Modeling in the “Real Modeling in the “Real

World”World” John BrittingJohn Britting

Wasatch Front Regional Wasatch Front Regional CouncilCouncil

April 19, 2005April 19, 2005

IntroductionIntroduction• Forecasting manager for Salt Lake City Forecasting manager for Salt Lake City

metropolitan planning organizationmetropolitan planning organization• MPOs maintain region’s short and long-term MPOs maintain region’s short and long-term

transportation planstransportation plans• The “3 C’s”The “3 C’s”

• Responsible for developing and using models Responsible for developing and using models to forecast future travel patternsto forecast future travel patterns• Mathematical models representing current travel Mathematical models representing current travel

behavior are used to forecast future travel behavior are used to forecast future travel behaviorbehavior

• Analyze future alternatives, quantify benefits and Analyze future alternatives, quantify benefits and costscosts

Quick Facts

• 2 MPOs

• 4 Counties

• 1300 Square Miles

•1.8 million people today

•2.7 million people by 2030

Typical AnalysesTypical Analyses

1) Air Quality Conformity -NAAQS

2) System Performance (aggregate)

-VMT, VHT, Mode Share, etc.

3) Corridor-level Analyses

-Identify and compare options

4) Facility Performance

-V/C, Ridership, speed

The other 3 C’sThe other 3 C’s

• ComplexityComplexity• Challenges (legal)Challenges (legal)• CreativityCreativity

Advancing the modeling practice is Advancing the modeling practice is not easy.not easy.

What is a Travel Model?What is a Travel Model?

A systematic tool to forecast future A systematic tool to forecast future travel. travel.

One of many tools used in decision-One of many tools used in decision-making process.making process.

The 5 steps of modeling process The 5 steps of modeling process (typically) are:(typically) are: 1. Land Use Forecasting 1. Land Use Forecasting 2. Trip Generation2. Trip Generation 3. Trip Distribution3. Trip Distribution 4. Mode Split4. Mode Split 5. Trip Assignment5. Trip Assignment

Model InputsModel Inputs

Network of zones Network of zones

and linksand links• 1300 zones 1300 zones

contain contain demographic demographic data data (people/jobs)(people/jobs)

• 20,000 links 20,000 links describe describe road/transit road/transit infrastructure infrastructure (lanes, speed, (lanes, speed, capacity, capacity, headway etc.)headway etc.)

NetworksNetworks

Trip GenerationTrip Generation

Trip GenerationTrip Generation Trip DistributionTrip Distribution Mode ChoiceMode Choice Trip AssignmentTrip Assignment

Each zone produces and attracts Each zone produces and attracts trips, based on the amount and trips, based on the amount and types of activities within the TAZ.types of activities within the TAZ.

Modeling Steps

TAZ Population Jobs

393

679

176

LANDUSE DATA

1000

500

0

0

300

800

Trip DistributionTrip Distribution

Trip Distribution Trip Distribution estimates the estimates the number of trips number of trips between zonesbetween zones

Trip GenerationTrip Generation Trip DistributionTrip Distribution Mode ChoiceMode Choice Trip AssignmentTrip Assignment

Modeling Steps

Mode ChoiceMode ChoiceMode Choice considers travel time, auto availability, and costs in estimating the likelihood of making trips by car, train, bus, etc.

Trip GenerationTrip Generation Trip DistributionTrip Distribution Mode ChoiceMode Choice Trip AssignmentTrip Assignment

Modeling Steps

Trip AssignmentTrip Assignment

Trip assignment estimates which road or route should be taken. Considers travel time, congestion, speed, distance, transit transfers, etc.

Trip GenerationTrip Generation Trip DistributionTrip Distribution Mode ChoiceMode Choice Trip AssignmentTrip Assignment

Modeling Steps

Trip-based ModelsTrip-based Models

Limitations of Traditional Limitations of Traditional ModelsModels• Aggregate and Trip-basedAggregate and Trip-based

• Poor accountingPoor accounting• Assume similarity within zonesAssume similarity within zones• Over-simplifies family dynamics and location Over-simplifies family dynamics and location

choicechoice• No feedback to land-use forecasting No feedback to land-use forecasting

processprocess• Land-use does not change with transportationLand-use does not change with transportation

• Simplistic response to land-useSimplistic response to land-use• No sensitivity to urban form (diversity, No sensitivity to urban form (diversity,

density, design)density, design)

