An Overview of
UrbanSim
Center for Urban Simulation
and Policy Analysis
University of Washington
www.urbansim.org
Results of Needs Assessment (in order)
1.
Analyze Effects of Land Use on Transportation
2.
Analyze Multimodal Assignments
3.
Promote Common Use of Data
4.
Manage Data Needs
5.
Analyze All Modes of Travel
6.
Analyze Effects of Land Use Policies
7.
Support Visualization Techniques
8.
Analyze Effects of Transportation Pricing Policies
9.
Analyze Effects of Growth Management Policies
10. Analyze Effects of Transportation on Land Use
Recommendations for New Model
Design (made in 2001)
• Model real estate, labor and transportation demand and supply
market interactions in an integrated microsimulation framework.
 Eliminate artificial separation of household choices
• Represent processes at appropriate temporal and spatial detail
 Real estate and labor markets: annual, parcel
 Activity and travel: mid-term model effort: 5 daily periods, parcel /
term: continuous time
long-
• Integrate and extend recent advances in operational models
 Disaggregate land use models (Eugene, Honolulu, Salt Lake City)
 Activity based travel models (San Francisco, Portland)
• Implement as a distributed model system
 for use by PSRC, cities and counties, state agencies, public
 with a web-based user-interface
• Implementation plan balancing needs, costs, schedule, and risks
Linked Urban Markets
Services
Governments
Infrastructure
Land
Housing
Developers
Households
Labor
Floorspace
Businesses
Flow of consumption from supplier to consumer
Regulation or Pricing
Long-term Modeling Strategy:
Integrated Model of Markets for Real Estate, Labor and
Transportation
Households
Demographic Processes
• Ageing
• Household structure
• Migration
Long-term Choices
• Residential Mobility
• Housing Choice
• Labor Supply
• Workplace Choice
• Vehicle Ownership
Short-term Choices
• Activity Generation
• Activity Scheduling
• Allocation of Vehicles
• Activity Location
Governments
Land Use Regulation
• Land use plans
• Growth management
Transportation
• Infrastructure
• Pricing
Developers
Real Estate Processes
• Land development
• Housing development
• Non-res development
• Redevelopment
Businesses
Economic Processes
• Economic structure
• Output goods/services
• Inter-regional trade
Long-term Choices
• Mobility
• Location Choice
• Labor Demand
Short-term Choices
• Goods movement
An Illustration of the Approach
• Consider a major decrease in transport costs
• In reality, a household could substitute
among any combination of interdependent
changes:






Change travel routes, modes, times to take advantage
Make more trips
Make longer trips to other destinations
Move residence to buy more space or amenities farther out
Change jobs or enter job market
Add a household vehicle
• The proposed model would recognize these
as interdependent choices, whereas current
models would not
Phased Model Improvements: 2002-5
• Implement Land Use Model based on
UrbanSim (current specification)
 Phase I: Develop database
 Phase II: Estimate model paramaters
 Phase III: Test and validate model system
• Integrate with current PSRC models:
 STEP macroeconomic model
 Travel model system
UrbanSim Design Objectives
• Support coordinated land use, transportation, and
environmental planning and modeling
• Use a transparent behavioral framework
• Represent interactions of markets and policies
• Represent sufficient detail to support:
 Municipal applications; corridor studies
 Non-motorized transport policies and TOD
 Environmental and land use policies
• Support trade-off analysis among objectives
 Efficiency
 Equity
 Environmental Impact
• Develop an Open Source modeling platform
UrbanSim Model Design
• Discrete Choice Framework




Household Relocation and Location Choice
Business Relocation and Location Choice
Real Estate Development
Explicit Markets for Real Estate
• Governmental policies exogenous: scenarios
• Dynamic




