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Modeling in Support of Long Range Transportation Planning
Scott Festin, AICP
Data Manager
Wasatch Front Regional Council
March 29, 2007
Introduction
• 11 years at WFRC– Data Manager
• Socioeconomic Data
• GIS
• BS, Geography, University of Utah
• MA, Geography, UNC-Charlotte
• Eisenhower Research Fellow, Federal Highway Administration, Washington, DC
Wasatch Front Regional Council
• Metropolitan Planning Organization (MPO) for the Salt Lake City and Ogden-Layton Urbanized Areas
• 46 Cities, 3 Counties in Urbanized Area• Additional work in Tooele and Morgan Counties• “3C” process
– Comprehensive– Coordinated– Continuing
• Coordinate with Mountainland Association of Governments (Provo/Orem Urbanized Area)
Wasatch Front Regional Council
• 18 Member board of elected officials– Salt Lake County-8 members– Davis County-4 members– Weber County-4 members– Morgan County-1 member– Tooele County-1 member– 3 Non-Voting members from:
• Utah Association of Counties• Utah League of Cities & Towns• Envision Utah
• Professional Staff of 22
WFRC Staff
• Chuck Chappell, Executive Director– 9 Planners
– 7 Engineers
– Support staff
Short Range Planning TIP
Long Range Planning RTP
Modeling Travel Model/UrbanSim
Technical Support Socioeconomics, GIS, Air Quality
Administration Accounting, Secretarial, Public Involvement, CDBG, Etc.
Wasatch Front Regional Council
• Metropolitan Planning Organization (MPO) for the Salt Lake City and Ogden-Layton Urbanized Areas
• Federally mandated and created by the Governor.• Urbanized areas with more than 50,000 population
required to have an MPO. (23 USC 134 (b)(1))• WFRC formed in 1969, made an MPO in 1972.• Two primary products
– Regional Transportation Plan (RTP)– Transportation Improvement Program (TIP)
Regional Transportation Plan
• Must contain the following elements:– An identification of transportation facilities that should function as
an integrated metropolitan transportation system.– A financial plan based on reasonably anticipated revenues that
demonstrates how the adopted long- range transportation plan can be implemented.
– Ensure the preservation of the existing metropolitan transportation system, and make the most efficient use of existing transportation facilities
– Indicate proposed transportation enhancement activities
• Must be updated at least every four years• Minimum 20 year planning horizon
Transportation Improvement Program
• Must contain the following elements:– a priority list of proposed federally supported projects and
strategies to be carried out within the 4-year period after the initial adoption of the transportation improvement program; and
– a financial plan that:• (i) demonstrates how the transportation improvement program
can be implemented; • (ii) indicates resources from public and private sources that are
reasonably expected to be available to carry out the program; • (iii) identifies innovative financing techniques to finance projects,
programs, and strategies; and • (iv) may include, for illustrative purposes, additional projects that
would be included in the approved transportation improvement program if reasonable additional resources beyond those identified in the financial plan were available.
Funding Prioritization
• All Federal Transportation funding must be prioritized and authorized by the Board.
• This is done through the TIP and RTP.– Projects need to be on the RTP and TIP to be built.
• In the first phase of the RTP (2007-2015), there will be approximately $5.7 Billion in highway and transit capital expenditures.
Modeling to Support Transportation Planning
• Socioeconomics
• Travel Demand Modeling
• Air Quality Modeling
• UrbanSim Landuse Model
• Real World Data
• Socioeconomic data form the foundation of all MPO modeling
• WFRC maintains the only set of small area population and employment projections– Internal uses– Public sector uses
• Water and sewer planning• Schools
– Private sector uses• Economic development• Community activism
Socioeconomics
Socioeconomic Data
Travel Demand Model
Air Quality Model
What is a Travel Model?
A systematic tool to forecast future travel. One of many tools used in decision-making process.
• The 4 steps of modeling process (typically) are:– 0. Land Use Forecasting (Socioeconomics) – 1. Trip Generation– 2. Trip Distribution– 3. Mode Split– 4. Trip Assignment
Model Inputs
Network of zones and
links• 1300 zones contain
socioeconomic data (people/jobs)
• 20,000 links describe road/transit infrastructure (lanes, speed, capacity, headway etc.)
