1. 2009 Minnesota MPO Conference August 11, 2009
Incorporating Uncertainty of Inputs in Travel Demand Modeling Activities
2009 Minnesota MPO Conference
August 11, 2009
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2. Presentation Objectives
Clarify what we mean by “uncertainty”
Identify key drivers of uncertainty
Highlight examples from others
Discuss possible options for strengthening Minnesota modeling practices, including opportunities, constraints and challenges
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3. Special Report 288 Metropolitan Travel Forecasting
Inherent Weaknesses of the Models…
“Poor representation of uncertainty is another deficiency. Most travel forecasting models produce a single answer, although the model is estimated, calibrated, and validated on the basis of data sets subject to sampling and other errors.” TRB 2007, page 85
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4. Terms and Distinctions
Modeling Bias
Measurement or sampling errors
Specification errors
Uncertainty
Variable and conflicting views and assumptions about the future
“With careful planning we can minimize bias, but uncertainty in the estimates will always be there and often times this uncertainty is not recognized or even quantified.” – Steve Ruegg, Parsons Brinckerhoff
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5. Factors Contributing to Uncertainty
Traffic and VMT estimates
Land use
Population
Household numbers and changes in composition
Economic activities, including employment/job numbers and locations
Funding and the timing of related system improvements
Mode usage
Transportation related policies
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6. Trends in VMT, Population, Labor Force, Households and Employment
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7. Municipal Boundary Adjustments
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8. Total VMT Growth on All Roads in Minnesota 1992-2008
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9. Total Population Growth 1992-2008
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10. Total Percent Employment Growth 1992-2008
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11. County Level VMT and Socio-Economic Trends
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12. County Level VMT and Socio-Economic Trends
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13. County Level VMT and Socio-Economic Trends
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14. Past Errors in State Demographic Center Projections of Population
Mpls/StP Area
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15. Updating the Metro Profile From an April, 2008 memo to the Transportation Technical Committee (Metro COG projections include building permits issued)
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16. Incorporating Uncertainty – What the Experts Say….
Utilize the most robust data available
Consider the sources of uncertainty and qualitatively assess the probability and/or likelihood of variability
Establish a range of alternative scenarios or sensitivity tests around data inputs that have significant variability
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17. The Land Use Scenario DevelopeR (LUSDR) – Oregon DOT
“LUSDR was developed as a stochastic microsimulation to facilitate the automatic generation of multiple scenarios subject to general specifications of subject to general specifications of potential urban reserve areas. The governments in the metropolitan area identified areas that they would like to include within urban reserve areas and the general mix of uses (residential, commercial industrial) that they would like to achieve. This inventory was treated as a future land supply and LUSDR was then run several dozen times to produce scenarios that vary in the arrangement of land uses but are all consistent with the regional inputs, land use designations and development location behavior. The scenarios show the variety of ways that growth might occur if lands were made available as proposed. The regional transportation model was run for each of these scenarios to compare the transportation effects.”
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18. FTA Examples – Ken Cervenka
To promote transparency FTA now requires:
Documentation of capital-cost and rider uncertainties
Use of ranges in forecast estimates
Documentation of critical assumptions and significant sources of uncertainty
Exploration of alternative outcomes, likelihoods and implications, even those outside of modeled behaviors or current experiences
Engaging decision makers in risk analysis and accuracy discussions
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19. Honolulu Rail Project Example
Source of Uncertainty
Lower Bound
Best Estimate
Upper Bound
Western End Employment
Increased Job Growth
Current Plan
2017 Distribution Pattern
2030 Highway Investments
2030 Highway Investment Plan
More Modest Investment Plan
No Improvements
Bus Restructuring Revisions
Revise Top Ten Routes
Revise Top Five Routes
Existing Bus Plan
Fixed Guideway Service Levels
5 Minute Peak
10 Minute Off-Peak
3 Minute Peak
6 Minute Off-Peak --
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20. Department of Transport United Kingdom – April 2009
Provide a systematic analysis method for dealing with uncertainty
Create an uncertainty log to track:
All the local and external uncertainties and factors likely to affect traffic, patronage, revenues, etc.
The current status of each of these factors and the anticipated probability of uncertainty
Invite wide consultation on to promote consensus on the assessment of uncertainty
Use the uncertainty log to define a “core” scenario and alternative scenarios for describing the future
Report findings and educate decision makers, the public and affected stakeholders to think of a range of options
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21. Group Discussion Given current trends and uncertainties….
How are others here today using risk assessments in their work?
What are some possible options for strengthening modeling in Minnesota?
What opportunities, challenges and constraints do we need to consider as we move forward?
What are some possible next steps?
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22. Uncertainty in Socioeconomic Forecasting -- Todd Graham, Metropolitan Council
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