Path-dependent (history matters)
Supply fixed in short run (one year)
Adjustment toward equilibrium in long-run
Annual time steps
How is UrbanSim Different?
• Dynamic, non-equilibrium approach
• Spatial detail very high
• Behavioral approach empirically measures
responses to policies
• Focuses visioning on goals and objectives
• Links visioning to planning and evaluation
Household
Grid Cell
HOUSEHOLD_ID
GRID_ID
PLAN_TYPE_ID
GRID_ID
COMMERCIAL_SQFT
PERCENT_WATER
PERSONS
GOVERNMENTAL_SQFT
PERCENT_WETLAND
WORKERS
INDUSTRIAL_SQFT
PERCENT_STREAM_BUFFER
AGE_OF_HEAD
COMMERCIAL_IMPROVEMENT_VALUE
PERCENT_FLOODPLAIN
INCOME
INDUSTRIAL_IMPROVEMENT_VALUE
PERCENT_SLOPE
CHILDREN
GOVERNMENTAL_IMPROVEMENT_VALUE
PERCENT_OPEN_SPACE
RACE_ID
NONRESIDENTIAL_LAND_VALUE
PERCENT_PUBLIC_SPACE
CARS
RESIDENTIAL_LAND_VALUE
PERCENT_ROADS
RESIDENTIAL_IMPROVEMENT_VALUE
IS_OUTSIDE_URBAN_
RESIDENTIAL_UNITS
GROWTH_BOUNDARY
YEAR_BUILT
IS_INSIDE_NATIONAL_FOREST
Job
FRACTION_RESIDENTIAL_LAND
IS_INSIDE_TRIBAL_LAND
JOB_ID
PERCENT_UNDEVELOPABLE
IS_INSIDE_MILITARY_BASE
GRID_ID
TOTAL_NONRES_SQFT
ZONE_ID
SECTOR_ID
DEVELOPMENT_TYPE_ID
CITY_ID
HOME_BASED
DISTANCE_TO_ARTERIAL
COUNTY_ID
SIC
DISTANCE_TO_HIGHWAY
PERCENT_AGRICULTURAL_
RELATIVE_X
RELATIVE_Y
PROTECTED_LANDS
ACRES
Key Model Components
• Household and Employment Location
 Standard multinomial logit
 Grid cell is unit of choice
• Real Estate Development
 Multinomial logit
 24 development type outcomes
• Real Estate Price Estimation
 Hedonic regression
Data Inputs
•
•
•
•
•
•
•
Regional Control Totals
Parcel Data
Business Establishments
Household Data (Census, Travel Survey)
Land Use Plan/Zoning
Environmental Features
Public Land ownership
Residential Location Variables
• Housing Characteristics
 Prices (interacted with income)
 Development types (density, land use mix)
 Housing age
• Regional accessibility
 Job accessibility by auto-ownership group
 Travel time to CBD and airport
• Urban design-scale (local accessibility)
 Neighborhood land use mix and density
 Neighborhood employment
Employment Location Variables
• Real Estate Characteristics
 Prices
 Development type (land use mix, density)
• Regional accessibility
 Access to population
 Travel time to CBD, airport
• Urban design-scale
 Proximity to highway, arterials
 Local agglomeration economies within & between
sectors: center formation
Development Variables
• Site characteristics
 Existing development characteristics
 Land use plan
 Environmental constraints
• Urban design-scale




Proximity to highway and arterials
Proximity to existing development
Neighborhood land use mix and property values
Recent development in neighborhood
• Regional
 Access to population and employment
 Travel time to CBD, airport
Land Price Variables
• Site characteristics
 Development type
 Land use plan
 Environmental constraints
• Regional accessibility
 Access to population and employment
• Urban design-scale
 Land use mix and density
 Proximity to highways and arterials
UrbanSim – Travel Model Interactions
Households by
Income
Age of head
Size
Workers
Children
Employment by sector
Travel Models
UrbanSim
Composite Utility by Auto Ownership
Highway Travel Times
Vehicle Ownership Probabilities
Creating Policy Scenarios
• Macroeconomic Assumptions
 Household and employment control totals
• Development constraints
 Can select any combination of
• Political and planning overlays
• Environmental overlays
• Land use plan designation
 Constraints determine which development types
cannot be built
• Transportation infrastructure
• User-specified events
Puget Sound
Regional Council
4 Counties
72 Cities
3 Ports
WS Dept of Transp
WS Transp Comm
also:
6 transit agencies
6 Associate Members
2 adjacent counties
2 tribes
1 port
Evans School of
Public Affairs, UW
SNOHOMISH
Everett
Bremerton
Bellevue
Seattle
KITSAP
Tacoma
PIERCE
KING
Puget Sound
Regional Council
Population: 3,275,847
Area: 6,287.8 sq mi
SNOHOMISH
Everett
Bremerton
Bellevue
Seattle
KITSAP
Tacoma
PIERCE
KING
Puget Sound
Regional Council
Population: 3,275,847
Area: 6,287.8 sq mi
Urban Growth Area
Population: 2,804,125
Area: 980.1 sq mi
SNOHOMISH
Everett
Bremerton
Bellevue
Seattle
KITSAP
Tacoma
PIERCE
KING
Major Steps in Data Preparation
1. Determine study area boundary
2. Generate grid over study area
3. Assemble and standardize parcel data
4. Impute missing data on parcels
5. Assemble employment data
6. Assign employment to parcels
7. Convert Parcel data to grid
8. Convert other GIS layers to grid
9. Assign Development Types
10. Synthesize household database
11. Diagnose data quality and make refinements
12. Document data and process