Networks
Trip Generation
• Trip Generation• Trip Distribution• Mode Choice• Trip Assignment
Each zone produces and attracts trips, based on the amount and types of activities within the TAZ.
Modeling Steps
TAZ Population Jobs
393
679
176
LANDUSE DATA
1000
500
0
0
300
800
Trip Distribution
Trip Distribution estimates the number of trips between zones
• Trip Generation• Trip Distribution• Mode Choice• Trip Assignment
Modeling Steps
Mode Choice
Mode Choice considers travel time, auto availability, and costs in estimating the likelihood of making trips by car, train, bus, etc.
• Trip Generation• Trip Distribution• Mode Choice• Trip Assignment
Modeling Steps
Trip Assignment
Trip assignment estimates which road or route should be taken. Considers travel time, congestion, speed, distance, transit transfers, etc.
• Trip Generation• Trip Distribution• Mode Choice• Trip Assignment
Modeling Steps
Difficult Emerging Questions
• Land-use affects transportation decisions
• Transportation affects land-use growth
• New technologies (e.g. ITS, rail)
• New policies (e.g. tolls, taxes)
Introduction to UrbanSim
• Forecasts future land-use (households, jobs)• Effective means to incorporate city and county land-use
plans into regional transportation plans• State-of-the-art
– Defensible microeconomic theory
– Incorporates transportation accessibility– Locally calibrated– Tremendous interest across the U.S.
• Still in developmental stages• First use for planning was past summer
WFRC Interest
• Effort began in 1997
• Committed to exploring and discussing linkages between land-use and transportation in RTP– Wasatch Choices visioning effort
• Extensive staff time fine-tuning UrbanSim database and model– Major technical questions have been answered– Updating input data
UrbanSim – Travel Model Interactions
UrbanSimTravel Models
Households by Income Age of head Size Workers ChildrenEmployment by sector
AccessibilityHighway Travel TimesVehicle Ownership Probabilities
Linked Urban Markets
Governments Infrastructure
Land
FloorspaceHousing
Households BusinessesLabor
Services
Developers
Flow of consumption from supplier to consumer
Regulation or Pricing
Overview of Modeling system
• >30 models within local UrbanSim application– Land Value (by type of use)– Real Estate Development (by type of use; intensity)– Residential location (by type of household)– Employment location (by type of industry)
Key Variables in Models
• Land value • Vacant land (for developer models)• Accessibility measures (for example)
– Proximity to transportation facilities– Jobs/households within 30 minutes
• Neighborhood traits (for example)– Housing and employment within walking distance– Neighborhood mix (e.g. by income, by type of real estate)
• Decision-maker’s characteristics (e.g. income, HH size, sector)
Model Constraints
• Environmental features– Steep slope– Wetlands/lakes/streams– Superfund
• Regional Policies– Urban growth boundary– Open Space
• Local Land Policies– Type of use– Allowable density of use
Political Challenges
• Political issues can be more challenging than the technical
• Inherent resistance to change
• Committing to a tool like UrbanSim affects entire planning realm (local/regional/state)
Real World Data
• Models are a representation of reality– There is some uncertainty in all models– Law of diminishing returns
• Models are only as good as the data inputs– “Garbage in, Garbage out"
Data Sources
• Very little data used in modeling was collected for use in modeling
• UrbanSim input data– Parcel data collected and maintained by County
Assessors for Property tax assessment.– Employment data collected by Workforce Services for
administering unemployment insurance.
• Data limitations
Best Available Data
• The data you want may not always available
• Data that you can make work, is usually available
• Make due with the data that’s available– “Use it up, wear it out, make it do or do without.“
-FDR
• Data are surprisingly flexible. They can be made to fit.
Data Synthesis
• Sometimes you have to be creative in getting the data you need.
• Example:– Commercial space in Davis County
• Not in parcel data• Estimates of floor space per employee• Have locations of employers and number of employees• Create space by calculating space requirements by number
of employees
• It's an estimate and it's not perfect.
Emerging Issues
• American Community Survey– Census Long-Form data on an annual basis– Trade-offs
• Disaggregated models vs. Data privacy– Models are working at a finer level– Many data sources have privacy restrictions
Questions
• Contact Information– Scott Festin, AICP
Wasatch Front Regional Council295 Jimmy Doolittle Rd.Salt Lake City, UT 84116
(801) 363-4230 [email protected]
http://www.wfrc.org