october 21, 2013 jennifer murray traffic forecasting section chief wisconsin department of...
TRANSCRIPT
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Creating a Supply-Chain Methodology
for FreightForecasting in
WisconsinOctober 21, 2013
Jennifer MurrayTraffic Forecasting Section Chief
Wisconsin Department of Transportation
TRB – SHRP2 Symposium: Innovations in Freight Demand Modeling and Data Improvement
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Multimodal Freight Fusion Forecasting Model
Create a statewide freight forecasting framework that integrates travel demand modeling with freight analysis tools, provides performance metrics and analyzes alternative strategies to move freight.
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Objectives for Multimodal Freight Fusion Forecasting Model
Use forecasting model day-to-day Implement national best-practices Visualize the data in one place Align transportation investment with needs Build forward thinking and credibility
with stakeholders
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WISCONSINChicago
Twin CitiesLake Superior
Lake Michigan
Mississip
pi R
iver
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Wisconsin Freight Facilities
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Governor’s Freight Industry Summit
Freight Mobility Action Agenda
Transportation Finance & Policy Commission
Connections 2030: Wisconsin’s Long-range Transportation Plan
Stakeholder Meetings
Freight Industry Partners
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Top Commodity Profiles - Economic Drivers
Tonnage Value Economic
Importance Flows Forecasts
Commodity Tons Mode
Transportation issues associated with each commodity
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Draft Highway Freight Factors on Southeast State
Trunk Highways
Criteria
Thresholds
Weight/Hierarchy
Traffic segments assigned
draft highway “Freight Factor” scores
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Draft Highway Freight Factor Scores
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Continued Partnerships
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Multimodal Freight Fusion Forecasting Model
Freight supply-chain forecasting tool based on traditional statewide 4-step model
Economics of moving freight Business production locations, product types,
availability and general business development timeframes
System performance measures
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Data Improvements Needed Vehicle classification count data Data disaggregation investigation
Commodity information○ Shipping costs○ Commodity weights
Freight supply-chainIntermodal terminal supply-chain dataNew business data
Diesel fuel consumption data Non-highway modes
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Permanent Count Stations (ATRs)Continuous Weight-in-Motion
Continuous ClassContinuous Length
Portable Count StationsShort-term Length
Miscellaneous CountsManual
Centralized Processing
Data Analysis
Data Collection Standards
FHWA/WisDOT StandardsBinning
Data Collection
Traffic Forecast/Projection
Vehicle-Miles of Travel
ModelingMeta Manager
Travel Demand ModelMicrosimulation
Identified Project NeedBudget
Capacity Analysis
Accountability
Expertise in Review and Development of Products
Sufficient Truck Counts
Standard WisDOT Approach Statewide
Data-Driven Concept for FreightFusion Forecasting and Modeling
(as represented by Vehicle Classification Count Data)
Data Refinement / Improvement
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Freight Forecasting with Fusion Concept
Concept continuing to evolve – use the data, contribute to the data – “PLUG-IN”
Flexibility and tailored to needsAir quality modelingMechanistic Empirical Pavement Design
software inputsOversize, over-weight vehicles
Multimodal aspect provides insights Survey businesses for data
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Web-based Interactive Corridor
Mapping Application
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Fusion Model Role
Analysis Transportation project planning
and programming MAP-21 opportunities Last-mile connections Partnering Good stewardship
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Schematic Business Plan for
Fusion Concept Outline long-range goals, expectations Specific uses for the model Guidelines for development, technology,
transportation modes, tool and data updates Budget Performance measures Implementation - “the everyday”
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Thank You!