SHRPII Project C04: Improving Our Understanding of How Congestion - - PowerPoint PPT Presentation

SHRPII C04: TEG Meeting, Washington, DC - January 14, 2010 1

SHRPII Project C04:

Improving Our Understanding of How Congestion & Pricing Affect Travel Demand

PB / Parsons Brinckerhoff Northwestern University Mark Bradley Research & Consulting Resource System Group University of California at Irvine University of Texas at Austin

SHRPII C04: TEG Meeting, Washington, DC - January 14, 2010 2

Project Overview and Objectives

Bob Donnelly, Project Manager

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Research Vision: 3 Domains

Data Demand / Choice Supply / Networks Pricing & Congestion

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Core Research Team: Principal Investigators

Mark Bradley Peter Vovsha PB Bob Donnelly (PM) Hani Mahmassani NU

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Research Team: Other Key Members

 Tom Adler, RSG  Rosella Picado / Surabhi Gupta (PB)  Ken Small / David Brownstone (UC-Irvine)  Kara Kockelman, UT-Austin  Frank Koppelman  John Bowman  Jean Wolf, GeoStats

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Primary Objectives and Focus

• f CO4 Research

 Assess, select and thoroughly analyze travel behavior data in order to

formulate and recommend ways to better and more fully model important impacts of congestion and pricing on travelers and transportation systems, leading to “break-through” solutions, in general and with respect to some key issues:

 Highway utility formulation – assessment of delays /time in congestion  Heteroscedasticity of travelers’ VOT,  Reliability of travel

 Site specific testing - estimation of new relationships / impacts of

pricing & congestion & travel demand, with validation of findings and testing for cross sites / transferability

 Consideration of implications and requirement for application, with

some implementation testing / demonstration

 Synthesis of findings and general recommendations for model

developers, with an emphasis on model structure and statistical estimation of parameters

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Primary Data to support modeling advancements:

 Travel behavior data:

 Stated Preference surveys (SP) – choice experiments,

endogenous supply measures

 Revealed Preference surveys (RP), supplemented with

supply-side measures

 Panel surveys / Repeated measurements

 Time and costs / networks: observed and simulated:

 “Snapshot” – concurrent with demand measures 

Time-series / longitudinal – (e.g. variability/reliability)



Forecasting simulation capability

 Modeling systems

 Source of road use cost and LOS measures affecting  Capacity to absorb advanced methods (i.e., ABM+dynamic

simulation framework)

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C04 Research Settings

 Principal Sites: Integrated regional data and

implementation testing:



San Francisco (SFCTA, MTC)



Seattle (PSRC)



New York (NYMTC, MTA, NYCDOT, PANYNJ)

 Supporting Sites: Project site specific analysis /

Transferability testing:



Minneapolis: I-394 MnPASS HOT (MnDOT)



Chicago (CMAP)



San Diego: I-15 ML (SANDAG)



Orange County: SR-91 (OCTA)



Baltimore Region: DYNASMART-P



NY BPM Region: Mode and Route choice demand model implementation with DYNASMART-P

Heading to finish …

 Past: Project development and enhancement of

data were more consuming time and resources than expected

 Present: With time extension, the focus is now

intensely on completing and integrating the model estimation, addressing and documenting necessary technical details

 Next: Recognize the need for generalized findings to

emerge that will inform modelers (and their patrons) regarding productive paths for model improvements related to highway congestion and pricing

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