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Metropolitan Travel Forecasting: Current Practice and Future Direction AMPO Travel Modeling Work Group December 10, 2007 Washington, DC

Metropolitan Travel Forecasting: Current Practice and Future Direction AMPO Travel Modeling Work Group December 10, 2007 Washington, DC

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Metropolitan Travel Forecasting: Current Practice and Future Direction

AMPO Travel Modeling Work Group

December 10, 2007

Washington, DC

1863Founding of the National Academy of

Sciences

About the National Academies

Historic mission: form committees of experts to address critical national issues and give advice to the federal government and the public.

Provide independent, objective, and non-partisan advice with high standards of scientific and technical quality. Checks and balances are applied at every step in the study process to protect the integrity of the reports and to maintain public confidence in them.

Transportation Research Board

One of five major divisions within the National Academies

Much of what TRB does is different from the core mission of the National Academies

“Metropolitan Travel Forecasting” is a traditional National Academies policy study

Sponsors of the Study

Office of the Secretary, USDOT Federal Highway Administration Federal Transit Administration

Scope of the Study

Determine state of practice in metropolitan travel forecasting

Identify technical shortcomings of the models for their intended uses

Recommend actions needed to ensure appropriate technical processes are being used

CommitteeMartin Wachs, chairman, RAND Corporation, MPOs

Michael R. Morris, North Central Texas COG Charles L. Purvis, Oakland MTCGuy Rousseau, Atlanta Regional Commission Richard E. Walker, Metro Portland, OR

AcademiaGeorge B. Dresser, TTI, TXRonald W. Eash, Northwestern University, ILRobert A. Johnston, University of California, DavisEric J. Miller, University of Toronto, Canada

State DOTsLaura L. Cove, North Carolina DOTMary Lynn Tischer, Virginia DOT

ConsultantsThomas B. DeenRichard H. Pratt

Technical Advisory Group

Williams Davidson, PB Consult Thomas Rossi, Cambridge Systematics Williams Woodford, AECOM

Sources of Information

Web-based survey of MPOs In-depth interviews of MPOs Literature review Briefings from stakeholders The expertise of the committee

Review of the Committee’s Report

Elizabeth Deakin, U of California Mark Hallenbeck, U of Washington Lester Hoel, U of Virginia Charles Howard, Seattle MPO Keith Killough, SCAG Ron Kirby, Washington DC MPO Frank Koppelman, Northwestern U Keith Lawton, Consultant

Oversight of the Review Process

Adib Kanafani, U California

Mike Walton, U Texas

The Result

Findings

4-step model is basic approach (estimate trips, distribute among origins and destinations, determine mode, assign to network)

• Basic framework unchanged for over 50 years

• Many variations in complexity of approach

• Complex issues lead to complex models (e.g. travel models linked with land use models)

• San Francisco City, Columbus Ohio MPO, and New York MTC have adopted more advanced approaches

Findings (con’t)

There is no single approach to travel forecasting that is “correct” for all MPOs

The planning context and the nature of questions being asked should determine the type and complexity of model tools employed

Findings- Current Models

Inadequate for demand analysis of many applications

• Induced travel

• Land use policies

• HOT and time variable road pricing

• Environmental justice

• Telecommuting

• Mode of access to transit

• Traveler response to congested networks

Findings- Current Models (con’t)

Certain modes are poorly characterized, e.g.

Non-motorized travel Freight and commercial vehicle travel

Findings- Current Models (con’t)

Inadequate for supply-side analysis-

No disaggregate estimates of volumes and speeds on specific routes by time of day. This affects-• Evaluation of traffic ops improvements

• Time shifting in congested networks

• Evaluation of freight movement policies

• Emissions estimates

• Evacuation planning

Findings- Current Models (con’t)

Advanced travel models are being developed

• Detailed representation of person and household activities and travel

• Continuous representation of time and network performance

• Implemented in a few places – appear to work well

Findings- Current Practice

Inadequate data Optimism bias Quality control Validation errors

(FTA commended for efforts to ensure QC)

Findings- Obstacles to Model Improvement

• Preoccupation with meeting immediate demands of production

• Fear of legal challenges

• Significant budget and staff limitations

• Insufficient evidence that advanced models can be implemented for a reasonable cost and provide significant improvements

• Poor/inadequate data

Findings- Federal Government

Federal support for models development not commensurate with federal demands on modeling

• Reduction in federal support: in 60’s and 70’s federal investment = $15 million annually in current dollars compared with about $2.5 million today

• Growth in federal planning and environmental requirements for states and MPOs has increased significantly

Overarching Recommendations

Develop and implement new modeling approaches better suited to providing reliable forecasts for such applications as operational analyses, environmental assessments, evaluation of policy alternatives, freight forecasts

Take steps to ensure better practice• Federal, state, regional collaboration needed

to deliver better models and practice

Recommendations for MPOs

MPOs would benefit from establishing a national cooperative R&D program

• $4-5 million annually, governed by MPOs themselves, for models selection, deployment, evaluation

• NYSMPO “shared cost initiative”

Recommendations for MPOs (con’t)

Continue peer reviews University partnerships Reasonableness checks of project

forecasts Document experience with advanced

practice

Recommendations for States

Support development of MPO cooperative research program

Evaluate, in cooperation with MPOs, socio-economic forecasts used for modeling

Continue MUGs

Recommendations for Federal Gov’t

Support and provide funding for incremental improvements to 4-step models that are appropriate for use.

Support and provide funding for development, implementation, evaluation of advanced models.

Continue TMIP Increase funding – 0.005% of federal aid is about $20

million, which is roughly comparable to the $15 million of support in the ‘60s and ‘70s.

MPO Certification- models check-list; incorporate MPO peer reviews

Provide flexibility for MPOs to apply models appropriate to their needs.

Federal, State, Local

Establish goals, responsibilities, improved training elements, means of improving travel models—perhaps through a steering committee of principle stakeholders.

Develop and keep current a national handbook of practice (not a standards manual)—perhaps through national organization that could bring partners together & perhaps funded by MPO CRP, NCHRP, federal government.

Document data requirements for updating travel models, validating models, freight modeling, meeting air quality conformity requirements, etc.

A strategy for change

Practice resistant to change. For the past 40 years, advances in R&D &

innovation in modeling has led to only incremental change.

Need to break out of this cycle. Harness the coordinated resources of each

level of government. Return to creativity and innovation of the early

days of travel forecasting.

TRB Annual Meeting SessionMetropolitan Travel Forecasting: Current Practice and Future Direction-

Wednesday, January 16, 2008, 7:30 PM - 9:30 PM, Hilton Georgetown W.Charles L. Purvis, Metropolitan Transportation Commission, presiding

Findings and Recommendations of the Report Martin Wachs, RAND Corporation

Perspectives of Stakeholders Gloria Shepherd, Federal Highway AdministrationRonald T. Fisher, Federal Transit AdministrationCharles E. Howard, Puget Sound Regional CouncilDeb Miller, Kansas Department of Transportation

Proposal for a Metropolitan Planning Cooperative Research Program Michael R. Morris, North Central Texas Council of Governments

Summary of Discussion and Next Steps Martin Wachs, RAND Corporation