Tour-based ModelsTour-based Models

Difficult Emerging Difficult Emerging QuestionsQuestions

• Land-use affects Land-use affects transportation transportation decisionsdecisions

• Transportation Transportation affects land-use affects land-use growthgrowth

• New technologies New technologies (e.g. ITS, rail)(e.g. ITS, rail)

• New policies (e.g. New policies (e.g. tolls, taxes)tolls, taxes)

Introduction to Introduction to UrbanSimUrbanSim

Forecasts future land-use (households, jobs)Forecasts future land-use (households, jobs) Effective means to incorporate city and Effective means to incorporate city and

county land-use plans into regional county land-use plans into regional transportation planstransportation plans

State-of-the-artState-of-the-art Defensible microeconomic theoryDefensible microeconomic theory

Incorporates transportation Incorporates transportation accessibilityaccessibility

Locally calibratedLocally calibrated Tremendous interest across the U.S.Tremendous interest across the U.S.

WFRC InterestWFRC Interest

Committed to exploring and discussing Committed to exploring and discussing linkages between land-use and linkages between land-use and transportation in LRTPtransportation in LRTP Wasatch Choices visioning effortWasatch Choices visioning effort

Extensive staff time fine-tuning UrbanSim Extensive staff time fine-tuning UrbanSim database and modeldatabase and model Major technical questions have been answeredMajor technical questions have been answered Testing about to begin anew in visioning effortTesting about to begin anew in visioning effort

UrbanSim – Travel Model UrbanSim – Travel Model InteractionsInteractions

UrbanSimTravel Models

Households by Income Age of head Size Workers ChildrenEmployment by sector

AccessibilityHighway Travel TimesVehicle Ownership Probabilities

Linked Urban MarketsLinked Urban Markets

Governments Infrastructure

Land

FloorspaceHousing

Households BusinessesLabor

Services

Developers

Flow of consumption from supplier to consumer

Regulation or Pricing

Overview of Modeling Overview of Modeling systemsystem

>30 models within local UrbanSim >30 models within local UrbanSim applicationapplication Land Value (by type of use)Land Value (by type of use) Real Estate Development (by type of Real Estate Development (by type of

use; intensity)use; intensity) Residential location (by type of Residential location (by type of

household)household) Employment location (by type of Employment location (by type of

industry)industry)

Key Variables in ModelsKey Variables in Models Land value Land value Vacant land (for developer models)Vacant land (for developer models) Accessibility measures (for example)Accessibility measures (for example)

Proximity to transportation facilitiesProximity to transportation facilities Jobs/households within 30 minutesJobs/households within 30 minutes

Neighborhood traits (for example)Neighborhood traits (for example) Housing and employment within walking distanceHousing and employment within walking distance Neighborhood mix (e.g. by income, by type of real Neighborhood mix (e.g. by income, by type of real

estate)estate) Decision-maker’s characteristics (e.g. Decision-maker’s characteristics (e.g.

income, HH size, sector)income, HH size, sector)

Model ConstraintsModel Constraints Environmental featuresEnvironmental features

Steep slopeSteep slope Wetlands/lakes/streamsWetlands/lakes/streams SuperfundSuperfund

Regional PoliciesRegional Policies Urban growth boundaryUrban growth boundary Open SpaceOpen Space

Local Land PoliciesLocal Land Policies Type of useType of use Allowable density of useAllowable density of use

Observed Predicted

Lan

d P

rice V

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Lan

d P

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Resi

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Locati

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R

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V

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Observed Total Observed % Modeled Utility

VisioningVisioning

Plans to test UrbanSim extensively Plans to test UrbanSim extensively over next 4-6 monthsover next 4-6 months

Plenty of opportunity for local Plenty of opportunity for local review and feedbackreview and feedback

Relatively safe opportunity to vary Relatively safe opportunity to vary land and transportation policies and land and transportation policies and see what the model sayssee what the model says

Political ChallengesPolitical Challenges

Political issues can be more Political issues can be more challenging than the technicalchallenging than the technical

Inherent resistance to changeInherent resistance to change Committing to a tool like UrbanSim Committing to a tool like UrbanSim

affects entire planning realm affects entire planning realm (local/regional/state)(local/regional/state)

Implications for project development Implications for project development must be well understoodmust be well understood