea-Tac Airport, Port of Seattle, and Port of Tacoma) • Warehouse and distribution centers (located in the SR 167 corridor). Trips to and from the ports of Seattle and Tacoma and the warehouse and distribution centers are input to the truck model, while trips to the other special generators are input to the passenger model. For the Port of Seattle, the trips between the Port and the intermodal yards are specified separately from remaining regional or external trips to and from the Port. External Travel Three types of external travel are added to the trip tables for passenger and truck models: • Trips from outside the region destined to somewhere in the region • Trips from inside the region destined to somewhere outside the region • Trips from outside the region destined to somewhere outside the region, but that pass through the region on the way There are 18 external stations in the Puget Sound region. Passenger and truck external trips are developed separately from observed data sources, and forecasts are based on relevant growth patterns. Time-of-Day Models - a.m. peak (5:00 a.m. to 9:59 a.m.) in 30- minute increments - Midday (10:00 a.m. to 2:59 p.m.) in 30- minute increments - p.m. peak (3:00 p.m. to 7:59 p.m.) in 30- minute increments - Evening (8:00 p.m. to 10:59 p.m.) - Night (11:00 p.m. to 4:59 a.m.) Other Models - a.m. peak (6:00 a.m. to 8:59 a.m.) - Midday (9:00 a.m. to 2:59 p.m.) - p.m. peak (3:00 p.m. to 5:59 p.m.) - Evening (6:00 p.m. to 9:59 p.m.) - Night (10:00 p.m. to 5:59 a.m.) Table 24. Time periods.

Modeling Tools at PSRC 85 Commercial Vehicles Commercial vehicles are defined as any vehicle used for commercial purposes and can include autos, vans, sport utility vehicles, small trucks, and medium and heavy trucks. These are inclu- sive of all commercial vehicles, such as taxis, rental cars, school buses, ambulances, etc., but these special-purpose vehicles are not directly represented in the current model; instead, they are indirectly represented. These commercial vehicles are forecast using a truck model that includes all commercial vehicles based on relative weight classes and that separates light, medium, and heavy trucks for analysis purposes (see Table 25). This truck model was developed using a conversion of truck volumes to passenger-car equiva- lents (PCE) for assignment purposes. This factor provides a means to account for the fact that larger trucks take up more capacity on the roads than passenger cars. This model is important to determine the effects on capacity and congestion for assignment of both trucks and passenger cars. The following assumptions were used: • Light trucks are 1.0 PCE • Medium trucks are 1.5 PCEs • Heavy trucks are 2.0 PCEs Vehicle Classes Seven classes of vehicles are assigned in the multi-class assignment: • Single-occupant vehicle (SOV) • 2-person carpools (HOV2) • 3+ person carpools (HOV3) • Vanpools • Light trucks • Medium trucks • Heavy trucks In order to combine vehicle costs and times, the value of time for each vehicle class was stratified, and SOVs were further stratified by purpose and income class to capture differences in values of time for each market segment (see Figure 14). HOV and vanpool vehicles are further subdivided by time period because vehicle occupancies vary by trip purpose and time period, and this affects the overall value of time for each vehicle. Gross Vehicle Weight Light Truck Four or more tires Two axles Less than 16,000 lb Medium Truck Single unit Six or more tires Two to four axles 16,000 to 52,000 lb Heavy Truck Double or triple unit Combinations Five or more axles More than 52,000 lb Note: Light trucks also include non-personal use of cars and vans. ConfigurationTruck Type Table 25. Commercial vehicles classes.

86 Smart Growth and Urban Goods Movement $- $20.00 $40.00 $60.00 $80.00 $100.00 $120.00 SO Vl ow inc SO Vm idi nc SO Vm idh igh inc SO Vh igh inc SO V am m idd ay pm ev en in g ni gh t am m idd ay pm ev en in g ni gh t am m idd ay pm ev en in g ni gh t Li gh t M ed ium He av y Work Non- work HOV2 HOV3+ Vanpool Truck Market Segment (Purpose, Mode and Time Period) Va lu e o f T im e ( $ p er h ou r) Figure 14. Value of time by market segment.

Abbreviations and acronyms used without definitions in TRB publications: A4A Airlines for America AAAE American Association of Airport Executives AASHO American Association of State Highway Officials AASHTO American Association of State Highway and Transportation Officials ACI–NA Airports Council International–North America ACRP Airport Cooperative Research Program ADA Americans with Disabilities Act APTA American Public Transportation Association ASCE American Society of Civil Engineers ASME American Society of Mechanical Engineers ASTM American Society for Testing and Materials ATA American Trucking Associations CTAA Community Transportation Association of America CTBSSP Commercial Truck and Bus Safety Synthesis Program DHS Department of Homeland Security DOE Department of Energy EPA Environmental Protection Agency FAA Federal Aviation Administration FHWA Federal Highway Administration FMCSA Federal Motor Carrier Safety Administration FRA Federal Railroad Administration FTA Federal Transit Administration HMCRP Hazardous Materials Cooperative Research Program IEEE Institute of Electrical and Electronics Engineers ISTEA Intermodal Surface Transportation Efficiency Act of 1991 ITE Institute of Transportation Engineers MAP-21 Moving Ahead for Progress in the 21st Century Act (2012) NASA National Aeronautics and Space Administration NASAO National Association of State Aviation Officials NCFRP National Cooperative Freight Research Program NCHRP National Cooperative Highway Research Program NHTSA National Highway Traffic Safety Administration NTSB National Transportation Safety Board PHMSA Pipeline and Hazardous Materials Safety Administration RITA Research and Innovative Technology Administration SAE Society of Automotive Engineers SAFETEA-LU Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (2005) TCRP Transit Cooperative Research Program TEA-21 Transportation Equity Act for the 21st Century (1998) TRB Transportation Research Board TSA Transportation Security Administration U.S.DOT United States Department of Transportation